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Kovacevic B, Ewertsen C, Kristensen TS, Penninga L, Hansen CP. Progression of resectable pancreatic ductal adenocarcinoma during surgical delay and effects on survival - A propensity score matched study. Pancreatology 2025; 25:228-233. [PMID: 39616070 DOI: 10.1016/j.pan.2024.11.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 10/19/2024] [Accepted: 11/22/2024] [Indexed: 03/22/2025]
Abstract
BACKGROUND Surgery is the only curative treatment for pancreatic cancer, but less than 25 % of the patients present with a resectable tumor at the time of diagnosis. The aim of this study is to evaluate progression during surgical treatment delay and examine any associations between surgical treatment delay and survival. METHODS This is a retrospective, single center propensity score matched study including treatment naïve patients with pancreatic adenocarcinoma between 2018 and 2022. Outcomes included disease progression during surgical treatment delay in patients where follow-up imaging was performed as well as overall and recurrence-free survival for the entire cohort. RESULTS The study cohort consisted of 290 patients of whom 129 (44.5 %) underwent follow-up imaging. Radiological progression to unresectable disease during surgical delay was seen in 14 cases (10.9 %), with another 17 cases (13.2 %) deemed unresectable during intended resection. Tumor size progression was observed in 29 patients (22.5 %) with an average tumor growth rate of 7.4 mm (95%CI 5.8-8.9, p < 0.001). Median time to surgery was 37 days with no observed associations between treatment delay and overall survival (HR = 1.02, 95%CI 0.76-1.38, p = 0.996), or the risk of recurrence (HR = 1.06, 95%CI 0.77-1.48, p = 0.709). CONCLUSION Progression in tumor size does not seem to affect survival in our study population. In general, surgical treatment delay in up-front resectable patients does not seem to be associated with survival or the risk of recurrence, but the optimal and maximal time to surgery as well as the optimal timing of the follow-up scanning remain unclear.
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Affiliation(s)
- Bojan Kovacevic
- Department of Surgery, Copenhagen University Hospital - Rigshospitalet, Denmark; Gastro Unit, Division of Endoscopy, Copenhagen University Hospital - Herlev and Gentofte, Denmark.
| | - Caroline Ewertsen
- Department of Radiology, Copenhagen University Hospital - Rigshospitalet, Denmark
| | | | - Luit Penninga
- Department of Surgery, Copenhagen University Hospital - Rigshospitalet, Denmark
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Laga Boul-Atarass I, Cepeda Franco C, Sanmartín Sierra JD, Castell Monsalve J, Padillo Ruiz J. Virtual 3D models, augmented reality systems and virtual laparoscopic simulations in complicated pancreatic surgeries: state of art, future perspectives, and challenges. Int J Surg 2025; 111:2613-2623. [PMID: 39869381 DOI: 10.1097/js9.0000000000002231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Accepted: 12/07/2024] [Indexed: 01/28/2025]
Abstract
Pancreatic surgery is considered one of the most challenging interventions by many surgeons, mainly due to retroperitoneal location and proximity to key and delicate vascular structures. These factors make pancreatic resection a demanding procedure, with successful rates far from optimal and frequent postoperative complications. Surgical planning is essential to improve patient outcomes, and in this regard, many technological advances made in the last few years have proven to be extremely useful in medical fields. This review aims to outline the potential and limitations of 3D digital and 3D printed models in pancreatic surgical planning, as well as the impact and challenges of novel technologies such as augmented/virtual reality systems or artificial intelligence to improve medical training and surgical outcomes.
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Affiliation(s)
- Imán Laga Boul-Atarass
- Department of Surgery, Virgen del Rocio University Hospital, Seville, Spain
- Oncology Surgery, Cell Therapy, and Organ Transplantation Group, Instituto de Biomedicina de Sevilla (IBiS), University of Sevilla, Seville, Spain
| | - Carmen Cepeda Franco
- Department of Surgery, Virgen del Rocio University Hospital, Seville, Spain
- Oncology Surgery, Cell Therapy, and Organ Transplantation Group, Instituto de Biomedicina de Sevilla (IBiS), University of Sevilla, Seville, Spain
| | | | | | - Javier Padillo Ruiz
- Department of Surgery, Virgen del Rocio University Hospital, Seville, Spain
- Oncology Surgery, Cell Therapy, and Organ Transplantation Group, Instituto de Biomedicina de Sevilla (IBiS), University of Sevilla, Seville, Spain
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R S, J V, F P, DA B, A L, E G, A F, C T, L B, B E. 3D modeling to predict vascular involvement in resectable pancreatic adenocarcinoma. Heliyon 2025; 11:e41473. [PMID: 39850404 PMCID: PMC11754173 DOI: 10.1016/j.heliyon.2024.e41473] [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: 08/09/2024] [Revised: 11/27/2024] [Accepted: 12/23/2024] [Indexed: 01/25/2025] Open
Abstract
Background Current management of patients with borderline resectable pancreatic adenocarcinoma (BR-PDAC) depends on the degree of involvement of the major arterial and venous structures. The aim of this study was to evaluate 3D segmentation and printing to predict tumor size and vascular involvement of BR-PDAC to improve pre-operative planning of vascular resection and better select patients for neoadjuvant therapy. Methods We retrospectively evaluated 16 patients with BR-PDAC near vascular structures who underwent pancreatoduodenectomy (PD) with or without vascular resection between 2015 and 2021. The pre-operative computed tomography (CT) images were processed by segmentation with 3D reconstruction and printed as 3D models. Two radiologists specialized in pancreatic imaging and two pancreatic surgeons blindly and independently analyzed the pre-operative CT scans and 3D models using a defined checklist. Their evaluations were compared to the pre-operative 2D-CT reports utilized for patient management. A positive delta was defined by the 3D analysis resulting in greater accuracy in predicting vascular involvement as proven intraoperatively or histopathologically. Results Fourteen PD, one total pancreatectomy, and one exploratory laparotomy were performed. Ten patients had a positive delta concerning vascular involvement of the superior mesenteric or portal vein. Tumor extension was also more accurately evaluated by 3D modeling than by 2D-CT (p < 0.05). Conclusions Our pilot study demonstrates that 3D segmentation can provide additional information for choosing the best treatment strategy and surgical plain in patients with BR-PDAC. Especially for upcoming mini-invasive techniques like laparoscopic and robotic resections, better pre-operative planning is essential to allow safety and prevent vascular injury.
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Affiliation(s)
- Sguinzi R
- Department of General Surgery, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland
| | - Vidal J
- Department of Radiology, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland
| | - Poroes F
- Department of Radiology, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland
| | - Bartolucci DA
- Department of Radiology, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland
| | - Litchinko A
- Department of General Surgery, University Hospital of Geneva, 1205, Switzerland
| | - Gossin E
- University of Fribourg, Faculty of Science and Medicine - Section of Medicine, 1700, Fribourg, Switzerland
| | - Fingerhut A
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, PR China
| | - Toso C
- Department of General Surgery, University Hospital of Geneva, 1205, Switzerland
| | - Buhler L
- Department of General Surgery, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland
| | - Egger B
- Department of General Surgery, Fribourg Cantonal Hospital, 1700, Fribourg, Switzerland
- University of Fribourg, Faculty of Science and Medicine - Section of Medicine, 1700, Fribourg, Switzerland
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Corallo C, Al-Adhami AS, Jamieson N, Valle J, Radhakrishna G, Moir J, Albazaz R. An update on pancreatic cancer imaging, staging, and use of the PACT-UK radiology template pre- and post-neoadjuvant treatment. Br J Radiol 2025; 98:13-26. [PMID: 39460945 DOI: 10.1093/bjr/tqae217] [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] [Received: 12/12/2023] [Revised: 10/01/2024] [Accepted: 10/22/2024] [Indexed: 10/28/2024] Open
Abstract
Pancreatic ductal adenocarcinoma continues to have a poor prognosis, although recent advances in neoadjuvant treatments (NATs) have provided some hope. Imaging assessment of suspected tumours can be challenging and requires a specific approach, with pancreas protocol CT being the primary imaging modality for staging with other modalities used as problem-solving tools to facilitate appropriate management. Imaging assessment post NAT can be particularly difficult due to a current lack of robust radiological criteria to predict response and differentiate treatment induced fibrosis/inflammation from residual tumour. This review aims to provide an update of pancreatic ductal adenocarcinoma with particular focus on three points: tumour staging pre- and post-NAT including vascular assessment, structured reporting with introduction of the PAncreatic Cancer reporting Template-UK (PACT-UK) radiology template, and the potential future role of artificial intelligence in the diagnosis and staging of pancreatic cancer.
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Affiliation(s)
- Carmelo Corallo
- Department of Radiology, St James's University Hospital, Leeds LS9 7TF, United Kingdom
| | - Abdullah S Al-Adhami
- Department of Radiology, Glasgow Royal Infirmary, Glasgow G31 2ER, United Kingdom
| | - Nigel Jamieson
- HPB Unit, Glasgow Royal Infirmary, Glasgow G31 2ER, United Kingdom
| | - Juan Valle
- Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, United Kingdom
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester M20 4 BX, United Kingdom
| | | | - John Moir
- HPB Unit, Freeman Hospital, Newcastle Upon Tyne NE7 7DN, United Kingdom
| | - Raneem Albazaz
- Department of Radiology, St James's University Hospital, Leeds LS9 7TF, United Kingdom
- University of Leeds, Leeds LS2 9JT, United Kingdom
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Amor M, Siddiqui MA, Kazi IA, Kabir A, Nasrullah A. Solitary metastasis to the head of the pancreas from lung adenocarcinoma mimicking pancreatic ductal adenocarcinoma: A case report. Radiol Case Rep 2024; 19:6193-6198. [PMID: 39376954 PMCID: PMC11456792 DOI: 10.1016/j.radcr.2024.09.010] [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: 08/12/2024] [Revised: 09/01/2024] [Accepted: 09/03/2024] [Indexed: 10/09/2024] Open
Abstract
Solitary pancreatic metastasis is a rare cause of pancreatic neoplasm. Pancreatic ductal adenocarcinoma is the primary differential consideration when a solitary pancreatic mass is diagnosed, as it is the most common solitary solid pancreatic neoplasm. A majority of pancreatic ductal adenocarcinomas arise in the region of the head of the pancreas; however, specific neoplastic and non-neoplastic lesions can occur at or adjacent to the pancreatic head, which can mimic a pancreatic ductal adenocarcinoma. Therefore, a histopathological diagnosis is essential for confirming pancreatic ductal adenocarcinoma. Isolated solitary metastasis from primary lung adenocarcinoma is a rare cause of a solitary pancreatic head mass. We report a case in which imaging and pathology were integral to the diagnosis of a solitary lung adenocarcinoma metastasis to the head of the pancreas, which ultimately guided appropriate patient management.
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Affiliation(s)
- Mostafa Amor
- School of Medicine, University of Missouri, Columbia, MI, USA
| | | | - Irfan Amir Kazi
- Department of Radiology, University of Missouri, Columbia, MI, USA
| | - Asad Kabir
- Department of Pulmonary Critical Care and Sleep Medicine, Mosiac Life Care, St. Joseph, MI, USA
| | - Ayesha Nasrullah
- Department of Radiology, University of Missouri, Columbia, MI, USA
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Biswas S, Afrose S, Mita MA, Hasan MR, Shimu MSS, Zaman S, Saleh MA. Next-Generation Sequencing: An Advanced Diagnostic Tool for Detection of Pancreatic Disease/Disorder. JGH Open 2024; 8:e70061. [PMID: 39605899 PMCID: PMC11599877 DOI: 10.1002/jgh3.70061] [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: 07/28/2024] [Revised: 11/05/2024] [Accepted: 11/11/2024] [Indexed: 11/29/2024]
Abstract
The pancreas is involved in digestion and glucose regulation in the human body. Given the recognized link between chronic pancreatitis and pancreatic cancer, addressing pancreatic disorders and pancreatic cancer is particularly challenging. This review aims to highlight the limitations of traditional methods in diagnosing pancreatic disorders and cancer and explore several next-generation sequencing (NGS) approaches as a promising alternative. There are distinct clinical symptoms that are shared by a number of clinical phenotypes of pancreatic illness induced by particular genetic mutations. Traditional diagnostic methods encompass computed tomography, magnetic resonance imaging, contrast-enhanced Doppler ultrasound, endoscopic ultrasound, endoscopic retrograde cholangiopancreatography, transabdominal ultrasound, laparoscopy, and positron emission tomography have a prognostic ability of only 5% or less and a 5-year survival rate. Genetic sequencing can be employed as an alternative to conventional diagnostic techniques. Sanger sequencing and NGS are currently largely operated genome analysis, with no exception for pancreatic disease diagnosis. The NGS methods can sequence millions to billions of short DNA fragments, enabling enormous sample screening in a short amount of time with low-abundance detection, like in 0.1%-1% mutation prevalence declining approximate cost. Whole-genome sequencing, whole-exome sequencing, RNA sequencing, and single-cell NGS are a few NGS methods utilized to diagnose pancreatic disease. For both research and clinical applications, the NGS techniques can provide a precise diagnosis of pancreatic disorders in a short amount of time at a reasonable expenditure.
