Artificial intelligence to detectMYCtranslocation in slides of diffuse large B-cell lymphoma

In patients with suspected lymphoma, the tissue biopsy provides lymphoma confirmation, classification, and prognostic factors, including genetic changes. We developed a deep learning algorithm to detect MYC rearrangement in scanned histological slides of diffuse large B-cell lymphoma. The H&E-stained slides of 287 cases from 11 hospitals were used for training and evaluation. The overall sensitivity to detect MYC rearrangement was 0.93 and the specificity 0.52, showing that prediction of MYC translocation based on morphology alone was possible in 93% of MYC-rearranged cases. This would allow a simple and fast prescreening, saving approximately 34% of genetic tests with the current algorithm.

Automated summary

A deep learning algorithm was developed to detect MYC rearrangement in scanned histological slides, showing a high sensitivity of 0.93 and specificity of 0.52. This approach could allow for simple and fast prescreening, potentially saving around 34% of genetic tests.