Artificial intelligence interpretation of touch print smear cytology of testicular specimen from patients with azoospermia.

Journal: Journal of assisted reproduction and genetics
PMID: 39225840

Abstract

PURPOSE: Identification of mature sperm at microdissection testicular sperm extraction (mTESE) is a crucial step of sperm retrieval to help patients with non-obstructive azoospermia (NOA) proceed to intracytoplasmic sperm injection. Touch print smear (TPS) cytology allows immediate interpretation and prompt sperm identification intraoperatively. In this study, we leverage machine learning (ML) to facilitate TPS reading and conquer the learning curve for new operators.

Authors

  • Chen-Hao Hsu
    Department of Urology, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Chun-Fu Yeh
    Smart Medical and Healthcare, Service Systems Technology Center, Industrial Technology Research Institute, Hsinchu County 310, Taiwan.
  • I-Shen Huang
    Department of Urology, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Wei-Jen Chen
    Department of Urology, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Yu-Ching Peng
    School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan.
  • Cheng-Han Tsai
    Author Affiliations: Department of Information Management and Institute of Healthcare Information Management, National Chung Cheng University, Chiayi County, and Department of Emergency Medicine, Chiayi Branch, Taichung Veteran's General Hospital (Tsai); and Department of Information Management and Asian Institute for Impact Measurement and Management, National Central University, Taoyuan City (Hu), Taiwan.
  • Mong-Chi Ko
    Taiwan AI Labs, Taipei, Taiwan.
  • Chun-Ping Su
    Taiwan AI Labs, Taipei, Taiwan.
  • Hann-Chyun Chen
    Taiwan AI Labs, Taipei, Taiwan.
  • Wei-Lin Wu
    Taiwan AI Labs, Taipei, Taiwan.
  • Tyng-Luh Liu
    Taiwan AI Labs, Taipei, Taiwan.
  • Kuang-Min Lee
    Taiwan AI Labs, Taipei, Taiwan.
  • Chiao-Hsuan Li
    Taiwan AI Labs, Taipei, Taiwan.
  • Ethan Tu
    Taiwan AI Labs, Taipei, Taiwan.
  • William J Huang
    Shu-Tien Urological Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC.

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