Bruno, Marco J.

Abstract Despite growing interest in AI for pancreatic cyst management, no prior study has systematically investigated how lesion characteristics influence model behavior or provided a comprehensive explainability analysis in IPMN malignancy risk stratification. We present the first multi-center study integrating explainable AI with uncertainty quantification to evaluate how cyst type, size, and location affect deep learning performance in IPMN malignancy prediction. Our retrospective study analyzed 170 IPMNs from seven centers using a radiomics-deep learning fusion model. Cases were stratified by dysplasia grade, IPMN type, size, and location; with model interpretability assessed using SHAP, LIME, Grad-CAM, and uncertainty quantification. Overall accuracy was 67.1%, with model uncertainty lower for correct versus incorrect predictions (0.72 vs 0.78, p < 0.001). On subgroup analysis: Low-Risk lesion accuracy exceeded High-Risk (81.3% vs. 42.9%, p < 0.001), BD accuracy was inversely correlated with cyst size while MD remained stable, and body and whole-pancreas cysts stratified more accurately than tail cysts (77.8%, 76.6% vs. 47.8%). AI models face significant, previously uncharacterized performance drops when evaluating complex high-risk IPMNs. Our study shows that integrating uncertainty quantification can successfully flag unreliable predictions, enabling a selective-prediction framework where clinicians can confidently rely on AI for low-risk, low-uncertainty lesions while deferring high-uncertainty cases to expert review.

Abstract Pancreatic cancer, projected to become the second-deadliest malignancy in Western societies by 2030, requires urgent innovations in early detection and risk stratification. Intraductal papillary mucinous neoplasms (IPMNs) represent critical precursor lesions, but current clinical guidelines demonstrate suboptimal accuracy in malignancy prediction, leading to either unnecessary surgeries or missed opportunities for early intervention. In this paper, we present Cyst-X, an artificial intelligence (AI) framework that accurately predicts IPMN malignant transformation using multicenter magnetic resonance imaging (MRI) data. Unlike most previous approaches that rely on computed tomography (CT), our method capitalizes on the superior soft tissue contrast of MRI, allowing for more precise identification of subtle imaging biomarkers. We developed and validated deep learning models on 723 T1-weighted and 738 T2-weighted MRI scans from 764 patients among seven international institutions, demonstrating significantly superior performance (AUC=0.82) compared to current clinical (Kyoto) guidelines (AUC=0.75) and expert radiologists. AI-based imaging features correlate strongly with clinically recognized malignancy markers, providing potential biologically relevant insights. This approach holds promise to significantly refine clinical decision-making, reduce unnecessary surgeries, and better identify high-risk IPMN patients for timely intervention. Our approach integrates a novel pancreas segmentation network with robust classification models that identify subtle imaging biomarkers associated with malignancy risk. Importantly, we demonstrate that these models retain high performance in a privacy-preserving federated learning setting, where institutions collaboratively train AI models without exchanging patient data to address key regulatory and ethical barriers. We publicly release the Cyst-X dataset--the first large-scale, multi-center pancreatic cyst MRI collection--to accelerate research in this field. This study addresses a critical clinical need while establishing technical foundations for privacy-preserving AI in radiology that could transform pancreatic cancer management through earlier intervention and reduced unnecessary procedures. The dataset can be accessed at https://osf.io/74vfs/, and the source code for our deep learning segmentation and classification models is available at https://github.com/NUBagciLab/Cyst-X.

ABSTRACTBackgroundPancreatic cysts are increasingly discovered on imaging studies performed for unrelated conditions. Currently, surveillance of these lesions poses a substantial burden on patients, and health care recourses. We hypothesized that individuals with small and stable cysts have a diminutive risk of progressing to high‐grade dysplasia (HGD) or pancreatic cancer (PC) that is similar to that in the general population.MethodsThis nested PACYFIC‐study is a collaboration among 44 centers in Europe and Northern‐America, and investigates the risk of HGD and PC for different cyst sizes and growth rates in participants without baseline worrisome features (WF) or high‐risk stigmata (HRS).ResultsOf the 2369 PACYFIC participants, 975 met the inclusion criteria, with a mean age of 67 years (SD 13) and 65% being female. Of these, 438 individuals (45%) had a baseline small cyst size (< 15 mm), and 885 (91%) individuals had a slow growth rate (< 2.5 mm/year). During a median follow‐up of 45 months (IQR 27), 20 individuals (2.1%) developed HGD, or PC. Individuals with small cysts had a 1.5‐fold lower risk of developing WF or HRS (hazard ratio [HR] 0.7 [0.5–1.0], p = 0.03) than those with larger cysts but a similar risk of developing HGD or PC (p > 0.05). Slow growth was protective against the development of WF or HRS (HR 0.4 [0.2–0.6], p < 0.001) and HGD or PC (HR 0.04 [95% CI 0.02–0.12], p < 0.001). Individuals with small, stable sized cysts without baseline WF or HRS did not have a higher risk of HGD or PC than the general population (standardized incidence ratio [SIR] 1.13 [95% CI 0.01–6.30]).ConclusionCyst size < 15 mm and growth rate < 2.5 mm/year appear to be “reassuring” features associated with a negligible risk of developing WF or HRS and HGD or PC. For cysts with these characteristics—and without baseline WF or HRS—less intensive surveillance (than currently recommended) or even cessation may be appropriate.

