Postcontrast Fluid-attenuated Inversion Recovery Research Articles

NIMG-88. EVALUATION OF DIFFUSION AND PERFUSION MRI FEATURES FOR DIFFERENTIATING RECURRENT BRAIN METASTASES AND RADIATION NECROSIS

Abstract BACKGROUND Brain metastases (BM) are a frequent and serious complication of cancer. Differentiating between BM and radiation-induced necrosis (RN) after radiotherapy remains challenging. Diffusion-weighted imaging (DWI) derived apparent diffusion coefficient (ADC) maps and perfusion-weighted imaging (PWI) derived relative cerebral blood volume (rCBV) have the potential to distinguish between BM and RN. Despite the potential of these imaging modalities, previous studies have been limited by the absence of histopathological confirmation. In this study, we utilized a patient cohort that underwent stereotactic biopsy as part of their Laser Interstitial Thermal Therapy (LITT) following suspicious radiographic progression. This allowed us to evaluate the efficacy of ADC and rCBV imaging features with histopathological validation. METHODS In this study, 29 patients underwent MRI scans (3 with 1.5T, 26 with 3T) prior to LITT. Pathology confirmed 11 patients with BM and 18 with RN. Regions of interest (ROIs) in the contrast-enhanced lesion and T2 hyperintensity lesion were identified using post-contrast T1-weighted images and fluid-attenuated inversion recovery (FLAIR) images. Mean values and histogram-based features (standard deviation, 10%, 90%) of lesion volume, ADC, and rCBV within tumor ROIs were compared between the BM and RN using the Wilcoxon rank-sum test. RESULTS Our findings indicated that the mean values of ADC in the enhancing and non-enhancing lesion ROIs did not significantly differ between BM and RN patients. However, in the contrast-enhanced lesion regions, we observed a significant difference in the standard deviation of rCBV (p<0.05), and the 90th percentile value of rCBV also suggested potential differences between BM and RN (p=0.069). In the T2 hyperintensity lesion regions, lesion volume (p<0.05) and the mean of rCBV (p<0.05) show significant differences between BM and RN. CONCLUSION This study demonstrates the potential of using rCBV to aid in the clinical diagnosis of BM. Additionally, our findings indicate that T2 hyperintensity regions, beyond just contrast-enhancing lesions, may provide valuable information for differential diagnosis.

Poor venous outflow is associated with hyperintense acute reperfusion marker on follow-up MRI in patients with acute ischemic stroke with a large vessel occlusion

BackgroundHyperintense acute reperfusion marker (HARM) refers to delayed enhancement in the subarachnoid or subpial space on post-contrast fluid attenuated inversion recovery (FLAIR) images. HARM is a measure of blood–brain barrier...

Age-associated gadolinium leakage into ocular structures in patients with acute traumatic brain injury

BackgroundGadolinium Leakage into Ocular Structures (GLOS) is common following acute cerebrovascular events. The objective of this study was to investigate the occurrence of GLOS in an acute traumatic brain injury (TBI) cohort without acute cerebrovascular injury and to explore associated factors. MethodsEnrolled acute TBI patients had a baseline MRI ≤48 h of injury (TP1) and follow-up MRI ≤72 h after baseline (TP2). Vitreous chamber enhancement and signal intensity ratios (SIRs) were calculated using pre- and post-contrast Fluid Attenuated Inversion Recovery (FLAIR). White matter hyperintensities (WMHs) were assessed using the Fazekas scale. ResultsOf the 128 TBI patients included, median age was 47 years, 70% male, and 66% presented with Glasgow Coma Scale of 15. No GLOS was detected at TP1 but was present in 23% of patients at TP2. GLOS+ patients were older (68 years [56–76] vs 39 years [27–53], p < 0.001), more likely to report falls as injury mechanism (62% vs 36%, p = 0.006), report history of hypertension (41% vs 19%, p = 0.025), and had a higher burden of WMHs (59% vs 14% with a total Fazekas ≥2, p < 0.001). Quantitative SIRs confirmed qualitative assessments: GLOS+ patients had higher SIRs at TP2 (0.43 vs 0.22, p < 0.001). Age (OR 3.28, 95%CI [1.88–5.71], p < 0.001) and prior TBI history (OR 4.99, 95%CI [1.46–17.06], p = 0.010) were independent predictors of GLOS. When age was removed, total Fazekas score (OR 2.53, 95%CI [1.60–4.00], p < 0.001) was an independent predictor of GLOS. ConclusionsGLOS is primarily associated with age and may serve as another imaging marker of chronic vascular disease.

