Amare Rohan, Bahadori Amir A, Eckels Steven
Institute for Environmental Research and Alan Levin Department of Mechanical EngineeringKansas State University Manhattan KS 66502 USA.
Radiological Engineering Analysis Laboratory.
IEEE Open J Eng Med Biol. 2020 May 14;1:174-186. doi: 10.1109/OJEMB.2020.2994557. eCollection 2020.
The thermoregulation mechanism is a complex system that executes vital processes in the human body. Various models have been proposed to simulate the thermoregulatory response of an adult human to environmental stimuli. However, these models generally rely on stylized phantoms that lack the anatomical details of voxel phantoms used in radiation dosimetry and shielding research. The goal of this work is to introduce voxel phantoms to thermoregulation research by modeling the physical energy exchange between tissue and its surroundings, discuss a specific challenge associated with voxel phantoms, propose a method to address this challenge, and demonstrate its application. One of the major challenges in using voxel phantoms is the stair-step effect on the surface of the voxelized domain. This effect causes over-estimation of surface area, accurate knowledge of which is critical for modeling heat exchanging systems. A methodology to generate a voxel domain from medical imaging data and reduce error in the surface area caused by the stair-step effect is presented. The methodology, based on a structured mesh and finite-volume method, is demonstrated with tumors generated from magnetic resonance imaging (MRI) scans of mice. The methodology discussed in the paper shows a decrease in surface area over-estimation from 50% to 15% for a sphere and 47% to 17% for tumor models generated directly from MRI scans. This work provides a direct method to generate a smoother domain from medical imaging data and reducing surface area error in a voxelized domain. The technique presented is independent of domain material, including tissue type, and can be extended to any homogeneous or inhomogeneous domain. The increase in surface area accuracy obtained by smoothing the voxel domain results in more accurate temperature estimates in heat transfer simulation.
体温调节机制是一个在人体中执行重要过程的复杂系统。人们已经提出了各种模型来模拟成年人体对环境刺激的体温调节反应。然而，这些模型通常依赖于缺乏辐射剂量学和屏蔽研究中使用的体素模型解剖细节的简化模型。这项工作的目标是通过对组织与其周围环境之间的物理能量交换进行建模，将体素模型引入体温调节研究，讨论与体素模型相关的一个特定挑战，提出一种解决这一挑战的方法，并展示其应用。使用体素模型的主要挑战之一是体素化区域表面的阶梯效应。这种效应会导致表面积的高估，而准确了解表面积对于热交换系统的建模至关重要。本文提出了一种从医学成像数据生成体素区域并减少阶梯效应引起的表面积误差的方法。该方法基于结构化网格和有限体积法，通过对小鼠磁共振成像（MRI）扫描生成的肿瘤进行了演示。本文讨论的方法表明，对于直接从MRI扫描生成的球体和肿瘤模型，表面积高估从50%降至15%，从47%降至17%。这项工作提供了一种直接方法，可从医学成像数据生成更平滑的区域，并减少体素化区域中的表面积误差。所提出的技术与包括组织类型在内的区域材料无关，并且可以扩展到任何均匀或非均匀区域。通过平滑体素区域获得的表面积精度的提高，在传热模拟中可以得到更准确的温度估计。
