Cardiac computed tomography-derived myocardial mass at risk using the Voronoi-based segmentation algorithm: A...

Area of Science:

• Cardiovascular Imaging
• Medical Physics
• Anatomical Pathology

Background:

• Myocardial mass at risk (MMAR) is a crucial predictor of adverse cardiac events in patients with ischemic heart disease.
• Accurate MMAR assessment is vital for risk stratification and treatment planning.

Purpose of the Study:

• To validate the accuracy of MMAR calculated from cardiac computed tomography (CCT) data using a Voronoi-based segmentation algorithm.
• To compare CCT-derived MMAR with actual MMAR measured on ex-vivo swine hearts.

Main Methods:

• Fifteen swine hearts underwent coronary artery injection with India ink and contrast agent, followed by 16-row CT imaging.
• Ventricles were cross-sectioned, and actual MMAR was calculated using the disc-summation method.
• CT-based MMAR was automatically computed using the Voronoi-based segmentation algorithm for comparison.

Main Results:

• CT-based MMAR showed strong correlations with actual MMAR for the left anterior descending (LAD) artery (r=0.92), left circumflex (LCX) artery (r=0.96), and right coronary artery (RCA) (r=0.96).
• CT-based MMAR values were comparable to actual MMAR measurements across all major coronary artery territories.

Conclusions:

• The Voronoi-based segmentation algorithm applied to CCT data reliably estimates actual MMAR.
• This CT-based method offers a validated approach for assessing MMAR in clinical settings.