Your browser doesn't support javascript.
loading
AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer.
Wahab, Noorul; Toss, Michael; Miligy, Islam M; Jahanifar, Mostafa; Atallah, Nehal M; Lu, Wenqi; Graham, Simon; Bilal, Mohsin; Bhalerao, Abhir; Lashen, Ayat G; Makhlouf, Shorouk; Ibrahim, Asmaa Y; Snead, David; Minhas, Fayyaz; Raza, Shan E Ahmed; Rakha, Emad; Rajpoot, Nasir.
Afiliação
  • Wahab N; Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, UK.
  • Toss M; Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.
  • Miligy IM; Department of Histopathology, Sheffield Teaching Hospitals NHS Trust, Sheffield, UK.
  • Jahanifar M; Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.
  • Atallah NM; Department of Pathology, Faculty of Medicine, Menoufia University, Shebin El-Koum, Egypt.
  • Lu W; Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, UK.
  • Graham S; Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.
  • Bilal M; Department of Pathology, Faculty of Medicine, Menoufia University, Shebin El-Koum, Egypt.
  • Bhalerao A; Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, UK.
  • Lashen AG; Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, UK.
  • Makhlouf S; Histofy Ltd, Birmingham, UK.
  • Ibrahim AY; Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, UK.
  • Snead D; Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, UK.
  • Minhas F; Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.
  • Raza SEA; Department of Pathology, Faculty of Medicine, Menoufia University, Shebin El-Koum, Egypt.
  • Rakha E; Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.
  • Rajpoot N; Department of Pathology, Faculty of Medicine, Assiut University, Asyut, Egypt.
NPJ Precis Oncol ; 7(1): 122, 2023 Nov 15.
Article em En | MEDLINE | ID: mdl-37968376
Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of variability among observers in BC grading. Here we propose an objective Haematoxylin & Eosin (H&E) image-based prognostic marker for early-stage luminal/Her2-negative BReAst CancEr that we term as the BRACE marker. The proposed BRACE marker is derived from AI based assessment of heterogeneity in BC at a detailed level using the power of deep learning. The prognostic ability of the marker is validated in two well-annotated cohorts (Cohort-A/Nottingham: n = 2122 and Cohort-B/Coventry: n = 311) on early-stage luminal/HER2-negative BC patients treated with endocrine therapy and with long-term follow-up. The BRACE marker is able to stratify patients for both distant metastasis free survival (p = 0.001, C-index: 0.73) and BC specific survival (p < 0.0001, C-index: 0.84) showing comparable prediction accuracy to Nottingham Prognostic Index and Magee scores, which are both derived from manual histopathological assessment, to identify luminal BC patients that may be likely to benefit from adjuvant chemotherapy.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: NPJ Precis Oncol Ano de publicação: 2023 Tipo de documento: Article País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: NPJ Precis Oncol Ano de publicação: 2023 Tipo de documento: Article País de publicação: Reino Unido