Peripheral arterial disease treatment planning using noninvasive and invasive imaging methods

Csore, Judit; Drake, Madeline; Roy, Trisha L.

doi:10.1016/j.jvscit.2023.101263

Cited by 5 publications

(2 citation statements)

References 65 publications

(81 reference statements)

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“…In Europe, specifically in countries like the Netherlands, the cost per PAD patient is about EUR 17 thousand [ 33 ], while in Germany, the total cost of early endovascular intervention is approximately EUR 24 thousand per patient over 5 years [ 34 ]. Despite advances in diagnostic imaging, including magnetic resonance angiography, intravascular ultrasound, and optical coherence tomography [ 35 ], the PAD/CLI scenario is still unfavorable for many patients, and there is a real need for novel therapeutic approaches that can treat this critical unmet medical need. Thus, the present study reveals the c-Kit signaling pathway in endothelial cells as a potential therapeutic target for future treatments in PAD/CLI.…”

Section: Discussionmentioning

confidence: 99%

Loss of c-Kit in Endothelial Cells Protects against Hindlimb Ischemia

Falero-Diaz,

Barboza,

Vazquez-Padron

et al. 2024

Biomedicines

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Background: Critical limb ischemia (CLI) is the end stage of peripheral artery disease (PAD), and around 30% of CLI patients are ineligible for current treatments. The angiogenic benefits of c-Kit have been reported in the ischemia scenario; however, the present study demonstrates the effects of specific endothelial c-Kit signaling in arteriogenesis during hindlimb ischemia. Methods: We created conditional knockout mouse models that decrease c-Kit (c-Kit VE-Cadherin CreERT2—c-Kit) or its ligand (SCF VE-Cadherin CreERT2—SCF) specifically in endothelial cells (ECs) after tamoxifen treatment. These mice and a control group (wild-type VE-Cadherin CreERT2—WT) were subjected to hindlimb ischemia or aortic crush to evaluate perfusion/arteriogenesis and endothelial barrier permeability, respectively. Results: Our data confirmed the lower gene expression of c-Kit and SCF in the ECs of c-Kit and SCF mice, respectively. In addition, we confirmed the lower percentage of ECs positive for c-Kit in c-Kit mice. Further, we found that c-Kit and SCF mice had better limb perfusion and arteriogenesis compared to WT mice. We also demonstrated that c-Kit and SCF mice had a preserved endothelial barrier after aortic crush compared to WT. Conclusions: Our data demonstrate the deleterious effects of endothelial SCF/c-Kit signaling on arteriogenesis and endothelial barrier integrity.

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Section: Discussionmentioning

confidence: 99%

Loss of c-Kit in Endothelial Cells Protects against Hindlimb Ischemia

Falero-Diaz,

Barboza,

Vazquez-Padron

et al. 2024

Biomedicines

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“…They are associated with abnormalities in blood vessel lumen geometry, such as stenoses caused by pathological deposition of atherosterotic plaque inside the vessel [2]. The diagnosis and treatment of vascular diseases requires accurate lumen geometry quantification, in a non-invasive way where possible [3]. Three-dimensional imaging is the main technique used to acquire quantitative information about the vasculature [4].…”

Section: Introductionmentioning

confidence: 99%

Using Deep Learning and B-Splines to Model Blood Vessel Lumen from 3D Images

Materka,

Jurek

2024

Sensors

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Accurate geometric modeling of blood vessel lumen from 3D images is crucial for vessel quantification as part of the diagnosis, treatment, and monitoring of vascular diseases. Our method, unlike other approaches which assume a circular or elliptical vessel cross-section, employs parametric B-splines combined with image formation system equations to accurately localize the highly curved lumen boundaries. This approach avoids the need for image segmentation, which may reduce the localization accuracy due to spatial discretization. We demonstrate that the model parameters can be reliably identified by a feedforward neural network which, driven by the cross-section images, predicts the parameter values many times faster than a reference least-squares (LS) model fitting algorithm. We present and discuss two example applications, modeling the lower extremities of artery–vein complexes visualized in steady-state contrast-enhanced magnetic resonance images (MRI) and the coronary arteries pictured in computed tomography angiograms (CTA). Beyond applications in medical diagnosis, blood-flow simulation and vessel-phantom design, the method can serve as a tool for automated annotation of image datasets to train machine-learning algorithms.

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