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Affiliation(s)
- Suvro Biswas
- Miocrobiology Laboratory, Department of Genetic Engineering and BiotechnologyUniversity of RajshahiBangladesh
| | - Shamima Afrose
- Department of Genetic Engineering and BiotechnologyUniversity of RajshahiRajshahiBangladesh
| | - Mohasana Akter Mita
- Department of Genetic Engineering and BiotechnologyUniversity of RajshahiRajshahiBangladesh
| | - Md. Robiul Hasan
- Department of Genetic Engineering and BiotechnologyUniversity of RajshahiRajshahiBangladesh
| | | | - Shahriar Zaman
- Miocrobiology Laboratory, Department of Genetic Engineering and BiotechnologyUniversity of RajshahiBangladesh
| | - Md. Abu Saleh
- Miocrobiology Laboratory, Department of Genetic Engineering and BiotechnologyUniversity of RajshahiBangladesh
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Kunz JM, Maloca P, Allemann A, Fasler D, Soysal S, Däster S, Kraljević M, Syeda G, Weixler B, Nebiker C, Ochs V, Droeser R, Walker HL, Bolli M, Müller B, Cattin P, Staubli SM. Assessment of resectability of pancreatic cancer using novel immersive high-performance virtual reality rendering of abdominal computed tomography and magnetic resonance imaging. Int J Comput Assist Radiol Surg 2024; 19:1677-1687. [PMID: 38252362 PMCID: PMC11365822 DOI: 10.1007/s11548-023-03048-0] [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: 03/07/2023] [Accepted: 12/11/2023] [Indexed: 01/23/2024]
Abstract
PURPOSE Virtual reality (VR) allows for an immersive and interactive analysis of imaging data such as computed tomography (CT) and magnetic resonance imaging (MRI). The aim of this study is to assess the comprehensibility of VR anatomy and its value in assessing resectability of pancreatic ductal adenocarcinoma (PDAC). METHODS This study assesses exposure to VR anatomy and evaluates the potential role of VR in assessing resectability of PDAC. Firstly, volumetric abdominal CT and MRI data were displayed in an immersive VR environment. Volunteering physicians were asked to identify anatomical landmarks in VR. In the second stage, experienced clinicians were asked to identify vascular involvement in a total of 12 CT and MRI scans displaying PDAC (2 resectable, 2 borderline resectable, and 2 locally advanced tumours per modality). Results were compared to 2D standard PACS viewing. RESULTS In VR visualisation of CT and MRI, the abdominal anatomical landmarks were recognised by all participants except the pancreas (30/34) in VR CT and the splenic (31/34) and common hepatic artery (18/34) in VR MRI, respectively. In VR CT, resectable, borderline resectable, and locally advanced PDAC were correctly identified in 22/24, 20/24 and 19/24 scans, respectively. Whereas, in VR MRI, resectable, borderline resectable, and locally advanced PDAC were correctly identified in 19/24, 19/24 and 21/24 scans, respectively. Interobserver agreement as measured by Fleiss κ was 0.7 for CT and 0.4 for MRI, respectively (p < 0.001). Scans were significantly assessed more accurately in VR CT than standard 2D PACS CT, with a median of 5.5 (IQR 4.75-6) and a median of 3 (IQR 2-3) correctly assessed out of 6 scans (p < 0.001). CONCLUSION VR enhanced visualisation of abdominal CT and MRI scan data provides intuitive handling and understanding of anatomy and might allow for more accurate staging of PDAC and could thus become a valuable adjunct in PDAC resectability assessment in the future.
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Affiliation(s)
- Julia Madlaina Kunz
- Faculty of Medicine, University of Basel, Klingelbergstrasse 61, 4056, Basel, Switzerland
| | - Peter Maloca
- Institute of Molecular and Clinical Ophthalmology Basel (IOB), Mittlere Strasse 91, 4031, Basel, Switzerland
- Department of Ophthalmology, University of Basel, 4031, Basel, Switzerland
- Moorfields Eye Hospital, NHS Foundation Trust, London, EC1V 2PD, UK
| | - Andreas Allemann
- Clarunis, University Center for Gastrointestinal and Liver Diseases, 4002, Basel, Switzerland
| | - David Fasler
- Department of Radiology St. Claraspital Basel, Kleinriehenstrasse 30, 4058, Basel, Switzerland
| | - Savas Soysal
- Clarunis, University Center for Gastrointestinal and Liver Diseases, 4002, Basel, Switzerland
| | - Silvio Däster
- Clarunis, University Center for Gastrointestinal and Liver Diseases, 4002, Basel, Switzerland
| | - Marko Kraljević
- Clarunis, University Center for Gastrointestinal and Liver Diseases, 4002, Basel, Switzerland
| | - Gulbahar Syeda
- Department of HPB Surgery and Liver Transplantation, Royal Free Hospital, London, NHS Foundation Trust, Pond Street, London, NW3 2Q, UK
| | - Benjamin Weixler
- Department of General, Visceral and Vascular Sugery, Charité Campus Benjamin Franklin, Hindenburgdamm 20, 12203, Berlin, Germany
| | - Christian Nebiker
- Surgical Department, Cantonal Hospital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - Vincent Ochs
- Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167c, 4123, Allschwil, Switzerland
| | - Raoul Droeser
- Clarunis, University Center for Gastrointestinal and Liver Diseases, 4002, Basel, Switzerland
| | | | - Martin Bolli
- Clarunis, University Center for Gastrointestinal and Liver Diseases, 4002, Basel, Switzerland
| | - Beat Müller
- Clarunis, University Center for Gastrointestinal and Liver Diseases, 4002, Basel, Switzerland
| | - Philippe Cattin
- Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167c, 4123, Allschwil, Switzerland
| | - Sebastian Manuel Staubli
- Faculty of Medicine, University of Basel, Klingelbergstrasse 61, 4056, Basel, Switzerland.
- Clarunis, University Center for Gastrointestinal and Liver Diseases, 4002, Basel, Switzerland.
- Department of HPB Surgery and Liver Transplantation, Royal Free Hospital, London, NHS Foundation Trust, Pond Street, London, NW3 2Q, UK.
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8
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Bugazia D, Al-Najjar E, Esmail A, Abdelrahim S, Abboud K, Abdelrahim A, Umoru G, Rayyan HA, Abudayyeh A, Al Moustafa AE, Abdelrahim M. Pancreatic ductal adenocarcinoma: the latest on diagnosis, molecular profiling, and systemic treatments. Front Oncol 2024; 14:1386699. [PMID: 39011469 PMCID: PMC11247645 DOI: 10.3389/fonc.2024.1386699] [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: 02/16/2024] [Accepted: 05/30/2024] [Indexed: 07/17/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is currently the fourth leading cause of death in the United States and is expected to be ranked second in the next 10 years due to poor prognosis and a rising incidence. Distant metastatic PDAC is associated with the worst prognosis among the different phases of PDAC. The diagnostic options for PDAC are convenient and available for staging, tumor response evaluation, and management of resectable or borderline resectable PDAC. However, imaging is crucial in PDAC diagnosis, monitoring, resectability appraisal, and response evaluation. The advancement of medical technologies is evolving, hence the use of imaging in PDAC treatment options has grown as well as the utilization of ctDNA as a tumor marker. Treatment options for metastatic PDAC are minimal with the primary goal of therapy limited to symptom relief or palliation, especially in patients with low functional capacity at the point of diagnosis. Molecular profiling has shown promising potential solutions that would push the treatment boundaries for patients with PDAC. In this review, we will discuss the latest updates from evidence-based guidelines regarding diagnosis, therapy response evaluation, prognosis, and surveillance, as well as illustrating novel therapies that have been recently investigated for PDAC, in addition to discussing the molecular profiling advances in PDAC.
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Affiliation(s)
- Doaa Bugazia
- Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Ebtesam Al-Najjar
- Section of GI Oncology, Department of Medical Oncology, Houston Methodist Cancer Center, Houston, TX, United States
| | - Abdullah Esmail
- Section of GI Oncology, Department of Medical Oncology, Houston Methodist Cancer Center, Houston, TX, United States
| | - Saifudeen Abdelrahim
- Challenge Early College HS, Houston Community College, Houston, TX, United States
| | - Karen Abboud
- Department of Pharmacy, Houston Methodist Hospital, Houston, TX, United States
| | | | - Godsfavour Umoru
- Department of Pharmacy, Houston Methodist Hospital, Houston, TX, United States
| | - Hashem A Rayyan
- Department of Medicine, Faculty of Medicine, The University of Jordan, Amman, Jordan
| | - Ala Abudayyeh
- Section of Nephrology, Division of Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | | | - Maen Abdelrahim
- Section of GI Oncology, Department of Medical Oncology, Houston Methodist Cancer Center, Houston, TX, United States
- Department of Medicine, Weill Cornell Medical College, New York, NY, United States
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Muaddi H, Kearse L, Warner S. Multimodal Approaches to Patient Selection for Pancreas Cancer Surgery. Curr Oncol 2024; 31:2260-2273. [PMID: 38668070 PMCID: PMC11049254 DOI: 10.3390/curroncol31040167] [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] [Received: 03/24/2024] [Revised: 04/05/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024] Open
Abstract
With an overall 5-year survival rate of 12%, pancreas ductal adenocarcinoma (PDAC) is an aggressive cancer that claims more than 50,000 patient lives each year in the United States alone. Even those few patients who undergo curative-intent resection with favorable pathology reports are likely to experience recurrence within the first two years after surgery and ultimately die from their cancer. We hypothesize that risk factors for these early recurrences can be identified with thorough preoperative staging, thus enabling proper patient selection for surgical resection and avoiding unnecessary harm. Herein, we review evidence supporting multidisciplinary and multimodality staging, comprehensive neoadjuvant treatment strategies, and optimal patient selection for curative-intent surgical resections. We further review data generated from our standardized approach at the Mayo Clinic and extrapolate to inform potential future investigations.
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Affiliation(s)
| | | | - Susanne Warner
- Division of Hepatobiliary and Pancreas Surgery, Mayo Clinic, Rochester, MN 55902, USA; (H.M.)
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Kaneko J, Hayashi Y, Kazami Y, Nishioka Y, Miyata A, Ichida A, Kawaguchi Y, Akamatsu N, Hasegawa K. Resection and reconstruction of the largest abdominal vein system (the inferior vena cava, hepatic, and portal vein): a narrative review. Transl Gastroenterol Hepatol 2024; 9:23. [PMID: 38716218 PMCID: PMC11074493 DOI: 10.21037/tgh-23-90] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 02/10/2024] [Indexed: 02/12/2025] Open
Abstract
BACKGROUND AND OBJECTIVE As tumors invade major abdominal veins, surgical procedures are transformed from simple and basic to complicated and challenging. In this narrative review, we focus on what is currently known and not known regarding the technical aspects of major abdominal venous resection and its reconstruction, patency, and oncologic benefit in a cross-cutting perspective. METHODS A systematic literature search was performed in PubMed and Semantic Scholar from inception up to October 18, 2023. We reviewed 106 papers by title, abstract, and full text regarding resection or reconstruction of the inferior vena cava, hepatic vein confluence, portal vein (PV), and middle hepatic vein (MHV) tributaries in living donor liver transplantation (LDLT) in a cross-cutting perspective. KEY CONTENT AND FINDINGS The oncologic benefit of aggressive hepatic vein resection with suitable reconstruction against adenocarcinoma remains unclear, and further studies are required to clarify this point. A superior mesenteric/PV resection is now a universal, indispensable, and effective procedure for pancreatic ductal adenocarcinoma. Although many case series using tailor-made autologous venous grafts have been reported, not only size mismatch but also additional surgical incisions and a longer operation time remain obstacles for venous reconstruction. The use of autologous alternative tissue remains only an alternative procedure because the patency rate of customized tubular conduit type to interpose or replace the resected vein is not known. Unlike arterial replacement, venous replacement using synthetic vascular grafts is still rarely reported and there are several inherent limitations except for reconstruction of tributaries of MHV in LDLT. CONCLUSIONS Various approaches to abdominal vein resection and replacement or reconstruction are technically feasible with satisfactory results. Synthetic vascular grafts may be appropriate but have a certain rate of complications.
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Affiliation(s)
- Junichi Kaneko
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yoshihiro Hayashi
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yusuke Kazami
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yujiro Nishioka
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akinori Miyata
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akihiko Ichida
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yoshikuni Kawaguchi
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Nobuhisa Akamatsu
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kiyoshi Hasegawa
- Hepato-Biliary-Pancreatic Surgery, Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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11
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Anghel C, Grasu MC, Anghel DA, Rusu-Munteanu GI, Dumitru RL, Lupescu IG. Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images. Diagnostics (Basel) 2024; 14:438. [PMID: 38396476 PMCID: PMC10887967 DOI: 10.3390/diagnostics14040438] [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: 01/10/2024] [Revised: 02/10/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) stands out as the predominant malignant neoplasm affecting the pancreas, characterized by a poor prognosis, in most cases patients being diagnosed in a nonresectable stage. Image-based artificial intelligence (AI) models implemented in tumor detection, segmentation, and classification could improve diagnosis with better treatment options and increased survival. This review included papers published in the last five years and describes the current trends in AI algorithms used in PDAC. We analyzed the applications of AI in the detection of PDAC, segmentation of the lesion, and classification algorithms used in differential diagnosis, prognosis, and histopathological and genomic prediction. The results show a lack of multi-institutional collaboration and stresses the need for bigger datasets in order for AI models to be implemented in a clinically relevant manner.
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Affiliation(s)
- Cristian Anghel
- Faculty of Medicine, Department of Medical Imaging and Interventional Radiology, Carol Davila University of Medicine and Pharmacy Bucharest, 020021 Bucharest, Romania; (C.A.); (R.L.D.); (I.G.L.)
- Department of Radiology and Medical Imaging, Fundeni Clinical Institute, 022328 Bucharest, Romania; (D.A.A.); (G.-I.R.-M.)
| | - Mugur Cristian Grasu
- Faculty of Medicine, Department of Medical Imaging and Interventional Radiology, Carol Davila University of Medicine and Pharmacy Bucharest, 020021 Bucharest, Romania; (C.A.); (R.L.D.); (I.G.L.)
- Department of Radiology and Medical Imaging, Fundeni Clinical Institute, 022328 Bucharest, Romania; (D.A.A.); (G.-I.R.-M.)
| | - Denisa Andreea Anghel
- Department of Radiology and Medical Imaging, Fundeni Clinical Institute, 022328 Bucharest, Romania; (D.A.A.); (G.-I.R.-M.)
| | - Gina-Ionela Rusu-Munteanu
- Department of Radiology and Medical Imaging, Fundeni Clinical Institute, 022328 Bucharest, Romania; (D.A.A.); (G.-I.R.-M.)
| | - Radu Lucian Dumitru
- Faculty of Medicine, Department of Medical Imaging and Interventional Radiology, Carol Davila University of Medicine and Pharmacy Bucharest, 020021 Bucharest, Romania; (C.A.); (R.L.D.); (I.G.L.)
