Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Dec 8;46(46):5045-5048.
doi: 10.1093/eurheartj/ehaf707.

Clinical photon-counting computed tomography in living patients detects intra-plaque haemorrhage and thrombus in carotid plaques

Annelie Shami  1 , Jiangming Sun  1 , My Celander  2 , Ana Persson  1 , Andreas Edsfeldt  1   3   4 , Martin Bech  2 , Marie-Louise Aurumskjöld  5   6 , Isabel Gonçalves  1   3
Affiliations

Clinical photon-counting computed tomography in living patients detects intra-plaque haemorrhage and thrombus in carotid plaques

Annelie Shami et al. Eur Heart J. .
No abstract available

Keywords: Atherosclerosis; Carotid arteries; Computed tomography; Plaque; X-ray.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Comparison of the attenuation of distinct atherosclerotic plaque features scanned by photon-counting computed tomography of living patients pre-operatively and the corresponding microscopic images of the plaques obtained by carotid endarterectomy. (A) Patient characteristics are shown. Continuous measurements are shown as mean with standard deviation. Categorical variables are shown as absolute numbers (indicating ‘yes’) and percentages (indicating ‘yes’, if not otherwise specified). Body mass index is shown as kg/m2. Fasting lipoproteins (cholesterol, triglycerides, LDL, and HDL) are shown as mmol/L, while HbA1c is shown as mmol/mol. N = 10, except n = 8 for LDL and HDL. High-resolution photon-counting computed tomography angiography overview volume rendering technique images are shown in (B) with zoomed region (white box) denoting a high degree of stenosis in the left carotis interna (indicated by white arrows). Regions of interest (annotated circles) are shown in representative corresponding images acquired from photon-counting computed tomography scanning (70 keV) and through histochemistry (Russell-Movat’s pentachrome stain) of two different plaques in (C) and (D). The lumen is denoted by an asterisk, and scale bars represent 1 mm. Measured Hounsfield units (with a 95% confidence interval) are shown for all measured energies (E; 40–190 keV, note the segmented X axis), along with Hounsfield unit ranges resulting from this dataset at 70 keV, an energy level well within the interval of sufficient statistical power for all the studied plaque feature comparisons [except for intra-plaque haemorrhage (IPH) vs thrombus, where slightly lower power (0.761) is achieved]. Annotated plaque features are compared using the Kruskal–Wallis test followed by Dunn’s post-hoc test and Bonferroni correction for multiple comparisons. Hounsfield units measured for calcifications were distinguishable from that of all other features at all energy levels (P-values ranging from 2.0 × 10−123 to 2.0 × 10−127), as was Hounsfield units for intra-plaque haemorrhage (P = 2.0 × 10−20 to 2.0 × 10−29), with the exception of comparison with thrombus. Thrombus Hounsfield units were distinct from all features (excluding intra-plaque haemorrhage) at 40–166 keV (P = .049 to 8.0 × 10−21), while indistinguishable from fibrosis >167 keV. Besides calcification, intra-plaque haemorrhage, and thrombus, Hounsfield units for fibrosis could be differentiated from lipid core at all energy levels (P = 5.0 × 10−9 to 1.0 × 10−15) and from necrosis Hounsfield units at 40–86 keV (P = .047 to .0007), while lipid core and necrosis Hounsfield units were only weakly distinguishable (P = .043–.049) from each other at 80–116 and 150–190 keV (except for at 184 keV). In (F), differences in coefficients derived through a mixed-effects model were found for all evaluated plaque features (P < 9.7 × 10−7, shown with 95% confidence interval), as assessed by t-test (with Benjamini–Hochberg adjustment for multiple comparisons). n (calcium) = 340, n (intra-plaque haemorrhage) = 106, n (thrombus) = 43; n (lipid core) = 107, n (fibrosis) = 470, n (necrosis) = 62
See this image and copyright information in PMC

References

    1. Sakakura K, Nakano M, Otsuka F, Ladich E, Kolodgie FD, Virmani R. Pathophysiology of atherosclerosis plaque progression. Heart Lung Circ 2013;22:399–411. 10.1016/j.hlc.2013.03.001 - DOI - PubMed
    1. McNally JS, McLaughlin MS, Hinckley PJ, Treiman SM, Stoddard GJ, Parker DL, et al. Intraluminal thrombus, intraplaque hemorrhage, plaque thickness, and current smoking optimally predict carotid stroke. Stroke 2015;46:84–90. 10.1161/STROKEAHA.114.006286 - DOI - PubMed
    1. Meloni A, Cau R, Saba L, Positano V, De Gori C, Occhipinti M, et al. Photon-counting computed tomography angiography of carotid arteries: a topical narrative review with case examples. Diagnostics (Basel) 2024;14:2012. 10.3390/diagnostics14182012 - DOI - PMC - PubMed
    1. Shami A, Sun J, Gialeli C, Markstad H, Edsfeldt A, Aurumskjold ML, et al. Atherosclerotic plaque features relevant to rupture-risk detected by clinical photon-counting CT ex vivo: a proof-of-concept study. Eur Radiol Exp 2024;8:14. 10.1186/s41747-023-00410-4 - DOI - PMC - PubMed
    1. Gonçalves I, Moses J, Dias N, Pedro LM, Fernandes e Fernandes J, Nilsson J, et al. Changes related to age and cerebrovascular symptoms in the extracellular matrix of human carotid plaques. Stroke 2003;34:616–22. 10.1161/01.STR.0000058157.69113.F6 - DOI - PubMed