Atherosclerosis is a progressive inflammatory disease characterized by plaque formation
due to subintimal lipid accumulation in the arteries, which eventually leads to cardiovascular
events. Carotid endarterectomy (CEA) is commonly performed to reduce mortality due
to plaque accumulation. Currently, CEA candidates are selected based on plaque burden,
but ultrasound (US) pixel grayscale analysis of plaque lesions may better identify
plaque composition and vulnerability to rupture. Grayscale ranges representing various
tissue types have been previously defined in the literature using decades-old US systems.
Direct histologic validation of these ranges has not been established. Our objective
was to assess the ability of US to identify plaque tissues based on existing grayscale
pixel ranges and validate them via histologic analysis of excised plaques.
METHODS AND RESULTS
A 3D carotid US (Philips Healthcare EPIQ Elite, XL14-3 transducer) was performed on
4 participants prior to undergoing CEA. The excised plaques were fixed, decalcified,
and embedded in 2% agarose for imaging. Each plaque was sectioned every 2 mm, trichrome-stained,
and histological composition was determined using QuPath, a digital image analysis
software. The 3D US image was iSliced using QLab Philips software and slices were
registered to corresponding histological sections. US plaque composition was analyzed
using a novel, semi-automated software (IntelliPlaque) that applied the previously
published grayscale ranges ex-vivo to map tissue types within the plaque. Matched
paired t-tests were used to compare tissue composition between US and histology. Comparison
of plaque tissue composition determined by US (percent fibrous, muscle, fat, blood,
and calcified tissue) and the corresponding histological sections (n=27) indicated
some resemblance. Percent fat-like tissue on US was not significantly different from
percent foam cells on histology, indicating resemblance for this tissue type (mean
difference=-0.20±0.41%, r=0.27; p=0.63). Similarly, percent muscle and percent calcium
on US were not significantly different from histology (p>0.1). Percent fibrous and
percent blood were significantly different, indicating poor resemblance. The weakest
resemblance was between percent fat-like tissue on US and percent lipid-rich/necrotic
core on histology (-19.80±3.09%, r=0.66; p < 0.0001).
Our findings suggest that existing grayscale ranges corresponding to the necrotic
core and/or blood tissue are outdated and require re-validation using modern US technology.
US pixel distribution analysis is a non-invasive, rapid assessment tool that can improve
patient risk stratification beyond plaque burden alone. Updated grayscale ranges will
improve the detection of plaque composition and potentially risk of plaque rupture.