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Mariani I, Maino C, Giandola TP, Franco PN, Drago SG, Corso R, Talei Franzesi C, Ippolito D. Texture Analysis and Prediction of Response to Neoadjuvant Treatment in Patients with Locally Advanced Rectal Cancer. GASTROINTESTINAL DISORDERS 2024; 6:858-870. [DOI: 10.3390/gidisord6040060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2025] Open
Abstract
Background: The purpose of this study is to determine the relationship between the texture analysis extracted from preoperative rectal magnetic resonance (MR) studies and the response to neoadjuvant treatment. Materials and Methods: In total, 88 patients with rectal adenocarcinoma who underwent staging MR between 2017 and 2022 were retrospectively enrolled. After the completion of neoadjuvant treatment, they underwent surgical resection. The tumour regression grade (TRG) was collected. Patients with TRG 1–2 were classified as responders, while patients with TRG 3 to 5 were classified as non-responders. A texture analysis was conducted using LIFEx software (v 7.6.0), where T2-weighted MR sequences on oriented axial planes were uploaded, and a region of interest (ROI) was manually drawn on a single slice. Features with a Spearman correlation index > 0.5 have been discarded, and a LASSO feature selection has been applied. Selected features were trained using bootstrapping. Results: According to the TRG classes, 49 patients (55.8%) were considered responders, while 39 (44.2) were non-responders. Two features were associated with the responder class: GLCM_Homogeneity and Discretized Histo Entropy log 2. Regarding GLCM_Homogeneity, the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were 0.779 (95% CIs = 0.771–0.816), 86% (80–90), and 67% (60–71). Regarding Discretized Histo Entropy log 2, we found 0.775 AUC (0.700–0.801), 80% sensitivity (74–83), and 63% specificity (58–69). Combining both radiomics features the radiomics signature diagnostic accuracy increased (AUC = 0.844). Finally, the AUC of 1000 bootstraps were 0.810. Conclusions: Texture analysis can be considered an advanced tool for determining a possible correlation between pre-surgical MR data and the response to neoadjuvant therapy.
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Affiliation(s)
- Ilaria Mariani
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy
| | - Cesare Maino
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy
| | - Teresa Paola Giandola
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy
| | - Paolo Niccolò Franco
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy
| | - Silvia Girolama Drago
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy
| | - Rocco Corso
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy
| | - Cammillo Talei Franzesi
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy
| | - Davide Ippolito
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, Italy
- School of Medicine, University of Milano Bicocca, Via Cadore 33, 20090 Monza, Italy
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Drago SG, Maino C, Giandola TP, Franco PN, Corso R, Talei Franzesi C, Pecorelli A, Ippolito D. Correlations between Apparent Diffusion Coefficient (ADC) and Prognosis in Patients with Locally Advanced Rectal Cancer. Life (Basel) 2024; 14:1282. [PMID: 39459582 PMCID: PMC11509644 DOI: 10.3390/life14101282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 09/28/2024] [Accepted: 10/04/2024] [Indexed: 10/28/2024] Open
Abstract
BACKGROUND the aim of this study is to assess the performance of diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values in predicting the response to neoadjuvant chemoradiation therapy (CRT) and outcome in patients with locally advanced rectal cancer (LARC). MATERIALS AND METHODS ninety-four patients with magnetic resonance imaging (MRI) pre- and post-neoadjuvant treatment were retrospectively enrolled. Three regions of interest (ROIs) were manually drawn on three different slices of the tumor for every DWI sequence. ROIs were positioned to include only high signal areas and avoid artifacts or necrotic areas. ROIs were automatically copied onto the corresponding ADC maps and the system derived three different ADC values, distinguishing between mean, maximum, and minimum values, and the standard deviation (SD). Only mean ADC values were considered. After surgical intervention, pTNM and the Mandard tumor regression grade (TRG) were obtained. Patients with a TRG of 1-2 were classified as responders, while patients with a TRG from 3 to 5 were classified as non-responders. RESULTS no correlation was found between pre-ADC values and TRG classes, while post-ADC and ΔADC values showed a significant correlation with TRG classes (r = -0.285, p = 0.002 and r = -0.290, p = 0.019, respectively). Post-ADC values were statistically different between responders and non-responders (p = 0.019). When considering the relation between overall survival (OS) and ADC values, pre-ADC showed a negative correlation with OS (r = -0.381, p = 0.001), while a positive correlation was found between ΔADC values and OS (r = 0.323, p = 0.013). According to ΔADC values, the mean OS time between responders and non-responders showed a significant difference (p = 0.030). A statistical difference was found between TRG classes and OS (p = 0.038) and by dividing patients in responders and non-responders (p = 0.019). CONCLUSIONS the pre-ADC and ΔADC values could be used as useful predictors for patient prognosis, thus helping the treatment planning. On the other hand, the post-ADC values, thanks to their relationship with the TRG classes, could be the ideal tool to predict the histopathological response and plan a conservative approach to the treatment of rectal cancer.
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Affiliation(s)
- Silvia Girolama Drago
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy; (S.G.D.); (C.M.); (T.P.G.); (P.N.F.); (R.C.); (C.T.F.); (D.I.)
| | - Cesare Maino
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy; (S.G.D.); (C.M.); (T.P.G.); (P.N.F.); (R.C.); (C.T.F.); (D.I.)
| | - Teresa Paola Giandola
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy; (S.G.D.); (C.M.); (T.P.G.); (P.N.F.); (R.C.); (C.T.F.); (D.I.)
| | - Paolo Niccolò Franco
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy; (S.G.D.); (C.M.); (T.P.G.); (P.N.F.); (R.C.); (C.T.F.); (D.I.)
| | - Rocco Corso
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy; (S.G.D.); (C.M.); (T.P.G.); (P.N.F.); (R.C.); (C.T.F.); (D.I.)
| | - Cammillo Talei Franzesi
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy; (S.G.D.); (C.M.); (T.P.G.); (P.N.F.); (R.C.); (C.T.F.); (D.I.)
| | - Anna Pecorelli
- Radiologia Addomino Pelvica Diagnostica e Interventistica IRCCS Azienda Ospedaliera Universitaria di Bologna Policlinico di Sant’Orsola, Via Pietro Albertoni 15, 40138 Bolonga, BO, Italy
| | - Davide Ippolito
- Department of Diagnostic Radiology, IRCCS Fondazione San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy; (S.G.D.); (C.M.); (T.P.G.); (P.N.F.); (R.C.); (C.T.F.); (D.I.)
- School of Medicine, University of Milano Bicocca, Via Cadore 33, 20090 Monza, MB, Italy
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Curcean S, Curcean A, Martin D, Fekete Z, Irimie A, Muntean AS, Caraiani C. The Role of Predictive and Prognostic MRI-Based Biomarkers in the Era of Total Neoadjuvant Treatment in Rectal Cancer. Cancers (Basel) 2024; 16:3111. [PMID: 39272969 PMCID: PMC11394290 DOI: 10.3390/cancers16173111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 09/02/2024] [Accepted: 09/06/2024] [Indexed: 09/15/2024] Open
Abstract
The role of magnetic resonance imaging (MRI) in rectal cancer management has significantly increased over the last decade, in line with more personalized treatment approaches. Total neoadjuvant treatment (TNT) plays a pivotal role in the shift from traditional surgical approach to non-surgical approaches such as 'watch-and-wait'. MRI plays a central role in this evolving landscape, providing essential morphological and functional data that support clinical decision-making. Key MRI-based biomarkers, including circumferential resection margin (CRM), extramural venous invasion (EMVI), tumour deposits, diffusion-weighted imaging (DWI), and MRI tumour regression grade (mrTRG), have proven valuable for staging, response assessment, and patient prognosis. Functional imaging techniques, such as dynamic contrast-enhanced MRI (DCE-MRI), alongside emerging biomarkers derived from radiomics and artificial intelligence (AI) have the potential to transform rectal cancer management offering data that enhance T and N staging, histopathological characterization, prediction of treatment response, recurrence detection, and identification of genomic features. This review outlines validated morphological and functional MRI-derived biomarkers with both prognostic and predictive significance, while also exploring the potential of radiomics and artificial intelligence in rectal cancer management. Furthermore, we discuss the role of rectal MRI in the 'watch-and-wait' approach, highlighting important practical aspects in selecting patients for non-surgical management.
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Affiliation(s)
- Sebastian Curcean
- Department of Radiation Oncology, Iuliu Hatieganu University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania
- Department of Radiation Oncology, 'Prof. Dr. Ion Chiricuta' Oncology Institute, 34-36 Republicii Street, 400015 Cluj-Napoca, Romania
| | - Andra Curcean
- Department of Imaging, Affidea Center, 15c Ciresilor Street, 400487 Cluj-Napoca, Romania
| | - Daniela Martin
- Department of Radiation Oncology, 'Prof. Dr. Ion Chiricuta' Oncology Institute, 34-36 Republicii Street, 400015 Cluj-Napoca, Romania
| | - Zsolt Fekete
- Department of Radiation Oncology, Iuliu Hatieganu University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania
- Department of Radiation Oncology, 'Prof. Dr. Ion Chiricuta' Oncology Institute, 34-36 Republicii Street, 400015 Cluj-Napoca, Romania
| | - Alexandru Irimie
- Department of Oncological Surgery and Gynecological Oncology, Iuliu Hatieganu University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania
- Department of Oncological Surgery, 'Prof. Dr. Ion Chiricuta' Oncology Institute, 34-36 Republicii Street, 400015 Cluj-Napoca, Romania
| | - Alina-Simona Muntean
- Department of Radiation Oncology, 'Prof. Dr. Ion Chiricuta' Oncology Institute, 34-36 Republicii Street, 400015 Cluj-Napoca, Romania
| | - Cosmin Caraiani
- Department of Medical Imaging and Nuclear Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
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Zhang Z, Guo S, Cheng C, Cao K, Jiang H, Jin G, Zuo C. Integrated 68 Ga-FAPI-04 PET/MR in Pancreatic Cancer : Prediction of Tumor Response and Tumor Resectability After Neoadjuvant Therapy. Clin Nucl Med 2024; 49:715-721. [PMID: 38914015 DOI: 10.1097/rlu.0000000000005300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
PURPOSE This study aimed to investigate the value of 68 Ga-fibroblast activation protein inhibitor (FAPI) PET/MR semiquantitative parameters in the prediction of tumor response and resectability after neoadjuvant therapy in patients with pancreatic cancer. PATIENTS AND METHODS This study was performed retrospectively in patients with borderline resectable or locally advanced pancreatic cancer who underwent 68 Ga-FAPI PET/MRI from June 2020 to June 2022. The SUV max , SUV mean , SUV peak , uptake tumor volume (UTV), and total lesion FAP expression (TLF) of the primary tumor were recorded. The target-to-background ratios (TBRs) of the primary tumor to normal tissue muscle (TBR muscle ) and blood (TBR blood ) were also calculated. In addition, the minimum apparent diffusion coefficient value of the tumor was measured. After 3-4 cycles of gemcitabine + nab-paclitaxel chemotherapy, patients were divided into responders and nonresponders groups according to RECIST criteria (v.1.1). They were also divided into resectable and unresectable groups according to the surgical outcome. The variables were compared separately between groups. RESULTS A total of 18 patients who met the criteria were included in this study. The UTV and TLF were significantly higher in nonresponders than in responders ( P < 0.05). The SUV max , SUV mean , and TBR muscle were significantly higher in unresectable patients than in resectable ones ( P < 0.05). Receiver operating characteristic curve analysis identified UTV (area under the curve [AUC] = 0.840, P = 0.015) and TLF (AUC = 0.877, P = 0.007) as significant predictors for the response to gemcitabine + nab-paclitaxel chemotherapy, with cutoff values of 25.05 and 167.38, respectively. In addition, SUV max (AUC = 0.838, P = 0.016), SUV mean (AUC = 0.812, P = 0.026), and TBR muscle (AUC = 0.787, P = 0.041) were significant predictors of the resectability post-NCT, with cutoff values of 14.0, 6.0, and 13.9, respectively. According to logistic regression analysis, TLF was found to be significantly associated with tumor response ( P = 0.032) and was an independent predictor of tumor response ( P = 0.032). In addition, apparent diffusion coefficient value was an independent predictor of tumor resectability ( P = 0.043). CONCLUSIONS This pilot study demonstrates the value of 68 Ga-FAPI PET/MR for the prediction of tumor response and resectability after neoadjuvant therapy. It may aid in individualized patient management by guiding the treatment regimens.
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Affiliation(s)
- Zeyu Zhang
- From the Departments of Nuclear Medicine
| | | | - Chao Cheng
- From the Departments of Nuclear Medicine
| | | | - Hui Jiang
- Pathology, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Gang Jin
- Hepatobiliary Pancreatic Surgery
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González Del Portillo E, Couñago F, López-Campos F. Neoadjuvant treatment of rectal cancer: Where we are and where we are going. World J Clin Oncol 2024; 15:790-795. [PMID: 39071468 PMCID: PMC11271721 DOI: 10.5306/wjco.v15.i7.790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 04/28/2024] [Accepted: 05/17/2024] [Indexed: 07/16/2024] Open
Abstract
Locally advanced rectal cancer requires a multidisciplinary approach based on total neoadjuvant treatment with radiotherapy (RT) and chemotherapy (ChT), followed by deferred surgery. Currently, alternatives to the standard total neoadjuvant therapy (TNT) are being explored, such as new ChT regimens or the introduction of immunotherapy. With standard TNT, up to a third of patients may achieve a complete pathological response (CPR), potentially avoiding surgery. However, as of now, we lack predictive markers of response that would allow us to define criteria for a conservative organ strategy. The presence of mutations, genes, or new imaging tests is helping to define these criteria. An example of this is the diffusion coefficient in the diffusion-weighted sequence of magnetic resonance imaging and the integration of this imaging technique into RT treatment. This allows for the monitoring of the evolution of this coefficient over successive RT sessions, helping to determine which patients will achieve CPR or those who may require intensification of neoadjuvant therapy.
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Affiliation(s)
| | - Felipe Couñago
- Department of Radiation Oncology, GenesisCare Madrid, Madrid 28010, Spain
| | - Fernando López-Campos
- Department of Radiation Oncology, Hospital Universitario Ramón Y Cajal, Madrid 28034, Spain
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Yacheva A, Dardanov D, Zlatareva D. The Multipurpose Usage of Diffusion-Weighted MRI in Rectal Cancer. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:2162. [PMID: 38138265 PMCID: PMC10744943 DOI: 10.3390/medicina59122162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 12/11/2023] [Accepted: 12/12/2023] [Indexed: 12/24/2023]
Abstract
Background and Objectives: Colorectal cancer is the third most common oncological disease worldwide. The standard treatment of locally advanced rectal tumors is neoadjuvant radiochemotherapy in combination with surgical resection. The choice of specific treatment algorithm is highly dependent on MRI findings. The aim of this study is to show the potential role of ADC measurements in rectal cancer and their usage in different clinical scenarios. Materials and Methods: A total of 135 patients had rectal MRI evaluation. Seventy-five (56%) had histologically proven rectal adenocarcinoma and sixty (44%) were evaluated as rectal disease-free. An ADC measurement in the most prominent region of interest was obtained for all patients. Eighteen patients (24% of the rectal cancer group) had a second MRI after neoadjuvant chemoradiotherapy with comparison of the ADC values at the same region of interest as previously measured. Results: Rectal cancer ADC values were found to be significantly lower than the ones in the control group (p < 0.001). A statistically significant correlation was found when ADC values in rectal tumors of different T stages were compared (p = 0.039)-those with higher T stage as in locally advanced disease showed lower ADC values. Patients with extramural vascular invasion showed significantly lower ADC values (p = 0.01). There was a significant increase in ADC values after treatment (p < 0.001), and a negative correlation was observed (r = -0.6572; p = 0.004)-tumors with low initial ADC values showed a higher increase in ADC. Conclusions: ADC measurements have a complementary role in the assessment of rectal cancer and have the potential to predict the response to chemoradiotherapy and improve the planning of proper treatment strategies.
