Near Real-Time Estimation of Blood Loss and Flow-Pressure Redistribution during Unilateral Nephrectomy

被引:1
|
作者
Cowley, James [1 ]
Kyeremeh, Justicia [2 ]
Stewart, Grant D. [2 ]
Luo, Xichun [3 ]
Shu, Wenmiao [1 ]
Kazakidi, Asimina [1 ]
机构
[1] Univ Strathclyde, Dept Biomed Engn, Glasgow G4 0NW, Scotland
[2] Univ Cambridge, Dept Surg, Cambridge CB2 0QQ, England
[3] Univ Strathclyde, Ctr Precis Mfg, Dept Design Mfg & Engn Management, Glasgow G1 1XJ, Scotland
基金
英国科研创新办公室;
关键词
blood loss; kidney tumor; renal arteries; vessel cutting; surgery; resection; two-kidney vasculature; simulation; mathematical modelling; lumped-parameter model; blood flux; pressure; ACUTE KIDNEY INJURY; WALL SHEAR-STRESS; TUBULOGLOMERULAR FEEDBACK; MATHEMATICAL-MODEL; ARTERIAL NETWORKS; AUTOREGULATION; DYNAMICS; PATTERNS; HEMODYNAMICS; BIFURCATION;
D O I
10.3390/fluids9090214
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
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.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] An Embedded Device for Real-Time Noninvasive Intracranial Pressure Estimation
    Matthews, Jonathan M.
    Fanelli, Andrea
    Heldt, Thomas
    INTRACRANIAL PRESSURE & NEUROMONITORING XVI, 2018, 126 : 85 - 88
  • [32] Effects of unilateral real-time biofeedback on propulsive forces during gait
    Christopher Schenck
    Trisha M. Kesar
    Journal of NeuroEngineering and Rehabilitation, 14
  • [33] Effects of unilateral real-time biofeedback on propulsive forces during gait
    Schenck, Christopher
    Kesar, Trisha M.
    JOURNAL OF NEUROENGINEERING AND REHABILITATION, 2017, 14
  • [34] Real-time intraocular pressure changes during keratomileusis
    Kasetsuwan, N
    Pangilinan, PT
    Moreira, LB
    Shah, SS
    Sanchez, D
    Schallhorn, S
    McDonnell, PJ
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 1997, 38 (04) : 1974 - 1974
  • [35] Real-Time Intermediate Flow Estimation for Video Frame Interpolation
    Huang, Zhewei
    Zhang, Tianyuan
    Heng, Wen
    Shi, Boxin
    Zhou, Shuchang
    COMPUTER VISION - ECCV 2022, PT XIV, 2022, 13674 : 624 - 642
  • [36] Real-Time Air Traffic Flow Estimation in the Terminal Area
    Yang, Bong-Jun
    Menon, P. K.
    JOURNAL OF AIRCRAFT, 2015, 52 (03): : 778 - 791
  • [37] On parameter estimation of a simple real-time flow aggregation model
    Fu, Huirong
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2006, 19 (07) : 795 - 808
  • [38] Real-time measurement of cerebral blood flow during and after repetitive transcranial magnetic stimulation: A near-infrared spectroscopy study
    Park, Eunhee
    Kang, Min Jae
    Lee, Ahee
    Chang, Won Hyuk
    Shin, Yong-Il
    Kim, Yun-Hee
    NEUROSCIENCE LETTERS, 2017, 653 : 78 - 83
  • [39] Event-based Real-time Optical Flow Estimation
    Lee, Alex Junho
    Kim, Ayoung
    2017 17TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), 2017, : 787 - 791
  • [40] Towards an operational near real-time precipitable water vapor estimation
    Dousa, J
    PHYSICS AND CHEMISTRY OF THE EARTH PART A-SOLID EARTH AND GEODESY, 2001, 26 (03): : 189 - 194