Diagnostic accuracy of proton magnetic resonance spectroscopy and perfusion-weighted imaging in brain gliomas follow-up: a single institutional experience. Issue 3 (June 2017)

• Record Type: Journal Article
• Authors: Anselmi, Monica; Catalucci, Alessia; Felli, Valentina; Vellucci, Valentina; Di Sibio, Alessandra; Gravina, Giovanni Luca; Di Staso, Mario; Di Cesare, Ernesto; Masciocchi, Carlo
• Is Part Of: Neuroradiology journal. Volume 30:Issue 3(2017:Jun.)
• Page Start: 240
• Page End: 252
• Publication Date: 2017-06
• Subjects: MRI -- 1H-MRS -- glioma -- perfusion MRI -- spectroscopy; Nervous system -- Radiography -- Periodicals; Neuroradiography -- Periodicals; Electronic journals; 616.804757
• DOI: 10.1177/1971400916688354
• Languages: English
• ISSNs: 1971-4009

Abstract

Objectives: The objective of this study was to evaluate whether proton magnetic resonance spectroscopy and perfusion magnetic resonance imaging (MRI) are able to increase diagnostic accuracy in the follow-up of brain gliomas, identifying the progression of disease before it becomes evident in the standard MRI; also to evaluate which of the two techniques has the best diagnostic accuracy. Methods: Eighty-three patients with cerebral glioma (50 high-grade gliomas (HGGs), 33 low-grade gliomas (LGGs)) were retrospectively enrolled. All patients underwent standard MRI, H spectroscopic and perfusion echo-planar imaging MRI. For spectroscopy variations of choline/creatine, choline/N-acetyl-aspartate ratio, and lipids and lactates peak were considered. For perfusion 2.0 was considered the cerebral blood volume cut-off for progression. The combination of functional parameters gave a multiparametric score (0–2) to predict outcome. Diagnostic performance was determined by the receiver operating characteristic curve, with sensitivity, specificity, positive predictive and negative predictive values. Results: In patients with LGGs a combined score of at least 1 was the best predictor for progression (odds ratio (OR) 3.91) with 8.4 months median anticipation of diagnosis compared to standard MRI. The individual advanced magnetic resonance technique did not show a diagnostic accuracy comparable to the combination of the two. Overall diagnostic accuracy area under the curve (AUC) was 0.881. In patients with HGGs the multiparametric score did not improve diagnostic accuracy significantly. Perfusion MRI was the best predictor of progression (OR 3.65), with 6.7 months median anticipation of diagnosis. Overall diagnostic accuracy AUC was 0.897. Then spectroscopy and perfusion MRI are able to identify tumour progression during follow-up earlier than standard MRI. Conclusion: In patients with LGGs the combination of the functional parameters seems to be the best method for diagnosis of progression. In patients with HGGs perfusion is the best diagnostic method.