Pre-operative lung ablation prediction using deep learning.

Journal: European radiology
PMID:

Abstract

OBJECTIVE: Microwave lung ablation (MWA) is a minimally invasive and inexpensive alternative cancer treatment for patients who are not candidates for surgery/radiotherapy. However, a major challenge for MWA is its relatively high tumor recurrence rates, due to incomplete treatment as a result of inaccurate planning. We introduce a patient-specific, deep-learning model to accurately predict post-treatment ablation zones to aid planning and enable effective treatments.

Authors

  • Krishna Nand Keshavamurthy
    Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA. keshavak@mskcc.org.
  • Carsten Eickhoff
    Department of Computer Science, ETH Zurich, Zurich, Switzerland; Center for Biomedical Informatics, Brown University, Providence, RI, USA.
  • Etay Ziv
    Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.