Vascular access dysfunction is one of the main causes of morbidity and hospitalization in hemodialysis patients. This major clinical problem points out the need for prediction of hemodynamic changes induced by vascular access surgery. Here we reviewed the potential of a patient-specific computational vascular network model that includes vessel wall remodeling to predict blood flow change within 6 weeks after surgery for different arteriovenous fistula configurations. For model validation, we performed a multicenter, prospective clinical study to collect longitudinal data on arm vasculature before and after surgery. Sixty-three patients with newly created arteriovenous fistula were included in the validation data set and divided into four groups based on fistula configuration. Predicted brachial artery blood flow volumes 40 days after surgery had a significantly high correlation with measured values. Deviation of predicted from measured brachial artery blood flow averaged 3% with a root mean squared error of 19.5%, showing that the computational tool reliably predicted patient-specific blood flow increase resulting from vascular access surgery and subsequent vascular adaptation. This innovative approach may help the surgeon to plan the most appropriate fistula configuration to optimize access blood flow for hemodialysis, potentially reducing the incidence of vascular access dysfunctions and the need of patient hospitalization.

Validation of a patient-specific hemodynamic computational model for surgical planning of vascular access in hemodialysis patients / A. Caroli, S. Manini, L. Antiga, K. Passera, B. Ene-Iordache, S. Rota, G. Remuzzi, A. Bode, J. Leermakers, F.N. Van De Vosse, R. Vanholder, M. Malovrh, J. Tordoir, A. Remuzzi, ARCH project Consortium. - In: KIDNEY INTERNATIONAL. - ISSN 0085-2538. - 84:6(2013 Dec), pp. 1237-1245.

Validation of a patient-specific hemodynamic computational model for surgical planning of vascular access in hemodialysis patients

S. Rota;G. Remuzzi;
2013

Abstract

Vascular access dysfunction is one of the main causes of morbidity and hospitalization in hemodialysis patients. This major clinical problem points out the need for prediction of hemodynamic changes induced by vascular access surgery. Here we reviewed the potential of a patient-specific computational vascular network model that includes vessel wall remodeling to predict blood flow change within 6 weeks after surgery for different arteriovenous fistula configurations. For model validation, we performed a multicenter, prospective clinical study to collect longitudinal data on arm vasculature before and after surgery. Sixty-three patients with newly created arteriovenous fistula were included in the validation data set and divided into four groups based on fistula configuration. Predicted brachial artery blood flow volumes 40 days after surgery had a significantly high correlation with measured values. Deviation of predicted from measured brachial artery blood flow averaged 3% with a root mean squared error of 19.5%, showing that the computational tool reliably predicted patient-specific blood flow increase resulting from vascular access surgery and subsequent vascular adaptation. This innovative approach may help the surgeon to plan the most appropriate fistula configuration to optimize access blood flow for hemodialysis, potentially reducing the incidence of vascular access dysfunctions and the need of patient hospitalization.
access blood flow; hemodialysis access; vascular access; Adult; Aged; Aged, 80 and over; Blood Flow Velocity; Europe; Female; Graft Occlusion, Vascular; Humans; Longitudinal Studies; Male; Middle Aged; Patient Selection; Prospective Studies; Regional Blood Flow; Reproducibility of Results; Time Factors; Treatment Outcome; Upper Extremity; Vascular Patency; Young Adult; Arteriovenous Shunt, Surgical; Computer Simulation; Decision Support Techniques; Hemodynamics; Models, Cardiovascular; Renal Dialysis; Surgery, Computer-Assisted; Nephrology
Settore MED/14 - Nefrologia
dic-2013
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/329685
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