Background: Coronary computed tomography angiography (CCTA) provides non-invasive
quantitative assessments of plaque burden and composition. The quantitative assessment
of plaque components requires the use of analysis software that provides reproducible
semi-automated plaque detection and analysis. However, commercially available plaque
analysis software can vary widely in the degree of automation, resulting in differences
in terms of reproducibility and time spent. Aim: To compare the reproducibility and
time spent of two CCTA analysis software tools using different algorithms for the
quantitative assessment of coronary plaque volumes and composition in two independent
patient cohorts. Methods: The study population included 100 patients from two different
cohorts: 50 patients from a single-center (Siemens Healthineers, SOMATOM Force (DSCT))
and another 50 patients from a multi-center study (5 different > 64 slice CT scanner
types). Quantitative measurements of total calcified and non-calcified plaque volume
of the right coronary artery (RCA), left anterior descending (LAD), and left circumflex
coronary artery (LCX) were performed on a total of 300 coronaries by two independent
readers, using two different CCTA analysis software tools (Tool #1: Siemens Healthineers,
syngo.via Frontier CT Coronary Plaque Analysis and Tool #2: Siemens Healthineers,
successor CT Coronary Plaque Analysis prototype). In addition, the total time spent
for the analysis was recorded with both programs. Results: The patients in cohorts
1 and 2 were 62.8 +/- 10.2 and 70.9 +/- 11.7 years old, respectively, 10 (20.0%) and
35 (70.0%) were female and 34 (68.0%) and 20 (40.0%), respectively, had hyperlipidemia.
In Cohort #1, the inter- and intra-observer variabilities for the assessment of plaque
volumes per patient for Tool #1 versus Tool #2 were 22.8%, 22.0%, and 26.0% versus
2.3%, 3.9%, and 2.5% and 19.7%, 21.4%, and 22.1% versus 0.2%, 0.1%, and 0.3%, respectively,
for total, noncalcified, and calcified lesions (p < 0.001 for all between Tools #1
and 2 both for inter- and intra-observer). The inter- and intra-observer variabilities
using Tool #2 remained low at 2.9%, 2.7%, and 3.0% and 3.8%, 3.7%, and 4.0%, respectively,
for total, non-calcified, and calcified lesions in Cohort #2. For each dataset, the
median processing time was higher for Tool #1 versus Tool #2 (459.5 s IQR = 348.0-627.0
versus 208.5 s; IQR = 198.0-216.0) (p < 0.001). Conclusion: The plaque analysis Tool
#2 (CT-guided PCI) encompassing a higher degree of automated support required less
manual editing, was more time-efficient, and showed a higher intra- and inter-observer
reproducibility for the quantitative assessment of plaque volumes both in a representative
single-center and in a multi-center validation cohort.
