scholarly journals Deep learning reveals 3D atherosclerotic plaque distribution and composition

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Vanessa Isabell Jurtz ◽  
Grethe Skovbjerg ◽  
Casper Gravesen Salinas ◽  
Urmas Roostalu ◽  
Louise Pedersen ◽  
...  
Keyword(s):  
Deep Learning ◽  
Atherosclerotic Plaque ◽  
Immune Cell ◽  
Ex Vivo ◽  
Light Sheet ◽  
Plaque Burden ◽  
Plaque Composition ◽  
Disease Trajectory ◽  
Non Destructive ◽  
Light Sheet Fluorescence Microscopy

AbstractComplications of atherosclerosis are the leading cause of morbidity and mortality worldwide. Various genetically modified mouse models are used to investigate disease trajectory with classical histology, currently the preferred methodology to elucidate plaque composition. Here, we show the strength of light-sheet fluorescence microscopy combined with deep learning image analysis for characterising and quantifying plaque burden and composition in whole aorta specimens. 3D imaging is a non-destructive method that requires minimal ex vivo handling and can be up-scaled to large sample sizes. Combined with deep learning, atherosclerotic plaque in mice can be identified without any ex vivo staining due to the autofluorescent nature of the tissue. The aorta and its branches can subsequently be segmented to determine how anatomical position affects plaque composition and progression. Here, we find the highest plaque accumulation in the aortic arch and brachiocephalic artery. Simultaneously, aortas can be stained for markers of interest (for example the pan immune cell marker CD45) and quantified. In ApoE−/− mice we observe that levels of CD45 reach a plateau after which increases in plaque volume no longer correlate to immune cell infiltration. All underlying code is made publicly available to ease adaption of the method.

Abstract 1985: Increased Plaque Mass, but not Relative Plaque Composition, Distinguishes Culprit Coronary Artery Lesions in Patients with Acute Coronary Syndrome: A Lesion Analysis by Intravascular Ultrasound Histology

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Andrew Frutkin ◽  
Sameer K Mehta ◽  
Justin R McCrary ◽  
John House ◽  
Steven P Marso
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Intravascular Ultrasound ◽  
Atherosclerotic Plaque ◽  
Obstructive Coronary Artery Disease ◽  
Plaque Burden ◽  
Lumen Area ◽  
Coronary Artery Lesions ◽  
Plaque Composition ◽  
Artery Disease

INTRODUCTION Intravascular ultrasound Virtual Histology (IVUS-VH) uses radiofrequency analysis to measure coronary artery plaque geometry and classify plaque components into one of four categories: fibrous, fibrofatty, necrotic or calcified. We hypothesized that patients with acute coronary artery syndrome (ACS) would have atherosclerotic plaque geometry and composition that differs from patients with stable, obstructive coronary artery disease. METHODS In a crossectional study we used IVUS-VH to image 38 culprit lesions of 28 ACS patients and 104 lesions of 71 non-ACS patients prior to intervention. In both ACS and non-ACS patients, culprit lesions were defined as the site of percutaneous coronary intervention with at least 3 contiguous frames of > 40% percent plaque burden (100 × [external elastic membrane (EEM ) area − lumen area]/EEM area ) and a neointimal thickness > 600 um subtending an arc of > 10% vessel circumference. Plaque geometry and composition were measured with IVUS-VH software (pcVH v.2.2, Volcano Corp). A remodeling index was calculated as the ratio of the EEM area at the frame of the minimal lumen area to the EEM area of a reference frame (within 10 mm of MLA). RESULTS Lesions of ACS patients were longer and had greater plaque volume than non-ACS patients (Table ). The proportions of IVUS-derived plaque components were similar in both ACS and non-ACS culprit lesions (Table ). CONCLUSION Culprit coronary artery lesions in ACS patients have greater plaque mass than in non-ACS patients, but relative plaque composition is similar between these patient populations. Measurements of atherosclerotic plaque mass may discriminate better than plaque composition as to which patients with severe, obstructive coronary artery disease are at greatest risk of coronary artery thrombosis. Longitudinal studies using IVUS-VH will best resolve which IVUS-VH measurements of plaque geometry and composition have greatest predictive value.

scholarly journals Mutation of the Cell Cycle Regulator p27kip1 Drives Pseudohypoxic Pheochromocytoma Development

