Division of Clinical Neurosciences, School of Molecular and Clinical Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland, UK.
Eur Radiol. 2012 Mar;22(3):625-32. doi: 10.1007/s00330-011-2284-2. Epub 2011 Sep 25.
To create and evaluate an interactive software tool for measuring imaging data in situations where hand-drawn region-of-interest measurements are unfeasible, for example, when the structure of interest is patchy with ill-defined boundaries.
An interactive grid overlay software tool was implemented that enabled coding of voxels dependent on their imaging appearance with a series of user-defined classes. The Grid Analysis Tool (GAT) was designed to automatically extract quantitative imaging data, grouping the results by tissue class. Inter- and intra-observer reproducibility was evaluated by six observers of various backgrounds in a study of acute stroke patients.
The software tool enabled a more detailed classification of the stroke lesion than would be possible with a region-of-interest approach. However, inter-observer coefficients of variation (CVs) were relatively high, reaching 70% in "possibly abnormal" tissue and around 15-20% in normal appearing tissues, while intra-observer CVs were no more than 13% in "possibly abnormal" tissue and generally less than 1% in normal-appearing tissues.
The grid-overlay method overcomes some of the limitations of conventional Region Of Interest (ROI) approaches, providing a viable alternative for segmenting patchy lesions with ill-defined boundaries, but care is required to ensure acceptable reproducibility if the method is applied by multiple observers.
Computer software developed to overcome limitations of conventional regions of interest measurements • This software is suitable for patchy lesions with ill-defined borders • Allows a more detailed assessment of imaging data.
创建并评估一种交互式软件工具,用于测量在手绘感兴趣区域测量不可行的情况下的成像数据,例如,当感兴趣的结构呈斑片状且边界不明确时。
实现了一种交互式网格覆盖软件工具,该工具允许根据其成像外观使用一系列用户定义的类别对体素进行编码。Grid Analysis Tool(GAT)旨在自动提取定量成像数据,按组织类别对结果进行分组。六位具有不同背景的观察者对急性中风患者进行了研究,评估了该工具的观察者间和观察者内的可重复性。
与使用感兴趣区域方法相比,该软件工具能够对中风病变进行更详细的分类。然而,观察者间的变异系数(CV)相对较高,在“可能异常”组织中达到 70%,在正常表现组织中约为 15-20%,而观察者内的 CV 在“可能异常”组织中不超过 13%,在正常表现组织中通常不超过 1%。
网格叠加方法克服了传统感兴趣区域(ROI)方法的一些限制,为分割具有不明确边界的斑片状病变提供了一种可行的替代方法,但如果该方法由多个观察者应用,则需要注意确保可接受的可重复性。
开发了一种计算机软件来克服传统感兴趣区域测量的局限性•该软件适用于边界不明确的斑片状病变•允许更详细地评估成像数据。