Automatic Coronary Calcium Scoring in Non-Contrast-Enhanced ECG-Triggered Cardiac CT with Ambiguity Detection

Jelmer M. Wolterink*, Tim Leiner, Richard A.P. Takx, Max A. Viergever, Ivana Išgum

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

43 Citations (Scopus)

Abstract

The amount of coronary artery calcification (CAC) is a strong and independent predictor of cardiovascular events. We present a system that automatically quantifies total patient and per coronary artery CAC in non-contrast-enhanced, ECG-triggered cardiac CT. The system identifies candidate calcifications that cannot be automatically labeled with high certainty and optionally presents these to an expert for review. Candidates were extracted by intensity-based thresholding and described by location features derived from estimated coronary artery positions, as well as size, shape and intensity features. Next, a two-class classifier distinguished between coronary calcifications and negatives or a multiclass classifier labeled CAC per coronary artery. Candidates that could not be labeled with high certainty were identified by entropy-based ambiguity detection and presented to an expert for review and possible relabeling. The system was evaluated with 530 test images. Using the two-class classifier, the intra-class correlation coefficient (ICC) between reference and automatically determined total patient CAC volume was 0.95. Using the multiclass classifier, the ICC between reference and automatically determined per artery CAC volume was 0.98 (LAD), 0.69 (LCX), and 0.95 (RCA). In 49% of CTs, no ambiguous candidates were identified, while review of the remaining CTs increased the ICC for total patient CAC volume to 1.00, and per artery CAC volume to 1.00 (LAD), 0.95 (LCX), and 0.99 (RCA). In conclusion, CAC can be automatically identified in non-contrast-enhanced ECG-triggered cardiac CT. Ambiguity detection with expert review may enable the application of automatic CAC scoring in the clinic with a performance comparable to that of a human expert.

Original languageEnglish
Article number7061518
Pages (from-to)1867-1878
Number of pages12
JournalIEEE transactions on medical imaging
Volume34
Issue number9
DOIs
Publication statusPublished - 1 Sep 2015
Externally publishedYes

Keywords

  • Ambiguity detection
  • automatic calcium scoring
  • cardiac CT
  • coronary artery calcium
  • guided review
  • supervised classification

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