Amgad, MohamedMohamedAmgadStovgaard, Elisabeth SpechtElisabeth SpechtStovgaardBalslev, EvaEvaBalslevThagaard, JeppeJeppeThagaardChen, WeijieWeijieChenDudgeon, SarahSarahDudgeonSharma, AshishAshishSharmaKerner, Jennifer KJennifer KKernerDenkert, CarstenCarstenDenkertYuan, YinyinYinyinYuanAbdulJabbar, KhalidKhalidAbdulJabbarWienert, StephanStephanWienertSavas, PeterPeterSavasVoorwerk, LeonieLeonieVoorwerkBeck, Andrew HAndrew HBeckMadabhushi, AnantAnantMadabhushiHartman, JohanJohanHartmanSebastian, Manu MManu MSebastianHorlings, Hugo MHugo MHorlingsHudeček, JanJanHudečekCiompi, FrancescoFrancescoCiompiMoore, David ADavid AMooreSingh, RajendraRajendraSinghRoblin, ElvireElvireRoblinBalancin, Marcelo LuizMarcelo LuizBalancinMathieu, Marie-ChristineMarie-ChristineMathieuLennerz, Jochen KJochen KLennerzKirtani, PawanPawanKirtaniI-CHUN CHENBraybrooke, Jeremy PJeremy PBraybrookePruneri, GiancarloGiancarloPruneriDemaria, SandraSandraDemariaAdams, SylviaSylviaAdamsSchnitt, Stuart JStuart JSchnittLakhani, Sunil RSunil RLakhaniRojo, FedericoFedericoRojoComerma, LauraLauraComermaBadve, Sunil SSunil SBadveKhojasteh, MehrnoushMehrnoushKhojastehSymmans, W FraserW FraserSymmansSotiriou, ChristosChristosSotiriouGonzalez-Ericsson, PaulaPaulaGonzalez-EricssonPogue-Geile, Katherine LKatherine LPogue-GeileKim, Rim SRim SKimRimm, David LDavid LRimmViale, GiuseppeGiuseppeVialeHewitt, Stephen MStephen MHewittBartlett, John M SJohn M SBartlettPenault-Llorca, FrédériqueFrédériquePenault-LlorcaGoel, ShomShomGoelHUANG-CHUN LIENLoibl, SibylleSibylleLoiblKos, ZuzanaZuzanaKosLoi, ShereneShereneLoiHanna, Matthew GMatthew GHannaMichiels, StefanStefanMichielsKok, MarleenMarleenKokNielsen, Torsten OTorsten ONielsenLazar, Alexander JAlexander JLazarBago-Horvath, ZsuzsannaZsuzsannaBago-HorvathKooreman, Loes F SLoes F SKooremanvan der Laak, Jeroen A W MJeroen A W Mvan der LaakSaltz, JoelJoelSaltzGallas, Brandon DBrandon DGallasKurkure, UdayUdayKurkureBarnes, MichaelMichaelBarnesSalgado, RobertoRobertoSalgadoCooper, Lee A DLee A DCooper2023-10-312023-10-3120202374-4677https://scholars.lib.ntu.edu.tw/handle/123456789/636702Assessment 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.enBreast cancer; Cancer imaging; Prognostic markers; Tumour biomarkers; Tumour immunology[SDGs]SDG3review10.1038/s41523-020-0154-2324118182-s2.0-85083451193https://api.elsevier.com/content/abstract/scopus_id/85083451193