Volume 28, Issue 5 (Iran South Med J 2026)                   Iran South Med J 2026, 28(5): 838-849 | Back to browse issues page


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Honarmandi M, Zakariaee S S. Diagnostic Performance of Semi-Quantitative Indices of Dynamic T1-Weighted Magnetic Resonance Imaging for Presurgical Glioma Grading. Iran South Med J 2026; 28 (5) :838-849
URL: http://ismj.bpums.ac.ir/article-1-2452-en.html
1- Department of Radiology, School of Medicine, Ilam University of Medical Sciences, Ilam, Iran
2- Department of Medical Physics, School of Paramedical Sciences, Ilam University of Medical Sciences, Ilam, Iran , zakariaee-s@medilam.ac.ir
Abstract:   (111 Views)
Background: In recent years, complementary methods, including imaging-based approaches, have been proposed for better grading of glioma tumors due to the inherent limitations of histopathology as the standard method. This study aimed to determine the diagnostic performance of semi-quantitative parameters of dynamic T1-weighted magnetic resonance imaging (T1W-MRI) for presurgical glioma grading.
Materials and Methods: Patients with brain tumors referred to the imaging department of a referral cancer center between February 2021 and July 2023 were retrospectively reviewed. Thirty-one patients with glioma confirmed by pathology results met the inclusion criteria. The mean age of the patients was 39.2±1.14 years, and 18 participants were male (58.06%). Semi-quantitative parameters (IAUC, Peak, and Initial Slope) were quantified using dynamic T1W-MRI data. The Mann-Whitney U test was used to assess the significance of the difference between these parameters in different grades of glioma. The performance of these parameters for glioma grading was evaluated using receiver operating characteristic (ROC) curve analysis.
Results: IAUC, Peak, and Initial slope parameters showed significant differences between different glioma grades (P≤0.041), and the results indicated that IAUC had the best grading performance compared to the other studied parameters.
Conclusion: Semi-quantitative parameters quantified using dynamic T1W-MRI are valuable indices that can reliably discriminate between glioma grades. These non-invasive physiological imaging parameters can serve as a powerful complement to the standard histopathological grading system.
Full-Text [PDF 658 kb]   (51 Downloads)    
Type of Study: Original | Subject: Radiology
Received: 2025/11/23 | Accepted: 2026/02/24 | Published: 2026/05/25

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