Thiels, Cornelius A.

Objective: To develop an artificial intelligence–based pipeline to assess and triage patient-submitted postoperative wound images. Background: The rise of outpatient surgeries, remote monitoring, and patient-submitted wound images via online portals has contributed to a growing administrative workload on clinicians. Early identification of surgical site infection (SSI) is essential for reducing postoperative morbidity. Methods: Patients ≥18 years old who underwent surgery at 9 affiliated Mayo Clinic hospitals (2019-2022) and were captured by the National Surgical Quality Improvement Program (NSQIP) were included. Eligibility required submission of one image via the patient portal within 30 days after surgery. Images were independently screened in duplicate to determine the presence of an incision. SSI outcomes were obtained from NSQIP. The developed model consisted of 2 stages: incision detection and SSI detection in images with incisions. Four pretrained architectures were evaluated using 10-fold cross-validation, with upsampling and data augmentation to mitigate class imbalance. An end-to-end pipeline, image quality assessment and sensitivity analysis stratified by race were also performed. Results: Among 6060 patients, the median age was 54 years (interquartile range: 40–65), 61.4% (n=3805) were female, and 92.5% (n=5731) identified as White. SSIs were confirmed in 6.2% (n=386) images. Vision Transformer outperformed all others, achieving an incision detection accuracy of 0.94 (area under the curve=0.98) and an SSI detection accuracy of 0.73 (area under the curve=0.81). In addition, it demonstrated strong performance in assessing image quality. Sensitivity analysis revealed comparable performance across racial subgroups. Conclusion: This artificial intelligence pipeline demonstrates promising performance in automating wound image assessment and SSI detection, reducing clinical workload and improving postoperative care.

e14551 Background: Extracellular vesicles (EVs) are microscopic particles released by all cell types with a distinct fingerprint reflecting the cell of origin. In patients with prostate cancer, PSMA+EVs have been associated with clinical outcomes. In this study, we investigated tumor-derived EVs (tdEVs) using the tumor-specific CD326 marker as a novel biomarker for pancreas ductal adenocarcinoma (PDAC). Methods: The study included patients with localized PDAC treated on a prospective phase 2 clinical trial evaluating a 15-fraction chemoradiation (CRT) regimen. Blood samples were obtained after induction chemotherapy (C) (prior to CRT) and in follow-up. 20 healthy controls were included. High-resolution flow cytometry enumerated levels of fluorescent antibody labelled tumor-specific CD326 (EpCAM)-positive EVs. All samples were de-identified and randomly coded. The technologist responsible for EV analysis was blinded to patient information and clinical data. Each sample was run in triplicate. Flow cytometry data was analyzed with custom-built software to automatically determine and apply gates and generate reports with scatter plots and EV concentrations for each combination of markers and data summaries. Results: tdEV data were analyzed from 70 patients with pre-CRT samples. Patients had mean age 66 years (9.0 standard deviation), with 60% ECOG 0, 43% borderline resectable and 48% locally advanced. Patients had a median 8 cycles of C prior to CRT, and 70% proceeded to surgery after CRT. 2-year overall survival (OS) was 54%. Patient samples showed elevated total CD326 EVs compared to the healthy controls (p = 0.0005). Furthermore, patient CD326 EVs revealed two distinct subpopulations: small (120-1,000nm) and large (1,000-3,000nm) size CD326 EVs. No large CD326 subpopulation was found in healthy donor samples. Higher pre-CRT levels of total CD326 and large CD326 EVs were associated with decreased progression-free survival (PFS) (hazard ratio (HR) = 2.38, p = 0.013 and HR = 2.017, p = 0.021) on multivariable models with surgical resection. Resection was associated with increased PFS (p < 0.0001), and the interaction terms did not meet significance (p = 0.083 and p = 0.21). No differences in pre-CRT total or large CD326 EVs were identified between patients with or without surgical resection (p = 0.72 and p = 0.83). CA19-9 levels were not predictive of clinical outcomes in this trial and showed no association with EV levels. Conclusions: We present an association between clinical outcomes and tdEVs in PDAC, highlighting their potential as a novel, independent biomarker. If validated, tdEVs may offer an opportunity to personalize care and improve risk stratification.