- Department of Radiology and Medical Imaging, Fundeni Clinical Institute, 022328 Bucharest, Romania; (D.A.A.); (G.-I.R.-M.)
| | - Ioana Gabriela Lupescu
- Faculty of Medicine, Department of Medical Imaging and Interventional Radiology, Carol Davila University of Medicine and Pharmacy Bucharest, 020021 Bucharest, Romania; (C.A.); (R.L.D.); (I.G.L.)
- Department of Radiology and Medical Imaging, Fundeni Clinical Institute, 022328 Bucharest, Romania; (D.A.A.); (G.-I.R.-M.)
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12
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Duncan ZN, Summerlin D, West JT, Packard AT, Morgan DE, Galgano SJ. PET/MRI for evaluation of patients with pancreatic cancer. Abdom Radiol (NY) 2023; 48:3601-3609. [PMID: 37191756 DOI: 10.1007/s00261-023-03943-9] [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] [Received: 02/17/2023] [Revised: 04/25/2023] [Accepted: 04/26/2023] [Indexed: 05/17/2023]
Abstract
Pancreatic cancers are the third leading cause of cancer-related death in the USA and outcomes remain poor despite improvements in imaging and treatment paradigms. Currently, computed tomography (CT) and magnetic resonance imaging (MRI) are frequently utilized for staging and restaging of these malignancies, but positron emission tomography (PET)/CT can play a role in troubleshooting and improve whole-body staging. PET/MRI is a novel imaging modality that allows for simultaneous acquisition of PET and MRI images, leading to improved image quality and potential increased sensitivity. Early studies suggest that PET/MRI may play a larger role in pancreatic cancer imaging in future. This manuscript will briefly discuss current imaging approaches to pancreatic cancer and outline existing evidence and published data supporting the use of PET/MRI for pancreatic cancers.
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Affiliation(s)
- Zoey N Duncan
- University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA
| | - David Summerlin
- Department of Radiology, University of Alabama at Birmingham Medical Center, Birmingham, AL, USA
| | - Janelle T West
- Department of Radiology, University of Alabama at Birmingham Medical Center, Birmingham, AL, USA
| | | | - Desiree E Morgan
- Department of Radiology, University of Alabama at Birmingham Medical Center, Birmingham, AL, USA
| | - Samuel J Galgano
- Department of Radiology, University of Alabama at Birmingham Medical Center, Birmingham, AL, USA.
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Li B, Ni J, Chen F, Lu F, Zhang L, Wu W, Zhang Z. Evaluation of three-dimensional dual-energy CT cholangiopancreatography image quality in patients with pancreatobiliary dilatation: Comparison with conventional single-energy CT. Eur J Radiol Open 2023; 11:100537. [PMID: 37942123 PMCID: PMC10628547 DOI: 10.1016/j.ejro.2023.100537] [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: 07/14/2023] [Revised: 10/18/2023] [Accepted: 10/24/2023] [Indexed: 11/10/2023] Open
Abstract
Objective This study aimed to evaluate three-dimensional (3D) negative-contrast CT cholangiopancreatography (nCTCP) image quality using dual-energy CT (DECT) with iterative reconstruction (IR) technique in patients with pancreatobiliary dilatation compared with single-energy CT (SECT). Methods Of the patients, 67 and 56 underwent conventional SECT (SECT set) and DECT with IR technique (DECT set), respectively. All patients were retrospectively analyzed during the portal phase to compare objective image quality and other data including patient demographics, hepatic and pancreatic parenchymal enhancement, noise, and attenuation difference (AD) between dilated ducts and enhanced hepatic parenchyma, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and CT volume dose index (CTDIvol). Two radiologists used the five-point Likert scale to evaluate the subjective image quality of 3D nCTCP regarding image noise, sharpness of dilated ducts, and overall image quality. Statistical analyses used the Mann-Whitney U test. Results No significant difference in patient demographics in either CT set was showed during objective evaluation (p > 0.05). However, higher hepatic and pancreatic parenchymal enhancement, AD, SNR, and CNR and lower hepatic and pancreatic noise (p < 0.005) as well as CTDIvol (p = 0.005) on DECT than on SECT were observed. Higher mean grades on DECT than on SECT were showed for image noise (4.65 vs 3.92), sharpness of dilated ducts (4.52 vs 3.94), and overall image quality (4.45 vs 3.91; p < 0.001), respectively during subjective evaluation. Conclusion A higher overall image quality and lower radiation dose on 3D nCTCP can be obtained by DECT with IR technique than with conventional SECT in patients with pancreatobiliary dilatation.
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Affiliation(s)
- Bin Li
- Department of Radiology, Wuxi No.2 People’s Hospital, 68 Zhong shan Rd., Wuxi 214002, Jiangsu, PR China
| | - JianMing Ni
- Department of Radiology, Wuxi No.2 People’s Hospital, 68 Zhong shan Rd., Wuxi 214002, Jiangsu, PR China
| | - FangMing Chen
- Department of Radiology, Wuxi No.2 People’s Hospital, 68 Zhong shan Rd., Wuxi 214002, Jiangsu, PR China
| | - FengQi Lu
- Department of Radiology, Wuxi No.2 People’s Hospital, 68 Zhong shan Rd., Wuxi 214002, Jiangsu, PR China
| | - Lei Zhang
- Department of Radiology, Wuxi No.2 People’s Hospital, 68 Zhong shan Rd., Wuxi 214002, Jiangsu, PR China
| | - WenJuan Wu
- Department of Radiology, Wuxi No.2 People’s Hospital, 68 Zhong shan Rd., Wuxi 214002, Jiangsu, PR China
| | - ZhuiYang Zhang
- Department of Radiology, Wuxi No.2 People’s Hospital, 68 Zhong shan Rd., Wuxi 214002, Jiangsu, PR China
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Pacella G, Brunese MC, D’Imperio E, Rotondo M, Scacchi A, Carbone M, Guerra G. Pancreatic Ductal Adenocarcinoma: Update of CT-Based Radiomics Applications in the Pre-Surgical Prediction of the Risk of Post-Operative Fistula, Resectability Status and Prognosis. J Clin Med 2023; 12:7380. [PMID: 38068432 PMCID: PMC10707069 DOI: 10.3390/jcm12237380] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 11/21/2023] [Accepted: 11/23/2023] [Indexed: 09/10/2024] Open
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) is the seventh leading cause of cancer-related deaths worldwide. Surgical resection is the main driver to improving survival in resectable tumors, while neoadjuvant treatment based on chemotherapy (and radiotherapy) is the best option-treatment for a non-primally resectable disease. CT-based imaging has a central role in detecting, staging, and managing PDAC. As several authors have proposed radiomics for risk stratification in patients undergoing surgery for PADC, in this narrative review, we have explored the actual fields of interest of radiomics tools in PDAC built on pre-surgical imaging and clinical variables, to obtain more objective and reliable predictors. METHODS The PubMed database was searched for papers published in the English language no earlier than January 2018. RESULTS We found 301 studies, and 11 satisfied our research criteria. Of those included, four were on resectability status prediction, three on preoperative pancreatic fistula (POPF) prediction, and four on survival prediction. Most of the studies were retrospective. CONCLUSIONS It is possible to conclude that many performing models have been developed to get predictive information in pre-surgical evaluation. However, all the studies were retrospective, lacking further external validation in prospective and multicentric cohorts. Furthermore, the radiomics models and the expression of results should be standardized and automatized to be applicable in clinical practice.
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Affiliation(s)
- Giulia Pacella
- Department of Medicine and Health Science “V. Tiberio”, University of Molise, 86100 Campobasso, Italy; (G.P.)
| | - Maria Chiara Brunese
- Department of Medicine and Health Science “V. Tiberio”, University of Molise, 86100 Campobasso, Italy; (G.P.)
| | | | - Marco Rotondo
- Department of Medicine and Health Science “V. Tiberio”, University of Molise, 86100 Campobasso, Italy; (G.P.)
| | - Andrea Scacchi
- General Surgery Unit, University of Milano-Bicocca, 20126 Milan, Italy
| | - Mattia Carbone
- San Giovanni di Dio e Ruggi d’Aragona Hospital, 84131 Salerno, Italy;
| | - Germano Guerra
- Department of Medicine and Health Science “V. Tiberio”, University of Molise, 86100 Campobasso, Italy; (G.P.)
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Lee T, Yoon JH, Park JY, Lee J, Choi JW, Ahn C, Lee JM. Deep learning-based iodine contrast-augmenting algorithm for low-contrast-dose liver CT to assess hypovascular hepatic metastasis. Abdom Radiol (NY) 2023; 48:3430-3440. [PMID: 37704805 DOI: 10.1007/s00261-023-04039-0] [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] [Received: 07/28/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 09/15/2023]
Abstract
PURPOSE To investigate the image quality and diagnostic performance of low-contrast-dose liver CT using a deep learning-based iodine contrast-augmenting algorithm (DLICA) for hypovascular hepatic metastases. METHODS This retrospective study included 128 patients who underwent contrast-enhanced dual-energy CT for hepatic metastasis surveillance between July 2019 and June 2022 using a 30% reduced iodine contrast dose in the portal phase. Three image types were reconstructed: 50-keV virtual monoenergetic images (50-keV VMI); linearly blended images simulating 120-kVp images (120-kVp); and post-processed 120-kVp images using DLICA (DLICA 120-kVp). Three reviewers evaluated lesion conspicuity, image contrast, and subjective image noise. We also measured image noise, contrast-to-noise ratios (CNRs), and signal-to-noise ratios (SNRs). The diagnostic performance for hepatic metastases was evaluated using a jackknife alternative free-response receiver operating characteristic method with the consensus of two independent radiologists as the reference standard. RESULTS DLICA 120-kVp demonstrated significantly higher CNR of lesions to liver (5.7 ± 3.1 vs. 3.8 ± 2.1 vs. 3.8 ± 2.1) and higher SNR compared with 50-keV VMI and 120-kVp (p < 0.001 for all). DLICA 120-kVp had significantly lower image noise than 50-kVp VMI for all regions (p < 0.001 for all). DLICA 120-kVp also exhibited superior lesion conspicuity (4.0 [3.3-4.3] vs. 3.7 [3.0-4.0] vs. 3.7 [3.0-4.0]), higher image contrast, and lower subjective image noise compared with 50-keV VMI and 120-kVp (p < 0.001 for all). Although there was no significant difference in the figure of merit for lesion diagnosis among the three methods (p = 0.11), DLICA 120-kVp had a significantly higher figure of merit for lesions with a diameter < 20 mm than 50-keV VMI (0.677 vs. 0.648, p = 0.007). On a per-lesion basis, DLICA 120-kVp also demonstrated higher sensitivity than the 50-keV VMI (81.2% vs. 72.9%, p < 0.001). The specificities per lesion were not significantly different among the three algorithms (p = 0.15). CONCLUSION DLICA at 120-kVp provided superior lesion conspicuity and image quality and similar diagnostic performance for hypovascular hepatic metastases compared with 50-keV VMI.
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Affiliation(s)
- Taehee Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jeong Hee Yoon
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Jin Young Park
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Jihyuk Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jae Won Choi
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Armed Forces Yangju Hospital, Yangju, Republic of Korea
| | - Chulkyun Ahn
- Department of Transdisciplinary Studies, Program in Biomedical Radiation Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
- ClariPi Research, Seoul, Republic of Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
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Chu LC, Ahmed T, Blanco A, Javed A, Weisberg EM, Kawamoto S, Hruban RH, Kinzler KW, Vogelstein B, Fishman EK. Radiologists' Expectations of Artificial Intelligence in Pancreatic Cancer Imaging: How Good Is Good Enough? J Comput Assist Tomogr 2023; 47:845-849. [PMID: 37948357 PMCID: PMC10823576 DOI: 10.1097/rct.0000000000001503] [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] [Indexed: 07/29/2023]
Abstract
BACKGROUND Existing (artificial intelligence [AI]) tools in radiology are modeled without necessarily considering the expectations and experience of the end user-the radiologist. The literature is scarce on the tangible parameters that AI capabilities need to meet for radiologists to consider them useful tools. OBJECTIVE The purpose of this study is to explore radiologists' attitudes toward AI tools in pancreatic cancer imaging and to quantitatively assess their expectations of these tools. METHODS A link to the survey was posted on the www.ctisus.com website, advertised in the www.ctisus.com email newsletter, and publicized on LinkedIn, Facebook, and Twitter accounts. This survey asked participants about their demographics, practice, and current attitudes toward AI. They were also asked about their expectations of what constitutes a clinically useful AI tool. The survey consisted of 17 questions, which included 9 multiple choice questions, 2 Likert scale questions, 4 binary (yes/no) questions, 1 rank order question, and 1 free text question. RESULTS A total of 161 respondents completed the survey, yielding a response rate of 46.3% of the total 348 clicks on the survey link. The minimum acceptable sensitivity of an AI program for the detection of pancreatic cancer chosen by most respondents was either 90% or 95% at a specificity of 95%. The minimum size of pancreatic cancer that most respondents would find an AI useful at detecting was 5 mm. Respondents preferred AI tools that demonstrated greater sensitivity over those with greater specificity. Over half of respondents anticipated incorporating AI tools into their clinical practice within the next 5 years. CONCLUSION Radiologists are open to the idea of integrating AI-based tools and have high expectations regarding the performance of these tools. Consideration of radiologists' input is important to contextualize expectations and optimize clinical adoption of existing and future AI tools.
