Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT.

Journal: Abdominal radiology (New York)
PMID: 30778739

Abstract

PURPOSE: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial overlap in the imaging findings of benign and malignant renal masses, particularly between clear cell RCC (ccRCC) and benign oncocytoma (ONC). Radiomics has attracted increased attention for its utility in pre-operative work-up on routine clinical images. Radiomics based approaches have converted medical images into mineable data and identified prognostic imaging signatures that machine learning algorithms can use to construct predictive models by learning the decision boundaries of the underlying data distribution. The TensorFlow™ framework from Google is a state-of-the-art open-source software library that can be used for training deep learning neural networks for performing machine learning tasks. The purpose of this study was to investigate the diagnostic value and feasibility of a deep learning-based renal lesion classifier using open-source Google TensorFlow™ Inception in differentiating ccRCC from ONC on routine four-phase MDCT in patients with pathologically confirmed renal masses.

Authors

  • Heidi Coy
    Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Ronald Reagan-UCLA Medical Center, 924 Westwood Boulevard, Suite 615, Los Angeles, CA, 90024, USA. hcoy@mednet.ucla.edu.
  • Kevin Hsieh
    Department of Computer Science, School of Engineering at UCLA, NRB 635 Charles E. Young Dr. South Suite 116, BOX 951769, Los Angeles, CA, 90095-1769, USA.
  • Willie Wu
    Department of Bioengineering, School of Engineering at UCLA, NRB 635 Charles E. Young Dr. South Suite 116, BOX 951769, Los Angeles, CA, 90095-1769, USA.
  • Mahesh B Nagarajan
    Department of Radiological Sciences, University of California Los Angeles, Los Angeles, USA.
  • Jonathan R Young
    Department of Radiology, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, CA, 91010, USA.
  • Michael L Douek
    Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Ronald Reagan-UCLA Medical Center, 924 Westwood Boulevard, Suite 615, Los Angeles, CA, 90024, USA.
  • Matthew S Brown
    University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, USA.
  • Fabien Scalzo
  • Steven S Raman
    Department of Radiologic Sciences David Geffen School of Medicine, University of California Los Angeles CA.

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