Johnson L A, Pearlman J D, Miller C A, Young T I, Thulborn K R
Nuclear Magnetic Resonance Center, Massachusetts General Hospital, Charlestown 02129.
AJNR Am J Neuroradiol. 1993 Nov-Dec;14(6):1373-8.
A semiautomated border identification algorithm, insensitive to user bias, is evaluated for accuracy and speed in the measurement of ventricular volumes from three-dimensional MR images.
A three-dimensional gradient-echo technique was implemented on a Signa clinical imaging system. Data from phantoms and patients were analyzed for volume using a segmentation algorithm designed with: 1) correction for partial volume averaging; 2) insensitivity to user bias; and 3) speed. Accuracy, precision, and intra- and interobserver variability were determined.
Average error for phantom studies was 4% to 6%, or 1 to 2 cc across the volumes, which ranged from normal to mild hydrocephalus (< 60 cc). Patient studies showed intra- and interobserver error of 2.3% and 7.8%, respectively. The correction for partial volume averaging resulted in a threefold decrease in error. Data were acquired and reconstructed within 7 minutes. Experienced radiologists required less than 15 minutes to perform each analysis.
This algorithm allows accurate measurement of ventricular volumes in an efficient, minimally supervised manner.
评估一种对用户偏差不敏感的半自动边界识别算法在从三维磁共振图像测量心室容积时的准确性和速度。
在Signa临床成像系统上实施三维梯度回波技术。使用设计的分割算法分析来自体模和患者的数据以获取容积，该算法具有：1）部分容积平均校正；2）对用户偏差不敏感；3）速度快。确定准确性、精密度以及观察者内和观察者间的变异性。
体模研究的平均误差为4%至6%，或在所测量的容积范围内为1至2立方厘米，容积范围从正常到轻度脑积水（<60立方厘米）。患者研究显示观察者内和观察者间误差分别为2.3%和7.8%。部分容积平均校正使误差降低了三倍。数据采集和重建在7分钟内完成。经验丰富的放射科医生进行每次分析所需时间不到15分钟。
该算法能够以高效、最少监督的方式准确测量心室容积。
