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Li H, Zhang J, Liu B, Zheng Z, Xu Y. Histogram analysis of multiple mathematical diffusion-weighted imaging models for preoperative prediction of Ki-67 expression in hepatocellular carcinoma. Front Oncol 2025; 15:1531236. [PMID: 40134596 PMCID: PMC11932891 DOI: 10.3389/fonc.2025.1531236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Accepted: 02/19/2025] [Indexed: 03/27/2025] Open
Abstract
Objective To explore whether a combination of clinico-radiological factors and histogram parameters based on monoexponential, biexponential, and stretched exponential models derived from the whole-tumor volume on diffusion-weighted imaging (DWI) could predict Ki-67 expression in hepatocellular carcinoma(HCC). Materials and Methods Histogram parameters based on whole-tumor volumes were derived from monoexponential model, biexponential model, and stretched exponential model. Histogram parameters were compared between HCCs with high and low Ki-67 expression. Multivariate logistic regression and receiver operating characteristic curves were used to assess the ability to predict Ki-67 expression (expression index ≤ 20% vs. >20%). Results In the training and test set, the 5th percentile of distributed diffusion coefficient (DDC) yielded the area under the curve (AUC) value of 0.816 (95% CI 0.713 to 0.894) and 0.867 (95% CI 0.655 to 0.972), respectively. Multivariable analysis showed that alpha-fetoprotein (AFP) level, skewness of perfusion fraction(f), and 5th percentile of DDC were independent predictors of high Ki-67 expression in HCCs. In the training and test sets, the AUC of the combined model for predicting high Ki-67 expression in HCCs were 0.902 (95% CI 0.814 to 0.957) and 0.908 (95% CI 0.707 to 0.989), respectively. Conclusion Histogram parameters of multiple mathematical DWI models can be useful for predicting high Ki-67 expression in HCCs, and our combined model based on AFP level, skewness of f, and 5th percentile of DDC may be an effective approach for predicting Ki-67 expression in HCCs.
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Affiliation(s)
| | | | | | | | - Yikai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
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Brancato V, Cerrone M, Garbino N, Salvatore M, Cavaliere C. Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma: A quantitative review with Radiomics Quality Score. World J Gastroenterol 2024; 30:381-417. [PMID: 38313230 PMCID: PMC10835534 DOI: 10.3748/wjg.v30.i4.381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/05/2023] [Accepted: 01/10/2024] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND Radiomics is a promising tool that may increase the value of magnetic resonance imaging (MRI) for different tasks related to the management of patients with hepatocellular carcinoma (HCC). However, its implementation in clinical practice is still far, with many issues related to the methodological quality of radiomic studies. AIM To systematically review the current status of MRI radiomic studies concerning HCC using the Radiomics Quality Score (RQS). METHODS A systematic literature search of PubMed, Google Scholar, and Web of Science databases was performed to identify original articles focusing on the use of MRI radiomics for HCC management published between 2017 and 2023. The methodological quality of radiomic studies was assessed using the RQS tool. Spearman's correlation (ρ) analysis was performed to explore if RQS was correlated with journal metrics and characteristics of the studies. The level of statistical signi-ficance was set at P < 0.05. RESULTS One hundred and twenty-seven articles were included, of which 43 focused on HCC prognosis, 39 on prediction of pathological findings, 16 on prediction of the expression of molecular markers outcomes, 18 had a diagnostic purpose, and 11 had multiple purposes. The mean RQS was 8 ± 6.22, and the corresponding percentage was 24.15% ± 15.25% (ranging from 0.0% to 58.33%). RQS was positively correlated with journal impact factor (IF; ρ = 0.36, P = 2.98 × 10-5), 5-years IF (ρ = 0.33, P = 1.56 × 10-4), number of patients included in the study (ρ = 0.51, P < 9.37 × 10-10) and number of radiomics features extracted in the study (ρ = 0.59, P < 4.59 × 10-13), and time of publication (ρ = -0.23, P < 0.0072). CONCLUSION Although MRI radiomics in HCC represents a promising tool to develop adequate personalized treatment as a noninvasive approach in HCC patients, our study revealed that studies in this field still lack the quality required to allow its introduction into clinical practice.