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Affiliation(s)
- Linda C. Chu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland
| | - Taha Ahmed
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland
| | - Alejandra Blanco
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland
| | - Ammar Javed
- Department of Surgery, New York University Grossman School of Medicine, New York, NY
| | - Edmund M. Weisberg
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland
| | - Satomi Kawamoto
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland
| | - Ralph H. Hruban
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Kenneth W. Kinzler
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Bert Vogelstein
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Elliot K Fishman
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland
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17
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Jajodia A, Wang A, Alabousi M, Wilks C, Kulkarni A, van der Pol CB. MRI vs. CT for pancreatic adenocarcinoma vascular invasion: comparative diagnostic test accuracy systematic review and meta-analysis. Eur Radiol 2023; 33:6883-6891. [PMID: 37083741 DOI: 10.1007/s00330-023-09659-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 01/26/2023] [Accepted: 02/22/2023] [Indexed: 04/22/2023]
Abstract
OBJECTIVES To perform a systematic review comparing the diagnostic accuracy of MRI vs. CT for assessing pancreatic ductal adenocarcinoma (PDAC) vascular invasion. METHODS MEDLINE, EMBASE, Cochrane Central, and Scopus were searched until December 2021 for diagnostic accuracy studies comparing MRI vs. CT to evaluate vascular invasion of pathologically confirmed PDAC in the same patients. Findings on resection or exploratory laparotomy were the preferred reference standard. Data extraction, risk of bias, and applicability assessment were performed by two authors using the Quality Assessment of Diagnostic Accuracy Studies-Comparative Tool. Bivariate random-effects meta-analysis and meta-regression were performed with 95% confidence intervals (95% CI). RESULTS Three studies were included assessing 474 vessels without vascular invasion and 65 with vascular invasion in 107 patients. All patients were imaged using MRI at ≥ 1.5 T and a pancreatic protocol CT. No difference was shown between MRI and CT for diagnosing PDAC vascular invasion: MRI/CT sensitivity (95% CI) were 71% (47-87%)/74% (56-86%), and specificity were 97% (94-99%)/97% (94-98%). Sources of bias included selection bias from only a subset of CT patients undergoing MRI and verification bias from patients with unresectable disease not confirmed on surgery. No patients received neoadjuvant therapy prior to staging. CONCLUSIONS Based on limited data, no difference was observed between MRI and pancreatic protocol CT for PDAC vascular invasion assessment. MRI may be an adequate substitute for pancreatic protocol CT in some patients, particularly those who have already had a single-phase CT. Larger and more recent cohort studies at low risk of bias, including patients who have received neoadjuvant therapy, are needed. CLINICAL RELEVANCE STATEMENT Abdominal MRI performed similarly to pancreatic protocol CT at assessing pancreatic ductal adenocarcinoma vascular invasion, suggesting local staging is adequate in some patients using MRI. More data are needed using larger, more recent cohorts including patients with neoadjuvant treatment. KEY POINTS • Based on limited data, no difference was found between MRI and pancreatic protocol CT sensitivity and specificity for diagnosing PDAC vascular invasion (p = 0.81, 0.73 respectively). • Risk of bias could be reduced in future PDAC MRI vs CT comparative diagnostic test accuracy research by ensuring all enrolled patients undergo both imaging modalities being compared in random order and regardless of the findings on either modality. • More studies are needed that directly compare the diagnostic performance of MRI and CT for PDAC staging after neoadjuvant therapy.
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Affiliation(s)
- Ankush Jajodia
- Department of Radiology, McMaster University, Hamilton Health Sciences, Hamilton, Canada
| | - Ashley Wang
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Canada
| | - Mostafa Alabousi
- Joint Department of Medical Imaging, University of Toronto, University Health Network, Toronto, Canada
| | - Christopher Wilks
- Department of Radiology, McMaster University, Hamilton Health Sciences, Hamilton, Canada
| | - Ameya Kulkarni
- Department of Radiology, McMaster University, Hamilton Health Sciences, Hamilton, Canada
- Department of Diagnostic Imaging, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, 711 Concession Street, Hamilton, ON, L8V 1C3, Canada
| | - Christian B van der Pol
- Department of Radiology, McMaster University, Hamilton Health Sciences, Hamilton, Canada.
- Department of Diagnostic Imaging, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, 711 Concession Street, Hamilton, ON, L8V 1C3, Canada.
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Xie N, Fan X, Chen D, Chen J, Yu H, He M, Liu H, Yin X, Li B, Wang H. Peritumoral and Intratumoral Texture Features Based on Multiparametric MRI and Multiple Machine Learning Methods to Preoperatively Evaluate the Pathological Outcomes of Pancreatic Cancer. J Magn Reson Imaging 2023; 58:379-391. [PMID: 36426965 DOI: 10.1002/jmri.28538] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/13/2022] [Accepted: 11/14/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Radiomics-based preoperative evaluation of lymph node metastasis (LNM) and histological grade (HG) might facilitate the decision-making for pancreatic cancer and further efforts are needed to develop effective models. PURPOSE To develop multiparametric MRI (MP-MRI)-based radiomics models to evaluate LNM and HG. STUDY TYPE Retrospective. POPULATION The pancreatic cancer patients from the main center (n = 126) were assigned to the training and validation sets at a 4:1 ratio. The patients from the other center (n = 40) served as external test sets. FIELD STRENGTH/SEQUENCE A 3.0 T and 1.5 T/T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast enhancement T1-weighted imaging. ASSESSMENT A total of 10,686 peritumoral and intratumoral radiomics features were extracted which contained first-order, shape-based, and texture features. The following three-step method was applied to reduce the feature dimensionality: SelectKBest (a function from scikit-learn package), least absolute shrinkage and selection operator (LASSO), and recursive feature elimination based on random forest (RFE-RF). Six classifiers (random forest, logistic regression, support vector machine, K-nearest neighbor, decision tree, and XGBOOST) were trained and selected based on their performance to construct the clinical, radiomics, and combination models. STATISTICAL TESTS Delong's test was used to compare the models' performance. P value less than 0.05 was considered significant. RESULTS Twelve significant features for LNM and 11 features for HG were obtained. Random forest and logistic regression performed better than the other classifiers in evaluating LNM and HG, respectively, according to the surgical pathological results. The best performance was obtained with the models that combined peritumoral and intratumoral features with area under curve (AUC) values of 0.944 and 0.892 in the validation and external test sets for HG and 0.924 and 0.875 for LNM. DATA CONCLUSION Radiomics holds the potential to evaluate LNM and HG of pancreatic cancer. The combination of peritumoral and intratumoral features will make models more accurate. EVIDENCE LEVEL 4. TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- Ni Xie
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Pancreatic Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuhui Fan
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- R & D Center of Medical Artificial Intelligence and Medical Engineering, Shanghai General Hospital, Shanghai, China
- National Center for Translational Medicine (Shanghai), Shanghai, China
| | - Desheng Chen
- Department of General Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingwen Chen
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- R & D Center of Medical Artificial Intelligence and Medical Engineering, Shanghai General Hospital, Shanghai, China
- National Center for Translational Medicine (Shanghai), Shanghai, China
| | - Hongwei Yu
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- R & D Center of Medical Artificial Intelligence and Medical Engineering, Shanghai General Hospital, Shanghai, China
- National Center for Translational Medicine (Shanghai), Shanghai, China
| | - Meijuan He
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- R & D Center of Medical Artificial Intelligence and Medical Engineering, Shanghai General Hospital, Shanghai, China
- National Center for Translational Medicine (Shanghai), Shanghai, China
| | - Hao Liu
- Yizhun Medical AI Technology Co. Ltd., Beijing, China
| | - Xiaorui Yin
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- R & D Center of Medical Artificial Intelligence and Medical Engineering, Shanghai General Hospital, Shanghai, China
| | - Baiwen Li
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Pancreatic Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Han Wang
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- R & D Center of Medical Artificial Intelligence and Medical Engineering, Shanghai General Hospital, Shanghai, China
- National Center for Translational Medicine (Shanghai), Shanghai, China
- Jiading Branch of Shanghai General Hospital, Shanghai, China
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19
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Megibow AJ. Pancreatic Cysts: Radiology. Gastrointest Endosc Clin N Am 2023; 33:519-531. [PMID: 37245933 DOI: 10.1016/j.giec.2023.03.008] [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: 05/30/2023]
Abstract
This article reviews the types of pancreatic cysts encountered in Radiologic practice. It summarizes the malignancy risk of each of the following: serous cystadenoma, mucinous cystic tumor, intraductal papillary mucinous neoplasm main duct and side branch, and some miscellaneous cysts such as neuroendocrine tumor and solid pseudopapillary epithelial neoplasm. Specific reporting recommendations are given. The choice between radiology follow-up versus endoscopic analysis is discussed.
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Affiliation(s)
- Alec J Megibow
- Department of Radiology, NYU-Langone Health, 550 1st Avenue, Room HCC 232, New York, NY 10016, USA.
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20
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Vats N, Mayer P, Kortes F, Klauß M, Grenacher L, Stiller W, Kauczor HU, Skornitzke S. Evaluation and timing optimization of CT perfusion first pass analysis in comparison to maximum slope model in pancreatic adenocarcinoma. Sci Rep 2023; 13:10595. [PMID: 37391443 PMCID: PMC10313720 DOI: 10.1038/s41598-023-37381-w] [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: 12/15/2022] [Accepted: 06/21/2023] [Indexed: 07/02/2023] Open
Abstract
For implementation, performance evaluation and timing optimization of CT perfusion first pass analysis (FPA) by correlation with maximum slope model (MSM) in pancreatic adenocarcinoma, dynamic CT perfusion acquisitions of 34 time-points were performed in 16 pancreatic adenocarcinoma patients. Regions of interest were marked in both parenchyma and carcinoma. FPA, a low radiation exposure CT perfusion technique, was implemented. Blood flow (BF) perfusion maps were calculated using FPA and MSM. Pearson's correlation between FPA and MSM was calculated at each evaluated time-point to determine optimum timing for FPA. Differences in BF between parenchyma and carcinoma were calculated. Average BF for MSM was 106.8 ± 41.5 ml/100 ml/min in parenchyma and 42.0 ± 24.8 ml/100 ml/min in carcinoma, respectively. For FPA, values ranged from 85.6 ± 37.5 ml/100 ml/min to 117.7 ± 44.5 ml/100 ml/min in parenchyma and from 27.3 ± 18.8 ml/100 ml/min to 39.5 ± 26.6 ml/100 ml/min in carcinoma, depending on acquisition timing. A significant difference (p value < 0.0001) between carcinoma and parenchyma was observed at all acquisition times based on FPA measurements. FPA shows high correlation with MSM (r > 0.90) and 94% reduction in the radiation dose compared to MSM. CT perfusion FPA, where the first scan is obtained after the arterial input function exceeds a threshold of 120 HU, followed by a second scan after 15.5-20.0 s, could be used as a potential imaging biomarker with low radiation exposure for diagnosing and evaluating pancreatic carcinoma in clinical practice, showing high correlation with MSM and the ability to differentiate between parenchyma and carcinoma.
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Affiliation(s)
- Neha Vats
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
| | - Philipp Mayer
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
| | - Franziska Kortes
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
- Radiology Rhein-Neckar, Bodelschwinghstraße 10, 68723, Schwetzingen, Germany
| | - Miriam Klauß
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
| | - Lars Grenacher
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
- Conradia Radiology and Medical Prevention, Conradia Radiologie München, Augustenstraße 115, 80798, Munich, Germany
| | - Wolfram Stiller
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
| | - Stephan Skornitzke
- Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany.
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Yao Y, Chen Y, Gou S, Chen S, Zhang X, Tong N. Auto-segmentation of pancreatic tumor in multi-modal image using transferred DSMask R-CNN network. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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22
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Li B, Lu F, Ni J, Wu W, Xu H, Zhang Z. Preoperative evaluation of malignant pancreatobiliary obstruction: A novel technique for multiphase fusion 3D CT images. Eur J Radiol Open 2022; 10:100464. [PMID: 36545431 PMCID: PMC9761364 DOI: 10.1016/j.ejro.2022.100464] [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: 06/16/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022] Open
Abstract
The purpose of this article is to describe a novel technique of multiphase fusion three-dimensional (3D) images in patients with malignant pancreatobiliary obstruction. Multiphase fusion 3D images of CT arteriography, portovenography and hepatic venography combined with negative-contrast CT cholangiopancreatography can be done with enhanced multiphase CT scan using intravenous contrast agent at once. This technique may be feasible for one-stop evaluation of malignant pancreatobiliary obstruction.
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23
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Javed AA, Young RWC, Habib JR, Kinny-Köster B, Cohen SM, Fishman EK, Wolfgang CL. Cinematic Rendering: Novel Tool for Improving Pancreatic Cancer Surgical Planning. Curr Probl Diagn Radiol 2022; 51:878-883. [PMID: 35595587 DOI: 10.1067/j.cpradiol.2022.04.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 03/24/2022] [Accepted: 04/18/2022] [Indexed: 12/17/2023]
Abstract
Pancreatic ductal adenocarcinoma is the third-leading cause of all cancer-related deaths in the US. While 20% of patients have resectable disease at diagnosis, improved control of systemic disease using effective chemotherapeutic regimens allows for aggressive operations involving complex vascular resection and reconstruction. A pancreas protocol computed tomography (PPCT) is the gold standard imaging modality in determining local resectability (degree of tumor-vessel involvement), however, it is limited by the inter-operator variability. While post-processing-3D-rendering helps, it does not allow for real-time dynamic assessment of resectability. A recent development in post-process-rendering called cinematic rendering (CR) overcomes this by utilizing advanced light modeling to generate photorealistic 3D images with enhanced details. Cinematic rendering allows for nuanced visualization of areas of interest. Our preliminary experience, as one of the first centers to incorporate the routine use of CR, has proven very useful in surgical planning. For local determination of resectability, vascular mapping allows for accurate assessment of major arteries and the portovenous system. For the portovenous anatomy it assists in determining the optimal surgical approach (extent of resection, appropriate technique for reconstruction, and need for mesocaval shunting). For arterial anatomy, vessel encasement either represents dissectible involvement via periadventitial dissection or true vessel invasion that is unresectable. CR could potentially provide superior ability than traditional PPCT to discern between the two. Additionally, CR allows for better 3D visualization of arterial anatomic variants which, if not appreciated preoperatively, increases risk of intraoperative ischemia and postoperative complications. Lastly, CR could help avoid unnecessary surgery by enhanced identification of occult metastatic disease that is metastatic disease that is otherwise not appreciated on a standard PPCT.
