• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.785-788
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• 2024

This study describes a unique case of single mucin-rich brain metastasis in a patient with breast cancer, mimicking the T2-fluid attenuation inversion recovery (FLAIR) mismatch sign and masquerading as an isocitrate dehydrogenase-mutant astrocytoma. This case highlights the importance of considering mucin-rich lesions in the differential diagnosis of intracranial tumors exhibiting T2-FLAIR mismatch. Clinicians must recognize the potential convergence in imaging characteristics between these metastases and gliomas to guarantee prompt and accurate patient care.

• Investigative Magnetic Resonance Imaging
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• v.20 no.2
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• pp.88-94
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• 2016

Purpose: Fluid-attenuated inversion recovery (FLAIR) imaging can be obtained faster with shorter repletion time (TR), but it gets noisier. We hypothesized that shorter-TR FLAIR obtained at 3 tesla (3T) with a 32-channel coil may be comparable to conventional FLAIR. The aim of this study was to compare the diagnostic value between conventional FLAIR (TR = 9000 ms, FLAIR9000) and shorter-TR FLAIR (TR = 6000 ms, FLAIR6000) at 3T in terms of diffusion-weighted imaging-FLAIR mismatch. Materials and Methods: We recruited 184 patients with acute ischemic stroke (28 patients < 4.5 hours) who had undergone 5-mm diffusion-weighted imaging (DWI) and two successive 5-mm FLAIR images (no gap; in-plane resolution, $0.9{\times}0.9mm$) at 3T with a 32-channel coil. The acquisition times for FLAIR9000 and FLAIR6000 were 108 seconds (generalized autocalibrating partially parallel acquisitions [GRAPPA] = 2) and 60 seconds (GRAPPA = 3), respectively. Two radiologists independently assessed the paired imaging sets (DWI-FLAIR9000 and DWI-FLAIR6000) for the presence of matched hyperintense lesions on each FLAIR imaging. The signal intensity ratios (area of DWI lesion to contralateral normal-appearing region) on both FLAIR imaging sets were compared. Results: DWI-FLAIR9000 mismatch was present in 39 of 184 (21.2%) patients, which was perfectly the same on FLAIR6000. Three of 145 patients (2%) with DWI-matched lesions on FLAIR9000 had discrepancy on FLAIR6000, showing no significant difference (P > 0.05). Interobserver agreement was excellent for both DWI-FLAIR9000 and DWI-FLAIR6000 (k = 0.904 and 0.883, respectively). Between the two FLAIR imaging sets, there was no significant difference of signal intensity ratio (mean, standard deviation; $1.25{\pm}0.20$; $1.24{\pm}0.20$, respectively) (P > 0.05). Conclusion: For the determination of mismatch or match between DWI and FLAIR imaging, there is no significant difference between FLAIR9000 and FLAIR6000 at 3T with a 32-channel coil.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.772-783
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• 2023

Objective: Imaging-based survival stratification of patients with gliomas is important for their management, and the 2021 WHO classification system must be clinically tested. The aim of this study was to compare integrative imaging- and pathology-based methods for survival stratification of patients with diffuse glioma. Materials and Methods: This study included diffuse glioma cases from The Cancer Genome Atlas (training set: 141 patients) and Asan Medical Center (validation set: 131 patients). Two neuroradiologists analyzed presurgical CT and MRI to assign gliomas to five imaging-based risk subgroups (1 to 5) according to well-known imaging phenotypes (e.g., T2/FLAIR mismatch) and recategorized them into three imaging-based risk groups, according to the 2021 WHO classification: group 1 (corresponding to risk subgroup 1, indicating oligodendroglioma, isocitrate dehydrogenase [IDH]-mutant, and 1p19q-codeleted), group 2 (risk subgroups 2 and 3, indicating astrocytoma, IDH-mutant), and group 3 (risk subgroups 4 and 5, indicating glioblastoma, IDHwt). The progression-free survival (PFS) and overall survival (OS) were estimated for each imaging risk group, subgroup, and pathological diagnosis. Time-dependent area-under-the receiver operating characteristic analysis (AUC) was used to compare the performance between imaging-based and pathology-based survival model. Results: Both OS and PFS were stratified according to the five imaging-based risk subgroups (P < 0.001) and three imaging-based risk groups (P < 0.001). The three imaging-based groups showed high performance in predicting PFS at one-year (AUC, 0.787) and five-years (AUC, 0.823), which was similar to that of the pathology-based prediction of PFS (AUC of 0.785 and 0.837). Combined with clinical predictors, the performance of the imaging-based survival model for 1- and 3-year PFS (AUC 0.813 and 0.921) was similar to that of the pathology-based survival model (AUC 0.839 and 0.889). Conclusion: Imaging-based survival stratification according to the 2021 WHO classification demonstrated a performance similar to that of pathology-based survival stratification, especially in predicting PFS.