Unusual MRI abnormality in patients with nonketotic hyperglycaemia-associated seizures.

Nonketotic hyperglycaemia (NKH) is a metabolic disorder typically observed in individuals with inadequately managed or undiagnosed diabetes mellitus (DM). Seizures are a common clinical presentation in NKH, and they tend to respond better to glucose correction than anticonvulsant therapy. MRI scans may reveal both subcortical T2/fluid-attenuated inversion recovery (FLAIR) imaging hypointensity and cortical changes, including cortical grey matter T2/FLAIR imaging hyperintensity and cortical or leptomeningeal enhancement, although cortical abnormalities are less frequently observed. These alterations are reversible when the underlying metabolic disturbance is effectively addressed. We suggest the role of iron accumulation as a mechanism for subcortical T2 hypointensity using T2* weighted imaging. Our cases substantiate the significance of subcortical T2/FLAIR hypointensity as a fundamental feature of this condition. In the appropriate clinical context, the recognition of these MRI abnormalities can help prevent misdiagnosis and facilitate timely treatment.

Utilizing Radiomics of Peri-Lesional Edema in T2-FLAIR Subtraction Digital Images to Distinguish High-Grade Glial Tumors From Brain Metastasis.

BACKGROUND: Differentiating high-grade glioma (HGG) and isolated brain metastasis (BM) is important for determining appropriate treatment. Radiomics, utilizing quantitative imaging features, offers the potential for improved diagnostic accuracy in this context. PURPOSE: To differentiate high-grade (grade 4) glioma and BM using machine learning models from radiomics data obtained from T2-FLAIR digital subtraction images and the peritumoral edema area. STUDY TYPE: Retrospective. POPULATION: The study included 1287 patients. Of these, 602 were male and 685 were female. Of the 788 HGG patients included in the study, 702 had solitary masses. Of the 499 BM patients included in the study, 112 had solitary masses. Initially, the model was developed and tested on solitary masses. Subsequently, the model was developed and tested separately for all patients (solitary and multiple masses). FIELD STRENGTH/SEQUENCE: Axial T2-weighted fast spin-echo sequence (T2WI) and T2-weighted fluid-attenuated inversion recovery sequence (T2-FLAIR), using 1.5-T and 3.0-T scanners. ASSESSMENT: Radiomic features were extracted from digitally subtracted T2-FLAIR images in the area of peritumoral edema. The maximum relevance-minimum redundancy (mRMR) method was then used for dimensionality reduction. The naive Bayes algorithm was used in model development. The interpretability of the model was explored using SHapley Additive exPlanations (SHAP). STATISTICAL TESTS: Chi-square test, one-way analysis of variance, and Kruskal-Wallis test were performed. The P values <0.05 were considered statistically significant. The performance metrics include area under curve (AUC), sensitivity (SENS), and specificity (SPEC). RESULTS: The mean age of HGG patients was 61.4 ± 13.2 years and 61.7 ± 12.2 years for BM patients. In the external validation cohort, the model achieved AUC: 0.991, SENS: 0.983, and SPEC: 0.922. The external cohort results for patients with solitary lesions were AUC: 0.987, SENS: 0.950, and SPEC: 0.922. DATA CONCLUSION: The artificial intelligence model, developed with radiomics data from the peritumoral edema area in T2-FLAIR digital subtraction images, might be able to differentiate isolated BM from HGG. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

AB084. T2-fluid-attenuated inversion recovery (T2-FLAIR) mismatch as predictive MRI findings of diffuse astrocytoma: a case report.