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Affiliation(s)
- Ammar A Javed
- Department of Surgery, The Johns Hopkins School of Medicine, Baltimore, MD; Department of Surgery, NYU Grossman School of Medicine, New York, NY
| | - Robert W C Young
- Department of Surgery, The Johns Hopkins School of Medicine, Baltimore, MD
| | - Joseph R Habib
- Department of Surgery, The Johns Hopkins School of Medicine, Baltimore, MD
| | - Benedict Kinny-Köster
- Department of Surgery, The Johns Hopkins School of Medicine, Baltimore, MD; Department of Surgery, NYU Grossman School of Medicine, New York, NY
| | - Steven M Cohen
- Department of Surgery, NYU Grossman School of Medicine, New York, NY
| | - Elliot K Fishman
- Department of Radiology, The Johns Hopkins School of Medicine, Baltimore, MD
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24
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Laino ME, Ammirabile A, Lofino L, Mannelli L, Fiz F, Francone M, Chiti A, Saba L, Orlandi MA, Savevski V. Artificial Intelligence Applied to Pancreatic Imaging: A Narrative Review. Healthcare (Basel) 2022; 10:1511. [PMID: 36011168 PMCID: PMC9408381 DOI: 10.3390/healthcare10081511] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/31/2022] [Accepted: 08/08/2022] [Indexed: 12/19/2022] Open
Abstract
The diagnosis, evaluation, and treatment planning of pancreatic pathologies usually require the combined use of different imaging modalities, mainly, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Artificial intelligence (AI) has the potential to transform the clinical practice of medical imaging and has been applied to various radiological techniques for different purposes, such as segmentation, lesion detection, characterization, risk stratification, or prediction of response to treatments. The aim of the present narrative review is to assess the available literature on the role of AI applied to pancreatic imaging. Up to now, the use of computer-aided diagnosis (CAD) and radiomics in pancreatic imaging has proven to be useful for both non-oncological and oncological purposes and represents a promising tool for personalized approaches to patients. Although great developments have occurred in recent years, it is important to address the obstacles that still need to be overcome before these technologies can be implemented into our clinical routine, mainly considering the heterogeneity among studies.
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Affiliation(s)
- Maria Elena Laino
- Artificial Intelligence Center, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy
| | - Angela Ammirabile
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy
- Department of Diagnostic and Interventional Radiology, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy
| | - Ludovica Lofino
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy
- Department of Diagnostic and Interventional Radiology, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy
| | | | - Francesco Fiz
- Nuclear Medicine Unit, Department of Diagnostic Imaging, E.O. Ospedali Galliera, 56321 Genoa, Italy
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital, 72074 Tübingen, Germany
| | - Marco Francone
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy
- Department of Diagnostic and Interventional Radiology, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy
| | - Arturo Chiti
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy
- Department of Nuclear Medicine, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy
| | - Luca Saba
- Department of Radiology, University of Cagliari, 09124 Cagliari, Italy
| | | | - Victor Savevski
- Artificial Intelligence Center, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy
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Xu J, Wang S, Wang X, Wang Y, Xue H, Yan J, Xu M, Jin Z. Effects of contrast enhancement boost postprocessing technique in combination with different reconstruction algorithms on the image quality of abdominal CT angiography. Eur J Radiol 2022; 154:110388. [DOI: 10.1016/j.ejrad.2022.110388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 05/22/2022] [Accepted: 05/30/2022] [Indexed: 12/24/2022]
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Farrukh J, Balasubramaniam R, James A, Wadhwani SS, Albazaz R. Pancreatic adenocarcinoma: imaging techniques for diagnosis and management. Br J Hosp Med (Lond) 2022; 83:1-12. [PMID: 35653327 DOI: 10.12968/hmed.2022.0065] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2023]
Abstract
Pancreatic cancer is a leading cause of death from cancer but only a minority of patients with pancreatic ductal adenocarcinomas are eligible for curative resection. The increasing role of neoadjuvant therapy provides hope of improving outcomes. However, progress is also reliant on advances in imaging that can identify disease earlier and accurately assess treatment response. Computed tomography remains the cornerstone in evaluation of resectability, offering excellent spatial resolution. However, in high-risk patients, additional magnetic resonance imaging and positron emission tomography-computed tomography may further guide treatment decisions. Conventional computed tomography can be limited in its ability to determine disease response after neoadjuvant therapy. Dual-energy computed tomography and computed tomography or magnetic resonance imaging perfusion studies emerging as potentially better alternatives. Combined with pioneering advances in radiomic analysis, these modalities also show promise in analysing tumour heterogeneity and thereby more accurately predicting outcomes. This article reviews these imaging techniques.
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Affiliation(s)
- Jawaad Farrukh
- Department of Radiology, Royal Stoke University Hospital, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK
| | - Ravivarma Balasubramaniam
- Department of Radiology, Royal Stoke University Hospital, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK
| | - Anitha James
- Department of Radiology, Royal Stoke University Hospital, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK
| | - Sharan S Wadhwani
- Department of Radiology, Queen Elizabeth Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Raneem Albazaz
- Department of Radiology, St James's University Hospital, The Leeds Teaching Hospitals NHS Trust, Leeds, UK
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Influence of Baseline CT Body Composition Parameters on Survival in Patients with Pancreatic Adenocarcinoma. J Clin Med 2022; 11:jcm11092356. [PMID: 35566483 PMCID: PMC9105849 DOI: 10.3390/jcm11092356] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 04/20/2022] [Accepted: 04/21/2022] [Indexed: 01/06/2023] Open
Abstract
Pancreatic cancer is the seventh leading cause of cancer death in both sexes. The aim of this study is to analyze baseline CT body composition using artificial intelligence to identify possible imaging predictors of survival. We retrospectively included 103 patients. First, the presence of surgical treatment and cut-off values for sarcopenia and obesity served as independent variates. Second, the presence of surgery, subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle index (SMI) served as independent variates. Cox regression analysis was performed for 1-year, 2-year, and 3-year survival. Possible differences between patients undergoing surgical versus nonsurgical treatment were analyzed. Presence of surgery significantly predicted 1-year, 2-year, and 3-year survival (p = 0.01, <0.001, and <0.001, respectively). Across the follow-up periods of 1-year, 2-year, and 3-year survival, the presence of sarcopenia became an equally important predictor of survival (p = 0.25, 0.07, and <0.001, respectively). Additionally, increased VAT predicted 2-year and 3-year survival (p = 0.02 and 0.04, respectively). The impact of sarcopenia on 3-year survival was higher in the surgical treatment group (p = 0.02 and odds ratio = 2.57) compared with the nonsurgical treatment group (p = 0.04 and odds ratio = 1.92). Fittingly, a lower SMI significantly affected 3-year survival only in patients who underwent surgery (p = 0.02). Especially if surgery is performed, AI-derived sarcopenia and reduced muscle mass are unfavorable imaging predictors.
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Zakaria A, Al-Share B, Klapman JB, Dam A. The Role of Endoscopic Ultrasonography in the Diagnosis and Staging of Pancreatic Cancer. Cancers (Basel) 2022; 14:1373. [PMID: 35326524 PMCID: PMC8946253 DOI: 10.3390/cancers14061373] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/05/2022] [Accepted: 03/07/2022] [Indexed: 02/06/2023] Open
Abstract
Pancreatic cancer is the fourth leading cause of cancer-related death and the second gastrointestinal cancer-related death in the United States. Early detection and accurate diagnosis and staging of pancreatic cancer are paramount in guiding treatment plans, as surgical resection can provide the only potential cure for this disease. The overall prognosis of pancreatic cancer is poor even in patients with resectable disease. The 5-year survival after surgical resection is ~10% in node-positive disease compared to ~30% in node-negative disease. The advancement of imaging studies and the multidisciplinary approach involving radiologists, gastroenterologists, advanced endoscopists, medical, radiation, and surgical oncologists have a major impact on the management of pancreatic cancer. Endoscopic ultrasonography is essential in the diagnosis by obtaining tissue (FNA or FNB) and in the loco-regional staging of the disease. The advancement in EUS techniques has made this modality a critical adjunct in the management process of pancreatic cancer. In this review article, we provide an overall description of the role of endoscopic ultrasonography in the diagnosis and staging of pancreatic cancer.
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Affiliation(s)
- Ali Zakaria
- Department of Gastroenterology-Advanced Endoscopy, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA; (J.B.K.); (A.D.)
| | - Bayan Al-Share
- Department of Hematology and Oncology, Karmanos Cancer Center, Wayne State University, Detroit, MI 48201, USA;
| | - Jason B. Klapman
- Department of Gastroenterology-Advanced Endoscopy, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA; (J.B.K.); (A.D.)
| | - Aamir Dam
- Department of Gastroenterology-Advanced Endoscopy, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA; (J.B.K.); (A.D.)
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da Costa WL, Tran Cao HS, Gu X, Massarweh NN. Bayesian Approach to Understand the Association Between Treatment Down-staging and Survival for Patients With Pancreatic Adenocarcinoma. Ann Surg 2022; 275:415-421. [PMID: 35120060 DOI: 10.1097/sla.0000000000005249] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVE To evaluate the association between staging concordance, treatment sequencing, and response to neoadjuvant therapy (NAT) on the survival of patients with pancreatic ductal adenocarcinoma (PDAC). SUMMARY OF BACKGROUND DATA NAT is increasingly utilized in the management of patients with PDAC, but it is unclear whether its benefit is contingent on tumor down-staging. METHODS This was a cohort study of stage I-III PDAC patients in the National Cancer Database (2006-2015) treated with upfront resection or NAT followed by surgery. We determined staging concordance using patients' clinical and pathological staging data. For NAT patients, we used Bayesian analysis to ascertain staging concordance accounting for down-staging. RESULTS Among 16,597 patients treated at 979 hospitals, 13,982 had an upfront resection and 2,615 NAT followed by surgery. Overall survival (OS) at 5-years ranged from 26.0% (95% CI 24.9%-27.1%) among cT1-2N0 patients to 18.6% (17.9%-19.2%) among cT1-3N+ ones. Patients with cT3-4 or cN+ tumors had improved OS after NAT compared to upfront surgery (all p< 0.001), while there was no difference among patients with cT1-2N0 (P = 0.16) disease. Relative to accurately staged cT1-2-3N+ or cT4 patients treated with upfront surgery, NAT was associated with a lower risk of death [HR 0.46 (0.37-0.57) for N+; HR 0.56 (0.40-0.77) for T4 disease], even among those without tumor down-staging [HR 0.81 (0.73-0.90) for N+; HR 0.48 (0.39-0.60) for T4]. CONCLUSIONS NAT is associated with improved survival for PDAC, particularly for patients with more advanced disease and regardless of down-staging. Consideration should be given to recommending NAT for all PDAC patients.
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Affiliation(s)
- Wilson Luiz da Costa
- Department of Medicine, Epidemiology, and Population Sciences, Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX
| | - Hop S Tran Cao
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Xiangjun Gu
- Department of Medicine, Epidemiology, and Population Sciences, Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX
| | - Nader N Massarweh
- Atlanta VA Health Care System, Decatur, GA
- Division of Surgical Oncology, Department of Surgery, Emory University School of Medicine, Atlanta, GA
- Department of Surgery, Morehouse School of Medicine, Atlanta, GA
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30
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Karmazanovsky GG, Abuladze LR. Computer-assisted and magnetic resonance imaging assessment of tumors and tumor invasion of the duodenum. ANNALY KHIRURGICHESKOY GEPATOLOGII = ANNALS OF HPB SURGERY 2022; 27:12-21. [DOI: 10.16931/1995-5464.2022-1-12-21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2025]
Abstract
Aim: To present the computed tomography and magnetic resonance imaging assessments of benign and malignant duodenal tumors, pancreatic head adenocarcinoma invading the duodenum, and duodenal dystrophy.Methods: We searched for scientific papers and clinical guidelines in the information and analytical databases PubMed and Google Scholar from the 2013–2021 period using the following search terms: duodenal neoplasms, adenocarcinoma, duodenum, duodenal neuroendocrine tumors, duodenal adenoma, gastrointestinal stromal tumor, cholangiocarcinoma, radiology, magnetic resonance imaging, computed tomography, pancreatic head cancer. Then, we examined the reference lists of all the identified studies to collate the papers that would meet the eligibility criteria.Results: We analyzed 1494 articles, 22 of which were included in our review. From the papers published within 1992–2021, 35 articles from the reference lists were additionally included. Based on the search results, several domains of articles were clustered; the articles from those domains were reviewed and evaluated that involved the abovementioned diagnostic features.Conclusion: The early diagnosis and selection of appropriate management methods remain extremely relevant for the treatment of duodenal tumors, and hence, require careful attention from diagnosticians and clinicians.
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Affiliation(s)
- G. G. Karmazanovsky
- A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation; N.I. Pirogov Russian National Research Medical University of the Ministry of Healthcare of the Russian
Federation
| | - L. R. Abuladze
- A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of Moscow
Healthcare Department
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31
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Maffei ME. Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics. Int J Mol Sci 2022; 23:1339. [PMID: 35163262 PMCID: PMC8835851 DOI: 10.3390/ijms23031339] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/22/2022] [Accepted: 01/22/2022] [Indexed: 02/08/2023] Open
Abstract
Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.
