Braak-tau^(IQ):一种适用于阿尔茨海默病tau PET图像的量化分解方法  

Braak-tau^(IQ):a quantization decomposition method based on tau PET images in Alzheimer′s disease

作　　者：门建炜 石蓉 王敏 张琪 鲁佳荧 张慧玮[3] 赵倩华 蒋皆恢 左传涛[3] 管一晖[3] Men Jianwei;Shi Rong;Wang Min;Zhang Qi;Lu Jiaying;Zhang Huiwei;Zhao Qianhua;Jiang Jiehui;Zuo Chuantao;Guan Yihui(School of Life and Science,Shanghai University/Shanghai Institute of Biomedical Engineering,Shanghai 200444,China;School of Communication and Information Engineering,Shanghai University,Shanghai 200444,China;Nuclear Medicine/PET Center,Huashan Hospital,Fudan University,Shanghai 200235,China;Department of Neurology,Huashan Hospital,Fudan University,Shanghai 200040,China)

机构地区：[1]上海大学生命科学学院,上海生物医学工程研究所,上海200444 [2]上海大学通信与信息工程学院,上海200444 [3]复旦大学附属华山医院核医学/PET中心,上海200235 [4]复旦大学附属华山医院神经内科,上海200040

出　　处：《中华核医学与分子影像杂志》2024年第12期718-723,共6页Chinese Journal of Nuclear Medicine and Molecular Imaging

基　　金：国家自然科学基金(62206165,81971641);上海市科技计划项目(22YF1413900)。

摘　　要：目的基于tau^(IQ)算法,建立一种基于Braak分期纵向且不涉及β-淀粉样蛋白(Aβ)显像的体素级别量化方法,以实现特异性tau量化。方法该横断面研究纳入2018年11月至2020年7月间复旦大学附属华山医院核医学/PET中心的92例受试者[男35例、女57例,年龄(62.9±10.4)岁],其中认知正常(CN)者28名、轻度认知障碍(MCI)患者20例、阿尔茨海默病(AD)患者44例。所有受试者采集^(18)F-florzolotau PET图像及简易精神状态检查量表(MMSE)和临床痴呆评定量表(CDR)评分。通过Braak分期构建tau纵向数据集,采用logistic回归进行体素级别拟合得到基准矩阵,最后通过最小二乘法对矩阵进行分解,得到特异性沉淀系数Tau_(load)。采用单因素方差分析(事后检验为Tukey法)比较组间Tau_(load)、SUV比值(SUVR)差异,采用ROC曲线分析CN、MCI与AD两两组间的分类能力,采用Spearman秩相关分析Tau_(load)、SUVR与MMSE评分、CDR评分之间的相关性。结果CN组的Tau_(load)接近于0,并显著低于MCI组与AD组(F=55.03,P<0.001;事后检验均P<0.001),各ROI的SUVR差异也均有统计学意义(F值:36.46~55.38,均P<0.001);相较于SUVR,Tau_(load)显示出更大的组间差异。在CN、MCI与AD两两组间的ROC曲线分析中,Tau_(load)的AUC一直保持最高(0.754~1.000)。Tau_(load)及各ROI的SUVR与MMSE评分呈负相关性(r_(s)值:-0.698~-0.583,均P<0.05),与CDR评分呈正相关性(r_(s)值:0.648~0.783,均P<0.05),其中Tau_(load)的相关系数绝对值最高。结论相对于传统半定量SUVR方法,Braak-tau^(IQ)算法不需要特定参考脑区也可以实现特异性tau量化性能。ObjectiveA voxel-level quantification method based on the tau^(IQ) algorithm and Braak staging,excludingβ-amyloid(Aβ)imaging,was developed to achieve specific tau quantification.MethodsThis cross-sectional study included 92 subjects(35 males,57 females;age(62.9±10.4)years)from the Nuclear Medicine/PET Center of Huashan Hospital,Fudan University between November 2018 and July 2020.The cohort comprised 28 cognitively normal(CN)individuals,20 patients with mild cognitive impairment(MCI),and 44 patients with Alzheimer′s disease(AD).All participants underwent ^(18)F-florzolotau PET imaging,Mini-Mental State Examination(MMSE),and Clinical Dementia Rating(CDR)scoring.A longitudinal tau dataset was constructed based on Braak staging.Voxel-level logistic regression fitting provided a baseline matrix,decomposed via least squares to yield the Tau_(load) coefficient.One-way analysis of variance(with post hoc Tukey)was used to compare Tau_(load) and SUV ratio(SUVR)among groups.ROC curve analysis was used to evaluate classification between CN,MCI and AD.Spearman rank correlation was used to assess the relationships between Tau_(load),SUVR,and MMSE scores or CDR scores.ResultsThe Tau_(load) in the CN group was close to 0 and significantly lower than that in the MCI and AD groups(F=55.03,P<0.001;post hoc tests all P<0.001).Significant differences were also observed in the SUVR across all ROIs(F values:36.46-55.38,all P<0.001).Compared to SUVR,Tau_(load) demonstrated greater intergroup differences.In ROC curve analyses between each pair of CN,MCI,and AD groups,Tau_(load) consistently achieved the highest AUC(0.754-1.000).Both Tau_(load) and SUVR for each ROI were negatively correlated with MMSE scores(r_(s) values:from-0.698 to-0.583,all P<0.05)and positively correlated with CDR scores(r_(s) values:0.648-0.783,all P<0.05),with Tau_(load) showing the highest absolute correlation coefficients.ConclusionCompared to the traditional semi-quantitative SUVR method,the Braak-tau^(IQ) algorithm does not require a specific reference b

关 键 词：阿尔茨海默病 认知功能障碍 苯并噻唑类 TAU蛋白质类 正电子发射断层显像术 算法 

分 类 号：R749.16[医药卫生—神经病学与精神病学] R817.4[医药卫生—临床医学]