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Computer tomography-based assessment of perivascular adipose tissue in patients with abdominal aortic aneurysms.

ABSTRACT: This retrospective study investigates perivascular adipose tissue (PVAT) alterations in CT as a marker of inflammation in patients with abdominal aortic aneurysms (AAA). 100 abdominal CT scans of patients with abdominal aortic aneurysms and 100 age and sex matched controls without underlying aortic disease were included. Artificial Intelligence (AI) assisted segmentation of the aorta and the surrounding adipose tissue was performed. Adipose tissue density was measured in Hounsfield units (HU) close (2-5mm, HU_close) and distant (10-12mm, HU_distant) to the aortic wall. To investigate alterations in adipose tissue density close to the aorta (HU_close) as a potential marker of inflammation, we calculated the difference HU_Δ = HU_close-HU_distant and the fat attenuation ratio HU_ratio = HU_close/HU_distant as normalized attenuation measures. These two markers were compared i) inter-individually between AAA patients and controls and ii) intra-individually between the aneurysmal and non-aneurysmal segments in AAA patients. Since most AAAs are generally observed infrarenal, the aneurysmal section of the AAA patients was compared with the infrarenal section of the aorta of the control patients. In inter-individual comparisons, higher HU_Δ and a lower HU_ratio were observed (aneurysmal: 8.9 ± 5.1 HU vs. control: 6.9 ± 4.8 HU, p-value = 0.006; aneurysmal: 89.8 ± 5.7% vs. control: 92.1 ± 5.5% p-value = 0.004). In intra-individual comparisons, higher HU_Δ and lower HU_ratio were observed (aneurysmal: 8.9 ± 5.1 HU vs. non-aneurysmal: 5.5 ± 4.1 HU, p-value < 0.001; aneurysmal: 89.8 ± 5.7% vs. non-aneurysmal 93.3 ± 4.9%, p-value < 0.001). The results indicate PVAT density alterations in AAA patients. This motivates further research to establish non-invasive imaging markers for vascular and perivascular inflammation in AAA.

SUBMITTER: Ginzburg D

PROVIDER: S-EPMC11372190 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature

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Computer tomography-based assessment of perivascular adipose tissue in patients with abdominal aortic aneurysms.

Ginzburg Daniel D Nowak Sebastian S Attenberger Ulrike U Luetkens Julian J Sprinkart Alois Martin AM Kuetting Daniel D

Scientific reports 20240903 1

This retrospective study investigates perivascular adipose tissue (PVAT) alterations in CT as a marker of inflammation in patients with abdominal aortic aneurysms (AAA). 100 abdominal CT scans of patients with abdominal aortic aneurysms and 100 age and sex matched controls without underlying aortic disease were included. Artificial Intelligence (AI) assisted segmentation of the aorta and the surrounding adipose tissue was performed. Adipose tissue density was measured in Hounsfield units (HU) cl ...[more]

PMID: 39227666

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Project description:ObjectiveRecent studies have highlighted the active and potential role of perivascular adipose tissue (PVAT) in atherosclerosis and aneurysm progression, respectively. This study explored the link between PVAT attenuation and abdominal aortic aneurysm (AAA) progression using computed tomography angiography (CTA).Materials and methodsThis multicenter retrospective study analyzed patients with AAA who underwent CTA at baseline and follow-up between March 2015 and July 2022. The following parameters were obtained: maximum diameter and total volume of the AAA, presence or absence of intraluminal thrombus (ILT), maximum diameter and volume of the ILT, and PVAT attenuation of the aortic aneurysm at baseline CTA. PVAT attenuation was divided into high (> -73.4 Hounsfield units [HU]) and low (≤ -73.4 HU). Patients who had or did not have AAA progression during the follow-up, defined as an increase in the aneurysm volume > 10 mL from baseline, were identified. Kaplan-Meier and multivariable Cox regression analyses were used to investigate the association between PVAT attenuation and AAA progression.ResultsOur study included 167 participants (148 males; median age: 70.0 years; interquartile range: 63.0-76.0 years), of which 145 (86.8%) were diagnosed with AAA accompanied by ILT. Over a median period of 11.3 months (range: 6.0-85.0 months), AAA progression was observed in 67 patients (40.1%). Multivariable Cox regression analysis indicated that high baseline PVAT attenuation (adjusted hazard ratio [aHR] = 2.23; 95% confidence interval [CI], 1.16-4.32; P = 0.017) was independently associated with AAA progression. This association was demonstrated within the patients of AAA with ILT subcohort, where a high baseline PVAT attenuation (aHR = 2.23; 95% CI, 1.08-4.60; P = 0.030) was consistently independently associated with AAA progression.ConclusionElevated PVAT attenuation is independently associated with AAA progression, including patients of AAA with ILT, suggesting the potential of PVAT attenuation as a predictive imaging marker for AAA expansion.