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Affiliation(s)
- Valentina Brancato
- Department of Information Technology, IRCCS SYNLAB SDN, Naples 80143, Italy
| | - Marco Cerrone
- Department of Radiology, IRCCS SYNLAB SDN, Naples 80143, Italy
| | - Nunzia Garbino
- Department of Radiology, IRCCS SYNLAB SDN, Naples 80143, Italy
| | - Marco Salvatore
- Department of Radiology, IRCCS SYNLAB SDN, Naples 80143, Italy
| | - Carlo Cavaliere
- Department of Radiology, IRCCS SYNLAB SDN, Naples 80143, Italy
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Zhou L, Chen Y, Li Y, Wu C, Xue C, Wang X. Diagnostic value of radiomics in predicting Ki-67 and cytokeratin 19 expression in hepatocellular carcinoma: a systematic review and meta-analysis. Front Oncol 2024; 13:1323534. [PMID: 38234405 PMCID: PMC10792117 DOI: 10.3389/fonc.2023.1323534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024] Open
Abstract
Background Radiomics have been increasingly used in the clinical management of hepatocellular carcinoma (HCC), such as markers prediction. Ki-67 and cytokeratin 19 (CK-19) are important prognostic markers of HCC. Radiomics has been introduced by many researchers in the prediction of these markers expression, but its diagnostic value remains controversial. Therefore, this review aims to assess the diagnostic value of radiomics in predicting Ki-67 and CK-19 expression in HCC. Methods Original studies were systematically searched in PubMed, EMBASE, Cochrane Library, and Web of Science from inception to May 2023. All included studies were evaluated by the radiomics quality score. The C-index was used as the effect size of the performance of radiomics in predicting Ki-67and CK-19 expression, and the positive cutoff values of Ki-67 label index (LI) were determined by subgroup analysis and meta-regression. Results We identified 34 eligible studies for Ki-67 (18 studies) and CK-19 (16 studies). The most common radiomics source was magnetic resonance imaging (MRI; 25/34). The pooled C-index of MRI-based models in predicting Ki-67 was 0.89 (95% CI:0.86-0.92) in the training set, and 0.87 (95% CI: 0.82-0.92) in the validation set. The pooled C-index of MRI-based models in predicting CK-19 was 0.86 (95% CI:0.81-0.90) in the training set, and 0.79 (95% CI: 0.73-0.84) in the validation set. Subgroup analysis suggested Ki-67 LI cutoff was a significant source of heterogeneity (I 2 = 0.0% P>0.05), and meta-regression showed that the C-index increased as Ki-67 LI increased. Conclusion Radiomics shows promising diagnostic value in predicting positive Ki-67 or CK-19 expression. But lacks standardized guidelines, which makes the model and variables selection dependent on researcher experience, leading to study heterogeneity. Therefore, standardized guidelines are warranted for future research. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023427953.
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Affiliation(s)
- Lu Zhou
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Yiheng Chen
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Yan Li
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Chaoyong Wu
- Shenzhen Hospital of Beijing University of Chinese Medicine, Shenzhen, China
| | - Chongxiang Xue
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Xihong Wang
- The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, China
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Zhang Y, Sheng R, Yang C, Dai Y, Zeng M. Higher field reduced FOV diffusion-weighted imaging for abdominal imaging at 5.0 Tesla: image quality evaluation compared with 3.0 Tesla. Insights Imaging 2023; 14:171. [PMID: 37840062 PMCID: PMC10577120 DOI: 10.1186/s13244-023-01513-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 08/27/2023] [Indexed: 10/17/2023] Open
Abstract
OBJECTIVE To evaluate the image quality of reduced field-of-view (rFOV) DWI for abdominal imaging at 5.0 Tesla (T) compared with 3.0 T. METHODS Fifteen volunteers were included into this prospective study. All the subjects underwent the 3.0 T and 5.0 T MR examinations (time interval: 2 ± 1.9 days). Free-breathing (FB), respiratory-triggered (RT), and navigator-triggered (NT) spin-echo echo-planner imaging-based rFOV-DWI examinations were conducted at 3.0 T and 5.0 T (FB3.0 T, NT3.0 T, RT3.0 T, FB5.0 T, NT5.0 T, and RT5.0 T) with two b values (b = 0 and 800 s/mm2), respectively. The signal-to-noise ratio (SNR) of different acquisition approaches were determined and statistically compared. The image quality was assessed and statistically compared with a 5-point scoring system. RESULTS The SNRs of any 5.0 T DWI images were significantly higher than those of any 3.0 T DWI images for same anatomic locations. Moreover, 5.0 T rFOV-DWIs had the significantly higher sharpness scores than 3.0 T rFOV-DWIs. Similar distortion scores were observed at both 3.0 T and 5.0 T. Finally, RT5.0 T displayed the best overall image quality followed by NT5.0 T, FB5.0 T, RT3.0 T, NT3.0 T and FB3.0 T (RT5.0 T = 3.9 ± 0.3, NT5.0 T = 3.8 ± 0.3, FB5.0 T = 3.4 ± 0.3, RT3.0 T = 3.2 ± 0.4, NT3.0 T = 3.1 ± 0.4, and FB3.0 T = 2.7 ± 0.4, p < 0.001). CONCLUSION The 5.0 T rFOV-DWI showed better overall image quality and improved SNR compared to 3.0 T rFOV-DWI, which holds clinical potential for identifying the abdominal abnormalities in routine practice. CRITICAL RELEVANCE STATEMENT This study provided evidence that abdominal 5.0 Tesla reduced field of view diffusion-weighted imaging (5.0 T rFOV-DWI) exhibited enhanced image quality and higher SNR compared to its 3.0 Tesla counterparts, holding clinical promise for accurately visualizing abdominal abnormalities. KEY POINTS • rFOV-DWI was firstly integrated with high-field-MRI for visualizing various abdominal organs. • This study indicated the feasibility of abdominal 5.0 T-rFOV-DWI. • Better image quality was identified for 5.0 T rFOV-DWI.
