Clinical implementation of artificial-intelligence-assisted detection of breast cancer metastases in sentinel lymph nodes: the CONFIDENT-B single-center, non-randomized clinical trial
Carmen van Dooijeweert, R. N. Flach, Natalie D. ter Hoeve, Celien P.H. Vreuls, Roel Goldschmeding, Jan Erik Freund, P. Pham, Tri Q. Nguyen, Elsken van der Wall, G. W. J. Frederix, Nikolas Stathonikos, P. J. van Diest
Abstract
Pathologists' assessment of sentinel lymph nodes (SNs) for breast cancer (BC) metastases is a treatment-guiding yet labor-intensive and costly task because of the performance of immunohistochemistry (IHC) in morphologically negative cases. This non-randomized, single-center clinical trial (International Standard Randomized Controlled Trial Number:14323711) assessed the efficacy of an artificial intelligence (AI)-assisted workflow for detecting BC metastases in SNs while maintaining diagnostic safety standards. From September 2022 to May 2023, 190 SN specimens were consecutively enrolled and allocated biweekly to the intervention arm (n = 100) or control arm (n = 90). In both arms, digital whole-slide images of hematoxylin-eosin sections of SN specimens were assessed by an expert pathologist, who was assisted by the 'Metastasis Detection' app (Visiopharm) in the intervention arm. Our primary endpoint showed a significantly reduced adjusted relative risk of IHC use (0.680, 95% confidence interval: 0.347-0.878) for AI-assisted pathologists, with subsequent cost savings of ~3,000 €. Secondary endpoints showed significant time reductions and up to 30% improved sensitivity for AI-assisted pathologists. This trial demonstrates the safety and potential for cost and time savings of AI assistance.