Leptomeningeal metastases in isocitrate dehydrogenase-wildtype glioblastomas revisited: Comprehensive analysis of incidence, risk factors, and prognosis based on post-contrast fluid-attenuated inversion recovery.

The incidence of leptomeningeal metastases (LM) has been reported diversely. This study aimed to investigate the incidence, risk factors, and prognosis of LM in patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma. A total of 828 patients with IDH-wildtype glioblastoma were enrolled between 2005 and 2022. Baseline preoperative MRI including post-contrast fluid-attenuated inversion recovery (FLAIR) was used for LM diagnosis. Qualitative and quantitative features, including distance between tumor and subventricular zone (SVZ) and tumor volume by automatic segmentation of the lateral ventricles and tumor, were assessed. Logistic analysis of LM development was performed using clinical, molecular, and imaging data. Survival analysis was performed. The incidence of LM was 11.4%. MGMTp unmethylation (odds ratio [OR] = 1.92, P = .014), shorter distance between tumor and SVZ (OR = 0.94, P = .010), and larger contrast-enhancing tumor volume (OR = 1.02, P < .001) were significantly associated with LM. The overall survival (OS) was significantly shorter in patients with LM than in those without (log-rank test; P < .001), with median OS of 12.2 and 18.5 months, respectively. The presence of LM remained an independent prognostic factor for OS in IDH-wildtype glioblastoma (hazard ratio = 1.42, P = .011), along with other clinical, molecular, imaging, and surgical prognostic factors. The incidence of LM is high in patients with IDH-wildtype glioblastoma, and aggressive molecular and imaging factors are correlated with LM development. The prognostic significance of LM based on post-contrast FLAIR imaging suggests the acknowledgment of post-contrast FLAIR as a reliable diagnostic tool for clinicians.

Concurrent spontaneous coronary dissection and reversible cerebral vasoconstriction syndrome during postnatal care.

Pregnancy-associated spontaneous coronary artery dissection (SCAD) and reversible cerebral vasoconstriction syndrome (RCVS) are rare conditions that may occur during pregnancy and the postpartum period. The coexistence of both diseases may pose a risk to patients, potentially resulting in a variety of complications and clinical manifestations. This is considered the first case of a patient who successfully recovered from a critical condition in the postpartum period, with contemporaneous SCAD and RCVS. A 33-year-old female with no known medical history was referred to the emergency department after experiencing cardiac arrest, which occurred 1 week after giving birth to her third child. She complained of sudden anterior squeezing chest pain, accompanied by a headache, and eventually collapsed due to ventricular fibrillation with seizure. She was successfully resuscitated after receiving basic life support. She showed an alert mentality and did not experience any further seizure events or additional neurological symptoms. Although vital sign remained stable, the level of highly sensitive troponin I was significantly elevated. Electrocardiography revealed sinus rhythm with T-wave inversion at V1-4, while chest computed tomography (CT) demonstrated severe aspiration pneumonia. The patient was admitted to the intensive care unit due to a high requirement of O2 supply. A consultation with the neurologic department and a brain magnetic resonance angiography (MRA) were conducted for the thunderclap headache. The brain MRA demonstrated stenosis in the basilar artery, the right M2 segment, and bilateral A1 segments, along with sulcal hyperintensity on post-contrast fluid-attenuated inversion recovery (FLAIR) suggesting blood-brain barrier breakdown due to vasoconstriction. Formal echocardiography showed regional wall motion abnormality in the left anterior descending artery (LAD) territory. After the improvement of pneumonia, a coronary angiography was performed, revealing diffuse luminal narrowing from the mid to distal LAD due to a long segmental, extensive dissection. We decided to maintain the medical therapy. A follow-up coronary CT angiography performed 6months later revealed complete remission of the dissected coronary vessel, and a brain MRA checked 3months later showed resolved vasoconstriction of the relevant cerebral vessels. The physicians must be aware of pregnancy-associated complications in certain patients. Clear diagnoses and proper treatments are required in pregnant patients who may be exposed to multiple acute conditions, in order to reduce complications and achieve favorable outcomes.

Development of A Radiomic Model for MGMT Promoter Methylation Detection in Glioblastoma Using Conventional MRI.