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Affiliation(s)
- Aneta Yacheva
- Department of Diagnostic Imaging, University Hospital Alexandrovska, Medical University of Sofia, 1431 Sofia, Bulgaria
| | - Dragomir Dardanov
- Department of Surgery, University Hospital Lozenetz, 1407 Sofia, Bulgaria
| | - Dora Zlatareva
- Department of Diagnostic Imaging, University Hospital Alexandrovska, Medical University of Sofia, 1431 Sofia, Bulgaria
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Lu Z, Xia K, Jiang H, Weng X, Wu M. Improved effects of the b-value for 2000 sec/mm 2 DWI on an accurate qualitative and quantitative assessment of rectal cancer. Arab J Gastroenterol 2023; 24:230-237. [PMID: 37989671 DOI: 10.1016/j.ajg.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Revised: 04/21/2023] [Accepted: 09/03/2023] [Indexed: 11/23/2023]
Abstract
BACKGROUND AND STUDY OBJECTIVES A higher b-value Diffusion-weighted imaging (DWI) would improve the contrast between cancerous and noncancerous tissue. Apparent diffusion coefficient (ADC)-histogram analysis is a method that can provide statistical data and quantitative information on tumor heterogeneity. This study aimed to compare two high b-values (1000 and 2000 sec/mm2) DWI in tumor detection and diagnostic performance in identifying early-stage tumor rectal cancer. PATIENTS AND METHODS This blinded and blinded retrospective study involved 56 patients with rectal cancer and 45 patients. Two radiologists evaluated the qualitative detection parameters and quantitative parameters of the ADC evaluated histogram and compared them between two DWI sequences (b-value for 1000 sec/mm2 and 2000 sec/mm2). The characteristic curves were used to assess diagnostic administration for the ADC histogram in discriminating early-stage tumors. RESULTS The b-value for 2000 sec/mm2 DWI significantly improved AUCs, sensitivity, specificity, and precision and decreased false-positive rate for detection compared to the b-value for 1000 sec/mm2 (p < 0.05). The mean and fifth percentile ADC value for stage I using the b-value for 1000 sec/mm2 DWI was significantly higher than stage ≥ II (p = 0.036II and 0.016 respectively), as the well as fifth, 10th, mean ADC of the fifth, 10th, and 25th ADC percentile at b-value for 2000 sec/mm2 (p = 0.031, 0.014, 0.035 and 0.025 respectively). The AUCs of the fifth percentile ADC at b-value for 2000 sec/mm2 DWI in both readers in differentiating the stage Ⅰ tumor were the highest (0.732 and 0.751). CONCLUSION The b-value for 2000 sec/mm2 DWI could improve the accurate detection of rectal cancer. The fifth percentile ADC at b-value for 2000 sec/mm2 sec/mm2 DWI was more useful for discriminating early stage than the b-value for 1000 sec/mm2 DWI.
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Affiliation(s)
- Zhihua Lu
- Department of Radiology, Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, China.
| | - Kaijian Xia
- Department of Information, Changshu No.1 People's Hospital, Affiliated Changshu Hospital of Soochow University, Suzhou, China
| | - Heng Jiang
- Department of Radiology, Changshu No.1 People's Hospital, Affiliated Changshu Hospital of Soochow University, Suzhou, China
| | - Xiaoyan Weng
- Department of Radiology, Changshu No.1 People's Hospital, Affiliated Changshu Hospital of Soochow University, Suzhou, China
| | - Mei Wu
- Department of Pathology, Changshu No.1 People's Hospital, Affiliated Changshu Hospital of Soochow University, Suzhou, China
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Chuong MD, Palm RF, Tjong MC, Hyer DE, Kishan AU. Advances in MRI-Guided Radiation Therapy. Surg Oncol Clin N Am 2023; 32:599-615. [PMID: 37182995 DOI: 10.1016/j.soc.2023.02.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
Abstract
Image guidance for radiation therapy (RT) has evolved over the last few decades and now is routinely performed using cone-beam computerized tomography (CBCT). Conventional linear accelerators (LINACs) that use CBCT have limited soft tissue contrast, are not able to image the patient's internal anatomy during treatment delivery, and most are not capable of online adaptive replanning. RT delivery systems that use MRI have become available within the last several years and address many of the imaging limitations of conventional LINACs. Herein, the authors review the technical characteristics and advantages of MRI-guided RT as well as emerging clinical outcomes.
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Affiliation(s)
- Michael D Chuong
- Department of Radiation Oncology, Miami Cancer Institute, 8900 North Kendall Drive, Miami, FL 33176, USA.
| | - Russell F Palm
- Department of Radiation Oncology, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, FL 33612, USA
| | - Michael C Tjong
- Department of Radiation Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Daniel E Hyer
- Department of Radiation Oncology, University of Iowa, 200 Hawkins Dr, Iowa City, IA 52242, USA
| | - Amar U Kishan
- Department of Radiation Oncology, University of California Los Angeles, 1338 S Hope Street, Los Angeles, CA 90015, USA
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Kayal EB, Alampally JT, Sharma R, Bakhshi S, Mehndiratta A, Kumar R, Chandrashekhara SH, Jana M, Bhalla AS, Sharma MC, Mridha AR, Vishnubhatla S, Kandasamy D. Chemotherapy response evaluation using diffusion weighted MRI in Ewing Sarcoma: A single center experience. Acta Radiol 2023; 64:1508-1517. [PMID: 36071615 DOI: 10.1177/02841851221124669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Non-invasive biomarkers for early chemotherapeutic response in Ewing sarcoma family of tumors (ESFT) are useful for optimizing existing treatment protocol. PURPOSE To assess the role of diffusion-weighted magnetic resonance imaging (MRI) in the early evaluation of chemotherapeutic response in ESFT. MATERIAL AND METHODS A total of 28 patients (mean age = 17.2 ± 5.6 years) with biopsy proven ESFT were analyzed prospectively. Patients underwent MRI acquisition on a 1.5-T scanner at three time points: before starting neoadjuvant chemotherapy (baseline), after first cycle chemotherapy (early time point), and after completion of chemotherapy (last time point). RECIST 1.1 criteria was used to evaluate the response to chemotherapy and patients were categorized as responders (complete and partial response) and non-responders (stable and progressive disease). Tumor diameter, absolute apparent diffusion coefficient (ADC), and normalized ADC (nADC) values in the tumor were measured. Baseline parameters and relative percentage change of parameters after first cycle chemotherapy were assessed for early detection of chemotherapy response. RESULTS The responder:non-responder ratio was 21:7. At baseline, ADC ([0.864 ± 0.266 vs. 0.977 ± 0.246]) × 10-3mm2/s; P = 0.205) and nADC ([0.740 ± 0.254 vs. 0.925 ± 0.262] × 10-3mm2/s; P = 0.033) among responders was lower than the non-responders and predicted response to chemotherapy with AUCs of 0.6 and 0.735, respectively. At the early time point, tumor diameter (27% ± 14% vs. 4.6% ± 10%; P = 0.002) showed a higher reduction and ADC (75% ± 44% vs. 52% ± 72%; P = 0.039) and nADC (81% ± 44% vs. 48% ± 67%; P = 0.008) showed a higher increase in mean values among responders than the non-responders and identified chemotherapy response with AUC of 0.890, 0.723, and 0.756, respectively. CONCLUSION Baseline nADC and its change after the first cycle of chemotherapy can be used as non-invasive surrogate markers of early chemotherapeutic response in patients with ESFT.
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Affiliation(s)
- Esha Baidya Kayal
- Centre for Biomedical Engineering, 28817Indian Institute of Technology Delhi, New Delhi, India
| | | | - Raju Sharma
- Department of Radiodiagnosis, 28730All India Institute of Medical Sciences, New Delhi, India
| | - Sameer Bakhshi
- Department of Medical Oncology, Dr B.R. Ambedkar Institute-Rotary Cancer Hospital (IRCH), 28730All India Institute of Medical Sciences, New Delhi, India
| | - Amit Mehndiratta
- Centre for Biomedical Engineering, 28817Indian Institute of Technology Delhi, New Delhi, India
- Department of Biomedical Engineering, 28730All India Institute of Medical Sciences, New Delhi, India
| | - Rakesh Kumar
- Department of Nuclear Medicine, 28730All India Institute of Medical Sciences, New Delhi, India
| | - S H Chandrashekhara
- Department of Medical Radiodiagnosis, Dr B.R. Ambedkar Institute-Rotary Cancer Hospital (IRCH), 28730All India Institute of Medical Sciences, New Delhi, India
| | - Manisha Jana
- Department of Radiodiagnosis, 28730All India Institute of Medical Sciences, New Delhi, India
| | - Ashu Seith Bhalla
- Department of Radiodiagnosis, 28730All India Institute of Medical Sciences, New Delhi, India
| | - Mehar Chand Sharma
- Department of Pathology, 28730All India Institute of Medical Sciences, New Delhi, India
| | - Asit Ranjan Mridha
- Department of Pathology, 28730All India Institute of Medical Sciences, New Delhi, India
| | - Sreenivas Vishnubhatla
- Department of Biostatistics, 28730All India Institute of Medical Sciences, New Delhi, India
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Lerouge L, Gries M, Chateau A, Daouk J, Lux F, Rocchi P, Cedervall J, Olsson AK, Tillement O, Frochot C, Acherar S, Thomas N, Barberi-Heyob M. Targeting Glioblastoma-Associated Macrophages for Photodynamic Therapy Using AGuIX ®-Design Nanoparticles. Pharmaceutics 2023; 15:pharmaceutics15030997. [PMID: 36986856 PMCID: PMC10057379 DOI: 10.3390/pharmaceutics15030997] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/15/2023] [Accepted: 03/17/2023] [Indexed: 03/30/2023] Open
Abstract
Glioblastoma (GBM) is the most difficult brain cancer to treat, and photodynamic therapy (PDT) is emerging as a complementary approach to improve tumor eradication. Neuropilin-1 (NRP-1) protein expression plays a critical role in GBM progression and immune response. Moreover, various clinical databases highlight a relationship between NRP-1 and M2 macrophage infiltration. In order to induce a photodynamic effect, multifunctional AGuIX®-design nanoparticles were used in combination with a magnetic resonance imaging (MRI) contrast agent, as well as a porphyrin as the photosensitizer molecule and KDKPPR peptide ligand for targeting the NRP-1 receptor. The main objective of this study was to characterize the impact of macrophage NRP-1 protein expression on the uptake of functionalized AGuIX®-design nanoparticles in vitro and to describe the influence of GBM cell secretome post-PDT on the polarization of macrophages into M1 or M2 phenotypes. By using THP-1 human monocytes, successful polarization into the macrophage phenotypes was argued via specific morphological traits, discriminant nucleocytoplasmic ratio values, and different adhesion abilities based on real-time cell impedance measurements. In addition, macrophage polarization was confirmed via the transcript-level expression of TNFα, CXCL10, CD-80, CD-163, CD-206, and CCL22 markers. In relation to NRP-1 protein over-expression, we demonstrated a three-fold increase in functionalized nanoparticle uptake for the M2 macrophages compared to the M1 phenotype. The secretome of the post-PDT GBM cells led to nearly a three-fold increase in the over-expression of TNFα transcripts, confirming the polarization to the M1 phenotype. The in vivo relationship between post-PDT efficiency and the inflammatory effects points to the extensive involvement of macrophages in the tumor zone.
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Affiliation(s)
- Lucie Lerouge
- Department of Biology, Signals and Systems in Cancer and Neuroscience, CRAN, UMR7039, Université de Lorraine-French National Scientific Research Center (CNRS), 54500 Vandœuvre-lès-Nancy, France
| | - Mickaël Gries
- Department of Biology, Signals and Systems in Cancer and Neuroscience, CRAN, UMR7039, Université de Lorraine-French National Scientific Research Center (CNRS), 54500 Vandœuvre-lès-Nancy, France
| | - Alicia Chateau
- Department of Biology, Signals and Systems in Cancer and Neuroscience, CRAN, UMR7039, Université de Lorraine-French National Scientific Research Center (CNRS), 54500 Vandœuvre-lès-Nancy, France
| | - Joël Daouk
- Department of Biology, Signals and Systems in Cancer and Neuroscience, CRAN, UMR7039, Université de Lorraine-French National Scientific Research Center (CNRS), 54500 Vandœuvre-lès-Nancy, France
| | - François Lux
- Institute of Light and Matter (ILM), UMR5306, Université de Lyon-CNRS, 69100 Lyon, France
| | - Paul Rocchi
- Institute of Light and Matter (ILM), UMR5306, Université de Lyon-CNRS, 69100 Lyon, France
| | - Jessica Cedervall
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Biomedical Center, Uppsala University, 75105 Uppsala, Sweden
| | - Anna-Karin Olsson
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Biomedical Center, Uppsala University, 75105 Uppsala, Sweden
| | - Olivier Tillement
- Institute of Light and Matter (ILM), UMR5306, Université de Lyon-CNRS, 69100 Lyon, France
| | - Céline Frochot
- Reactions and Chemical Engineering Laboratory (LRGP), UMR7274, Université de Lorraine-CNRS, 54000 Nancy, France
| | - Samir Acherar
- Laboratory of Chemical Physics of Macromolecules (LCPM), UMR7375, Université de Lorraine-CNRS, 54000 Nancy, France
| | - Noémie Thomas
- Department of Biology, Signals and Systems in Cancer and Neuroscience, CRAN, UMR7039, Université de Lorraine-French National Scientific Research Center (CNRS), 54500 Vandœuvre-lès-Nancy, France
| | - Muriel Barberi-Heyob
- Department of Biology, Signals and Systems in Cancer and Neuroscience, CRAN, UMR7039, Université de Lorraine-French National Scientific Research Center (CNRS), 54500 Vandœuvre-lès-Nancy, France
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11
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Ingle M, Blackledge M, White I, Wetscherek A, Lalondrelle S, Hafeez S, Bhide S. Quantitative analysis of diffusion weighted imaging in rectal cancer during radiotherapy using a magnetic resonance imaging integrated linear accelerator. Phys Imaging Radiat Oncol 2022; 23:32-37. [PMID: 35756883 PMCID: PMC9214864 DOI: 10.1016/j.phro.2022.06.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 05/16/2022] [Accepted: 06/02/2022] [Indexed: 11/25/2022] Open
Abstract
Background and purpose Magnetic resonance imaging integrated linear accelerator (MR-Linac) platforms enable acquisition of diffusion weighted imaging (DWI) during treatment providing potential information about treatment response. Obtaining DWI on these platforms is technically different from diagnostic magnetic resonance imaging (MRI) scanners. The aim of this project was to determine feasibility of obtaining DWI and calculating apparent diffusion coefficient (ADC) parameters longitudinally in rectal cancer patients on the MR-Linac. Materials and methods Nine patients undergoing treatment on MR-Linac had DWI acquired using b-values 0, 30, 150, 500 s/mm2. Gross tumour volume (GTV) and normal tissue was delineated on DWI throughout treatment and median ADC was calculated using an in-house tool (pyOsirix ®). Results Seven out of nine patients were included in the analysis; all demonstrated downstaging at follow-up. A total of 63 out of 70 DWI were analysed (7 excluded due to poor image quality). An increasing trend of ADC median for GTV (1.15 × 10-3 mm2/s interquartile range (IQ): 1.05-1.17 vs 1.59 × 10-3 mm2/s IQ: 1.37 - 1.64; p = 0.0156), correlating to treatment response. In comparison ADC median for normal tissue remained the same between first and last fraction (1.61 × 10-3 mm2/s IQ: 1.56-1.71 vs 1.67 × 10-3 mm2/s IQ: 1.37-2.00; p = 0.9375). Conclusions DWI assessment in rectal cancer patients on MR-Linac is feasible. Initial results provide foundations for further studies to determine DWI use for treatment adaptation in rectal cancer.
