Thiels, Cornelius A.

ABSTRACT Background Evaluating fairness in artificial intelligence (AI) is essential before clinical implementation to prevent unintended harm across diverse patient populations. This study assesses performance differences of an image-based surgical site infection (SSI) detection model across age, gender, geography, race, and skin color. Methods Model development/validation study using retrospective, multicenter data across surgical subspecialties from adults who submitted an image of their incision via the electronic health record within 30 days of their procedure between 2019-2024. Area under receiver operating curve (AUROC) was compared by age (<55 vs. ≥55 years old), gender (male vs. female), geography (Rochester, Minnesota vs. Jacksonville, Florida vs. Scottsdale, Arizona vs. regional Minnesota/Wisconsin areas), race (White/Caucasian vs. non-White/Caucasian), and skin color (Fitpatrick I-III vs. IV-VI and Monk A-E vs. F-J). Results Training data contained 13,702 images from 4,274 patients between 2019-2022 (50.1% ≥55 years old; 63.2% female; 91.6% White/Caucasian; 58.5% Rochester, 17.3% Florida, 10.5% Arizona; 96.3% light skin tone), of which 1,348 images (9.8%) had an SSI. No differences in SSI detection existed for age, gender, race, or skin color (AUROC 0.83-0.87, p>0.09), however geographical differences were significant: lowest AUROC 0.83 (95% CI 0.77-0.88) vs. highest AUROC 0.87 (95% CI 0.84-0.89, p=0.01). Temporal validation using 4,242 images from 1,353 patients between 2022-2023 showed intact fairness across subgroups (ΔAUROC ≤0.06) except geography (ΔAUROC ≤0.16). Conclusions The model behaved fairly across age, gender, race, and skin color, however geographical differences persisted. These findings have practical implications underscoring the importance of evaluating bias in clinical AI before deployment.

ABSTRACT Background and Objectives Pancreatic ductal adenocarcinoma (PDAC) remains highly lethal, but the contribution of nonbiological factors to long‐term survival is unclear. We evaluated demographic, socioeconomic, clinical, treatment, and care‐delivery factors associated with 3‐year survival and whether these associations persisted at 5 years. Methods National Cancer Database patients with stage I–III PDAC diagnosed from 2012 to 2022 were analyzed using multivariable logistic regression adjusted for treatment pathway. Results Among 57,053 patients, 51,071 were eligible for a 3‐year analysis, and 12,205 (23.9%) survived. Compared with chemotherapy alone, surgery with chemotherapy (OR, 7.12; 95% CI, 6.64–7.63) and surgery alone (OR, 3.84; 95% CI, 3.49–4.23) had the strongest associations with survival. Younger age, lower comorbidity, Asian race, Spanish/Hispanic ethnicity, private insurance, lower grade, body or tail location, and lower nodal burden were independently associated with survival. Black race and treatment timing were not significant after adjustment. Findings were directionally consistent at 5 years. Conclusion Demographic, socioeconomic, and clinical factors independently influence 3‐year survival in PDAC. These findings underscore the need to complement biologic and therapeutic advances with structural interventions, such as insurance expansion and improved access to high‐quality centers, to mitigate disparities and improve outcomes in this highly lethal cancer.

ABSTRACT Background ACS‐NSQIP began capturing operative approach in 2022. With increased adoption of minimally invasive (MIS) techniques for malignancy, a contemporary review of benchmark outcomes for open, laparoscopic and robotic gastrectomy is warranted. Methods We performed a retrospective cohort study of adults in ACS‐NSQIP (2022–2024) undergoing partial or total gastrectomy (CPT 43631‐4 and 43620‐2) for cancer. Outcomes included operative time, length of stay (LOS), unplanned conversion‐to‐open, and 30‐day morbidity, mortality, and readmission. Multivariable logistic regression evaluated patient and operative factors associated with morbidity. Results Among 1,459 patients (median age 66, 60.4% male), 66.8% underwent partial gastrectomy and 33.2% total gastrectomy. Approaches were 61.2% open, 19.5% laparoscopic, and 19.3% robotic. Thirty‐day mortality (1.8%), major complications (18.2%), and readmissions (10.3%) did not differ by approach. Unplanned conversion‐to‐open occurred in 14.0% of MIS. Robotic had longer median operative time of +1.2 and +1.7 h than laparoscopic and open and median −1 and −2 days shorter LOS respectively ( p < 0.001). Hypoalbuminemia (OR 3.10), CKD ≥ 3 (OR 1.75), and anemia (OR 1.48) were independently associated with major complications ( p < 0.05). Conclusion Operative approach influences operative time and LOS but not short‐term morbidity and mortality. The newly available ACS‐NSQIP operative approach variable enables approach‐specific benchmarks for cancer‐related gastrectomy.

