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A Multiparametric MRI-Based Scoring System for Differentiation Between Pseudoprogression and True Progression in High-Grade Glioma | ||
| Journal of Biomedical Physics and Engineering | ||
| مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 10 خرداد 1405 | ||
| نوع مقاله: Original Research | ||
| نویسندگان | ||
| Mohammad Ghorbani1؛ Mohammad Ali Oghabian* 1، 2؛ Samira Raminfard2، 3؛ Maryam Farsi4؛ Nahid Sadighi3، 4؛ Mostafa Farzin5، 6 | ||
| 1Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran | ||
| 2Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute, Tehran University of Medical Sciences, Tehran, Iran | ||
| 3Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Imam Khomeini Complex Hospital, Tehran University of Medical Sciences, Tehran, Iran | ||
| 4Medical Imaging Center of Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences, Tehran, Iran | ||
| 5Department of Radiation Oncology, Cancer Institute, IKHC, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran | ||
| 6Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Science, Tehran, Iran | ||
| چکیده | ||
| Background: Differentiating Pseudoprogression (PSP) from True Progression (TP) in High-Grade Gliomas (HGGs) is challenging. Integrating parameters from advanced Magnetic Resonance Imaging (MRI) techniques may improve diagnostic performance. Objective: Integrating multiparametric MRI (mp-MRI) with a Multiparametric Scoring System (MSS) may improve PSP-TP differentiation. Material and Methods: In this prospective study, thirty HGG patients with post-standard treatment underwent mp-MRI on a 3T system, including Dynamic Susceptibly Contrast (DSC) MRI, Intravoxel Incoherent Motion (IVIM) MRI, Magnetic Resonance Spectroscopy (MRS), and anatomical imaging. Parametric maps were extracted, registered to anatomical images, and analyzed within a Volume of Interest (VOI) on the enhancing lesion in post-contrast T1-weighted images. Mean VOI values were compared between PSP and TP groups. Statistical analysis identified significant parameters, their Area Under the Curve’s (AUC), and optimal cutoffs, used to assign binary scores (0 or 1) and calculate a sum score for each patient. The diagnostic performance of the sum score was assessed using Receiver Operating Characteristic (ROC) curve analysis against a reference standard determined by follow-up MRI or histopathology when available. Results: nCBV, nCBF, and nMTT from DSC MRI, normalized-D* from IVIM-MRI, and normalized-Cho/Cr from MRS exhibited significantly higher values in the TP group. Normalized-D and -ADC from IVIM-MRI were significantly elevated in the PSP group. The MSS approach, integrating these parameters into a sum score, demonstrated high diagnostic performance with 0.958 AUC, 87.5% sensitivity, and 92.9% specificity for distinguishing PSP from TP. Conclusion: Addressing the limitations of single-parameter MRI approaches, the MSS method effectively integrates mp-MRI parameters to distinguish PSP from TP in HGG patients, enhancing diagnostic performance. | ||
| کلیدواژهها | ||
| Multiparametric Magnetic Resonance Imaging؛ Glioma؛ Brain Neoplasms؛ Multiparametric Scoring System؛ Pseudoprogression؛ Treatment Assessment | ||
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