Evaluation and Management of the Vulnerable Plaque

Virtual pathology: Reaching higher standards for noninvasive CTA tissue characterization capability by using histology as a truth standard

AIMS

Despite advances in therapy, reduction in myocardial infarction or death remains elusive. Whereas computed tomography angiography (CTA) is increasingly appreciated, the analyses are often subjective or qualitative. Methods for specific tissue characterization using histopathologic correlates have recently been reported. We extend this here to demonstrate accurate discrimination between, and quantitation of, lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH), and fibrotic tissues.

METHODS

NCT02143102 collected 576 tissue samples with paired CTA. Cardiovascular pathologists annotated LRNC, IPH, and dense calcification (CALC) regions as a reference standard. Blinded to histology, CTA was analyzed using ElucidVivo (Elucid Bioimaging Inc., Boston, MA USA). Structure and tissue characteristics of atherosclerotic plaque from CTA, accounting for both the imaging acquisition process and the biology, accounting for differences in density distributions that result from the different cellular and molecular level milieu of the relevant tissue types.

RESULTS

LRNC was tested across a true range of 0-10 mm², with a difference of 0.15 mm² and a slope of 0.92. IPH was tested across a true range of 0-18 mm², with a difference from histology of 1.68 mm² and a slope of 0.95. CALC was tested across a range of 0-14 mm², with a difference of -0.06 mm² and a slope of 0.99. Matrix tissue (MATX) was tested across a range of 4-52 mm², with a difference of 0.02 mm² and a slope of 0.91.

CONCLUSION

LRNC, IPH, CALC, and MATX may be objectively quantified using histopathologic correlates automatically from CTA for use singly or in combination to optimize patient care. The availability of objectively validated quantitative markers that may be followed longitudinally may extend the clinical utility of CTA. Additionally, these measures contribute efficacy variables for developing novel drugs and clinical decision support tools for tailored therapeutics.

Patient-specific biomechanical analysis of atherosclerotic plaques enabled by histologically validated tissue characterization from computed tomography angiography: A case study

BACKGROUND

Rupture of unstable atherosclerotic plaques with a large lipid-rich necrotic core and a thin fibrous cap cause myocardial infarction and stroke. Yet it has not been possible to assess this for individual patients. Clinical guidelines still rely on use of luminal narrowing, a poor indicator but one that persists for lack of effective means to do better. We present a case study demonstrating the assessment of biomechanical indices pertaining to plaque rupture risk non-invasively for individual patients enabled by histologically validated tissue characterization.

METHODS

Routinely acquired clinical images of plaques were analyzed to characterize vascular wall tissues using software validated by histology (ElucidVivo, Elucid Bioimaging Inc.). Based on the tissue distribution, wall stress and strain were then calculated at spatial locations with varied fibrous cap thicknesses at diastolic, mean and systolic blood pressures.

RESULTS

The von Mises stress of 152 [131, 172] kPa and the equivalent strain of 0.10 [0.08, 0.12] were calculated where the fibrous cap thickness was smallest (560 μm) (95% CI in brackets). The stress at this location was at a level predictive of plaque failure. Stress and strain at locations with larger cap thicknesses were calculated to be lower, demonstrating a clinically relevant range of risk levels.

CONCLUSION

Patient specific tissue characterization can identify distributions of stress and strain in a clinically relevant range. This capability may be used to identify high-risk lesions and personalize treatment decisions for individual patients with cardiovascular disease and improve prevention of myocardial infarction and stroke.

Virtual Transcriptomics: Noninvasive Phenotyping of Atherosclerosis by Decoding Plaque Biology From Computed Tomography Angiography Imaging

[Figure: see text].