Semiautomated Volumetric Measurement on Postcontrast MR Imaging for Analysis of Recurrent and Residual Disease in Glioblastoma Multiforme
Semiautomated Volumetric Measurement on Postcontrast MR Imaging for Analysis of Recurrent and Residual Disease in Glioblastoma Multiforme
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DOI：
10.3174/ajnr.a3724
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发表时间：
2014-03-01
影响因子：
3.5
通讯作者：
Filippi, C. G.
中科院分区：
文献类型：
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作者：
Chow, D. S.;Qi, J.;Filippi, C. G.
背景和目的：胶质母细胞瘤患者术后监测的一个局限性是缺乏量化残留和复发疾病的客观指标。对比增强组织的自动化计算机辅助体积分析代表了一种潜在的工具，以帮助放射科医生在这些患者。在这项研究中，我们假设，计算机辅助体积测定法将显示出增加的精度和速度比传统的1D和2D技术在评估残留和/或复发tumor.MATERIALS和METHODS：这项回顾性研究包括本机胶质母细胞瘤与MR成像在2 - 4 -48小时后切除和2-4个月后进行的患者。1D和2D测量由2名神经放射科医生（具有附加资格证书）进行。通过使用手动分割和计算机辅助容量测定法进行容量测定，该方法结合了基于区域的活动轮廓和水平集方法。使用已建立的1D、2D和体积标准品评估肿瘤缓解。比较了手动和计算机辅助容量测定分割时间。观察者之间的相关性确定1D，2D，和容积techniques.RESULTS：29例患者进行了分析。与计算机辅助容量法相比，1D和2D之间疾病状态的差异分别为10.3%（3/29）和17.2%（5/29）。手动和计算机辅助容量测定技术之间的平均分割时间分别为9.7分钟和< 1分钟（P <0.01）。观察者间的相关性最高的是体积测量（0.995; 95% CI，0.990-0.997）与1D相比（0.826; 95% CI，0.695-0.904）和二维（0.905; 95% CI，0.828-0.948）测量值。计算机辅助体积测定法提供了一种可重复的和更快的增强肿瘤负荷的体积评估，这对治疗试验中监测疾病进展和量化肿瘤负荷具有影响。
BACKGROUND AND PURPOSE:A limitation in postoperative monitoring of patients with glioblastoma is the lack of objective measures to quantify residual and recurrent disease. Automated computer-assisted volumetric analysis of contrast-enhancing tissue represents a potential tool to aid the radiologist in following these patients. In this study, we hypothesize that computer-assisted volumetry will show increased precision and speed over conventional 1D and 2D techniques in assessing residual and/or recurrent tumor.MATERIALS AND METHODS:This retrospective study included patients with native glioblastomas with MR imaging performed at 24-48 hours following resection and 2-4 months postoperatively. 1D and 2D measurements were performed by 2 neuroradiologists with Certificates of Added Qualification. Volumetry was performed by using manual segmentation and computer-assisted volumetry, which combines region-based active contours and a level set approach. Tumor response was assessed by using established 1D, 2D, and volumetric standards. Manual and computer-assisted volumetry segmentation times were compared. Interobserver correlation was determined among 1D, 2D, and volumetric techniques.RESULTS:Twenty-nine patients were analyzed. Discrepancy in disease status between 1D and 2D compared with computer-assisted volumetry was 10.3% (3/29) and 17.2% (5/29), respectively. The mean time for segmentation between manual and computer-assisted volumetry techniques was 9.7 minutes and < 1 minute, respectively (P < .01). Interobserver correlation was highest for volumetric measurements (0.995; 95% CI, 0.990-0.997) compared with 1D (0.826; 95% CI, 0.695-0.904) and 2D (0.905; 95% CI, 0.828-0.948) measurements.CONCLUSIONS:Computer-assisted volumetry provides a reproducible and faster volumetric assessment of enhancing tumor burden, which has implications for monitoring disease progression and quantification of tumor burden in treatment trials.