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利用31P磁共振波谱数据的人工神经网络分析评估肌肉疾病

Evaluation of muscle diseases using artificial neural network analysis of 31P MR spectroscopy data.

作者信息

Kari S, Olsen N J, Park J H

机构信息

Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

出版信息

Magn Reson Med. 1995 Nov;34(5):664-72. doi: 10.1002/mrm.1910340504.

Abstract

Dermatomyositis is an autoimmune disease characterized by an erythematous rash and severe muscle weakness. 31P Magnetic resonance spectroscopy (MRS) provides quantitative data for longitudinal monitoring of disease status and responses to immunosuppressive therapy. A disease variant, amyopathic dermatomyositis, presents with a typical rash but no clinical muscle weakness. However, metabolic abnormalities in the oxidative capacity of muscles of amyopathic patients during exercise were detected with 31P MRS. Because MRS provided the best quantitative data for evaluating dermatomyositis, the 31P metabolic parameters derived from the MR spectra were further processed using an artificial neural network (XERION). The neural network analyses provided additional clinical information from the weighted correlations of multiple 31P parameters, namely, inorganic phosphate, phosphocreatine, ATP, phosphodiesters, and selected ratios. This investigation analyzes the relative importance of the various metabolic parameters for accurate patient characterization and provides insights into the pathogenesis of the disease.

摘要

皮肌炎是一种自身免疫性疾病,其特征为红斑皮疹和严重的肌肉无力。31P磁共振波谱(MRS)可为疾病状态的纵向监测及免疫抑制治疗反应提供定量数据。一种疾病变体,无肌病性皮肌炎,表现为典型皮疹但无临床肌肉无力。然而,通过31P MRS检测到无肌病患者运动期间肌肉氧化能力的代谢异常。由于MRS为评估皮肌炎提供了最佳定量数据,因此使用人工神经网络(XERION)对从磁共振波谱得出的31P代谢参数进行了进一步处理。神经网络分析从多个31P参数(即无机磷酸盐、磷酸肌酸、ATP、磷酸二酯和选定比率)的加权相关性中提供了额外的临床信息。本研究分析了各种代谢参数对准确患者特征描述的相对重要性,并为该疾病的发病机制提供了见解。

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