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
Investigative Magnetic Resonance Imaging
; : 9-19, 2017.
Article
en En
| WPRIM
| ID: wpr-225906
Biblioteca responsable:
WPRO
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 ANDMETHODS:
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.Palabras clave
Texto completo:
1
Banco de datos:
WPRIM
Asunto principal:
Perfusión
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Biopsia
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Volumen Sanguíneo
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Neoplasias Encefálicas
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Imagen por Resonancia Magnética
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Sistema Nervioso Central
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Curva ROC
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Glioblastoma
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Área Bajo la Curva
/
Diagnóstico Diferencial
Tipo de estudio:
Diagnostic_studies
/
Guideline
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Investigative Magnetic Resonance Imaging
Año:
2017
Tipo del documento:
Article