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Affiliation(s)
- Yunfei Zhang
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, China
- Central Research Institute, United Imaging Healthcare, Shanghai, 201800, China
| | - Ruofan Sheng
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Chun Yang
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yongming Dai
- School of Biomedical Engineering, ShanghaiTech Univerisity, Shanghai, 200032, China.
| | - Mengsu Zeng
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, China.
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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Zhang Y, Sheng R, Yang C, Dai Y, Zeng M. The Feasibility of Using Tri-Exponential Intra-Voxel Incoherent Motion DWI for Identifying the Microvascular Invasion in Hepatocellular Carcinoma. J Hepatocell Carcinoma 2023; 10:1659-1671. [PMID: 37799828 PMCID: PMC10547827 DOI: 10.2147/jhc.s433948] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023] Open
Abstract
Purpose To assess the effectiveness of tri-exponential Intra-Voxel Incoherent Motion (tri-IVIM) MRI in preoperatively identifying microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Patients and Methods In this prospective study, 67 patients with HCC were included. Metrics from bi-exponential IVIM (bi-IVIM) and tri-IVIM were calculated. Subgroup comparisons were analyzed using the independent Student's t-test or Mann-Whitney U-test. Logistic regression was performed to explore clinical risk factors. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis. Results MVI-positive HCCs exhibited significantly lower true diffusion coefficient (Dt) from bi-IVIM, as well as fast-diffusion coefficients (Df) and slow-diffusion coefficients (Ds) from tri-IVIM, compared to MVI-negative HCCs (p < 0.05). Tumor size and alpha-fetoprotein (AFP) were identified as risk factors. The combination of tri-IVIM-derived metrics (Ds and Df) yielded higher diagnostic accuracy (AUC = 0.808) compared to bi-IVIM (AUC = 0.741). A predictive model based on a nomogram was constructed using Ds, Df, tumor size, and AFP, resulting in the highest diagnostic accuracy (AUC = 0.859). Decision curve analysis indicated that the constructed model, provided the highest net benefit by accurately stratifying the risk of MVI, followed by tri-IVIM and bi-IVIM. Conclusion Tri-IVIM can provide information on perfusion and diffusion for evaluating MVI in HCC. Additionally, tri-IVIM outperformed bi-IVIM in identifying MVI-positive HCC. By integrating clinical risk factors and metrics from tri-IVIM, a predictive nomogram exhibited the highest diagnostic accuracy, potentially aiding in the noninvasive and preoperative assessment of MVI.
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Affiliation(s)
- Yunfei Zhang
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, People’s Republic of China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Ruofan Sheng
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, People’s Republic of China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Yongming Dai
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, 200032, People’s Republic of China
| | - Mengsu Zeng
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, People’s Republic of China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, People’s Republic of China
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Zhang Y, Yang C, Sheng R, Dai Y, Zeng M. Preoperatively Identify the Microvascular Invasion of Hepatocellular Carcinoma with the Restricted Spectrum Imaging. Acad Radiol 2023; 30 Suppl 1:S30-S39. [PMID: 37442719 DOI: 10.1016/j.acra.2023.06.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 06/07/2023] [Accepted: 06/14/2023] [Indexed: 07/15/2023]
Abstract
RATIONALE AND OBJECTIVES To noninvasively and preoperatively identify the microvascular invasion (MVI) of hepatocellular carcinoma (HCC) with the restricted spectrum imaging (RSI). MATERIALS AND METHODS 62 patients were included into this prospective study and underwent the RSI examination with a 3.0-T scanner. Mono-exponential diffusion-weighted imaging-derived apparent diffusion coefficient (ADC) and RSI-derived metrics including f1 (fraction of restricted diffusion), f2 (fraction of hindered diffusion), f3 (fraction of free diffusion), and f1f2 (the multiply of f1 and f2) were calculated. Univariate and multivariate logistic regression were used to select the independent risk factors. Nomogram-based model was constructed with the selected indexes. Receiver operative characteristics analysis and calibration curve were used to evaluate the diagnostic accuracy. RESULTS MVI-positive HCC showed significantly higher f1 and lower ADC values (ADC: 1.549 ± 0.228 ×10-3 vs 1.365 ± 0.239 ×10-3 mm2/s, P = .003; f1: 0.1633 ± 0.0341 vs 0.2221 ± 0.0491, P < .001). Tumor size and f1 were selected as independent risk factors for MVI. The nomogram-based model was then constructed with tumor size and f1. Nomogram-based model (area under ROC curve [AUC]= 0.856) yielded the best diagnostic accuracy followed by f1 (AUC=0.842) and ADC (AUC=0.708). The AUC of both the f1 and nomogram model were significantly higher than that of ADC. CONCLUSION RSI-derived metrics can be utilized to noninvasively and efficiently identify the MVI of HCC. Considering the importance of MVI as a significant prognostic factor for HCC, the utilization of RSI has the potential to assist in prognostic prediction and clinical management.
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Affiliation(s)
- Yunfei Zhang
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China (Y.Z., R.S., M.Z.); Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China (Y.Z., C.Y., R.S., M.Z.)