BACKGROUND: Diffuse astrocytomas are a subtype of astrocytic tumors classified as World Health Organization (WHO) grade II tumors. Magnetic resonance imaging is a useful diagnostic tool for assessing diffuse astrocytomas. However, their growth pattern resembles other low-grade gliomas, such as oligodendroglioma. The potential magnetic resonance imaging (MRI) feature, T2-fluid-attenuated inversion recovery (T2-FLAIR) mismatch, may be predictive in identifying diffuse astrocytomas. This involves a hyperintense signal in T2-weighted and a hypointense signal in T2-FLAIR, which oligodendroglioma does not exhibit. CASE DESCRIPTION: A 30-year-old female seeks medical advice regarding her complaint of persistent headaches. The clinical findings suggested an anaplastic oligodendroglioma, and an MRI examination was requested to confirm. At first glance, MRI findings showed multiple cystic intratumoral and calcification, which is prone to oligodendroglioma diagnosis. However, a T2-FLAIR mismatch was observed upon closer examination, with a hyperintense signal in T2-weighted imaging and a hypointense signal in T2-FLAIR, potentially leading to diffuse astrocytoma diagnosis. Moreover, the histopathological analysis revealed isocitrate dehydrogenase (IDH)-mutant findings consistent with the characteristics of diffuse astrocytoma. Our findings of the observed T2-FLAIR mismatch were consistent with other reported cases and studies that have indicated the potential predictive value of T2-FLAIR mismatch in identifying diffuse astrocytomas. This case highlights the importance of careful observation and close examination of MRI findings, especially in differentiating between similar low-grade gliomas. The presence of a T2-FLAIR mismatch can aid clinicians in making informed decisions regarding the diagnosis and subsequent treatment plan for patients presenting with symptoms suggestive of astrocytic tumors. CONCLUSIONS: In conclusion, the T2-FLAIR mismatch sign is consistent with being the radiogenomic signature of IDH-mutant diffuse astrocytomas, as seen in our case report.

Comparison between contrast-enhanced fat-suppressed 3D FLAIR brain MR images and T2-weighted orbital MR images at 3 Tesla for the diagnosis of acute optic neuritis.

PURPOSE: The purpose of this study was to compare the capabilities of contrast-enhanced fat-suppressed (CE FS) three-dimensional fluid-attenuated inversion recovery (3D FLAIR) brain magnetic resonance imaging (MRI) with those of coronal T2-weighted orbital MRI obtained at 3 Tesla for the diagnosis of optic neuritis (ON). MATERIALS AND METHODS: Patients who presented to our center with acute visual loss and underwent MRI examination of the orbits and the brain between November 2014 and February 2020 were retrospectively included. Three radiologists independently and blindly analyzed CE FS 3D FLAIR and coronal T2-weighted images. Disagreements in image interpretation were resolved by consensus with an independent neuroradiologist who was not involved in the initial reading sessions. The primary adjudication criterion for the diagnosis of ON was the presence of an optic nerve hypersignal. Sensitivity, specificity, and accuracy of CE 3D FLAIR brain images were compared with those of coronal T2-weighted orbital images using McNemar test. Artifacts were classified into three categories and compared between the two image sets. RESULTS: A total of 1023 patients were included. There were 638 women and 385 men with a mean age of 42 ± 18.3 (standard deviation) years (age range: 6-92 years). Optic nerve hyperintensities were identified in 375/400 (94%) patients with ON using both 3D FLAIR and coronal T2-weighted images. Sensitivity, specificity, and accuracy of both sequences were 94% (95% CI: 91.3-96.1), 79% (95% CI: 75.5-82.2), and 89% (95% CI: 86.8-90.7), respectively. Optic disc hypersignal was detected in 120/400 patients (30%) using 3D FLAIR compared to 3/400 (0.75%) using coronal T2-weighted images (P < 0.001). Optic radiation hypersignal was observed in 2/400 (0.5%) patients using 3D FLAIR images. Significantly more artifacts (moderate or severe) were observed on coronal T2-weighted images (801/1023; 78%) by comparison with 3D FLAIR images (448/1023; 44%) (P < 0.001). CONCLUSION: The performance of 3D FLAIR brain MRI for the diagnosis of ON is not different from that of coronal T2-weighted orbital MRI and its use for optic nerve analysis may be beneficial.

Ultrafast Brain MRI at 3 T for MS: Evaluation of a 51-Second Deep Learning-Enhanced T2-EPI-FLAIR Sequence.