The methylation of the O6-methylguanine-DNA methyltransferase (MGMT) promoter is a molecular marker associated with a better response to chemotherapy in patients with glioblastoma (GB). Standard pre-operative magnetic resonance imaging (MRI) analysis is not adequate to detect MGMT promoter methylation. This study aims to evaluate whether the radiomic features extracted from multiple tumor subregions using multiparametric MRI can predict MGMT promoter methylation status in GB patients. This retrospective single-institution study included a cohort of 277 GB patients whose 3D post-contrast T1-weighted images and 3D fluid-attenuated inversion recovery (FLAIR) images were acquired using two MRI scanners. Three separate regions of interest (ROIs) showing tumor enhancement, necrosis, and FLAIR hyperintensities were manually segmented for each patient. Two machine learning algorithms (support vector machine (SVM) and random forest) were built for MGMT promoter methylation prediction from a training cohort (196 patients) and tested on a separate validation cohort (81 patients), based on a set of automatically selected radiomic features, with and without demographic variables (i.e., patients' age and sex). In the training set, SVM based on the selected radiomic features of the three separate ROIs achieved the best performances, with an average of 83.0% (standard deviation: 5.7%) for accuracy and 0.894 (0.056) for the area under the curve (AUC) computed through cross-validation. In the test set, all classification performances dropped: the best was obtained by SVM based on the selected features extracted from the whole tumor lesion constructed by merging the three ROIs, with 64.2% (95% confidence interval: 52.8-74.6%) accuracy and 0.572 (0.439-0.705) for AUC. The performances did not change when the patients' age and sex were included with the radiomic features into the models. Our study confirms the presence of a subtle association between imaging characteristics and MGMT promoter methylation status. However, further verification of the strength of this association is needed, as the low diagnostic performance obtained in this validation cohort is not sufficiently robust to allow clinically meaningful predictions.

Glioma Tumor Grading Using Radiomics on Conventional MRI: A Comparative Study of WHO 2021 and WHO 2016 Classification of Central Nervous Tumors.

Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics-based machine learning (ML) classifiers remains unexplored. To assess the performance of ML in classifying glioma tumor grades based on various WHO criteria. Retrospective. A neuropathologist regraded gliomas of 237 patients into WHO 2016 and 2021 from 2007 criteria. Multicentric 0.5 to 3 Tesla; pre- and post-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery. Radiomic features were selected using random forest-recursive feature elimination. The synthetic minority over-sampling technique (SMOTE) was implemented for data augmentation. Stratified 10-fold cross-validation with and without SMOTE was used to evaluate 11 classifiers for 3-grade (2, 3, and 4; WHO 2016 and 2021) and 2-grade (low and high grade; WHO 2007 and 2021) classification. Additionally, we developed the models on data randomly divided into training and test sets (mixed-data analysis), or data divided based on the centers (independent-data analysis). We assessed ML classifiers using sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). Top performances were compared with a t-test and categorical data with the chi-square test using a significance level of P < 0.05. In the mixed-data analysis, Stacking Classifier without SMOTE achieved the highest accuracy (0.86) and AUC (0.92) in 3-grade WHO 2021 grouping. The results of WHO 2021 were significantly better than WHO 2016 (P-value<0.0001). In the 2-grade analysis, ML achieved 1.00 in all metrics. In the independent-data analysis, ML classifiers showed strong discrimination between grade 2 and 4, despite lower performance metrics than the mixed analysis. ML algorithms performed better in glioma tumor grading based on WHO 2021 criteria. Nonetheless, the clinical use of ML classifiers needs further investigation. 3 TECHNICAL EFFICACY: Stage 2.

T1 contrast versus fluid-attenuated inversion recovery contrast technique for evaluation of cerebral tuberculosis

Objectives: T2-weighted (T2W) fluid-attenuated inversion recovery (FLAIR), a traditional magnetic resonance imaging (MRI) technique, is regarded as one of the most effective methods for examining brain disorders. The identification of brain pathologies can be significantly aided by T2 FLAIR and T1 post-contrast imaging. However, lesion enhancement is occasionally inconspicuous on T1-weighted image. Hence, for the evaluation of brain disorders, a MRI approach known as FLAIR contrast would combine the benefits of T2W FLAIR with contrast-enhancement on a single picture. Material and Methods: After obtaining clearance from the Institution’s Ethics Committee, contrast-enhanced MRI (CE-MRI) brain of 20 patients was taken for the study. CE-MRI was performed using 1.5 Tesla Intera PHILIPS with intravenous administration of gadolinium at approximately 0.1 mL/kg/body at a rate of 10 mL/15 s. Results: This study showed a better appreciation of lesion conspicuity when compared to prior T1 contrast images. However, there was no significant difference in the number of lesions, lesion extension, and degree of contrast-enhancement on comparison with T1 contrast images. Conclusion: T1 FLAIR contrast shows a better appreciation of lesion conspicuity when compared to T1 contrast images. Post-contrast FLAIR imaging is a valuable adjunct to post-contrast T1W imaging and effectively delineates cerebral tubercular pathologies. However, T1 FLAIR cannot be used as a replacement for conventional T1 fat saturated post-contrast imaging.