Project description:Purpose To assess periaortic adipose tissue attenuation at CT angiography in different abdominal aortic aneurysm disease states. Materials and Methods In a retrospective observational study from January 2018 to December 2022, periaortic adipose tissue attenuation was assessed at CT angiography in patients with asymptomatic or symptomatic (including rupture) abdominal aortic aneurysms and controls without aneurysms. Adipose tissue attenuation was measured using semiautomated software in periaortic aneurysmal and nonaneurysmal segments of the abdominal aorta and in subcutaneous and visceral adipose tissue. Periaortic adipose tissue attenuation values between the three groups were assessed using Student t tests and Wilcoxon rank sum tests followed by a multiregression model. Results Eighty-eight individuals (median age, 70 years [IQR, 65-78]; 78 male and 10 female patients) were included: 70 patients with abdominal aortic aneurysms (40 asymptomatic and 30 symptomatic, including 24 with rupture) and 18 controls. There was no evidence of differences in the periaortic adipose tissue attenuation in the aneurysmal segment in asymptomatic patients versus controls (-81.44 HU ± 7 [SD] vs -83.27 HU ± 9; P = .43) and attenuation in nonaneurysmal segments between asymptomatic patients versus controls (-75.43 HU ± 8 vs -78.81 HU ± 6; P = .08). However, symptomatic patients demonstrated higher periaortic adipose tissue attenuation in both aneurysmal (-57.85 HU ± 7; P < .0001) and nonaneurysmal segments (-58.16 HU ± 8; P < .0001) when compared with the other two groups. Conclusion Periaortic adipose tissue CT attenuation was not increased in stable abdominal aortic aneurysm disease. There was a generalized increase in attenuation in patients with symptomatic disease, likely reflecting the systemic consequences of acute rupture. Keywords: Abdominal Aortic Aneurysm, Periaortic Adipose Tissue Attenuation, CT Angiography ClinicalTrials.gov registration no. NCT02229006 © RSNA, 2024.

Project description:ObjectivesThe study aimed to investigate the relationship between the radiomic features of perivascular adipose tissue (PVAT) and abdominal aortic aneurysm (AAA) growth after endovascular aneurysm repair (EVAR).MethodsPatients with sub-renal AAA who underwent regular follow-up after EVAR between March 2014 and March 2024 were retrospectively collected. Two radiologists segmented aneurysms and PVAT. Patients were categorised into growing and non-growing groups based on volumetric changes observed in two follow-up computed tomography examinations. One hundred seven radiomic features were automatically extracted from the PVAT region. Univariable and multivariable logistic regression was performed to analyse radiomic features and clinical characteristics. Furthermore, the performance of the integrated clinico-radiological model was compared with models using only radiomic features or clinical characteristics separately.ResultsA total of 79 patients (68 ± 9 years, 89% men) were enroled in this study, 19 of whom had a growing aneurysm. Compared to the non-growing group, PVAT of growing AAA showed a higher surface area to volume ratio (non-growing vs growing, 0.63 vs 0.70, p = 0.04), and a trend of low dependence and high dispersion manifested by texture features (p < 0.05). The area under the curve of the integrated clinico-radiological model was 0.78 (95% confidence intervals 0.65-0.91), with a specificity of 87%. The integrated model outperformed models using only radiomic or clinical features separately (0.78 vs 0.69 vs 0.69).ConclusionsHigher surface area to volume ratio and more heterogeneous texture presentation of PVAT were associated with aneurysm dilation after EVAR. Radiomic features of PVAT have the potential to predict AAA progression.Clinical relevance statementRadiomic features of PVAT are associated with AAA progression and can be an independent risk factor for aneurysm dilatation to assist clinicians in postoperative patient surveillance and management.Key pointsAfter EVAR for AAA, patients require monitoring for progression. PVAT surrounding growing AAA after EVAR exhibits a more heterogeneous texture. Integrating PVAT-related features and clinical features results in better predictive performance.

Project description:Objective: Abdominal aortic aneurysm (AAA) refers to unusual permanent dilation of the abdominal aorta, and gradual AAA expansion can lead to fatal rupture. However, we lack clear understanding of the pathogenesis of this disease. The effect of perivascular adipose tissue (PVAT) on vascular functional status has attracted increasing attention. Here, we try to identify the potential mechanisms linking AAA and PVAT. Methods: We downloaded dataset GSE119717, including 30 dilated AAA PVAT samples and 30 non-dilated aorta PVAT samples from AAA cases, from Gene Expression Omnibus to identify differentially expressed genes (DEGs). We performed pathway enrichment analysis by Metascape, ClueGo and DAVID to annotate PVAT functional status according to the DEGs. A protein-protein interaction network, the support vector machine (SVM)-recursive feature elimination and the least absolute shrinkage and selection operator regression model were constructed to identify feature genes. Immune infiltration analysis was explored by CIBERSORT. And the correlation between feature gene and immune cells was also calculated. Finally, we used the angiotensin II (Ang II)-ApoE-/- mouse model of AAA to verify the effect of feature gene expression by confirming protein expression using immunohistochemistry and western blot. Results: We identified 22 DEGs, including 21 upregulated genes and 1 downregulated gene. The DEGs were mainly enriched in neutrophil chemotaxis and IL-17 signaling pathway. FOS was identified as a good diagnostic feature gene (AUC = 0.964). Immune infiltration analysis showed a higher level of T cells follicular helper, activated NK cells, Monocytes, activated Mast cells in AAA group. And FOS was correlated with immune cells. Immunohistochemistry and western blot confirmed higher FOS expression in PVAT of the AAA mouse model compared to control group. Conclusion: The differentially expressed genes and pathways identified in this study provide further understanding of how PVAT affects AAA development. FOS was identified as the diagnostic gene. There was an obvious difference in immune cells infiltration between normal and AAA groups.

