The impact of updated imaging software on the performance of machine learning models for breast cancer diagnosis: a multi-center, retrospective study.

Journal: Archives of gynecology and obstetrics
Published Date: Jan 30, 2025

Abstract

PURPOSE: Artificial Intelligence models based on medical (imaging) data are increasingly developed. However, the imaging software on which the original data is generated is frequently updated. The impact of updated imaging software on the performance of AI models is unclear. We aimed to develop machine learning models using shear wave elastography (SWE) data to identify malignant breast lesions and to test the models' generalizability by validating them on external data generated by both the original updated software versions.

Authors

  • Lie Cai
    Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany.
  • Michael Golatta
    University Breast Unit, Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany. Michael.golatta@med.uni-heidelberg.de.
  • Chris Sidey-Gibbons
    MD Anderson Center for INSPiRED Cancer Care, University of Texas, Houston, TX, United States.
  • Richard G Barr
    Northeastern Ohio Medical University, Youngstown, OH.
  • AndrĂ© Pfob
    University Breast Unit, Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany.

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