Residual Convolutional Neural Network for the Determination of Status in Low- and High-Grade Gliomas from MR Imaging.

Journal: Clinical cancer research : an official journal of the American Association for Cancer Research
Published Date: Nov 22, 2017

Abstract

Isocitrate dehydrogenase () mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the status of gliomas from MR imaging by applying a residual convolutional neural network to preoperative radiographic data. Preoperative imaging was acquired for 201 patients from the Hospital of University of Pennsylvania (HUP), 157 patients from Brigham and Women's Hospital (BWH), and 138 patients from The Cancer Imaging Archive (TCIA) and divided into training, validation, and testing sets. We trained a residual convolutional neural network for each MR sequence (FLAIR, T2, T1 precontrast, and T1 postcontrast) and built a predictive model from the outputs. To increase the size of the training set and prevent overfitting, we augmented the training set images by introducing random rotations, translations, flips, shearing, and zooming. With our neural network model, we achieved IDH prediction accuracies of 82.8% (AUC = 0.90), 83.0% (AUC = 0.93), and 85.7% (AUC = 0.94) within training, validation, and testing sets, respectively. When age at diagnosis was incorporated into the model, the training, validation, and testing accuracies increased to 87.3% (AUC = 0.93), 87.6% (AUC = 0.95), and 89.1% (AUC = 0.95), respectively. We developed a deep learning technique to noninvasively predict genotype in grade II-IV glioma using conventional MR imaging using a multi-institutional data set. .

Authors

  • Ken Chang
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.
  • Harrison X Bai
    Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • Hao Zhou
    State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China.
  • Chang Su
    Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut.
  • Wenya Linda Bi
    Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts.
  • Ena Agbodza
    Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • Vasileios K Kavouridis
    Department of Neurosurgery, Computational Neuroscience Outcomes Center, Brigham and Women's Hospital, Boston, Massachusetts.
  • Joeky T Senders
    Department of Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands; Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Alessandro Boaro
    Department of Neurosurgery, Computational Neuroscience Outcomes Center, Brigham and Women's Hospital, Boston, Massachusetts.
  • Andrew Beers
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.
  • Biqi Zhang
    Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts.
  • Alexandra Capellini
    Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts.
  • Weihua Liao
    Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China.
  • Qin Shen
    Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
  • Xuejun Li
  • Bo Xiao
    Department of Urology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
  • Jane Cryan
    Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.
  • Shakti Ramkissoon
    Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.
  • Lori Ramkissoon
    Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.
  • Keith Ligon
    Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.
  • Patrick Y Wen
    Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.
  • Ranjit S Bindra
    Department of Therapeutic Radiology, Yale University, New Haven, Connecticut.
  • John Woo
    Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • Omar Arnaout
    Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA. Electronic address: oarnaout@bwh.harvard.edu.
  • Elizabeth R Gerstner
    Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.
  • Paul J Zhang
    Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • Bruce R Rosen
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.
  • Li Yang
    Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Raymond Y Huang
    Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts. kalpathy@nmr.mgh.harvard.edu yangli762@gmail.com ryhuang@partners.org.
  • Jayashree Kalpathy-Cramer
    Department of Radiology, MGH/Harvard Medical School, Charlestown, Massachusetts.

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