Deep Learning Provides Rapid Screen for Breast Cancer Metastasis with Sentinel Lymph Nodes.

Journal: Annals of clinical and laboratory science
PMID: 38182154

Abstract

OBJECTIVE: Deep learning has been shown to be useful in detecting breast cancer metastases by analyzing whole slide images (WSI) of sentinel lymph nodes; however, it requires extensive analysis of all the lymph node slides. Our deep learning study attempts to provide a rapid screen for metastasis by analyzing only a small set of image patches to detect changes in tumor environment.

Authors

  • Kareem Allam
    Department of Pathology and Laboratory Medicine, University of Texas Health Science Center-Houston, Medical School, Houston, TX, USA.
  • Xiaohong Iris Wang
    Department of Pathology and Laboratory Medicine, University of Texas Health Science Center-Houston, Medical School, Houston, TX, USA.
  • Songlin Zhang
    College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China. z574066616@163.com.
  • Jianmin Ding
    Department of Pathology and Laboratory Medicine, University of Texas Health Science Center-Houston, Medical School, Houston, TX, USA.
  • Kevin Chiu
    Medical School, University of Texas Health Science Center-Houston, Houston, TX, USA.
  • Karan Saluja
    Department of Pathology and Laboratory Medicine, University of Texas Health Science Center-Houston, Medical School, Houston, TX, USA.
  • Amer Wahed
    The University of Texas Health Science Center at Houston-Department of Pathology and Laboratory Medicine, Houston, TX, USA.
  • Hongxia Sun
    Qingdao Jimo District Tongji Health Center and Medical Nursing, Qingdao, Shandong 266228, China.
  • Andy N D Nguyen
    The University of Texas Health Science Center at Houston-Department of Pathology and Laboratory Medicine, Houston, TX, USA Richard.Huang.1@uth.tmc.edu Nghia.D.Nguyen@uth.tmc.edu.

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