Magnetic resonance imaging in rabies encephalitis, a case report, and review of the literature

Rabies is an acute fatal disease of the central nervous system. Neuroimaging plays an important role, especially in establishing an early diagnosis and distinguishing it from other types of encephalitis. This case report aims to give a brief review of this condition and report the less common MRI findings of the disease. We herein report a case of a 61-year-old male bitten by a stray dog who presented with fever, vomiting, headache, sialorrhea, dysarthria, dysphagia, and upper limb weakness which progressed to lower limbs on the next day. T2W and FLAIR images demonstrated subtle bilateral hyperintense signal in the deep gray matter with more apparent increased signal intensity in the white matter of the frontal and parietal lobes which shows mild diffusion restriction but no postcontrast enhancement. The diagnosis of rabies encephalitis was made based on a typical history of exposure, a compatible clinical presentation, and MRI findings. Rabies diagnosis is essentially clinical. It is definitively confirmed by the isolation of the virus from biological samples such as saliva, CSF, hair, or detection of rabies antigens or antibodies. Magnetic resonance imaging (MRI) brain used as one of the modalities of investigation for distinguishing it from other encephalitis. Rabies per se does not have any characteristic features on the MRI brain.

Endovascular thrombectomy in wake-up stroke guided by arterial spin-labeling and fluid-attenuated inversion recovery versus diffusion-weighted imaging mismatch on MRI

OBJECTIVE

This purpose of this study is to investigate the effectiveness and safety of utilizing the arterial spin-labeling (ASL) combined with diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) combined with DWI double mismatch in the endovascular treatment of patients diagnosed with wake-up stroke (WUS).

METHODS

In this single-center trial, patients diagnosed with WUS underwent thrombectomy if acute ischemic lesions were observed on DWI indicating large precerebral circulation occlusion. Patients with no significant parenchymal hypersignal on FLAIR and ASL imaging showing a hypoperfusion tissue to infarct core volume ratio of at least 1.2 were included. The participants were divided into groups receiving endovascular thrombectomy plus medical therapy or medical therapy alone, based on their subjective preference. Functional outcomes were assessed using the ordinal score on the modified Rankin scale (mRs) at 90 days, along with the rate of functional independence.

RESULTS

In this study, a total of 77 patients were included, comprising 38 patients in the endovascular therapy group and 39 patients in the medical therapy group. The endovascular therapy group exhibited more favorable changes in the distribution of functional prognosis measured by mRs at 90 days, compared to the medical therapy group (adjusted common odds ratio, 3.25; 95% CI, 1.03 to 10.26; P < 0.01). Additionally, the endovascular therapy group had a higher proportion of patients achieving functional independence (odds ratio, 4.0; 95% CI, 1.36 to 11.81; P < 0.01). Importantly, there were no significant differences observed in the incidence of intracranial hemorrhage or mortality rates between the two groups.

CONCLUSION

Guided by the ASL-DWI and FLAIR-DWI double mismatch, endovascular thrombectomy combined with standard medical treatment appears to yield superior functional outcomes in patients with WUS and large vessel occlusion compared to standard medical treatment alone.

DeepFLAIR: A neural network approach to mitigate signal and contrast loss in temporal lobes at 7 Tesla FLAIR images

BACKGROUND AND PURPOSE

Higher magnetic field strength introduces stronger magnetic field inhomogeneities in the brain, especially within temporal lobes, leading to image artifacts. Particularly, T2-weighted fluid-attenuated inversion recovery (FLAIR) images can be affected by these artifacts. Here, we aimed to improve the FLAIR image quality in temporal lobe regions through image processing of multiple contrast images via machine learning using a neural network.

METHODS

Thirteen drug-resistant MR-negative epilepsy patients (age 29.2 ± 9.4y, 5 females) were scanned on a 7 T MRI scanner. Magnetization-prepared (MP2RAGE) and saturation-prepared with 2 rapid gradient echoes, multi-echo gradient echo with four echo times, and the FLAIR sequence were acquired. A voxel-wise neural network was trained on extratemporal-lobe voxels from the acquired structural scans to generate a new FLAIR-like image (i.e., deepFLAIR) with reduced temporal lobe inhomogeneities. The deepFLAIR was evaluated in temporal lobes through signal-to-noise (SNR), contrast-to-noise (CNR) ratio, the sharpness of the gray-white matter boundary and joint-histogram analysis. Saliency mapping demonstrated the importance of each input image per voxel.

RESULTS

SNR and CNR in both gray and white matter were significantly increased (p < 0.05) in the deepFLAIR's temporal ROIs, compared to the FLAIR. The gray-white matter boundary sharpness was either preserved or improved in 10/13 right-sided temporal regions and was found significantly increased in the ROIs. Multiple image contrasts were influential for the deepFLAIR reconstruction with the MP2RAGE second inversion image being the most important.

CONCLUSIONS

The deepFLAIR network showed promise to restore the FLAIR signal and reduce contrast attenuation in temporal lobe areas. This may yield a valuable tool, especially when artifact-free FLAIR images are not available.

