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  1. NLST Data Requests
  2. NDR-179

NLST-564 Request for CT Images

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      The project information is at https://cdas.cancer.gov/approved-projects/2329/.

       This is an approved project at a US institution requesting CT images only.

       

      A Deep Learning Model for Improved Cancer Risk Prediction in Lung Screening Low-Dose Chest Computed Tomography

      Principal Investigator

      Name
      Florian Fintelmann
      Degrees
      MD
      Institution
      Massachusetts General Hospital
      Position Title
      Assistant Professor of Radiology, Harvard Medical School
      Email
      fintelmann@mgh.harvard.edu

      About this Project

      Study
      NLST (Learn more about this study)
      Project ID
      NLST-564
      Title
      A Deep Learning Model for Improved Cancer Risk Prediction in Lung Screening Low-Dose Chest Computed Tomography
      Summary
      Together with collaborators at the Massachusetts Institute of Technology we will analyze the low-dose computed tomography (LDCT) examinations of the chest obtained in participants in the National Lung Screening Trial prior to the tissue diagnosis of lung cancer. The LDCT examinations of patients diagnosed with lung cancer will be compared with LDCT examinations of patients who did not develop lung cancer during the trial matched for age, gender and smoking exposure. We postulate that a deep learning algorithm can be trained to estimate the risk for developing a clinically active lung cancer within the next 12 months (1-year risk) and within the next 24 months (2-year risk).
      Aims
      Identify imaging features on low-dose computed tomography examinations of the chest obtained for screening that predict lung cancer
      Collaborators
      Lecia V. Sequist, MD (Massachusetts General Hospital)
      Regina Barzilay, PhD (Massachusetts Institute of Technology)
      Adam Yala, PhD candidate (Massachusetts Institute of Technology)

            tracyn T Nolan
            tracyn T Nolan
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