BACKGROUND: Surgeons and ostomy nurses receive a high volume of stoma photos from patients. OBJECTIVE: This study aimed to develop and validate an automated and scalable artificial intelligence pipeline for identification and triage of patient-submitted intestinal ostomy photos. DESIGN: Retrospective derivation and validation study with stakeholder engagement to guide model design. Clinical teams reviewed photos in duplicate and categorized them into: (a) obstructed view, (b) healthy stoma, (c) suitable for conservative management, or (d) requiring in-person review. Pre-trained neural networks including MobileNetV4, ResNet50, ViT and CLIP-ViT were fine-tuned with 5-fold cross-validation. SETTINGS: Nine Mayo Clinic hospitals (2019–2022). PATIENTS: Adult patients (≥18 years) undergoing surgery who submitted images within 30 days after surgery. MAIN OUTCOME MEASURES: Model performance was evaluated with area under the receiver operator curve, precision, recall, and F1-scores. RESULTS: In this study, 538 photos of abdominal ostomies were sent in by 191 patients (median age 52 years, IQR 40–63; 60.4% female). Expert consensus triaged 236 (43.9%) photos as having an obstructed view, 30 (5.6%) as healthy, 177 (32.9%) for conservative management, and 95 (17.7%) for in-person review. All models achieved area under the receiver operator curve >0.97 for identifying stomas. The CLIP-ViT model performed best at triage (macro- area under the receiver operator curve 0.94 ± 0.06; F1 0.77 ± 0.10). End-to-end detection and triage using CLIP-ViT achieved area under the receiver operator curve of 0.99 ± 0.01, precision of 0.87 ± 0.08, recall of 0.93 ± 0.04, and F1 of 0.89 ± 0.07. Attention maps showed that models focused on stomas to determine classification. LIMITATIONS: Low sample size and lack of prospective validation. CONCLUSIONS: A vision language model pipeline accurately detected and triaged patient-submitted ostomy photos. Prospective evaluation is now needed to support integration into multidisciplinary digital workflows. See Video Abstract .

Abstract Purpose: Pancreatic ductal adenocarcinoma (PDAC) frequently recurs after neoadjuvant therapy (NT) and curative-intent resection. Although major pathologic response predicts favorable outcomes, most patients achieve only minor response with a heterogeneous recurrence risk. We asked whether the spatial organization of residual PDAC encodes clinically relevant biology beyond residual tumor burden. Experimental Design: In a retrospective cohort of 203 patients with resected PDAC treated with NT and restricted to minor pathologic response, routine hematoxylin and eosin (H&E) whole-slide images were segmented into cancer and stroma using an artificial intelligence–enabled pipeline. Spatial composition (patch density, edge density) and configuration (compactness/complexity, intermixing) were quantified and tested for associations with disease-free survival (DFS) using multivariable models adjusted for standard clinicopathologic factors. Results: Shorter DFS was associated with a fragmented, interface-rich tumor–stroma ecology featuring higher edge density and diversity and reduced homotypic aggregation, independent of clinicopathologic variables. Two spatial risk models were independently prognostic: (i) cancer mean shape index plus stromal shape index variability [adjusted hazard ratio (HR), 1.71; P = 0.003] and (ii) mean stromal patch area plus edge density (adjusted HR, 2.19; P = 0.002). Both models stratified outcomes in which pathologic response grading and residual cancer area did not. High-risk configurations were further associated with reduced intratumoral tumor-infiltrating lymphocyte (TIL) density and infiltration ratio, with relative TIL accumulation at the cancer periphery and within the stroma, consistent with an immune-excluded phenotype. Conclusions: Residual cancer–stroma topology quantified from standard H&E slides yields independent prognostic signals after NT in PDAC, provides a cellular immune correlate for spatial risk, and motivates prospective validation and spatially informed adjuvant strategies.

Abstract Carcinoid heart disease (CHD) is associated with advanced neuroendocrine tumor liver metastases (NETLM) and may preclude surgical cytoreduction. We assessed perioperative and long‐term outcomes of hepatectomy in patients with CHD. We retrospectively analyzed 311 patients undergoing cytoreductive hepatectomy for intestinal NETLM: non‐functional ( n = 163), carcinoid syndrome (CS) without CHD ( n = 110), and CHD ( n = 38), including patients undergoing pre‐hepatectomy valve replacement. CHD patients more frequently had >10 liver metastases (78%) and larger lesions (median 9.5 cm) and required major hepatectomy more often (58%). Major morbidity was higher in CHD (up to 47%), yet 90‐day mortality remained low (≤4%). Median overall survival after hepatectomy was comparable across groups (12.5 vs. 9.1 vs. 11.4 years; p = .19), including matched analyses. With optimal cardiac management, cytoreductive hepatectomy in CHD is feasible and provides long‐term survival comparable to patients without CHD.

