JVS-vascular science最新文献

Objectives

The aim of this study was to analyze a series of new generations of explanted knitted polyethylene terephthalate (PET) vascular grafts (VGs) presenting nonanastomotic degradations according to preoperative computed tomography angiography (CTA) when available in order to better understand the mechanisms leading to rupture.

Methods

Explanted knitted PET VGs were collected as part of the Geprovas European Collaborative Retrieval Program. VGs implanted after 1990 presenting a nonanastomotic rupture of the fabric were included. Clinical data and pre-explantation CTA data when available were retrieved for each VG. The ruptures were characterized by macroscopic examination and optical microscopy according to a standardized protocol.

Results

Nineteen explants were collected across 11 European centers, 13 were implanted as infrainguinal bypasses, 3 at the aortic level, and 1 as an axillobifemoral bypass. The mean implantation duration was 9.2 years. Pre-explantation CTA data were available for 8 VGs and showed false aneurysms at the adductor canal level on 4 VGs, at the inguinal ligament level on 2 VGs, and in the proximal or middle third thigh level on 3 VGs. Examination revealed longitudinal ruptures on 9 explanted VGs (EVGs), transversal ruptures on 15 EVGs, 45°-oriented ruptures on 5 EVGs, V-shaped ruptures on 7 EVGs, and punctiform ruptures on 2 EVGs. Ruptures involved the remeshing line on 11 EVGs, the guideline on 10 EVGs, and the crimping valley on 15 EVGs.

At the microscopic level, two main degradation phenomena could be identified: a decrease in the density of the meshing and local ruptures of the PET fibers. Fourteen EVGs presented a loosening of the remeshing line and 17 EVGs an attenuation of the crimping.

Conclusions

New-generation PET VG degradation seems to result from both anatomic constraints and intrinsic textile structure phenomena.

Objective

To identify confounding variables influencing the accuracy of a convolutional neural network (CNN) specific for infrarenal abdominal aortic aneurysms (AAAs) on computed tomography angiograms (CTAs).

Methods

A Health Insurance Portability and Accountability Act-compliant, institutional review board-approved, retrospective study analyzed abdominopelvic CTA scans from 200 patients with infrarenal AAAs and 200 propensity-matched control patients. An AAA-specific trained CNN was developed by the application of transfer learning to the VGG-16 base model using model training, validation, and testing techniques. Model accuracy and area under the curve were analyzed based on data sets (selected, balanced, or unbalanced), aneurysm size, extra-abdominal extension, dissections, and mural thrombus. Misjudgments were analyzed by review of heatmaps, via gradient weighted class activation, overlaid on CTA images.

Results

The trained custom CNN model reported high test group accuracies of 94.1%, 99.1%, and 99.6% and area under the curve of 0.9900, 0.9998, and 0.9993 in selected (n = 120), balanced (n = 3704), and unbalanced image sets (n = 31,899), respectively. Despite an eightfold difference between balanced and unbalanced image sets, the CNN model demonstrated high test group sensitivities (98.7% vs 98.9%) and specificities (99.7% vs 99.3%) in unbalanced and balanced image sets, respectively. For aneurysm size, the CNN model demonstrates decreasing misjudgments as aneurysm size increases: 47% (16/34) for aneurysms <3.3 cm, 32% (11/34) for aneurysms 3.3 to 5 cm, and 20% (7/34) for aneurysms >5 cm. Aneurysms containing measurable mural thrombus were over-represented within type II (false-negative) misjudgments compared with type I (false-positive) misjudgments (71% vs 15%, P < .05). Inclusion of extra-abdominal aneurysm extension (thoracic or iliac artery) or dissection flaps in these imaging sets did not decrease the model's overall accuracy, indicating that the model performance was excellent without the need to clean the data set of confounding or comorbid diagnoses.

Conclusions

Analysis of an AAA-specific CNN model can accurately screen and identify infrarenal AAAs on CTA despite varying pathology and quantitative data sets. The highest anatomic misjudgments were with small aneurysms (<3.3 cm) or the presence of mural thrombus. Accuracy of the CNN model is maintained despite the inclusion of extra-abdominal pathology and imbalanced data sets.

Background

Peripheral arterial atheroprogression is increasingly prevalent, and is a risk factor for major limb amputations in individuals with risk factors such as diabetes. We previously demonstrated that bioactive lipids are significantly altered in arterial tissue of individuals with diabetes and advanced peripheral arterial disease.

Methods

Here we evaluated whether sphingolipid ceramide 18:1/16:0 (C16) is a cellular regulator in endothelial cells and peripheral tibial arterial tissue in individuals with diabetes.

Results

We observed that C16 is the single most elevated ceramide in peripheral arterial tissue from below the knee in individuals with diabetes (11% increase, P < .05). C16 content in tibial arterial tissue positively correlates with sphingomyelin (SPM) content in patients with and without diabetes (r² = 0.5, P < .005; r² = 0.17, P < .05; respectively). Tibial arteries of individuals with diabetes demonstrated no difference in CERS6 expression (encoding ceramide synthase 6; the predominate ceramide synthesis enzyme), but higher SMPD expression (encoding sphingomyelin phosphodiesterase that catalyzes ceramide synthesis from sphingomyelins; P < .05). SMPD4, but not SMPD2, was particularly elevated in maximally diseased (Max) tibial arterial segments (P < .05). In vitro, exogenous C16 caused endothelial cells (HUVECs) to have decreased proliferation (P < .03), increased apoptosis (P < .003), and decreased autophagy (P < .008). Selective knockdown of SMPD2 and SMPD4 decreased native production of C16 (P < .01 and P < .001, respectively), but only knockdown of SMPD4 rescued cellular proliferation (P < .005) following exogenous supplementation with C16.

Conclusions

Our findings suggest that C16 is a tissue biomarker for peripheral arterial disease severity in the setting of diabetes, and can impact endothelial cell viability and function.

Clinical relevance

Peripheral arterial disease and its end-stage manifestation known as chronic limb-threatening ischemia (CLTI) represent ongoing prevalent and intricate medical challenges. Individuals with diabetes have a heightened risk of developing CLTI and experiencing its complications, including wounds, ulcers, and major amputations. In the present study, we conducted a comprehensive examination of the molecular lipid composition within arterial segments from individuals with CLTI, and with and without diabetes. Our investigations unveiled a striking revelation: the sphingolipid ceramide 18:1/16:0 emerged as the predominant ceramide species that was significantly elevated in the peripheral arterial intima below the knee in patients with diabetes. Moreover, this heightened cera