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Affiliation(s)
- Massimo E Maffei
- Department Life Sciences and Systems Biology, University of Turin, Via Quarello 15/a, 10135 Turin, Italy
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32
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Wang L, Nie F, Dong T, Yin C, Li M, Li Y. Nonhypovascular pancreatic ductal adenocarcinomas: CEUS imaging findings and differentiation from other types of solid pancreatic lesions. Clin Hemorheol Microcirc 2022; 81:163-176. [PMID: 35253738 DOI: 10.3233/ch-221397] [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: 11/15/2022]
Abstract
OBJECTIVES To observe and assess the diagnostic value of contrast-enhanced ultrasound (CEUS) in patients with iso-/hypervascular solid pancreatic lesions. METHODS 70 pancreatic lesions (all confirmed by surgery or biopsy pathology) that manifested iso-/hyperenhancement on CEUS were retrospectively studied from January 2018 to January 2022, including 24 pancreatic ductal adenocarcinomas (PDAC), 15 mass-forming pancreatitis (MFP), 24 pancreatic neuroendocrine tumors (PNET) (14 hyper-PNETs, 10 iso-PNETs), and 7 solid pseudopapillary tumors of pancreas (SPTP). 65 pancreatic ductal adenocarcinomas (PDAC) that manifested hypoenhancement on CEUS were retrospectively studied from January 2020 to January 2022. CEUS patterns and the clinical and pathologic features were analyzed, and the diagnostic ability of CEUS for iso/hyperenhanced solid pancreatic lesions was assessed. RESULTS Centripetal enhancement, heterogeneous enhancement, early washout, and hypoenhancement in the late phase mostly appeared in iso-/hyper-PDACs (p < 0.05). Heterogeneous enhancement in small lesions (< 3 cm) as the diagnostic criterion for iso-/hyper-PDACs had an accuracy of 74.3% and a specificity of 91.3%. Iso-PNETs more commonly had larger tumor sizes and more often showed heterogeneous enhancement than hyper-PNETs (p = 0.007, p = 0.035, respectively). The characteristics of the combination of isoenhancement, homogeneous enhancement, and synchronous wash-in/out for MFP had a high accuracy of 90%. Capsular enhancement with heterogeneous enhancement inside for SPTP had an accuracy of 97.1%. CONCLUSION CEUS enhancement patterns have potentially great value in the differentiation of iso-/hyperenhanced pancreatic lesions.
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Affiliation(s)
- Lan Wang
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen, Chengguan District, Lanzhou, China. Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China
| | - Fang Nie
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen, Chengguan District, Lanzhou, China. Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China
| | - Tiantian Dong
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen, Chengguan District, Lanzhou, China. Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China
| | - Ci Yin
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen, Chengguan District, Lanzhou, China. Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China
| | - Ming Li
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen, Chengguan District, Lanzhou, China. Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China
| | - Yuanyuan Li
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen, Chengguan District, Lanzhou, China. Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China
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Chen X, Liu F, Xue Q, Weng X, Xu F. Metastatic pancreatic cancer: Mechanisms and detection (Review). Oncol Rep 2021; 46:231. [PMID: 34498718 PMCID: PMC8444192 DOI: 10.3892/or.2021.8182] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 08/19/2021] [Indexed: 12/13/2022] Open
Abstract
Pancreatic cancer (PC) is a lethal malignancy. Its prevalence rate remains low but continues to grow each year. Among all stages of PC, metastatic PC is defined as late-stage (stage IV) PC and has an even higher fatality rate. Patients with PC do not have any specific clinical manifestations. Most cases are inoperable at the time-point of diagnosis. Prognosis is also poor even with curative-intent surgery. Complications during surgery, postoperative pancreatic fistula and recurrence with metastatic foci make the management of metastatic PC difficult. While extensive efforts were made to improve survival outcomes, further elucidation of the molecular mechanisms of metastasis poses a formidable challenge. The present review provided an overview of the mechanisms of metastatic PC, summarizing currently known signaling pathways (e.g. epithelial-mesenchymal transition, NF-κB and KRAS), imaging that may be utilized for early detection and biomarkers (e.g. carbohydrate antigen 19-9, prostate cancer-associated transcript-1, F-box/LRR-repeat protein 7 and tumor stroma), giving insight into promising therapeutic targets.
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Affiliation(s)
- Xiangling Chen
- Department of Public Health, Chengdu Medical College, Chengdu, Sichuan 610500, P.R. China
| | - Fangfang Liu
- Department of Art, Art College, Southwest Minzu University, Chengdu, Sichuan 610041, P.R. China
| | - Qingping Xue
- Department of Public Health, Chengdu Medical College, Chengdu, Sichuan 610500, P.R. China
| | - Xiechuan Weng
- Department of Neuroscience, Beijing Institute of Basic Medical Sciences, Beijing 100850, P.R. China
| | - Fan Xu
- Department of Public Health, Chengdu Medical College, Chengdu, Sichuan 610500, P.R. China
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Alabousi M, McInnes MD, Salameh JP, Satkunasingham J, Kagoma YK, Ruo L, Meyers BM, Aziz T, van der Pol CB. MRI vs. CT for the Detection of Liver Metastases in Patients With Pancreatic Carcinoma: A Comparative Diagnostic Test Accuracy Systematic Review and Meta-Analysis. J Magn Reson Imaging 2021; 53:38-48. [PMID: 31943576 DOI: 10.1002/jmri.27056] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Revised: 12/29/2019] [Accepted: 12/30/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The detection of liver metastases is important for pancreatic cancer curative treatment eligibility. The data suggest that magnetic resonance imaging (MRI) is more sensitive than computed tomography (CT) for the diagnosis of pancreatic cancer liver metastases. However, MRI is not currently recommended in multiple published guidelines. PURPOSE To perform a comparative diagnostic test accuracy systematic review and meta-analysis comparing CT and MRI for pancreatic cancer liver metastases detection. STUDY TYPE Systematic review and meta-analysis. DATA SOURCES MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and multiple radiology society meeting archives were searched until November 2018. Comparative design studies reporting on liver CT and MRI accuracy for detection of pancreatic cancer liver metastases in the same cohort were included. FIELD STRENGTH 1.5T or 3.0T. ASSESSMENT Demographic, methodologic, and diagnostic test accuracy data were extracted. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. STATISTICAL TESTS Accuracy metrics were obtained using bivariate random-effects meta-analysis. The impact of different covariates on accuracy estimates was assessed using a meta-regression model. Covariates included modality, study design, tumor characteristics, risk of bias, and imaging protocols. RESULTS Fourteen studies including 987 patients with pancreatic cancer (205 with liver metastases) were included. Sensitivity for CT and MRI was 45% (confidence intervals [95% CI] 21-71%) and 83% (95% CI 74-88%), respectively. Specificity for CT and MRI was 94% (95% CI 84-98%) and 96% (95% CI 93-97%), respectively. The greater observed sensitivity of MRI was preserved in the meta-regression model (P = 0.01), while no difference in specificity was detected (P = 0.16). CT sensitivity was highest for triphasic and quadriphasic examinations compared to single phase or biphasic protocols (P = 0.03). Most studies were at high risk of bias. DATA CONCLUSION MRI is more sensitive than CT for pancreatic cancer liver metastases detection, accounting for confounding variables. Consideration of this finding in clinical practice guidelines is recommended. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
- Mostafa Alabousi
- Department of Radiology, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Matthew Df McInnes
- Department of Radiology and Epidemiology, University of Ottawa; Associate Scientist Ottawa Hospital Research Institute Clinical Epidemiology Program, Ottawa, Ontario, Canada
| | - Jean-Paul Salameh
- The Ottawa Hospital Research Institute Clinical Epidemiology Program, University of Ottawa, School of Epidemiology and Public Health, Ottawa, Ontario, Canada
| | - Janakan Satkunasingham
- Department of Diagnostic Imaging, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Yoan K Kagoma
- Department of Diagnostic Imaging, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Leyo Ruo
- Department of Surgery, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Brandon M Meyers
- Department of Medical Oncology, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Tariq Aziz
- Department of Pathology and Molecular Medicine, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Christian B van der Pol
- Department of Diagnostic Imaging, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
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Lapshyn H, Schulte T, Sondermann S, May K, Petrova E, Honselmann KC, Braun R, Zemskov S, Keck T, Wellner UF, Bausch D, Bolm L. Radiological prediction of portal vein infiltration in patients with pancreatic ductal adenocarcinoma. Pancreatology 2021; 21:155-162. [PMID: 33309623 DOI: 10.1016/j.pan.2020.11.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 11/02/2020] [Accepted: 11/24/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy characterized by early loco-regional invasion. Portal vein resection (PVR) during pancreatoduodenectomy (PD) for PDAC is performed if tumor cell invasion to the venous wall (PVI) is suspected. The aim of this study is to evaluate radiological criteria for predicting PVR and PVI. METHODS Patients undergoing PD for PDAC were identified from a prospectively maintained database. On the basis of CT- and MRI-based imaging portal vein tumor contact (PV), stranding of the superior mesenteric artery (SMA) and any alterations of the superior mesenterico-portal vein (SMPV) were evaluated. The accuracy of PVI and PVR prediction based on the radiological parameters was calculated. RESULTS 143 patients were included in the study. 48 patients underwent PVR (34%), PVI was diagnosed in 23 patients (16%). Median overall survival was 22 months. Prediction of PVR (sensitivity 79%, negative predictive value 88%, p = 0.010) and PVI (sensitivity 95%, negative predictive value 99%, p = 0.002) was most accurate for any SMPV alterations as compared to the other radiological parameters. SMPV alterations qualified as an independent prognostic parameter (26.5 months vs. 33.5months, p = 0.034). CONCLUSION Radiological evaluation of any SMPV alterations is a simple preoperative method to accurately predict PVI. Assessing SMPV alterations may help to identify candidates for neoadjuvant therapy.
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Affiliation(s)
- Hryhoriy Lapshyn
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany
| | - Theresa Schulte
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany
| | - Stefan Sondermann
- Department of Neuroradiology, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany
| | - Katharina May
- Department of Radiology, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany
| | - Ekaterina Petrova
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany
| | - Kim C Honselmann
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany
| | - Rüdiger Braun
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany
| | - Sergii Zemskov
- Department of General Surgery, Bogomolets National Medical University, Bogomolets, 01601, Kiev, No 13, Shevchenko Av, Ukraine
| | - Tobias Keck
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany.
| | - Ulrich F Wellner
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany
| | - Dirk Bausch
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany; Department of Surgery, Marien Hospital Herne, University Hospital of Ruhr University Bochum, Hölkeskampring 40, 44625, Herne, Germany
| | - Louisa Bolm
- Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23562, Luebeck, Germany.
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Barakat MT, Banerjee S. Incidental biliary dilation in the era of the opiate epidemic: High prevalence of biliary dilation in opiate users evaluated in the Emergency Department. World J Hepatol 2020; 12:1289-1298. [PMID: 33442455 PMCID: PMC7772725 DOI: 10.4254/wjh.v12.i12.1289] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 10/12/2020] [Accepted: 10/30/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Biliary dilation is frequently related to obstruction; however, non-obstructive factors such as age and previous cholecystectomy have also been reported. In the past two decades there has been a dramatic increase in opiate use/dependence and utilization of cross-sectional abdominal imaging, with increased detection of biliary dilation, particularly in patients who use opiates.
AIM To evaluate associations between opiate use, age, cholecystectomy status, ethnicity, gender, and body mass index utilizing our institution’s integrated informatics platform.
METHODS One thousand six hundred and eighty-five patients (20% sample) presenting to our Emergency Department for all causes over a 5-year period (2011-2016) who had undergone cross-sectional abdominal imaging and had normal total bilirubin were included and analyzed.
RESULTS Common bile duct (CBD) diameter was significantly higher in opiate users compared to non-opiate users (8.67 mm vs 7.24 mm, P < 0.001) and in patients with a history of cholecystectomy compared to those with an intact gallbladder (8.98 vs 6.72, P < 0.001). For patients with an intact gallbladder who did not use opiates (n = 432), increasing age did not predict CBD diameter (r2 = 0.159, P = 0.873). Height weakly predicted CBD diameter (r2 = 0.561, P = 0.018), but weight, body mass index, ethnicity and gender did not.
CONCLUSION Opiate use and a history of cholecystectomy are associated with CBD dilation in the absence of an obstructive process. Age alone is not associated with increased CBD diameter. These findings suggest that factors such as opiate use and history of cholecystectomy may underlie the previously-reported association of advancing age with increased CBD diameter. Further prospective study is warranted.
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Affiliation(s)
- Monique T Barakat
- Divisions of Adult and Pediatric Gastroenterology and Hepatology, Stanford University Medical Center, Stanford, CA 94305, United States
| | - Subhas Banerjee
- Division of Gastroenterology and Hepatology, Stanford University Medical Center, Stanford, CA 94304, United States
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Driescher C, Fuchs K, Haeberle L, Goering W, Frohn L, Opitz FV, Haeussinger D, Knoefel WT, Keitel V, Esposito I. Bile-Based Cell-Free DNA Analysis Is a Reliable Diagnostic Tool in Pancreatobiliary Cancer. Cancers (Basel) 2020; 13:E39. [PMID: 33375555 PMCID: PMC7818177 DOI: 10.3390/cancers13010039] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 12/16/2020] [Accepted: 12/22/2020] [Indexed: 12/13/2022] Open
Abstract
Currently available serum biomarkers for pancreatobiliary cancers lack sensitivity and specificity and ultimate diagnosis still requires invasive procedures for histological confirmation. The detection of tumor-specific genetic aberrations with utilization of cell free DNA (cfDNA) is a less invasive approach than traditional tissue biopsies; however, it has not been implemented into clinical routine. In this study, we investigated bile as a liquid biopsy source in pancreatobiliary cancers and compared its potential as cell-free DNA source to plasma. Blood (n = 37) and bile (n = 21) samples were collected from patients affected by pancreatic ductal adenocarcinoma (PDAC) and extrahepatic cholangiocarcinoma (CCA) or with non-malignant biliary obstructions (blood n = 16; bile n = 21). Panel-based next generation sequencing (NGS) and digital droplet PCR (ddPCR) were applied for tumor mutation profiling. NGS results from matched tumor tissues (n = 29) served as comparison. Sequencing of cfDNA from bile resulted in detection of 96.2% of the pathogenic tumor mutations found in matched tissue samples. On the other hand, only 31.6% of pathogenic tumor mutations found in tissue could be detected in plasma. In a direct comparison, only half of the mutations detected in bile cfDNA were concordantly detected in plasma from the same patients. Panel NGS and ddPCR displayed comparable sensitivity. In conclusion, bile is a suitable source of cfDNA for the diagnosis of pancreatobiliary cancer and performs more reliably than plasma. Although primary diagnosis still requires histologic confirmation, bile-derived cfDNA could offer an alternative if tissue sampling is not feasible and might allow less invasive disease monitoring.
