The cortical thickness has been used as a biomarker to assess different cerebral conditions and to detect alterations in the cortical mantle. In this work, we compare methods from the FreeSurfer software, the Computational Anatomy Toolbox (CAT12), a Laplacian approach and a new method here proposed, based on the Euclidean Distance Transform (EDT), and its corresponding computational phantom designed to validate the calculation algorithm. At region of interest (ROI) level, within- and inter-method comparisons were carried out with a test–retest analysis, in a subset comprising 21 healthy subjects taken from the Multi-Modal MRI Reproducibility Resource (MMRR) dataset. From the Minimal Interval Resonance Imaging in Alzheimer’s Disease (MIRIAD) data, classification methods were compared in their performance to detect cortical thickness differences between 23 healthy controls (HC) and 45 subjects with Alzheimer’s disease (AD). The validation of the proposed EDT-based method showed a more accurate and precise distance measurement as voxel resolution increased. For the within-method comparisons, mean test–retest measures (percentages differences/intraclass correlation/Pearson correlation) were similar for FreeSurfer (1.80%/0.90/0.95), CAT12 (1.91%/0.83/0.91), Laplacian (1.27%/0.89/0.95) and EDT (2.20%/0.88/0.94). Inter-method correlations showed moderate to strong values (R > 0.77) and, in the AD comparison study, all methods were able to detect cortical alterations between groups. Surface- and voxel-based methods have advantages and drawbacks regarding computational demands and measurement precision, while thickness definition was mainly associated to the cortical thickness absolute differences among methods. However, for each method, measurements were reliable, followed similar trends along the cortex and allowed detection of cortical atrophies between HC and patients with AD.

皮层厚度已被用作生物标志物，以评估不同的大脑状况并检测皮层的变化。在这项工作中，我们比较了FreeSurfer软件，计算解剖工具箱（CAT12），拉普拉斯方法和此处提出的基于欧氏距离变换（EDT）的新方法的方法，以及旨在验证计算结果的相应计算模型。算法。在感兴趣区域（ROI）级别，使用测试-再测试分析对方法内和方法间进行了比较，该子集中包括从多模态MRI再现性资源（MMRR）数据集中获取的21名健康受试者。根据阿尔茨海默氏病的最小间隔共振成像（MIRIAD）数据，比较了分类方法的性能，以检测23名健康对照（HC）和45名患有阿尔茨海默氏病（AD）的受试者之间的皮层厚度差异。所提出的基于EDT的方法的验证显示，随着体素分辨率的提高，距离测量更加精确。对于方法内比较，FreeSurfer（1.80％/ 0.90 / 0.95），CAT12（1.91％/ 0.83 / 0.91），Laplacian（1.27％/ 0.89 / 0.95）和EDT（2.20％/ 0.88 / 0.94）。方法间的相关性显示中等至强值（R> 0.77），在AD比较研究中，所有方法均能够检测组之间的皮层变化。基于表面和体素的方法在计算需求和测量精度方面具有优缺点，而厚度定义主要与方法之间的皮质厚度绝对差异有关。但是，对于每种方法，测量结果都是可靠的，沿着皮质的趋势类似，并且可以检测出HC和AD患者之间的皮质萎缩。