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.