Frei, Ana LeniAna LeniFreiOberson, Raphaël DenisRaphaël DenisObersonBaumann, EliasEliasBaumann0000-0003-4655-4925Perren, AurelAurelPerren0000-0002-6819-6092Grobholz, RainerRainerGrobholzLugli, AlessandroAlessandroLugli0000-0002-9264-5185Dawson, HeatherHeatherDawsonAbbet, ChristianChristianAbbetLertxundi, IbaiIbaiLertxundiReinhard, StefanStefanReinhard0000-0001-7272-7792Mookhoek, AartAartMookhoekFeichtinger, JohannJohannFeichtingerSarro, RossellaRossellaSarroGadient, GallusGallusGadientDommann-Scherrer, CorinaCorinaDommann-ScherrerBarizzi, JessicaJessicaBarizziBerezowska, SabinaSabinaBerezowskaGlatz, KatharinaKatharinaGlatzDertinger, SusanneSusanneDertingerBanz Wälti, Yara SarahYara SarahBanz Wälti0000-0003-4474-3132Schoenegg, ReneReneSchoeneggRubbia-Brandt, LauraLauraRubbia-BrandtFleischmann, AchimAchimFleischmannSaile, GuenterGuenterSaileMainil-Varlet, PierrePierreMainil-VarletBiral, RuggeroRuggeroBiralGiudici, LucaLucaGiudiciSoltermann, AlexAlexSoltermannChaubert, Audrey BaurAudrey BaurChaubertStadlmann, SylviaSylviaStadlmannDiebold, JoachimJoachimDieboldEgervari, KristofKristofEgervariBénière, CharlesCharlesBénièreSaro, FrancescaFrancescaSaroJanowczyk, AndrewAndrewJanowczykZlobec, IntiIntiZlobec0000-0001-6741-30002024-10-252024-10-252023-12https://boris-portal.unibe.ch/handle/20.500.12422/170180Tumor cell fraction (TCF) estimation is a common clinical task with well-established large inter-observer variability. It thus provides an ideal testbed to evaluate potential impacts of employing a computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n=69) were asked to visually estimate TCF in 10 regions of interest (ROI) from hematoxylin and eosin (H&E) colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD created overlay highlighting predicted tumor versus non-tumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tiers scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, inter-observer variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard-deviation of estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD, p < 0.0001. The intraclass correlation coefficient increased from 0.8 to 0.93 (CI95% [0.65, 0.93] vs [0.86, 0.98]) and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs. 4.17 ± 0.82 with CAD). TCFCAD estimation support demonstrated improved scoring accuracy, inter-pathologist agreement and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems.en500 - Science::570 - Life sciences; biology600 - Technology::610 - Medicine & healtharticle10.48350/1865543774292610.1016/j.modpat.2023.100335