Assessing the effectiveness of amide proton transfer MR imaging in the characterization of meningiomas and glioblastomas

Abstract

This study evaluates the diagnostic accuracy of Amide Proton Transfer (APT) Magnetic Resonance Imaging (MRI) for differentiating meningiomas and glioblastomas, two primary brain tumors with distinct clinical profiles and implications for treatment. While conventional MRI and CT remain widely used diagnostic tools, their limitations in sensitivity and specificity often lead to challenges in accurate tumor characterization. APT MRI, as an advanced imaging modality, leverages molecular and metabolic insights by detecting variations in protein and peptide concentrations, potentially addressing these diagnostic gaps. In a retrospective analysis of 61 patients, the diagnostic performance of APT MRI was assessed and compared with conventional MRI and CT scans. The analysis included quantitative metrics such as tumor core and peritumoral APT values (APTmin, APTmax, APTmean), providing a detailed evaluation of tumor heterogeneity and metabolic activity. APT MRI achieved sensitivity and specificity rates of 66.7% and 88%, respectively, for meningiomas, and 72% and 83.3% for glioblastomas. Receiver Operating Characteristic (ROC) curve analysis demonstrated Area Under the Curve (AUC) values of 0.53 for APT MRI and 0.54 for conventional MRI, while CT scan exhibited an AUC of 0.44. These values suggest that conventional MRI slightly outperforms APT MRI in differentiating meningiomas and glioblastomas, whereas CT scan showed suboptimal diagnostic performance. The relatively modest AUC values across all modalities underscore the need for further refinement in imaging protocols and diagnostic strategies. Despite the moderate diagnostic performance observed in this study, APT MRI demonstrated potential as a complementary imaging tool, particularly when integrated with conventional imaging techniques. The addition of APT MRI improved sensitivity and specificity in detecting glioblastomas and meningiomas, particularly in delineating tumor boundaries and identifying peritumoral infiltration areas where conventional imaging often struggles. This study underscores the potential of APT MRI to supplement conventional imaging by providing molecular-level insights that enhance tumor classification and treatment planning. However, the variability in performance metrics necessitates further investigation to optimize imaging protocols and establish standardized diagnostic criteria. Future research should focus on larger, more diverse patient cohorts and comparative studies to clarify APT MRI's role in neuro-oncology diagnostics. While this study demonstrates APT MRI's potential to refine diagnostic workflows for brain tumors, it also emphasizes the need for continued advancements to fully harness its clinical utility.