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China (Y.Z., C.Y., R.S., M.Z.)
| | - Ruofan Sheng
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China (Y.Z., R.S., M.Z.); Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China (Y.Z., C.Y., R.S., M.Z.)
| | - Yongming Dai
- School of Biomedical Engineering, ShanghaiTech Univerisity, Shanghai, China (Y.D.)
| | - Mengsu Zeng
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China (Y.Z., R.S., M.Z.); Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China (Y.Z., C.Y., R.S., M.Z.).
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Gong XQ, Liu N, Tao YY, Li L, Li ZM, Yang L, Zhang XM. Radiomics models based on multisequence MRI for predicting PD-1/PD-L1 expression in hepatocellular carcinoma. Sci Rep 2023; 13:7710. [PMID: 37173350 PMCID: PMC10182068 DOI: 10.1038/s41598-023-34763-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/07/2023] [Indexed: 05/15/2023] Open
Abstract
The purpose of this study was to explore the effectiveness of radiomics based on multisequence MRI in predicting the expression of PD-1/PD-L1 in hepatocellular carcinoma (HCC). One hundred and eight patients with HCC who underwent contrast-enhanced MRI 2 weeks before surgical resection were enrolled in this retrospective study. Corresponding paraffin sections were collected for immunohistochemistry to detect the expression of PD-1 and PD-L1. All patients were randomly divided into a training cohort and a validation cohort at a ratio of 7:3. Univariate and multivariate analyses were used to select potential clinical characteristics related to PD-1 and PD-L1 expression. Radiomics features were extracted from the axial fat-suppression T2-weighted imaging (FS-T2WI) images and the arterial phase and portal venous phase images from the axial dynamic contrast-enhanced MRI, and the corresponding feature sets were generated. The least absolute shrinkage and selection operator (LASSO) was used to select the optimal radiomics features for analysis. Logistic regression analysis was performed to construct single-sequence and multisequence radiomics and radiomic-clinical models. The predictive performance was judged by the area under the receiver operating characteristic curve (AUC) in the training and validation cohorts. In the whole cohort, PD-1 expression was positive in 43 patients, and PD-L1 expression was positive in 34 patients. The presence of satellite nodules served as an independent predictor of PD-L1 expression. The AUC values of the FS-T2WI, arterial phase, portal venous phase and multisequence models in predicting the expression of PD-1 were 0.696, 0.843, 0.863, and 0.946 in the training group and 0.669, 0.792, 0.800 and 0.815 in the validation group, respectively. The AUC values of the FS-T2WI, arterial phase, portal venous phase, multisequence and radiomic-clinical models in predicting PD-L1 expression were 0.731, 0.800, 0.800, 0.831 and 0.898 in the training group and 0.621, 0.743, 0.771, 0.810 and 0.779 in the validation group, respectively. The combined models showed better predictive performance. The results of this study suggest that a radiomics model based on multisequence MRI has the potential to predict the preoperative expression of PD-1 and PD-L1 in HCC, which could become an imaging biomarker for immune checkpoint inhibitor (ICI)-based treatment.
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Affiliation(s)
- Xue-Qin Gong
- Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing, 400030, China
| | - Ning Liu
- Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Yun-Yun Tao
- Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Li Li
- Department of Pathology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Zu-Mao Li
- Department of Pathology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Lin Yang
- Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China.
| | - Xiao-Ming Zhang
- Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
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Mao Q, Zhou MT, Zhao ZP, Liu N, Yang L, Zhang XM. Role of radiomics in the diagnosis and treatment of gastrointestinal cancer. World J Gastroenterol 2022; 28:6002-6016. [PMID: 36405385 PMCID: PMC9669820 DOI: 10.3748/wjg.v28.i42.6002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 09/24/2022] [Accepted: 10/27/2022] [Indexed: 11/10/2022] Open
Abstract
Gastrointestinal cancer (GIC) has high morbidity and mortality as one of the main causes of cancer death. Preoperative risk stratification is critical to guide patient management, but traditional imaging studies have difficulty predicting its biological behavior. The emerging field of radiomics allows the conversion of potential pathophysiological information in existing medical images that cannot be visually recognized into high-dimensional quantitative image features. Tumor lesion characterization, therapeutic response evaluation, and survival prediction can be achieved by analyzing the relationships between these features and clinical and genetic data. In recent years, the clinical application of radiomics to GIC has increased dramatically. In this editorial, we describe the latest progress in the application of radiomics to GIC and discuss the value of its potential clinical applications, as well as its limitations and future directions.
