2024
Identification of Glandular (Acinar)/Tubule Formation in Invasive Carcinoma of the Breast: A Study to Determine Concordance Using the World Health Organization Definition.
Lo Y, Lester S, Ellis I, Lanjewar S, Laurini J, Patel A, Bhattarai A, Ustun B, Harmon B, Kleer C, Ross D, Amin A, Wang Y, Bradley R, Turashvili G, Zeng J, Baum J, Singh K, Hakima L, Harigopal M, Komforti M, Shin S, Abbott S, Jaffer S, Badve S, Khoury T, D'Alfonso T, Ginter P, Collins V, Towne W, Gan Y, Nassar A, Sahin A, Flieder A, Aldrees R, Ngo M, Edema U, Sapna F, Schnitt S, Fineberg S. Identification of Glandular (Acinar)/Tubule Formation in Invasive Carcinoma of the Breast: A Study to Determine Concordance Using the World Health Organization Definition. Archives Of Pathology & Laboratory Medicine 2024, 148: 1119-1125. PMID: 38244086, DOI: 10.5858/arpa.2023-0163-oa.Peer-Reviewed Original ResearchInvasive breast cancerWorld Health Organization definitionNottingham grading systemOrganization definitionMedian concordance rateMicropapillary carcinomaMucinous carcinomaInvasive carcinomaBreast pathologistsBreast cancerConcordance rateGrading systemCarcinomaTubulesPathologistsBreastConcordanceProfessor EllisCancerCases
2022
Concordance in Breast Cancer Grading by Artificial Intelligence on Whole Slide Images Compares With a Multi-Institutional Cohort of Breast Pathologists.
Mantrala S, Ginter PS, Mitkari A, Joshi S, Prabhala H, Ramachandra V, Kini L, Idress R, D'Alfonso TM, Fineberg S, Jaffer S, Sattar AK, Chagpar AB, Wilson P, Singh K, Harigopal M, Koka D. Concordance in Breast Cancer Grading by Artificial Intelligence on Whole Slide Images Compares With a Multi-Institutional Cohort of Breast Pathologists. Archives Of Pathology & Laboratory Medicine 2022, 146: 1369-1377. PMID: 35271701, DOI: 10.5858/arpa.2021-0299-oa.Peer-Reviewed Original ResearchConceptsWhole slide imagingArtificial intelligenceNottingham grading systemDigital whole slide imagingVirtual microscopyBreast cancer gradingWhole slide imagesDeep learningAI methodologiesExplainable methodsDigital pathologySlide imagesCancer gradingMulti-institutional groupIntelligenceLearningImagesImportant criteriaFrameworkAdvent