Institute of Biophotonics, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Department of Research, Shin Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan.
Eur J Neurosci. 2024 Nov;60(9):6254-6266. doi: 10.1111/ejn.16557. Epub 2024 Oct 1.
Amnestic mild cognitive impairment (aMCI) is considered as an intermediate stage of Alzheimer's disease, but no MRI biomarkers currently distinguish aMCI from healthy individuals effectively. Fractal dimension, a quantitative parameter, provides superior morphological information compared to conventional cortical thickness methods. Few studies have used cortical fractal dimension values to differentiate aMCI from healthy controls. In this study, we aim to build an automated discriminator for accurately distinguishing aMCI using fractal dimension measures of the cerebral cortex. Thirty aMCI patients and 30 health controls underwent structural MRI of the brain. First, the atrophy of participants' cortical sub-regions of Desikan-Killiany cortical atlas was assessed using fractal dimension and cortical thickness. The fractal dimension is more sensitive than cortical thickness in reducing dimensional effects and may accurately reflect morphological changes of the cortex in aMCI. The aMCI group had significantly lower fractal dimension values in the bilateral temporal lobes, right limbic lobe and right parietal lobe, whereas they showed significantly lower cortical thickness values only in the bilateral temporal lobes. Fractal dimension analysis was able to depict most of the significantly different focal regions detected by cortical thickness, but additionally with more regions. Second, applying the measured fractal dimensions (and cortical thickness) of both cerebral hemispheres, an unsupervised discriminator was built for the aMCI and healthy controls. The proposed fractal dimension-based method achieves 80.54% accuracy in discriminating aMCI from healthy controls. The fractal dimension appears to be a promising biomarker for cortical morphology changes that can discriminate patients with aMCI from healthy controls.
遗忘型轻度认知障碍（aMCI）被认为是阿尔茨海默病的一个中间阶段，但目前没有 MRI 生物标志物能有效地将 aMCI 与健康个体区分开来。分形维数是一个定量参数，与传统的皮质厚度方法相比，它提供了更好的形态学信息。很少有研究使用皮质分形维数值来区分 aMCI 与健康对照组。在这项研究中，我们旨在构建一个自动判别器，使用大脑皮质的分形维数来准确地区分 aMCI。30 名 aMCI 患者和 30 名健康对照者接受了大脑结构 MRI 检查。首先，使用分形维数和皮质厚度评估了参与者的 Desikan-Killiany 皮质图谱皮质子区域的萎缩。分形维数在降低维度效应方面比皮质厚度更敏感，并且可以准确反映 aMCI 中皮质的形态变化。aMCI 组双侧颞叶、右侧边缘叶和右侧顶叶的分形维数明显降低，而双侧颞叶的皮质厚度明显降低。分形维数分析能够描绘出皮质厚度检测到的大多数显著不同的局灶性区域，但还能额外显示更多的区域。其次，应用双侧大脑半球的测量分形维数（和皮质厚度），为 aMCI 和健康对照组构建了一个无监督判别器。所提出的基于分形维数的方法在区分 aMCI 和健康对照组方面的准确率达到 80.54%。分形维数似乎是一种有前途的皮质形态变化生物标志物，可将 aMCI 患者与健康对照组区分开来。
