Lipid Core Plaque Distribution Using Near-infrared Spectroscopy Is Consistent with Pathological Evaluation in Carotid Artery Plaques

Abstract

Carotid artery stenting (CAS) is performed as a treatment for carotid artery stenosis. However, lipid-rich plaques cause embolic complications and sequelae. Near-infrared spectroscopy (NIRS) can identify lipid components by applying a near-infrared absorption pattern, and the distribution of lipid components can be evaluated as the maximum lipid core burden index (maxLCBI). Intravascular ultrasound (IVUS) equipped with NIRS has been clinically applied recently, and its diagnostic usefulness and validation have been reported for coronary arteries; however, its consistency with actual pathological diagnosis in carotid artery lesions has not been validated. In this study, we investigated the consistency between the maxLCBI values and histopathological diagnoses. Patients with cervical carotid artery stenosis who underwent carotid endarterectomy (CEA) were examined in this prospective study. Pathological diagnosis was determined after NIRS evaluation, which was performed on the extracted plaques ex vivo . The histological slices of decalcified and paraffin-embedded sections were stained by hematoxylin–eosin (HE) and Elastica van Gieson (EVG), and for low-density lipoprotein (LDL), C-reactive protein (CRP), CD68, and glycophorin A. The correlation between maxLCBI values and histological findings. Seventy lesions assessed by NIRS were pathologically analyzed. There was a positive linear correlation between maxLCBI values and pathological findings as determined by HE (angle), HE (area%), EVG, CRP, and CD68 staining (respectively, r = 0.624, p <0.001; r = 0.578, p <0.001; r = 0.534, p <0.001; r = 0.723, p <0.001; r = 0.653, p <0.001). In conclusion, the maxLCBI values assessed by NIRS showed a significant positive linear correlation with pathological evaluations in carotid lesions. The maxLCBI values in carotid arteries are consistent with pathological evaluations.

Near-Infrared Spectroscopy for Distinguishing Malignancy in Thyroid Nodules

“…16,17 Thyroid tissue also contains lipids with distinct NIR peaks related to C-H stretching overtones and combinations, typically between 1200 and 1300 nm. 18,19 In addition, amide linkages in thyroid tissue proteins contribute to the NIR region, allowing N-H and O-H stretches associated with protein structures to be observed in NIR. 20 Lipid, water, and protein concentrations vary in normal thyroid tissues, benign nodules, and malignant nodules.…”

Long-term changes after carotid stenting assessed by intravascular ultrasound and near-infrared spectroscopy

“…Therefore, chemogram does not directly detect thickness of the fibrous cap covering the lipidic core (5,6). Nonetheless, it has been repeatedly demonstrated that high LCBI (i.e., lipid rich plaque) represents a vulnerable plaque and low LCBI a stable lesion (7)(8)(9)(10)(20)(21)(22)(23). High LCBI also correlates with thin cap fibroatheroma detected on optical coherence tomography imaging (24).…”

“…Detection of lipid core with NIRS was not compared with another imaging method because there is no gold standard for plaque composition in vivo. However, the accuracy of NIRS has been recently validated on human carotid artery plaques (10). Computed tomography and magnetic resonance imaging are used to characterize carotid plaques, but their performance is largely limited by the implanted stent.…”

“…NIRS combined with IVUS has been utilized to assess coronary atherosclerosis and the effect of various interventions on the lipid signal in coronary plaques (7)(8)(9). NIRS proved to be accurate in detecting lipid rich atheroma in endarterectomy specimens of human internal carotid artery compared to histology gold standard (10). NIRS-IVUS imaging of carotid arteries in vivo proved to be safe and capable of detection of lipid rich plaques and their distribution in carotid stenosis (11) and characterization of the composition of carotid stenosis and restenosis (12).…”

Deep learning assisted classification of spectral photoacoustic imaging of carotid plaques

“…Manual annotations were done for five equally important classes: lipids, collagen, hemorrhages, smooth muscle cells, and background regions (including water). Two experts performed the annotation on the different regions of the sample by evaluating the staining, tissue texture and comparing the PA modulation of the annotated pixel with the literature reference spectra [33] , [34] , [35] (the criteria used to identify the spectra of the 5 classes is presented in Appendix ). Afterward, we shrunk the identified areas to exclude the signal from tissue interfaces and to account for registration mismatches ( Fig.…”