Radiomics Multifactorial in Silico Model for Spatial Prediction of Glioblastoma Progression and Recurrence: A Proof-of-Concept

BACKGROUND

Radiomics-based prediction of glioblastoma spatial progression and recurrence may improve personalized strategies. However, most prototypes are based on limited monofactorial Gompertzian models of tumor growth. The present study consists of a proof of concept on the accuracy of a radiomics multifactorial in silico model in predicting short-term spatial growth and recurrence of glioblastoma.

METHODS

A radiomics-based biomathematical multifactorial in silico model was developed using magnetic resonance imaging (MRI) data from a 53-year-old patient with newly diagnosed glioblastoma of the right supramarginal gyrus. Raw and optimized models were derived from the MRI at diagnosis and matched to the preoperative MRI obtained 28 days after diagnosis to test the accuracy in predicting the short-term spatial growth of the tumor. An additional optimized model was derived from the early postoperative MRI and matched to the MRI documenting tumor recurrence to test spatial accuracy in predicting the location of recurrence. The spatial prediction accuracy of the model was reported as an average Jaccard index.

RESULTS

Optimized models yielded an average Jaccard index of 0.69 and 0.26 for short-term tumor growth and long-term recurrence site, respectively.

CONCLUSIONS

The present radiomics-based multifactorial in silico model was feasible, reliable, and accurate for short-term spatial prediction of glioblastoma progression. The predictive value for the spatial location of recurrence was still low, and refinements in the description of tissue reorganization in the peritumoral and resected areas may be critical to optimize accuracy further.

FLAIR Hyperintensities in the Anterior Part of the Callosal Splenium in the Elderly Population: A Large Cohort Study

RATIONALE AND OBJECTIVES

Although hyperintensity in the anterior portion of the callosal splenium on FLAIR (aCS-hyperintensity) is a common finding in elderly adults, no previous studies have examined the clinical significance. In this large elderly population study, we aimed to investigate the associations of aCS-hyperintensity with vascular risk factors, cognitive decline, and other MRI measurements.

MATERIALS AND METHODS

This cross-sectional study included 2110 participants (median age, 69 years; 61.1% females) who underwent 3 T MRI. The participants were grouped as 215 with mild cognitive impairment (MCI) and 1895 cognitively normal older adults (NOAs). Two neuroradiologists evaluated aCS-hyperintensity by using a four-point scale (none, mild, moderate, and severe). Periventricular hyperintensities (PVHs) were also rated on a four-point scale according to the Fazekas scale. The total intracranial volume (ICV), total brain volume, choroid plexus volume (CPV), and lateral ventricle volume (LVV) were calculated.

RESULTS

Logistic regression analysis showed diabetes was the main predictor of aCS-hyperintensity after adjusting for potential confounders (age, sex, hypertension, and hyperlipidemia) (p < 0.01), whereas PVH was associated with hypertension (p < 0.01). aCS-hyperintensity rated as "severe" was associated with a presence of MCI (p < 0.01). For the imaging factors, LVV was an independent predictor of aCS-hyperintensity when brain volume and PVH grade were added to the analysis (p < 0.01).

CONCLUSION

Cerebral small vessel disease due to diabetes is a major contributor to the development of aCS-hyperintensity. Cerebrospinal fluid clearance failure may also relate to aCS-hyperintensity, which may offer new insights into the pathologic processes underlying MCI.

Deep Learning Accelerated Image Reconstruction of Fluid-Attenuated Inversion Recovery Sequence in Brain Imaging: Reduction of Acquisition Time and Improvement of Image Quality

RATIONALE AND OBJECTIVES

Fluid-attenuated inversion recovery (FLAIR) imaging is playing an increasingly significant role in the detection of brain metastases with a concomitant increase in the number of magnetic resonance imaging (MRI) examinations. Therefore, the purpose of this study was to investigate the impact on image quality and diagnostic confidence of an innovative deep learning-based accelerated FLAIR (FLAIRDLR) sequence of the brain compared to conventional (standard) FLAIR (FLAIRS) imaging.

MATERIALS AND METHODS

Seventy consecutive patients with staging cerebral MRIs were retrospectively enrolled in this single-center study. The FLAIRDLR was conducted using the same MRI acquisition parameters as the FLAIRS sequence, except for a higher acceleration factor for parallel imaging (from 2 to 4), which resulted in a shorter acquisition time of 1:39 minute instead of 2:40 minutes (-38%). Two specialized neuroradiologists evaluated the imaging datasets using a Likert scale that ranged from 1 to 4, with 4 indicating the best score for the following parameters: sharpness, lesion demarcation, artifacts, overall image quality, and diagnostic confidence. Additionally, the image preference of the readers and the interreader agreement were assessed.

RESULTS

The average age of the patients was 63 ± 11years. FLAIRDLR exhibited significantly less image noise than FLAIRS, with P-values of< .001 and< .05, respectively. The sharpness of the images and the ability to detect lesions were rated higher in FLAIRDLR, with a median score of 4 compared to a median score of 3 in FLAIRS (P-values of<.001 for both readers). In terms of overall image quality, FLAIRDLR was rated superior to FLAIRS, with a median score of 4 vs 3 (P-values of<.001 for both readers). Both readers preferred FLAIRDLR in 68/70 cases.