Leptomeningeal metastases in glioma revisited: incidence and molecular predictors based on postcontrast fluid-attenuated inversion recovery imaging.

Leptomeningeal metastases (LMs) in glioma have been underestimated given their low incidence and the lack of reliable imaging. Authors of this study aimed to investigate the real-world incidence of LMs using cerebrospinal fluid (CSF)-sensitive imaging, namely postcontrast fluid-attenuated inversion recovery (FLAIR) imaging, and to analyze molecular predictors for LMs in the molecular era. A total of 1405 adult glioma (World Health Organization [WHO] grade 2-4) patients underwent postcontrast FLAIR imaging at initial diagnosis and during treatment monitoring between 2001 and 2021. Collected molecular data included isocitrate dehydrogenase (IDH) mutation, 1p/19q codeletion, H3 K27 alteration, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. LM diagnosis was performed with MRI including postcontrast FLAIR sequences. Logistic regression analysis for LM development was performed with molecular, clinical, and imaging data. Overall survival (OS) was compared between patients with and those without LM. LM was identified in 228 patients (16.2%), 110 (7.8%) at the initial diagnosis and 118 (8.4%) at recurrence. Among the molecular diagnostics, IDH-wildtype (OR 3.14, p = 0.001) and MGMT promoter unmethylation (OR 1.43, p = 0.034) were independent predictors of LM. WHO grade 4 (OR 10.52, p < 0.001) and nonlobar location (OR 1.56, p = 0.048) were associated with LM at initial diagnosis, whereas IDH-wildtype (OR 5.04, p < 0.001) and H3 K27 alteration (OR 3.39, p = 0.003) were associated with LM at recurrence. Patients with LM had a worse median OS than those without LM (16.7 vs 32.0 months, p < 0.001, log-rank test), which was confirmed as an independent factor on multivariable Cox analysis (p = 0.004). CSF-sensitive imaging aids the diagnosis of LM, demonstrating a high incidence of LM in adult gliomas. Furthermore, molecular markers are associated with LM development in glioma, and patients with aggressive molecular markers warrant imaging surveillance for LM.

Reducing Gadolinium Exposure in Patients Undergoing Monitoring for Meningiomas.

Background Due to the non-malignant and slow-growing nature of many meningiomas, surveillance with serial magnetic resonance imaging (MRI) serves as an acceptable management plan. However, repeated imaging with gold-standard contrast-based studies may lead to contrast-associated adverse effects. Non-gadolinium T2 sequences may serve as a suitable alternative without the risk of adverse effects of contrast. Thus, this study sought to investigate the agreement between post-contrast T1 and non-gadolinium T2 MRI sequences in the measurement of meningioma growth. Methodology The Virginia Commonwealth University School of Medicine (VCU SOM) brain tumor database was used to create a cohort of meningioma patients and determine the number of patients who had T1 post-contrast imaging accompanied by readily measurable imaging from either T2 fast spin echo (FSE) or T2 fluid-attenuated inversion recovery (FLAIR) sequences. Measurements of the largest axial and perpendicular diameters of each tumor were conducted by two independent observers using T1 post-contrast, T2 FSE, and T2 FLAIR imaging series.Lin's concordance correlation coefficient (CCC) was calculated to assess inter-rater reliability between observers and agreement between measurements of tumor diameter among the different imaging sequences. Results In total, 33 patients (average age = 72.1 ± 12.9 years, 90% female) with meningiomas were extracted from our database, with 22 (66.7%) undergoing T1 post-contrast imaging accompanied with readily measurable imaging from T2 FSE and/or T2 FLAIR sequences. The inter-rater reliability between the measurements of T1 axial and perpendicular diameters was 0.96 (95% confidence interval (CI) = 0.92-0.98) and 0.92 (95% CI = 0.83-0.97), respectively. The inter-rater reliability between the measurements of T2 axial perpendicular diameters was 0.93 (95% = CI 0.92-0.97) and 0.89 (95% CI = 0.74-0.95), respectively. The agreements between the measurement of T1 and T2 FSE axial diameter by each observer were 0.97 (95% CI = 0.93-0.98) and 0.92 (95% CI = 0.81-0.97). The agreements between the measurements of T1 and T2 FSE perpendicular diameter measurements by each observer were 0.98 (95% CI = 0.95-0.99) and 0.88 (95% CI = 0.73-0.95). Conclusions Two-thirds of our patients had meningiomas that were readily measurable on either T2 FSE or T2 FLAIR sequences. Additionally, there was excellent inter-rater reliability between the observers in our study as well as an agreement between individual measurements of T1 post-contrast and T2 FSE tumor diameters. These findings suggest that T2 FSE may serve as a safe and similarly effective surveillance method for the long-term management of meningioma patients.