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Affiliation(s)
- Manasi Ingle
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Matthew Blackledge
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Ingrid White
- Guys and St Thomas NHS Trust, Great Maze Pond, London SE1 9RT, UK
| | - Andreas Wetscherek
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Susan Lalondrelle
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Shaista Hafeez
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Shreerang Bhide
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
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12
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Katharina Ingenerf M, Karim H, Fink N, Ilhan H, Ricke J, Treitl KM, Schmid-Tannwald C. Apparent diffusion coefficients (ADC) in response assessment of transarterial radioembolization (TARE) for liver metastases of neuroendocrine tumors (NET): a feasibility study. Acta Radiol 2022; 63:877-888. [PMID: 34225464 PMCID: PMC9194807 DOI: 10.1177/02841851211024004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background In patients with hepatic neuroendocrine tumors (NETs) locoregional therapies
such as transarterial radioembolization (TARE) are increasingly applied.
Response evaluation remains challenging and previous studies assessing
response with diffusion-weighted imaging (DWI) have been inconclusive. Purpose To perform a feasibility study to evaluate if response assessment with
quantitative apparent diffusion coefficient (ADC) in patients with liver
metastases of NETs after TARE will be possible. Material and Methods Retrospectively, 43 patients with 120 target lesions who obtained abdominal
magnetic resonance imaging (MRI) with DWI 39±28 days before and 74±46 days
after TARE were included. Intralesional ADC (ADCmin,
ADCmax, and ADCmean) were measured for a maximum
number of three lesions per patient on baseline and post-interventional DWI.
Tumor response was categorized according to RECIST 1.1 and mRECIST. Results TARE resulted in partial remission (PR) in 23% (63%), in stable disease (SD)
in 73% (23%), in progressive disease (PD) in 5% (7%) and in complete
response (CR) in 0% (1%) according to RECIST 1.1 (mRECIST, respectively).
ADC values increased significantly (P<0.005) after TARE
in the PR group whereas there was no significant change in the PD group.
Post-therapeutic ADC values of SD lesions increased significantly when
evaluated by RECIST 1.1 but not if evaluated by mRECIST. Percentual changes
of ADCmean values were slightly higher for responders compared to
non-responders (P<0.05). Conclusion ADC values seem to represent an additional marker for treatment response
evaluation after TARE in patients with secondary hepatic NET. A conclusive
study seems feasible though patient-based evaluation and overall survival
and progression free survival as alternate primary endpoints should be
considered.
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Affiliation(s)
- Maria Katharina Ingenerf
- Klinik und Poliklinik für Radiologie, Klinikum der Universität München, LMU München, Munich, Germany
| | - Homeira Karim
- Klinik und Poliklinik für Radiologie, Klinikum der Universität München, LMU München, Munich, Germany
| | - Nicola Fink
- Klinik und Poliklinik für Radiologie, Klinikum der Universität München, LMU München, Munich, Germany
| | - Harun Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Jens Ricke
- Klinik und Poliklinik für Radiologie, Klinikum der Universität München, LMU München, Munich, Germany
| | - Karla-Maria Treitl
- Klinik und Poliklinik für Radiologie, Klinikum der Universität München, LMU München, Munich, Germany
| | - Christine Schmid-Tannwald
- Klinik und Poliklinik für Radiologie, Klinikum der Universität München, LMU München, Munich, Germany
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13
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Qiu WR, Qi BB, Lin WZ, Zhang SH, Yu WK, Huang SF. Predicting the Lung Adenocarcinoma and Its Biomarkers by Integrating Gene Expression and DNA Methylation Data. Front Genet 2022; 13:926927. [PMID: 35846148 PMCID: PMC9280023 DOI: 10.3389/fgene.2022.926927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 06/13/2022] [Indexed: 11/17/2022] Open
Abstract
The early symptoms of lung adenocarcinoma patients are inapparent, and the clinical diagnosis of lung adenocarcinoma is primarily through X-ray examination and pathological section examination, whereas the discovery of biomarkers points out another direction for the diagnosis of lung adenocarcinoma with the development of bioinformatics technology. However, it is not accurate and trustworthy to diagnose lung adenocarcinoma due to omics data with high-dimension and low-sample size (HDLSS) features or biomarkers produced by utilizing only single omics data. To address the above problems, the feature selection methods of biological analysis are used to reduce the dimension of gene expression data (GSE19188) and DNA methylation data (GSE139032, GSE49996). In addition, the Cartesian product method is used to expand the sample set and integrate gene expression data and DNA methylation data. The classification is built by using a deep neural network and is evaluated on K-fold cross validation. Moreover, gene ontology analysis and literature retrieving are used to analyze the biological relevance of selected genes, TCGA database is used for survival analysis of these potential genes through Kaplan-Meier estimates to discover the detailed molecular mechanism of lung adenocarcinoma. Survival analysis shows that COL5A2 and SERPINB5 are significant for identifying lung adenocarcinoma and are considered biomarkers of lung adenocarcinoma.
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Affiliation(s)
- Wang-Ren Qiu
- Computer Department, Jing-De-Zhen Ceramic Institute, Jingdezhen, China
- *Correspondence: Wang-Ren Qiu, ; Shun-Fa Huang,
| | - Bei-Bei Qi
- Computer Department, Jing-De-Zhen Ceramic Institute, Jingdezhen, China
| | - Wei-Zhong Lin
- Computer Department, Jing-De-Zhen Ceramic Institute, Jingdezhen, China
| | - Shou-Hua Zhang
- Department of General Surgery, Jiangxi Provincial Children’s Hospital, Nanchang, China
| | - Wang-Ke Yu
- Computer Department, Jing-De-Zhen Ceramic Institute, Jingdezhen, China
| | - Shun-Fa Huang
- School of Information Engineering, Jingdezhen University, Jingdezhen, China
- *Correspondence: Wang-Ren Qiu, ; Shun-Fa Huang,
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14
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Jiménez de los Santos ME, Reyes-Pérez JA, Domínguez Osorio V, Villaseñor-Navarro Y, Moreno-Astudillo L, Vela-Sarmiento I, Sollozo-Dupont I. Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer. World J Gastroenterol 2022; 28:2609-2624. [PMID: 35949349 PMCID: PMC9254137 DOI: 10.3748/wjg.v28.i23.2609] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/25/2021] [Accepted: 04/25/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Whole-tumor apparent diffusion coefficient (ADC) histogram analysis is relevant to predicting the neoadjuvant chemoradiation therapy (nCRT) response in patients with locally advanced rectal cancer (LARC).
AIM To evaluate the performance of ADC histogram-derived parameters for predicting the outcomes of patients with LARC.
METHODS This is a single-center, retrospective study, which included 48 patients with LARC. All patients underwent a pre-treatment magnetic resonance imaging (MRI) scan for primary tumor staging and a second restaging MRI for response evaluation. The sample was distributed as follows: 18 responder patients (R) and 30 non-responders (non-R). Eight parameters derived from the whole-lesion histogram analysis (ADCmean, skewness, kurtosis, and ADC10th, 25th, 50th, 75th, 90th percentiles), as well as the ADCmean from the hot spot region of interest (ROI), were calculated for each patient before and after treatment. Then all data were compared between R and non-R using the Mann-Whitney U test. Two measures of diagnostic accuracy were applied: the receiver operating characteristic curve and the diagnostic odds ratio (DOR). We also reported intra- and interobserver variability by calculating the intraclass correlation coefficient (ICC).
RESULTS Post-nCRT kurtosis, as well as post-nCRT skewness, were significantly lower in R than in non-R (both P < 0.001, respectively). We also found that, after treatment, R had a larger loss of both kurtosis and skewness than non-R (∆%kurtosis and ∆skewness, P < 0.001). Other parameters that demonstrated changes between groups were post-nCRT ADC10th, ∆%ADC10th, ∆%ADCmean, and ROI ∆%ADCmean. However, the best diagnostic performance was achieved by ∆%kurtosis at a threshold of 11.85% (Area under the receiver operating characteristic curve [AUC] = 0.991, DOR = 376), followed by post-nCRT kurtosis = 0.78 × 10-3 mm2/s (AUC = 0.985, DOR = 375.3), ∆skewness = 0.16 (AUC = 0.885, DOR = 192.2) and post-nCRT skewness = 1.59 × 10-3 mm2/s (AUC = 0.815, DOR = 168.6). Finally, intraclass correlation coefficient analysis showed excellent intraobserver and interobserver agreement, ensuring the implementation of histogram analysis into routine clinical practice.
CONCLUSION Whole-tumor ADC histogram parameters, particularly kurtosis and skewness, are relevant biomarkers for predicting the nCRT response in LARC. Both parameters appear to be more reliable than ADCmean from one-slice ROI.
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Affiliation(s)
| | | | | | | | | | - Itzel Vela-Sarmiento
- Department of Gastrointestinal Surgery, National Cancer Institute, Mexico 14080, Mexico
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15
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Fontana G, Barcellini A, Boccuzzi D, Pecorilla M, Loap P, Cobianchi L, Vitolo V, Fiore MR, Vai A, Baroni G, Preda L, Imparato S, Orlandi E. Role of diffusion-weighted MRI in recurrent rectal cancer treated with carbon ion radiotherapy. Future Oncol 2022; 18:2403-2412. [PMID: 35712914 DOI: 10.2217/fon-2021-1554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: To evaluate the association between pretreatment diffusion-weighted MRI (DW-MRI) and 12-month radiological response in locally recurrent rectal cancer treated with carbon ion radiotherapy. Methods: Histogram analysis was performed on pretreatment DW-MRI for patients re-irradiated with carbon ion radiotherapy for local recurrence of rectal cancer. Results: A total of 17 patients were enrolled in the study. Pretreatment DW-MRI b-value of 1000 s/mm2 (b1000) and apparent diffusion coefficient (ADC) lesion median values for 1-year nonresponders (six patients) and responders (11 patients) demonstrated a median (interquartile of median values) of 62.5 (23.9) and 34.0 (13.0) and 953.0 (277.0) and 942.5 (339.0) μm2/s, respectively. All b1000 histogram features (h-features) and ADC h-kurtosis showed statistically significant differences, whereas only b1000 h-median, b1000 h-interquartile range and ADC h-kurtosis demonstrated remarkable diagnostic accuracy. Conclusion: DW-MRI showed promising results in predicting carbon ion radiotherapy outcome in local recurrence of rectal cancer, particularly with regard to b1000 h-median, b1000 h-interquartile range and ADC h-kurtosis.
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Affiliation(s)
- Giulia Fontana
- Clinical Bioengineering Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy
| | - Amelia Barcellini
- Radiation Oncology Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy
| | - Dario Boccuzzi
- Department of Radiology, Diagnostic Radiology Residency School, University of Pavia, Pavia, 27100, Italy.,Department of Radiology, Valduce Hospital, Como, 22100, Italy
| | - Mattia Pecorilla
- Radiology Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy
| | - Pierre Loap
- Radiation Oncology Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy.,Department of Radiation Oncology, Institut Curie, Paris, 75005, France
| | - Lorenzo Cobianchi
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, 27100, Italy.,Department of General Surgery, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy
| | - Viviana Vitolo
- Radiation Oncology Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy
| | - Maria Rosaria Fiore
- Radiation Oncology Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy
| | - Alessandro Vai
- Medical Physics Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy
| | - Guido Baroni
- Clinical Bioengineering Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy.,Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, 20133, Italy
| | - Lorenzo Preda
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, 27100, Italy.,Department of Radiology, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy
| | - Sara Imparato
- Radiology Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy
| | - Ester Orlandi
- Radiation Oncology Unit, Clinical Department, National Center for Oncological Hadrontherapy, Pavia, 27100, Italy
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16
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Wang J, Chen J, Zhou R, Gao Y, Li J. Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients. BMC Cancer 2022; 22:420. [PMID: 35439946 PMCID: PMC9017030 DOI: 10.1186/s12885-022-09518-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 04/08/2022] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND The purpose of this study was to investigate and validate multiparametric magnetic resonance imaging (MRI)-based machine learning classifiers for early identification of poor responders after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). METHODS Patients with LARC who underwent nCRT were included in this retrospective study (207 patients). After preprocessing of multiparametric MRI, radiomics features were extracted and four feature selection methods were used to select robust features. The selected features were used to build five machine learning classifiers, and 20 (four feature selection methods × five machine learning classifiers) predictive models for the screening of poor responders were constructed. The predictive models were evaluated according to the area under the curve (AUC), F1 score, accuracy, sensitivity, and specificity. RESULTS Eighty percent of all predictive models constructed achieved an AUC of more than 0.70. A predictive model using a support vector machine classifier with the minimum redundancy maximum relevance (mRMR) selection method followed by the least absolute shrinkage and selection operator (LASSO) selection method showed superior prediction performance, with an AUC of 0.923, an F1 score of 88.14%, and accuracy of 91.03%. The predictive performance of the constructed models was not improved by ComBat compensation. CONCLUSIONS In rectal cancer patients who underwent neoadjuvant chemoradiotherapy, machine learning classifiers with radiomics features extracted from multiparametric MRI were able to accurately discriminate poor responders from good responders. The techniques should provide additional information to guide patient-tailored treatment.
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Affiliation(s)
- Jia Wang
- Department of Ultrasound, Qingdao Women and Children Hospital, Shandong, Qingdao, China
| | - Jingjing Chen
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Shandong, Qingdao, China
| | - Ruizhi Zhou
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Shandong, Qingdao, China
| | - Yuanxiang Gao
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Shandong, Qingdao, China
| | - Jie Li
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Shandong, Qingdao, China.
