Thorax-encompassing multi-modality PET/CT deep learning model for resected lung cancer prognostication: A retrospective, multicenter study.

Journal: Medical physics
Published Date:

Abstract

BACKGROUND: Patients with early-stage non-small cell lung cancer (NSCLC) typically receive surgery as their primary form of treatment. However, studies have shown that a high proportion of these patients will experience a recurrence after their resection, leading to an increased risk of death. Cancer staging is currently the gold standard for establishing a patient's prognosis and can help clinicians determine patients who may benefit from additional therapy. However, medical images which are used to help determine the cancer stage, have been shown to hold unutilized prognostic information that can augment clinical data and better identify high-risk NSCLC patients. There remains an unmet need for models to incorporate clinical, pathological, surgical, and imaging information, and extend beyond the current staging system to assist clinicians in identifying patients who could benefit from additional therapy immediately after surgery.

Authors

  • Jaryd R Christie
    Department of Medical Biophysics, 6221Western University, London, Ontario, Canada.
  • Perrin Romine
    Swedish Cancer Institute, Seattle, Washington, USA.
  • Karen Eddy
    Baines Imaging Research Laboratory, London Health Sciences Center, London, Ontario, Canada.
  • Delphine L Chen
    Department of Molecular Imaging and Therapy, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Omar Daher
    Department of Medical Imaging, Western University, London, Ontario, Canada.
  • Mohamed Abdelrazek
    Department of Medical Imaging, 6221Western University, London, Ontario, Canada.
  • Richard A Malthaner
    Division of Thoracic Surgery, Department of Surgery, Western University, London, Ontario, Canada.
  • Mehdi Qiabi
    Division of Thoracic Surgery, Department of Surgery, Western University, London, Ontario, Canada.
  • Rahul Nayak
    Division of Thoracic Surgery, Department of Surgery, Western University, London, Ontario, Canada.
  • Paul Kinahan
    Department of Radiology, University of Washington, Seattle, Washington, USA.
  • Viswam S Nair
    Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA.
  • Sarah A Mattonen
    Department of Radiology, Stanford University, Stanford, CA, 94305, USA.