In neuroimaging, there is no equivalent alternative to magnetic resonance imaging (MRI). However, image acquisitions are generally time-consuming, which may limit utilization in some cases, e.g., in patients who cannot remain motionless for long or suffer from claustrophobia, or in the event of extensive waiting times. For multiple sclerosis (MS) patients, MRI plays a major role in drug therapy decision-making. The purpose of this study was to evaluate whether an ultrafast, T2-weighted (T2w), deep learning-enhanced (DL), echo-planar-imaging-based (EPI) fluid-attenuated inversion recovery (FLAIR) sequence (FLAIRUF) that has targeted neurological emergencies so far might even be an option to detect MS lesions of the brain compared to conventional FLAIR sequences. Therefore, 17 MS patients were enrolled prospectively in this exploratory study. Standard MRI protocols and ultrafast acquisitions were conducted at 3 tesla (T), including three-dimensional (3D)-FLAIR, turbo/fast spin-echo (TSE)-FLAIR, and FLAIRUF. Inflammatory lesions were grouped by size and location. Lesion conspicuity and image quality were rated on an ordinal five-point Likert scale, and lesion detection rates were calculated. Statistical analyses were performed to compare results. Altogether, 568 different lesions were found. Data indicated no significant differences in lesion detection (sensitivity and positive predictive value [PPV]) between FLAIRUF and axially reconstructed 3D-FLAIR (lesion size ≥3 mm × ≥2 mm) and no differences in sensitivity between FLAIRUF and TSE-FLAIR (lesion size ≥3 mm total). Lesion conspicuity in FLAIRUF was similar in all brain regions except for superior conspicuity in the occipital lobe and inferior conspicuity in the central brain regions. Further findings include location-dependent limitations of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as artifacts such as spatial distortions in FLAIRUF. In conclusion, FLAIRUF could potentially be an expedient alternative to conventional methods for brain imaging in MS patients since the acquisition can be performed in a fraction of time while maintaining good image quality.

Accelerating FLAIR imaging via deep learning reconstruction: potential for evaluating white matter hyperintensities.

PURPOSE: To evaluate deep learning-reconstructed (DLR)-fluid-attenuated inversion recovery (FLAIR) images generated from undersampled data, compare them with fully sampled and rapidly acquired FLAIR images, and assess their potential for white matter hyperintensity evaluation. MATERIALS AND METHODS: We examined 30 patients with white matter hyperintensities, obtaining fully sampled FLAIR images (standard FLAIR, std-FLAIR). We created accelerated FLAIR (acc-FLAIR) images using one-third of the fully sampled data and applied deep learning to generate DLR-FLAIR images. Three neuroradiologists assessed the quality (amount of noise and gray/white matter contrast) in all three image types. The reproducibility of hyperintensities was evaluated by comparing a subset of 100 hyperintensities in acc-FLAIR and DLR-FLAIR images with those in the std-FLAIR images. Quantitatively, similarities and errors of the entire image and the focused regions on white matter hyperintensities in acc-FLAIR and DLR-FLAIR images were measured against std-FLAIR images using structural similarity index measure (SSIM), regional SSIM, normalized root mean square error (NRMSE), and regional NRMSE values. RESULTS: All three neuroradiologists evaluated DLR-FLAIR as having significantly less noise and higher image quality scores compared with std-FLAIR and acc-FLAIR (p < 0.001). All three neuroradiologists assigned significantly higher frontal lobe gray/white matter visibility scores for DLR-FLAIR than for acc-FLAIR (p < 0.001); two neuroradiologists attributed significantly higher scores for DLR-FLAIR than for std-FLAIR (p < 0.05). Regarding white matter hyperintensities, all three neuroradiologists significantly preferred DLR-FLAIR (p < 0.0001). DLR-FLAIR exhibited higher similarity to std-FLAIR in terms of visibility of the hyperintensities, with 97% of the hyperintensities rated as nearly identical or equivalent. Quantitatively, DLR-FLAIR demonstrated significantly higher SSIM and regional SSIM values than acc-FLAIR, with significantly lower NRMSE and regional NRMSE values (p < 0.0001). CONCLUSIONS: DLR-FLAIR can reduce scan time and generate images of similar quality to std-FLAIR in patients with white matter hyperintensities. Therefore, DLR-FLAIR may serve as an effective method in traditional magnetic resonance imaging protocols.

T2-FLAIR imaging-based radiomic features for predicting early postoperative recurrence of grade II gliomas.

