[2604.09197] Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma

Computer Science > Computer Vision and Pattern Recognition arXiv:2604.09197 (cs) [Submitted on 10 Apr 2026] Title:Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma Authors:Francesca Fati, Felipe Coutinho, Marika Reinius, Marina Rosanu, Gabriel Funingana, Luigi De Vitis, Gabriella Schivardi, Hannah Clayton, Alice Traversa, Zeyu Gao, Guilherme Penteado, Shangqi Gao, Francesco Pastori, Ramona Woitek, Maria Cristina Ghioni, Giovanni Damiano Aletti, Mercedes Jimenez-Linan, Sarah Burge, Nicoletta Colombo, Evis Sala, Maria Francesca Spadea, Timothy L. Kline, James D. Brenton, Jaime Cardoso, Francesco Multinu, Elena De Momi, Mireia Crispin-Ortuzar, Ines P. Machado View a PDF of the paper titled Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma, by Francesca Fati and 27 other authors View PDF HTML (experimental) Abstract:Purpose. High-grade serous ovarian carcinoma (HGSOC) is characterized by pronounced biological and spatial heterogeneity and is frequently diagnosed at an advanced stage. Neoadjuvant chemotherapy (NACT) followed by delayed primary surgery is commonly employed in patients unsuitable for primary cytoreduction. The Chemotherapy Response Score (CRS) is a validated histopathological biomarker of response to NACT, but it is only available postoperatively. In this study, we investigate whe...