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Mavropoulos A, Johnson C, Lu V, Nieto J, Schneider EC, Saini K, Phelan ML, Hsie LX, Wang MJ, Cruz J, Mei J, Kim JJ, Lian Z, Li N, Boutet SC, Wong-Thai AY, Yu W, Lu QY, Kim T, Geng Y, Masaeli MM, Lee TD, Rao J. Artificial Intelligence-Driven Morphology-Based Enrichment of Malignant Cells from Body Fluid. Mod Pathol 2023; 36:100195. [PMID: 37100228 DOI: 10.1016/j.modpat.2023.100195] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/29/2023] [Accepted: 04/17/2023] [Indexed: 04/28/2023]
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 Deepcell platform that combines microfluidic sorting, brightfield imaging, and real-time deep learning interpretations based on multidimensional morphology to enrich carcinoma cells from malignant effusions without cell staining or labels. Carcinoma cell enrichment was validated with whole genome sequencing and targeted mutation analysis, which showed a higher sensitivity for detection of tumor fractions and critical somatic variant mutations that were initially at low levels or undetectable in presort patient samples. Our study demonstrates the feasibility and added value of supplementing traditional morphology-based cytology with deep learning, multidimensional morphology analysis, and microfluidic sorting.
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Affiliation(s)
| | | | - Vivian Lu
- Deepcell, Inc, Menlo Park, California
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Weibo Yu
- Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, California
| | - Qing-Yi Lu
- Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, California
| | - Teresa Kim
- Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, California
| | - Yipeng Geng
- Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, California
| | | | - Thomas D Lee
- Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, California
| | - Jianyu Rao
- Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, California.
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