Aim: To develop and validate a T2-weighted-fluid attenuated inversion recovery (T2-FLAIR) images-based radiomics model for predicting early postoperative recurrence (within 1 year) in patients with low-grade gliomas (LGGs).Methods: A retrospective analysis was performed by collecting clinical, pathological and magnetic resonance imaging (MRI) data from patients with LGG between 2017 and 2022. Regions of interest were delineated and radiomic features were extracted from T2-FLAIR images using 3D-Slicer software. To minimize redundant features, the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was used. Patients were categorized into two groups based on recurrence status: the recurrence group (RG) and the non-recurrence group (NRG). Radiomic features were used to develop models using three machine learning approaches: logistic regression (LR), random forest (RF) and support vector machine (SVM). The performance of the radiomic features was validated using fivefold cross-validation.Results: After rigorous screening, 105 patients met the inclusion criteria, and five radiomic features were identified. After 5-folds cross-validation, the average areas under the curves for LR, RF and SVM were 0.813, 0.741 and 0.772, respectively.Conclusion: T2-FLAIR-based radiomic features effectively predicted early recurrence in postoperative LGGs.

[Box: see text].

Clinical and Radiologic Follow-Up in Ecchordosis Physaliphora: A Case Series and Literature Review.

OBJECTIVE: This study endeavors to assess the clinical and radiologic findings of ecchordosis physaliphora (EP) in patients under long-term observation at our clinic as well as in cases reviewed from the existing literature. METHODS: In our study, we evaluated EP lesions in a total of 16 patients who underwent follow-up and treatment in the neurosurgical unit. We conducted a retrospective review using magnetic resonance imaging and computed tomography studies to confirm the diagnoses as EP. We conducted a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, encompassing a database search from inception to January 2024. We included confirmed cases of EP from both surgically and conservatively reported studies. RESULTS: Our study included a total of 16 patients, consisting of 9 (56.25%) men and 7 (43.75%) women, with an average age of 45 ± 17.3 years. Among them, 7 (43.75%) patients presented with headaches, while 3 (18.75%) reported hearing loss. Incidental EP was detected in 6 (37.5%) patients in the study during imaging performed for different indications. The key radiological features of EP comprised hypointensity on T1, hyperintensity on T2, and an absence of magnetic resonance imaging gadolinium enhancement. In 1 out of the 16 cases, we employed an endoscopic endonasal approach for resection, and there was no recurrence observed over an average postoperative follow-up period of 24 months. Among the 15 patients who underwent conservative follow-up, 12 (80%) had the classical type B EP, one (10%) patient exhibited benign notochordal tumor in the C2 vertebra, and another (10%) patient presented with a variant type EP. CONCLUSIONS: Utilizing a combination of imaging modalities, ensuring a clear radiological distinction between EP and chordoma, can offer substantial advantages in this context. Given that EP might be incidentally discovered and nonresistant symptoms may resolve on their own, considering conservative treatment before surgery may be a viable option in all cases.

T2-fluid attenuated inversion recovery fat-suppressed mismatch in the identification and characterization of lesions related to radiologically isolated syndrome.

The radiologically isolated syndrome is defined by the presence of incidentally identified T2-weighted hyperintense lesions, highly suggestive of central nervous system demyelination, following an MRI study that is performed for reasons other than for the investigation of symptoms related to multiple sclerosis (MS). These individuals also have no evidence of prior neurological symptoms associated with inflammatory demyelination and no alternative explanation for the observed MRI findings. Recently, the introduction of novel imaging techniques such as the "central vein sign" has improved lesion specificity for MS. In addition, the observation of T2-fluid attenuated inversion recovery (FLAIR) mismatch characteristics associated with gliomas and in those with MS with a higher disease burden appear to provide morphological data that relate to disease severity. The value of T2-FLAIR mismatch characteristics in discrete multi-focal lesions has not yet been well defined. Here, we present the value of a fat-suppressed T2-FLAIR sequence in the identification and characterization of T2-weighted hyperintensities resulting from inflammatory demyelination.

Diagnostic efficacy of contrast-enhanced fluid-attenuated inversion recovery (FLAIR) imaging in idiopathic cerebrospinal fluid rhinorrhea.

We report a case of a 50-year-old woman in which contrast-enhanced fluid-attenuated inversion recovery (FLAIR) was used for the diagnosis of idiopathic cerebrospinal fluid rhinorrhea. The pre- and postcontrast FLAIR subtraction images showed a contrasted protrusion of the right olfactory cleft canal, highlighting the potential practicality and effectiveness of using pre- and postcontrast FLAIR subtraction images in diagnosing idiopathic cerebrospinal fluid rhinorrhea, in conjunction with conventional high-resolution computed tomography and magnetic resonance cisternography. The successful diagnosis of cerebrospinal fluid rhinorrhea allowed for treatment through endoscopic nasal surgery to close the fistula with a positive clinical outcome.