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Affiliation(s)
- Qi Mao
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Mao-Ting Zhou
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Zhang-Ping Zhao
- Department of Radiology, Panzhihua Central Hospital, Panzhihua 617000, Sichuan Province, China
| | - Ning Liu
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Lin Yang
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Xiao-Ming Zhang
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
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Zhou Y, Zheng J, Yang C, Peng J, Liu N, Yang L, Zhang XM. Application of intravoxel incoherent motion diffusion-weighted imaging in hepatocellular carcinoma. World J Gastroenterol 2022; 28:3334-3345. [PMID: 36158259 PMCID: PMC9346463 DOI: 10.3748/wjg.v28.i27.3334] [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: 12/30/2021] [Revised: 04/26/2022] [Accepted: 06/23/2022] [Indexed: 02/06/2023] Open
Abstract
The morbidity and mortality of hepatocellular carcinoma (HCC) rank 6th and 4th, respectively, among malignant tumors worldwide. Traditional diffusion-weighted imaging (DWI) uses the apparent diffusion coefficient (ADC) obtained by applying the monoexponential model to reflect water molecule diffusion in active tissue; however, the value of ADC is affected by microcirculation perfusion. Using a biexponential model, intravoxel incoherent motion (IVIM)-DWI quantitatively measures information related to pure water molecule diffusion and microcirculation perfusion, thus compensating for the shortcomings of DWI. The number of studies examining the application of IVIM-DWI in patients with HCC has gradually increased over the last few years, and many results show that IVIM-DWI has vital value for HCC differentiation, pathological grading, and predicting and evaluating the treatment response. The present study principally reviews the principle of IVIM-DWI and its research progress in HCC differentiation, pathological grading, predicting and evaluating the treatment response, predicting postoperative recurrence and predicting gene expression prediction.
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Affiliation(s)
- Yi Zhou
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
- Department of Radiology, People's Hospital of Deyang City, Deyang 618000, Sichuan Province, China
| | - Jing Zheng
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Cui Yang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
- Department of Radiology, Panzhihua Central Hospital, Panzhihua 617000, Sichuan Province, China
| | - Juan Peng
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
- Department of Radiology, Sichuan Provincial People's Hospital Jinniu Hospital, Chengdu Jinniu District People's Hospital, Chengdu 610007, Sichuan Province, China
| | - Ning Liu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Lin Yang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Xiao-Ming Zhang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
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Sheng R, Zhang Y, Sun W, Ji Y, Zeng M, Yao X, Dai Y. Staging Chronic Hepatitis B Related Liver Fibrosis with a Fractional Order Calculus Diffusion Model. Acad Radiol 2022; 29:951-963. [PMID: 34429260 DOI: 10.1016/j.acra.2021.07.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 07/06/2021] [Accepted: 07/07/2021] [Indexed: 12/17/2022]
Abstract
RATIONALE AND OBJECTIVES Accurately staging liver fibrosis is of great clinical significance. We aimed to evaluate the clinical potential of the non-Gaussian fractional order calculus (FROC) diffusion model in staging liver fibrosis. MATERIALS AND METHODS A total of 82 patients with chronic hepatitis B (CHB) were included in this prospective study. Diffusion weighted imaging (DWI)-derived parameters including the diffusion coefficient (D), fractional order parameter (β) and microstructural quantity (μ) sourced from FROC-DWI, and apparent diffusion coefficient (ADC) derived from mono-exponential DWI, as well as the aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 (FIB-4) were calculated. Their correlations with fibrosis stages and the diagnostic efficacy in predicting liver fibrosis were assessed and compared. RESULTS D (r = -0.667), β (r = -0.671), μ (r = -0.481), and ADC (r = -0.665) displayed significant correlations with fibrosis stages (p < 0.001). D, β and ADC (p < 0.01) were independently associated with fibrosis; and compared to inflammatory activity, fibrosis was the independent factor significantly correlated with D, β and ADC (p < 0.001). There were no significant differences between the area under curves of D, β, μ or their combinations and ADC for predicting different fibrosis stages (p > 0.05). The diagnostic performance of the combined index with four diffusion metrics was better than D, β, μ or ADC used alone (p < 0.05) as well as APRI or FIB-4 (p < 0.01) in fibrosis staging. CONCLUSION FROC-DWI was valuable in staging liver fibrosis in patients with CHB, but there were no significant differences between the FROC-DWI parameters and the classical ADC. However, the combined DWI-derived index including D, β, μ and ADC offered the best diagnostic efficacy and may serve as a reliable tool for fibrosis evaluation, superior to APRI and FIB-4.
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Affiliation(s)
- Ruofan Sheng
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, China
| | - Yunfei Zhang
- Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Wei Sun
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, China.