e14626 Background: Despite advancements in neoadjuvant therapy and surgical techniques, patients with pancreatic ductal adenocarcinoma (PDAC) often experience high recurrence rates after total neoadjuvant therapy (TNT) and resection. Existing tumor response scoring systems, such as the College of American Pathologists (CAP) guidelines, fail to stratify recurrence risk effectively, emphasizing the need for novel, objective approaches. Methods: This study evaluated spatial characteristics of residual cancer and stroma in a multi-site cohort of 203 patients with resected PDAC following TNT, not having achieved a major pathologic response (CAP 2 or 3). Whole slide images (WSI) of hematoxylin and eosin-stained sections were digitized and analyzed using artificial intelligence to perform tissue segmentation. Metrics quantifying spatial morphology and configuration, inspired by principles of landscape ecology, were computed to explore spatial features of the tumor microenvironment (TME). Statistical models (recursive partitioning and regression tree [RPRT] model and Cox model with backwards eliminations) incorporating these features were developed to stratify recurrence risk. Results: Five metrics were used for risk classification model build. Three models successfully classified patients into high- and low-risk groups based on spatial metrics. Models demonstrated moderate discriminatory power (C-statistics: 0.560–0.566) and showed that increased tumor fragmentation, like stromal patch density and cancer patch shape index, were strongly associated with improved outcomes. Conclusions: Integrating spatial metrics of cancer-stroma configuration enhances risk stratification beyond conventional scoring systems. Given increased tumor fragmentation is associated with improved outcomes, these data indirectly suggest ecological mechanisms of treatment resistance. This approach offers a pathway toward personalized post-operative management strategies to improve outcomes in PDAC. Risk classification models. Model Description Event/n Median DFS (95% CI) HR(95% CI) p-value C-statistics 1(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 87 / 101 8.22(5.72 – 10.1) 1.64(1.20 – 2.25) 0.002 0.562 Low risk: log standard deviation of the stroma shape index ≤ 0.651 71 / 102 11.90(9.24 – 25.1) Ref 2(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 & mean cancer shape index ≤ 1.775 58 / 63 7.23(5.19 – 9.63) 1.82(1.31 – 2.52) 0.0003 0.560 Low risk: (log standard deviation of the stroma shape index > 0.651 & mean cancer shape index > 1.775) or log standard deviation of the stroma shape index ≤ 0.651 100 / 140 11.57(9.24 – 17.92) Ref 3(Backwards elimination) High risk: PI * > median 86 / 101 8.02(6.08 – 9.86) 1.73(1.26 – 2.37) 0.0007 0.566 Low risk:PI * ≤ median 72 / 102 15.72(9.97 – 25.05) Ref *PI: (0.2701 * log mean stroma area) + (0.3905 * log edge density).

