Ashton Edward A, Takahashi Chihiro, Berg Michel J, Goodman Andrew, Totterman Saara, Ekholm Sven
Department of Radiology, University of Rochester Medical Center, Rochester, New York 14580, USA.
J Magn Reson Imaging. 2003 Mar;17(3):300-8. doi: 10.1002/jmri.10258.
To evaluate the accuracy, reproducibility, and speed of two semiautomated methods for quantifying total white matter lesion burden in multiple sclerosis (MS) patients with respect to manual tracing and to other methods presented in recent literature.
Two methods involving the use of MRI for semiautomated quantification of total lesion burden in MS patients were examined. The first method, geometrically constrained region growth (GEORG), requires user specification of lesion location. The second technique, directed multispectral segmentation (DMSS), requires only the location of a single exemplar lesion. Test data sets included both clinical MS data and MS brain phantoms.
The mean processing times were 60 minutes for manual tracing, 10 minutes for region growth, and 3 minutes for directed segmentation. Intra- and interoperator coefficients of variation (CVs) were 5.1% and 16.5% for manual tracing, 1.4% and 2.3% for region growth, and 1.5% and 5.2% for directed segmentation. The average deviations from manual tracing were 9% for region growth and 5.7% for directed segmentation.
Both semiautomated methods were shown to have a significant advantage over manual tracing in terms of speed and precision. The accuracy of both methods was acceptable, given the high variability of the manual results.
评估两种半自动化方法在量化多发性硬化症(MS)患者总白质病变负担方面相对于手动追踪以及近期文献中提出的其他方法的准确性、可重复性和速度。
研究了两种利用MRI对MS患者总病变负担进行半自动化量化的方法。第一种方法,几何约束区域生长(GEORG),需要用户指定病变位置。第二种技术,定向多光谱分割(DMSS),仅需要单个典型病变的位置。测试数据集包括临床MS数据和MS脑模型。
手动追踪的平均处理时间为60分钟,区域生长为10分钟,定向分割为3分钟。手动追踪的操作者内和操作者间变异系数(CV)分别为5.1%和16.5%,区域生长为1.4%和2.3%,定向分割为1.5%和5.2%。相对于手动追踪的平均偏差,区域生长为9%,定向分割为5.7%。
两种半自动化方法在速度和精度方面均显示出相对于手动追踪具有显著优势。鉴于手动结果的高度变异性,两种方法的准确性均可接受。