Impact of virtual monoenergetic levels on coronary plaque volume components using photon-counting computed tomography

Abstract

Objectives: Virtual monoenergetic images (VMIs) from photon-counting CT (PCCT) may change quantitative coronary plaque volumes. We aimed to assess how plaque component volumes change with respect to VMIs.

Methods: Coronary CT angiography (CTA) images were acquired using a dual-source PCCT and VMIs were reconstructed between 40 and 180 keV in 10-keV increments. Polychromatic images at 120 kVp (T3D) were used as reference. Quantitative plaque analysis was performed on T3D images and segmentation masks were copied to VMI reconstructions. Calcified plaque (CP; > 350 Hounsfield units, HU), non-calcified plaque (NCP; 30 to 350 HU), and low-attenuation NCP (LAP; - 100 to 30 HU) volumes were calculated using fixed thresholds.

Results: We analyzed 51 plaques from 51 patients (67% male, mean age 65 ± 12 years). Average attenuation and contrast-to-noise ratio (CNR) decreased significantly with increasing keV levels, with similar values observed between T3D and 70 keV images (299 ± 209 vs. 303 ± 225 HU, p = 0.15 for mean HU; 15.5 ± 3.7 vs. 15.8 ± 3.5, p = 0.32 for CNR). Mean NCP volume was comparable between T3D and 100-180-keV reconstructions. There was a monotonic decrease in mean CP volume, with a significant difference between all VMIs and T3D (p < 0.05). LAP volume increased with increasing keV levels and all VMIs showed a significant difference compared to T3D, except for 50 keV (28.0 ± 30.8 mm³ and 28.6 ± 30.1 mm³, respectively, p = 0.63).

Conclusions: Estimated coronary plaque volumes significantly differ between VMIs. Normalization protocols are needed to have comparable results between future studies, especially for LAP volume which is currently defined using a fixed HU threshold.

Clinical relevance statement: Different virtual monoenergetic images from photon-counting CT alter attenuation values and therefore corresponding plaque component volumes. New clinical standards and protocols are required to determine the optimal thresholds to derive plaque volumes from photon-counting CT.

Key points: • Utilizing different VMI energy levels from photon-counting CT for the analysis of coronary artery plaques leads to substantial changes in attenuation values and corresponding plaque component volumes. • Low-energy images (40-70 keV) improved contrast-to-noise ratio, however also increased image noise. • Normalization protocols are needed to have comparable results between future studies, especially for low-attenuation plaque volume which is currently defined using a fixed HU threshold.

Keywords: Atherosclerosis; CT angiography; Coronary arteriosclerosis; Reproducibility of results.

Fig. 1

Representative CTA images of coronary plaques reconstructed in T3D and different VMI energy levels (40, 70, 120, and 180 keV). Quantitative plaque analyses of a partially calcified-predominantly non-calcified (panel A) and partially calcified-predominantly calcified (panel B) plaque are shown in T3D and different VMI reconstructions at 40, 70, 120, and 180 keV levels. The red line illustrates the border of the vessel wall and the orange line illustrates the lumen border segmented on T3D images. Corresponding cross-sectional images are also depicted at the point of the maximal narrowing of the lesion. The same window setting was applied for all represented images: window: 800; level: 250. Abbreviations: CP, calcified plaque; HU, Hounsfield unit; LAP, low-attenuation non-calcified plaque; NCP, non-calcified plaque

Fig. 2

Box plots showing the distribution of plaque attenuation and quantitative image quality parameters (SD, CNR, SNR) in different VMI energy levels and T3D images. Panel A depicts the distribution of attenuation values across different energy levels. Panel B depicts the distribution of image noise based on SD across different energy levels. Panel C depicts the distribution CNR across different energy levels. Panel D depicts the distribution SNR across different energy levels. Abbreviations: CNR, contrast-to-noise ratio; HU, Hounsfield unit; SD, standard deviation; SNR, signal-to-noise ratio

Fig. 3

Box plots showing the distribution of plaque volumes in different VMI energy levels and T3D images using the thresholds of method 1 for plaque characterization. Panel A shows the distribution of NCP volume across different energy levels using threshold of − 100 to 350 HU. Panel B shows the distribution of CP volume across different energy levels using the threshold of > 350 HU. Panel C shows the distribution of LAP volume across different energy levels using the threshold of − 100 to 30 HU. Abbreviations: CP, calcified plaque; HU, Hounsfield unit; LAP, low-attenuation non-calcified plaque; NCP, non-calcified plaque; SD, standard deviation

Fig. 4

Box plots showing the distribution of plaque volumes in different VMI energy levels and T3D images using the thresholds of method 2 for plaque characterization. Panel A shows the distribution of NCP volume across different energy levels using threshold of < 130 HU. Panel B shows the distribution of CP volume across different energy levels using the threshold of > 130 HU. Panel C shows the distribution of LAP volume across different energy levels using the threshold of < 30 HU. Abbreviations: CP, calcified plaque; HU, Hounsfield unit; LAP, low-attenuation non-calcified plaque; NCP, non-calcified plaque; SD, standard deviation