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 126
Author(s):  
Hermine Mohr ◽  
Simone Ballke ◽  
Nicole Bechmann ◽  
Sebastian Gulde ◽  
Jaber Malekzadeh-Najafabadi ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Ex Vivo ◽  
Light Sheet ◽  
Epigenetic Mark ◽  
Angiogenic Potential ◽  
Optoacoustic Tomography ◽  
Oncogenic Pathways ◽  
Aggressive Tumors ◽  
Light Sheet Fluorescence Microscopy

Background: Pseudohypoxic tumors activate pro-oncogenic pathways typically associated with severe hypoxia even when sufficient oxygen is present, leading to highly aggressive tumors. Prime examples are pseudohypoxic pheochromocytomas and paragangliomas (p-PPGLs), neuroendendocrine tumors currently lacking effective therapy. Previous attempts to generate mouse models for p-PPGLs all failed. Here, we describe that the rat MENX line, carrying a Cdkn1b (p27) frameshift-mutation, spontaneously develops pseudohypoxic pheochromocytoma (p-PCC). Methods: We compared rat p-PCCs with their cognate human tumors at different levels: histology, immunohistochemistry, catecholamine profiling, electron microscopy, transcriptome and metabolome. The vessel architecture and angiogenic potential of pheochromocytomas (PCCs) was analyzed by light-sheet fluorescence microscopy ex vivo and multi-spectral optoacoustic tomography (MSOT) in vivo. Results: The analysis of tissues at various stages, from hyperplasia to advanced grades, allowed us to correlate tumor characteristics with progression. Pathological changes affecting the mitochrondrial ultrastructure where present already in hyperplasias. Rat PCCs secreted high levels of norepinephrine and dopamine. Transcriptomic and metabolomic analysis revealed changes in oxidative phosphorylation that aggravated over time, leading to an accumulation of the oncometabolite 2-hydroxyglutarate, and to hypermethylation, evident by the loss of the epigenetic mark 5-hmC. While rat PCC xenografts showed high oxygenation, induced by massive neoangiogenesis, rat primary PCC transcriptomes possessed a pseudohypoxic signature of high Hif2a, Vegfa, and low Pnmt expression, thereby clustering with human p-PPGL. Conclusion: Endogenous rat PCCs recapitulate key phenotypic features of human p-PPGLs. Thus, MENX rats emerge as the best available animal model of these aggressive tumors. Our study provides evidence of a link between cell cycle dysregulation and pseudohypoxia.

Imaging Enhancement of Light-Sheet Fluorescence Microscopy via Deep Learning

2019 ◽  
Vol 31 (22) ◽  
pp. 1803-1806 ◽  
Author(s):  
Chen Bai ◽  
Chao Liu ◽  
Xianghua Yu ◽  
Tong Peng ◽  
Junwei Min ◽  
...  
Keyword(s):  
Deep Learning ◽  
Fluorescence Microscopy ◽  
Light Sheet ◽  
Light Sheet Fluorescence Microscopy

scholarly journals 3D light sheet fluorescence microscopy of lungs to dissect local host immune -Aspergillus fumigatusinteractions

2019 ◽  
Author(s):  
Jorge Amich ◽  
Zeinab Mokhtari ◽  
Marlene Strobel ◽  
Elena Vialetto ◽  
Natarajaswamy Kalleda ◽  
...  
Keyword(s):  
Animal Models ◽  
Fluorescence Microscopy ◽  
Immune Cell ◽  
Invasive Pulmonary Aspergillosis ◽  
Fungal Growth ◽  
Light Sheet ◽  
Murine Models ◽  
Pulmonary Aspergillosis ◽  
Local Host ◽  
Light Sheet Fluorescence Microscopy

