Coronary artery calcification identification and labeling in low-dose chest CT images

Yiting Xie; Shuang Liu; Albert Miller; Jeffrey A. Miller; Steven Markowitz; Ali Akhund; Anthony P. Reeves

doi:10.1117/12.2254125

3 March 2017 Coronary artery calcification identification and labeling in low-dose chest CT images

Yiting Xie, Shuang Liu, Albert Miller, Jeffrey A. Miller, Steven Markowitz, Ali Akhund, Anthony P. Reeves

Proceedings Volume 10134, Medical Imaging 2017: Computer-Aided Diagnosis; 101340L (2017) https://doi.org/10.1117/12.2254125
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

A fully automated computer algorithm has been developed to evaluate coronary artery calcification (CAC) from lowdose CT scans. CAC is identified and evaluated in three main coronary artery groups: Left Main and Left Anterior Descending Artery (LM + LAD) CAC, Left Circumflex Artery (LCX) CAC, and Right Coronary Artery (RCA) CAC. The artery labeling is achieved by segmenting all CAC candidates in the heart region and applying geometric constraints on the candidates using locally pre-identified anatomy regions. This algorithm was evaluated on 1,359 low-dose ungated CT scans, in which each artery CAC content was categorically visually scored by a radiologist into none, mild, moderate and extensive. The Spearman correlation coefficient R was used to assess the agreement between three automated CAC scores (Agatston-weighted, volume, and mass) and categorical visual scores. For Agatston-weighted automated scores, R was 0.87 for total CAC, 0.82 for LM + LAD CAC, 0.66 for LCX CAC and 0.72 for RCA CAC; results using volume and mass scores were similar. CAC detection sensitivities were: 0.87 for total, 0.82 for LM + LAD, 0.65 for LCX and 0.74 for RCA. To assess the impact of image noise, the dataset was further partitioned into three subsets based on heart region noise level (low<=80HU, medium=(80HU, 110HU], high>110HU). The low and medium noise subsets had higher sensitivities and correlations than the high noise subset. These results indicate that location specific heart risk assessment is possible from low-dose chest CT images.

Conference Presentation

Citation Download Citation

Yiting Xie, Shuang Liu, Albert Miller, Jeffrey A. Miller, Steven Markowitz, Ali Akhund, and Anthony P. Reeves "Coronary artery calcification identification and labeling in low-dose chest CT images", Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101340L (3 March 2017); https://doi.org/10.1117/12.2254125

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available