文献类型： 会议论文

第一作者： S. Duchesne

作者： S. Duchesne ¹ ; Y. Roland ² ; M. Verin ² ; C. Barillot ¹ ;

作者机构： 1.Unite/Equipe VISAGES U746, IRIS A, Campus Beaulieu, 35042 CEDEX, Rennes, France

2.Centre Hospitalier Universitaire de Rennes, Rennes, France

关键词： computer-aided diagnosis;MRI;morphology;movement disorders

会议名称： Medical imaging 2007.

主办单位：

页码： 65140X-1-65140X-8

摘要： Background: Reported error rates for initial clinical diagnosis in parkinsonian disorders can reach up to 35%. Reducing this initial error rate is an important research goal. The objective of this work is to evaluate the ability of an automated MR-based classification technique in the differential diagnosis of Parkinson's disease (PD), multiple systems atrophy (MSA) and progressive supranuclear palsy (PSP). Methods: A total of 172 subjects were included in this study: 152 healthy subjects, 10 probable PD patients and 10 age-matched patients with diagnostic of either probable MSA or PSP. T1-weighted (T1w) MR images were acquired and subsequently corrected, scaled, resampled and aligned within a common referential space. Tissue transformation and deformation features were then automatically extracted. Classification of patients was performed using forward, stepwise linear discriminant analysis within a multidimensional transformation/deformation feature space built from healthy subjects data. Leave-one-out classification was used to avoid over-determination. Findings: There were no age difference between groups. Highest accuracy (agreement with long-term clinical follow-up) of 85% was achieved using a single MR-based deformation feature. Interpretation: These preliminary results demonstrate that a classification approach based on quantitative parameters of 3D brainstem morphology extracted automatically from T1w MRI has the potential to perform differential diagnosis of PD versus MSA/PSP with high accuracy.

分类号： N5