Sotirios, Bisdas; Demetriou, Eleni; Topriceanu, Cristian C; Zakrzewska, Zosia; (2020) The role of APT imaging in gliomas grading: A systematic review and meta-analysis. European Journal of Radiology , 133 , Article 109353. 10.1016/j.ejrad.2020.109353.

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Abstract

Purpose: Gliomas are diagnosed and staged by conventional MRI. Although non-conventional sequences such as perfusion-weighted MRI may differentiate low-grade from high-grade gliomas, they are not reliable enough yet. The latter is of paramount importance for patient management. In this regard, we aim to evaluate the role of Amide Proton Transfer (APT) imaging in grading gliomas as a non-invasive tool to provide reliable differentiation across tumour grades. Methods: A systematic search of PubMed, Medline and Embase was conducted to identify relevant publications between 01/01/2008 and 15/09/2020. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess studies’ quality. A random-effects model standardized mean difference meta-analysis was performed to assess APT's ability to differentiate low-grade gliomas (LGGs) from high-grade gliomas (HGGs), WHO 2–4 grades, wild-type from mutated isocitrate dehydrogenase (IDH) gliomas, methylated from unmethylated O6-methylguanine-DNA methyltransferase (MGMT) gliomas. Area under the curve (AUC) of the Receiver Operating Characteristic (ROC) meta-analysis was employed to assess the diagnostic performance of APT. Results: 23 manuscripts met the inclusion criteria and reported the use of APT to differentiate glioma grades with histopathology as reference standard. APT-weighted signal intensity can differentiate LGGs from HGGs with an estimated size effect of (-1.61 standard deviations (SDs), p < 0.0001), grade 2 from grade 3 (-1.83 SDs, p = 0.005), grade 2 from grade 4 (-2.34 SDs, p < 0.0001) and IDH wild-type from IDH mutated (0.94 SDs, p = 0.003) gliomas. The combined AUC of 0.84 highlights the good diagnostic performance of APT-weighted imaging in differentiating LGGs from HGGs. Conclusions: APT imaging is an exciting prospect in differentiating LGGs from HGGs and with potential to predict the histopathological grade. However, more studies are required to optimize and improve its reliability.

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