Additional diagnostic role of MRI spectroscopy, diffusion and susceptibility imaging in differentiation of CPA masses: our experience with emphasis on schwannomas and meningiomas

AbstractBackgroundCPA masses are uncommon lesions and usually have quite distinctive imaging features. Still, diagnosis can be challenging in some cases, carrying a significant impact on the choice of treatment and surgical approach. The purpose of this study was to validate the usefulness of MRI spectroscopy, diffusion, and susceptibility in the characterization of CPA masses with the emphasis on the two commonest lesions: schwannomas and meningiomas.ResultsThe study included a total of 27 cases: schwannomas (n= 12), meningiomas (n= 7), epidermoid cysts (n= 2), two chondrosarcomas (n= 2), arachnoid cyst (n= 1), glomus tumor (n= 1), a meningeal metastasis (n= 1), and an endolymphatic sac tumor (n= 1). DWI revealed: eight lesions showed low ADC (<1 × 10−3 mm2/s), 15 lesions with intermediate ADC values (1–1.8 × 10−3 mm2/s), and 4 lesions had high ADC (>1.8 × 10−3 mm2/s.) Meningiomas showed low to intermediate ADC values while schwannomas showed intermediate to high ADC values. A cut-off ADC value of (1 × 10−3 mm2/s) is statistically significant in the differentiation of meningioma from schwannoma. A myoinositol peak was in all 12 schwannomas and single meningioma while 6 meningiomas displayed alanine peak, with a very good statistical significance. Remaining lesions revealed non-specific spectra. SWI made in 18 lesions revealed signal voids in three schwannomas and glomus.ConclusionsThough MRI features of CPA masses are distinctive in most clinical settings; MRI spectroscopy, diffusion, and susceptibility can provide highly informative additional data in problematic cases. An intermediate to high ADC value plus myoinositol peak and signal voids of micro-bleeds are highly suggestive of schwannomas. This is in contrary to meningiomas displaying low to intermediate ADC and an alanine peak with no micro-bleeds. The less common lesions revealed non-specific data.