Objectives

Alzheimer's disease (AD) is the most common type of dementia, and characterizing brain changes in AD is important for clinical diagnosis and prognosis. This study was designed to evaluate the classification performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in differentiating between AD patients and normal control (NC) subjects and to explore its potential effectiveness as a neuroimaging biomarker.

Methods

Thirty-one patients with probable AD and twenty NC subjects were included in the prospective study. IVIM data were subjected to postprocessing, and parameters including the apparent diffusion coefficient (ADC), slow diffusion coefficient (D_s), fast diffusion coefficient (D_f), perfusion fraction (fp) and D_f*fp were calculated. The classification model was developed and confirmed with cross-validation (group A/B) using Support Vector Machine (SVM). Correlations between IVIM parameters and Mini-Mental State Examination (MMSE) scores in AD patients were investigated using partial correlation analysis.

Results

Diffusion MRI revealed significant region-specific differences that aided in differentiating AD patients from controls. Among the analyzed regions and parameters, the D_f of the right precuneus (PreR) (ρ = 0.515; P = 0.006) and the left cerebellum (CL) (ρ = 0.429; P = 0.026) demonstrated significant associations with the cognitive function of AD patients. An area under the receiver operating characteristics curve (AUC) of 0.84 (95% CI: 0.66, 0.99) was calculated for the validation in dataset B after the prediction model was trained on dataset A. When the datasets were reversed, an AUC of 0.90 (95% CI: 0.75, 1.00) was calculated for the validation in dataset A, after the prediction model trained in dataset B.

Conclusion

IVIM imaging is a promising method for the classification of AD and NC subjects, and IVIM parameters of precuneus and cerebellum might be effective biomarker for the diagnosis of AD.

中文翻译：

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体素内不相干运动扩散加权成像在阿尔茨海默病的表征中

目标

阿尔茨海默病 (AD) 是最常见的痴呆类型，表征 AD 中的大脑变化对于临床诊断和预后很重要。本研究旨在评估体素内不相干运动 (IVIM) 扩散加权成像在区分 AD 患者和正常对照 (NC) 受试者方面的分类性能，并探讨其作为神经影像生物标志物的潜在有效性。

方法

前瞻性研究包括 31 名可能患有 AD 的患者和 20 名 NC 受试者。对IVIM数据进行后处理，计算表观扩散系数（ADC）、慢扩散系数（D _s）、快扩散系数（D _f）、灌注分数（fp）和D _f *fp等参数。使用支持向量机 (SVM) 通过交叉验证（A/B 组）开发和确认分类模型。使用偏相关分析研究了 AD 患者的 IVIM 参数与简易精神状态检查 (MMSE) 评分之间的相关性。

结果

弥散 MRI 揭示了显着的区域特异性差异，有助于区分 AD 患者与对照组。在分析的区域和参数中，右楔前叶 (PreR) (ρ = 0.515; P = 0.006) 和左小脑 (CL) (ρ = 0.429; P = 0.026) 的 D _f与认知功能显着相关AD患者。在数据集 A 上训练预测模型后，为数据集 B 中的验证计算接收者操作特征曲线 (AUC) 下面积 0.84 (95% CI: 0.66, 0.99)。当数据集反转时，AUC 为 0.90 (95% CI: 0.75, 1.00) 在数据集 B 中训练预测模型后，计算数据集 A 中的验证。

结论

IVIM 成像是一种很有前途的 AD 和 NC 受试者分类方法，楔前叶和小脑的 IVIM 参数可能是诊断 AD 的有效生物标志物。