TPS160 Background: Up to 50% of patients with gastric cancer (GC) may develop peritoneal metastasis (PM) that is associated with resistance to systemic therapy and poor prognosis. Although cytoreductive surgery and intraperitoneal (IP) chemotherapy were shown to modestly improve the survival of patients with PM from gastric GC (PM-G), these clinical trials were performed in the pre-immunotherapy era. The significant heterogeneity in trial design and patient selection criteria further limit the applicability of these trial results to current clinical practice where anti-PD-1/L1 immunotherapy and/or targeted therapy in combination with chemotherapy have become a common, standard first-line therapy for the majority of patients with metastatic GC, raising the question of whether chemotherapy such as paclitaxel remains the most effective IP therapy. IP therapy using novel immunotherapy such as bispecific antibodies and chimeric antigen receptor T-cell therapy have demonstrated safety and promising antitumor activities in PM-G. We are conducting a phase 1b clinical trial that evaluates the efficacy of IP interleukin-2 (IL-2) in patients with PM-G with stable disease on first-line chemo-immunotherapy based on the hypothesis that IP IL-2 may synergize with intravenous (IV) chemo-immunotherapy to improve the treatment of PM-G. Multi-omics studies using patient blood, peritoneal fluid, and tissue specimens serially collected from this trial will be performed to characterize the changes in the tumor immune microenvironment of PM-G and identify new therapeutic targets. Methods: Patients with PM only from gastric adenocarcinoma are eligible for this phase 1b trial. All participants will continue IV fluorouracil-containing chemotherapy with nivolumab every 2 weeks and concurrently receive up to 16 doses of IP IL-2 (aldesleukin 6 × 10 5 IU/m2) weekly through an indwelling peritoneal catheter (Bard). Diagnostic laparoscopy (DL) will be performed before initiation of IP IL-2 and after 8 doses of IP therapy to assess treatment response based on the peritoneal cancer index (PCI), which is the primary endpoint of the trial. Patients with at least stable radiographic disease will continue to receive another 8 doses of IP IL-2 and undergo a third DL. Secondary endpoints include safety, peritoneal regression grading score, overall survival, and progression-free survival. Major inclusion criteria include mismatch repair-proficient or microsatellite-stable GC, PCI of 3-24, absence of distant metastasis other than PM, stable disease on first-line IV chemo-immunotherapy, tolerability of anti-PD-1 therapy, and adequate organ function. Enrollment began in 2024 and remains active. To date, seven of planned 15 patients have received study treatment without significant treatment-related adverse events and three of these patients underwent curative-intent cytoreductive surgery. Clinical trial information: NCT05802056 .

Objective: To develop a predictive model for pathological complete response (pCR) after total neoadjuvant therapy (TNT) to inform selection for watch-and-wait (W/W). Summary Background Data: Patient selection for W/W after TNT for locally advanced rectal cancer remains challenging. Methods: An ensemble of tabular foundation models was fine-tuned in adults with clinical stage II or III microsatellite stable primary rectal adenocarcinoma undergoing TNT and total mesorectal excision (TNT+TME) from 2018-2023 to predict pCR, using pre-TNT, post-TNT and pre-TME variables. This model was externally validated on patients having TNT and W/W (TNT+W/W) to predict persistent clinical complete response (pcCR; the absence of local regrowth, distant metastases, or persistent near-cCR). Area under the receiver operator curve (AUROC), area under the precision-recall curve (AUPRC), and Brier score were calculated with 95% confidence intervals (CI). Results: Among 308 patients that underwent TNT+TME (median age 56; 40% female), the model predicted pCR with an AUROC 0.71 (95% CI 0.65-0.77), AUPRC 0.44 (95% CI 0.35-0.57), and was well calibrated with a Brier score of 0.17 (95% CI 0.15-0.20). At external validation in a cohort of 83 patients that are being managed with TNT+W/W (median age 57; 37% female), the model predicted pcCR with an AUROC 0.69 (95% CI 0.57-0.82), AUPRC 0.90 (95% CI 0.82-0.96), and Brier score of 0.30 (95% CI 0.26-0.33), improving to 0.17 with recalibration. Conclusions: This novel predictive model demonstrated good discrimination and calibration for pCR after TNT+TME with utility in TNT+W/W for pcCR after appropriate recalibration, supporting its application for W/W patient selection.

ABSTRACT Background and Objectives Occult intra‐abdominal metastases are identified in approximately 20% of patients with radiographically localized pancreatic ductal adenocarcinoma (PDAC) through staging laparoscopy, as peritoneal cytology is limited in sensitivity. Methylated DNA markers (MDMs) have demonstrated high diagnostic accuracy for PDAC in tumor tissue, blood, and pancreatic secretions. This study assesses the feasibility and diagnostic performance of MDMs in peritoneal lavage fluid collected during staging laparoscopy, comparing their performance to mutant KRAS (m KRAS ) detection. Methods DNA from peritoneal lavage fluid of PDAC patients was analyzed for m KRAS mutations (codons 12, 13, and 61) using droplet‐digital PCR and for 13 MDMs and a reference gene (B3GALT6) using quantitative methylation‐specific PCR. An MDM score was generated from the average signal of the 13 MDMs and evaluated for its ability to detect intra‐abdominal metastases via receiver operator characteristic (ROC) analysis. Results Among 48 patients, 15 (31%) had intra‐abdominal metastases. The MDM score showed 87% sensitivity and 90% specificity (AUC = 0.98), outperforming m KRAS , which showed 40% sensitivity and 85% specificity (AUC = 0.62; p < 0.0001). Conclusions MDMs in peritoneal lavage fluid may enable highly accurate molecular staging of PDAC and warrant validation in larger studies.