CONCLUSION

The feasibility of deep learning FLAIR brain imaging was shown with additional 38% reduction in examination time compared to standard FLAIR imaging. Furthermore, this technique has shown improvement in image quality, noise reduction, and lesion demarcation.

Fluid-attenuated inversion-recovery sequence with fat suppression as an alternative to contrast-enhanced MRI in pediatric synovitis

BACKGROUND

Non-contrast magnetic resonance imaging (MRI) fluid-attenuated inversion-recovery sequence (FLAIR) with fat suppression (FS) has not been validated in children.

OBJECTIVE

Compare FLAIR to T1-weighted post contrast (T1CE) in the detection of knee synovitis.

METHODS AND MATERIALS

Institutional review board (IRB) waived consent. Children who underwent T1CE and FLAIR sequences of the knee on a 3-T magnet from April 2021 to December 2021 were included. Two pediatric radiologists assessed axial FLAIR and T1CE images for synovitis and synovial thickness. Reliability and agreement were assessed. Sensitivities, specificities, and accuracy were calculated for FLAIR using T1CE as reference standard.

RESULTS

In total, 42 knees (39 patients) were assessed (median age 12.9 years (2.3-17.8 years); 62% male, 38% female). Readers judged 20/42 (48%) knees to have synovitis. Sensitivity of FLAIR for reader 1 was 79% (19/24; 95% CI 0.58, 0.93) and 84% (16/19; 95% CI 0.60, 0.97) for reader 2. Specificity of FLAIR for reader 1 was 94% (17/18; 95% CI 0.73, 1) and 83% (19/23; 95% CI 0.61, 0.95) for reader 2. Accuracy for readers 1 and 2 was 86% (36/42; 95% CI 0.71, 0.95) and 83% (35/42; 95% CI 0.69, 0.93), respectively. Inter-reader reliability was good (0.75-0.90) for synovial measurements for FLAIR (ICC = 0.80; 95% CI 0.71, 0.86) and moderate for T1 CE (ICC = 0.62 (95% CI 0.48, 0.73)).

CONCLUSION

FLAIR FS depicts synovium in the pediatric knee with similar reliability to T1 CE and may be an acceptable alternative to contrast in the initial diagnosis of synovitis.

Asymmetrical putaminal atrophy in parkinsonism-predominant multiple system atrophy (MSA-P): A case report

We encountered a case of multiple system atrophy parkinsonian subtype (MSA-P) with right-dominant parkinsonism in the early stage of the disease. Atrophy of the posterolateral putamen and iron deposition are the neuropathological hallmark of MSA-P. Coronal fluid-attenuated inversion-recovery (FLAIR) images showed atrophy and iron deposition in the left posterior putamen contralateral to the clinical dominant side in the early phase. Atrophy in the posterior putamen of patients with MSA-P was more clearly observed on coronal FLAIR images than on axial T2-weighted images. These findings reflected the pathological changes and might be a pathognomonic sign of MSA-P.

Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks

Introduction

Acquisition and pre-processing pipelines for diffusion-weighted imaging (DWI) volumes are resource- and time-consuming. Generating synthetic DWI scalar maps from commonly acquired brain MRI sequences such as fluid-attenuated inversion recovery (FLAIR) could be useful for supplementing datasets. In this work we design and compare GAN-based image translation models for generating DWI scalar maps from FLAIR MRI for the first time.

Methods

We evaluate a pix2pix model, two modified CycleGANs using paired and unpaired data, and a convolutional autoencoder in synthesizing DWI fractional anisotropy (FA) and mean diffusivity (MD) from whole FLAIR volumes. In total, 420 FLAIR and DWI volumes (11,957 images) from multi-center dementia and vascular disease cohorts were used for training/testing. Generated images were evaluated using two groups of metrics: (1) human perception metrics including peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), (2) structural metrics including a newly proposed histogram similarity (Hist-KL) metric and mean squared error (MSE).

Results

Pix2pix demonstrated the best performance both quantitatively and qualitatively with mean PSNR, SSIM, and MSE metrics of 23.41 dB, 0.8, 0.004, respectively for MD generation, and 24.05 dB, 0.78, 0.004, respectively for FA generation. The new histogram similarity metric demonstrated sensitivity to differences in fine details between generated and real images with mean pix2pix MD and FA Hist-KL metrics of 11.73 and 3.74, respectively. Detailed analysis of clinically relevant regions of white matter (WM) and gray matter (GM) in the pix2pix images also showed strong significant (p < 0.001) correlations between real and synthetic FA values in both tissue types (R = 0.714 for GM, R = 0.877 for WM).

Discussion/conclusion

Our results show that pix2pix's FA and MD models had significantly better structural similarity of tissue structures and fine details than other models, including WM tracts and CSF spaces, between real and generated images. Regional analysis of synthetic volumes showed that synthetic DWI images can not only be used to supplement clinical datasets, but demonstrates potential utility in bypassing or correcting registration in data pre-processing.

