Lack of Reproducibility of Histopathological Features in MYC-rearranged Large B-cell Lymphoma Using Digital Whole Slide Images: A Study from the Lunenburg Lymphoma Biomarker Consortium.

Yasodha NatkunamDaphne de JongPedro FarinhaPhilippe GaulardWolfram KlapperAndreas RosenwaldBirgitta SanderReuben ToozeRanjana AdvaniCatherine BurtonJohn G GribbenMarie-José KerstenEva KimbyGeorg LenzThierry MolinaFranck MorschhauserDavid ScottLaurie SehnWendy StevensAndrew ClearMaryse BaiaAbdelmalek HabiMad-Helenie ElsensohnCarole Langlois-JacquesDelphine Maucort-BoulchMaria Calaminici

Published in: Histopathology (2023)

Our findings indicate that there are no specific conventional morphological parameters that help subclassify MYC-rearranged LBCL or select cases for FISH analysis, and that incorporation of FISH data is essential for accurate classification and prognostication.

Keyphrases

deep learning
diffuse large b cell lymphoma
transcription factor
machine learning
convolutional neural network
big data
optical coherence tomography
artificial intelligence