Looi Jeffrey Chee Leong, Lindberg Olof, Liberg Benny, Tatham Vanessa, Kumar Rajeev, Maller Jerome, Millard Ellen, Sachdev Perminder, Högberg Göran, Pagani Marco, Botes Lisa, Engman Eva-Lena, Zhang Yi, Svensson Leif, Wahlund Lars-Olof
Research Centre for the Neurosciences of Ageing, Academic Unit of Psychological Medicine, Australian National University Medical School, The Canberra Hospital, Australian Capital Territory, Australia.
Psychiatry Res. 2008 Aug 30;163(3):279-88. doi: 10.1016/j.pscychresns.2007.07.005. Epub 2008 Jul 25.
Our aim was to develop a reliable and valid manual segmentation protocol for tracing the caudate nucleus in MRI for volumetric and, potentially, shape analysis of the caudate. Using the protocol, two inter- and intra-rater reliability studies were conducted using five different raters on two different image analysis platforms (ANALYZE, Mayo Biomedical Imaging Resource, Rochester MN, USA, and HERMES, Nuclear Diagnostics AB, Stockholm, Sweden). Reference images for the detailed protocol are described. Two studies were performed. In study 1, the intra-rater class correlation ICC(1,1) for an experienced rater (JCLL) using this protocol for caudate nucleus volumes was evaluated by repeating right and left caudate measurements on 10 scans (20 comparisons) and was 0.972. The inter-rater class correlation ICC(1,k) with OL was 0.922 on 5 scans (10 comparisons) and with BL was 0.960 on 5 scans (10 comparisons). In study 2, VT obtained an intra-rater class correlation of 0.9 on 5 scans (involving 10 comparisons, e.g. right and left caudate). The inter-rater class correlation ICC(1,k) was 0.988 on 5 scans (again involving 10 comparisons) with EM. We therefore developed a novel, reliable and reference image-based, method of outlining the caudate nucleus on axial MRI scans, usable in two different image analysis laboratories, across two different sets number of tracers reliably, and across software platforms. This method is therefore potentially usable for any image analysis package capable of displaying and measuring outlined voxels from MRI brain scans.
我们的目标是开发一种可靠且有效的手动分割方案,用于在磁共振成像(MRI)中追踪尾状核,以便对尾状核进行体积分析以及可能的形状分析。使用该方案,在两个不同的图像分析平台(美国明尼苏达州罗切斯特市梅奥生物医学成像资源中心的ANALYZE和瑞典斯德哥尔摩核诊断公司的HERMES)上,由五名不同的评估者进行了两项评估者间和评估者内可靠性研究。描述了详细方案的参考图像。进行了两项研究。在研究1中,通过对10次扫描(20次比较)重复测量右、左尾状核体积,评估了一名经验丰富的评估者(JCLL)使用该方案时的评估者内组内相关系数ICC(1,1),结果为0.972。在5次扫描(10次比较)中,与OL的评估者间组内相关系数ICC(1,k)为0.922,与BL的评估者间组内相关系数ICC(1,k)在5次扫描(10次比较)中为0.960。在研究2中,VT在5次扫描(涉及10次比较,如右、左尾状核)中获得了0.9的评估者内组内相关系数。在5次扫描(同样涉及10次比较)中,与EM的评估者间组内相关系数ICC(1,k)为0.988。因此,我们开发了一种基于参考图像的新颖、可靠的方法,用于在轴向MRI扫描上勾勒尾状核,该方法可在两个不同的图像分析实验室中可靠地用于两组不同数量的追踪器,并可跨软件平台使用。因此,该方法可能适用于任何能够显示和测量MRI脑部扫描中勾勒出的体素的图像分析软件包。