| | - Xiuzhong Yao
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, China
| | - Yongming Dai
- Central Research Institute, United Imaging Healthcare, Shanghai, China
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Wang F, Yan CY, Wang CH, Yang Y, Zhang D. The Roles of Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion Diffusion-Weighted Imaging Parameters in Preoperative Evaluation of Pathological Grades and Microvascular Invasion in Hepatocellular Carcinoma. Front Oncol 2022; 12:884854. [PMID: 35646649 PMCID: PMC9131658 DOI: 10.3389/fonc.2022.884854] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 03/31/2022] [Indexed: 12/14/2022] Open
Abstract
Background Currently, there are disputes about the parameters of diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and diffusion-weighted imaging (DWI) in predicting pathological grades and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). The aim of our study was to investigate and compare the predictive power of DKI and IVIM-DWI parameters for preoperative evaluation of pathological grades and MVI in HCC. Methods PubMed, Web of Science, and Embase databases were searched for relevant studies published from inception to October 2021. Review Manager 5.3 was used to summarize standardized mean differences (SMDs) of mean kurtosis (MK), mean diffusivity (MD), tissue diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), mean apparent diffusion coefficient (ADCmean), and minimum apparent diffusion coefficient (ADCmin). Stata12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC). Overall, 42 up-to-standard studies with 3,807 cases of HCC were included in the meta-analysis. Results The SMDs of ADCmean, ADCmin, and D values, but not those of D* and f values, significantly differed between well, moderately, and poorly differentiated HCC (P < 0.01). The sensitivity, specificity, and AUC of the MK, D, ADCmean, and ADCmin for preoperative prediction of poorly differentiated HCC were 69%/94%/0.89, 87%/80%/0.89, 82%/75%/0.86, and 83%/64%/0.81, respectively. In addition, the sensitivity, specificity, and AUC of the D and ADCmean for preoperative prediction of well-differentiated HCC were 87%/83%/0.92 and 82%/88%/0.90, respectively. The SMDs of ADCmean, ADCmin, D, MD, and MK values, but not f values, showed significant differences (P < 0.01) between MVI-positive (MVI+) and MVI-negative (MVI-) HCC. The sensitivity and specificity of D and ADCmean for preoperative prediction of MVI+ were 80%/80% and 74%/71%, respectively; the AUC of the D (0.87) was significantly higher than that of ADCmean (0.78) (Z = −2.208, P = 0.027). Sensitivity analysis showed that the results of the above parameters were stable and reliable, and subgroup analysis confirmed a good prediction effect. Conclusion DKI parameters (MD and MK) and IVIM-DWI parameters (D value, ADCmean, and ADCmin) can be used as a noninvasive and simple preoperative examination method to predict the grade and MVI in HCC. Compared with ADCmean and ADCmin, MD and D values have higher diagnostic efficacy in predicting the grades of HCC, and D value has superior diagnostic efficacy to ADCmean in predicting MVI+ in HCC. However, f value cannot predict the grade or MVI in HCC.
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Affiliation(s)
- Fei Wang
- Department of Medical Imaging, Luzhou People's Hospital, Luzhou, China.,Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Chun Yue Yan
- Department of Obstetrics, Luzhou People's Hospital, Luzhou, China
| | - Cai Hong Wang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Yan Yang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Dong Zhang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
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Brancato V, Garbino N, Salvatore M, Cavaliere C. MRI-Based Radiomic Features Help Identify Lesions and Predict Histopathological Grade of Hepatocellular Carcinoma. Diagnostics (Basel) 2022; 12:diagnostics12051085. [PMID: 35626241 PMCID: PMC9139902 DOI: 10.3390/diagnostics12051085] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/06/2022] [Accepted: 04/23/2022] [Indexed: 02/04/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common form of liver cancer. Radiomics is a promising tool that may increase the value of magnetic resonance imaging (MRI) in the management of HCC. The purpose of our study is to develop an MRI-based radiomics approach to preoperatively detect HCC and predict its histological grade. Thirty-eight HCC patients at staging who underwent axial T2-weighted and dynamic contrast-enhanced MRI (DCE-MRI) were considered. Three-dimensional volumes of interest (VOIs) were manually placed on HCC lesions and normal hepatic tissue (HT) on arterial phase post-contrast images. Radiomic features from T2 images and arterial, portal and tardive post-contrast images from DCE-MRI were extracted by using Pyradiomics. Feature selection was performed using correlation filter, Wilcoxon-rank sum test and mutual information. Predictive models were constructed for HCC differentiation with respect to HT and HCC histopathologic grading used at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. Promising results were obtained from radiomic prediction models, with best AUCs ranging from 71% to 96%. Radiomics MRI based on T2 and DCE-MRI revealed promising results concerning both HCC detection and grading. It may be a suitable tool for personalized treatment of HCC patients and could also be used to develop new prognostic biomarkers useful for HCC assessment without the need for invasive procedures.
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Andersson M, Jalnefjord O, Montelius M, Rizell M, Sternby Eilard M, Ljungberg M. Evaluation of response in patients with hepatocellular carcinoma treated with intratumoral dendritic cell vaccination using intravoxel incoherent motion (IVIM) MRI and histogram analysis. Acta Radiol 2021; 64:32-41. [PMID: 34904868 DOI: 10.1177/02841851211065935] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Immunotherapy of hepatocellular carcinoma (HCC) is an emerging method with promising results. Immunotherapy can have an antitumor effect without affecting tumor size, calling for functional imaging methods for response evaluation. PURPOSE To evaluate the response to intratumoral injections with the immune primer ilixadencel in HCCs with diffusion-weighted magnetic resonance imaging (DW-MRI) using intravoxel incoherent motion (IVIM) and histogram analysis. MATERIAL AND METHODS A total of 17 patients with advanced HCC were treated with intratumoral injections with ilixadencel on three occasions 2-5 weeks apart. The patients were examined with IVIM before each injection as well as approximately three months after the first injection. RESULTS The 10th percentile of perfusion-related parameter D* decreased significantly after the first and second intratumoral injections of ilixadencel compared to baseline (P < 0.05). There was a non-significant trend of lower median region of interest f (perfusion fraction) before injection 2 compared to baseline (P = 0.07). There were significant correlations between the 10th percentile and median of D at baseline and change in tumor size after three months (r = 0.79, P < 0.01 and r = 0.72, P < 0.05, respectively). CONCLUSION DW-MRI with IVIM and histogram analysis revealed significant reductions of D* early after treatment as well as an association between D at baseline and smaller tumor growth at three months. The lower percentiles (10th and 50th) were found more important. Further research is needed to confirm our preliminary findings of reduced perfusion after ilixadencel vaccinations, suggesting a treatment effect on HCC.