Project description:BackgroundWith a mortality rate of 65-85%, a ruptured abdominal aortic aneurysm (AAA) can have catastrophic consequences for patients. However, few effective pharmaceutical treatments are available to treat this condition. Therefore, elucidating the pathogenesis of AAA and finding the potential molecular targets for medical therapies are vital lines of research.MethodsAn mRNA microarray dataset of perivascular adipose tissue (PVAT) in AAA patients was downloaded and differentially expressed gene (DEG) screening was performed. Weighted gene co-expression networks for dilated and non-dilated PVAT samples were constructed via weighted correlation network analysis (WGCNA) and used to detect gene modules. Functional annotation analysis was performed for the DEGs and gene modules. We identified the hub genes of the modules and created a DEG co-expression network. We then mined crucial genes based on this network using Molecular Complex Detection (MCODE) in Cytoscape. Crucial genes with top-6 degree in the crucial gene cluster were visualized, and their potential clinical significance was determined.ResultsOf the 173 DEGs screened, 99 were upregulated and 74 were downregulated. Co-expression networks were built and we detected 6 and 5 modules for dilated and non-dilated PVAT samples, respectively. The turquoise and black modules for dilated PVAT samples were related to inflammation and immune response. MAP4K1 and PROK2 were the hub genes of these 2 modules, respectively. Then a DEG co-expression network with 112 nodes and 953 edges was created. PLAU was the crucial gene with the highest connectivity and showed potential clinical significance.ConclusionsUsing WGCNA, gene modules were detected and hub genes and crucial genes were identified. These crucial genes might be potential targets for pharmaceutic therapies and have potential clinical significance. Future in vitro and in vivo experiments are required to more comprehensively explore the biological mechanisms by which these genes affect AAA pathogenesis.

Project description:Background: Perivascular adipose tissue (PVAT) is a key regulator of vascular dysfunction. Impairment of PVAT phenotypic plasticity with aging may play a role in vascular pathology including abdominal aortic aneurysms (AAA). Yet, the mechanisms underlying PVAT plasticity in aneurysm pathogenesis remain elusive. Methods: Single-cell RNA sequencing (scRNA-seq) was performed on perivascular stromal cells (PVSCs) from young (2-3-month-old) and aged (18-20-month-old) mice. The expression of peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α) was measured in PVAT of aged mice and human aneurysm samples. Loss- and gain-of-function approaches were employed to investigate the role of SM22α-lineage PVSCs-derived PGC-1α in aneurysm development. Molecular mechanisms were explored through transcriptome and functional studies in young and aged mice, SM22αCre; Rosa26RFP/+; PGC1αf/f and SM22αCre; Rosa26RFP/+ mice with angiotensin II (AngII)- and DOCA/salt- induced AAA models. Results: SM22α+ cells accumulated in PVAT of angiotensin II-treated aged mice and patients with aortic aneurysms. scRNA-seq analysis revealed that aging disrupted the differentiation potential of SM22α-lineage PVSCs and led to reduced PGC-1α level. PGC1α downregulation in PVAT was observed in both mice AAA models and human aneurysm lesions. In mice with SM22α-driven PGC-1α-deletion AngII induced AAA formation was accompanied by PVSC-to-myofibroblast differentiation. in vitro PGC1α-knockdown suppressed nuclear YAP signaling, reducing adipocyte differentiation, while increasing MMP2-secreting myofibroblasts. Furthermore, PGC-1α overexpression in aged mice or administration of the YAP signaling inhibitor Verteporfin in SM22αCre; Rosa26RFP/+; PGC1αf/f mice restored PVAT function and conferred protection against aneurysm formation. Lastly, we employed the radiomics analysis to non-invasively evaluate PVAT in the context of AAA severity in humans. Conclusions: PGC-1α deficiency in SM22α-lineage stromal cells disrupts the balance between adipogenic and myofibrogenic differentiation through regulating the YAP signaling, ultimately promoting aneurysm development. Radiomics assessment may present a promising noninvasive approach for PVAT evaluation in aneurysms, offering valuable potential for clinical research.

Dataset Information

Computer tomography-based assessment of perivascular adipose tissue in patients with abdominal aortic aneurysms.

Publications

Computer tomography-based assessment of perivascular adipose tissue in patients with abdominal aortic aneurysms.

Similar Datasets

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