Clinical Validation of AI-Assisted Evaluation of Indeterminate Biliary Strictures in Digital-Single Operator Cholangioscopy: A Transcontinental Multicentric Study.
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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Mascarenhas Miguel, Widmer Jessica, Mendes Francisco, Ribeiro Tiago, Pinto da Costa Antonio, Agudo Belén, Martins Miguel, Afonso João, Mota Joana, Almeida Maria João, Cardoso Pedro, Frias Joana, Araújo Catarina, Cardoso Hélder, Plaza González Maria, Pérez-González Ana, Lera Dos Santos Marcos Eduardo, Moris Maria, Garcia de Paredes Ana Garcia, Foruny José, Bicudo de Oliveira Luiza, Ferreira de Carvalho Matheus, Maluf-Filho Fauze, Ferreira Maria Clara, Prince Tomazo, Velasquez Andrea, González Ivan Enrique, Ferreira João, Kim Grace E, Siddiqui Uzma D, Omrani Laleh R, Alrossais Naif, Keegan Mathew, Aslam Perveen, Aggarwal Vipul, Vilas-Boas Filipe, Pereira Pedro, Sabbagh Luis Carlos, Almuhaidb Aymen, Guimarães Hourneaux De Moura Eduardo, Macedo Guilherme, González-Haba Mariano
Аннотация
METHODS: This multicenter study included 135 D-SOC examinations from 129 patients (61 with malignant BS) across 14 centers in the United States, Brazil, Spain, Colombia, Australia, and Saudi Arabia. For each examination, up to 25 clinically relevant frames were selected and uploaded to a web-based platform for AI analysis. The model performed both detection and differentiation of BS: Detection was assessed by comparing AI-generated bounding boxes with expert-defined annotations using intersection-over-union (IoU), while differentiation was benchmarked against histopathology. Performance metrics included accuracy, sensitivity, specificity, and positive and negative predictive values.
RESULTS: At the patient level, malignant BS were identified with 86.0% accuracy, 84.1% sensitivity, and 85.7% specificity, with an area under the curve of 0.904. The model demonstrated robust detection performance, achieving a mean IoU of 70.3%. Performance was maintained across demographic variables and centers.
DISCUSSION: This first multicentric validation study demonstrates real-world performance of AI-assisted D-SOC analysis across multiples continents and devices, with robust accuracy for BS detection and differentiation. These findings support AI as an adjunctive tool in D-SOC, enhancing a more accurate evaluation of patients with indeterminate BS.