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CT图像上颅内总体积的体视学估计

Stereological estimation of total intracranial volume on CT images.

作者信息

Mazonakis Michael, Karampekios Spyros, Damilakis John, Voloudaki Argyro, Gourtsoyiannis Nicholas

机构信息

Department of Medical Physics, Division of Radiology, University Hospital of Iraklion, P.O. Box 1352, 71110 Iraklion, Crete, Greece.

出版信息

Eur Radiol. 2004 Jul;14(7):1285-90. doi: 10.1007/s00330-004-2253-0. Epub 2004 Feb 6.

DOI:10.1007/s00330-004-2253-0
PMID:14767605
Abstract

This study aims to investigate the possibility of generating stereological estimations of total intracranial volume (TIV) on CT scans. The study group included 16 consecutive patients referred for a cranial CT examination. The TIV was estimated using the stereological point counting technique. Volume measurements were optimized by systematically sampling CT sections and by defining an optimum spacing between test points of the grid. The intraobserver and interobserver variability of the optimized volumetric technique was determined. Stereological TIV estimations were compared with the respective planimetric measurements. The application of a test grid with a point spacing of 2.4 cm on 6-8 systematically sampled CT sections provided TIV estimations with a coefficient of error of less than 5%. The intraobserver and interobserver coefficient of variation values were found to be 2.4 and 4.0%, respectively. The 95% limits of agreement between stereological and planimetric TIV measurements were equal to -91.4 and 103.4 cm3. The mean time (+/- SD) needed to obtain stereological TIV estimations was 2.9 +/- 0.6 min. The application of the optimized stereological technique on CT scans enables the efficient estimation of TIV.

摘要

本研究旨在探讨在CT扫描上生成颅内总体积(TIV)体视学估计值的可能性。研究组包括16例连续接受头颅CT检查的患者。使用体视学点计数技术估计TIV。通过系统地对CT切片进行采样并定义网格测试点之间的最佳间距来优化体积测量。确定了优化体积技术的观察者内和观察者间变异性。将体视学TIV估计值与相应的平面测量值进行比较。在6 - 8个系统采样的CT切片上应用点间距为2.4 cm的测试网格,提供的TIV估计值误差系数小于5%。观察者内和观察者间变异系数值分别为2.4%和4.0%。体视学和平面测量TIV之间的95%一致性界限等于 -91.4和103.4 cm³。获得体视学TIV估计值所需的平均时间(±标准差)为2.9 ± 0.6分钟。在CT扫描上应用优化的体视学技术能够有效地估计TIV。

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