[Anti-myelin oligodendrocyte glycoprotein (MOG) antibody-associated cortical encephalitis with low signal in subcortical white matter on MRI FLAIR imaging].

A 32-year-old male presented with unilateral orbital-temporal pulsatile headache, followed by fever in the 38°C range and nausea. The patient experienced two episodes of transient dysarthria and tinnitus, each lasting several minutes. MRI revealed swelling of the left cerebral cortex, enhancement of the leptomeninges, dilation of the left middle cerebral artery, and subcortical FLAIR hypointensity. The clinical presentation and MRI findings raised suspicions of myelin oligodendrocyte glycoprotein (MOG) antibody-associated cortical encephalitis. After two courses of steroid pulse therapy, the patient's headache subsided, and there was a significant improvement in the swelling of the left cerebral cortex. Subsequently, serum MOG antibody positivity was confirmed. While unilateral cortical FLAIR hyperintensity and increased blood flow can be observed in various diseases, MOG antibody-associated cortical encephalitis is notably characterized by subcortical FLAIR hypointensity, a finding more frequently observed in this condition compared to other diseases. In this case, the findings were useful for early diagnosis and intervention.

Enhancing glioma care with advanced imaging: T2-FLAIR mismatch as a predictive biomarker in IDH-mutant astrocytoma.

The study highlights that diffuse glioma, a prevalent type of brain tumor, affect approximately 100,000 individuals worldwide each year. IDH-mutant astrocytoma and oligodendrogliomas typically have a more favorable prognosis compared to IDH-wildtype glioblastomas. However, many IDH-mutant astrocytoma has the potential to progress to grade 4 glioblastomas, leading to a less favorable prognosis. In a recent investigation, Shumpei Onishi et al. examined the T2-FLAIR mismatch sign as a possible imaging biomarker for assessing CDKN2A status in non-enhancing IDH-mutant astrocytoma. The findings indicate that the T2-FLAIR mismatch sign is linked to CDKN2A-intact astrocytoma, providing a valuable tool for diagnostic and prognostic purposes. Additionally, the use of Indocyanine Green (ICG) for real-time visualization during neurosurgical procedures demonstrates potential, though it may have limitations in specificity. While these advancements offer promise in glioma management, there remains a critical need for larger, standardized studies to validate these findings and further improve treatment outcomes.

T2-FLAIR mismatch sign, an imaging biomarker for CDKN2A-intact in non-enhancing astrocytoma, IDH-mutant.

INTRODUCTION: The WHO classification of central nervous system tumors (5th edition) classified astrocytoma, IDH-mutant accompanied with CDKN2A/B homozygous deletion as WHO grade 4. Loss of immunohistochemical (IHC) staining for methylthioadenosine phosphorylase (MTAP) was developed as a surrogate marker for CDKN2A-HD. Identification of imaging biomarkers for CDKN2A status is of immense clinical relevance. In this study, we explored the association between radiological characteristics of non-enhancing astrocytoma, IDH-mutant to the CDKN2A/B status. METHODS: Thirty-one cases of astrocytoma, IDH-mutant with MTAP results by IHC were included in this study. The status of CDKN2A was diagnosed by IHC staining for MTAP in all cases, which was further confirmed by comprehensive genomic analysis in 12 cases. The T2-FLAIR mismatch sign, cystic component, calcification, and intratumoral microbleeding were evaluated. The relationship between the radiological features and molecular pathological diagnosis was analyzed. RESULTS: Twenty-six cases were identified as CDKN2A-intact while 5 cases were CDKN2A-HD. The presence of > 33% and > 50% T2-FLAIR mismatch was observed in 23 cases (74.2%) and 14 cases (45.2%), respectively, and was associated with CDKN2A-intact astrocytoma (p = 0.0001, 0.0482). None of the astrocytoma, IDH-mutant with CDKN2A-HD showed T2-FLAIR mismatch sign. Cystic component, calcification, and intratumoral microbleeding were not associated with CDKN2A status. CONCLUSION: In patients with non-enhancing astrocytoma, IDH-mutant, the T2-FLAIR mismatch sign is a potential imaging biomarker for the CDKN2A-intact subtype. This imaging biomarker may enable preoperative prediction of CDKN2A status among astrocytoma, IDH-mutant.

