Faculty Bibliography

Intraductal Papillary Mucinous Neoplasm (IPMN) cysts are pre-malignant pancreas lesions, and they can progress into pancreatic cancer. Therefore, detecting and stratifying their risk level is of ultimate importance for effective treatment planning and disease control. However, this is a highly challenging task because of the diverse and irregular shape, texture, and size of the IPMN cysts as well as the pancreas. In this study, we propose a novel computer-aided diagnosis pipeline for IPMN risk classification from multi-contrast MRI scans. Our proposed analysis framework includes an efficient volumetric self-adapting segmentation strategy for pancreas delineation, followed by a newly designed deep learning-based classification scheme with a radiomics-based predictive approach. We test our proposed decision-fusion model in multi-center data sets of 246 multi-contrast MRI scans and obtain superior performance to the state of the art (SOTA) in this field. Our ablation studies demonstrate the significance of both radiomics and deep learning modules for achieving the new SOTA performance compared to international guidelines and published studies (81.9% vs 61.3% in accuracy). Our findings have important implications for clinical decision-making. In a series of rigorous experiments on multi-center data sets (246 MRI scans from five centers), we achieved unprecedented performance (81.9% accuracy). The code is available upon publication.

Intraductal Papillary Mucinous Neoplasm (IPMN) cysts are pre-malignant pancreas lesions, and they can progress into pancreatic cancer. Therefore, detecting and stratifying their risk level is of ultimate importance for effective treatment planning and disease control. However, this is a highly challenging task because of the diverse and irregular shape, texture, and size of the IPMN cysts as well as the pancreas. In this study, we propose a novel computer-aided diagnosis pipeline for IPMN risk classification from multi-contrast MRI scans. Our proposed analysis framework includes an efficient volumetric self-adapting segmentation strategy for pancreas delineation, followed by a newly designed deep learning-based classification scheme with a radiomics-based predictive approach. We test our proposed decision-fusion model in multi-center data sets of 246 multi-contrast MRI scans and obtain superior performance to the state of the art (SOTA) in this field. Our ablation studies demonstrate the significance of both radiomics and deep learning modules for achieving the new SOTA performance compared to international guidelines and published studies (81.9% vs 61.3% in accuracy). Our findings have important implications for clinical decision-making. In a series of rigorous experiments on multi-center data sets (246 MRI scans from five centers), we achieved unprecedented performance (81.9% accuracy). The code is available upon publication.

PURPOSE OF REVIEW/OBJECTIVE:As abdominal imaging becomes more sensitive and regularly used, pancreatic cystic lesions (PCLs) are being diagnosed more frequently. A small but clinically significant minority of these lesions have a predisposition to either harbor malignancy or undergo malignant transformation. This review highlights the current state and performance of cystic fluid biomarkers and how they may be incorporated into management. RECENT FINDINGS/RESULTS:Among the major domains of molecular testing for PCLs, DNA based analyses have demonstrated the highest accuracy in identifying cyst type and have the most data to support their clinical use. However, epigenetic and protein biomarker based molecular assessments have emerged with the potential to complement DNA based approaches. In addition, recent studies have increasingly demonstrated the value associated with combinations of mutations and other biomarkers in identifying higher grade mucinous cystic lesions. We present the performance of individual biomarkers in cyst fluid analysis with an emphasis on an algorithmic approach to improve the accurate identification of both cyst type and risk of malignant transformation.

INTRODUCTION/BACKGROUND:The development of non-anastomotic biliary strictures (NAS) following orthotopic adult liver transplantation (OLT) is associated with significant morbidity. We performed a systematic review and meta-analysis to identify all prognostic factors for the development of NAS. METHODS:A systematic review was conducted following preferred reporting items for systematic reviews and meta-analyses (PRISMA) and the meta-analysis of observational studies in epidemiology (MOOSE) guidelines. We used the Newcastle-Ottawa scale to assess the quality of the included studies. Using the random-effects model, we calculated the weighted pooled odds ratios (OR), mean differences (MD), hazard ratios (HR), and 95% confidence intervals (CI) of the risk factors. RESULTS:Based on 19 international studies that included a total of 8269 adult LT patients, we calculated an 8% overall incidence of NAS. In this study, 7 potential prognostic factors were associated with a statistically significant hazard ratio for NAS in pooled analyses including (1) DCD donors compared to DBD donors (2) PSC as an indication for a liver transplant (3) Roux-en-Y bile duct reconstruction compared to duct-to-duct reconstruction (4) hepatic artery thrombosis (5) longer cold ischemia time (6) longer warm ischemia time (7) and total operative times. CONCLUSION/CONCLUSIONS:In this systematic review and meta-analysis, we identified 7 prognostic factors for the development of NAS following OLT. These findings might lay the groundwork for development of diagnostic algorithms to better risk stratify patients at risk for development of NAS.

