Iterative image reconstruction algorithms in coronary CT angiography improve the detection of lipid-core plaque - a comparison with histology

Objectives To evaluate whether iterative reconstruction algorithms improve the diagnostic accuracy of coronary CT angiography (CCTA) for detection of lipid-core plaque (LCP) compared to histology. Methods and materials CCTA and histological data were acquired from three ex vivo hearts. CCTA images were reconstructed using filtered back projection (FBP), adaptivestatistical (ASIR) and model-based (MBIR) iterative algorithms. Vessel cross-sections were co-registered between FBP/ASIR/MBIR and histology. Plaque area <60 HU was semiautomatically quantified in CCTA. LCP was defined by histology as fibroatheroma with a large lipid/necrotic core. Area under the curve (AUC) was derived from logistic regression analysis as a measure of diagnostic accuracy. Results Overall, 173 CCTA triplets (FBP/ASIR/MBIR) were co-registered with histology. LCP was present in 26 crosssections. Average measured plaque area <60 HU was significantly larger in LCP compared to non-LCP cross-sections (mm(2): 5.78 +/- 2.29 vs. 3.39 +/- 1.68 FBP; 5.92 +/- 1.87 vs. 3.43 +/- 1.62 ASIR; 6.40 +/- 1.55 vs. 3.49 +/- 1.50 MBIR; all p<0.0001). AUC for detecting LCP was 0.803/0.850/0.903 for FBP/ASIR/MBIR and was significantly higher for MBIR compared to FBP (p=0.01). MBIR increased sensitivity for detection of LCP by CCTA. Conclusion Plaque area <60 HU in CCTA was associated with LCP in histology regardless of the reconstruction algorithm. However, MBIR demonstrated higher accuracy for detecting LCP, which may improve vulnerable plaque detection by CCTA.