Prediction of pancreatic neuroendocrine tumor grading using an artificial intelligence–based video analysis model (GradAINet) applied to contrast-enhanced EUS videos

作者：Matteo Tacelli, Adrien Meyer, Gaetano Lauri, Armine Vardazaryan, Paolo Biamonte, Bastien Andlauer, Rubino Nunziata, Gabriele Capurso, Leonardo Sosa-Valencia, Nicolas Padoy, Paolo Giorgio Arcidiacono · 发表于：Endoscopic Ultrasound · 年份：2026 · DOI：10.1097/eus.0000000000000190 · 研究领域：Neuroendocrine Tumor Research Advances、Pancreatic and Hepatic Oncology Research、Lung Cancer Research Studies

Background and Objectives: Pancreatic neuroendocrine neoplasms (PNENs) are rare tumors with heterogeneous outcomes. Tumor grading (G), based on mitotic count and Ki-67 index, is the main prognostic factor guiding treatment. EUS-guided fine-needle aspiration/biopsy is the current standard but shows a misgrading rate up to 25%. We evaluated an artificial intelligence-based video analysis model to predict PNEN grading from contrast-enhanced EUS (CE-EUS) recordings. Methods: This retrospective study was conducted at Istituti di Ricovero e Cura a Carattere Scientifico San Raffaele Hospital, Milan, a European Neuroendocrine Tumor Society Center of Excellence. Patients were eligible if CE-EUS videos ≥1 minute (arterial and venous phases) and cyto-histological confirmation of PNEN were available. Exclusion criteria included mixed neuroendocrine-non-neuroendocrine neoplasms, missing Ki-67 grading, or poor video quality. CE-EUS videos were processed with a deep-learning video transformer model (GradAINet). The dataset was split into training (70%), validation (10%), and testing (20%) cohorts. Diagnostic performance was evaluated using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and F1-score. Results: Between 2022 and 2024, 115 patients were included (49 female, 42.6%): 70 had G1, and 45 had G2-G3 tumors. Overall, 253,751 video frames were analyzed. GradAINet achieved a sensitivity of 0.817 (95% confidence interval [CI]: 0.556-1.000), specif...