Digital pathology and artificial intelligence as the next chapter in diagnostic hematopathology.

Journal: Seminars in diagnostic pathology
Published Date:

Abstract

Digital pathology has a crucial role in diagnostic pathology and is increasingly a technological requirement in the field. Integration of digital slides into the pathology workflow, advanced algorithms, and computer-aided diagnostic techniques extend the frontiers of the pathologist's view beyond the microscopic slide and enable true integration of knowledge and expertise. There is clear potential for artificial intelligence (AI) breakthroughs in pathology and hematopathology. In this review article, we discuss the approach of using machine learning in the diagnosis, classification, and treatment guidelines of hematolymphoid disease, as well as recent progress of artificial intelligence in flow cytometric analysis of hematolymphoid diseases. We review these topics specifically through the potential clinical applications of CellaVision, an automated digital image analyzer of peripheral blood, and Morphogo, a novel artificial intelligence-based bone marrow analyzing system. Adoption of these new technologies will allow pathologists to streamline workflow and achieve faster turnaround time in diagnosing hematological disease.

Authors

  • Elisa Lin
    Department of Pathology and Laboratory Medicine, University of Texas, Southwestern Medical Center, Dallas, Texas, United States of America.
  • Franklin Fuda
    Department of Pathology and Laboratory Medicine, University of Texas, Southwestern Medical Center, Dallas, Texas, United States of America.
  • Hung S Luu
    Department of Pathology and Laboratory Medicine, University of Texas, Southwestern Medical Center, Dallas, Texas, United States of America.
  • Andrew M Cox
    Cell & Molecular Biology | Luda Hill Department of Bioinformatics, University of Texas, Southwestern Medical Center, Dallas, Texas, United States of America.
  • Fengqi Fang
    Department of Oncology, The First Hospital of Dalian Medical University, Dalian, China.
  • Junlin Feng
    Hangzhou Zhiwei Information and Technology Inc., Hangzhou, China.
  • Mingyi Chen
    Department of Pathology and Laboratory Medicine, University of Texas, Southwestern Medical Center, Dallas, Texas, USA, mingyi.chen@utsouthwestern.edu.