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Principal Investigator
Eldad Elnekave
Zebra Medical Vision, LTD
Position Title
Chief Medical Officer
About this CDAS Project
NLST (Learn more about this study)
Project ID
Initial CDAS Request Approval
Oct 4, 2016
LDCT Cardiovascular Automatic Biomarker Screening Study
The purpose of this study is to assess the technical performance and clinical relevance of automatic cardiovascular - oriented machine learning applications developed at Zebra Medical Vision, LTD. The aim of this study is to demonstrate that automatic algorithmic assessment of screening low-dose chest CT's may provide valuable insight into the risk of cardiovascular events, Which were in fact the leading cause of death among participants of the national lung cancer screening trial. Zebra has developed relevant algorithms and tested them on internal data sets- specifically algorithms which quantify coronary calcium burden and identify hepatic steatosis. We would like to assess the significance of such algorithmic input upon the NLCST population.

1. Assess the performance of Zebra's automatic coronary calcium quantification algorithm upon low dose screening chest CT's.
2. Assess the performance of Zebra's automatic detection of hepatic steatosis upon low dose screening chest CT's.
3. Assess the performance of Zebra's visceral and pericardial fat quantification algorithms on low dose screening chest CT's.
4. Determine the possible predictive value of these algorithms (alone and in combination) upon risk of cardiovascular events within the NLCST cohort.


This study is at present entirely internal to Zebra Medical Vision

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