Suppr超能文献

一种用于量化大腿临床三维CT图像中肌肉-脂质分布的可重复半自动方法。

A reproducible semi-automatic method to quantify the muscle-lipid distribution in clinical 3D CT images of the thigh.

作者信息

Mühlberg Alexander, Museyko Oleg, Laredo Jean-Denis, Engelke Klaus

机构信息

Institute Of Medical Physics, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.

AP-HP, Radiologie Ostéo-Articulaire, Hôpital Lariboisière, Université Paris VII Denis Diderot, Paris, France.

出版信息

PLoS One. 2017 Apr 28;12(4):e0175174. doi: 10.1371/journal.pone.0175174. eCollection 2017.

Abstract

Many studies use threshold-based techniques to assess in vivo the muscle, bone and adipose tissue distribution of the legs using computed tomography (CT) imaging. More advanced techniques divide the legs into subcutaneous adipose tissue (SAT), anatomical muscle (muscle tissue and adipocytes within the muscle border) and intra- and perimuscular adipose tissue. In addition, a so-called muscle density directly derived from the CT-values is often measured. We introduce a new integrated approach to quantify the muscle-lipid system (MLS) using quantitative CT in patients with sarcopenia or osteoporosis. The analysis targets the thigh as many CT studies of the hip do not include entire legs The framework consists of an anatomic coordinate system, allowing delineation of reproducible volumes of interest, a robust semi-automatic 3D segmentation of the fascia and a comprehensive method to quantify of the muscle and lipid distribution within the fascia. CT density-dependent features are calibrated using subject-specific internal CT values of the SAT and external CT values of an in scan calibration phantom. Robustness of the framework with respect to operator interaction, image noise and calibration was evaluated. Specifically, the impact of inter- and intra-operator reanalysis precision and addition of Gaussian noise to simulate lower radiation exposure on muscle and AT volumes, muscle density and 3D texture features quantifying MLS within the fascia, were analyzed. Existing data of 25 subjects (age: 75.6 ± 8.7) with porous and low-contrast muscle structures were included in the analysis. Intra- and inter-operator reanalysis precision errors were below 1% and mostly comparable to 1% of cohort variation of the corresponding features. Doubling the noise changed most 3D texture features by up to 15% of the cohort variation but did not affect density and volume measurements. The application of the novel technique is easy with acceptable processing time. It can thus be employed for a comprehensive quantification of the muscle-lipid system enabling radiomics approaches to musculoskeletal disorders.

摘要

许多研究使用基于阈值的技术,通过计算机断层扫描(CT)成像在体内评估腿部的肌肉、骨骼和脂肪组织分布。更先进的技术将腿部划分为皮下脂肪组织(SAT)、解剖学肌肉(肌肉边界内的肌肉组织和脂肪细胞)以及肌内和肌周脂肪组织。此外,通常还会测量直接从CT值得出的所谓肌肉密度。我们引入了一种新的综合方法,利用定量CT对患有肌肉减少症或骨质疏松症的患者的肌肉 - 脂质系统(MLS)进行量化。由于许多髋部的CT研究并不包括整条腿,因此分析以大腿为目标。该框架由一个解剖坐标系组成,可实现对可重复感兴趣体积的描绘、筋膜的稳健半自动3D分割以及一种全面的方法来量化筋膜内的肌肉和脂质分布。CT密度相关特征使用SAT的受试者特定内部CT值和扫描校准体模的外部CT值进行校准。评估了该框架在操作员交互、图像噪声和校准方面的稳健性。具体而言,分析了操作员间和操作员内重新分析精度以及添加高斯噪声以模拟较低辐射暴露对肌肉和脂肪组织体积、肌肉密度以及量化筋膜内MLS的3D纹理特征的影响。分析纳入了25名受试者(年龄:75.6±8.7)的现有数据,这些受试者具有多孔和低对比度的肌肉结构。操作员内和操作员间重新分析精度误差低于1%,且大多与相应特征队列变异的1%相当。噪声加倍使大多数3D纹理特征最多改变队列变异的15%,但不影响密度和体积测量。该新技术应用简便,处理时间可接受。因此,它可用于对肌肉 - 脂质系统进行全面量化,从而实现对肌肉骨骼疾病的放射组学方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f91f/5409141/6c84b20f2551/pone.0175174.g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验