Abstract Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs), pancreatic cysts requiring surgery, from low-risk lesions remains a clinical challenge, often resulting in unnecessary procedures due to limited specificity of current methods. While radiomics and deep learning (DL) have been explored for pancreatic cancer, cyst-level malignancy risk stratification of IPMNs remains untapped. We conducted a multi-institutional study (seven centers, 359 T2W MRI images) to assess the feasibility of AI for predicting IPMN dysplasia grade using cyst-level image features. We developed and compared 2D and 3D radiomics-only, deep learning (DL)-only, and radiomics-DL fusion models, using expert radiologist scoring as a baseline reference. Model performance was evaluated using held-out test data. The radiomics-DL fusion model showed the highest discriminatory ability on the test set (AUC 0.692), outperforming the radiomics-only model (AUC 0.665). Expert accuracy varied widely (37.4%-66.7%). The fusion model integrating deep learning and radiomics features from routine T2W MRI (AUC: 0.692) demonstrates potential for objective, cyst-level risk stratification of IPMNs in a multi-center cohort, outperforming both radiomics-only models and expert radiologists. While performance requires improvement for standalone clinical use, this approach offers a scalable, non-invasive method to potentially improve diagnostic accuracy and reduce unnecessary surgical interventions.

Background The first commercialized single-use duodenoscope was cleared by the US Food and Drug Administration in December 2019. Data regarding endoscopic retrograde cholangiopancreatography (ERCP) using a single-use duodenoscope are needed on a broader range of cases conducted by endoscopists with varying levels of experience in a wide range of geographic areas. Methods 61 endoscopists at 22 academic centers in 11 countries performed ERCP procedures in adult patients aged ≥ 18. Outcomes included ERCP completion for the intended indication, rate of crossover to a reusable endoscope, device performance ratings, and serious adverse events (SAEs). Results Among 551 patients, 236 (42.8 %) were aged > 65, 281 (51.0 %) were men, and 256 (46.5 %) had their procedure as an inpatient. ERCPs included 196 (35.6 %) with American Society for Gastrointestinal Endoscopy complexity of grades 3–4. A total of 529 ERCPs (96.0 %) were completed: 503 (91.3 %) using only the single-use duodenoscope, and 26 (4.7 %) with crossover to a reusable endoscope. There were 22 ERCPs (4.0 %) that were not completed, of which 11 (2.0 %) included a crossover and 11 (2.0 %) were aborted cases (no crossover). Median ERCP completion time was 24.0 minutes. Median overall satisfaction with the single-use duodenoscope was 8.0 (scale of 1 to 10 [best]). SAEs were reported in 43 patients (7.8 %), including 17 (3.1 %) who developed post-ERCP pancreatitis. Conclusions In academic medical centers over a wide geographic distribution, endoscopists with varying levels of experience using the first marketed single-use duodenoscope had good ERCP procedural success and reported high performance ratings for this device.

