Non-invasive Serial Monitoring of Atherosclerotic Plaque Progression and Thrombosis with PET-CT in a Rabbit Model

2013 ◽  
Vol 111 (7) ◽  
pp. 13B
Author(s):  
Zhang Ming Duo ◽  
Zhao Quan Ming
Keyword(s):  
Atherosclerotic Plaque ◽  
Rabbit Model ◽  
Plaque Progression ◽  
Non Invasive ◽  
Pet Ct

Rapid inhibition of atherosclerotic plaque progression by sonodynamic therapy

2018 ◽  
Vol 115 (1) ◽  
pp. 190-203 ◽  
Author(s):  
Xin Sun ◽  
Shuyuan Guo ◽  
Jianting Yao ◽  
Huan Wang ◽  
Chenghai Peng ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Standard Of Care ◽  
Atherosclerotic Plaques ◽  
Plaque Progression ◽  
Peripheral Artery ◽  
Sonodynamic Therapy ◽  
Non Invasive ◽  
Atherosclerotic Burden ◽  
Artery Disease ◽  
Apoe Deficient Mouse

Abstract Aims Currently, efficient regimens to reverse atherosclerotic plaques are not available in the clinic. Herein, we present sonodynamic therapy (SDT) as a novel methodology to rapidly inhibit progression of atherosclerotic plaques. Methods and results In atherosclerotic rabbit and apoE-deficient mouse models, SDT efficiently decreased the atherosclerotic burden within 1 week, revealing a decrease in the size of the atherosclerotic plaque and enlarged lumen. The shrunken atherosclerotic plaques displayed compositional alterations, with a reduction in lesional macrophages and lipids. The rapid efficacy of SDT may be due to its induction of macrophage apoptosis, enhancement of efferocytosis, and amelioration of inflammation in the atherosclerotic plaque. Compared with atorvastatin, the standard of care for atherosclerosis, SDT showed more significant plaque shrinkage and lumen enlargement during 1 week treatment. Furthermore, SDT displayed good safety without obvious side effects. In a pilot clinical trial recruiting the patients suffering atherosclerotic peripheral artery disease, combination therapy of SDT with atorvastatin efficiently reduced progression of atherosclerotic plaque within 4 weeks, and its efficacy was able to last for at least 40 weeks. Conclusion SDT is a non-invasive and efficacious regimen to inhibit atherosclerotic plaque progression.

scholarly journals Non-Invasive Prediction of Site-Specific Coronary Atherosclerotic Plaque Progression Using Lipidomics, Blood Flow, and LDL Transport Modeling

2021 ◽  
Vol 11 (5) ◽  
pp. 1976
Author(s):  
Antonis I. Sakellarios ◽  
Panagiota Tsompou ◽  
Vassiliki Kigka ◽  
Panagiotis Siogkas ◽  
Savvas Kyriakidis ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Blood Flow ◽  
Computational Modeling ◽  
Atherosclerotic Plaque ◽  
Plaque Progression ◽  
Fractional Flow ◽  
Site Specific ◽  
Ldl Transport ◽  
Non Invasive ◽  
Coronary Atherosclerotic Plaque

Background: coronary computed tomography angiography (CCTA) is a first line non-invasive imaging modality for detection of coronary atherosclerosis. Computational modeling with lipidomics analysis can be used for prediction of coronary atherosclerotic plaque progression. Methods: 187 patients (480 vessels) with stable coronary artery disease (CAD) undergoing CCTA scan at baseline and after 6.2 ± 1.4 years were selected from the SMARTool clinical study cohort (Clinicaltrial.gov Identifiers NCT04448691) according to a computed tomography (CT) scan image quality suitable for three-dimensional (3D) reconstruction of coronary arteries and the absence of implanted coronary stents. Clinical and biohumoral data were collected, and plasma lipidomics analysis was performed. Blood flow and low-density lipoprotein (LDL) transport were modeled using patient-specific data to estimate endothelial shear stress (ESS) and LDL accumulation based on a previously developed methodology. Additionally, non-invasive Fractional Flow Reserve (FFR) was calculated (SmartFFR). Plaque progression was defined as significant change of at least two of the morphological metrics: lumen area, plaque area, plaque burden. Results: a multi-parametric predictive model, including traditional risk factors, plasma lipids, 3D imaging parameters, and computational data demonstrated 88% accuracy to predict site-specific plaque progression, outperforming current computational models. Conclusions: Low ESS and LDL accumulation, estimated by computational modeling of CCTA imaging, can be used to predict site-specific progression of coronary atherosclerotic plaques.

