Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK,
Neuroinformatics. 2014 Jul;12(3):405-12. doi: 10.1007/s12021-013-9217-y.
Hippocampal volumetric measures may be useful for Alzheimer's disease (AD) diagnosis and disease tracking; however, manual segmentation of the hippocampus is labour-intensive. Therefore, automated techniques are necessary for large studies and to make hippocampal measures feasible for clinical use. As large studies and clinical centres are moving from using 1.5 Tesla (T) scanners to higher field strengths it is important to assess whether specific image processing techniques can be used at these field strengths. This study investigated whether an automated hippocampal segmentation technique (HMAPS: hippocampal multi-atlas propagation and segmentation) and volume change measures (BSI: boundary shift integral) were as accurate at 3T as at 1.5T. Eighteen Alzheimer's disease patients and 18 controls with 1.5T and 3T scans at baseline and 12-month follow-up were used from the Alzheimer's Disease Neuroimaging Initiative cohort. Baseline scans were segmented manually and using HMAPS and their similarity was measured by the Jaccard index. BSIs were calculated for serial image pairs. We calculated pair-wise differences between manual and HMAPS rates at 1.5T and 3T and compared the SD of these differences at each field strength. The difference in mean Jaccards (manual and HMAPS) between 1.5T and 3T was small with narrow confidence intervals (CIs) and did not appear to be segmentor dependent. The SDs of the difference between volumes from manual and automated segmentations were similar at 1.5T and 3T, with a relatively narrow CI for their ratios. The SDs of the difference between BSIs from manual and automated segmentations were also similar at 1.5T and 3T but with a wider CI for their ratios. This study supports the use of our automated hippocampal voluming methods, developed using 1.5T images, with 3T images.
海马体容积测量可能有助于阿尔茨海默病(AD)的诊断和疾病跟踪;然而,手动分割海马体是一项劳动密集型工作。因此,对于大型研究和使海马体测量适用于临床使用,需要自动化技术。随着大型研究和临床中心从使用 1.5 特斯拉(T)扫描仪转向更高的场强,评估特定的图像处理技术是否可以在这些场强下使用变得非常重要。本研究调查了一种自动化海马体分割技术(HMAPS:海马体多图谱传播和分割)和体积变化测量(BSI:边界移位积分)在 3T 与 1.5T 时的准确性。从阿尔茨海默病神经影像学倡议队列中使用了 18 名阿尔茨海默病患者和 18 名对照者的 1.5T 和 3T 基线和 12 个月随访扫描。基线扫描手动分割,并使用 HMAPS 进行分割,通过 Jaccard 指数测量其相似性。为连续图像对计算 BSI。我们计算了手动和 HMAPS 在 1.5T 和 3T 之间的成对差异,并比较了每个场强下这些差异的 SD。1.5T 和 3T 之间手动和 HMAPS 平均 Jaccard 差异(手动和 HMAPS)的差异较小,置信区间较窄,似乎与分割器无关。手动和自动分割之间体积差异的 SD 在 1.5T 和 3T 时相似,其比值的置信区间较窄。手动和自动分割之间 BSI 差异的 SD 也相似,但其比值的置信区间较宽。这项研究支持使用我们使用 1.5T 图像开发的自动化海马体容积测量方法与 3T 图像一起使用。