Quantitative assessment of carotid plaque morphology (geometry and tissue composition) using computed tomography
Matthew T Chrencik1, Amir A Khan2, Lauren Luther1
1Department of Vascular Surgery, University of Maryland School of Medicine, Baltimore, Md; Vascular Service, Veterans Affairs Medical Center, Baltimore, Md.
Objective:
Quantification of carotid plaque morphology (geometry and tissue composition) may help stratify risk for future stroke and assess plaque progression or regression in response to medical risk factor modification. We assessed the feasibility and reliability of morphologic measurements of carotid plaques using computed tomography angiography (CTA) and determined the minimum detectable change in plaque features by this approach.
Methods:
CTA images of both carotid arteries in 50 patients were analyzed by two observers using a semiautomatic image analysis program, yielding 93 observations per user (seven arteries were excluded because of prior stenting). One observer repeated the analyses 4 weeks later. Measurements included total plaque volume; percentage stenosis (by diameter and area); and tissue composition for calcium, lipid-rich necrotic core (LRNC), and intraplaque hemorrhage (IPH). Reliability of measurements was assessed by intraclass and interclass correlation and Bland-Altman plots. Dice similarity coefficient (DSC) and modified Hausdorff distance (MHD) assessed reliability of geometric shape measurements. We additionally computed the minimum amount of change in these features detectable by our approach.
Results:
The cohort was 51% male (mean age, 70.1 years), and 56% had a prior stroke. The mean (± standard deviation) plaque volume was 837.3 ± 431.3 mm3, stenosis diameter was 44.5% ± 25.6%, and stenosis area was 58.1% ± 29.0%. These measurements showed high reliability. Intraclass correlation coefficients for plaque volume, percentage stenosis by diameter, and percentage stenosis by area were 0.96, 0.87, and 0.83, respectively; interclass correlation coefficients were 0.88, 0.84, and 0.78. Intraclass correlations for tissue composition were 0.99, 0.96, and 0.86 (calcium, LRNC, and IPH, respectively), and interclass correlations were 0.99, 0.92, and 0.92. Shape measurements showed high intraobserver (DSC, 0.95 ± 0.04; MHD, 0.16 ± 0.10 mm) and interobserver (DSC, 0.94 ± 0.05; MHD, 0.19 ± 0.12 mm) luminal agreement. This approach can detect a change of at least 3.9% in total plaque volume, 1.2 mm3 in calcium, 4.3 mm3 in LRNC, and 8.6 mm3 in IPH with the same observer repeating measurements and 9.9% in plaque volume, 1.9 mm3 in calcium, 7.9 mm3 in LRNC, and 6.8 mm3 in IPH for two different observers.
Conclusions:
Carotid plaque geometry (total volume, diameter stenosis, and area stenosis) and tissue composition (calcium, LRNC, and IPH) are measured reliably from clinical CTA images using a semiautomatic image analysis program. The minimum change in plaque volume detectable is ∼4% if the same observer makes both measurements and ∼10% for different observers. Small changes in plaque composition can also be detected reliably. This approach can facilitate longitudinal studies for identifying high-risk plaque features and for quantifying plaque progression or regression after treatment.
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