AbstractBackgroundSurveillance of pancreatic cysts focuses on the detection of (mostly morphologic) features warranting surgery. European guidelines consider elevated CA19.9 as a relative indication for surgery. We aimed to evaluate the role of CA19.9 monitoring for early detection and management in a cyst surveillance population.MethodsThe PACYFIC‐registry is a prospective collaboration that investigates the yield of pancreatic cyst surveillance performed at the discretion of the treating physician. We included participants for whom at least one serum CA19.9 value was determined by a minimum follow‐up of 12 months.ResultsOf 1865 PACYFIC participants, 685 met the inclusion criteria for this study (mean age 67 years, SD 10; 61% female). During a median follow‐up of 25 months (IQR 24, 1966 visits), 29 participants developed high‐grade dysplasia (HGD) or pancreatic cancer. At baseline, CA19.9 ranged from 1 to 591 kU/L (median 10 kU/L [IQR 14]), and was elevated (≥37 kU/L) in 64 participants (9%). During 191 of 1966 visits (10%), an elevated CA19.9 was detected, and these visits more often led to an intensified follow‐up (42%) than those without an elevated CA19.9 (27%; p < 0.001). An elevated CA19.9 was the sole reason for surgery in five participants with benign disease (10%). The baseline CA19.9 value was (as continuous or dichotomous variable at the 37 kU/L threshold) not independently associated with HGD or pancreatic cancer development, whilst a CA19.9 of ≥ 133 kU/L was (HR 3.8, 95% CI 1.1–13, p = 0.03).ConclusionsIn this pancreatic cyst surveillance cohort, CA19.9 monitoring caused substantial harm by shortening surveillance intervals (and performance of unnecessary surgery). The current CA19.9 cutoff was not predictive of HGD and pancreatic cancer, whereas a higher cutoff may decrease false‐positive values. The role of CA19.9 monitoring should be critically appraised prior to implementation in surveillance programs and guidelines.

AbstractBackgroundIdentifying branch‐duct intraductal papillary mucinous neoplasms (BD‐IPMNs) at lowest risk of progression may allow for a reduced intensity of surveillance.ObjectiveWe aimed to externally validate the previously developed Dutch‐American Risk stratification Tool (DART‐1; https://rtools.mayo.edu/DART/), which identifies cysts at low risk of developing worrisome features (WFs) or high‐risk stigmata (HRS).MethodsThree prospective cohorts of individuals under surveillance for BD‐IPMNs were combined, independent from the original development cohort. We assessed the performance (discrimination and calibration) of DART‐1, a multivariable Cox‐proportional logistic regression model with five predictors for the development of WFs or HRS.ResultsOf 832 individuals (mean age 77 years, SD 11.5) under surveillance for a median of 40 months (IQR 44), 163 (20%) developed WFs or HRS. DART‐1's discriminative ability (C‐statistic 0.68) was similar to that in the development cohort (0.64–0.72) and showed moderate calibration. DART‐1 adequately estimated the risk for patients in the middle risk quintile, and slightly underestimated it in the lowest quintiles. Their range of predicted versus observed 3‐year risk was 0%–0% versus 0%–3.7% for Q1; 0.3%–0.4% versus 3%–11% for Q2; and 2.6%–3% versus 2.4%–9.8% for Q3. The development of WFs or HRS was associated with pancreatic cancer (p < 0.001). Vice versa, in absence of WFs or HRS, the risk of malignancy was low (0.3%).ConclusionsThe performance of DART‐1 to predict the development of WFs or HRS in BD‐IPMN was validated in an external international cohort, with a discriminative ability equal as in the development cohort. Risk estimations were most accurate for patients with BD‐IPMNs in the middle risk quintile and slightly underestimated in the lowest quintiles.

The COVID-19 pandemic has had a profound impact on provision of endoscopy services globally as staff and real estate were repurposed. As we begin to recover from the pandemic, a cohesive international approach is needed, and guidance on how to resume endoscopy services safely to avoid unintended harm from diagnostic delays. The aim of these guidelines is to provide consensus recommendations that clinicians can use to facilitate the swift and safe resumption of endoscopy services. An evidence-based literature review was carried out on the various strategies used globally to manage endoscopy during the COVID-19 pandemic and control infection. A modified Delphi process involving international endoscopy experts was used to agree on the consensus statements. A threshold of 80% agreement was used to establish consensus for each statement. 27 of 30 statements achieved consensus after two rounds of voting by 34 experts. The statements were categorised as pre-endoscopy, during endoscopy and postendoscopy addressing relevant areas of practice, such as screening, personal protective equipment, appropriate environments for endoscopy and infection control precautions, particularly in areas of high disease prevalence. Recommendations for testing of patients and for healthcare workers, appropriate locations of donning and doffing areas and social distancing measures before endoscopy are unique and not dealt with by any other guidelines. This international consensus using a modified Delphi method to produce a series of best practice recommendations to aid the safe resumption of endoscopy services globally in the era of COVID-19.