PT  - JOURNAL ARTICLE
AU  - Chow, D.S.
AU  - Qi, J.
AU  - Guo, X.
AU  - Miloushev, V.Z.
AU  - Iwamoto, F.M.
AU  - Bruce, J.N.
AU  - Lassman, A.B.
AU  - Schwartz, L.H.
AU  - Lignelli, A.
AU  - Zhao, B.
AU  - Filippi, C.G.
TI  - Semiautomated Volumetric Measurement on Postcontrast MR Imaging for Analysis of Recurrent and Residual Disease in Glioblastoma Multiforme
AID  - 10.3174/ajnr.A3724
DP  - 2014 Mar 01
TA  - American Journal of Neuroradiology
PG  - 498--503
VI  - 35
IP  - 3
4099  - http://www.ajnr.org/content/35/3/498.short
4100  - http://www.ajnr.org/content/35/3/498.full
SO  - Am. J. Neuroradiol.2014 Mar 01; 35
AB  - 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. CAVcomputer-assisted volumetryGBMglioblastoma multiformeRANOResponse Assessment in Neuro-Oncology