Computer Science Department, University of Jaén, Jaén, Spain.
Gordon Center for Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
Hum Brain Mapp. 2017 Dec;38(12):5905-5918. doi: 10.1002/hbm.23773. Epub 2017 Aug 30.
Alzheimer's disease (AD) is a neurological disorder that creates neurodegenerative changes at several structural and functional levels in human brain tissue. The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of the human brain. In this study, we investigate spherical harmonic-based FD (SHFD), thickness, and local gyrification index (LGI) to assess whether they identify cortical surface abnormalities toward the conversion to AD. We study 33 AD patients, 122 mild cognitive impairment (MCI) patients (50 MCI converters and 29 MCI nonconverters), and 32 healthy controls (HC). SHFD, thickness, and LGI methodology allowed us to perform not only global level but also local level assessments in each cortical surface vertex. First, we found that global SHFD decreased in AD and future MCI converters compared to HC, and in MCI converters compared to MCI nonconverters. Second, we found that local white matter SHFD was reduced in AD compared to HC and MCI mainly in medial temporal lobe. Third, local white-matter SHFD was significantly reduced in MCI converters compared to MCI nonconverters in distributed areas, including the medial frontal lobe. Thickness and LGI metrics presented a reduction in AD compared to HC. Thickness was significantly reduced in MCI converters compared to healthy controls in entorhinal cortex and lateral temporal. In summary, SHFD was the only surface measure showing differences between MCI individuals that will convert or remain stable in the next 4 years. We suggest that SHFD may be an optimal complement to thickness loss analysis in monitoring longitudinal changes in preclinical and clinical stages of AD. Hum Brain Mapp 38:5905-5918, 2017. © 2017 Wiley Periodicals, Inc.
阿尔茨海默病（AD）是一种神经退行性疾病，会在人脑组织的多个结构和功能水平上产生神经变性变化。分形维数（FD）是一个定量参数，可用于描述人脑形态的变异性。在这项研究中，我们研究了基于球谐函数的 FD（SHFD）、厚度和局部脑回指数（LGI），以评估它们是否可以识别向 AD 转化的皮质表面异常。我们研究了 33 名 AD 患者、122 名轻度认知障碍（MCI）患者（50 名 MCI 转化者和 29 名 MCI 非转化者）和 32 名健康对照者（HC）。SHFD、厚度和 LGI 方法不仅允许我们在每个皮质表面顶点进行全局水平评估，还允许我们进行局部水平评估。首先，我们发现 AD 和未来的 MCI 转化者的全局 SHFD 与 HC 相比降低，与 MCI 非转化者相比降低。其次，我们发现 AD 患者的局部白质 SHFD 与 HC 和 MCI 相比降低，主要位于内侧颞叶。第三，与 MCI 非转化者相比，MCI 转化者在包括额内侧回在内的分布式区域的局部白质 SHFD 显著降低。与 HC 相比，AD 的厚度和 LGI 指标降低。与健康对照组相比，MCI 转化者的额内回和外侧颞叶的厚度显著降低。总之，SHFD 是唯一在未来 4 年内会发生转化或保持稳定的 MCI 个体之间存在差异的皮质表面测量指标。我们认为，SHFD 可能是在 AD 临床前和临床阶段监测纵向变化的一种优化补充，与厚度损失分析相结合。人类大脑映射 38:5905-5918, 2017. © 2017 Wiley Periodicals, Inc.
