Photon counting spectral CT component analysis of coronary artery atherosclerotic plaque samples

Abstract

Objective: To evaluate the capabilities of photon counting spectral CT to differentiate components of coronary atherosclerotic plaque based on differences in spectral attenuation and iodine-based contrast agent concentration.

Methods: 10 calcified and 13 lipid-rich non-calcified histologically demonstrated atheromatous plaques from post-mortem human coronary arteries were scanned with a photon counting spectral CT scanner. Individual photons were counted and classified in one of six energy bins from 25 to 70 keV. Based on a maximum likelihood approach, maps of photoelectric absorption (PA), Compton scattering (CS) and iodine concentration (IC) were reconstructed. Intensity measurements were performed on each map in the vessel wall, the surrounding perivascular fat and the lipid-rich and the calcified plaques. PA and CS values are expressed relative to pure water values. A comparison between these different elements was performed using Kruskal-Wallis tests with pairwise post hoc Mann-Whitney U-tests and Sidak p-value adjustments.

Results: RESULTS for vessel wall, surrounding perivascular fat and lipid-rich and calcified plaques were, respectively, 1.19 ± 0.09, 0.73 ± 0.05, 1.08 ± 0.14 and 17.79 ± 6.70 for PA; 0.96 ± 0.02, 0.83 ± 0.02, 0.91 ± 0.03 and 2.53 ± 0.63 for CS; and 83.3 ± 10.1, 37.6 ± 8.1, 55.2 ± 14.0 and 4.9 ± 20.0 mmol l(-1) for IC, with a significant difference between all tissues for PA, CS and IC (p < 0.012).

Conclusion: This study demonstrates the capability of energy-sensitive photon counting spectral CT to differentiate between calcifications and iodine-infused regions of human coronary artery atherosclerotic plaque samples by analysing differences in spectral attenuation and iodine-based contrast agent concentration.

Advances in knowledge: Photon counting spectral CT is a promising technique to identify plaque components by analysing differences in iodine-based contrast agent concentration, photoelectric attenuation and Compton scattering.

Figure 1.

Primary X-ray spectrum for 70 kVp.

Figure 2.

Illustration of the different X-ray mass attenuation effects for typical CT energy range (20–140 keV). Examples of photoelectric absorption (PA, dashed line) and Compton scattering (CS, dotted dashed line) effects of water. Mass attenuation coefficients for PA decrease when X-ray energy increases, whereas CS remains nearly constant. Attenuation of iodine (solid line) presents with a peak at 33.2 keV corresponding to the K-edge effect. The mass attenuation values were generated using the program XCOM® (NIST, Gaithersburg, MD).

Figure 3.

Photon counting spectral CT scanner principles. Each individual X-ray interacts in the semi-conductor detector and directly generates a large number of electron–hole pairs proportional to its energy. The resulting charge pulse does not only allow counting individual X-ray photons but also determining their primary energy by measuring the pulse height of the corresponding peak with multiple thresholds.

Figure 4.

Slice of a coronary artery presenting with a calcified plaque (black arrows). Histological slice (left part) and photon counting spectral CT images with CT-like image (centre) and iodine concentration (right part) map [linear scale from black (0 mmol l⁻¹) to white (130 mmol l⁻¹)].

Figure 5.

Slice of a coronary artery presenting with a lipid-rich plaque (white arrows): histological slice (left part) and photon counting spectral CT images with CT-like image (centre) and color-coded iodine concentration (right part) maps [linear scale from black (0 mmol l⁻¹) to white (70 mmol l⁻¹)]. Surrounding perivascular fat is also present on the slices (arrow heads).

Figure 6.

Successive graphs of photoelectric absorption (PA), Compton scattering (CS) and iodine concentration values of vessel wall, perivascular fat, lipid-rich plaque and calcified plaque. The y-axis of the PA graph is interrupted in order to display the upper values of PA in calcified plaque. Error bars represent the standard deviations. For each measured parameter, all values are significantly different (*p < 0.001) between the four measured tissues.