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

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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.

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MLA
Amgad, Mohamed, et al. “Report on Computational Assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.” NPJ BREAST CANCER, vol. 6, 2020.
APA
Amgad, M., Stovgaard, E. S., Balslev, E., Thagaard, J., Chen, W., Dudgeon, S., … Van de Vijver, K. (2020). Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group. NPJ BREAST CANCER, 6.
Chicago author-date
Amgad, Mohamed, Elisabeth Specht Stovgaard, Eva Balslev, Jeppe Thagaard, Weijie Chen, Sarah Dudgeon, Ashish Sharma, et al. 2020. “Report on Computational Assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.” NPJ BREAST CANCER 6.
Chicago author-date (all authors)
Amgad, Mohamed, Elisabeth Specht Stovgaard, Eva Balslev, Jeppe Thagaard, Weijie Chen, Sarah Dudgeon, Ashish Sharma, Jennifer K Kerner, Carsten Denkert, Yinyin Yuan, Khalid AbdulJabbar, Stephan Wienert, Peter Savas, Leonie Voorwerk, Andrew H Beck, Anant Madabhushi, Johan Hartman, Manu M Sebastian, Hugo M Horlings, Jan Hudecek, Francesco Ciompi, David A Moore, Rajendra Singh, Elvire Roblin, Marcelo Luiz Balancin, Marie-Christine Mathieu, Jochen K Lennerz, Pawan Kirtani, I-Chun Chen, Jeremy P Braybrooke, Giancarlo Pruneri, Sandra Demaria, Sylvia Adams, Stuart J Schnitt, Sunil R Lakhani, Federico Rojo, Laura Comerma, Sunil S Badve, Mehrnoush Khojasteh, W Fraser Symmans, Christos Sotiriou, Paula Gonzalez-Ericsson, Katherine L Pogue-Geile, Rim S Kim, David L Rimm, Giuseppe Viale, Stephen M Hewitt, John M S Bartlett, Frederique Penault-Llorca, Shom Goel, Huang-Chun Lien, Sibylle Loibl, Zuzana Kos, Sherene Loi, Matthew G Hanna, Stefan Michiels, Marleen Kok, Torsten O Nielsen, Alexander J Lazar, Zsuzsanna Bago-Horvath, Loes F S Kooreman, Jeroen A W M van der Laak, Joel Saltz, Brandon D Gallas, Uday Kurkure, Michael Barnes, Roberto Salgado, Lee A D Cooper, and Koen Van de Vijver. 2020. “Report on Computational Assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.” NPJ BREAST CANCER 6.
Vancouver
1.
Amgad M, Stovgaard ES, Balslev E, Thagaard J, Chen W, Dudgeon S, et al. Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group. NPJ BREAST CANCER. 2020;6.
IEEE
[1]
M. Amgad et al., “Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.,” NPJ BREAST CANCER, vol. 6, 2020.
@article{8662483,
  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.},
  articleno    = {16},
  author       = {Amgad, Mohamed and Stovgaard, Elisabeth Specht and Balslev, Eva and Thagaard, Jeppe and Chen, Weijie and Dudgeon, Sarah and Sharma, Ashish and Kerner, Jennifer K and Denkert, Carsten and Yuan, Yinyin and AbdulJabbar, Khalid and Wienert, Stephan and Savas, Peter and Voorwerk, Leonie and Beck, Andrew H and Madabhushi, Anant and Hartman, Johan and Sebastian, Manu M and Horlings, Hugo M and Hudecek, Jan and Ciompi, Francesco and Moore, David A and Singh, Rajendra and Roblin, Elvire and Balancin, Marcelo Luiz and Mathieu, Marie-Christine and Lennerz, Jochen K and Kirtani, Pawan and Chen, I-Chun and Braybrooke, Jeremy P and Pruneri, Giancarlo and Demaria, Sandra and Adams, Sylvia and Schnitt, Stuart J and Lakhani, Sunil R and Rojo, Federico and Comerma, Laura and Badve, Sunil S and Khojasteh, Mehrnoush and Symmans, W Fraser and Sotiriou, Christos and Gonzalez-Ericsson, Paula and Pogue-Geile, Katherine L and Kim, Rim S and Rimm, David L and Viale, Giuseppe and Hewitt, Stephen M and Bartlett, John M S and Penault-Llorca, Frederique and Goel, Shom and Lien, Huang-Chun and Loibl, Sibylle and Kos, Zuzana and Loi, Sherene and Hanna, Matthew G and Michiels, Stefan and Kok, Marleen and Nielsen, Torsten O and Lazar, Alexander J and Bago-Horvath, Zsuzsanna and Kooreman, Loes F S and van der Laak, Jeroen A W M and Saltz, Joel and Gallas, Brandon D and Kurkure, Uday and Barnes, Michael and Salgado, Roberto and Cooper, Lee A D and Van de Vijver, Koen},
  issn         = {2374-4677},
  journal      = {NPJ BREAST CANCER},
  language     = {eng},
  pages        = {13},
  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},
  volume       = {6},
  year         = {2020},
}

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