Validation and application of OCT tissue attenuation index for the detection of neointimal foam cells

Abstract

Neointimal infiltration with foamy macrophages is recognized as an early and important sign of de-novo atherosclerosis after stent implantation (neoatherosclerosis). Recent histopathological studies have proven that automated quantification of signal attenuation using intravascular optical coherence tomography (OCT) imaging allows for sensitive identification of macrophages in native atherosclerotic disease. Whether this is true for neointimal foam cells in the setting of neoatherosclerosis remains unknown. Autopsy samples of stented coronary arteries (n = 13 cases) were evaluated by histology and OCT. After co-registration with histology, the attenuation rate of emitted laser light was measured in regions with and without neointimal foamy macrophages relative to its peak intensity at the blood-tissue interface. Attenuation index was subsequently determined as slope of a regression curve fitted to individual data points. Receiver operating curve (ROC) analysis was used to establish an optimal cutoff for detecting foamy macrophages in homogenous and non-homogenous neointima, respectively. Finally, the tissue attenuation index was applied to confirm or exclude the presence of neointimal foamy macrophages in symptomatic patients presenting with in-stent restenosis and undergoing intravascular OCT imaging (n = 29 cases). Tissue attenuation index derived from post-mortem samples differed significantly between histologically confirmed regions with and without neointimal foamy macrophages (− 1.23 ± 1.42 vs. − 0.52 ± 1.79, p < 0.05). ROC analysis was able to distinguish neointima with foamy macrophage infiltration from neointima without (93% sensitivity, 73% specificity, cutoff − 0.79, AUC 0.87 for homogenous neointima and 40% sensitivity, 95% specificity, cutoff − 1.93, AUC 0.69 for non-homogenous neointima). In symptomatic patients presenting with in-stent restenosis after stent implantation and undergoing intravascular imaging with OCT, neointimal foamy macrophages were detected in 34.2% of homogenous and 43.6% of non-homogenous neointimal ROI's evaluated. OCT-derived and histopathologically validated tissue attenuation index enables identification of neointimal foamy macrophages in stented coronary arteries. Such image-based post-processing software algorithm may help discern and triage subjects at increased risk for device-related events.

Histopathology-Based Deep-Learning Predicts Atherosclerotic Lesions in Intravascular Imaging

“…Coronary arteries were then cut by an experienced pathologist according to the standard AHA classification. OCT imaging of the single segments was then performed as previously described ( 15 ): After careful preparation, vessels were wired with a 0.014-inch guidewire over which the OCT catheter (2.7-F, St. Jude Medical, St. Paul, Minnesota) was advanced. An imaging pullback was performed from the distal to the proximal arterial segments while simultaneously flushing the vessel with contrast to improve imaging quality (pullback speed 5 mm/s = 120 frames/s).…”

“…For intravascular imaging, several groups demonstrated the possibility of automated plaque characterization using semiautomated approaches such as quantification of various optical signal properties (e.g. light attenuation) (12)(13)(14)(15). The feasibility of using deep-learning algorithms for detection and visualization of atherosclerotic plaque components was also demonstrated recently (9,11,(16)(17)(18)(19).…”

DeepNeo: Deep Learning for neointimal tissue characterization using optical coherence tomography

“…A total of 1148 frames from 92 pullbacks were analyzed. Neointimal tissue was classified using a quadrant-based nominal character scoring system as previously described [19]: clockwise and starting at 12 o'clock, every frame was divided into four quadrants (see Figure 1 A), with the center of the lumen as the dividing point. Each quadrant was then independently classified according to its predominant neointimal appearance into one of four classes: homogenous neointima (uniform light reflection without localized areas of stronger or weaker backscattering properties), heterogenous neointima (consisting of a focal variation of the backscattering pattern, including patterns described as "layered"), neoatherosclerosis (containing neointimal foam cells, fibroatheroma or calcifications) [20,21] or not analyzable (quadrants with uncovered struts or side-branch openings).…”

Neoatherosclerosis: A Distinctive Pathological Mechanism of Stent Failure

“…However, surrogate measurements such as lipid angle have been validated to better estimate lipid plaque area [ 15 ]. Adventitia is also difficult to observe due to the insufficient penetration and obstruction by the struts from implanted stents [ 16 ]. It is also difficult to determine the boundary of calcification which is near the adventitia.…”