![]() These tissue recognition mistakes may have costly downstream consequences in automated digital pathology workflows, be it for diagnostic or research purposes. Omitted tissue areas could pose a significant problem for diagnostic accuracy, e.g., such as in cancer, identifying malignant regions in lymph nodes 17. Whole-slide scanners are known to fail to identify or “mask” the entire tissue region, e.g., due to dust specs, transparent tissue types (e.g., adipose) or weak immunostaining results. However, the process of WSI acquisition has its own technical challenges. 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. Roche Diagnostics has a total product portfolio for pathology diagnosis, including BenchMark Special Stains, H&E dyeing equipment HE600, and VANTAGE, a pathology management system, the company said.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. It’s Area of Interest (AOI) automatic detection function produces high-quality images, according to Roche. The device also applies a unique International Color Consortium (ICC) color profile to each image to ensure the digital image closely matches colors observed under a microscope. The DP 200 is a tray-type design that does not require slides to be moved directly, reducing scan errors and adding stability to equipment operation. These devices allow specialists to diagnose patients by utilizing digital images scanned from a tissue dyeing slide instead of microscopic readings. The advent of digital pathology scanner equipment has helped pathologists diagnose patients, anywhere, anytime, the company said. ![]() Specialist traditionally diagnosed a patient’s tissue slide by reading the microscope with the naked eye after staining during a biopsy. ![]()
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