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17
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[Complete response after neoadjuvant therapy: how certain is radiology?]. Chirurg 2021; 93:123-131. [PMID: 34936002 DOI: 10.1007/s00104-021-01548-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/12/2021] [Indexed: 11/11/2022]
Abstract
The concept of total neoadjuvant therapy (TNT) means a paradigm shift in the treatment of patients with rectal cancer. In cases in which the TNT induced a complete clinical response (cCR), an organ preserving watch and wait therapy concept can now be provided more often; however, this increases the demand for imaging for the determination of cCR and in the subsequent follow-up. In this article, the performance of radiology in these scenarios will be evaluated and discussed. Magnetic resonance imaging (MRI) is the current standard for local assessment of the rectum with a high sensitivity for diagnosis and staging of rectal cancer, residual tumor and tumor recurrence. However, the certain exclusion of residual malignant tissue is still difficult, in particular the differentiation of residual scar tissue from vital residual tumor is only possible with low specificity and a moderate negative predictive value (NPV). The currently discussed criteria for the assessment of imaging have not yet been validated in large cohorts and are frequently subjective. An improvement of the diagnostic accuracy for identification of cCR in patients after TNT and for monitoring patients in watch and wait treatment concepts can certainly be achieved by the integration of MRI, endoscopy and endosonography as well as clinical parameters. This should enable for identification of patients with an incomplete response or local recurrence, in time for extended treatment to be initiated without relevant impact on the patient outcome.
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18
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Cheng J, Cui ZX, Huang W, Ke Z, Ying L, Wang H, Zhu Y, Liang D. Learning Data Consistency and its Application to Dynamic MR Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3140-3153. [PMID: 34252025 DOI: 10.1109/tmi.2021.3096232] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Magnetic resonance (MR) image reconstruction from undersampled k-space data can be formulated as a minimization problem involving data consistency and image prior. Existing deep learning (DL)-based methods for MR reconstruction employ deep networks to exploit the prior information and integrate the prior knowledge into the reconstruction under the explicit constraint of data consistency, without considering the real distribution of the noise. In this work, we propose a new DL-based approach termed Learned DC that implicitly learns the data consistency with deep networks, corresponding to the actual probability distribution of system noise. The data consistency term and the prior knowledge are both embedded in the weights of the networks, which provides an utterly implicit manner of learning reconstruction model. We evaluated the proposed approach with highly undersampled dynamic data, including the dynamic cardiac cine data with up to 24-fold acceleration and dynamic rectum data with the acceleration factor equal to the number of phases. Experimental results demonstrate the superior performance of the Learned DC both quantitatively and qualitatively than the state-of-the-art.
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19
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Li D, Cui Y, Hou L, Bian Z, Yang Z, Xu R, Jia Y, Wu Z, Yang X. Diffusion kurtosis imaging-derived histogram metrics for prediction of resistance to neoadjuvant chemoradiotherapy in rectal adenocarcinoma: Preliminary findings. Eur J Radiol 2021; 144:109963. [PMID: 34562744 DOI: 10.1016/j.ejrad.2021.109963] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/14/2021] [Accepted: 09/16/2021] [Indexed: 01/04/2023]
Abstract
PURPOSE This study aimed to evaluate the potential role of diffusion kurtosis imaging (DKI)-derived parameters for assessing resistance to CRT in patients with Locally advanced rectal cancer (LARC) by using histogram analysis derived from whole-tumor volumes. METHOD 136 consecutive patients with histologically confirmed rectal adenocarcinoma who underwent MRI examination before and after chemoradiotherapy were enrolled in our retrospective study. The parameters D, K, and conventional apparent diffusion coefficient (ADC) were measured using whole-tumor volume histogram analysis. The AJCC tumor regression grading (TRG) system was the standard reference (resistance: TRG 3; non-resistance: TRG 0-2). Receiver operating characteristic (ROC) curves were used for evaluating the diagnostic performance. RESULTS Aside from the skew and kurtosis values, we found all the histogram metrics of D and ADC values significantly increased after CRT (all p < 0.001). In contrast, the histogram metrics of K values significantly decreased after CRT. The majority of percentiles metrics of D, K, and ADC values were correlated with tumor resistance before and after CRT (P < 0.05), except for the skew and kurtosis values. Regarding the comparison of the diagnostic performance of all the histogram metrics, the percentage Dmean change (ΔDmean) showed the highest AUC value of 0.939, and the corresponding sensitivity, specificity, PPV, and NPV were 84.1% and 94.6%, 88.1% and 92.6%, respectively. CONCLUSIONS These preliminary results demonstrated that DKI-derived histogram metrics, especially the pre-treatment metrics and ΔDmean, were useful to assess tumoral resistance to CRT and individual clinical management for patients with LARC.
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Affiliation(s)
- Dandan Li
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China
| | - Yanfen Cui
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China
| | - Lina Hou
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China
| | - Zeyu Bian
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China
| | - Zhao Yang
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China
| | - Ruxin Xu
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China
| | - Yaju Jia
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China
| | - Zhifang Wu
- Department of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan 030001, Shanxi, China; Shanxi Medical University, Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Taiyuan 030001, Shanxi, China.
| | - Xiaotang Yang
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China.
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20
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Predict Treatment Response by Magnetic Resonance Diffusion Weighted Imaging: A Preliminary Study on 46 Meningiomas Treated with Proton-Therapy. Diagnostics (Basel) 2021; 11:diagnostics11091684. [PMID: 34574025 PMCID: PMC8469991 DOI: 10.3390/diagnostics11091684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 09/10/2021] [Accepted: 09/10/2021] [Indexed: 11/16/2022] Open
Abstract
Objective: a considerable subgroup of meningiomas (MN) exhibit indolent and insidious growth. Strategies to detect earlier treatment responses based on tumour biology rather than on size can be useful. We aimed to characterize therapy-induced changes in the apparent diffusion coefficient (ADC) of MN treated with proton-therapy (PT), determining whether the pre- and early post-treatment ADC values may predict tumour response. Methods: Forty-four subjects with MN treated with PT were retrospectively enrolled. All patients underwent conventional magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) at baseline and each 3 months for a follow-up period up to 36 months after the beginning of PT. Mean relative ADC (rADCm) values of 46 MN were measured at each exam. The volume variation percentage (VV) for each MN was calculated. The Wilcoxon test was used to assess the differences in rADCm values between pre-treatment and post-treatment exams. Patients were grouped in terms of VV (threshold −20%). A p < 0.05 was considered statistically significant for all the tests. Results: A significant progressive increase of rADCm values was detected at each time point when compared to baseline rADCm (p < 0.05). Subjects that showed higher pre-treatment rADCm values had no significant volume changes or showed volume increase, while subjects that showed a VV < −20% had significantly lower pre-treatment rADCm values. Higher and earlier rADCm increases (3 months) are related to greater volume reduction. Conclusion: In MN treated with PT, pre-treatment rADCm values and longitudinal rADCm changes may predict treatment response.
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22
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Wang C, Padgett KR, Su MY, Mellon EA, Maziero D, Chang Z. Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy. Med Phys 2021; 49:2794-2819. [PMID: 34374098 DOI: 10.1002/mp.15130] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 06/23/2021] [Accepted: 06/28/2021] [Indexed: 11/11/2022] Open
Abstract
Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.
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Affiliation(s)
- Chunhao Wang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
| | - Kyle R Padgett
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA.,Department of Radiology, University of Miami, Miami, Florida, USA
| | - Min-Ying Su
- Department of Radiological Sciences, University of California, Irvine, California, USA.,Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Eric A Mellon
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA
| | - Danilo Maziero
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA
| | - Zheng Chang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
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23
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Zhu HT, Zhang XY, Shi YJ, Li XT, Sun YS. Automatic segmentation of rectal tumor on diffusion-weighted images by deep learning with U-Net. J Appl Clin Med Phys 2021; 22:324-331. [PMID: 34343402 PMCID: PMC8425941 DOI: 10.1002/acm2.13381] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 03/28/2021] [Accepted: 07/06/2021] [Indexed: 12/17/2022] Open
Abstract
Purpose Manual delineation of a rectal tumor on a volumetric image is time‐consuming and subjective. Deep learning has been used to segment rectal tumors automatically on T2‐weighted images, but automatic segmentation on diffusion‐weighted imaging is challenged by noise, artifact, and low resolution. In this study, a volumetric U‐shaped neural network (U‐Net) is proposed to automatically segment rectal tumors on diffusion‐weighted images. Methods Three hundred patients of locally advanced rectal cancer were enrolled in this study and divided into a training group, a validation group, and a test group. The region of rectal tumor was delineated on the diffusion‐weighted images by experienced radiologists as the ground truth. A U‐Net was designed with a volumetric input of the diffusion‐weighted images and an output of segmentation with the same size. A semi‐automatic segmentation method was used for comparison by manually choosing a threshold of gray level and automatically selecting the largest connected region. Dice similarity coefficient (DSC) was calculated to evaluate the methods. Results On the test group, deep learning method (DSC = 0.675 ± 0.144, median DSC is 0.702, maximum DSC is 0.893, and minimum DSC is 0.297) showed higher segmentation accuracy than the semi‐automatic method (DSC = 0.614 ± 0.225, median DSC is 0.685, maximum DSC is 0.869, and minimum DSC is 0.047). Paired t‐test shows significant difference (T = 2.160, p = 0.035) in DSC between the deep learning method and the semi‐automatic method in the test group. Conclusion Volumetric U‐Net can automatically segment rectal tumor region on DWI images of locally advanced rectal cancer.
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Affiliation(s)
- Hai-Tao Zhu
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiao-Yan Zhang
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Yan-Jie Shi
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiao-Ting Li
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Ying-Shi Sun
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
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24
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Ko CC, Yeh LR, Kuo YT, Chen JH. Imaging biomarkers for evaluating tumor response: RECIST and beyond. Biomark Res 2021; 9:52. [PMID: 34215324 PMCID: PMC8252278 DOI: 10.1186/s40364-021-00306-8] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 06/10/2021] [Indexed: 12/12/2022] Open
Abstract
Response Evaluation Criteria in Solid Tumors (RECIST) is the gold standard for assessment of treatment response in solid tumors. Morphologic change of tumor size evaluated by RECIST is often correlated with survival length and has been considered as a surrogate endpoint of therapeutic efficacy. However, the detection of morphologic change alone may not be sufficient for assessing response to new anti-cancer medication in all solid tumors. During the past fifteen years, several molecular-targeted therapies and immunotherapies have emerged in cancer treatment which work by disrupting signaling pathways and inhibited cell growth. Tumor necrosis or lack of tumor progression is associated with a good therapeutic response even in the absence of tumor shrinkage. Therefore, the use of unmodified RECIST criteria to estimate morphological changes of tumor alone may not be sufficient to estimate tumor response for these new anti-cancer drugs. Several studies have reported the low reliability of RECIST in evaluating treatment response in different tumors such as hepatocellular carcinoma, lung cancer, prostate cancer, brain glioma, bone metastasis, and lymphoma. There is an increased need for new medical imaging biomarkers, considering the changes in tumor viability, metabolic activity, and attenuation, which are related to early tumor response. Promising imaging techniques, beyond RECIST, include dynamic contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI), diffusion-weight imaging (DWI), magnetic resonance spectroscopy (MRS), and 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET). This review outlines the current RECIST with their limitations and the new emerging concepts of imaging biomarkers in oncology.
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Affiliation(s)
- Ching-Chung Ko
- Department of Medical Imaging, Chi Mei Medical Center, Tainan, Taiwan.,Department of Health and Nutrition, Chia Nan University of Pharmacy and Science, Tainan, Taiwan
| | - Lee-Ren Yeh
- Department of Radiology, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan
| | - Yu-Ting Kuo
- Department of Medical Imaging, Chi Mei Medical Center, Tainan, Taiwan.,Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Jeon-Hor Chen
- Department of Radiology, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan. .,Tu & Yuan Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, 164 Irvine Hall, Irvine, CA, 92697 - 5020, USA.
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25
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Han Z, Li M, Chen J, Ji D, Zhan T, Peng Y, Xue W, Li Y, Cai Y, Sun Y, Wu Q, Du C, Gu J. Surgery may not benefit patients with locally advanced rectal cancer who achieved clinical complete response following neoadjuvant chemoradiotherapy. Asian J Surg 2021; 45:97-104. [PMID: 33888366 DOI: 10.1016/j.asjsur.2021.03.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 02/03/2021] [Accepted: 03/26/2021] [Indexed: 12/20/2022] Open
Abstract
PURPOSE We compared the long-term outcome of the watch and wait (WW) strategy and surgery in patients with locally advanced rectal cancer. PATIENTS AND METHODS This prospective cohort study included 84 patients who achieved clinical complete response (cCR) after neoadjuvant chemoradiotherapy (NCRT). They were divided into the WW group (n = 58) and surgery group (SG, n = 26). Patients in the SG underwent total mesorectal excision. The study site was the Peking University Cancer Hospital. RESULTS Eighty-four patients were included (58 and 26 in the WW group and SG, respectively). A total of 76·9% of the patients in the SG achieved pathological complete response (pCR) and 23·1% of the patients had a residual tumor. The total recurrence and metastasis rate was 15·4% (4/26) in the SG and 18·9% (11/58) in the WW group. There was no significant difference in the recurrence and metastasis rate between the two groups. In the WW group, 9 cases developed tumor regrowth during follow-up and underwent salvage surgery. The overall survival rate of the WW group (96·6% vs 92·3%) was not significantly different from that of the SG (P > 0·05). The WW patients also retained their anal sphincter function and avoided surgery-related complications. CONCLUSION The WW strategy is a feasible treatment option in patients with cCR after NCRT. Surgery may not bring benefits to these cCR patients.
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Affiliation(s)
- Zihan Han
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gastrointestinal Surgery, Peking University Cancer Hospital & Institute, China
| | - Ming Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gastrointestinal Surgery, Peking University Cancer Hospital & Institute, China
| | - Jiajia Chen
- Department of General Surgery, Peking University Shougang Hospital, Beijing, China
| | - Dengbo Ji
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gastrointestinal Surgery, Peking University Cancer Hospital & Institute, China
| | - Tiancheng Zhan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gastrointestinal Surgery, Peking University Cancer Hospital & Institute, China
| | - Yifan Peng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gastrointestinal Surgery, Peking University Cancer Hospital & Institute, China
| | - Weicheng Xue
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Pathology, Peking University Cancer Hospital & Institute, China
| | - Yongheng Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, China
| | - Yong Cai
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, China
| | - Yingshi Sun
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Imaging, Peking University Cancer Hospital & Institute, China
| | - Qi Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Endoscopy, Peking University Cancer Hospital & Institute, China
| | - Changzheng Du
- School of Medicine, The Southern University of Science and Technology, 1088Xue Yuan Road, Shenzhen, Guangdong, 518055, People's Republic of China.
| | - Jin Gu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gastrointestinal Surgery, Peking University Cancer Hospital & Institute, China; Peking University International Cancer Institute, China; Department of General Surgery, Peking University Shougang Hospital, Beijing, China; Peking-Tsinghua Center for Life Science, China.