Within-Modality Synthesis and Novel Radiomic Evaluation of Brain MRI Scans

One of the most common challenges in brain MRI scans is to perform different MRI sequences depending on the type and properties of tissues. In this paper, we propose a generative method to translate T2-Weighted (T2W) Magnetic Resonance Imaging (MRI) volume from T2-weight-Fluid-attenuated-Inversion-Recovery (FLAIR) and vice versa using Generative Adversarial Networks (GAN). To evaluate the proposed method, we propose a novel evaluation schema for generative and synthetic approaches based on radiomic features. For the evaluation purpose, we consider 510 pair-slices from 102 patients to train two different GAN-based architectures Cycle GAN and Dual Cycle-Consistent Adversarial network (DC²Anet). The results indicate that generative methods can produce similar results to the original sequence without significant change in the radiometric feature. Therefore, such a method can assist clinics to make decisions based on the generated image when different sequences are not available or there is not enough time to re-perform the MRI scans.

Leptomeningeal enhancement of myelin oligodendrocyte glycoprotein antibody-associated encephalitis: uncovering novel markers on contrast-enhanced fluid-attenuated inversion recovery images

Background

Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) is a newly defined autoimmune inflammatory demyelinating central nervous system (CNS) disease characterized by antibodies against MOG. Leptomeningeal enhancement (LME) on contrast-enhanced fluid-attenuated inversion recovery (CE-FLAIR) images has been reported in patients with other diseases and interpreted as a biomarker of inflammation. This study retrospectively analyzed the prevalence and distribution of LME on CE-FLAIR images in children with MOG antibody-associated encephalitis (MOG-E). The corresponding magnetic resonance imaging (MRI) features and clinical manifestations are also presented.

Methods

The brain MRI images (native and CE-FLAIR) and clinical manifestations of 78 children with MOG-E between January 2018 and December 2021 were analyzed. Secondary analyses evaluated the relationship between LME, clinical manifestations, and other MRI measures.

Results

Forty-four children were included, and the median age at the first onset was 70.5 months. The prodromal symptoms were fever, headache, emesis, and blurred vision, which could be progressively accompanied by convulsions, decreased level of consciousness, and dyskinesia. MOG-E showed multiple and asymmetric lesions in the brain by MRI, with varying sizes and blurred edges. These lesions were hyperintense on the T2-weighted and FLAIR images and slightly hypointense or hypointense on the T1-weighted images. The most common sites involved were juxtacortical white matter (81.8%) and cortical gray matter (59.1%). Periventricular/juxtaventricular white matter lesions (18.2%) were relatively rare. On CE-FLAIR images, 24 (54.5%) children showed LME located on the cerebral surface. LME was an early feature of MOG-E (P = 0.002), and cases without LME were more likely to involve the brainstem (P = 0.041).

Conclusion

LME on CE-FLAIR images may be a novel early marker among patients with MOG-E. The inclusion of CE-FLAIR images in MRI protocols for children with suspected MOG-E at an early stage may be useful for the diagnosis of this disease.

Detecting haplotype-specific transcript variation in long reads with FLAIR2

Background

RNA-Seq has brought forth significant discoveries regarding aberrations in RNA processing, implicating these RNA variants in a variety of diseases. Aberrant splicing and single nucleotide variants in RNA have been demonstrated to alter transcript stability, localization, and function. In particular, the upregulation of ADAR, an enzyme which mediates adenosine-to-inosine editing, has been previously linked to an increase in the invasiveness of lung ADC cells and associated with splicing regulation. Despite the functional importance of studying splicing and SNVs, short read RNA-Seq has limited the community's ability to interrogate both forms of RNA variation simultaneously.

Results

We employed long-read technology to obtain full-length transcript sequences, elucidating cis-effects of variants on splicing changes at a single molecule level. We have developed a computational workflow that augments FLAIR, a tool that calls isoform models expressed in long-read data, to integrate RNA variant calls with the associated isoforms that bear them. We generated nanopore data with high sequence accuracy of H1975 lung adenocarcinoma cells with and without knockdown of ADAR. We applied our workflow to identify key inosine-isoform associations to help clarify the prominence of ADAR in tumorigenesis.

Conclusions

Ultimately, we find that a long-read approach provides valuable insight toward characterizing the relationship between RNA variants and splicing patterns.

Predicting DWI-FLAIR mismatch on NCCT: the role of artificial intelligence in hyperacute decision making

Background

The presence of diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) mismatch was used to determine eligibility for intravenous thrombolysis in clinical trials. However, due to the restricted availability of MRI and the ambiguity of image assessment, it is not widely implemented in clinical practice.