Mucin-Rich Brain Metastasis May Show the T2-FLAIR Mismatch Sign: A Case Report and Literature Review.

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.

Unveiling Opportunities for Intervention: A Prospective Cohort Study Investigating the Clinical Significance of Diffusion-Weighted Imaging (DWI)-Fluid-Attenuated Inversion Recovery (FLAIR) Mismatch Beyond the Window Period in Acute Ischemic Stroke.

INTRODUCTION: Acute ischemic stroke causes irreversible damage to the brain parenchyma surrounded by salvageable tissue known as the ischemic penumbra. Magnetic resonance imaging (MRI), particularly the mismatch between abnormal diffusion-weighted imaging (DWI) signals and normal fluid-attenuated inversion recovery (FLAIR) signals, plays a critical role in detecting ischemic penumbra. It also allows for the identification of patients who may benefit from reperfusion therapy. Hence, this prospective cohort study aimed to explore the correlation between DWI-FLAIR mismatch and clinical outcomes in acute ischemic stroke patients, specifically those with delayed or uncertain symptom onset, offering potential insights into reperfusion therapy. METHODOLOGY: A total of 38 thrombotic stroke patients aged above 18 were included in this prospective cohort study. Baseline data, including demographics, lifestyle factors, and medical history, were recorded. DWI-FLAIR mismatch was evaluated through brain MRI within 4.5 hours to 12 hours of symptom onset. RESULTS:  Of the cohort, 63.2% were males, predominantly in the 61-70 age group. Smoking and alcohol consumption were reported by 15.79% each. DWI-FLAIR mismatch was present in 20 out of 38 subjects. No statistically significant differences were noted in the mean National Institutes of Health Stroke Scale (NIHSS) and Modified Rankin Scale (MRS) scores between subjects with and without DWI-FLAIR mismatch. Thrombolysis in wake-up stroke subjects demonstrated a substantial reduction in mean MRS at discharge (1.29±0.95) and at six to eight weeks (1.71±1.11), suggesting potential benefits on functional outcomes. CONCLUSION:  The prevalence of DWI-FLAIR mismatch was seen in the majority of patients beyond their window period and also showed beneficiary outcomes with a mean reduction in NHISS and MRS scores following thrombolysis.

Usefulness of synthetic MRI for differentiation of IDH-mutant diffuse gliomas and its comparison with the T2-FLAIR mismatch sign.

INTRODUCTION: The T2-FLAIR mismatch sign is a characteristic imaging biomarker for astrocytoma, isocitrate dehydrogenase (IDH)-mutant. However, investigators have provided varying interpretations of the positivity/negativity of this sign given for individual cases the nature of qualitative visual assessment. Moreover, MR sequence parameters also influence the appearance of the T2-FLAIR mismatch sign. To resolve these issues, we used synthetic MR technique to quantitatively evaluate and differentiate astrocytoma from oligodendroglioma. METHODS: This study included 20 patients with newly diagnosed non-enhanced IDH-mutant diffuse glioma who underwent preoperative synthetic MRI using the Quantification of Relaxation Times and Proton Density by Multiecho acquisition of a saturation-recovery using Turbo spin-Echo Readout (QRAPMASTER) sequence at our institution. Two independent reviewers evaluated preoperative conventional MR images to determine the presence or absence of the T2-FLAIR mismatch sign. Synthetic MRI was used to measure T1, T2 and proton density (PD) values in the tumor lesion. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance. RESULTS: The pathological diagnoses included astrocytoma, IDH-mutant (n = 12) and oligodendroglioma, IDH-mutant and 1p/19q-codeleted (n = 8). The sensitivity and specificity of T2-FLAIR mismatch sign for astrocytoma were 66.7% and 100% [area under the ROC curve (AUC) = 0.833], respectively. Astrocytoma had significantly higher T1, T2, and PD values than did oligodendroglioma (p < 0.0001, < 0.0001, and 0.0154, respectively). A cutoff lesion T1 value of 1580 ms completely differentiated astrocytoma from oligodendroglioma (AUC = 1.00). CONCLUSION: Quantitative evaluation of non-enhanced IDH-mutant diffuse glioma using synthetic MRI allowed for better differentiation between astrocytoma and oligodendroglioma than did conventional T2-FLAIR mismatch sign. Measurement of T1 and T2 value by synthetic MRI could improve the differentiation of IDH-mutant diffuse gliomas.