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26
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Qiu J, Liu J, Bi Z, Sun X, Wang X, Zhang J, Liu C, Zhu J, Qin N. Integrated slice-specific dynamic shimming diffusion weighted imaging (DWI) for rectal Cancer detection and characterization. Cancer Imaging 2021; 21:32. [PMID: 33827704 PMCID: PMC8028796 DOI: 10.1186/s40644-021-00403-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 03/26/2021] [Indexed: 11/10/2022] Open
Abstract
PURPOSE To compare integrated slice-specific dynamic shimming (iShim) diffusion weighted imaging (DWI) and single-shot echo-planar imaging (SS-EPI) DWI in image quality and pathological characterization of rectal cancer. MATERIALS AND METHODS A total of 193 consecutive rectal tumor patients were enrolled for retrospective analysis. Among them, 101 patients underwent iShim-DWI (b = 0, 800, and 1600 s/mm2) and 92 patients underwent SS-EPI-DWI (b = 0, and 1000 s/mm2). Qualitative analyses of both DWI techniques was performed by two independent readers; including adequate fat suppression, the presence of artifacts and image quality. Quantitative analysis was performed by calculating standard deviation (SD) of the gluteus maximus, signal intensity (SI) of lesion and residual normal rectal wall, apparent diffusion coefficient (ADC) values (generated by b values of 0, 800 and 1600 s/mm2 for iShim-DWI, and by b values of 0 and 1000 s/mm2 for SS-EPI-DWI) and image quality parameters, such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of primary rectal tumor. For the primary rectal cancer, two pathological groups were divided according to pathological results: Group 1 (well-differentiated) and Group 2 (poorly differentiated). Statistical analyses were performed with p < 0.05 as significant difference. RESULTS Compared with SS-EPI-DWI, significantly higher scores of image quality were obtained in iShim-DWI cases (P < 0.001). The SDbackground was significantly reduced on b = 1600 s/mm2 images and ADC maps of iShim-DWI. Both SNR and CNR of b = 800 s/mm2 and b = 1600 s/mm2 images in iShim-DWI were higher than those of b = 1000 s/mm2 images in SS-EPI-DWI. In primary rectal cancer of iShim-DWI cohort, SIlesion was significantly higher than SIrectum in both b = 800 and 1600 s/mm2 images. ADC values were significantly lower in Group 2 (0.732 ± 0.08) × 10- 3 mm2/s) than those in Group 1 ((0.912 ± 0.21) × 10- 3 mm2/s). ROC analyses showed significance of ADC values and SIlesion between the two groups. CONCLUSION iShim-DWI with b values of 0, 800 and 1600 s/mm2 is a promising technique of high image quality in rectal tumor imaging, and has potential ability to differentiate rectal cancer from normal wall and predicting pathological characterization.
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Affiliation(s)
- Jianxing Qiu
- Department of Radiology, Peking University First Hospital, 8 XiShiKu Avenue, XiCheng District, Beijing, 100034, China
| | - Jing Liu
- Department of Radiology, Peking University First Hospital, 8 XiShiKu Avenue, XiCheng District, Beijing, 100034, China
| | - Zhongxu Bi
- Department of Radiology, Peking University First Hospital, 8 XiShiKu Avenue, XiCheng District, Beijing, 100034, China
| | - Xiaowei Sun
- Department of Radiology, Peking University First Hospital, 8 XiShiKu Avenue, XiCheng District, Beijing, 100034, China
| | - Xin Wang
- Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China
| | - Junling Zhang
- Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China
| | - Chengwen Liu
- MR Collaboration, Siemens Healthcare, Ltd., Beijing, China
| | - Jinxia Zhu
- MR Collaboration, Siemens Healthcare, Ltd., Beijing, China
| | - Naishan Qin
- Department of Radiology, Peking University First Hospital, 8 XiShiKu Avenue, XiCheng District, Beijing, 100034, China.
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Khwaja SA, Thipphavong S, Kirsch R, Menezes RJ, Kennedy ED, Brierley JD, Jhaveri KS. Evaluation of a multiparametric MRI scoring system for histopathologic treatment response following preoperative chemoradiotherapy for rectal cancer. Eur J Radiol 2021; 138:109628. [PMID: 33721764 DOI: 10.1016/j.ejrad.2021.109628] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 02/08/2021] [Accepted: 02/28/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE To evaluate the performance of a multiparametric (mp) MRI scoring system for assessment of tumour response in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (CRT). METHOD Fifty-nine consecutive patients with LARC who had rectal MRI before and after CRT followed by surgery were included. Two radiologists retrospectively assessed tumour response using a proposed mpMRI scoring system. Treatment response was classified as complete, near complete, partial or poor. Accuracy, sensitivity, specificity, positive predictive value and negative predictive values were calculated and inter-reader agreements were assessed. Pathologic tumour regression grade (pTRG) was the reference standard. RESULTS Treatment response was correctly predicted by both readers in 32.2%-40.7% of patients. Overestimation was more common than underestimation. Sensitivity, specificity, PPV and NPV for pathologic complete response (pCR) among both readers was 16.7-33.0 %, 88.7-94.2 %, 14.3-40.0 % and 92.5-94.2 % respectively. Sensitivity and PPV for both readers improved to 56.0-60.0 % and 53.6-66.7 % respectively when complete response and near complete response categories (good responders) were combined. Inter-reader agreement using the scoring system was fair (κ = 0.383). Agreement between mpMRI score and pathological tumour response was poor to fair for both readers (κ = 0.050 to 0.258) but improved when complete and near complete response categories (good responders) were combined (κ = 0.214 to 0.362). CONCLUSIONS Despite low agreement between radiological tumour response and pTRG, the proposed mpMRI-based scoring system appears useful in identifying good responders who may benefit from nonoperative management strategies.
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Affiliation(s)
- Samir A Khwaja
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, University of Toronto, Ontario, Canada; Department of Radiology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.
| | - Seng Thipphavong
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, University of Toronto, Ontario, Canada.
| | - Richard Kirsch
- Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada.
| | - Ravi J Menezes
- Joint Department of Medical Imaging, University Health Network, University of Toronto, Ontario, Canada.
| | - Erin D Kennedy
- Department of Surgery, Mount Sinai Hospital, Toronto, Ontario, Canada.
| | - James D Brierley
- Department of Radiation Oncology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
| | - Kartik S Jhaveri
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, University of Toronto, Ontario, Canada.
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van Houdt PJ, Yang Y, van der Heide UA. Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy. Front Oncol 2021; 10:615643. [PMID: 33585242 PMCID: PMC7878523 DOI: 10.3389/fonc.2020.615643] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/08/2020] [Indexed: 12/20/2022] Open
Abstract
MRI-guided radiotherapy systems have the potential to bring two important concepts in modern radiotherapy together: adaptive radiotherapy and biological targeting. Based on frequent anatomical and functional imaging, monitoring the changes that occur in volume, shape as well as biological characteristics, a treatment plan can be updated regularly to accommodate the observed treatment response. For this purpose, quantitative imaging biomarkers need to be identified that show changes early during treatment and predict treatment outcome. This review provides an overview of the current evidence on quantitative MRI measurements during radiotherapy and their potential as an imaging biomarker on MRI-guided radiotherapy systems.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles, CA, United States
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
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Zhao M, Zhao L, Yang H, Duan Y, Li G. Apparent diffusion coefficient for the prediction of tumor response to neoadjuvant chemo-radiotherapy in locally advanced rectal cancer. Radiat Oncol 2021; 16:17. [PMID: 33472660 PMCID: PMC7819172 DOI: 10.1186/s13014-020-01738-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 12/26/2020] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Patients with locally advanced rectal cancer generally have different response rates to preoperative neoadjuvant chemo-radiotherapy. This study investigated the value of the apparent diffusion coefficient (ADC) as a predictor to forecast the response to neoadjuvant chemo-radiotherapy in patients with locally advanced rectal cancer. METHODS Ninety-one locally advanced rectal cancer patients who underwent neoadjuvant chemo-radiotherapy between 2015 and 2018 were enrolled. Diffusion-weighted magnetic resonance imaging was performed before treatment and within 4 weeks after the completion of neoadjuvant chemo-radiotherapy. Mean ADC values of regions of interest were evaluated by two radiologists. The tumor response was evaluated according to RESCIST 1.1. The cut-off value for the mean ADC and increasing percentage (ΔADC%) after neoadjuvant chemo-radiotherapy was calculated using the receiver operating characteristic curve. The response rate of pre-ADC and ΔADC% above/below the cut-off values was determined using the chi-square test, respectively. Primary tumor progression-free survival (PFS) was analyzed using the Kaplan-Meier method, based on the pre-ADC and ΔADC% cut-off values. RESULTS The cut-off value of mean pre-ADC and ΔADC% was 0.94 × 10-3 mm2/s (80.36% sensitivity, 74.29% specificity) and 26.0% (73.21% sensitivity, 77.14% specificity), respectively. Lower mean pre-ADC values were related to a better response rate (83.3% vs 29.7%, P < 0.001) and PFS (26.12 vs 17.70 months, P = 0.004). ΔADC% above the cut-off value was also related to a better response rate (83.7% vs 35.7%, P < 0.001) and PFS (26.93 vs 15.65 months, P = 0.034). CONCLUSIONS The mean ADC pre-treatment value and ΔADC% were potential predictors for the tumor response in locally advanced rectal cancer patients treated with neoadjuvant chemo-radiotherapy.
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Affiliation(s)
- Mengjing Zhao
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China
| | - Lihao Zhao
- Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China
| | - Han Yang
- Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China
| | - Yuxia Duan
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
| | - Gang Li
- Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
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Di Re AM, Sun Y, Sundaresan P, Hau E, Toh JWT, Gee H, Or M, Haworth A. MRI radiomics in the prediction of therapeutic response to neoadjuvant therapy for locoregionally advanced rectal cancer: a systematic review. Expert Rev Anticancer Ther 2021; 21:425-449. [PMID: 33289435 DOI: 10.1080/14737140.2021.1860762] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Introduction: The standard of care for locoregionally advanced rectal cancer is neoadjuvant therapy (NA CRT) prior to surgery, of which 10-30% experience a complete pathologic response (pCR). There has been interest in using imaging features, also known as radiomics features, to predict pCR and potentially avoid surgery. This systematic review aims to describe the spectrum of MRI studies examining high-performing radiomic features that predict NA CRT response.Areas covered: This article reviews the use of pre-therapy MRI in predicting NA CRT response for patients with locoregionally advanced rectal cancer (T3/T4 and/or N1+). The primary outcome was to identify MRI radiomic studies; secondary outcomes included the power and the frequency of use of radiomic features.Expert opinion: Advanced models incorporating multiple radiomics categories appear to be the most promising. However, there is a need for standardization across studies with regards to; the definition of NA CRT response, imaging protocols, and radiomics features incorporated. Further studies are needed to validate current radiomics models and to fully ascertain the value of MRI radiomics in the response prediction for locoregionally advanced rectal cancer.
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Affiliation(s)
- Angelina Marina Di Re
- Colorectal Department, Westmead Hospital, Cnr Hawkesbury, Westmead, NSW.,School of Physics, University of Sydney, Camperdown, NSW, Australia
| | - Yu Sun
- School of Physics, University of Sydney, Camperdown, NSW, Australia
| | - Purnima Sundaresan
- Radiation Oncology Network, Western Sydney Local Health District, Cnr Hawkesbury, Westmead, NSW, Australia.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia
| | - Eric Hau
- Radiation Oncology Network, Western Sydney Local Health District, Cnr Hawkesbury, Westmead, NSW, Australia.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia.,Centre for Cancer Research, Westmead Institute of Medical Research, Westmead, NSW, Australia
| | - James Wei Tatt Toh
- Colorectal Department, Westmead Hospital, Cnr Hawkesbury, Westmead, NSW.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia.,Centre for Cancer Research, Westmead Institute of Medical Research, Westmead, NSW, Australia
| | - Harriet Gee
- Radiation Oncology Network, Western Sydney Local Health District, Cnr Hawkesbury, Westmead, NSW, Australia.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia
| | - Michelle Or
- Radiation Oncology Network, Western Sydney Local Health District, Cnr Hawkesbury, Westmead, NSW, Australia
| | - Annette Haworth
- School of Physics, University of Sydney, Camperdown, NSW, Australia
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31
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Ingle M, Lalondrelle S. Current Status of Anatomical Magnetic Resonance Imaging in Brachytherapy and External Beam Radiotherapy Planning and Delivery. Clin Oncol (R Coll Radiol) 2020; 32:817-827. [PMID: 33169690 DOI: 10.1016/j.clon.2020.10.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 10/06/2020] [Accepted: 10/08/2020] [Indexed: 02/06/2023]
Abstract
Radiotherapy planning and delivery have dramatically improved in recent times. Imaging is key to a successful three-dimensional and increasingly four-dimensional based pathway with computed tomography embedded as the backbone modality. Computed tomography has significant limitations for many tumour sites where soft-tissue discrimination is suboptimal, and where magnetic resonance imaging (MRI) has largely superseded in the diagnostic arena. MRI is increasingly used together with computed tomography in the radiotherapy planning pathway and is now established as a prerequisite for several tumours. With the advent of combined MRI and linear accelerator (MR-linac) systems, a transition to MRI-based radiotherapy planning is becoming reality, with increasing experience and research involving these new platforms. In this overview, we aim to highlight how magnetic resonance-guided imaging has improved radiotherapy, using gynaecological malignancies to illustrate, in both external beam radiotherapy and image-guided brachytherapy, and will assess the early evidence for magnetic resonance-guided radiotherapy using combined MR-linac systems.
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Affiliation(s)
- M Ingle
- Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK; Institute of Cancer Research, London, UK
| | - S Lalondrelle
- Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK; Institute of Cancer Research, London, UK.
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32
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Haak HE, Maas M, Trebeschi S, Beets-Tan RGH. Modern MR Imaging Technology in Rectal Cancer; There Is More Than Meets the Eye. Front Oncol 2020; 10:537532. [PMID: 33117678 PMCID: PMC7578261 DOI: 10.3389/fonc.2020.537532] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 09/02/2020] [Indexed: 12/29/2022] Open
Abstract
MR imaging (MRI) is now part of the standard work up of patients with rectal cancer. Restaging MRI has been traditionally used to plan the surgical approach. Its role has recently increased and been adopted as a valuable tool to assist the clinical selection of clinical (near) complete responders for organ preserving treatment. Recently several studies have addressed new imaging biomarkers that combined with morphological provides a comprehensive picture of the tumor. Diffusion-weighted MRI (DWI) has entered the clinics and proven useful for response assessment after chemoradiotherapy. Other functional (quantitative) MRI technologies are on the horizon including artificial intelligence modeling. This narrative review provides an overview of recent advances in rectal cancer (re)staging by imaging with a specific focus on response prediction and evaluation of neoadjuvant treatment response. Furthermore, directions are given for future research.