Methods

A total of 222 acute ischemic stroke patients underwent non-contrast computed tomography (NCCT), DWI, and FLAIR within 1 h of one another. Human experts manually segmented ischemic lesions on DWI and FLAIR images and independently graded the presence of DWI-FLAIR mismatch. Deep learning (DL) models based on the nnU-net architecture were developed to predict ischemic lesions visible on DWI and FLAIR images using NCCT images. Inexperienced neurologists evaluated the DWI-FLAIR mismatch on NCCT images without and with the model's results.

Results

The mean age of included subjects was 71.8 ± 12.8  years, 123 (55%) were male, and the baseline NIHSS score was a median of 11 [IQR, 6-18]. All images were taken in the following order: NCCT - DWI - FLAIR, starting after a median of 139 [81-326] min after the time of the last known well. Intravenous thrombolysis was administered in 120 patients (54%) after NCCT. The DL model's prediction on NCCT images revealed a Dice coefficient and volume correlation of 39.1% and 0.76 for DWI lesions and 18.9% and 0.61 for FLAIR lesions. In the subgroup with 15  mL or greater lesion volume, the evaluation of DWI-FLAIR mismatch from NCCT by inexperienced neurologists improved in accuracy (from 0.537 to 0.610) and AUC-ROC (from 0.493 to 0.613).

Conclusion

The DWI-FLAIR mismatch may be reckoned using NCCT images through advanced artificial intelligence techniques.

Association of RNF213 polymorphism and cortical hyperintensity sign on fluid-attenuated inversion recovery images after revascularization surgery for moyamoya disease: possible involvement of intrinsic vascular vulnerability

A cortical hyperintensity on fluid-attenuated inversion recovery images (FLAIR cortical hyperintensity (FCH)) is an abnormal finding after revascularization surgery for moyamoya disease. This study aimed to investigate the pathophysiology of FCH through genetic analyses of RNF213 p.R4810K polymorphism and perioperative hemodynamic studies using single-photon emission computed tomography. We studied 96 hemispheres in 65 adults and 47 hemispheres in 27 children, who underwent combined direct and indirect revascularization. Early or late FCH was defined when it was observed on postoperative days 0-2 and 6-9, respectively. FCH scores (range: 0-6) were evaluated according to the extent of FCH in the operated hemisphere. FCHs were significantly more prevalent in adult patients than pediatric patients (early: 94% vs. 78%; late: 97% vs. 59%). In pediatric patients, FCH scores were significantly improved from the early to late phase regardless of the RNF213 genotype (mutant median [IQR]: 2 [1-5] vs. 1 [0-2]; wild-type median: 4 [0.5-6] vs. 0.5 [0-1.75]). In adults, FCH scores were significantly improved in patients with the wild-type RNF213 allele (median: 4 [2-5.25] vs. 2 [2, 3]); however, they showed no significant improvement in patients with the RNF213 mutation. FCH scores were significantly higher in patients with symptomatic cerebral hyperperfusion than those without it (early median: 5 [4, 5] vs. 4 [2-5]; late median: 4 [3-5] vs. 3 [2-4]). In conclusion, the RNF213 p.R4810K polymorphism was associated with prolonged FCH, and extensive FCH was associated with symptomatic cerebral hyperperfusion in adult patients with moyamoya disease.

The presence of pachymeningeal hyperintensity on non-contrast flair imaging in patients with spontaneous intracranial hypotension

PURPOSE

Traditionally, in the work-up of patients for spontaneous intracranial hypotension, T1 post-contrast imaging is performed in order to assess for pachymeningeal enhancement. The aim of this study is to assess whether pachymeningeal hyperintensity can be identified on a non-contrast FLAIR sequence in these patients as a surrogate sign for pachymeningeal enhancement.

METHODS

The patient cohort was identified from a prospectively maintained database of patients with a clinical diagnosis of intracranial hypotension. Patients who had both a post-contrast T1 sequence brain as well as non-contrast FLAR sequence of the brain were reviewed. Imaging was retrospectively reviewed by three independent neuroradiologists. Each study was assessed for the presence or absence of pachymeningeal hyperintensity on the FLAIR sequence.

RESULTS

From January 2010 to July 2022, 177 patients were diagnosed with spontaneous intracranial hypotension. In total, 121 were excluded as post-contrast imaging was not performed during their work-up. Twenty-four were excluded as the FLAIR sequence was performed after administration of contrast. Six were excluded as there was no pachymeningeal thickening present on T1 post-contrast imaging, although there were other signs of intracranial hypotension. The study group therefore consisted of 26 patients. Pachymeningeal thickening was correctly identified on the non-contrast FLAIR sequence in all patients (100%).

CONCLUSION

Where present, diffuse pachymeningeal hyperintensity can be accurately identified on a non-contrast FLAIR sequence in patients with spontaneous intracranial hypotension. This potentially obviates the need for gadolinium base contrast agents in the work-up of these patients.

Noninvasive prediction of histological grading in pediatric low-grade gliomas using preoperative T2-FLAIR radiomics features

OBJECTIVE

To investigate the clinical application value of radiomics based on magnetic resonance T2-FLAIR sequence images to distinguish pediatric low-grade gliomas of histological grades 1 and 2.

