Investig Magn Reson Imaging.  2017 Mar;21(1):9-19. 10.13104/imri.2017.21.1.9.

Differentiation between Glioblastoma and Primary Central Nervous System Lymphoma Using Dynamic Susceptibility Contrast-Enhanced Perfusion MR Imaging: Comparison Study of the Manual versus Semiautomatic Segmentation Method

• Kim YE
• Choi SH
• Lee ST
• Kim TM
• Park CK
• Park SH
• Kim IH

• KMID: 2376264
• DOI: http://doi.org/10.13104/imri.2017.21.1.9

Abstract

BACKGROUND
Normalized cerebral blood volume (nCBV) can be measured using manual or semiautomatic segmentation method. However, the difference in diagnostic performance on brain tumor differentiation between differently measured nCBV has not been evaluated. PURPOSE: To compare the diagnostic performance of manually obtained nCBV to that of semiautomatically obtained nCBV on glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) differentiation.
MATERIALS AND METHODS
Histopathologically confirmed forty GBM and eleven PCNSL patients underwent 3T MR imaging with dynamic susceptibility contrast-enhanced perfusion MR imaging before any treatment or biopsy. Based on the contrast-enhanced T1-weighted imaging, the mean nCBV (mCBV) was measured using the manual method (manual mCBV), random regions of interest (ROIs) placement by the observer, or the semiautomatic segmentation method (semiautomatic mCBV). The volume of enhancing portion of the tumor was also measured during semiautomatic segmentation process. T-test, ROC curve analysis, Fisher's exact test and multivariate regression analysis were performed to compare the value and evaluate the diagnostic performance of each parameter.
RESULTS
GBM showed a higher enhancing volume (P = 0.0307), a higher manual mCBV (P = 0.018) and a higher semiautomatic mCBV (P = 0.0111) than that of the PCNSL. Semiautomatic mCBV had the highest value (0.815) for the area under the curve (AUC), however, the AUCs of the three parameters were not significantly different from each other. The semiautomatic mCBV was the best independent predictor for the GBM and PCNSL differential diagnosis according to the stepwise multiple regression analysis.
CONCLUSION
We found that the semiautomatic mCBV could be a better predictor than the manual mCBV for the GBM and PCNSL differentiation. We believe that the semiautomatic segmentation method can contribute to the advancement of perfusion based brain tumor evaluation.

Keyword

Glioblastoma (GBM); Primary central nervous system lymphoma (PCNSL); Perfusion; Dynamic susceptibility; contrast-enhanced perfusion MR imaging (DSC-PWI); Semiautomatic segmentation

MeSH Terms

Area Under Curve
Biopsy
Blood Volume
Brain Neoplasms
Central Nervous System*
Diagnosis, Differential
Glioblastoma*
Humans
Lymphoma*
Magnetic Resonance Imaging*
Methods*
Perfusion*
ROC Curve

Figure

• 

  Fig. 1 Flowchart of patient selection. Patients who received MR imaging with perfusion at 3T scanner before any treatment or biopsy from January 2011 to July 2013 were selected and enrolled in the study. DSC PWI = dynamic susceptibility contrast-enhanced perfusion magnetic resonance imaging; GBM = glioblastoma; MR = magnetic resonance; PCNSL = primary central nervous system lymphoma; WHO = World Health Organization

• 

  Fig. 2 Flowchart summarizing the manual and semiautomatic segmentation method. (a) Contrast enhanced T1 weighted images and nCBV maps were co-registered in a patient with glioblastoma. After making the overlaid structural image 100% opaque, a 3.52 mm2 sized region of interest (ROI) was randomly drawn on each axial plane of co-registered images. In total, 5 to 10 ROIs were drawn in each tumor (Red-shaded area on the last picture) and were analyzed to measure the manual mCBV. (b) Contrast enhanced T1 weighted images and perfusion images were co-registered. Tissue within the manually defined volume of interest (VOI) is automatically segmented into six clusters. The combination of clusters depicting the tumor best is selected, and non-tumor regions are erased manually. Semiautomatically processed VOI of each tumor (Red-shaded area on the last picture) was analyzed to measure the semiautomatic mCBV.

• 

  Fig. 3 A 66-year-old man with a glioblastoma in the right high frontal lobe. The mass shows high signal intensity on T2 FLAIR (a), increased CBV of 4.3 (manual mCBV) and 2.34 (semiautomatic mCBV) (b) and heterogeneous enhancement (c and d).

• 

  Fig. 4 A 72-year-old woman with a primary central nervous system lymphoma in the right periventricular region of the parietooccipital lobe and corpus callosum splenium. The mass lesion shows high signal intensity on the T2 FLAIR image (a), a low CBV of 1.33 (manual mCBV) and 1.03 (semiautomatic mCBV) (b), and homogeneous enhancement (c and d).

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