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Affiliation(s)
- Caroline Driescher
- Institute of Pathology, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (C.D.); (L.H.); (W.G.); (L.F.); (F.V.O.)
| | - Katharina Fuchs
- Department of Gastroenterology, Hepatology and Infectious Diseases, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (K.F.); (D.H.); (V.K.)
| | - Lena Haeberle
- Institute of Pathology, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (C.D.); (L.H.); (W.G.); (L.F.); (F.V.O.)
| | - Wolfgang Goering
- Institute of Pathology, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (C.D.); (L.H.); (W.G.); (L.F.); (F.V.O.)
| | - Lisa Frohn
- Institute of Pathology, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (C.D.); (L.H.); (W.G.); (L.F.); (F.V.O.)
| | - Friederike V. Opitz
- Institute of Pathology, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (C.D.); (L.H.); (W.G.); (L.F.); (F.V.O.)
| | - Dieter Haeussinger
- Department of Gastroenterology, Hepatology and Infectious Diseases, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (K.F.); (D.H.); (V.K.)
| | - Wolfram Trudo Knoefel
- Department of General, Thoracic and Pediatric Surgery, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany;
| | - Verena Keitel
- Department of Gastroenterology, Hepatology and Infectious Diseases, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (K.F.); (D.H.); (V.K.)
| | - Irene Esposito
- Institute of Pathology, Heinrich-Heine-University and University Hospital of Duesseldorf, 40225 Duesseldorf, Germany; (C.D.); (L.H.); (W.G.); (L.F.); (F.V.O.)
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Liang W, Shao J, Liu W, Ruan S, Tian W, Zhang X, Wan D, Huang Q, Ding Y, Xiao W. Differentiating Hepatic Epithelioid Angiomyolipoma From Hepatocellular Carcinoma and Focal Nodular Hyperplasia via Radiomics Models. Front Oncol 2020; 10:564307. [PMID: 33123475 PMCID: PMC7573543 DOI: 10.3389/fonc.2020.564307] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 08/31/2020] [Indexed: 12/20/2022] Open
Abstract
Background: We conduct a study in developing and validating two radiomics-based models to preoperatively distinguish hepatic epithelioid angiomyolipoma (HEAML) from hepatic carcinoma (HCC) as well as focal nodular hyperplasia (FNH). Methods: Totally, preoperative contrast-enhanced computed tomography (CT) data of 170 patients and preoperative contrast-enhanced magnetic resonance imaging (MRI) data of 137 patients were enrolled in this study. Quantitative texture features and wavelet features were extracted from the regions of interest (ROIs) of each patient imaging data. Then two radiomics signatures were constructed based on CT and MRI radiomics features, respectively, using the random forest (RF) algorithm. By integrating radiomics signatures with clinical characteristics, two radiomics-based fusion models were established through multivariate linear regression and 10-fold cross-validation. Finally, two diagnostic nomograms were built to facilitate the clinical application of the fusion models. Results: The radiomics signatures based on the RF algorithm achieved the optimal predictive performance in both CT and MRI data. The area under the receiver operating characteristic curves (AUCs) reached 0.996, 0.879, 0.999, and 0.925 for the training as well as test cohort from CT and MRI data, respectively. Then, two fusion models simultaneously integrated clinical characteristics achieved average AUCs of 0.966 (CT data) and 0.971 (MRI data) with 10-fold cross-validation. Through decision curve analysis, the fusion models were proved to be excellent models to distinguish HEAML from HCC and FNH in comparison between the clinical models and radiomics signatures. Conclusions: Two radiomics-based models derived from CT and MRI images, respectively, performed well in distinguishing HEAML from HCC and FNH and might be potential diagnostic tools to formulate individualized treatment strategies.
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Affiliation(s)
- Wenjie Liang
- Department of Radiology, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jiayuan Shao
- Polytechnic Institute, Zhejiang University, Hangzhou, China
| | - Weihai Liu
- Department of Radiology, The People's Hospital of Beilun District, Ningbo, China
| | - Shijian Ruan
- College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China
| | - Wuwei Tian
- College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China
| | - Xiuming Zhang
- Department of Pathology, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Dalong Wan
- Department of Hepatobiliary and Pancreatic Surgery, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Qiang Huang
- Department of Radiology, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yong Ding
- Polytechnic Institute, Zhejiang University, Hangzhou, China.,College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China
| | - Wenbo Xiao
- Department of Radiology, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
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Ma H, Liu ZX, Zhang JJ, Wu FT, Xu CF, Shen Z, Yu CH, Li YM. Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis. World J Gastroenterol 2020; 26:5156-5168. [PMID: 32982116 PMCID: PMC7495037 DOI: 10.3748/wjg.v26.i34.5156] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 05/19/2020] [Accepted: 08/26/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Efforts should be made to develop a deep-learning diagnosis system to distinguish pancreatic cancer from benign tissue due to the high morbidity of pancreatic cancer. AIM To identify pancreatic cancer in computed tomography (CT) images automatically by constructing a convolutional neural network (CNN) classifier. METHODS A CNN model was constructed using a dataset of 3494 CT images obtained from 222 patients with pathologically confirmed pancreatic cancer and 3751 CT images from 190 patients with normal pancreas from June 2017 to June 2018. We established three datasets from these images according to the image phases, evaluated the approach in terms of binary classification (i.e., cancer or not) and ternary classification (i.e., no cancer, cancer at tail/body, cancer at head/neck of the pancreas) using 10-fold cross validation, and measured the effectiveness of the model with regard to the accuracy, sensitivity, and specificity. RESULTS The overall diagnostic accuracy of the trained binary classifier was 95.47%, 95.76%, 95.15% on the plain scan, arterial phase, and venous phase, respectively. The sensitivity was 91.58%, 94.08%, 92.28% on three phases, with no significant differences (χ 2 = 0.914, P = 0.633). Considering that the plain phase had same sensitivity, easier access, and lower radiation compared with arterial phase and venous phase , it is more sufficient for the binary classifier. Its accuracy on plain scans was 95.47%, sensitivity was 91.58%, and specificity was 98.27%. The CNN and board-certified gastroenterologists achieved higher accuracies than trainees on plain scan diagnosis (χ 2 = 21.534, P < 0.001; χ 2 = 9.524, P < 0.05; respectively). However, the difference between CNN and gastroenterologists was not significant (χ 2 = 0.759, P = 0.384). In the trained ternary classifier, the overall diagnostic accuracy of the ternary classifier CNN was 82.06%, 79.06%, and 78.80% on plain phase, arterial phase, and venous phase, respectively. The sensitivity scores for detecting cancers in the tail were 52.51%, 41.10% and, 36.03%, while sensitivity for cancers in the head was 46.21%, 85.24% and 72.87% on three phases, respectively. Difference in sensitivity for cancers in the head among the three phases was significant (χ 2 = 16.651, P < 0.001), with arterial phase having the highest sensitivity. CONCLUSION We proposed a deep learning-based pancreatic cancer classifier trained on medium-sized datasets of CT images. It was suitable for screening purposes in pancreatic cancer detection.
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Affiliation(s)
- Han Ma
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
| | - Zhong-Xin Liu
- College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, Zhejiang Province, China
| | - Jing-Jing Zhang
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
| | - Feng-Tian Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
| | - Cheng-Fu Xu
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
| | - Zhe Shen
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
| | - Chao-Hui Yu
- Department of Gastroenterology, Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
| | - You-Ming Li
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
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Hindman NM, Arif-Tiwari H, Kamel IR, Al-Refaie WB, Bartel TB, Cash BD, Chernyak V, Goldstein A, Grajo JR, Horowitz JM, Kamaya A, McNamara MM, Porter KK, Srivastava PK, Zaheer A, Carucci LR. ACR Appropriateness Criteria ® Jaundice. J Am Coll Radiol 2020; 16:S126-S140. [PMID: 31054739 DOI: 10.1016/j.jacr.2019.02.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 02/08/2019] [Indexed: 02/07/2023]
Abstract
Jaundice is the end result of myriad causes, which makes the role of imaging in this setting particularly challenging. In the United States, the most common causes of all types of jaundice fall into four categories including hepatitis, alcoholic liver disease, blockage of the common bile duct by a gallstone or tumor, and toxic reaction to a drug or medicinal herb. Clinically, differentiating between the various potential etiologies of jaundice requires a detailed history, targeted physical examination, and pertinent laboratory studies, the results of which allow the physician to categorize the type of jaundice into mechanical or nonmechanical causes. Imaging modalities used to evaluate the jaundiced patient (all etiologies) include abdominal ultrasound (US), CT, MR cholangiopancreatography, endoscopic retrograde cholangiopancreatography and endoscopic US. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.
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Affiliation(s)
| | | | - Hina Arif-Tiwari
- University of Arizona, Banner University Medical Center, Tucson, Arizona
| | - Ihab R Kamel
- Panel Chair, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Waddah B Al-Refaie
- Georgetown University Hospital, Washington, District of Columbia; American College of Surgeons
| | | | - Brooks D Cash
- University of Texas McGovern Medical School, Houston, Texas; American Gastroenterological Association
| | | | | | - Joseph R Grajo
- University of Florida College of Medicine, Gainesville, Florida
| | | | - Aya Kamaya
- Stanford University Medical Center, Stanford, California
| | | | | | - Pavan K Srivastava
- University of Illinois College of Medicine, Chicago, Illinois; American College of Physicians
| | | | - Laura R Carucci
- Specialty Chair, Virginia Commonwealth University Medical Center, Richmond, Virginia
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41
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Rhee H, Park MS. The Role of Imaging in Current Treatment Strategies for Pancreatic Adenocarcinoma. Korean J Radiol 2020; 22:23-40. [PMID: 32901458 PMCID: PMC7772381 DOI: 10.3348/kjr.2019.0862] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Revised: 04/30/2020] [Accepted: 05/18/2020] [Indexed: 02/06/2023] Open
Abstract
In pancreatic cancer, imaging plays an essential role in surveillance, diagnosis, resectability evaluation, and treatment response evaluation. Pancreatic cancer surveillance in high-risk individuals has been attempted using endoscopic ultrasound (EUS) or magnetic resonance imaging (MRI). Imaging diagnosis and resectability evaluation are the most important factors influencing treatment decisions, where computed tomography (CT) is the preferred modality. EUS, MRI, and positron emission tomography play a complementary role to CT. Treatment response evaluation is of increasing clinical importance, especially in patients undergoing neoadjuvant therapy. This review aimed to comprehensively review the role of imaging in relation to the current treatment strategy for pancreatic cancer, including surveillance, diagnosis, evaluation of resectability and treatment response, and prediction of prognosis.
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Affiliation(s)
- Hyungjin Rhee
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Mi Suk Park
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
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Kobi M, Veillette G, Narurkar R, Sadowsky D, Paroder V, Shilagani C, Gilet A, Flusberg M. Imaging and Management of Pancreatic Cancer. Semin Ultrasound CT MR 2020; 41:139-151. [PMID: 32446428 DOI: 10.1053/j.sult.2019.12.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Pancreatic cancer is an aggressive disease with rising incidence and high mortality despite advances in imaging and therapeutic options. Surgical resection is currently the only curative treatment, with expanding roles for adjuvant and neoadjuvant chemoradiation. Accurate detection, staging, and post-treatment monitoring of pancreatic cancer are critical to improving survival and imaging plays a central role in the multidisciplinary approach to this disease. This article will provide a broad overview of the imaging and management of pancreatic cancer with a focus on diagnosis and staging, operative and nonoperative treatments, and post-therapeutic appearances after surgery and chemoradiation therapy.
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Affiliation(s)
- Mariya Kobi
- Department of Radiology, Montefiore Medical Center, Bronx, NY
| | | | - Roshni Narurkar
- Department of Hematology and Oncology, Westchester Medical Center, Valhalla, NY
| | - David Sadowsky
- Department of Radiology, Westchester Medical Center, Valhalla, NY
| | - Viktoriya Paroder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Anthony Gilet
- Department of Radiology, Westchester Medical Center, Valhalla, NY
| | - Milana Flusberg
- Department of Radiology, Westchester Medical Center, Valhalla, NY.
