![]() ![]() In the histology-based analyses, local plaque indices such as plaque hemorrhage and neovascularity were shown to correlate with more adverse vascular outcomes 7, 9.Īccurate tissue segmentation is a necessary initial step in WSI analysis in digital pathology workflows, particularly for deep learning-based classification. This has led to several prospective studies to correlate local atherosclerotic plaque composition with future local and systemic vascular outcomes, using histology 7– 10, RNA 12, 13, genetics 14, and protein 15, 16 data. The Athero-Express study 3 is a large-scale vascular tissue biobank comprising over 3,600 carotid and femoral endarterectomy surgical specimens, which include detailed clinical outcomes and follow-up. Overall, this has simplified archiving, enabled remote diagnosis, and accelerated both clinical decision-making and research investigations 11.Īpplication of quantitative WSI analysis pipelines requires access to uniformly processed and well-characterized tissue biobanks. WSI data provides a rich resource for quantitative and qualitative image analysis and has been a focus of digital pathology 10. These features can now be easily captured from stained tissue sections and digitized as high-resolution Whole Slide Images (WSI). For example, in pre-clinical models of atherosclerosis, the amount of smooth muscle content and collagen extracellular matrix in the plaque often correlates with greater plaque stability 8. While histology-based assessment of cancer and other diseases is often required for clinical diagnosis, histological analysis of atherosclerosis can reveal the extent of disease progression as well as underlying etiology. However, the value of atherosclerotic plaque composition in predicting cardiovascular events remains a subject of debate and ongoing research 7– 9. ![]() For instance, more stable, fibrous-rich atheroma plaques are typically asymptomatic, whereas unstable, thin-cap fibroatheroma plaques are more prone to rupture and thrombus formation underlying cerebral or coronary events 5, 6. The composition of atherosclerotic plaques is highly variable, with different plaque types having distinct clinical manifestations 3, 7. Historically, researchers and pathologists have characterized atherosclerotic plaque through standard histology and light microscopy analysis 3– 6. The image analysis system can substitute for or support visual counting by a pathologist.Atherosclerosis is a chronic inflammatory process resulting in arterial stiffening and plaque formation, and is the leading cause of myocardial infarction, ischemic stroke, and peripheral artery disease 1, 2. The performance of 30-9 is equivalent to that of MIB-1 in Ki67 assessment of breast cancer. Ki67-positive rates showed a strong correlation between the image analytical values and the pathologist-counted median values (r = 0.952). Between 30-9 and MIB-1, there was no significant difference of CV%, showing variabilities of Ki67-positive rates among pathologists. Ki67-positive rates by 30-9 showed a strong correlation with those by MIB-1 for all pathologists (pathologist #1: r = 0.985, pathologist #2: r = 0.987, pathologist #3: r = 0.982). In addition, the images of 30-9-stained slides were analyzed using the image analysis system, VENTANA Virtuoso. Three pathologists independently studied images of the counting areas to determine Ki67-positive rates. We scanned all the stained slides with Ventana iScan HT and selected the Ki67 counting areas based on morphological findings. The tissue sections were stained immunohistochemically with anti-Ki67 antibodies, 30-9 and MIB-1, as well as with hematoxylin and eosin for morphological analysis. We aimed to validate the performance of anti-Ki67 antibody clone 30-9 by comparison with clone MIB-1 and to investigate utility of the image analysis system in Ki67 assessment using clinical breast cancer samples.Ī series of sequential tissue sections was prepared from formalin-fixed paraffin-embedded blocks of surgically resected breast cancer specimens from 50 patients. Although Ki67 has important clinical relevance in breast cancer, its assessment results vary according to assay due to differences in both analytical and interpretation processes. ![]()
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