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Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research.
Ly, Amy; Garcia, Victor; Blenman, Kim R M; Ehinger, Anna; Elfer, Katherine; Hanna, Matthew G; Li, Xiaoxian; Peeters, Dieter J E; Birmingham, Ryan; Dudgeon, Sarah; Gardecki, Emma; Gupta, Rajarsi; Lennerz, Jochen; Pan, Tony; Saltz, Joel; Wharton, Keith A; Ehinger, Daniel; Acs, Balazs; Dequeker, Elisabeth M C; Salgado, Roberto; Gallas, Brandon D.
Affiliation
  • Ly A; Department of Pathology, Massachusetts General Hospital, Boston, MA, USA.
  • Garcia V; Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability, US Food and Drug Administration, Silver Spring, MD, USA.
  • Blenman KRM; Department of Internal Medicine, Section of Medical Oncology and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA.
  • Ehinger A; Department of Computer Science, Yale School of Engineering and Applied Science, New Haven, CT, USA.
  • Elfer K; Department of Genetics, Pathology and Molecular Diagnostics, Laboratory Medicine, Region Skane, Lund University, Lund, Sweden.
  • Hanna MG; Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability, US Food and Drug Administration, Silver Spring, MD, USA.
  • Li X; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Peeters DJE; Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA.
  • Birmingham R; Department of Pathology, University Hospital Antwerp, Edegem, Belgium.
  • Dudgeon S; Department of Pathology, Algemeen Ziekenhuis (AZ) Sint-Maarten, Mechelen, Belgium.
  • Gardecki E; Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability, US Food and Drug Administration, Silver Spring, MD, USA.
  • Gupta R; Department of Biomedical Informatics, Emory University, Atlanta, GA, USA.
  • Lennerz J; Center for Computational Health, Yale School of Medicine, New Haven, CT, USA.
  • Pan T; Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability, US Food and Drug Administration, Silver Spring, MD, USA.
  • Saltz J; Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA.
  • Wharton KA; Department of Pathology, Center for Integrated Diagnostics, Massachusetts General Hospital, Boston, MA, USA.
  • Ehinger D; Department of Biomedical Informatics, Emory University, Atlanta, GA, USA.
  • Acs B; Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA.
  • Dequeker EMC; Roche Diagnostic Solutions, Oro Valley, AZ, USA.
  • Salgado R; Department of Clinical Sciences, Division of Oncology, Lund University, Lund, Sweden.
  • Gallas BD; Department of Genetics, Pathology, and Molecular Diagnostics, Skane University Hospital, Lund, Sweden.
Histopathology ; 84(6): 915-923, 2024 May.
Article in En | MEDLINE | ID: mdl-38433289
ABSTRACT
A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment. Visual TIL assessment may suffer from significant interobserver variability. To improve interobserver agreement, regulatory science experts at the US Food and Drug Administration partnered with academic pathologists internationally to create a freely available online continuing medical education (CME) course to train pathologists in assessing breast cancer stromal TILs using an interactive format with expert commentary. Here we describe and provide a user guide to this CME course, whose content was designed to improve pathologist accuracy in scoring breast cancer TILs. We also suggest subsequent steps to translate knowledge into clinical practice with proficiency testing.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms Limits: Female / Humans Language: En Journal: Histopathology Year: 2024 Document type: Article Affiliation country:
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Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms Limits: Female / Humans Language: En Journal: Histopathology Year: 2024 Document type: Article Affiliation country: