Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Level E4 Cambridge Biomedical Campus, Cambridge CB2 0SP, UK.
Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Level E4 Cambridge Biomedical Campus, Cambridge CB2 0SP, UK.
Ageing Res Rev. 2022 Aug;79:101651. doi: 10.1016/j.arr.2022.101651. Epub 2022 May 25.
Sensitive and specific antemortem biomarkers of neurodegenerative disease and dementia are crucial to the pursuit of effective treatments, required both to reliably identify disease and to track its progression. Atrophy is the structural magnetic resonance imaging (MRI) hallmark of neurodegeneration. However in most cases it likely indicates a relatively advanced stage of disease less susceptible to treatment as some disease processes begin decades prior to clinical onset. Among emerging metrics that characterise brain shape rather than volume, fractal dimension (FD) quantifies shape complexity. FD has been applied in diverse fields of science to measure subtle changes in elaborate structures. We review its application thus far to structural MRI of the brain in neurodegenerative disease and dementia. We identified studies involving subjects who met criteria for mild cognitive impairment, Alzheimer's Disease, Vascular Dementia, Lewy Body Dementia, Frontotemporal Dementia, Amyotrophic Lateral Sclerosis, Parkinson's Disease, Huntington's Disease, Multiple Systems Atrophy, Spinocerebellar Ataxia and Multiple Sclerosis. The early literature suggests that neurodegenerative disease processes are usually associated with a decline in FD of the brain. The literature includes examples of disease-related change in FD occurring independently of atrophy, which if substantiated would represent a valuable advantage over other structural imaging metrics. However, it is likely to be non-specific and to exhibit complex spatial and temporal patterns. A more harmonious methodological approach across a larger number of studies as well as careful attention to technical factors associated with image processing and FD measurement will help to better elucidate the metric's utility.
神经退行性疾病和痴呆症的敏感和特异性的生前生物标志物对于追求有效的治疗方法至关重要,这既需要可靠地识别疾病,又需要跟踪其进展。萎缩是神经退行性变的结构磁共振成像(MRI)标志。然而,在大多数情况下,它可能表明疾病处于相对较晚的阶段,治疗效果较差,因为一些疾病过程在临床发病前几十年就开始了。在描述大脑形状而不是体积的新兴指标中,分形维数(FD)量化了形状的复杂性。FD 已应用于科学的多个领域,以测量复杂结构的细微变化。我们回顾了它在神经退行性疾病和痴呆症的结构 MRI 中的应用。我们确定了涉及符合轻度认知障碍、阿尔茨海默病、血管性痴呆、路易体痴呆、额颞叶痴呆、肌萎缩侧索硬化症、帕金森病、亨廷顿病、多系统萎缩症、脊髓小脑共济失调和多发性硬化症标准的受试者的研究。早期文献表明,神经退行性疾病过程通常与大脑 FD 的下降有关。文献中包括 FD 与萎缩无关的疾病相关变化的例子,如果得到证实,将代表比其他结构成像指标更有价值的优势。然而,它可能是非特异性的,并表现出复杂的空间和时间模式。更多的研究采用更加和谐的方法,以及仔细关注与图像处理和 FD 测量相关的技术因素,将有助于更好地阐明该指标的效用。