MATERIALS AND METHODS

Retrospective study of pediatric low-grade gliomas treated in our institution from April 2017 to July 2021. The histological grading follows the 2021 WHO classification of tumors of the central nervous system, and contains the necessary molecular phenotype information. The 3D slicer(https://slicer.org/) is used to outline VOI based on T2-FLAIR sequence and extract three-dimensional imaging features. All enrolled cases are randomly assigned to training set and test set according to 7:3; SMOTE (Synthetic Minority Oversampling Technique) method was used to balance the data of the training set, and then min-max normalization was used to normalize the data of the radiomics features. Dimension reduction and screening were carried out through Pearson Correlation Coefficients(PCC), analysis of variance(ANOVA), and least absolute shrinkage and selection operator(LASSO) algorithms for the radiomics features, The best binary logistic regression model is established by using the best subset regression, and the ROC curve, calibration curve and decision curve are used to analyze and evaluate the model.

RESULTS

A total of 113 patients were enrolled, 79 in the training set and 34 in the test set. There was no significant difference in sex and age between WHO grade 1 and 2 pediatric low-grade gliomas. A total of 1643 radiomics features were extracted from T2-FLAIR images, and finally 9 features were selected to construct a binary logistic regression model.The areas under the curve were 0.902 (95% confidence interval [CI] 0.814‒0.967) and 0.831 (95%CI 0.613‒0.975) for the training and test sets, respectively, with sensitivities of 86.70% and 85.7% and specificities of 81.3% and 59.3%, respectively. For model calibration, the mean absolute errors were 0.054 and 0.058 for the training and test sets, respectively. The decision curve analysis showed clinical gains for using the model in both the training and testing sets.

CONCLUSIONS

The T2-FLAIR radiomics model can be used for preoperative identification of grade 1 and grade 2 pediatric low-grade gliomas.

Suppression of inner ear signal intensity on fluid-attenuated inversion recovery magnetic resonance imaging in cats with vestibular disease

OBJECTIVES

Otitis media/interna (OMI) is the most common cause of peripheral vestibular disease in cats. The inner ear contains endolymph and perilymph, with perilymph being very similar in composition to cerebrospinal fluid (CSF). As a very-low-protein fluid, it would be expected that normal perilymph should suppress on fluid-attenuated inversion recovery (FLAIR) MRI sequences. Based on this, we hypothesized that MRI FLAIR sequences should provide a non-invasive way of diagnosing inflammatory/infectious diseases such as OMI in cats, something that has previously been demonstrated in humans and, more recently, in dogs.

METHODS

This was a retrospective cohort study in which 41 cats met the inclusion criteria. They were placed into one of four groups, based on presenting complaint: clinical OMI (group A); inflammatory central nervous system (CNS) disease (group B); non-inflammatory structural disease (group C); and normal brain MRI (control group; group D). Transverse T2-weighted and FLAIR MRI sequences at the level of the inner ears bilaterally were compared in each group. The inner ear was selected as a region of interest using Horos, with a FLAIR suppression ratio calculated to account for variability in signal intensity between MRIs. This FLAIR suppression ratio was then compared between groups. Statistical analyses were performed by an experienced statistician, with a general linear model used to compare mean FLAIR suppression ratio, CSF nucleated cell count and CSF protein concentration between groups.

RESULTS

The OMI group (group A) had significantly lower FLAIR suppression scores compared with all other groups. The CSF cell count was also significantly increased in the OMI (group A) and inflammatory CNS disease (group B) groups compared with the control group (group D).

CONCLUSIONS AND RELEVANCE

This study demonstrates the utility of MRI FLAIR sequences in diagnosing presumptive OMI in cats, similarly to in humans and dogs. This study is relevant to practicing veterinary neurologists and radiologists in interpreting MRI findings in cats with suspected OMI.

Alzheimer's and vascular disease classification using regional texture biomarkers in FLAIR MRI

Interactions between subcortical vascular disease and dementia due to Alzheimer's disease (AD) are unclear, and clinical overlap between the diseases makes diagnosis challenging. Existing studies have shown regional microstructural changes specific to each disease, and that textures in fluid-attenuated inversion recovery (FLAIR) MRI images may characterize abnormalities in tissue microstructure. This work aims to investigate regional FLAIR biomarkers that can differentiate dementia cohorts with and without subcortical vascular disease. FLAIR and diffusion MRI (dMRI) volumes were obtained in 65 mild cognitive impairment (MCI), 21 AD, 44 subcortical vascular MCI (scVMCI), 22 Mixed etiology, and 48 healthy elderly patients. FLAIR texture and intensity biomarkers were extracted from the normal appearing brain matter (NABM), WML penumbra, blood supply territory (BST), and white matter tract regions of each patient. All FLAIR biomarkers were correlated to dMRI metrics in each region and global WML load, and biomarker means between groups were compared using ANOVA. Binary classifications were performed using Random Forest classifiers to investigate the predictive nature of the regional biomarkers, and SHAP feature analysis was performed to further investigate optimal regions of interest for differentiating disease groups. The regional FLAIR biomarkers were strongly correlated to MD, while all biomarker regions but white matter tracts were strongly correlated to WML burden. Classification between Mixed disease and healthy, AD, and scVMCI patients yielded accuracies of 97%, 81%, and 72% respectively using WM tract biomarkers. Classification between scVMCI and healthy, MCI, and AD patients yielded accuracies of 89%, 84%, and 79% respectively using penumbra biomarkers. Only the classification between AD and healthy patients had optimal results using NABM biomarkers. This work presents novel regional FLAIR biomarkers that may quantify white matter degeneration related to subcortical vascular disease, and which indicate that investigating degeneration in specific regions may be more important than assessing global WML burden in vascular disease groups.