Multicenter validation of synthetic FLAIR as a substitute for FLAIR sequence in acute ischemic stroke.

PURPOSE: To evaluate performance of synthetic and real FLAIR for identifying early stroke in a multicenter cohort. METHODS: This retrospective study was conducted using DWI and FLAIR extracted from the Endovascular Treatment in Ischemic Stroke image registry (2017-2021). The database was partitioned into subsets according to MRI field strength and manufacturer, and randomly divided into training set (70%) used for model fine-tuning, validation set (15%), and test set (15%). In test set, five readers, blinded to FLAIR sequence type, assessed DWI-FLAIR mismatch using real and synthetic FLAIR. Interobserver agreement for DWI-FLAIR rating and concordance between synthetic and real FLAIR were evaluated with kappa statistics. Sensitivity and specificity for identification of ⩽4.5 h AIS were compared in patients with known onset-to-MRI delay using McNemar's test. RESULTS: 1454 complete MRI sets (1172 patients, median (IQR) age: 73 years (62-82); 762 women) acquired on 125 MRI units were analyzed. In test set (207 MRI), interobserver reproducibility for DWI-FLAIR mismatch labeling was substantial for real and synthetic FLAIR (Fleiss κ = 0.79 (95%CI: 0.73-0.84) and 0.77 (95%CI: 0.71-0.82), respectively). After consensus, concordance between real and synthetic FLAIR was excellent (κ = 0.85 (95%CI: 0.78-0.92)). In 141 MRI sets with known onset-to-MRI delay, diagnostic performances for ⩽4.5 h AIS identification did not differ between real and synthetic FLAIR (sensitivity: 60/71 (85%) vs 59/71 (83%), p = .56; specificity: 65/70 (93%) vs 65/70 (93%), p > 0.99). CONCLUSION: A deep-learning-based FLAIR fine-tuned on multicenter data can provide comparable performances to real FLAIR for early AIS identification. This approach may help reducing MR protocol duration and motion artifacts.

Improving the lesion appearance on FLAIR images synthetized from quantitative MRI: a fast, hybrid approach.

OBJECTIVE: The image quality of synthetized FLAIR (fluid attenuated inversion recovery) images is generally inferior to its conventional counterpart, especially regarding the lesion contrast mismatch. This work aimed to improve the lesion appearance through a hybrid methodology. MATERIALS AND METHODS: We combined a full brain 5-min MR-STAT acquisition followed by FLAIR synthetization step with an ultra-under sampled conventional FLAIR sequence and performed the retrospective and prospective analysis of the proposed method on the patient datasets and a healthy volunteer. RESULTS: All performance metrics of the proposed hybrid FLAIR images on patient datasets were significantly higher than those of the physics-based FLAIR images (p < 0.005), and comparable to those of conventional FLAIR images. The small difference between prospective and retrospective analysis on a healthy volunteer demonstrated the validity of the retrospective analysis of the hybrid method as presented for the patient datasets. DISCUSSION: The proposed hybrid FLAIR achieved an improved lesion appearance in the clinical cases with neurological diseases compared to the physics-based FLAIR images, Future prospective work on patient data will address the validation of the method from a diagnostic perspective by radiological inspection of the new images over a larger patient cohort.

Super T2-FLAIR mismatch sign: a prognostic imaging biomarker for non-enhancing astrocytoma, IDH-mutant.