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Affiliation(s)
- Hester E Haak
- Department of Radiology, Netherlands Cancer Institute, Antoni van Leeuwenhoek, Amsterdam, Netherlands.,Department of Surgery, Netherlands Cancer Institute, Antoni van Leeuwenhoek, Amsterdam, Netherlands.,GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, Netherlands
| | - Monique Maas
- Department of Radiology, Netherlands Cancer Institute, Antoni van Leeuwenhoek, Amsterdam, Netherlands
| | - Stefano Trebeschi
- Department of Radiology, Netherlands Cancer Institute, Antoni van Leeuwenhoek, Amsterdam, Netherlands.,GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Antoni van Leeuwenhoek, Amsterdam, Netherlands.,GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, Netherlands.,Department of Regional Health Research, University of Southern Denmark, Odense, Denmark
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33
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Zhu HT, Zhang XY, Shi YJ, Li XT, Sun YS. A Deep Learning Model to Predict the Response to Neoadjuvant Chemoradiotherapy by the Pretreatment Apparent Diffusion Coefficient Images of Locally Advanced Rectal Cancer. Front Oncol 2020; 10:574337. [PMID: 33194680 PMCID: PMC7658629 DOI: 10.3389/fonc.2020.574337] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 10/12/2020] [Indexed: 12/11/2022] Open
Abstract
Background and Purpose Pretreatment prediction of the response to neoadjuvant chemoradiotherapy (NCRT) helps to determine the subsequent plans for the patients with locally advanced rectal cancer (LARC). If the good responders (GR) and non-good responders (non-GR) can be accurately predicted, they can choose to intensify the neoadjuvant chemoradiotherapy to decrease the risk of tumor progression during NCRT and increase the chance of organ preservation. Compared with radiomics methods, deep learning (DL) may adaptively extract features from the images without the need of feature definition. However, DL suffers from limited training samples and signal discrepancy among different scanners. This study aims to construct a DL model to predict GRs by training apparent diffusion coefficient (ADC) images from different scanners. Methods The study retrospectively recruited 700 participants, chronologically divided into a training group (n = 500) and a test group (n = 200). Deep convolutional neural networks were constructed to classify GRs and non-GRs. The networks were designed with a max-pooling layer parallelized by a center-cropping layer to extract features from both the macro and micro scale. ADC images and T2-weighted images were collected at 1.5 Tesla and 3.0 Tesla. The networks were trained by the image patches delineated by radiologists in ADC images and T2-weighted images, respectively. Pathological results were used as the ground truth. The deep learning models were evaluated on the test group and compared with the prediction by mean ADC value. Results Area under curve (AUC) of receiver operating characteristic (ROC) is 0.851 (95% CI: 0.789–0.914) for DL model with ADC images (DL_ADC), significantly larger (P = 0.018, Z = 2.367) than that of mean ADC with AUC = 0.723 (95% CI: 0.637–0.809). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of DL_ADC model are 94.3%, 68.3%, 87.4% and 83.7%, respectively. The DL model with T2-weighted images (DL_T2) produces an AUC of 0.721 (95% CI: 0.640–0.802), significantly (P = 0.000, Z = 3.554) lower than that of DL_ADC model. Conclusion Deep learning model reveals the potential of pretreatment apparent diffusion coefficient images for the prediction of good responders to neoadjuvant chemoradiotherapy.
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Affiliation(s)
- Hai-Tao Zhu
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiao-Yan Zhang
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Yan-Jie Shi
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiao-Ting Li
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
| | - Ying-Shi Sun
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China
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34
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Onal Y, Samanci C. The Role of Diffusion-weighted Imaging in Patients with Gastric Wall Thickening. Curr Med Imaging 2020; 15:965-971. [PMID: 32013813 DOI: 10.2174/1573405614666181115120109] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 10/18/2018] [Accepted: 10/26/2018] [Indexed: 01/20/2023]
Abstract
BACKGROUND Gastric cancer is the second leading cause of cancer death worldwide. AIMS In the benign and malign gastric pathologies, we measured the Apparent Diffusion Coefficient (ADC) value from the thickened section of the stomach wall. We assessed the diagnostic value of ADC and we wanted to see whether this value could be used to diagnose gastric pathologies. STUDY DESIGN This study has a prospective study design. METHODS A total of 90 patients, 27 with malign gastric pathologies 63 with benign gastric pathologies with Gastric Wall (GW) thickening in multidector CT, were evaluated by T2 weighted axial MR imaging and Diffusion-Weighted Imaging (DWI). Measurements were made both from the thickened wall and from the normal GW. Also, a new method called GW/spine ADC ratio was performed in image analysis. The value found after ADC measurement from the GW was proportioned to the spinal cord ADC value in the same section. RESULTS The ADC values measured from the pathological wall in patients with gastric malignancy (1.115 ± 0.156 x10-3 mm2/s) were significantly lower than the healthy wall measurements (1.621 ± 0.292 × 10-3 mm2/s) and benign gastric diseases (1.790± 0.359 x10-3 mm2/s). GW/spine ADC ratio was also lower in gastric malignancy group. CONCLUSION ADC measurement in DWI can be used to distinguish between benign and malign gastric pathologies.
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Affiliation(s)
- Yilmaz Onal
- Department of Radiology, Sultan Abdulhamid Han Training and Research Hospital, Haydarpasa, Istanbul, Turkey
| | - Cesur Samanci
- Department of Radiology, Sultan Abdulhamid Han Training and Research Hospital, Haydarpasa, Istanbul, Turkey
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35
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Abstract
The management of rectal cancer is complex and continually evolving. With advancements in technology and the use of multidisciplinary teams to guide the treatment decision making, staging, oncologic, and functional outcomes are improving, and the management is moving toward personalized treatment strategies to optimize each individual patient's outcomes. Key in this evolution is imaging. Magnetic resonance imaging (MRI) has emerged as the dominant method of pelvic imaging in rectal cancer, and use of MRI for staging is best practice in multiple international guidelines. MRI allows a noninvasive assessment of the tumor site, relationship to surrounding structures, and provides highly accurate rectal cancer staging, which is necessary for determining the appropriate treatment strategy. However, the applications of MRI extend far beyond pretreatment staging. MRI can be used to predict outcomes in locally advanced rectal cancer and guide the surgical or nonsurgical plan, serving as a predictive and prognostic biomarker. With continued MRI hardware improvement and new sequence development, MRI may offer new perspectives in the assessment of treatment response and new innovations that could provide better insight into the staging, restaging, and outcomes with rectal cancer.
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Affiliation(s)
- Deborah S Keller
- Division of Colorectal Surgery, Department of Surgery, Medical University of South Carolina, Charleston, South Carolina
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36
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Attenberger UI, Tavakoli A, Stocker D, Stieb S, Riesterer O, Turina M, Schoenberg SO, Pilz L, Reiner CS. Reduced and standard field-of-view diffusion weighted imaging in patients with rectal cancer at 3 T-Comparison of image quality and apparent diffusion coefficient measurements. Eur J Radiol 2020; 131:109257. [PMID: 32947092 DOI: 10.1016/j.ejrad.2020.109257] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 06/30/2020] [Accepted: 08/24/2020] [Indexed: 01/03/2023]
Abstract
PURPOSE To compare a zoomed EPI-DWI (z-EPI) with a standard EPI-DWI (s-EPI) in the primary diagnostics of rectal cancer and assess its potential of reduced image artifacts. METHOD 22 therapy-naïve patients with rectal cancer underwent rectal MRI at a 3 T-system. The protocols consisted of a z-EPI DWI and s-EPI DWI sequence. Images were assessed by two independent and experienced readers regarding overall image quality and artifacts on a 5-point Likert scale, as well as overall sequence preference. In a lesion-based analysis, tumor and lymph node detection were rated on a 4-point Likert scale. Apparent diffusion coefficient (ADC) measurements were performed. RESULTS Overall Image quality score for z-EPI and s-EPI showed no statistically significant differences (p = 0.80/0.54, reader 1/2) with a median score of 4 ("good" image quality) for both sequences. The image quality preference rank for z-EPI and s-EPI was given the category 'no preference' in 64 % (reader 1) and 50 % (reader 2). Most artifact-related scores (susceptibility, motion and distortion) did not show reproducible significant differences between z-EPI and s-EPI. The two sequences exhibited comparable, mostly good and excellent quality scores for tumor and lymph node detection (p = 0.19-0.99). ADC values were significantly lower for z-EPI than for s-EPI (p = 0.001/0.002, reader 1/2) with good agreement of ADC measurements between both readers. CONCLUSION Our data showed comparable image quality and lesion detection for the z-EPI and the s-EPI sequence in MRI of rectal cancer, whereas the mean ADC of the tumor was significantly lower in z-EPI compared to s-EPI.
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Affiliation(s)
- U I Attenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany.
| | - A Tavakoli
- Department of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Mannheim, Germany; Department of Radiology, German Cancer Research Center (DKFZ), Germany.
| | - D Stocker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.
| | - S Stieb
- Department of Radiation Oncology, University Hospital Zurich, Zurich, Switzerland
| | - O Riesterer
- Department of Radiation Oncology, University Hospital Zurich, Zurich, Switzerland.
| | - M Turina
- Department of Surgery and Transplantation, University Hospital Zurich, Zurich, Switzerland.
| | - S O Schoenberg
- Department of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Mannheim, Germany.
| | - L Pilz
- Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
| | - C S Reiner
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.
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37
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Sauter AP, Kössinger A, Beck S, Deniffel D, Dapper H, Combs SE, Rummeny EJ, Pfeiffer D. Dual-energy CT parameters in correlation to MRI-based apparent diffusion coefficient: evaluation in rectal cancer after radiochemotherapy. Acta Radiol Open 2020; 9:2058460120945316. [PMID: 32995044 PMCID: PMC7503032 DOI: 10.1177/2058460120945316] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 07/03/2020] [Indexed: 01/04/2023] Open
Abstract
Background Rectal cancer (RC) is a frequent malignancy for which magnetic resonance imaging (MRI) is the most common and accurate imaging. Iodine concentration (IC) can be quantified with spectral dual-layer computed tomography CT (DL-CT), which could improve imaging of RC, especially for evaluation of response to radiochemotherapy (RCT). Purpose To compare a DL-CT system to MRI as the non-invasive imaging gold standard for imaging of RC to evaluate the possibility of a response evaluation with DL-CT. Material and Methods Eleven patients who received DL-CT as well as MRI before and after RCT of RC were retrospectively included into this study. For each examination, a region of interest (ROI) was placed within the tumor. For MRI, the mean apparent diffusion coefficient (ADC) was assessed. For DL-CT, IC, z-effective, and Hounsfield Units (HU) were measured. IC, z-effective, and HU were normalized to the aorta. ADC was correlated to absolute and relative normalized IC, z-effective, and HU with Spearman’s ρ. Differences before and after treatment were tested with Wilcoxon signed-rank test. Results HU, IC, and Z-effective values in DL-CT images decreased significantly after RCT (P<0.01 for each comparison). The mean ADC increased significantly after RCT. Spearman’s ρ of the absolute IC difference and the absolute ADC (both before and after RCT) is high and significant (ρ = 0.73; P = 0.01), whereas the ρ-value for z-effective (ρ = 0.56) or HU (ρ = 0.45) to ADC was lower and non-significant. Conclusion Response evaluation of RC after RCT could be possible with DL-CT via the measurement of IC.
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Affiliation(s)
- Andreas P Sauter
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Antonia Kössinger
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Stefanie Beck
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Dominik Deniffel
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Hendrik Dapper
- Department of Radiation Oncology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany.,Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, Neuherberg, Germany.,Deutsches Konsortium für Translationale Krebsforschung (dktk), Partner Site Munich, Munich, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany.,Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, Neuherberg, Germany.,Deutsches Konsortium für Translationale Krebsforschung (dktk), Partner Site Munich, Munich, Germany
| | - Ernst J Rummeny
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Daniela Pfeiffer
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
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38
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Maffazzioli L, Zilio MB, Klamt AL, Duarte JA, Mazzini GS, Campos VJ, Chedid MF, Gurski RR. ADC as a predictor of pathologic response to neoadjuvant therapy in esophageal cancer: a systematic review and meta-analysis. Eur Radiol 2020; 30:3934-3942. [PMID: 32157409 DOI: 10.1007/s00330-020-06723-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 01/31/2020] [Accepted: 02/05/2020] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Diffusion-weighted magnetic resonance imaging (DWI) is part of clinical practice. The aim of this study was to evaluate the role of apparent diffusion coefficient (ADC) as a predictor of pathologic response to neoadjuvant therapy (nCRT) in patients with esophageal cancer (EC). METHODS The MEDLINE, Embase, and Google Scholar databases were systematically searched for studies using ADC to evaluate response to neoadjuvant therapy in patients with EC. Methodological quality of the studies was evaluated with the QUADAS tool. Data from eligible studies were extracted and evaluated by two independent reviewers. Meta-analyses were performed comparing mean ADC values between responders and non-responders to nCRT in three different scenarios: baseline (BL) absolute values; percent change between intermediate (IM) values and BL; and percent change between final follow-up (FU) value and baseline BL. RESULTS Seven studies (n = 158 patients) were included. Responders exhibited a statistically significant percent increase in ADC during nCRT (mean difference [MD] 21.06%, 95%CI = 13.04-29.09; I2 = 49%; p = 0.12). A similar increase was identified in the complete pathologic response (pCR) versus non-complete pathologic response (npCR) subgroup (MD = 25.68%, 95%CI = 18.87-32.48; I2 = 0%; p = 0.60). At the end of treatment, responders also exhibited a statistically significant percent increase in ADC (MD = 22.49%, 95%CI = 9.94-35.05; I2 = 0%; p = 0.46). BL ADC was not associated with any definition of pathologic response (MD = 0.11%, 95%CI = - 0.21-0.42; I2 = 85%; p < 0.01). CONCLUSION These results suggest that ADC can be used as a predictor of pathologic response, with a statistically significant association between percent ADC increase during and after treatment and pCR. ADC may serve as a tool to help in guiding clinical decisions. KEY POINTS • DWI is routinely included in MRI oncological protocols. • ADC can be used as a predictor of pathologic response, with a statistically significant association between percent ADC increase during and after treatment and pCR.
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Affiliation(s)
- Leticia Maffazzioli
- Division of Radiology, Hospital de Clinicas de Porto Alegre, Federal University of Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos 2350, 2nd Floor, Porto Alegre, 90035-903, Brazil.
