Validation of the Alzheimer's disease-resemblance atrophy index in classifying and predicting progression in Alzheimer's disease.
Validation of the Alzheimer's disease-resemblance atrophy index in classifying and predicting progression in Alzheimer's disease.
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DOI：
10.3389/fnagi.2022.932125
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发表时间：
2022
影响因子：
4.8
通讯作者：
中科院分区：
文献类型：
--
作者：
用于表征痴呆风险的自动化工具有可能帮助阿尔茨海默病（AD）的诊断，预后和治疗。在这里，我们研究了一种新的基于机器学习的脑萎缩标志物，即AD相似性萎缩指数（AD-RAI），以评估其重测信度，并进一步验证其在疾病分类和预测中的用途。从阿尔茨海默病最小间隔共振成像（MIRIAD）数据集中获得年龄和性别匹配的44名可能AD（年龄：69.13 ± 7.13; MMSE：27-30）和22名非痴呆对照（年龄：69.38 ± 7.21; MMSE：27-30）参与者。包括2年内最多9个时间点的连续T1加权图像（n = 678），包括同一天在相同参与者身上采集的179对背靠背扫描和以2周间隔采集的40对扫描。使用AccuBrain®自动处理所有图像以计算AD-RAI。首先评估了其当天重复性和2周重复性。使用受试者工作特征曲线评价AD-RAI的区分性能，其中DeLong检验用于评价其相对于定量内侧颞叶萎缩（QMTA）和海马体积（分别通过颅内体积（ICV）-比例和ICV-残差方法调整）的性能（HVR和HRV）。线性混合效应模型被用来调查纵向轨迹的AD-RAI和基线AD-RAI预测认知能力下降。最后，评估AD-RAI和MMSE评分之间的纵向关联。AD-RAI具有良好的同日重复性和良好的2周重复性。AD-RAI的AUC（99.8%; 95%CI = [99.3%，100%]）与QMTA（96.8%; 95%CI = [92.9%，100%]）相当，优于HVR（86.8%; 95%CI = [78.2%，95.4%]）或HRV（90.3%; 95%CI = [83.0%，97.6%]）。虽然AD组的基线AD-RAI显著较高，但在2年内未显示可检测的变化。基线AD-RAI与MMSE评分和MMSE评分随时间的变化率呈负相关。AD患者的AD-RAI值与MMSE评分之间也存在纵向负相关。AD-RAI代表了一种潜在的生物标志物，可支持AD诊断，并用于预测AD患者未来认知功能下降的速度。
Automated tools for characterising dementia risk have the potential to aid in the diagnosis, prognosis, and treatment of Alzheimer’s disease (AD). Here, we examined a novel machine learning-based brain atrophy marker, the AD-resemblance atrophy index (AD-RAI), to assess its test-retest reliability and further validate its use in disease classification and prediction. Age- and sex-matched 44 probable AD (Age: 69.13 ± 7.13; MMSE: 27–30) and 22 non-demented control (Age: 69.38 ± 7.21; MMSE: 27–30) participants were obtained from the Minimal Interval Resonance Imaging in Alzheimer’s Disease (MIRIAD) dataset. Serial T1-weighted images (n = 678) from up to nine time points over a 2-year period, including 179 pairs of back-to-back scans acquired on same participants on the same day and 40 pairs of scans acquired at 2-week intervals were included. All images were automatically processed with AccuBrain® to calculate the AD-RAI. Its same-day repeatability and 2-week reproducibility were first assessed. The discriminative performance of AD-RAI was evaluated using the receiver operating characteristic curve, where DeLong’s test was used to evaluate its performance against quantitative medial temporal lobe atrophy (QMTA) and hippocampal volume adjusted by intracranial volume (ICV)-proportions and ICV-residuals methods, respectively (HVR and HRV). Linear mixed-effects modelling was used to investigate longitudinal trajectories of AD-RAI and baseline AD-RAI prediction of cognitive decline. Finally, the longitudinal associations between AD-RAI and MMSE scores were assessed. AD-RAI had excellent same-day repeatability and excellent 2-week reproducibility. AD-RAI’s AUC (99.8%; 95%CI = [99.3%, 100%]) was equivalent to that of QMTA (96.8%; 95%CI = [92.9%, 100%]), and better than that of HVR (86.8%; 95%CI = [78.2%, 95.4%]) or HRV (90.3%; 95%CI = [83.0%, 97.6%]). While baseline AD-RAI was significantly higher in the AD group, it did not show detectable changes over 2 years. Baseline AD-RAI was negatively associated with MMSE scores and the rate of the change in MMSE scores over time. A negative longitudinal association was also found between AD-RAI values and the MMSE scores among AD patients. The AD-RAI represents a potential biomarker that may support AD diagnosis and be used to predict the rate of future cognitive decline in AD patients.
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影响因子：
14.5
作者：
Dong, Aoyan;Toledo, Jon B.;Davatzikos, Christos
通讯作者：
Davatzikos, Christos
DOI：
10.1038/s41572-021-00269-y
发表时间：
2021-05-13
期刊：
Nature reviews. Disease primers
影响因子：
--
作者：
Knopman DS;Amieva H;Petersen RC;Chételat G;Holtzman DM;Hyman BT;Nixon RA;Jones DT
通讯作者：
Jones DT
影响因子：
38.1
作者：
Frisoni, Giovanni B.;Fox, Nick C.;Jack, Clifford R., Jr.;Scheltens, Philip;Thompson, Paul M.
通讯作者：
Thompson, Paul M.
影响因子：
3.8
作者：
Bakdash JZ;Marusich LR
通讯作者：
Marusich LR
DOI：
10.18632/aging.203082
发表时间：
2021-05-25
期刊：
Aging
影响因子：
--
作者：
Liu W;Au LWC;Abrigo J;Luo Y;Wong A;Lam BYK;Fan X;Kwan PWL;Ma HW;Ng AYT;Chen S;Leung EYL;Ho CL;Wong SHM;Chu WC;Ko H;Lau AYL;Shi L;Mok VCT;Alzheimer’s Disease Neuroimaging Initiative
通讯作者：
Alzheimer’s Disease Neuroimaging Initiative