预测糖尿病和高血压肾病血液动力学结果的硅模拟方法

IF 3 2区 医学 Q3 ENGINEERING, BIOMEDICAL Annals of Biomedical Engineering Pub Date : 2024-07-05 DOI:10.1007/s10439-024-03573-2
Ning Wang, Ivan Benemerito, Steven P Sourbron, Alberto Marzo
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引用次数: 0

摘要

肾脏疾病的早期诊断仍是一项尚未解决的临床难题,妨碍了及时有效的干预。糖尿病和高血压是导致肾脏疾病的两个主要原因,经常会同时出现,只有通过侵入性活检才能加以区分。在这项研究中,我们开发了一种建模方法来模拟老龄化、糖尿病和高血压虚拟人群动脉网络中的血流速度、容积流速和压力波传播。通过将我们对压力、容积流速和波形衍生指标的预测与文献中有关老龄化人群的体内数据进行比较,对模型进行了验证。该模型模拟了肾脏疾病的影响,并与文献中有关糖尿病和高血压肾病的活体数据进行了定量校准。我们的研究从肾脏血流速度和血流脉动性中发现了一些潜在的生物标记物。对于典型的患者年龄组,糖尿病肾病早期和严重阶段的阻力指数值分别为 0.69(标清 0.05)和 0.74(标清 0.02)。在高血压肾病的相同阶段也观察到类似的趋势,范围分别为 0.65(标清 0.07)至 0.73(标清 0.05)。通过单个病变肾脏的平均肾血流量在糖尿病肾病中为 329(标清 40,早期)至 317(标清 38,重度)毫升/分钟,在高血压肾病中为 443(标清 54,早期)至 388(标清 47,重度)毫升/分钟,显示出作为肾病早期诊断生物标志物的潜力。这种建模方法证明了其在为生物标记物鉴定提供信息和促进临床试验设置方面的潜在应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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An In Silico Modelling Approach to Predict Hemodynamic Outcomes in Diabetic and Hypertensive Kidney Disease

Early diagnosis of kidney disease remains an unmet clinical challenge, preventing timely and effective intervention. Diabetes and hypertension are two main causes of kidney disease, can often appear together, and can only be distinguished by invasive biopsy. In this study, we developed a modelling approach to simulate blood velocity, volumetric flow rate, and pressure wave propagation in arterial networks of ageing, diabetic, and hypertensive virtual populations. The model was validated by comparing our predictions for pressure, volumetric flow rate and waveform-derived indexes with in vivo data on ageing populations from the literature. The model simulated the effects of kidney disease, and was calibrated to align quantitatively with in vivo data on diabetic and hypertensive nephropathy from the literature. Our study identified some potential biomarkers extracted from renal blood flow rate and flow pulsatility. For typical patient age groups, resistive index values were 0.69 (SD 0.05) and 0.74 (SD 0.02) in the early and severe stages of diabetic nephropathy, respectively. Similar trends were observed in the same stages of hypertensive nephropathy, with a range from 0.65 (SD 0.07) to 0.73 (SD 0.05), respectively. Mean renal blood flow rate through a single diseased kidney ranged from 329 (SD 40, early) to 317 (SD 38, severe) ml/min in diabetic nephropathy and 443 (SD 54, early) to 388 (SD 47, severe) ml/min in hypertensive nephropathy, showing potential as a biomarker for early diagnosis of kidney disease. This modelling approach demonstrated its potential application in informing biomarker identification and facilitating the setup of clinical trials.

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来源期刊
Annals of Biomedical Engineering
Annals of Biomedical Engineering 工程技术-工程:生物医学
CiteScore
7.50
自引率
15.80%
发文量
212
审稿时长
3 months
期刊介绍: Annals of Biomedical Engineering is an official journal of the Biomedical Engineering Society, publishing original articles in the major fields of bioengineering and biomedical engineering. The Annals is an interdisciplinary and international journal with the aim to highlight integrated approaches to the solutions of biological and biomedical problems.
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