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Affiliation(s)
- Mats Andersson
- Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute and Department of Radiology, Karolinska University Hospital, Stockholm, Sweden
| | - Oscar Jalnefjord
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Mikael Montelius
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Magnus Rizell
- Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Malin Sternby Eilard
- Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Maria Ljungberg
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
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Feng W, Gao Y, Lu XR, Xu YS, Guo ZZ, Lei JQ. Correlation between molecular prognostic factors and magnetic resonance imaging intravoxel incoherent motion histogram parameters in breast cancer. Magn Reson Imaging 2021; 85:262-270. [PMID: 34740800 DOI: 10.1016/j.mri.2021.10.027] [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: 08/22/2020] [Revised: 07/26/2021] [Accepted: 10/17/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To explore the efficacy of the quantitative parameter histogram analysis of intravoxel incoherent motion (IVIM) for different molecular prognostic factors of breast cancer. MATERIALS AND METHODS A total of 72 patients with breast cancer who were confirmed by surgical pathology and underwent preoperative magnetic resonance imaging (MRI) were analyzed retrospectively. A region of interest (ROI) was drawn in each slice of the IVIM images. Whole-tumor histogram parameters were obtained with Firevoxel's software by accumulating all ROIs. Next, Kolmogorov-Smirnov test, Student's t-test, Mann-Whitney U test, receiver operating characteristic curve analysis and spearman rank correlation analysis were used to assess the relationship between histogram parameters and molecular prognostic factors of breast cancer. RESULTS Among estrogen receptor (ER)-negative ROCs, the apparent diffusion coefficient (ADC) 10th percentile had the highest ROC of 0.792, with a cut-off value of 0.788 × 10-3 mm2/s, and sensitivity and specificity of 0.714 and 0.867, respectively. The negative correlation between lymph node metastasis status and ADC standard deviation was significant (ρ = -0.44, the correlation coefficients was represented by ρ). Positive correlations were observed between hormonal expression of ER and progesterone receptor (PR) with heterogeneity metrics of ADC or perfusion fraction (f), such as ADC inhomogeneity (ρ = 0.37, ρ = 0.29) and f skewness (ρ = 0.32, ρ = 0.28). Negative correlations were observed with numerical metrics, such as the ADC median (ρ = -0.31, ρ = -0.34) and f 45th percentile (ρ = -0.35, ρ = -0.28). The positive correlations between human epidermal receptor factor-2 (HER2) and pseudo-diffusivity (Dp) numerical metrics, Ki-67 expression, and heterogeneity metrics of Dp were high. CONCLUSIONS The ADC 10th percentile had the largest area under the curve in the ER-negative ROC analysis, and the ADC standard deviation was the most valuable in the correlation analysis of lymph node metastasis. Whole-lesion quantitative histogram parameters of IVIM could, therefore, provide a scientific basis for radiomics to further guide clinical practice in the prognosis of breast cancer.
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Affiliation(s)
- Wen Feng
- The First School of Clinical Medicine, Lanzhou University, Lanzhou 730000, Gansu, China; Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China
| | - Ya Gao
- Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China
| | - Xing-Ru Lu
- Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China
| | - Yong-Sheng Xu
- Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China
| | - Zhuan-Zhuan Guo
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shanxi, China
| | - Jun-Qiang Lei
- Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China.
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Gong XQ, Tao YY, Wu Y, Liu N, Yu X, Wang R, Zheng J, Liu N, Huang XH, Li JD, Yang G, Wei XQ, Yang L, Zhang XM. Progress of MRI Radiomics in Hepatocellular Carcinoma. Front Oncol 2021; 11:698373. [PMID: 34616673 PMCID: PMC8488263 DOI: 10.3389/fonc.2021.698373] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 08/31/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is the sixth most common cancer in the world and the third leading cause of cancer-related death. Although the diagnostic scheme of HCC is currently undergoing refinement, the prognosis of HCC is still not satisfactory. In addition to certain factors, such as tumor size and number and vascular invasion displayed on traditional imaging, some histopathological features and gene expression parameters are also important for the prognosis of HCC patients. However, most parameters are based on postoperative pathological examinations, which cannot help with preoperative decision-making. As a new field, radiomics extracts high-throughput imaging data from different types of images to build models and predict clinical outcomes noninvasively before surgery, rendering it a powerful aid for making personalized treatment decisions preoperatively. OBJECTIVE This study reviewed the workflow of radiomics and the research progress on magnetic resonance imaging (MRI) radiomics in the diagnosis and treatment of HCC. METHODS A literature review was conducted by searching PubMed for search of relevant peer-reviewed articles published from May 2017 to June 2021.The search keywords included HCC, MRI, radiomics, deep learning, artificial intelligence, machine learning, neural network, texture analysis, diagnosis, histopathology, microvascular invasion, surgical resection, radiofrequency, recurrence, relapse, transarterial chemoembolization, targeted therapy, immunotherapy, therapeutic response, and prognosis. RESULTS Radiomics features on MRI can be used as biomarkers to determine the differential diagnosis, histological grade, microvascular invasion status, gene expression status, local and systemic therapeutic responses, and prognosis of HCC patients. CONCLUSION Radiomics is a promising new imaging method. MRI radiomics has high application value in the diagnosis and treatment of HCC.