Histologic Definition of Enhancing Core and FLAIR Hyperintensity Region of Glioblastoma, IDH-Wild Type: A Clinico-Pathologic Study on a Single-Institution Series

The extent of resection beyond the enhancing core (EC) in glioblastoma IDH-wild type (GBM, IDHwt) is one of the most debated topics in neuro-oncology. Indeed, it has been demonstrated that local disease recurrence often arises in peritumoral areas and that radiologically-defined FLAIR hyperintensity areas of GBM IDHwt are often visible beyond the conventional EC. Therefore, the need to extend the surgical resection also to the FLAIR hyperintensity areas is a matter of debate. Since little is known about the histological composition of FLAIR hyperintensity regions, in this study we aimed to provide a comprehensive description of the histological features of EC and FLAIR hyperintensity regions sampled intraoperatively using neuronavigation and 5-aminolevulinic acid (5-ALA) fluorescence, in 33 patients with GBM, IDHwt. Assessing a total 109 histological samples, we found that FLAIR areas consisted in: (i) fragments of white matter focally to diffusely infiltrated by tumor cells in 76% of cases; (ii) a mixture of white matter with reactive astrogliosis and grey matter with perineuronal satellitosis in 15% and (iii) tumor tissue in 9%. A deeper knowledge of the histology of FLAIR hyperintensity areas in GBM, IDH-wt may serve to better guide neurosurgeons on the choice of the most appropriate surgical approach in patients with this neoplasm.

FLAIR-hyperintense lesions in anti-MOG-associated encephalitis with seizures overlaying anti-N-methyl-D-aspartate receptor encephalitis: a case report and literature review

Background

FLAIR-hyperintense lesions in anti-MOG-associated encephalitis with seizures (FLAMES) has been identified increasingly frequently in recent years. However, this rare MOG antibody disease may coexist with anti-N-methyl-D-aspartate receptor encephalitis (anti-NMDARe), in an overlap syndrome with unknown clinical features and prognosis.

Methods

We report a new case of this overlap syndrome and present a systematic review of similar cases in the literature to provide information on the clinical presentation, MRI features, EGG abnormalities, treatment, and prognosis of patients with this rare syndrome.

Results

A total of 12 patients were analyzed in the study. The most common clinical manifestations of FLAMES overlaid with anti-NMDARe were epilepsy (12/12), headache (11/12), and fever (10/12). Increases in intracranial pressure (median: 262.5 mmH₂O, range: 150-380 mmH₂O), cerebrospinal fluid (CSF) leukocyte count (median: 128×10⁶/L, range: 1-610×10⁶/L), and protein level (median: 0.48 g/L) were also observed. The median CSF anti-NMDAR antibody titer was 1:10 (1:1-1:32), while the median serum MOG antibody titer was 1:32 (1:10-1:1024). Seven cases exhibited unilateral cortical FLAIR hyperintensity, and five cases (42%) had bilateral cortical FLAIR hyperintensity, including four cases involving the bilateral medial frontal lobes. Of the 12 patients, five showed lesions at other sites (e.g., the brainstem, corpus callosum, or frontal orbital gyrus) before or after the development of cortical encephalitis. EEG showed slow waves in four cases, spike-slow waves in two cases, an epileptiform pattern in one case, and normal waves in two cases. The median number of relapses was two. Over a mean follow-up period of 18.5 months, only one patient experienced residual visual impairment, while the remaining 11 patients had good prognoses.

Conclusion

FLAMES alone is difficult to distinguish from overlap syndrome based on clinical features. However, FLAMES with bilateral medial frontal lobe involvement suggests the presence of the overlap syndrome.

Cerebral Amyloid Angiopathy-Related Inflammation: A Single-Center Experience and a Literature Review

