Near real-time estimation of blood loss and flow-pressure re-distribution during unilateral nephrectomy

Radical or partial nephrectomy, commonly used for the treatment of kidney tumors, is a surgical procedure with a risk of high blood loss. The primary aim of this study is to quantify blood loss and elucidate the redistribution of blood flux and pressure between the two kidneys and the abdominal aorta during renal resection. We have developed a robust research methodology that introduces a new lumped-parameter mathematical model, specifically focusing on the vasculature of both kidneys using a non-Newtonian Carreau fluid. This model, a first-order approximation, accounts for the variation in the total impedance of the vasculature when various vessels are severed in the diseased kidney (assumed to be the left in this work). The model offers near real-time estimations of the flow–pressure redistribution within the vascular network of the two kidneys and the downstream aorta for several radical or partial nephrectomy scenarios. Notably, our findings indicate that the downstream aorta receives an approximately 1.27 times higher percentage of the redistributed flow from the diseased kidney compared to that received by the healthy kidney, in nearly all examined cases. The implications of this study are significant, as they can inform the development of surgical protocols to minimize blood loss and can assist surgeons in evaluating the adequacy of the remaining kidney vasculature.

Publication Details

Journal
Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)
Published
2024-09-13
Primary Topic
Innovative Approaches in Technology and Social Development
Type
article
Field-Weighted Citation Impact
0.00

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article

Near real-time estimation of blood loss and flow-pressure re-distribution during unilateral nephrectomy

Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)
Innovative Approaches in Technology and Social Development
article

Near real-time estimation of blood loss and flow-pressure re-distribution during unilateral nephrectomy

article en

Abstract

Radical or partial nephrectomy, commonly used for the treatment of kidney tumors, is a surgical procedure with a risk of high blood loss. The primary aim of this study is to quantify blood loss and elucidate the redistribution of blood flux and pressure between the two kidneys and the abdominal aorta during renal resection. We have developed a robust research methodology that introduces a new lumped-parameter mathematical model, specifically focusing on the vasculature of both kidneys using a non-Newtonian Carreau fluid. This model, a first-order approximation, accounts for the variation in the total impedance of the vasculature when various vessels are severed in the diseased kidney (assumed to be the left in this work). The model offers near real-time estimations of the flow–pressure redistribution within the vascular network of the two kidneys and the downstream aorta for several radical or partial nephrectomy scenarios. Notably, our findings indicate that the downstream aorta receives an approximately 1.27 times higher percentage of the redistributed flow from the diseased kidney compared to that received by the healthy kidney, in nearly all examined cases. The implications of this study are significant, as they can inform the development of surgical protocols to minimize blood loss and can assist surgeons in evaluating the adequacy of the remaining kidney vasculature.

Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)
UK Research and Innovation, Engineering and Physical Sciences Research Council
Good health and well-being
Openalex Percentile: Top 33%
Innovative Approaches in Technology and Social Development
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Near real-time estimation of blood loss and flow-pressure re-distribution during unilateral nephrectomy · Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) (2024) | TGRS Research Map | TGRS