Artificial Intelligence-Driven Morphology-Based Enrichment of Malignant Cells from Body Fluid.

Anastasia Mavropoulos¹, Chassidy Johnson¹, Vivian Lu¹, Jordan Nieto¹, Emilie C Schneider¹, Kiran Saini¹, Michael L Phelan¹, Linda X Hsie¹, Maggie J Wang¹, Janifer Cruz¹, Jeanette Mei¹, Julie J Kim¹, Zhouyang Lian¹, Nianzhen Li¹, Stephane C Boutet¹, Amy Y Wong-Thai¹, Weibo Yu², Qing-Yi Lu², Teresa Kim², Yipeng Geng², Maddison Mahdokht Masaeli¹, Thomas D Lee², Jianyu Rao³

¹Deepcell, Inc, Menlo Park, California.

²Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, California.

³Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, California. Electronic address: JRao@mednet.ucla.edu.

PubMed DOI

Abstract

Cell morphology is a fundamental feature used to evaluate patient specimens in pathologic analysis. However, traditional cytopathology analysis of patient effusion samples is limited by low tumor cell abundance coupled with the high background of nonmalignant cells, restricting the ability of downstream molecular and functional analyses to identify actionable therapeutic targets. We applied the De…

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