scholarly journals P684Effects of colchicine on atherosclerotic plaque progression and composition: a multimodality imaging study in a rabbit model of atherosclerosis

2017 ◽  
Vol 38 (suppl_1) ◽  
Author(s):  
A. Cecconi ◽  
J.P. Vilchez Tschischke ◽  
J. Mateo ◽  
J. Sanchez-Gonzalez ◽  
B. Lopez-Melgar ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Multimodality Imaging ◽  
Rabbit Model ◽  
Imaging Study ◽  
Plaque Progression

scholarly journals Non-invasive imaging of atherosclerotic plaque macrophage in a rabbit model with F-18 FDG PET: a histopathological correlation

2006 ◽  
Vol 6 (1) ◽  
Author(s):  
Zhuangyu Zhang ◽  
Josef Machac ◽  
Gerard Helft ◽  
Stephen G Worthley ◽  
Cheuk Tang ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Fdg Pet ◽  
Rabbit Model ◽  
Non Invasive ◽  
Histopathological Correlation ◽  
Plaque Macrophage

scholarly journals Detection of Vulnerable Atherosclerotic Plaque and Prediction of Thrombosis Events in a Rabbit Model Using 18F-FDG -PET/CT

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e61140 ◽  
Author(s):  
Quan-ming Zhao ◽  
Xin Zhao ◽  
Ting-ting Feng ◽  
Ming-duo Zhang ◽  
Xu-cui Zhuang ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Fdg Pet ◽  
Rabbit Model ◽  
Vulnerable Atherosclerotic Plaque ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct

11C-metomidate PET-CT in primary aldosteronism: five possible indications for a non-invasive alternative to adrenal vein sampling

2015 ◽  
Author(s):  
Andrew S Powlson ◽  
Olympia Koulouri ◽  
Elena Azizan ◽  
Carmela Maniero ◽  
Kevin Taylor ◽  
...  
Keyword(s):  
Primary Aldosteronism ◽  
Adrenal Vein ◽  
Adrenal Vein Sampling ◽  
Non Invasive ◽  
Pet Ct

scholarly journals A [68Ga]Ga-DOTANOC PET/CT Radiomic Model for Non-Invasive Prediction of Tumour Grade in Pancreatic Neuroendocrine Tumours

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 870
Author(s):  
Alessandro Bevilacqua ◽  
Diletta Calabrò ◽  
Silvia Malavasi ◽  
Claudio Ricci ◽  
Riccardo Casadei ◽  
...  
Keyword(s):  
Neuroendocrine Tumour ◽  
Area Under The Curve ◽  
Tumour Volume ◽  
Assessment Method ◽  
Second Order ◽  
Tumour Grade ◽  
Non Invasive ◽  
Pet Ct ◽  
Median Test ◽  
Fdg Pet Ct

Predicting grade 1 (G1) and 2 (G2) primary pancreatic neuroendocrine tumour (panNET) is crucial to foresee panNET clinical behaviour. Fifty-one patients with G1-G2 primary panNET demonstrated by pre-surgical [68Ga]Ga-DOTANOC PET/CT and diagnostic conventional imaging were grouped according to the tumour grade assessment method: histology on the whole excised primary lesion (HS) or biopsy (BS). First-order and second-order radiomic features (RFs) were computed from SUV maps for the whole tumour volume on HS. The RFs showing the lowest p-values and the highest area under the curve (AUC) were selected. Three radiomic models were assessed: A (trained on HS, validated on BS), B (trained on BS, validated on HS), and C (using the cross-validation on the whole dataset). The second-order normalized homogeneity and entropy was the most effective RFs couple predicting G2 and G1. The best performance was achieved by model A (test AUC = 0.90, sensitivity = 0.88, specificity = 0.89), followed by model C (median test AUC = 0.87, sensitivity = 0.83, specificity = 0.82). Model B performed worse. Using HS to train a radiomic model leads to the best prediction, although a “hybrid” (HS+BS) population performs better than biopsy-only. The non-invasive prediction of panNET grading may be especially useful in lesions not amenable to biopsy while [68Ga]Ga-DOTANOC heterogeneity might recommend FDG PET/CT.

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