ABSTRACTAspergillus fumigatusis an opportunistic fungal pathogen that can cause life-threatening invasive lung infections in immunodeficient patients. The cellular and molecular processes of infection during onset, establishment and progression are highly complex and depend on both fungal attributes and the immune status of the host. Therefore, preclinical animal models are paramount to investigate and gain better insight into the infection process. Yet, despite their extensive use, commonly employed murine models of invasive pulmonary aspergillosis are not well understood due to analytical limitations. Here we present quantitative light sheet fluorescence microscopy (LSFM) to describe fungal growth and the local immune response in whole lungs at cellular resolution within its anatomical context. We analyzed three very common murine models of pulmonary aspergillosis based on immunosuppression with corticosteroids, chemotherapy-induced leukopenia or myeloablative irradiation. LSFM uncovered distinct architectures of fungal growth and degrees of tissue invasion in each model. Furthermore, LSFM revealed the spatial distribution, interaction and activation of two key immune cell populations in antifungal defense: alveolar macrophages and polymorphonuclear neutrophils. Interestingly, the patterns of fungal growth correlated with the detected effects of the immunosuppressive regimens on the local immune cell populations. Moreover, LSFM demonstrates that the commonly used intranasal route of spore administration did not result in the desired intra-alveolar deposition, as more than 60% of fungal growth occurred outside of the alveolar space. Hence, LSFM allows for more rigorous characterization of murine models of invasive pulmonary aspergillosis and pinpointing their strengths and limitations.IMPORTANCEThe use of animal models of infection is essential to advance our understanding of complex host-pathogen interactions that take place duringAspergillus fumigatuslung infections. As in the case of humans, mice need to be immunosuppressed to become susceptible to invasive pulmonary aspergillosis, the most serious infection caused byA. fumigatus. There are several immunosuppressive regimens that are routinely used to investigate fungal growth and/or immune responses in murine models of invasive pulmonary aspergillosis (IPA). However, the precise consequences that each immunosuppressive model has on the local immune populations and for fungal growth are not completely understood. Here we employed light sheet fluorescence microscopy (LSFM) to analyze whole lungs at cellular resolution, to pin down the scenario commonly used IPA models. Our results will be valuable to optimize and refine animal models to maximize their use in future research.VISUAL ABSTRACTQuantitative light sheet fluorescence microscopy to dissect local host-pathogen interactions in the lung afterA. fumigatusairway infection.

scholarly journals Epicardial Adipose Tissue Volume Is Associated with High Risk Plaque Profiles in Suspect CAD Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Dongkai Shan ◽  
Guanhua Dou ◽  
Junjie Yang ◽  
Xi Wang ◽  
Jingjing Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Artery ◽  
High Risk ◽  
Atherosclerotic Plaque ◽  
Plaque Burden ◽  
Multivariable Logistic Regression Analysis ◽  
Plaque Composition ◽  
Coronary Syndrome ◽  
Risk Predictor ◽  
Noncalcified Plaque

Objective. To explore the association between EAT volume and plaque precise composition and high risk plaque detected by coronary computed tomography angiography (CCTA). Methods. 101 patients with suspected coronary artery disease (CAD) underwent CCTA examination from March to July 2019 were enrolled, including 70 cases acute coronary syndrome (ACS) and 31 cases stable angina pectoris (SAP). Based on CCTA image, atherosclerotic plaque precise compositions were analyzed using dedicated quantitative software. High risk plaque was defined as plaque with more than 2 high risk features (spotty calcium, positive remolding, low attenuation plaque, napkin-ring sign) on CCTA image. The association between EAT volume and plaque composition was assessed as well as the different of correlation between ACS and SAP was analyzed. Multivariable logistic regression analysis was used to explore whether EAT volume was independent risk factors of high risk plaque (HRP). Results. EAT volume in the ACS group was significantly higher than that of the SAP group ( 143.7 ± 49.8  cm3 vs. 123.3 ± 39.2  cm3, P = 0.046 ). EAT volume demonstrated a significant positive correlation with total plaque burden ( r = 0.298 , P = 0.003 ), noncalcified plaque burden ( r = 0.245 , P = 0.013 ), lipid plaque burden ( r = 0.250 , P = 0.012 ), and homocysteine ( r = 0.413 , P ≤ 0.001 ). In ACS, EAT volume was positively correlated with total plaque burden ( r = 0.309 , P = 0.009 ), noncalcified plaque burden ( r = 0.242 , P = 0.044 ), and lipid plaque burden ( r = 0.240 , P = 0.045 ); however, no correlation was observed in SAP. Patients with HRP have larger EAT volume than those without HRP ( 169 ± 6.2  cm3 vs. 130.6 ± 5.3  cm3, P = 0.002 ). After adjustment by traditional risk factors and coronary artery calcium score (CACS), EAT volume was an independent risk predictor of presence of HRP (OR: 1.018 (95% CI: 1.006-1.030), P = 0.004 ). Conclusions. With the increasing EAT volume, more dangerous plaque composition burdens increase significantly. EAT volume is a risk predictor of HRP independent of convention cardiovascular risk factors and CACS, which supports the potential impact of EAT on progression of coronary atherosclerotic plaque.

scholarly journals Innovations in ex vivo Light Sheet Fluorescence Microscopy

2021 ◽  
Author(s):  
Pablo Delgado-Rodriguez ◽  
Claire Jordan Brooks ◽  
Juan José Vaquero ◽  
Arrate Munoz-Barrutia
Keyword(s):  
Fluorescence Microscopy ◽  
Ex Vivo ◽  
Light Sheet ◽  
Light Sheet Fluorescence Microscopy
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