利用磁共振成像的放射学特征评估与年龄相关的小腿肌肉质量差异

IF 2.9 2区 工程技术 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Takuro Shiiba, Suzumi Mori, Takuya Shimozono, Shuji Ito, Kazuki Takano
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引用次数: 0

摘要

以肌肉质量和力量下降为特征的 "肌肉疏松症 "影响着老年人的健康,导致跌倒率、住院率和死亡率上升。肌肉质量反映了肌肉的微观和宏观变化,是决定身体功能的关键因素。为了利用从磁共振(MR)图像中提取的放射组学特征来评估肌肉质量与年龄有关的变化,研究人员使用了一个由 24 名成年人组成的数据集,分为老年组(男/女:6/6,66-79 岁)和年轻组(男/女:6/6,21-31 岁),研究对行动能力至关重要的小腿背屈肌和跖屈肌的放射组学特征。磁共振图像使用 MaZda 软件进行特征提取处理。使用主成分分析和递归特征消除进行降维,然后使用机器学习模型进行分类,如支持向量机、极梯度提升和天真贝叶斯。在对分类器进行训练和测试时使用了留一验证测试,并使用接收者工作特征曲线下面积(AUC)来评估分类性能。分析结果表明,不同年龄组之间的放射学特征分布存在显著差异,老年人的肌肉纹理复杂性和变异性更高。在所有模型中,跖屈肌的 AUC 值与背屈肌相似或更高。当背屈肌与跖屈肌结合使用时,它们的 AUC 往往高于单独使用时。小腿核磁共振图像中的放射线学特征反映了老化,尤其是跖屈肌的老化。与传统的肌肉质量评估相比,放射线组学分析能更深入地了解与年龄相关的肌肉质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Assessment of Age-Related Differences in Lower Leg Muscles Quality Using Radiomic Features of Magnetic Resonance Images

Assessment of Age-Related Differences in Lower Leg Muscles Quality Using Radiomic Features of Magnetic Resonance Images

Sarcopenia, characterised by a decline in muscle mass and strength, affects the health of the elderly, leading to increased falls, hospitalisation, and mortality rates. Muscle quality, reflecting microscopic and macroscopic muscle changes, is a critical determinant of physical function. To utilise radiomic features extracted from magnetic resonance (MR) images to assess age-related changes in muscle quality, a dataset of 24 adults, divided into older (male/female: 6/6, 66–79 years) and younger (male/female: 6/6, 21–31 years) groups, was used to investigate the radiomics features of the dorsiflexor and plantar flexor muscles of the lower leg that are critical for mobility. MR images were processed using MaZda software for feature extraction. Dimensionality reduction was performed using principal component analysis and recursive feature elimination, followed by classification using machine learning models, such as support vector machine, extreme gradient boosting, and naïve Bayes. A leave-one-out validation test was used to train and test the classifiers, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the classification performance. The analysis revealed that significant differences in radiomic feature distributions were found between age groups, with older adults showing higher complexity and variability in muscle texture. The plantar flexors showed similar or higher AUC than the dorsiflexors in all models. When the dorsiflexor muscles were combined with the plantar flexor muscles, they tended to have a higher AUC than when they were used alone. Radiomic features in lower-leg MR images reflect ageing, especially in the plantar flexor muscles. Radiomic analysis can offer a deeper understanding of age-related muscle quality than traditional muscle mass assessments.

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来源期刊
Journal of Digital Imaging
Journal of Digital Imaging 医学-核医学
CiteScore
7.50
自引率
6.80%
发文量
192
审稿时长
6-12 weeks
期刊介绍: The Journal of Digital Imaging (JDI) is the official peer-reviewed journal of the Society for Imaging Informatics in Medicine (SIIM). JDI’s goal is to enhance the exchange of knowledge encompassed by the general topic of Imaging Informatics in Medicine such as research and practice in clinical, engineering, and information technologies and techniques in all medical imaging environments. JDI topics are of interest to researchers, developers, educators, physicians, and imaging informatics professionals. Suggested Topics PACS and component systems; imaging informatics for the enterprise; image-enabled electronic medical records; RIS and HIS; digital image acquisition; image processing; image data compression; 3D, visualization, and multimedia; speech recognition; computer-aided diagnosis; facilities design; imaging vocabularies and ontologies; Transforming the Radiological Interpretation Process (TRIP™); DICOM and other standards; workflow and process modeling and simulation; quality assurance; archive integrity and security; teleradiology; digital mammography; and radiological informatics education.
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