Your browser doesn't support javascript.
loading
Clinical implementation of artificial-intelligence-assisted detection of breast cancer metastases in sentinel lymph nodes: the CONFIDENT-B single-center, non-randomized clinical trial.
van Dooijeweert, C; Flach, R N; Ter Hoeve, N D; Vreuls, C P H; Goldschmeding, R; Freund, J E; Pham, P; Nguyen, T Q; van der Wall, E; Frederix, G W J; Stathonikos, N; van Diest, P J.
Affiliation
  • van Dooijeweert C; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands. c.vandooijeweert-3@umcutrecht.nl.
  • Flach RN; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Ter Hoeve ND; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Vreuls CPH; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Goldschmeding R; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Freund JE; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Pham P; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Nguyen TQ; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • van der Wall E; Department of Medical Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Frederix GWJ; Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Stathonikos N; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • van Diest PJ; Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands. p.j.vandiest@umcutrecht.nl.
Nat Cancer ; 5(8): 1195-1205, 2024 Aug.
Article in En | MEDLINE | ID: mdl-38937624
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 Number14323711) 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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Artificial Intelligence / Sentinel Lymph Node / Lymphatic Metastasis Limits: Adult / Aged / Female / Humans / Middle aged Language: En Journal: Nat Cancer Year: 2024 Document type: Article Affiliation country: Netherlands Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Artificial Intelligence / Sentinel Lymph Node / Lymphatic Metastasis Limits: Adult / Aged / Female / Humans / Middle aged Language: En Journal: Nat Cancer Year: 2024 Document type: Article Affiliation country: Netherlands Country of publication: United kingdom