Delayed post-contrast MRI in the assessment of Meniere’s disease—initial South Australian experience

Background: The underlying pathology of Meniere’s disease (MD) has long been attributed to endolymphatic hydrops (EH), until recently only detectable on post-mortem studies. In this retrospective cross-sectional study, we utilised heavily T2 weighted post-contrast 3D FLAIR (fluid attenuated inversion recovery) sequences at 3T MRI (magnetic resonance imaging) for detection and grading of EH in patients with clinically suspected MD.

Comparison of post contrast fluid attenuated inversion recovery, 3D T1-SPACE, and T1W MRI sequences with fat suppression in the diagnosis of infectious meningitis.

To assess the usefulness of post contrast Fluid attenuated inversion recovery (FLAIR), 3D T1-SPACE, and T1W magnetic resonance imaging (MRI) sequences with fat suppression in diagnosis of infectious meningitis. 75 patients with clinical suspicion of meningitis were evaluated with post contrast FLAIR (PC-FLAIR), post contrast T1-SPACE (PC-T1-SPACE), and post contrast T1WI (PC-T1WI). Sensitivity, specificity, positive predictive value, and negative predictive value of individual sequences were assessed. The sensitivity of PC-FLAIR (88.4%) was greater than PC-T1-SPACE (85.5%) and PC-T1WI (82.6%), considering cerebrospinal fluid (CSF) analysis as gold standard (p < 0.05). Kappa inter-rater agreement between two radiologists was 0.921 for PC-T1-SPACE, 0.921 for PC-T1WI, and 1.0 for PC-FLAIR with a p value <0.05. Both PC-T1-SPACE and PC-FLAIR performed equally in sulcal space enhancement. PC-T1-SPACE and PC-T1WI performed better in evaluation of pachymeningeal enhancement, ependymal enhancement in cases of ventriculitis, whereas PC-FLAIR was more sensitive in assessment of basal cistern enhancement and enhancement along the cerebellar folia. Meningeal enhancement could be better appreciated in PC-FLAIR image than PC-T1WI and PC-T1-SPACE. Enhancement in PC-T1-SPACE was comparable to that of PC-T1WI. Being a T1 based spin echo sequence, PC-T1-SPACE has all the advantages of PC-T1WI in addition to its ability to differentiate meningeal enhancement from leptomeningeal vessels. Hence, PC-T1WI can be replaced by PC-T1-SPACE and PC-FLAIR can be added to routine MRI protocol in suspected case of meningitis.

EPID-05. LEPTOMENINGEAL METASTASES IN GLIOMA REVISITED: HIGH INCIDENCE AND THEIR MOLECULAR PREDICTORS BASED ON RECENT IMAGING AND MOLECULAR DIAGNOSTICS

Abstract BACKGROUND Leptomeningeal metastases (LM) in glioma has been underestimated due to low incidence and lack of reliable imaging. This study aimed to investigate a real-world incidence of LM using a CSF-sensitive MR imaging technique and analyze molecular predictors for LM in the molecular era. METHODS Total 1,405 adult glioma patients underwent post-contrast fluid attenuated inversion recovery (FLAIR) imaging at initial diagnosis and during treatment monitoring between March 2001 and October 2021. Molecular data included isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion, H3 K27M alteration, and O6-methylguanine-methyltransferase (MGMT) promoter methylation status. Multivariable logistic regression analysis for LM development was performed in molecular data, clinical data, and imaging characteristics. Median overall survival (OS) was compared between patients with and without LM using Kaplan-Meier survival curves and log-rank test. RESULTS LM was identified in 16.2% of glioma (228 of 1405), with 7.8% (110 of 1405) at initial diagnosis, and 8.4% (118 of 1405) at recurrence. Among molecular diagnostics, IDH-wildtype (odds ratio [OR] 3.14, P = .001) and MGMT promoter unmethylation (OR 1.43, P = .034) were independent predictors of LM. WHO grade 4 (OR 10.52, P &amp;lt; .001) and nonlobar location (OR 1.54, P =.048) were associated with LM at initial diagnosis, whereas IDH-wildtype (OR 5.04, P &amp;lt; .001) and H3 K27M alteration (OR 3.39, P =.003) were significantly associated with LM at recurrence. Patients with LM had a worse median OS than those without LM (16.7 vs. 32.0 months, log-rank test; P &amp;lt; .001). CONCLUSIONS CSF-sensitive MR imaging diagnostics aid diagnosis of LM and reduced an underdiagnosed condition in adult gliomas. Molecular markers affect LM at initial diagnosis and at recurrence, and patients with aggressive molecular markers warrant imaging surveillance of LM.