PURPOSE: The T2-FLAIR mismatch sign is a highly specific diagnostic imaging biomarker for astrocytoma, IDH-mutant. However, a definitive prognostic imaging biomarker has yet to be identified. This study investigated imaging prognostic markers, specifically analyzing T2-weighted and FLAIR images of this tumor. METHODS: We retrospectively analyzed 31 cases of non-enhancing astrocytoma, IDH-mutant treated at our institution, and 30 cases from The Cancer Genome Atlas (TCGA)/The Cancer Imaging Archive (TCIA). We defined "super T2-FLAIR mismatch sign" as having a significantly strong low signal comparable to cerebrospinal fluid at non-cystic lesions rather than just a pale FLAIR low-signal tumor lesion as in conventional T2-FLAIR mismatch sign. Cysts were defined as having a round or oval shape and were excluded from the criteria for the super T2-FLAIR mismatch sign. We evaluated the presence or absence of the T2-FLAIR mismatch sign and super T2-FLAIR mismatch sign using preoperative MRI and analyzed the progression-free survival (PFS) and overall survival (OS) by log-rank test. RESULTS: The T2-FLAIR mismatch sign was present in 17 cases (55%) in our institution and 9 cases (30%) within the TCGA-LGG dataset without any correlation with PFS or OS. However, the super T2-FLAIR mismatch sign was detected in 8 cases (26%) at our institution and 13 cases (43%) in the TCGA-LGG dataset. At our institution, patients displaying the super T2-FLAIR mismatch sign showed significantly extended PFS (122.7 vs. 35.9 months, p = 0.0491) and OS (not reached vs. 116.7 months, p = 0.0232). Similarly, in the TCGA-LGG dataset, those with the super T2-FLAIR mismatch sign exhibited notably longer OS (not reached vs. 44.0 months, p = 0.0177). CONCLUSION: The super T2-FLAIR mismatch is a promising prognostic imaging biomarker for non-enhancing astrocytoma, IDH-mutant.

Evaluation of preoperative magnetic resonance imaging features and diagnostic effectiveness of grades II and III intracranial solitary fibroma.

OBJECTIVES: To explore the value of preoperative magnetic resonance imaging (MRI) characterization of intracranial solitary fibrous tumors (ISFT) and to evaluate the effectiveness of preoperative MRI features in predicting pathological grading. MATERIALS AND METHODS: This retrospective analysis comprised the clinical and preoperative MRI characterization of 55 patients with ISFT in our hospital, including 27 grade II cases and 28 grade III cases confirmed by postoperative pathology. Variables included age, sex, tumor location, cross-midline status, signal characteristics of T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), T2-fluid-attenuated inversion recovery (T2-FLAIR), and diffusion­weighted imaging (DWI), peritumoral edema, intralesional hemorrhage, focal necrosis/cystic degeneration, tumor empty vessel, maximum tumor diameter, maximum, minimum, and average values of apparent diffusion coefficient (ADCmax, ADCmin, and ADCmean), tumors enhancement mode, meningeal tail sign, skull invasion, cerebral parenchymal invasion, and venous sinus involvement. The independent samples t test or Mann-Whitney U test was performed to compare continuous data between the two groups, and the Pearson chi-squared test or Fisher's exact test was used to compare categorical data. In addition, bivariate logistic regression was performed to construct a comprehensive model, and receiver operating characteristic (ROC) curves were generated to calculate the areas under the curve (AUCs), thereby determining the value of each parameter in the differential diagnosis of grades II and III ISFT. RESULTS: The mean age at onset was similar between patients with grades II and III ISFT (46.77 ± 14.66 years and 45.82 ± 12.07 years, respectively). The proportions of men among patients with grades II and III ISFT were slightly higher than those of female patients (male/female: 1.25 [15/12] and 1.33 [16/12], respectively). There were significant differences between grades II and III ISFT in the T2-FLAIR and DWI signal characteristics, maximum, minimum, and average values of the apparent diffusion coefficient (ADCmax, ADCmin, and ADCmean), tumor location, and skull invasion (P = 0.001, P = 0.018, P = 0.000, P = 0.000, P = 0.000, P = 0.010, and P = 0.032, respectively). However, no significant differences were noted between grades II and III ISFT in age, sex, cross-midline status, T1WI and T2WI signal characteristics, peritumoral edema, intralesional hemorrhage, focal necrosis/cystic degeneration, tumor empty vessel shadow, enhancement mode, meningeal tail sign, maximum tumor diameter, brain parenchyma invasion, or venous sinus involvement (all P > 0.05). Moreover, binary logistic regression analysis showed that the model accuracy was 89.1% when ADCmin was included in the regression equation. Moreover, ROC curve analysis showed that the AUC of ADCmin was 0.805 (0.688, 0.922), sensitivity was 74.1%, specificity was 75.0%, and the cutoff value was 672 mm2/s. CONCLUSIONS: Grade III ISFT patients displayed more mixed T2-FLAIR signal characteristics and DWI signal characteristics than grade II patients, as shown by higher skull invasion and tumor mass collapse midline distribution and lower ADCmax, ADCmean, and ADCmin values. The ADCmin value was significant in the preoperative assignment of grades II and III ISFT, thereby contributing to enhanced accuracy in the imaging grading diagnosis of the disease.