Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Amgad, Mohamed and Cooper, Lee A. D. (2020) In npj Breast Cancer 6(16).
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.... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
and
contributor
LU orcid
author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
npj Breast Cancer
volume
6
issue
16
article number
16
publisher
Nature Publishing Group
external identifiers
  • pmid:32411818
  • scopus:85083451193
ISSN
2374-4677
DOI
10.1038/s41523-020-0154-2
language
English
LU publication?
yes
id
b5845f7d-3a31-4964-a587-210fd46c1b89
date added to LUP
2020-05-15 01:32:05
date last changed
2023-08-18 04:01:16
@article{b5845f7d-3a31-4964-a587-210fd46c1b89,
  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.}},
  author       = {{Amgad, Mohamed and Cooper, Lee A. D.}},
  issn         = {{2374-4677}},
  language     = {{eng}},
  month        = {{05}},
  number       = {{16}},
  publisher    = {{Nature Publishing Group}},
  series       = {{npj Breast Cancer}},
  title        = {{Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group}},
  url          = {{http://dx.doi.org/10.1038/s41523-020-0154-2}},
  doi          = {{10.1038/s41523-020-0154-2}},
  volume       = {{6}},
  year         = {{2020}},
}