- Post-Graduation Program in Medicine: Surgical Sciences, Medical School of UFRGS, Porto Alegre, Brazil.
| | - Mariana B Zilio
- Post-Graduation Program in Medicine: Surgical Sciences, Medical School of UFRGS, Porto Alegre, Brazil
- Division of Gastrointestinal Surgery, Hospital de Clínicas de Porto Alegre (HCPA), Medical School of UFRGS, Porto Alegre, Brazil
| | - Alexandre L Klamt
- Post-Graduation Program in Medicine: Surgical Sciences, Medical School of UFRGS, Porto Alegre, Brazil
- Division of Gastroenterology, Hospital de Clínicas de Porto Alegre (HCPA), Medical School of UFRGS, Porto Alegre, Brazil
| | - Juliana A Duarte
- Division of Radiology, Hospital de Clinicas de Porto Alegre, Federal University of Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos 2350, 2nd Floor, Porto Alegre, 90035-903, Brazil
| | - Guilherme S Mazzini
- Division of Gastrointestinal Surgery, Hospital de Clínicas de Porto Alegre (HCPA), Medical School of UFRGS, Porto Alegre, Brazil
| | - Vinicius J Campos
- Post-Graduation Program in Medicine: Surgical Sciences, Medical School of UFRGS, Porto Alegre, Brazil
| | - Marcio F Chedid
- Post-Graduation Program in Medicine: Surgical Sciences, Medical School of UFRGS, Porto Alegre, Brazil
- Division of Gastrointestinal Surgery, Hospital de Clínicas de Porto Alegre (HCPA), Medical School of UFRGS, Porto Alegre, Brazil
| | - Richard R Gurski
- Post-Graduation Program in Medicine: Surgical Sciences, Medical School of UFRGS, Porto Alegre, Brazil
- Division of Gastrointestinal Surgery, Hospital de Clínicas de Porto Alegre (HCPA), Medical School of UFRGS, Porto Alegre, Brazil
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Shayesteh SP, Alikhassi A, Farhan F, Gahletaki R, Soltanabadi M, Haddad P, Bitarafan-Rajabi A. Prediction of Response to Neoadjuvant Chemoradiotherapy by MRI-Based Machine Learning Texture Analysis in Rectal Cancer Patients. J Gastrointest Cancer 2020; 51:601-609. [PMID: 31456114 PMCID: PMC7205769 DOI: 10.1007/s12029-019-00291-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection is the standard treatment for locally advanced rectal cancer (LARC). Radiomics can be used as noninvasive biomarker for prediction of response to therapy. The main aim of this study was to evaluate the association of MRI texture features of LARC with nCRT response and the effect of Laplacian of Gaussian (LoG) filter and feature selection algorithm in prediction process improvement. METHODS All patients underwent MRI with a 3T clinical scanner, 1 week before nCRT. For each patient, intensity, shape, and texture-based features were derived from MRI images with LoG filter using the IBEX software and without preprocessing. We identified responder from a non-responder group using 9 machine learning classifiers. Then, the effect of preprocessing LoG filters with 0.5, 1 and 1.5 value on these classification algorithms' performance was investigated. Eventually, classification algorithm's results were compared in different feature selection methods. RESULT Sixty-seven patients with LARC were included in the study. Patients' nCRT responses included 11 patients with Grade 0, 19 with Grade 1, 26 with Grade 2, and 11 with Grade 3 according to AJCC/CAP pathologic grading. In MR Images which were not preprocessed, the best performance was for Ada boost classifier (AUC = 74.8) with T2W MR Images. In T1W MR Images, the best performance was for aba boost classifier (AUC = 78.1) with a σ = 1 preprocessing LoG filter. In T2W MR Images, the best performance was for naive Bayesian network classifier (AUC = 85.1) with a σ = 0.5 preprocessing LoG filter. Also, performance of machine learning models with CfsSubsetEval (CF SUB E) feature selection algorithm was better than others. CONCLUSION Machine learning can be used as a response predictor model in LARC patients, but its performance should be improved. A preprocessing LoG filter can improve the machine learning methods performance and at the end, the effect of feature selection algorithm on model's performance is clear.
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Affiliation(s)
- Sajad P. Shayesteh
- Department of Physiology, Pharmacology and Medical Physics, Faculty of Medicine, Alborz University of Medical Sciences, Karaj, Iran
| | - Afsaneh Alikhassi
- Department of Radiology, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran
| | - Farshid Farhan
- Radiation Oncology Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
- Radiation Oncology Department, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Reza Gahletaki
- Radiation Oncology Department, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Masume Soltanabadi
- Department of Nuclear Medicine, Faculty of Medicine, Shahrekord University of Medical Sciences, Shahrekord, Chaharmahal and Bakhtiari Iran
| | - Peiman Haddad
- Radiation Oncology Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
- Radiation Oncology Department, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmad Bitarafan-Rajabi
- Cardiovascular Intervention Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
- Echocardiography Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
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40
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Survival Benefit for Metformin Through Better Tumor Response by Neoadjuvant Concurrent Chemoradiotherapy in Rectal Cancer. Dis Colon Rectum 2020; 63:758-768. [PMID: 32384406 DOI: 10.1097/dcr.0000000000001624] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND Metformin may reduce cancer risk and mortality and improve radiotherapy responses in several malignancies. OBJECTIVE This study aimed to compare tumor responses and prognoses of metformin and nonmetformin groups of diabetic patients receiving neoadjuvant concurrent chemoradiotherapy for rectal cancer. DESIGN This is a retrospective study. SETTING This study was conducted at a single institution in the Republic of Korea. PATIENTS Between January 2000 and November 2017, 104 patients with rectal cancer who were taking diabetes medication and treated with neoadjuvant concurrent chemoradiotherapy followed by radical surgery were reviewed. Patients were divided into those taking (n = 62) and not taking metformin (n = 42). Tumor responses, survival, and other outcomes were analyzed. MAIN OUTCOME MEASURES Tumor response, rectal cancer-specific survival, and disease-free survival rates were measured. RESULTS Tumor regression grade (p = 0.002), pathological complete response (p = 0.037), and N downstaging (p < 0.001) after neoadjuvant concurrent chemoradiotherapy were significantly higher in the metformin group than in the nonmetformin group. In analysis of cancer-specific mortality, metformin use, differentiation (well, moderate vs poor), pathological Union for International Cancer Control stage (3 vs 1-2), ypN stage (1-2 vs 0), and N downstaging (HR, 0.256 (95% CI, 0.082-0.794), p = 0.018; HR, 0.147 (95% CI, 0.031-0.697), p = 0.016; HR, 3.693 (95% CI, 1.283-10.635), p = 0.015; HR, 3.181 (95% CI, 1.155-8.759), p = 0.025, and HR, 0.175 (95% CI, 0.040-0.769), p = 0.021) were significant factors related to mortality in diabetic patients with rectal cancer. In addition, in the multivariate analysis of cancer recurrence, the interaction between metformin use and lymph node downstaging was a significant predictive factor (HR, 0.222 (95% CI, 0.077-0.639); p = 0.005). LIMITATIONS This was a small retrospective study conducted at a single institution. CONCLUSIONS Metformin use was associated with better tumor responses and cancer-specific survival, as well as a lower risk of cancer recurrence, in patients with diabetes mellitus who had lymph node downstaging after neoadjuvant concurrent chemoradiotherapy in rectal cancer. See Video Abstract at http://links.lww.com/DCR/B185. BENEFICIO EN SUPERVIVENCIA CON METFORMINA A TRAVÉS DE UNA MEJOR RESPUESTA TUMORAL CON QUIMIORRADIOTERAPIA CONCURRENTE NEOADYUVANTE EN CÁNCER RECTAL: La metformina puede reducir el riesgo de cáncer y la mortalidad y mejorar las respuestas a la radioterapia en varios tumores malignos.Comparar las respuestas tumorales y los pronósticos de los grupos con metformina y sin metformina de pacientes diabéticos que reciben quimiorradioterapia concurrente neoadyuvante para cáncer de recto.Estudio retrospectivo.Institución única en la República de Corea.Se revisaron 104 pacientes entre enero de 2000 y noviembre de 2017, con cáncer rectal que tomaban medicamentos para diabetes y que fueron tratados con quimiorradioterapia concurrente neoadyuvante seguida de cirugía radical. Los pacientes se dividieron en aquellos que tomaban (n = 62) y los que no tomaban metformina (n = 42). Se analizaron las respuestas tumorales, la supervivencia y otros resultados.Se midieron las tasas de la respuesta tumoral, la supervivencia específica de cáncer rectal y de la supervivencia libre de enfermedad.El grado de regresión tumoral (p = 0.002), la remisión patológica completa (p = 0.037) y la reducción de la etapa N (p < 0.001) después de la quimiorradioterapia concurrente neoadyuvante fueron significativamente mayores en el grupo de metformina que en el grupo sin metformina. En el análisis de la mortalidad específica por cáncer, el uso de metformina, la diferenciación (bien, moderada vs pobre), el estadio patológico UICC (3 vs 1-2), el estadio ypN (1-2 vs 0) y la disminución de la etapa N (hazard ratios [intervalos de confianza 95%]: 0.256 [0.082-0.794], p = 0.018; 0.147 [0.031-0.697], p = 0.016; 3.693 [1.283-10.635], p = 0.015; 3.181 [1.155-8.759], p = 0.025 y 0.175 [0.040-0.769], p = 0.021, respectivamente) fueron factores significativos relacionados con la mortalidad en pacientes diabéticos con cáncer rectal. Adicionalmente, en el análisis multivariado de la recurrencia del cáncer, la interacción entre el uso de metformina y la disminución de la etapa ganglionar (N) fue un factor predictivo significativo (hazard ratios [intervalos de confianza del 95%]: 0.222 [0.077-0.639]; p = 0.005).Este fue un estudio retrospectivo pequeño realizado en un solo instituto.El uso de metformina se asoció con mejores respuestas tumorales y supervivencia específica de cáncer, así como un menor riesgo de recurrencia del cáncer, en pacientes con disminución de la etapa ganglionar (N) después de quimiorradioterapia concurrente neoadyuvante en pacientes con cáncer rectal y diabetes. Consulte Video Resumen en http://links.lww.com/DCR/B185. (Traducción-Dr. Jorge Silva Velazco).
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Peng Y, Xu C, Hu X, Shen Y, Hu D, Kamel I, Li Z. Reduced Field-of-View Diffusion-Weighted Imaging in Histological Characterization of Rectal Cancer: Impact of Different Region-of-Interest Positioning Protocols on Apparent Diffusion Coefficient Measurements. Eur J Radiol 2020; 127:109028. [DOI: 10.1016/j.ejrad.2020.109028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 03/11/2020] [Accepted: 04/14/2020] [Indexed: 01/21/2023]
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Zhang XY, Wang L, Zhu HT, Li ZW, Ye M, Li XT, Shi YJ, Zhu HC, Sun YS. Predicting Rectal Cancer Response to Neoadjuvant Chemoradiotherapy Using Deep Learning of Diffusion Kurtosis MRI. Radiology 2020; 296:56-64. [PMID: 32315264 DOI: 10.1148/radiol.2020190936] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background Preoperative response evaluation with neoadjuvant chemoradiotherapy remains a challenge in the setting of locally advanced rectal cancer. Recently, deep learning (DL) has been widely used in tumor diagnosis and treatment and has produced exciting results. Purpose To develop and validate a DL method to predict response of rectal cancer to neoadjuvant therapy based on diffusion kurtosis and T2-weighted MRI. Materials and Methods In this prospective study, participants with locally advanced rectal adenocarcinoma (≥cT3 or N+) proved at histopathology and baseline MRI who were scheduled to undergo preoperative chemoradiotherapy were enrolled from October 2015 to December 2017 and were chronologically divided into 308 training samples and 104 test samples. DL models were constructed primarily to predict pathologic complete response (pCR) and secondarily to assess tumor regression grade (TRG) (TRG0 and TRG1 vs TRG2 and TRG3) and T downstaging. Other analysis included comparisons of diffusion kurtosis MRI parameters and subjective evaluation by radiologists. Results A total of 383 participants (mean age, 57 years ± 10 [standard deviation]; 229 men) were evaluated (290 in the training cohort, 93 in the test cohort). The area under the receiver operating characteristic curve (AUC) was 0.99 for the pCR model in the test cohort, which was higher than the AUC for raters 1 and 2 (0.66 and 0.72, respectively; P < .001 for both). AUC for the DL model was 0.70 for TRG and 0.79 for T downstaging. AUC for pCR with the DL model was better than AUC for the best-performing diffusion kurtosis MRI parameters alone (diffusion coefficient in normal diffusion after correcting the non-Gaussian effect [Dapp value] before neoadjuvant therapy, AUC = 0.76). Subjective evaluation by radiologists yielded a higher error rate (1 - accuracy) (25 of 93 [26.9%] and 23 of 93 [24.8%] for raters 1 and 2, respectively) in predicting pCR than did evaluation with the DL model (two of 93 [2.2%]); the radiologists achieved a lower error rate (12 of 93 [12.9%] and 13 of 93 [14.0%] for raters 1 and 2, respectively) when assisted by the DL model. Conclusion A deep learning model based on diffusion kurtosis MRI showed good performance for predicting pathologic complete response and aided the radiologist in assessing response of locally advanced rectal cancer after neoadjuvant chemoradiotherapy. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Koh in this issue.
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Affiliation(s)
- Xiao-Yan Zhang
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
| | - Lin Wang
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
| | - Hai-Tao Zhu
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
| | - Zhong-Wu Li
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
| | - Meng Ye
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
| | - Xiao-Ting Li
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
| | - Yan-Jie Shi
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
| | - Hui-Ci Zhu
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
| | - Ying-Shi Sun
- From the Departments of Radiology (X.Y.Z., H.T.Z., M.Y., X.T.L., Y.J.S., H.C.Z., Y.S.S.), Gastrointestinal Surgery (L.W.), and Pathology (Z.W.L.), Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing 100142, China
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Improved Liver Diffusion-Weighted Imaging at 3 T Using Respiratory Triggering in Combination With Simultaneous Multislice Acceleration. Invest Radiol 2020; 54:744-751. [PMID: 31335634 DOI: 10.1097/rli.0000000000000594] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVES The aim of this study was to retrospectively compare optimized respiratory-triggered diffusion-weighted imaging with simultaneous multislice acceleration (SMS-RT-DWI) of the liver with a standard free-breathing echo-planar DWI (s-DWI) protocol at 3 T with respect to the imaging artifacts inherent to DWI. MATERIALS AND METHODS Fifty-two patients who underwent a magnetic resonance imaging study of the liver were included in this retrospective study. Examinations were performed on a 3 T whole-body magnetic resonance system (MAGNETOM Skyra; Siemens Healthcare, Erlangen, Germany). In all patients, both s-DWI and SMS-RT-DWI of the liver were obtained. Images were qualitatively evaluated by 2 independent radiologists with regard to overall image quality, liver edge sharpness, sequence-related artifacts, and overall scan preference. For quantitative evaluation, signal-to-noise ratio was measured from signal-to-noise ratio maps. The mean apparent diffusion coefficient (ADC) was measured in each liver quadrant. The Wilcoxon rank-sum test was used for analysis of the qualitative parameters and the paired Student t test for quantitative parameters. RESULTS Overall image quality, liver edge sharpness, and sequence-related artifacts of SMS-RT-DWI received significantly better ratings compared with s-DWI (P < 0.05 for all). For 90.4% of the examinations, both readers overall preferred SMS-RT-DWI to s-DWI. Acquisition time for SMS-RT-DWI was 34% faster than s-DWI. Signal-to-noise ratio values were significantly higher for s-DWI at b50 but did not statistically differ at b800, and they were more homogenous for SMS-RT-DWI, with a significantly lower standard deviation at b50. Mean ADC values decreased from the left to right hepatic lobe as well as from cranial to caudal for s-DWI. With SMS-RT-DWI, mean ADC values were homogeneous throughout the liver. CONCLUSIONS Optimized, multislice, respiratory-triggered DWI of the liver at 3 T substantially improves image quality with a reduced scan acquisition time compared with s-DWI.