GNA11-mutated Sturge-Weber syndrome has distinct neurological and dermatological features.

Sturge-Weber syndrome (SWS) is a neurocutaneous disorder characterized by clinical manifestations involving the brain, eye and skin. SWS is commonly caused by somatic mutations in G protein subunit Alpha Q (GNAQ). Five cases of subunit Alpha 11 (GNA11) mutations have been reported. We studied phenotypic features of GNA11-SWS and compared them with those of classic SWS. Within two European multidisciplinary centers we looked for patients with clinical characteristics of SWS and a GNA11 mutation. Clinical and radiological data were collected retrospectively and prospectively. We identified three patients with SWS associated with a somatic GNA11 mutation. All had disseminated capillary malformation (CM) and hyper- or hypotrophy of an extremity. At birth, the CMs of the face, trunk and limbs were pink and patchy, and slowly darkened with age, evolving to a purple color. Two of the patients had glaucoma. All had neurological symptoms and moderate brain atrophy with a lower degree of severity than that classically associated with SWS. Susceptibility-weighted imaging (SWI) and contrast-enhanced fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging demonstrated the best sensitivity to reveal the pial angiomas. We have differentiated two distinct clinical/radiological phenotypes of SWS; GNAQ- and GNA11-SWS. The classic GNAQ-SWS is characterized by a homogeneous dark-red CM, commonly associated with underlying soft tissue hypertrophy. The CM in GNA11-SWS is more reticulate and darkens with time, and the neurological picture is milder. SWI and post-contrast FLAIR sequences appear to be necessary to demonstrate leptomeningeal angiomatosis. Anti-epileptic medication or future targeted therapies may be useful, as in classic SWS.

Role of contrast-enhanced flair sequence in magnetic resonance imaging for evaluating intracranial pathologies

Background: Magnetic resolution imaging (MRI) has superior soft tissue contrast for characterization and diagnosing various intracranial lesions. Various MRI techniques are used for characterizing intracranial lesions. Post contrast T1 imaging is the traditional technique used for assessing lesion contrast enhancement. This study intends to assess the use of post contrast Fluid Attenuated Inversion Recovery (FLAIR) imaging for assessing lesion contrast enhancement. Results: The participants were analyzed by age, gender, number of lesions observed for each participant, signal intensity pattern for all intracranial lesions on both post contrast sequences, comparison of degree of contrast enhancement of all intracranial lesions on both post contrast sequences, comparison between various intra-axial & extra-axial intracranial lesions on both post contrast sequences, comparison between various intracranial lesions based on their etiology on both post contrast sequences and comparison of each intracranial lesion on both post contrast sequences. Conclusion: The study suggests that the overall degree of contrast enhancement is superior for contrast enhanced T1 sequences for the majority of the lesions, however complete lesion pathology cannot be assessed on this sequence alone. Although post contrast FLAIR sequence has shown greater degree of contrast enhancement in infectious meningitis, hemangioblastoma and toxoplasmosis, this was not statistically significant (p value >0.05) possibly owing to less sample size. Hence, further studies with more sample size should be assessed to establish the significance. Therefore, contrast enhanced FLAIR sequence is an important adjunct for imaging of the various intracranial pathologies and should be incorporated for evaluating various intracranial pathologies.

Leptomeningeal Gadolinium Enhancement in Autoimmune GFAP Astrocytopathy.

A 46-year-old woman presented with urinary retention, headache, tremor, ataxia, mental slowness, and tetra-hyperreflexia following urinary infection. MRI showed signs of encephalomyelitis with diffuse postcontrast 3D fluid-attenuated inversion recovery leptomeningeal enhancement, a common finding in several neuroinflammatory conditions1 (Figures 1 and 2). An extensive diagnostic workup (serum and CSF neurotropic viruses, Borrelia burgdorferi , Treponema pallidum , serum anti–myelin oligodendrocyte glycoprotein and anti–aquaporin-4 antibodies, antinuclear antibodies, extractable nuclear antigen , antineutrophil cytoplasmic antibodies, angiotensin-converting enzyme and α-chitotriosidase levels, quantiferon, total body CT scan) was unrevealing. CSF analysis disclosed lymphocytic pleocytosis (204 leukocytes/μL), high protein levels (123 mg/dL), CSF-restricted oligoclonal bands, and anti–glial fibrillary acidic protein (GFAP) antibodies (cell-based assay), leading to the diagnosis of autoimmune GFAP astrocytopathy.2 After receiving IV methylprednisolone, the patient improved substantially.

