Refined prognostication of pathological complete response in breast cancer using radiomic features and optimized InceptionV3 with DCE-MRI.

Journal: Scientific reports
Published Date:

Abstract

BACKGROUND: Neoadjuvant therapy plays a pivotal role in breast cancer treatment, particularly for patients aiming to conserve their breast by reducing tumor size pre-surgery. The ultimate goal of this treatment is achieving a pathologic complete response (pCR), which signifies the complete eradication of cancer cells, thereby lowering the likelihood of recurrence. This study introduces a novel predictive approach to identify patients likely to achieve pCR using radiomic features extracted from MR images, enhanced by the InceptionV3 model and cutting-edge validation methodologies.

Authors

  • Satyabrata Pattanayak
    Department of Computer Sciences and Engineering, Amrita School of Computing, Amrita Vishwavidyapeetham, Bengaluru, Bengaluru, Karnataka, 560067, India.
  • Tripty Singh
    Department of Computer Sciences and Engineering, Amrita School of Computing, Amrita Vishwavidyapeetham, Bengaluru, Bengaluru, Karnataka, 560067, India. tripty_singh@blr.amrita.edu.
  • Rishabh Kumar
    Radiation Oncology, Amrita Hospital, Faridabad, India.