Egger Karl, Amtage Florian, Yang Shan, Obmann Markus, Schwarzwald Ralf, Köstering Lena, Mader Irina, Koenigsdorf Julia, Weiller Cornelius, Kaller Christoph P, Urbach Horst
Department of Neuroradiology, University Medical Center Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.
Freiburg Brain Imaging Center, University Medical Center Freiburg, Freiburg, Germany.
Clin Neuroradiol. 2018 Mar;28(1):63-67. doi: 10.1007/s00062-016-0523-2. Epub 2016 Jun 22.
Magnetic resonance (MR) relaxometry is of increasing scientific relevance in neurodegenerative disorders but is still not established in clinical routine. Several studies have investigated relaxation time alterations in disease-specific areas in Parkinson's disease (PD), all using manually drawn regions of interest (ROI). Implementing MR relaxometry into the clinical setting involves the reduction of time needed for postprocessing using an investigator-independent and reliable approach. The aim of this study was to evaluate an automated, atlas-based ROI method for evaluating T2* relaxation times in patients with PD.
Automated atlas-based ROI analysis of quantitative T2* maps were generated from 20 PD patients and 20 controls. To test for the accuracy of the atlas-based ROI segmentation, we evaluated the spatial overlap in comparison with manually segmented ROIs using the Dice similarity coefficient (DSC). Additionally, we tested for group differences using our automated atlas-based ROIs of the putamen, globus pallidus, and substantia nigra.
A good spatial overlap accuracy was shown for the automated segmented putamen (mean DSC, 0.64 ± 0.04) and was inferior but still acceptable for the substantia nigra (mean DSC, 0.50 ± 0.17). Based on our automated defined ROI selection, a significant decrease of T2* relaxation time was found in the putamen as well as in the internal and external globus pallidus in PD patients compared with healthy controls.
Automated digital brain atlas-based approaches are reliable, more objective and time-efficient, and therefore have the potential to replace the time-consuming manual drawing of ROIs.
磁共振（MR）弛豫测量法在神经退行性疾病中的科学相关性日益增加，但仍未应用于临床常规检查。多项研究调查了帕金森病（PD）特定疾病区域的弛豫时间变化，均使用手动绘制的感兴趣区域（ROI）。将MR弛豫测量法应用于临床需要采用一种独立于研究者且可靠的方法来减少后处理所需时间。本研究的目的是评估一种基于图谱的自动化ROI方法，用于评估PD患者的T2*弛豫时间。
对20例PD患者和20例对照者的定量T2*图进行基于图谱的自动化ROI分析。为了测试基于图谱的ROI分割的准确性，我们使用Dice相似系数（DSC）评估与手动分割ROI相比的空间重叠情况。此外，我们使用基于图谱的自动化壳核、苍白球和黑质ROI测试组间差异。
自动化分割的壳核显示出良好的空间重叠准确性（平均DSC，0.64±0.04），黑质的准确性较差但仍可接受（平均DSC，0.50±0.17）。基于我们自动定义的ROI选择，与健康对照相比，PD患者的壳核以及苍白球内部和外部的T2*弛豫时间显著降低。
基于数字脑图谱的自动化方法可靠、更客观且省时，因此有可能取代耗时的手动绘制ROI。
