Diffusion-weighted imaging does not predict histological grading in meningiomas
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This study aims to verify the reliability of diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) measurements to differentiate benign from atypical/malignant meningiomas and among different sub-types.
Pre-operative DWI of 102 patients (74 females, mean age 58 years, age range 34–85 years) affected by a pathologically proven intracranial meningioma were retrospectively reviewed. DWI signal intensity of tumors was classified as hypo-, iso- or hyper-intense to grey matter. ADC values and normalised ADCratio (ADCmeningioma/ADCnormal appearing white matter) of the neoplastic tissue (avoiding calcifications and cystic or necrotic areas) were measured by two neuroradiologists unaware of each others’ reading. MRI and histological findings were compared.
Meningiomas were histologically graded as malignant (1%), atypical (21.5%) and benign (77.5%). Meningothelial, transitional and fibrous were the most frequent benign sub-types (44, 16 and 10 cases, respectively). There was no statistical difference between typical and atypical/malignant meningiomas when considering mean ADC values (0.964 ± 0.192 × 10−3 vs 0.923 ± 0.085 × 10−3 cm2/s, p = 0.3 t-Student) or ADCratio (1.266 ± 0.290 vs 1.185 ± 0.115, p = 0.2 t-Student). ADC values or ADCratio did not differ significantly among meningioma sub-types although a nearly significant difference was found between meningothelial and transitional (post hoc analysis p = 0.06). Inter-observer agreement of ADC and ADCratio measurements was high (r = 0.95 and 0.92, respectively, Pearson’s linear coefficient). DWI intensity did not reach a significant correlation with meningioma’s grading (p = 0.08).
According to our study, DWI and ADC measurement do not seem reliable in grading meningiomas or identifying histological sub-types. Hence, these parameters should not be recommended for surgical or treatment planning.
KeywordsMeningioma DWI ADC Brain MRI Grading
We thank Mr. Valerio Gerunda for his excellent technical support. This work was supported in part by Grant Ricerca Finalizzata 2008 from Regione Veneto to Prof. d’Avella.
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