BACKGROUND AND AIMS/OBJECTIVE:Low-risk branch duct intraductal papillary mucinous neoplasms (BD-IPMN lacking worrisome features (WF) and high-risk stigmata (HRS)), warrant surveillance. However, their optimal duration, especially among cysts with initial five years of size stability, warrants further investigation. We aim to systematically review the surveillance of low-risk BD-IPMNs and investigate incidence of WF/HRS and advanced neoplasia: high-grade dysplasia and pancreatic cancer during the initial (<five-year) and extended surveillance period (≥five-year). METHODS:A systematic search (CRD42020117120) identified studies investigating long-term IPMN surveillance outcomes of low-risk IPMN among Cochrane Library, Embase, Google Scholar, Ovid Medline, PubMed, Scopus, and Web of Science, from inception until July 9, 2021. The outcomes included incidence of WF/HRS and advanced neoplasia, disease-specific mortality, and surveillance-related harm (expressed as % patient-years). The meta-analysis relied on time-to-event plots and utilized random-effects model. RESULTS:Forty-one eligible studies underwent systematic review, and eighteen studies were meta-analyzed. Pooled incidence of WF/HRS among low-risk BD-IPMNs during initial and extended surveillance were 2.2% [95%CI:1.0%-3.7%] and 2.9% [95%CI:1.0%-5.7%] patient-years, respectively, whereas incidence of advanced neoplasia were 0.6%[95%CI:0.2%-1.00%] and 1.0%[95%CI:0.6%-1.5%] patient-years, respectively. Pooled incidence of disease-specific mortality during initial and extended surveillance were 0.3% [95%CI:0.1% - 0.6%] and 0.6% [95%CI: 0.0%-1.6%] patient-years, respectively. Among BD-IPMNs with initial size stability, extended surveillance had WF/HRS and advanced neoplasia incidence of 1.9%[95%CI:1.2%-2.8%] and 0.2%[95%CI:0.1%-0.5%] patient-years, respectively. CONCLUSION/CONCLUSIONS:A lower incidence of advanced neoplasia during extended surveillance among low-risk, stable-sized BD-IPMNs is a key finding of this study. However, the survival benefit of surveillance among this population warrants further exploration through high-quality studies before recommending surveillance cessation with certainty.

Since its emergence as a diagnostic modality in the 1980s, endoscopic ultrasound (EUS) has provided the clinician profound access to gastrointestinal organs to aid in the direct visualization, sampling, and subsequent identification of pancreatic pathology. In recent years, advancements in EUS as an interventional technique have promoted the use of local ablative therapies as a minimally invasive alternative to the surgical management of pancreatic neuroendocrine tumors (pNETs) and pancreatic cystic neoplasms (PCNs), especially for those deemed to be poor operative candidates. EUS-guided local therapies have demonstrated promising efficacy in addressing a spectrum of pancreatic neoplasms, while also balancing local adverse effects on healthy parenchyma. This article serves as a review of the current literature detailing the mechanisms, outcomes, complications, and limitations of EUS-guided local ablative therapies such as chemical ablation and radiofrequency ablation (RFA) for the treatment of pNETs and PCNs, as well as a discussion of future applications of EUS-guided techniques to address a broader scope of pancreatic pathology.

Cholangiocarcinoma remains an aggressive and deadly malignancy that is often diagnosed late. Intrinsic tumour characteristics and the growth pattern of cancer cells contribute to the challenges of diagnosis and chemoresistance. However, establishing an early and accurate diagnosis, and in some instances identifying targetable changes, has the potential to impact survival. Primary sclerosing cholangitis, a chronic cholangiopathy prodromal to the development of a minority of cholangiocarcinomas, poses a particular diagnostic challenge. We present our diagnostic and theranostic approach to the initial evaluation of cholangiocarcinomas, focusing on extrahepatic cholangiocarcinoma. This involves a multipronged strategy incorporating advanced imaging, endoscopic methods, multiple approaches to tissue sampling, and molecular markers. We also provide an algorithm for the sequential use of these tools.

The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. Here, we perform single-cell RNA sequencing on freshly collected human PDAC samples either before or after chemotherapy. Overall, we find a heterogeneous mixture of basal and classical cancer cell subtypes, along with distinct cancer-associated fibroblast and macrophage subpopulations. Strikingly, classical and basal-like cancer cells exhibit similar transcriptional responses to chemotherapy and do not demonstrate a shift towards a basal-like transcriptional program among treated samples. We observe decreased ligand-receptor interactions in treated samples, particularly between TIGIT on CD8 + T cells and its receptor on cancer cells, and identify TIGIT as the major inhibitory checkpoint molecule of CD8 + T cells. Our results suggest that chemotherapy profoundly impacts the PDAC TME and may promote resistance to immunotherapy.