The Clinical Significance of the Hyperintense Acute Reperfusion Marker Sign in Subacute Infarction Patients

Purpose: The hyperintense acute reperfusion marker (HARM) is characterized by the delayed enhancement of the subarachnoid or subpial space observed on postcontrast fluid-attenuated inversion recovery (FLAIR) images, and is considered a cerebral reperfusion marker for various brain disorders, including infarction. In this study, we evaluated the cerebral distribution patterns of HARM for discriminating between an enhancing subacute infarction and an enhancing mass located in the cortex and subcortical white matter. Materials and methods: We analyzed consecutive patients who experienced a subacute ischemic stroke, were hospitalized, and underwent conventional brain magnetic resonance imaging including postcontrast FLAIR within 14 days from symptom onset, as well as those who had lesions corresponding to a clinical sign detected by diffusion-weighted imaging and postcontrast T1-weighted imaging between May 2019 and May 2021. A total of 199 patients were included in the study. Of them, 94 were finally included in the subacute infarction group. During the same period, 76 enhancing masses located in the cortex or subcortical white matter, which were subcategorized as metastasis, malignant glioma, and lymphoma, were analyzed. We analyzed the overall incidence of HARM in subacute ischemic stroke cases, and compared the enhancement patterns between cortical infarctions and cortical masses. Results: Among 94 patients with subacute stroke, 78 patients (83%) presented HARM, and among 76 patients with subcortical masses, 48 patients (63%) presented peripheral rim enhancement. Of 170 subcortical enhancing lesions, 88 (51.8%) showed HARM, and 78 (88.6%) were determined to be subacute infarction. Among 94 patients with subacute stroke, 48 patients (51%) had diffusion restrictions, and HARM was found in 39 patients (81.2%). Of the 46 patients (49%) without diffusion restriction, 39 patients (84.8%) showed HARM. Conclusions: The presence of HARM was significantly associated with subacute infarctions. For the masses, a peripheral rim enhancement pattern was observed around the mass rather than the cerebral sulci on postcontrast FLAIR.

MRI-Based Radiomics Signature for the Prediction of Response of Lung Cancer Brain Metastases After Whole-Brain Radio-Therapy

Local response prediction for brain metastases (BMs) from lung cancer after Whole-Brain Radiotherapy (WBRT) is challenging, as existing criteria are based solely on unidimensional measurements. This study sought to determine whether radiomic features of lung cancer BMs derived from pre-treatment magnetic resonance imaging (MRI) could be used to predict local response following WBRT.A total of 88 Lung Cancer patients with BMs treated with WBRT were analyzed. After volumes of interest were drawn, 944 radiomic features including first-order, shape, Gray Level Co-occurrence Matrix (GLCM), Gray Level Dependence Matrix (GLDM), Gray Level Run Length Matrix (GLRLM), Gray Level Size Zone Matrix (GLSZM), Neighborhood Gray Tone Difference Matrix (NGTDM), and Laplacian of Gaussian (LoG) features were extracted, using the baseline pre-treatment post-contrast T1 (T1c) and T2 fluid-attenuated inversion recovery (FLAIR) MRI sequences, respectively. Local response status was determined by contrasting the baseline and follow-up MRI according to the RANO-BM criteria. The independent samples t test or Mann-Whitney U test, and then least absolute shrinkage and selection operator (LASSO) were used for dimensionality reduction and feature selection. An adaboost classifier was trained using the selected radiomic features and evaluated using the area under the receiver operating characteristic curve (AUC) in both the training and testing sets. Other discrimination metrics, including classification accuracy, positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity, were also calculated.The optimal radiomics signature was developed based on a multivariable logistic regression with 4, 5, 6 radiomic features on T1c, T2 FLAIR and T1c+T2 FLAIR, respectively. The radiomics model based on T1c features presented the AUC of (0.920 vs. 0.805, respectively) for both the training and testing sets, followed by T2 FLAIR features (0.893 vs. 0.701, respectively), and T1c+T2 FLAIR features (0.971 vs. 0.857, respectively). The classification accuracy of the radiomics model also well predicted the local response of BMs for both the models), and training and testing sets (T1c: 82.9% vs. 77.8%, T2 FLAIR: 82.9% vs. 77.8%, T1c+T2 FLAIR: 90.0% vs. 77.8%, respectively).Radiomics holds promise for predicting local tumor response following WBRT in patients with lung cancer and brain metastases. A predictive model built on radiomic features from an institutional cohort performed well on cross-validation testing. These results warrant further validation in independent datasets. Such work could prove invaluable for guiding management of individual patients and assessing outcomes of novel interventions.

