Computational Radiologic/Pathologic Correlation for Imaging Biomarker Discovery in Lung Cancer
Principal Investigator
Name
Deni Aberle
Degrees
MD
Institution
University of California Los Angeles
Position Title
Principal Investigator
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
201206-0032
Initial CDAS Request Approval
Jun 25, 2012
Title
Computational Radiologic/Pathologic Correlation for Imaging Biomarker Discovery in Lung Cancer
Summary
Hypothesis:
1. Computed tomography (CT) features of CT screen-detected nodules correlate with and predict histopathologic features of resected lung cancers, specifically lepidic features seen in microscopy of the resected tumors.
2. A secondary hypothesis is that CT features of nodules correlate with biological behavior and outcomes (stage at diagnosis, overall survival OS, and progression free survival PFS).
3. Annotation image mark-up (AIM) enables efficient capture of quantitative and semantic information from radiology and pathology images and enables correlative scientific discovery through computational analysis of annotated features in large-scale radiology and pathology image databases.
1. Computed tomography (CT) features of CT screen-detected nodules correlate with and predict histopathologic features of resected lung cancers, specifically lepidic features seen in microscopy of the resected tumors.
2. A secondary hypothesis is that CT features of nodules correlate with biological behavior and outcomes (stage at diagnosis, overall survival OS, and progression free survival PFS).
3. Annotation image mark-up (AIM) enables efficient capture of quantitative and semantic information from radiology and pathology images and enables correlative scientific discovery through computational analysis of annotated features in large-scale radiology and pathology image databases.
Collaborators
Deni Aberle
Daniel Rubin
Wilbur Franklin
Piotr Kulesza
Christine Berg Fenghai Duan
Philip Boiselle
Matthew Brown
Kathy Brown
Eric Hart
Reggie Munden
Kavita Garg