Abstract Despite advances in surgery and chemotherapy, patients with resectable pancreatic ductal adenocarcinoma (PDAC) face high recurrence rates (40-60%). Total neoadjuvant therapy (TNT) seeks to enhance margin-negative resections (R0) and address micrometastatic disease, with potential survival benefits. Yet, TNT still results in high recurrence rates, with 1-, 2-, and 3-year disease-free survival (DFS) at 65%, 48%, and 32%, respectively. Residual cancer extent is a key prognostic factor in PDAC after TNT. Tumor response scores show favorable outcomes only for patients achieving near-complete or complete pathologic response. In a cohort of 511 PDAC patients treated with TNT and surgery (2015-2022), improved DFS was only found in those with a complete pathologic response (pCR, 7.8%). This highlights the limited use of current response scoring in stratifying post-TNT patient risk, underscoring the need to better understand disease persistence and relapse. Here we developed a quantitative method to assess residual cancer. Using a digital pathology H&E library from 2180 PDAC cases (2000-2022), an AI platform segmented tissue into cancer epithelium, stroma, and normal regions. For 202 TNT-treated cases without pCR, we calculated a ratio of cancer area to stromal area from representative slides. Modeled after the histologic tumor regression grade (HTRG) system, cases were classified into &lt;5%, 5-50%, or &gt;50% cancer-to-stroma ratios. However, this measure alone showed no difference in DFS, suggesting tumor burden cannot fully explain differences in clinical outcomes. We hypothesized that the spatial organization of the tumor microenvironment (TME) is a determinant of patient outcomes. Drawing from landscape ecology, which studies spatial properties of ecosystems, we applied similar principles to analyze tissue architecture. Using an AI-based two-class segmentation of whole-slide images, we assessed spatial features like patch area, perimeter, density, and Shannon diversity. Python’s ‘pylandstats’ package calculated 21 spatial metrics, reduced via stepwise Cox regression using the Akaike information criterion (AIC). The final model included mean Shannon diversity, mean and standard deviation of stromal patch areas, and stromal patch density. Kaplan-Meier analysis of 202 samples stratified model predictions into quartiles, correlating with high (mean DFS 10.85 months), medium (19.32 months), and low risk (25.92 months) groups. These findings aligned with model expectations, underscoring the potential of spatial TME analysis to predict outcomes. Citation Format: Andrea V. Maraone, Zafar Siddiqui, Luis H. Cisneros, Merih D. Toruner, Mark Truty, Cornelius Thiels, Robert R. McWilliams, Steven R. Alberts, Rondell P. Graham, Carlo Maley, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Tumor spatial configuration predicts pancreatic cancer recurrence risk after total neoadjuvant therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5070.

Abstract Given the heterogeneous clinical behavior of pancreatic neuroendocrine tumors (pNETs), improved prognostic markers are needed to guide management and post‐resection surveillance. Patients who underwent resection of large (≥3 cm) sporadic well‐differentiated pNETs from 2000 to 2019 were identified. The Ki‐67 proliferation index was determined using immunohistochemistry, and alternative lengthening of telomeres (ALT) status was assessed using fluorescence in situ hybridization. Recurrence‐free and overall survival were estimated using Kaplan–Meier analysis. Multivariable Cox regression analysis evaluated factors associated with recurrence‐free survival. A total of 106 patients were identified. ALT was positive in 57 (54%) and negative in 49 (46%). Ki‐67 was ≥3% in 74 (70%) and <3% in 32 (30%). Tumors with Ki‐67 ≥3% were more likely to be ALT positive (61% vs. 38%, p = .046). Stratifying by ALT status and Ki‐67 proliferation index, median recurrence‐free survival was 4.6 years for patients with ALT‐positive/Ki‐67 ≥3% tumors, 3.1 years for patients with ALT‐positive/Ki‐67 <3% tumors, 12.4 years for patients with ALT‐negative/Ki‐67 ≥3% tumors, and 20.2 years for patients with ALT‐negative/Ki‐67 <3% tumors ( p < .001). Initial recurrence was distant in 82% and locoregional in 18%. Across all groups, overall survival was similar ( p = .19). In multivariable analysis, advanced age, ALT positivity, perineural invasion, and lymph node metastases were associated with increased recurrence risk (all p < .05). ALT and Ki‐67 provide complementary information on post‐resection recurrence risk, which can guide subsequent surveillance and management strategies. These data support the incorporation of ALT testing into routine clinical practice.

The peritoneum is the second most common site of metastasis in patients with pancreatic ductal adenocarcinoma (PDAC). Up to half of all patients that undergo curative-intent resection eventually develop peritoneal metastasis (PM), which accounts for significant morbidity and drives mortality. Despite recent advances in management, PM is associated with very poor prognosis, which is often measured in weeks to months. Clinical manifestations including bowel obstruction, ascites, and urinary obstruction have profound impact on quality of life. Even with relatively advanced disease, PM often remains occult on imaging and thus tend to be underdiagnosed and understudied. Many patients with peritoneal-only PM are excluded from clinical trials because response cannot be measured by standard radiographic criteria. Furthermore, as patients with PM are not eligible for surgical resection and low-volume peritoneal disease is often not amenable to percutaneous biopsy, tissue samples for peritoneal-specific translational studies are limited. Intraperitoneal therapeutics have been proposed as an attractive option for PM, as better penetration of tumor tissue can be achieved with less systemic toxicity compared with intravenous chemotherapy. Heated intraperitoneal chemotherapy (HIPEC), typically combined with cytoreductive surgery (CRS), is an option for select patients with PM from gynecologic or gastrointestinal primary, and for patients with primary peritoneal mesothelioma. However, the incorporation of locoregional therapy for PM in patients with PDAC has been poorly studied given the aggressive nature of pancreatic cancer and overall poor prognosis. With recent advances in existing treatment options, there may be a subset of patients who may derive benefits from locoregional control with cytoreduction and/or intraperitoneal chemotherapy. Critically, additional work is needed to determine PM-favorable clinical and tumoral predictive biomarkers to identify patients who may benefit from a more aggressive approach. We describe the current state of management of patients with peritoneal metastasis from PDAC and review the available data exploring peritoneal-directed therapy with cytoreductive surgery and/or intraperitoneal chemotherapy.