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Affiliation(s)
- Xue-Qin Gong
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Yun-Yun Tao
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Yao–Kun Wu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Ning Liu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xi Yu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Ran Wang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Jing Zheng
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Nian Liu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xiao-Hua Huang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Jing-Dong Li
- Department of Hepatocellular Surgery, Institute of Hepato-Biliary-Intestinal Disease, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Gang Yang
- Department of Hepatocellular Surgery, Institute of Hepato-Biliary-Intestinal Disease, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xiao-Qin Wei
- School of Medical Imaging, North Sichuan Medical College, Nanchong, China
| | - Lin Yang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xiao-Ming Zhang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
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The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review. J Clin Med 2021; 10:jcm10122641. [PMID: 34203995 PMCID: PMC8232758 DOI: 10.3390/jcm10122641] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/10/2021] [Accepted: 06/14/2021] [Indexed: 12/14/2022] Open
Abstract
The importance of Diffusion Weighted Imaging (DWI) in hepatocellular carcinoma (HCC) has been widely handled in the literature. Due to the mono-exponential model limitations, several studies recently investigated the role of non-Gaussian DWI models in HCC. However, their results are variable and inconsistent. Therefore, the aim of this systematic review is to summarize current knowledge on non-Gaussian DWI techniques in HCC. A systematic search of the literature, including PubMed, Google Scholar, MEDLINE, and ScienceDirect databases, was performed to identify original articles since 2010 that evaluated the role of non-Gaussian DWI models for HCC diagnosis, grading, response to treatment, and prognosis. Studies were grouped and summarized according to the non-Gaussian DWI models investigated. We focused on the most used non-Gaussian DWI models (Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Stretched Exponential—SE). The quality of included studies was evaluated by using QUADAS-2 and QUIPS tools. Forty-three articles were included, with IVIM and DKI being the most investigated models. Although the role of non-Gaussian DWI models in clinical settings has not fully been established, our findings showed that their parameters may potentially play a role in HCC. Further studies are required to identify a standardized DWI acquisition protocol for HCC diagnosis, grading, response to treatment, and prognosis.
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Gene Polymorphism of MUC15, MMP14, BRAF, and COL1A1 Is Associated with Capsule Formation in Hepatocellular Carcinoma. Can J Gastroenterol Hepatol 2021; 2021:9990305. [PMID: 34007838 PMCID: PMC8100414 DOI: 10.1155/2021/9990305] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/09/2021] [Accepted: 04/16/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND The presence of a capsule is an important prognostic factor in hepatocellular carcinoma (HCC). Capsule formation is affected by tumor-host interaction, which may include collagen deposition and extracellular matrix (ECM) degradation. PURPOSE This study aimed to examine whether single-nucleotide polymorphisms (SNPs) in the genes for COL1A1 MUC15, MMP14, CD97, SMYD3, BRAF, and transforming growth factor beta 1 (TGF-β) are related to capsule formation. METHODS We prospectively recruited and analyzed 185 patients with HCC with or without a capsule between 2019 and 2020. The SNPs involved were analyzed by polymerase chain reaction. Differences in the allele and genotype frequency between the cases and controls were evaluated using the chi-square test. Odds ratios and 95% confidence intervals were calculated by logistic regression analysis with adjustment for age and sex. Stratification analyses were also performed with preselected variables. RESULTS The single-locus analysis showed that the presence of a capsule was significantly associated with five SNPs : MUC15 rs17309195 (P=0.01), rs12271124 (P= 0.02), rs10430847 (P=0.04), MMP14 rs17884816 (P=0.01), and BRAF rs74512895 (P=0.03). Adjusted logistic regression revealed that the decreased capsule formation was statistically significantly associated with BRAF rs76603725, COL1A1 rs2269336, and MUC15 rs17309195, while MMP14 rs17884816 and MUC15 rs10430847, rs2063278, and rs967490 were associated with increased capsule formation. The MUC15 block 2 haplotype was associated with increased capsule formation. CONCLUSIONS MUC15, MMP14, BRAF, and COL1A1 gene polymorphisms are associated with capsule formation in HCC. Studies involving larger samples are needed to confirm our results.
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