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Intravoxel incoherent motion magnetic resonance imaging for predicting the long-term efficacy of immune checkpoint inhibitors in patients with non-small-cell lung cancer. Lung Cancer 2020; 143:47-54. [PMID: 32203770 DOI: 10.1016/j.lungcan.2020.03.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 02/26/2020] [Accepted: 03/13/2020] [Indexed: 01/18/2023]
Abstract
OBJECTIVES Conventional evaluation of anti-tumor activity on the basis of tumor size is inadequate for immune checkpoint inhibitors (ICIs). We therefore aimed to assess the usefulness of intravoxel incoherent motion magnetic resonance imaging (IVIM-MRI) for evaluation of the therapeutic efficacy of ICIs. MATERIALS AND METHODS A chest IVIM-MRI was performed before and 2, 4, and 8 weeks after administration of ICIs in patients with advanced non-small-cell lung cancer. Apparent diffusion coefficient (ADC), skewness of ADC (ADCskew), kurtosis of ADC (ADCkurt), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were evaluated at each evaluation point and changes from the baseline (Δ). RESULTS Twenty patients were enrolled in this study. An increased ADC 8 weeks and decreased ADCkurt and ΔADCkurt 4 weeks after ICIs was associated with objective responses and longer progression-free survival (PFS). A decreased ΔADCskew at 4 weeks was associated with objective responses, disease control, and longer PFS and overall survival. There was no correlation between the efficacy of ICIs and D, D* and f. All of three patients who had pseudoprogression had decreased ΔADCskew at 4 weeks and two of them had decreased ΔADCkurt at 4 weeks. Inversely, all five patients who had progressive disease (PD) did not have increased ΔADCskew at 4 weeks and only one of them had decreased ΔADCkurt at 4 weeks. CONCLUSIONS Changes in histograms of ADC may be useful for predicting long-term efficacy and distinguishing between pseudoprogression and actual PD after ICIs.
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Tchelebi LT, Romesser PB, Feuerlein S, Hoffe S, Latifi K, Felder S, Chuong MD. Magnetic Resonance Guided Radiotherapy for Rectal Cancer: Expanding Opportunities for Non-Operative Management. Cancer Control 2020; 27:1073274820969449. [PMID: 33118384 PMCID: PMC7791447 DOI: 10.1177/1073274820969449] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Colorectal cancer is the third most common cancer in men and the second most common in women worldwide, and the incidence is increasing among younger patients. 30% of these malignancies arise in the rectum. Patients with rectal cancer have historically been managed with preoperative radiation, followed by radical surgery, and adjuvant chemotherapy, with permanent colostomies in up to 20% of patients. Beginning in the early 2000s, non-operative management (NOM) of rectal cancer emerged as a viable alternative to radical surgery in select patients. Efforts have been ongoing to optimize neoadjuvant therapy for rectal cancer, thereby increasing the number of patients potentially eligible to forgo radical surgery. Magnetic resonance guided radiotherapy (MRgRT) has recently emerged as a treatment modality capable of intensifying preoperative radiation therapy for rectal cancer patients. This technology may also predict which patients will achieve a complete response to preoperative therapy, thereby allowing for more appropriate selection of patients for NOM. The present work seeks to illustrate the potential role MRgRT could play in personalizing rectal cancer treatment thus expanding the role of NOM in rectal cancer.
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Affiliation(s)
- Leila T. Tchelebi
- Department of Radiation Oncology, Penn State College of Medicine,
Hershey, PA, USA
| | - Paul B. Romesser
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer
Center, New York, NY, USA
| | - Sebastian Feuerlein
- Department of Diagnostic Imaging and Interventional Radiology,
Moffitt Cancer Center, Tampa, FL, USA
| | - Sarah Hoffe
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL,
USA
| | - Kujtim Latifi
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL,
USA
| | - Seth Felder
- Department of Gastrointestinal Oncology, Moffitt Cancer Center,
Tampa, FL, USA
| | - Michael D. Chuong
- Department of Radiation Oncology, Miami Cancer Institute, Miami, FL,
USA
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Bologna M, Corino VDA, Montin E, Messina A, Calareso G, Greco FG, Sdao S, Mainardi LT. Assessment of Stability and Discrimination Capacity of Radiomic Features on Apparent Diffusion Coefficient Images. J Digit Imaging 2019; 31:879-894. [PMID: 29725965 PMCID: PMC6261192 DOI: 10.1007/s10278-018-0092-9] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
The objectives of the study are to develop a new way to assess stability and discrimination capacity of radiomic features without the need of test-retest or multiple delineations and to use information obtained to perform a preliminary feature selection. Apparent diffusion coefficient (ADC) maps were computed from diffusion-weighted magnetic resonance images (DW-MRI) of two groups of patients: 18 with soft tissue sarcomas (STS) and 18 with oropharyngeal cancers (OPC). Sixty-nine radiomic features were computed, using three different histogram discretizations (16, 32, and 64 bins). Geometrical transformations (translations) of increasing entity were applied to the regions of interest (ROIs), and the intra-class correlation coefficient (ICC) was used to compare the features computed on the original and modified ROIs. The distribution of ICC values for minimal and maximal entity translations (ICC10 and ICC100, respectively) was used to adjust thresholds of ICC (ICCmin and ICCmax) used to discriminate between good, unstable (ICC10 < ICCmin), and non-discriminative features (ICC100 > ICCmax). Fifty-four and 59 radiomic features passed the stability-based selection for all the three histogram discretizations for the OPC and STS datasets, respectively. The excluded features were similar across the different histogram discretizations (Jaccard’s index 0.77 ± 0.13 and 0.9 ± 0.1 for OPC and STS, respectively) but different between datasets (Jaccard’s index 0.19 ± 0.02). The results suggest that the observed radiomic features are mainly stable and discriminative, but the stability depends on the region of the body under observation. The method provides a way to assess stability without the need of test-retest or multiple delineations.
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Affiliation(s)
- Marco Bologna
- Departement of Electronics, Information and Bioengineering, Milan, Italy.
| | | | - Eros Montin
- Departement of Electronics, Information and Bioengineering, Milan, Italy
| | | | | | | | - Silvana Sdao
- Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Luca T Mainardi
- Departement of Electronics, Information and Bioengineering, Milan, Italy
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Hall WA, Paulson ES, van der Heide UA, Fuller CD, Raaymakers BW, Lagendijk JJW, Li XA, Jaffray DA, Dawson LA, Erickson B, Verheij M, Harrington KJ, Sahgal A, Lee P, Parikh PJ, Bassetti MF, Robinson CG, Minsky BD, Choudhury A, Tersteeg RJHA, Schultz CJ. The transformation of radiation oncology using real-time magnetic resonance guidance: A review. Eur J Cancer 2019; 122:42-52. [PMID: 31614288 PMCID: PMC8447225 DOI: 10.1016/j.ejca.2019.07.021] [Citation(s) in RCA: 139] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 07/11/2019] [Accepted: 07/16/2019] [Indexed: 12/11/2022]
Abstract
Radiation therapy (RT) is an essential component of effective cancer care and is used across nearly all cancer types. The delivery of RT is becoming more precise through rapid advances in both computing and imaging. The direct integration of magnetic resonance imaging (MRI) with linear accelerators represents an exciting development with the potential to dramatically impact cancer research and treatment. These impacts extend beyond improved imaging and dose deposition. Real-time MRI-guided RT is actively transforming the work flows and capabilities of virtually every aspect of RT. It has the opportunity to change entirely the delivery methods and response assessments of numerous malignancies. This review intends to approach the topic of MRI-based RT guidance from a vendor neutral and international perspective. It also aims to provide an introduction to this topic targeted towards oncologists without a speciality focus in RT. Speciality implications, areas for physician education and research opportunities are identified as they are associated with MRI-guided RT. The uniquely disruptive implications of MRI-guided RT are discussed and placed in context. We further aim to describe and outline important future changes to the speciality of radiation oncology that will occur with MRI-guided RT. The impacts on RT caused by MRI guidance include target identification, RT planning, quality assurance, treatment delivery, training, clinical workflow, tumour response assessment and treatment scheduling. In addition, entirely novel research areas that may be enabled by MRI guidance are identified for future investigation.
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Affiliation(s)
- William A Hall
- Medical College of Wisconsin, Department of Radiation Oncology, USA.
| | - Eric S Paulson
- Medical College of Wisconsin, Department of Radiation Oncology, USA
| | | | - Clifton D Fuller
- University of Texas, MD Anderson Cancer Center, USA; Netherlands Cancer Institute, the Netherlands
| | - B W Raaymakers
- UMC Utrecht, Department of Radiotherapy, the Netherlands
| | | | - X Allen Li
- Medical College of Wisconsin, Department of Radiation Oncology, USA
| | - David A Jaffray
- Princess Margaret Cancer Centre, University of Toronto, Canada
| | - Laura A Dawson
- Princess Margaret Cancer Centre, University of Toronto, Canada
| | - Beth Erickson
- Medical College of Wisconsin, Department of Radiation Oncology, USA
| | - Marcel Verheij
- Radbound University Medical Center, Nijmegen, the Netherlands
| | - Kevin J Harrington
- The Institute of Cancer Research, The Royal Marsden NHS Foundation Trust, UK
| | - Arjun Sahgal
- Sunnybrook Health Sciences Centre, University of Toronto, Canada
| | - Percy Lee
- University of California, Los Angeles, USA
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Li Y, Liu W, Pei Q, Zhao L, Güngör C, Zhu H, Song X, Li C, Zhou Z, Xu Y, Wang D, Tan F, Yang P, Pei H. Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer. Cancer Med 2019; 8:7244-7252. [PMID: 31642204 PMCID: PMC6885895 DOI: 10.1002/cam4.2636] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 09/01/2019] [Accepted: 10/07/2019] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Total mesorectal excision following neoadjuvant chemoradiotherapy (nCRT) is recommended in the latest treatment of locally advanced rectal cancer (LARC). OBJECTIVE To predict whether patients with LARC can achieve pathologic complete response (pCR), comparing MRI-based radiomics between before and after neoadjuvant radiotherapy (nRT) was performed. METHODS One hundred and sixty-five MRI-based radiomics features in axial T2-weighted images were obtained quantitatively from Imaging Biomarker Explorer Software. The specific features of conventional and developing radiomics were selected with the analysis of least absolute shrinkage and selection operator logistic regression, of which the predictive performance was analyzed with receiver operating curve and calibration curve, and applied to an independent cohort. RESULTS One hundred and thirty-one target patients were enrolled in the present study. A radiomics signature founded on seven radiomics features was generated in the primary cohort. A remarkable difference about Rad-score between pCR and non-pCR group occurred in both of primary (P < .001) or validation cohorts (P < .001). The value of area under the curves was 0.92 (95% CI, 0.86-0.99) and 0.87 (95% CI, 0.74-1.00) in the primary and validation cohorts, respectively. The Rad-score (OR = 23.581; P < .001) from multivariate logistic regression analysis was significant as an independent factor of pCR. CONCLUSION Our predictive model based on radiomics features was an independent predictor for pCR in LARC and could be a candidate in clinical practice.
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Affiliation(s)
- Yuqiang Li
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China.,Department of General Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Wenxue Liu
- Department of Rheumatology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,Department of Cardiology, Xiangya Hospital, Central South University, Changsha, China
| | - Qian Pei
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Lilan Zhao
- Department of Thoracic surgery, Fujian Provincial Hospital, Fuzhou, China
| | - Cenap Güngör
- Department of General Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hong Zhu
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiangping Song
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Chenglong Li
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Zhongyi Zhou
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Yang Xu
- Department of General Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Dan Wang
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Fengbo Tan
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Pei Yang
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China.,Department of Oncology, Hunan Cancer Hospital, Changsha, China
| | - Haiping Pei
- Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
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Mainenti PP, Stanzione A, Guarino S, Romeo V, Ugga L, Romano F, Storto G, Maurea S, Brunetti A. Colorectal cancer: Parametric evaluation of morphological, functional and molecular tomographic imaging. World J Gastroenterol 2019; 25:5233-5256. [PMID: 31558870 PMCID: PMC6761241 DOI: 10.3748/wjg.v25.i35.5233] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 08/06/2019] [Accepted: 08/24/2019] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer (CRC) represents one of the leading causes of tumor-related deaths worldwide. Among the various tools at physicians' disposal for the diagnostic management of the disease, tomographic imaging (e.g., CT, MRI, and hybrid PET imaging) is considered essential. The qualitative and subjective evaluation of tomographic images is the main approach used to obtain valuable clinical information, although this strategy suffers from both intrinsic and operator-dependent limitations. More recently, advanced imaging techniques have been developed with the aim of overcoming these issues. Such techniques, such as diffusion-weighted MRI and perfusion imaging, were designed for the "in vivo" evaluation of specific biological tissue features in order to describe them in terms of quantitative parameters, which could answer questions difficult to address with conventional imaging alone (e.g., questions related to tissue characterization and prognosis). Furthermore, it has been observed that a large amount of numerical and statistical information is buried inside tomographic images, resulting in their invisibility during conventional assessment. This information can be extracted and represented in terms of quantitative parameters through different processes (e.g., texture analysis). Numerous researchers have focused their work on the significance of these quantitative imaging parameters for the management of CRC patients. In this review, we aimed to focus on evidence reported in the academic literature regarding the application of parametric imaging to the diagnosis, staging and prognosis of CRC while discussing future perspectives and present limitations. While the transition from purely anatomical to quantitative tomographic imaging appears achievable for CRC diagnostics, some essential milestones, such as scanning and analysis standardization and the definition of robust cut-off values, must be achieved before quantitative tomographic imaging can be incorporated into daily clinical practice.
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Affiliation(s)
- Pier Paolo Mainenti
- Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples 80145, Italy
| | - Arnaldo Stanzione
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Salvatore Guarino
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Valeria Romeo
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Lorenzo Ugga
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Federica Romano
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Giovanni Storto
- IRCCS-CROB, Referral Cancer Center of Basilicata, Rionero in Vulture 85028, Italy
| | - Simone Maurea
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Arturo Brunetti
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
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Chiloiro G, Boldrini L, Meldolesi E, Re A, Cellini F, Cusumano D, Corvari B, Mantini G, Balducci M, Valentini V, Gambacorta MA. MR-guided radiotherapy in rectal cancer: First clinical experience of an innovative technology. Clin Transl Radiat Oncol 2019; 18:80-86. [PMID: 31341981 PMCID: PMC6630154 DOI: 10.1016/j.ctro.2019.04.006] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2019] [Revised: 04/03/2019] [Accepted: 04/05/2019] [Indexed: 12/15/2022] Open
Abstract
•This study represents one of the first reports of online MRgRT.•Integrated Low-field MR provides better anatomical visualization than CBCT or MVCT.•Better visualization of the target can help to reduce the margins from CTV to PTV.•MRgRT appears a feasible option in rectal cancer treatment offering potential benefits.•MRgRT represents a promising technology for rectal cancer management.
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Affiliation(s)
- Giuditta Chiloiro
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
| | - Luca Boldrini
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
| | - Elisa Meldolesi
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
| | - Alessia Re
- Unità di Radioterapia Oncologica, Fondazione di Ricerca e Cura Giovanni Paolo II, Università Cattolica del Sacro Cuore, Campobasso, Italy
| | - Francesco Cellini
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
| | - Davide Cusumano
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Fisica Sanitaria, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
| | - Barbara Corvari
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
| | - Giovanna Mantini
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
- Università Cattolica del Sacro Cuore, Istituto di Radiologia, Roma, Italy
| | - Mario Balducci
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
- Università Cattolica del Sacro Cuore, Istituto di Radiologia, Roma, Italy
| | - Vincenzo Valentini
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
- Università Cattolica del Sacro Cuore, Istituto di Radiologia, Roma, Italy
| | - Maria Antonietta Gambacorta
- Fondazione Policlinico Universitario “A. Gemelli” IRCCS, UOC di Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Roma, Italy
- Università Cattolica del Sacro Cuore, Istituto di Radiologia, Roma, Italy
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