ABSTRACT Background Surgical resection for pancreas ductal adenocarcinoma (PDAC) remains the mainstay of treatment. Regardless of enhanced survival rates, disparities in patient outcomes and experiences driven by the social determinants of health (SDH) persist. The area deprivation index (ADI) comprises 17 indicators related to education, employment, housing‐quality, and poverty. We sought to examine the impact of ADI on surgical outcomes of PDAC patients. Methods Patients who underwent pancreatoduodenectomy or distal pancreatectomy for PDAC between January 2011 and December 2022 were identified. ADI was calculated using patient zip codes and categorized into quartiles, with the highest indicating the most marginalized. The primary outcome was loss to follow‐up after surgical resection. To account for confounders, a competing risk multivariable regression analysis was used. Results A total of 1001 patients had a mean age of 66.6 (±9.64), with 46.3% ( n = 463) of patients being female. A majority, 94.6% ( n = 947), identified as white, and 64.1% ( n = 641) had at least a college degree. The median length of follow‐up after surgery was 1.8 years (interquartile range: 0.9–3.5). Multivariable analysis adjusting for competing risk of death, showed that patients who are least marginalized are 1.57 times more likely to have their follow‐up than those most marginalized (hazard ratio: 1.57, 95% confidence interval: 1.08–2.29, p = 0.017). Conclusion SDH impact many aspects of patient's care including a higher risk of loss to follow‐up for marginalized patients after surgery for PDAC. Future efforts should seek to identify and lower barriers faced by marginalized patients with system‐level changes to ensure equitable access.

Background Short-term outcomes after pancreatoduodenectomy (PD) are well-studied, but long-term reoperation rates and their indications remain poorly characterized. Methods A single-center retrospective chart review was performed on patients who underwent PD for pancreatic adenocarcinoma between 1/2011 and 12/2021. Reoperations occurring >90 days after PD were dichotomized to being related or unrelated to the index PD or pancreatic adenocarcinoma. The Kaplan-Meier analysis estimated the incidence of long-term reoperation at 1 and 5 years postoperatively. Results Six-hundred twenty-eight patients were included. The 5-year incidence of any additional operation >90 days after PD was 30.0% (95% CI 23.2-36.2%), and the 5-year incidence of any long-term related reoperation was 21.2% (95% CI 15.0-26.8%). The most common indications for reoperations by 5-year incidence were cancer recurrence (12.8%, 95% CI 7.6-17.7%), incisional hernia (6.2%, 95% CI 2.6-9.7%), small bowel obstruction (1.3%, 95% CI 0.2-2.4%), and leak, fistula, or infection (1.0%, 95% CI 0.1-2.0%). Of the examined risk factors, only 90-day reoperation was found to be predictive of long-term related reoperations ( P = 0.02). Additionally, the 5-year incidence of endoscopic or interventional radiology procedures was 20.2% (95% CI 14.5-25.4%). However, 40.9% (95% CI 33.6-47.3%) of patients required additional surgery or procedures of any kind between 90 days and 5 years after PD. Discussion Within 5 years of PD, one in three patients required additional surgery, and one in five had operations for related indications. Related reoperative indications included recurrence, hernia, PD-specific complications, and small bowel obstruction. However, the rates of each of these reoperations were relatively low.