Fifty-eighth annual meeting of the american association of physicists in medicine
TH-CD-206-07: Determination of Patient-Specific Myocardial Mass at Risk Using Computed Tomography Angiography
To evaluate the accuracy of a patient-specific coronary perfusion territory assignment algorithm that uses CT angiography (CTA) and a minimum-cost-path approach to assign coronary perfusion territories on a voxel-by-voxel basis for determination of myocardial mass at risk.
Intravenous (IV) contrast (370 mg/mL iodine, 25 mL, 7 mL/s) was injected centrally into five swine (35–45 kg) and CTA was performed using a 320-slice CT scanner at 100 kVp and 200 mA. Additionally, a 4F catheter was advanced into the left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) and contrast (30 mg/mL iodine, 10 mL, 1.5 mL/s) was directly injected into each coronary artery for isolation of reference coronary perfusion territories. Semiautomatic myocardial segmentation of the CTA data was then performed and the centerlines of the LAD, LCX, and RCA were digitally extracted through image processing. Individual coronary perfusion territories were then assigned using a minimum-cost-path approach, and were quantitatively compared to the reference coronary perfusion territories.
The results of the coronary perfusion territory assignment algorithm were in good agreement with the reference coronary perfusion territories. The average volumetric assignment error from mitral orifice to apex was 5.5 ± 1.1%, corresponding to 2.1 ± 0.7 grams of myocardial mass misassigned for each coronary perfusion territory.
The results indicate that accurate coronary perfusion territory assignment is possible on a voxel-by-voxel basis using CTA data and an assignment algorithm based on a minimum-cost-path approach. Thus, the technique can potentially be used to accurately determine patient-specific myocardial mass at risk distal to a coronary stenosis, improving coronary lesion assessment and treatment.
Conflict of Interest (only if applicable): Grant funding from Toshiba America Medical Systems.