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Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
- Source :
- npj Breast Cancer, Vol 6, Iss 1, Pp 1-13 (2020), The International Immuno-Oncology Biomarker Working Group, Lien, H-C, Loibl, S, Kos, Z, Loi, S, Hanna, M G, Michiels, S, Kok, M, Nielsen, T O, Lazar, A J, Bago-Horvath, Z, Kooreman, L F S, van der Laak, J A W M, Saltz, J, Gallas, B D, Kurkure, U, Barnes, M, Salgado, R & Cooper, L A D 2020, ' Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group ', npj Breast Cancer, vol. 6, 16 . https://doi.org/10.1038/s41523-020-0154-2, npj Breast Cancer, npj Breast Cancer, 2020, 6 (1), pp.16. ⟨10.1038/s41523-020-0154-2⟩, NPJ breast cancer, Vol. 6, p. 16 [1-13] (2020), NPJ BREAST CANCER, NPJ breast cancer, 6, npj Breast Cancer, Nature, 2020, 6 (1), pp.16. ⟨10.1038/s41523-020-0154-2⟩, NPJ breast cancer, 6, 1, 2020, ' Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group ', NPJ Breast Cancer . https://doi.org/10.1038/s41523-020-0154-2, NPJ Breast Cancer
- Publication Year :
- 2020
-
Abstract
- Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.<br />info:eu-repo/semantics/published
- Subjects :
- 0301 basic medicine
Computer science
[SDV]Life Sciences [q-bio]
Review Article
DIGITAL PATHOLOGY
Tumour biomarkers
Tumours of the digestive tract Radboud Institute for Health Sciences [Radboudumc 14]
Prognostic markers
0302 clinical medicine
Breast cancer
Ecology,Evolution & Ethology
Visual scoring
Medicine and Health Sciences
Pharmacology (medical)
Chemical Biology & High Throughput
Human Biology & Physiology
IN-SITU
Medicinsk bildbehandling
Genome Integrity & Repair
Sciences bio-médicales et agricoles
lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
SOLID TUMORS
3. Good health
Women's cancers Radboud Institute for Health Sciences [Radboudumc 17]
Oncology
030220 oncology & carcinogenesis
Tumour immunology
TILS
Tumor immunology
Genetics & Genomics
[SDV.CAN]Life Sciences [q-bio]/Cancer
Cancer imaging
lcsh:RC254-282
CLASSIFICATION
03 medical and health sciences
Signalling & Oncogenes
STANDARDIZED METHOD
QUALITY-CONTROL
SDG 3 - Good Health and Well-being
BREAST-CANCER
Radiology, Nuclear Medicine and imaging
IMAGE-ANALYSIS
Computational & Systems Biology
Tumor-infiltrating lymphocytes
Digital pathology
Médecine pathologie humaine
Tumour Biology
Data science
Biomarker (cell)
Cancérologie
Medical Image Processing
030104 developmental biology
Workflow
T-CELLS
Subjects
Details
- ISSN :
- 23744677
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- NPJ breast cancer
- Accession number :
- edsair.doi.dedup.....6a7c7a6ecc3ef9fc2cd6fab6b66d92d9
- Full Text :
- https://doi.org/10.1038/s41523-020-0154-2