MRI-based radiomics signature for the prediction of response of lung cancer brain metastases after whole-brain radiotherapy.

e21096 MRI-based Radiomics signature for the Prediction of Response of Lung Cancer Brain Metastases After Whole-Brain Radiotherapy Background: Local response prediction for brain metastases (BMs) from lung cancer after Whole-Brain Radiotherapy (WBRT) is challenging, as existing criteria are based solely on unidimensional measurements. This study sought to determine whether radiomic features of lung cancer BMs derived from pre-treatment magnetic resonance imaging (MRI) could be used to predict local response following WBRT. Methods: A total of 88 Lung Cancer patients with BMs treated with WBRT were analyzed. After volumes of interest were drawn, 944 radiomic features including first-order, shape, Gray Level Co-occurrence Matrix (GLCM), Gray Level Dependence Matrix (GLDM), Gray Level Run Length Matrix (GLRLM), Gray Level Size Zone Matrix (GLSZM), Neighborhood Gray Tone Difference Matrix (NGTDM), and Laplacian of Gaussian (LoG) features were extracted, using the baseline pre-treatment post-contrast T1 (T1c) and T2 fluid-attenuated inversion recovery (FLAIR) MRI sequences, respectively. Local response status was determined by contrasting the baseline and follow-up MRI according to the RANO-BM criteria. The independent samples t test or Mann-Whitney U test, and then least absolute shrinkage and selection operator (LASSO) were used for dimensionality reduction and feature selection. An adaboost classifier was trained using the selected radiomic features and evaluated using the area under the receiver operating characteristic curve (AUC) in both the training and testing sets. Other discrimination metrics, including classification accuracy, positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity, were also calculated. Results: The optimal radiomics signature was developed based on a multivariable logistic regression with 4, 5, 6 radiomic features on T1c, T2 FLAIR and T1c+T2 FLAIR, respectively. The radiomics model based on T1c features presented the AUC of (0.920 vs. 0.805, respectively) for both the training and testing sets, followed by T2 FLAIR features (0.893 vs. 0.701, respectively), and T1c+T2 FLAIR features (0.971 vs. 0.857, respectively). The classification accuracy of the radiomics model also well predicted the local response of BMs for both the the training and testing sets (T1c: 82.9% vs. 77.8%, T2 FLAIR: 82.9% vs. 77.8%, T1c+T2 FLAIR: 90.0% vs. 77.8%, respectively). Conclusions: Radiomics holds promise for predicting local tumor response following WBRT in patients with lung cancer and brain metastases. A predictive model built on radiomic features from an institutional cohort performed well on cross-validation testing. These results warrant further validation in independent datasets. Such work could prove invaluable for guiding management of individual patients and assessing outcomes of novel interventions.

Leptomeningeal enhancement on post-contrast FLAIR images for early diagnosis of Susac syndrome

Background: Leptomeningeal enhancement (LME) is a key feature of Susac syndrome (SuS) but is only occasionally depicted on post-contrast T1-weighted images (T1-WI). Objective: As post-contrast fluid-attenuated inversion recovery (FLAIR) may be more sensitive, our aim was to assess LME in SuS on this sequence. Methods: From 2010 to 2020, 20 patients with definite SuS diagnosis were retrospectively enrolled in this multicentre study. Two radiologists independently assessed the number of LME on post-contrast FLAIR and T1-WI acquisitions performed before any treatment. A chi-square test was used to compare both sequences and the interrater agreement was calculated. Results: Thirty-five magnetic resonance imagings (MRIs) were performed before treatment, including 19 post-contrast FLAIR images in 17 patients and 25 post-contrast T1-WI in 19 patients. In terms of patients, LME was observed on all post-contrast FLAIR, contrary to post-contrast T1-WI (17/17 (100%) vs. 15/19 (79%), p < 0.05). In terms of sequences, LME was observed on all post-contrast FLAIR, contrary to post-contrast T1-WI (19/19 (100%) vs. 16/25 (64%), p < 0.005). LME was disseminated at both supratentorial (19/19) and infratentorial (18/19) levels on post-contrast FLAIR, contrary to post-contrast T1-WI (3/25 and 9/25, respectively). Interrater agreement was excellent for post-contrast FLAIR (κ = 0.95) but only moderate for post-contrast T1-WI (κ = 0.61). Conclusion: LME was always observed and easily visible on post-contrast FLAIR images prior to SuS treatment. In association with other MRI features, it is highly indicative of SuS.