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Deng Y, Ming B, Wu JL, Zhou T, Zhang SY, Chen Y, Lan C, Zhang XM. Magnetic resonance imaging for preoperative staging of pancreatic cancer based on the 8 th edition of AJCC guidelines. J Gastrointest Oncol 2020; 11:329-336. [PMID: 32399274 DOI: 10.21037/jgo.2020.03.06] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Background Preoperative staging of pancreatic cancer determines the choice of treatment. Magnetic resonance imaging (MRI) plays an important role in preoperative staging of pancreatic cancer. The American Joint Committee on Cancer (AJCC) TNM staging system was revised to its 8th version in 2016, there has been no report correlating the 8th edition of the AJCC TNM staging with preoperative MRI examinations and pathological findings. The purpose of our study is to determine the staging accuracy and evaluate the resectability by using MRI about pancreatic cancer compared with intraoperative or pathological findings according to the 8th edition of the AJCC TNM staging system. Methods One hundred thirty-two patients with a pathological diagnosis of pancreatic cancer who underwent preoperative MRI were identified. The clinical data, MRI findings and pathological findings were analyzed. Preoperative MRI staging and resectability evaluation were compared with pathological findings. The accuracy of MRI for preoperative T and N staging was evaluated, and the sensitivity, specificity and accuracy of MRI in evaluating the resectability were assessed. All the staging and resectability assessments were according to the 8th edition of the AJCC TNM staging system. Results Analysis showed that the accuracy of MRI for evaluation of the T and N stages was 82.6% (109/132) and 74.2% (98/132), respectively. The sensitivity and specificity of MRI in assessing the resectability were 94.2% and 71.4%, respectively. Integrating the 8th edition of the AJCC TNM stage, no significant differences were identified between the preoperative MRI and pathological results for the staging of pancreatic cancer (P=0.805). Conclusions MRI is highly accurate for T staging and moderately accurate for N staging. MRI provides important preoperative evaluation of the stage and resectability of pancreatic cancer based on the 8th edition of the AJCC TNM staging system.
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Affiliation(s)
- Yan Deng
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China
| | - Bing Ming
- Department of Radiology, Deyang People's Hospital, Deyang 618000, China
| | - Jia-Long Wu
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China
| | - Ting Zhou
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China
| | - Shi-Yong Zhang
- Department of Radiology, Deyang People's Hospital, Deyang 618000, China
| | - Yong Chen
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China
| | - Chuan Lan
- Department of Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China
| | - Xiao-Ming Zhang
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China
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Kulkarni NM, Mannelli L, Zins M, Bhosale PR, Arif-Tiwari H, Brook OR, Hecht EM, Kastrinos F, Wang ZJ, Soloff EV, Tolat PP, Sangster G, Fleming J, Tamm EP, Kambadakone AR. White paper on pancreatic ductal adenocarcinoma from society of abdominal radiology's disease-focused panel for pancreatic ductal adenocarcinoma: Part II, update on imaging techniques and screening of pancreatic cancer in high-risk individuals. Abdom Radiol (NY) 2020; 45:729-742. [PMID: 31768594 DOI: 10.1007/s00261-019-02290-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Its high mortality rate is attributed to its aggressive biology and frequently late presentation. While surgical resection remains the only potentially curative treatment, only 10-20% of patients will present with surgically resectable disease. Over the past several years, development of vascular bypass graft techniques and introduction of neoadjuvant treatment regimens have increased the number of patients who can undergo resection with a curative intent. While the role of conventional imaging in the detection, characterization, and staging of patients with PDAC is well established, its role in monitoring treatment response, particularly following neoadjuvant therapy remains challenging because of the complex anatomic and histological nature of PDAC. Novel morphologic and functional imaging techniques (such as DECT, DW-MRI, and PET/MRI) are being investigated to improve the diagnostic accuracy and the ability to measure response to therapy. There is also a growing interest to detect PDAC and its precursor lesions at an early stage in asymptomatic patients to increase the likelihood of achieving cure. This has led to the development of pancreatic cancer screening programs. This article will review recent updates in imaging techniques and the current status of screening and surveillance of individuals at a high risk of developing PDAC.
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Affiliation(s)
- Naveen M Kulkarni
- Department of Radiology, Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI, 53226, USA.
| | | | - Marc Zins
- Department of Radiology, Groupe Hospitalier Paris Saint-Joseph, 185 rue Raymond Losserand, 75014, Paris, France
| | - Priya R Bhosale
- Abdominal Imaging Department, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1473, Houston, TX, 77030-400, USA
| | - Hina Arif-Tiwari
- Department of Medical Imaging, University of Arizona College of Medicine, 1501 N. Campbell Ave, P.O. Box 245067, Tucson, AZ, 85724, USA
| | - Olga R Brook
- Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Shapiro 4, Boston, MA, 02215-5400, USA
| | - Elizabeth M Hecht
- Department of Radiology, Columbia University Medical Center, 622 W 168th St, PH1-317, New York, NY, 10032, USA
| | - Fay Kastrinos
- Division of Digestive and Liver Diseases, Department of Medicine, Columbia University Medical Cancer, 161 Fort Washington Avenue, Suite: 862, New York, NY, 10032, USA
| | - Zhen Jane Wang
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Avenue, San Francisco, CA, 94143, USA
| | - Erik V Soloff
- Department of Radiology, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Parag P Tolat
- Department of Radiology, Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI, 53226, USA
| | - Guillermo Sangster
- Department of Radiology, Ochsner LSU Health Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA
| | - Jason Fleming
- Gastrointestinal Oncology, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, FL, 33612, USA
| | - Eric P Tamm
- Abdominal Imaging Department, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1473, Houston, TX, 77030-400, USA
| | - Avinash R Kambadakone
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, White 270, Boston, MA, 02114, USA
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45
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Cui SJ, Tang TY, Zou XW, Su QM, Feng L, Gong XY. Role of imaging biomarkers for prognostic prediction in patients with pancreatic ductal adenocarcinoma. Clin Radiol 2020; 75:478.e1-478.e11. [PMID: 32037002 DOI: 10.1016/j.crad.2019.12.023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 12/30/2019] [Indexed: 12/13/2022]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumours. PDAC has a poor prognosis; therefore, it is necessary to perform further risk stratification. Identifying prognostic factors before treatment might help to implement suitable and personalised treatment for individuals and avoid side effects. Conventional staging systems and tumour biomarkers are fundamental to establish prognosis; however, they have obvious limitations. Novel imaging biomarkers extracted from advanced imaging techniques offer opportunities to evaluate underlying tumour physiological characteristics, such as mutational status, cellular composition, local microenvironment, tumour metabolism, and biological behaviour. Thus, imaging biomarkers might help the decision making of oncologists and surgeons. The present review discusses the functions of imaging biomarkers for prognostic prediction in patients with PDAC and their potential value for further translation in clinical practice.
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Affiliation(s)
- S-J Cui
- The Second Clinical Medical College, Zhejiang Chinese Medical University, 310053, Hangzhou, China; Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, 310013, Hangzhou, China
| | - T-Y Tang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China
| | - X-W Zou
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China
| | - Q-M Su
- Department of General Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - L Feng
- Department of Nuclear Medicine, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - X-Y Gong
- Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, 310013, Hangzhou, China; Institute of Artificial Intelligence and Remote Imaging, Hangzhou Medical College, 310000, Hangzhou, China.
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Haj-Mirzaian A, Kawamoto S, Zaheer A, Hruban RH, Fishman EK, Chu LC. Pitfalls in the MDCT of pancreatic cancer: strategies for minimizing errors. Abdom Radiol (NY) 2020; 45:457-478. [PMID: 31897686 DOI: 10.1007/s00261-019-02390-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Multidetector computed tomography (MDCT) is a widely used cross-sectional imaging modality for initial evaluation of patients with suspected pancreatic ductal adenocarcinoma (PDAC). However, diagnosis of PDAC can be challenging due to numerous pitfalls associated with image acquisition and interpretation, including technical factors, imaging features, and cognitive errors. Accurate diagnosis requires familiarity with these pitfalls, as these can be minimized using systematic strategies. Suboptimal acquisition protocols and other technical errors such as motion artifacts and incomplete anatomical coverage increase the risk of misdiagnosis. Interpretation of images can be challenging due to intrinsic tumor features (including small and isoenhancing masses, exophytic masses, subtle pancreatic duct irregularities, and diffuse tumor infiltration), presence of coexisting pathology (including chronic pancreatitis and intraductal papillary mucinous neoplasm), mimickers of PDAC (including focal fatty infiltration and focal pancreatitis), distracting findings, and satisfaction of search. Awareness of pitfalls associated with the diagnosis of PDAC along with the strategies to avoid them will help radiologists to minimize technical and interpretation errors. Cognizance and mitigation of these errors can lead to earlier PDAC diagnosis and ultimately improve patient prognosis.
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Affiliation(s)
- Arya Haj-Mirzaian
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Satomi Kawamoto
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Atif Zaheer
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ralph H Hruban
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Elliot K Fishman
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Linda C Chu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Beker K, Lee KS, Tsai LL, Hegazi T, Garces-Descovich A, Brook A, Mortele KJ. Differentiation of pancreatic head ductal adenocarcinoma from inflammatory pancreatic pseudomass by MR cholangio-pancreatography: utility of the duct-interrupted, corona, and attraction signs. Abdom Radiol (NY) 2019; 44:4048-4056. [PMID: 31352623 DOI: 10.1007/s00261-019-02155-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
PURPOSE To determine sensitivity and specificity of the "duct-interrupted," "corona," and "attraction" signs on MR cholangio-pancreatography (MRCP) in distinguishing pancreatic head ductal adenocarcinoma (PDAC) from inflammatory pancreatic pseudomass (IPP). MATERIALS AND METHODS This study included 53 adults (33 men and 20 women, mean age, 55 years; range, 17-87 years) with a pancreatic head mass who underwent MRCP. Three blinded radiologists independently reviewed each MRCP exam and three signs were assessed: (1) the "duct-interrupted" sign, deemed positive for PDAC if the duct within the mass demonstrated complete interruption with upstream dilation; (2) the "corona" sign, considered positive for PDAC if dilated side-branches were located exclusively outside the mass; and (3) the "attraction" sign, deemed positive for IPP if the dilated common bile duct showed attraction and angulation towards the mass. Sensitivity, specificity, and positive and negative predictive values of the signs were calculated, as well as interobserver agreement. RESULTS Out of 53 masses, 17 (32%) were PDAC and 36 (68%) were IPP. Sensitivity, specificity, and positive and negative predictive values of the "duct-interrupted" sign to differentiate between PDAC from IPP for the three readers were 29-53%, 89-95%, 56-82% and 73-81%, respectively (κ = 0.41); for the "corona" sign, they were 29-53%, 81-100%, 56-100%, and 75-78%, respectively (κ = 0.4), and for the "attraction" sign, they were 20-25%, 71-82%, 64-75%, and 31-34%, respectively (κ = 0.54). CONCLUSION The "duct-interrupted" and "corona" MRCP signs have high specificity for diagnosing PDAC, while the "attraction" sign has good specificity for identifying IPP.
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Affiliation(s)
- Kevin Beker
- Division of Body MRI, Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, 02115, USA
| | - Karen S Lee
- Division of Body MRI, Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, 02115, USA
| | - Leo L Tsai
- Division of Body MRI, Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, 02115, USA
| | - Tarek Hegazi
- Division of Body MRI, Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, 02115, USA
| | - Alejandro Garces-Descovich
- Division of Body MRI, Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, 02115, USA
| | - Alexander Brook
- Division of Body MRI, Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, 02115, USA.
| | - Koenraad J Mortele
- Division of Body MRI, Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, 02115, USA
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Kobi M, Veillette G, Narurkar R, Sadowsky D, Paroder V, Shilagani C, Gilet A, Flusberg M. DUPLICATE: Imaging and Management of Pancreatic Cancer. Semin Ultrasound CT MR 2019. [DOI: 10.1053/j.sult.2019.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Choi SY, Kim JH, Park HJ, Han JK. Preoperative CT findings for prediction of resectability in patients with gallbladder cancer. Eur Radiol 2019; 29:6458-6468. [PMID: 31254061 DOI: 10.1007/s00330-019-06323-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 05/24/2019] [Accepted: 06/12/2019] [Indexed: 12/17/2022]
Abstract
OBJECTIVES To predict residual tumor (R) classification in patients with a surgery for gallbladder (GB) cancer, using preoperative CT. METHODS One hundred seventy-three patients with GB cancer who underwent CT and subsequent surgery were included. Two radiologists assessed CT findings, including tumor morphology, location, T stage, adjacent organ invasion, hepatic artery (HA) invasion, portal vein invasion, lymph node metastasis, metastasis, resectability, gallstone, and combined cholecystitis. The R classification was categorized as no residual tumor (R0) and residual tumor (R1 or R2). We analyzed the correlation between CT findings and R classification. We also followed up the patients as long as five years and analyzed the relationship between the R classification and the overall survival (OS). RESULTS There were 134 patients with R0 and 39 patients with R1/R2. On multivariable analysis, liver invasion (Exp(B) = 3.19, p = 0.010), bile duct invasion (Exp(B) = 3.69, p = 0.031), and HA invasion (Exp(B) = 3.74, p = 0.039) were independent, significant predictors for residual tumor. When two of these three criteria were combined, the accuracy for predicting a positive resection margin was 83.38% with a specificity of 93.28%. The OS and the median patient survival time differed significantly according to the resection margin, i.e., 56.0% and 134.4 months in the R0 resection and 5.1% and 10.8 months in the R1/R2 resection group (p < 0.001). CONCLUSIONS Preoperative CT findings could aid in planning surgery and determining the resectability using the high-risk findings of residual tumor, including liver invasion, bile duct invasion, and HA invasion. KEY POINTS • Liver invasion, bile duct invasion, and HA invasion were significant preoperative CT predictors for residual tumor in GB cancer. • HA invasion showed the highest OR on multivariate analysis and the highest predictor point on a nomogram for predicting a positive resection margin. • Association of two factors can predict positive resection margin with an accuracy of 83.38% and a specificity of 93.28%.
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Affiliation(s)
- Seo-Youn Choi
- Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, 170 Jomaru-ro, Wonmi-gu, Bucheon, 14584, Republic of Korea
| | - Jung Hoon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
| | - Hyun Jeong Park
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul, 06973, Republic of Korea
| | - Joon Koo Han
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
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50
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Dallongeville A, Corno L, Silvera S, Boulay-Coletta I, Zins M. Initial Diagnosis and Staging of Pancreatic Cancer Including Main Differentials. Semin Ultrasound CT MR 2019; 40:436-468. [PMID: 31806145 DOI: 10.1053/j.sult.2019.08.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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