BACKGROUND AND PURPOSE: In cerebral gliomas, rCBV correlates with tumor grade and histologic findings of vascular proliferation. Moreover, ADC assesses water diffusivity and is inversely correlated with tumor grade. In the present work, we have studied whether combined rCBV and ADC values improve the diagnostic accuracy of MR imaging in the preoperative grading of gliomas. MATERIALS AND METHODS: One hundred sixty-two patients with histopathologically confirmed diffuse gliomas underwent DWI and DSC. Mean rCBV and ADC values were compared among the tumor groups with the Student t test or ANOVA. ROC analysis was used to determine rCBV and ADC threshold values for glioma grading. RESULTS: rCBV had significantly different values between grade II and IV gliomas and between grade III and IV tumors, but there were no significant differences between grade II and III gliomas (P > .05). Grade II and III tumors also did not differ when astrocytomas, oligodendrogliomas, and oligoastrocytomas were considered separately. ADC values were significantly different for all 3 grades. The ADC threshold value of 1.185 × 10(-3) mm(2)/s and the rCBV cutoff value of 1.74 could be used with high sensitivity in the characterization of high-grade gliomas. The area under the ROC curve for the maximum rCBV and minimum ADC was 0.72 and 0.75, respectively. The combination of rCBV and ADC values increased the area under the ROC curve to 0.83. CONCLUSIONS: ADC measurements are better than rCBV values for distinguishing the grades of gliomas. The combination of minimum ADC and maximum rCBV improves the diagnostic accuracy of glioma grading.
BACKGROUND AND PURPOSE: In cerebral gliomas, rCBV correlates with tumor grade and histologic findings of vascular proliferation. Moreover, ADC assesses water diffusivity and is inversely correlated with tumor grade. In the present work, we have studied whether combined rCBV and ADC values improve the diagnostic accuracy of MR imaging in the preoperative grading of gliomas. MATERIALS AND METHODS: One hundred sixty-two patients with histopathologically confirmed diffuse gliomas underwent DWI and DSC. Mean rCBV and ADC values were compared among the tumor groups with the Student t test or ANOVA. ROC analysis was used to determine rCBV and ADC threshold values for glioma grading. RESULTS:rCBV had significantly different values between grade II and IV gliomas and between grade III and IV tumors, but there were no significant differences between grade II and III gliomas (P > .05). Grade II and III tumors also did not differ when astrocytomas, oligodendrogliomas, and oligoastrocytomas were considered separately. ADC values were significantly different for all 3 grades. The ADC threshold value of 1.185 × 10(-3) mm(2)/s and the rCBV cutoff value of 1.74 could be used with high sensitivity in the characterization of high-grade gliomas. The area under the ROC curve for the maximum rCBV and minimum ADC was 0.72 and 0.75, respectively. The combination of rCBV and ADC values increased the area under the ROC curve to 0.83. CONCLUSIONS: ADC measurements are better than rCBV values for distinguishing the grades of gliomas. The combination of minimum ADC and maximum rCBV improves the diagnostic accuracy of glioma grading.
Authors: T Sugahara; Y Korogi; M Kochi; I Ikushima; Y Shigematu; T Hirai; T Okuda; L Liang; Y Ge; Y Komohara; Y Ushio; M Takahashi Journal: J Magn Reson Imaging Date: 1999-01 Impact factor: 4.813
Authors: Thomas C Kwee; Craig J Galbán; Christina Tsien; Larry Junck; Pia C Sundgren; Marko K Ivancevic; Timothy D Johnson; Charles R Meyer; Alnawaz Rehemtulla; Brian D Ross; Thomas L Chenevert Journal: J Magn Reson Imaging Date: 2010-03 Impact factor: 4.813
Authors: R K Gupta; T F Cloughesy; U Sinha; J Garakian; J Lazareff; G Rubino; L Rubino; D P Becker; H V Vinters; J R Alger Journal: J Neurooncol Date: 2000-12 Impact factor: 4.130
Authors: Michael H Lev; Yelda Ozsunar; John W Henson; Amjad A Rasheed; Glenn D Barest; Griffith R Harsh; Markus M Fitzek; E Antonio Chiocca; James D Rabinov; Andrew N Csavoy; Bruce R Rosen; Fred H Hochberg; Pamela W Schaefer; R Gilberto Gonzalez Journal: AJNR Am J Neuroradiol Date: 2004-02 Impact factor: 3.825
Authors: N Sadeghi; N D'Haene; C Decaestecker; M Levivier; T Metens; C Maris; D Wikler; D Baleriaux; I Salmon; S Goldman Journal: AJNR Am J Neuroradiol Date: 2007-12-13 Impact factor: 3.825
Authors: A Hilario; J M Sepulveda; A Perez-Nuñez; E Salvador; J M Millan; A Hernandez-Lain; V Rodriguez-Gonzalez; A Lagares; A Ramos Journal: AJNR Am J Neuroradiol Date: 2014-01-23 Impact factor: 3.825
Authors: A Tietze; M B Hansen; L Østergaard; S N Jespersen; R Sangill; T E Lund; M Geneser; M Hjelm; B Hansen Journal: AJNR Am J Neuroradiol Date: 2015-05-14 Impact factor: 3.825
Authors: Valeria Cuccarini; A Erbetta; M Farinotti; L Cuppini; F Ghielmetti; B Pollo; F Di Meco; M Grisoli; G Filippini; G Finocchiaro; M G Bruzzone; M Eoli Journal: J Neurooncol Date: 2016-01 Impact factor: 4.130
Authors: Reza Farjam; Christina I Tsien; Felix Y Feng; Diana Gomez-Hassan; James A Hayman; Theodore S Lawrence; Yue Cao Journal: Neuro Oncol Date: 2013-12-09 Impact factor: 12.300
Authors: S Fellah; D Caudal; A M De Paula; P Dory-Lautrec; D Figarella-Branger; O Chinot; P Metellus; P J Cozzone; S Confort-Gouny; B Ghattas; V Callot; N Girard Journal: AJNR Am J Neuroradiol Date: 2012-12-06 Impact factor: 3.825
Authors: J Cha; S T Kim; D-H Nam; D-S Kong; H-J Kim; Y K Kim; H Y Kim; G M Park; P Jeon; K H Kim; H S Byun Journal: Clin Neuroradiol Date: 2016-03-07 Impact factor: 3.649