A component‐by‐component characterisation of high‐risk atherosclerotic plaques by multiphoton microscopic imaging

Jain, Manu; Wu, Binlin; Pisapia, David; Salvatore, Steven; Mukherjee, Sushmita; Narula, Navneet

doi:10.1111/jmi.12584

Cited by 4 publications

(1 citation statement)

References 24 publications

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“…Patients with vulnerable plaques had significantly higher numbers of TIA. According to previous studies, these patients exhibit a higher risk of acute cerebrovascular events caused by the rupture of vulnerable plaques (34)(35)(36).…”

Section: Discussionmentioning

confidence: 89%

Specific matrix metalloproteinases and calcification factors are associated with the vulnerability of human carotid plaque

et al. 2018

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The rupture of atherosclerotic plaque provokes the majority of acute cerebrovascular events. Studies have demonstrated that various matrix metalloproteinases (MMPs) may promote atherosclerotic plaque progression and rupture. However, results have been incongruous and the mechanisms of this remain obscured. Therefore, in the current study, carotid plaques were characterized by assessing the levels of MMPs and calcification factors, and evaluating their association with plaque vulnerability. Human carotid plaques were obtained from carotid endarterectomies, and classified into stable and vulnerable groups by ultrasonography and histological analyses. The mRNA and protein levels of MMPs, vascular endothelial growth factor (VEGF), bone sialoprotein 2 (BSP) and osteopontin were investigated by reverse transcription-quantitative polymerase chain reaction and western blotting, respectively. Immunohistochemistry was used to localize MMP-2 and MMP-14 in stable and vulnerable plaques. The activation of various associated signaling pathways was also investigated using western blotting. The mRNA levels of MMP-2, -7, -9 and -14 were elevated in vulnerable plaques, among which expression of MMP-2 and -14 were the highest. Consistent with the mRNA levels, the protein levels of MMP-2 and -14 were also elevated. Immunohistochemistry also demonstrated positive staining of MMP-2 and MMP-14 in vulnerable plaques. Factors that indicate neovascularization and calcification, including VEGF and BSP, were concurrently elevated in vulnerable plaques. In addition, the protein levels of extracellular regulated kinase (ERK) and protein kinase C (PKC) were upregulated in vulnerable plaques. The current study provides novel insights into the MMP profiles of vulnerability plaques, and may assist in the development of novel methods for the diagnosis of plaque vulnerability and the prevention of plaque rupture.

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Section: Discussionmentioning

confidence: 89%

Specific matrix metalloproteinases and calcification factors are associated with the vulnerability of human carotid plaque

et al. 2018

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Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy

Wang,

Pan,

Zhang

et al. 2024

Light Sci Appl

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Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for disease detection. Advances in digital pathology and developments in computer vision technology have led to the application of artificial intelligence (AI) in this field. Despite these advancements, the variability in pathologists’ subjective interpretations of diagnostic criteria can lead to inconsistent outcomes. To meet the need for precision in cancer therapies, there is an increasing demand for accurate pathological diagnoses. Consequently, traditional diagnostic pathology is evolving towards “next-generation diagnostic pathology”, prioritizing on the development of a multi-dimensional, intelligent diagnostic approach. Using nonlinear optical effects arising from the interaction of light with biological tissues, multiphoton microscopy (MPM) enables high-resolution label-free imaging of multiple intrinsic components across various human pathological tissues. AI-empowered MPM further improves the accuracy and efficiency of diagnosis, holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic criteria. In this review, we systematically outline the applications of MPM in pathological diagnosis across various human diseases, and summarize common multiphoton diagnostic features. Moreover, we examine the significant role of AI in enhancing multiphoton pathological diagnosis, including aspects such as image preprocessing, refined differential diagnosis, and the prognostication of outcomes. We also discuss the challenges and perspectives faced by the integration of MPM and AI, encompassing equipment, datasets, analytical models, and integration into the existing clinical pathways. Finally, the review explores the synergy between AI and label-free MPM to forge novel diagnostic frameworks, aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems in clinical settings.

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Optical Biopsy for Prostate Cancer Diagnosis Using Fluorescence Spectroscopy

Gao

Smith

2018

Int. J. Hi. Spe. Ele. Syst.

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Native fluorescence spectra are acquired from fresh normal and cancerous human prostate tissues. The fluorescence data are analyzed using an unsupervised machine learning algorithm such as non-negative matrix factorization. The nonnegative spectral components are retrieved and attributed to the native fluorophores such as collagen, reduced nicotinamide adenine dinucleotide (NADH), and flavin adenine dinucleotide (FAD) in tissue. The retrieved scores of the components are used to estimate the relative concentrations of the native fluorophores such as NADH and FAD and the redox ratio. A supervised machine learning algorithm such as support vector machine (SVM) is used to classify normal and cancerous tissue samples based on either the relative concentrations of NADH and FAD or the redox ratio alone. Various statistical measures such as sensitivity, specificity, and accuracy, along with the area under receiver operating characteristic (ROC) curve are used to show the classification performance. A cross validation method such as leave-one-out is used to further evaluate the predictive performance of the SVM classifier to avoid bias due to overfitting, and the accuracy was found to be 93.3%.

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A component‐by‐component characterisation of high‐risk atherosclerotic plaques by multiphoton microscopic imaging

Cited by 4 publications

References 24 publications

Specific matrix metalloproteinases and calcification factors are associated with the vulnerability of human carotid plaque

Specific matrix metalloproteinases and calcification factors are associated with the vulnerability of human carotid plaque

Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy

Optical Biopsy for Prostate Cancer Diagnosis Using Fluorescence Spectroscopy

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