@article {AgostaP3.182作者= {Federica Agosta Elisa Canu和弗兰西斯卡imperiale弗朗西斯卡卡索和安德烈·丰塔纳和朱塞佩·马格纳尼Andrea Falini和吉安卡洛Comi马西莫菲利皮主持},title ={附加值的多通道结构的MRI的临床诊断原发性进行性失语变体(P3.182)},体积={90}={15}补充数量,elocation-id = {P3.182} ={2018},出版商= {Wolters Kluwer健康,公司代表美国神经病学学会},文摘={目的:确定一个多通道的附加值磁共振成像(MRI)语言评估方法的鉴别诊断non-fluent (nfv)、语义(sv)和logopenic (lv)变异原发性进行性失语(PPA)。首页背景:PPA变异可能存在一个重叠的照片和诊断在临床实践中可能是一个挑战。设计/方法:57例(28 nfvPPA 15 svPPA 14 lvPPA)和38健康对照组被招募。对抗命名、对象知识重复,和语法的理解。参与者进行了3 d t1和扩散张量磁共振成像(DT)。皮质厚度(CT)和DT-MR成像指标的白质(WM)大片。随机森林分析确定语言和核磁共振特性与每个相关的临床综合征。最后,使用接收操作特性曲线分析,个别病人分类进行单独使用语言特性的组合({\ textquoteleft} {\ textquoteright})语言模型,通过添加这个模型CT措施,梗死后变量,两者的结合磁共振成像模式。结果:语言模型就能够区分svPPA nfvPPA和患者lvPPA高精度(AUC 0.88 {\ textendash} {\ textendash} 1.00, 1.00和0.97)。当梗死后指标的胼胝体膝和左额歪斜的呼吸道被添加到语言模型,正确的分类nfvPPA相对于lvPPA从0.75 AUC显著增加({\ textquoteleft}语言模型只{\ textquoteright})到0.97 ({\ textquoteleft}语言+梗死后模型{\ textquoteright})。相反,CT措施,两者的结合MRI形态没有改善nfvPPA / lvPPA分类精度当添加到语言评估。结论:语言特性仅能够区分svPPA和另外两个PPA变体。相反,梗死后可能提高nfvPPA的鉴别诊断和lvPPA最艰难的两个杰出的基于语音生产形式。WM改变观察nfvPPA lvPPA相比可以反映tauopathy下面。Study Supported by: The study was supported by the Italian Ministry of Health (grant numbers GR-2010-2303035 and GR-2011-02351217).Disclosure: Dr. Agosta has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with EXCEMED{\textemdash} Excellence in Medical Education. Dr. Canu has nothing to disclose. Dr. imperiale has nothing to disclose. Dr. Caso has nothing to disclose. Dr. Fontana has nothing to disclose. Dr. Magnani has nothing to disclose. Dr. Falini has nothing to disclose. Dr. Comi has nothing to disclose. Dr. Filippi has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen Idec, Merk-Serono, Novartis, Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in an editorial capacity for Journal of Neurology. Dr. Filippi has received research support from Biogen Idec, Novartis, Teva Pharmaceutical Industries.}, issn = {0028-3878}, URL = {//www.ez-admanager.com/content/90/15_Supplement/P3.182}, eprint = {//www.ez-admanager.com/content}, journal = {Neurology} }