Whitwell Jennifer L, Weigand Stephen D, Duffy Joseph R, Strand Edythe A, Machulda Mary M, Senjem Matthew L, Gunter Jeffrey L, Lowe Val J, Jack Clifford R, Josephs Keith A
Department of Radiology, Mayo Clinic, Rochester, MN, USA.
Department of Health Sciences Research (Biostatistics), Mayo Clinic, Rochester, MN, USA.
Neuroimage Clin. 2016 Jan 20;11:90-98. doi: 10.1016/j.nicl.2016.01.014. eCollection 2016.
Beta-amyloid (Aβ) deposition can be observed in primary progressive aphasia (PPA) and progressive apraxia of speech (PAOS). While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified) and PAOS (n = 42) subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+) status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+) status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+) status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified PPA subjects.
β-淀粉样蛋白（Aβ）沉积可在原发性进行性失语（PPA）和进行性言语失用症（PAOS）中观察到。虽然它通常与语法缺失型PPA相关，但也有例外情况，这使得仅根据临床诊断来预测Aβ状态具有挑战性。我们旨在确定MRI区域体积或临床数据是否有助于预测Aβ沉积。139名PPA（n = 97；15名语法缺失型、53名语音缺失型、13名语义型和16名未分类型）和PAOS（n = 42）受试者被前瞻性纳入一项横断面研究，并接受了言语/语言评估、3.0 T MRI和C11-匹兹堡复合物B PET检查。使用1.5的标准化摄取值比率（SUVR）切点来确定Aβ的存在。基于图谱的分割用于计算大脑中42个感兴趣区域的灰质体积。使用惩罚二元逻辑回归来确定哪些MRI区域组合以及哪些言语和语言测试组合最能预测Aβ（+）状态。最佳MRI模型和最佳临床模型在根据Aβ状态准确分类受试者的能力方面表现相当。MRI使用14个区域准确分类了81%的受试者。左侧颞上回和顶下小叶体积较小以及左侧布洛卡区体积较大对Aβ（+）状态具有特别的预测性。临床评分使用经12项测试准确分类了83%的受试者。语音错误和复述缺陷，以及无语法缺失和运动性言语缺陷对Aβ（+）状态具有特别的预测性。相比之下，临床诊断能够准确分类89%的受试者。然而，MRI模型在预测未分类PPA中的Aβ沉积方面表现良好。临床诊断在群体水平上对Aβ状态提供了最佳预测，尽管区域MRI测量以及言语和语言测试也表现良好，并且在预测未分类PPA受试者的Aβ状态方面可能具有优势。
