Through our partnerships with cardiovascular specialists across disciplines and our technologically advanced facilities, the University of Michigan Section of Vascular Surgery is uniquely equipped to treat difficult and complex cases, and to translate new treatments and approaches from the lab to the bedside.
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We provide comprehensive clinical care for vascular disease, seeing more than 12,000 clinic visits a year and performing more than 1,200 operations and procedures. We’re committed to delivering collaborative medicine across specialties, giving patients a single home for their care. Our clinical strengths include multidisciplinary clinical programs for aortic disease, venous disease, pediatric renovascular hypertension, and peripheral arterial disease. We’re also experts in EVAR, FEVAR, TEVAR, and TRIVEX.
Michigan is home to one of the first integrated vascular surgery residency programs in the country, offering a mature and comprehensive program to trainees seeking an experience that combines the best of academic medicine — including extensive experience in open and endovascular surgery cases and protected time for research and academic development. Our 2-year vascular surgery fellowship program prepares graduates to lead clinical and research efforts upon graduation, providing opportunities to fine-tune surgical expertise while developing as investigators during a research rotation.
With a depth of expertise, our research portfolio stands as one of the largest and most diverse for any unit of our kind. Our endowed vascular surgery research facility, the Computational Vascular Biomechanics Laboratory and the 4,900-square-foot Conrad Jobst Laboratories, unites faculty investigators from across the section in a central hub that accelerates discovery through collaboration. The Jobst Labs focus on venous thrombosis, vascular inflammation, thrombus resolution, traumatic injury, nephropathy, abdominal aneurysms, and medical device testing. Our multidisciplinary vascular biomechanics team works to compute hemodynamics in complex image-based cardiovascular models to assess surgical approaches.