Background: Limited data exist regarding the prevalence of clinical, neuroimaging, and genetic markers among patients diagnosed with Cerebral Amyloid Angiopathy−related inflammation (CAA-ri). We sought to determine these characteristics in patients diagnosed in our center and to summarize available literature published either as single-case reports or small case series (<5 patients). Methods: We reported our single-center experience of patients diagnosed with CAA-ri according to international criteria during a seven-year period (2015−2022), and we abstracted data from 90 previously published cases. Results: Seven patients (43% women, mean age 70 ± 13 years) were diagnosed with CAA-ri in our center. The most common symptom at presentation was focal neurological dysfunction (71%), and the most prevalent radiological finding was the presence of T2/FLAIR white matter hyperintensities (100%). All patients were treated with corticosteroids and had a favorable functional outcome. Among 90 previously published CAA-ri cases (51% women, mean age 70 ± 9 years), focal neurological dysfunction was the most common symptom (76%), followed by a cognitive decline (46%) and headache (34%). The most prevalent neuroimaging findings were cerebral microbleeds (85%), asymmetric T2/FLAIR white matter hyperintensities (81%), and gadolinium-enhancing T1-lesions (37%). Genetic testing for the Apolipoprotein-E gene was available in 27 cases; 59% carried the APOE ε4/ε4 genotype. The majority of the published CAA-ri cases (78%) received corticosteroid monotherapy, while 17 patients (19%) were treated with additional immunosuppressive treatment. Favorable functional outcome following treatment was documented in 70% of patients. Conclusion: Improving the vigilance of clinicians regarding the early recognition and accurate diagnosis of CAA-ri is crucial for swift therapy initiation, which may result in improved functional outcomes.

Multisite MRI reproducibility of lateral ventricular volume using the NAIMS cooperative pilot dataset

BACKGROUND AND PURPOSE

The North American Imaging in Multiple Sclerosis (NAIMS) multisite project identified interscanner reproducibility issues with T1-based whole brain volume (WBV). Lateral ventricular volume (LVV) acquired on T2-fluid-attenuated inverse recovery (FLAIR) scans has been proposed as a robust proxy measure. Therefore, we sought to determine the relative magnitude of scanner-induced T2-FLAIR-based LVV and T1-based WBV measurement errors in relation to clinically meaningful changes.

METHODS

This was a post hoc analysis of the NAIMS pilot dataset in which a relapsing-remitting MS patient with no intrastudy clinical or radiological activity was imaged twice on seven different Siemens scanners across the United States. LVV was determined using the automated NeuroSTREAM technique on T2-FLAIR and WBV was determined with SIENAX on high-resolution T1-MPRAGE. Average LVV and WBV were measured, and absolute intrascanner and interscanner coefficients of variation (CoVs) were calculated. The variabilities were compared to previously established annual pathological and clinically meaningful cutoffs of 0.40% for WBV and of 3.51% for LVV.

RESULTS

Mean LVV across all seven scan/rescan pairs was 45.87 ± 1.15 ml. Average LVV intrascanner CoV was 1.42% and interscanner CoV was 1.78%, both smaller than the reported annualized clinically meaningful cutoff of 3.51%. In contrast, intra- and interscanner CoVs for WBV (0.99% and 1.15%) were both higher than the established cutoff of 0.40%. Individually, 1/7 intrasite and 2/7 intersite pair-wise LVV comparisons were above the 3.51% cutoff, whereas 4/7 intrasite and 7/7 intersite WBV comparisons were above the 0.40% cutoff.

CONCLUSION

Fully automated LVV segmentation has higher absolute variability than WBV, but much lower relative variability compared to clinically relevant changes, and may therefore be a meaningful proxy outcome measure of neurodegeneration.

Causal structure discovery identifies risk factors and early brain markers related to evolution of white matter hyperintensities

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White matter health mediates the effect of vascular health on white matter hyperintensity.

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Midlife physical activities and smoking status impact late-life white matter health.

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Causal methods help understand the biological mechanisms underlying increased dementia risk.

Our goal was to understand the complex relationship between age, sex, midlife risk factors, and early white matter changes measured by diffusion tensor imaging (DTI) and their role in the evolution of longitudinal white matter hyperintensities (WMH). We identified 1564 participants (1396 cognitively unimpaired, 151 mild cognitive impairment and 17 dementia participants) with age ranges of 30–90 years from the population-based sample of Mayo Clinic Study of Aging. We used computational causal structure discovery and regression analyses to evaluate the predictors of WMH and DTI, and to ascertain the mediating effect of DTI on WMH. We further derived causal graphs to understand the complex interrelationships between midlife protective factors, vascular risk factors, diffusion changes, and WMH. Older age, female sex, and hypertension were associated with higher baseline and progression of WMH as well as DTI measures (P ≤ 0.003). The effects of hypertension and sex on WMH were partially mediated by microstructural changes measured on DTI. Higher midlife physical activity was predictive of lower WMH through a direct impact on better white matter tract integrity as well as an indirect effect through reducing the risk of hypertension by lowering BMI. This study identified key risks factors, early brain changes, and pathways that may lead to the evolution of WMH.

Rare pitfall in the magnetic resonance imaging of status epilepticus

Brain MRI in Status Epilepticus (SE) is often helpful in diagnosis, lateralization and localization of the seizure focus. MRI changes in SE include predominantly ipsilateral diffusion weighted imaging (DWI) changes in the hippocampus and pulvinar or similar changes involving basal ganglia, thalamus, cerebellum, brain stem and external capsule (Chatzikonstantinou et al., 2011 [1]). These changes are thought to be due to transient vasogenic and cytotoxic edema due to either transient damage or breakdown of blood brain barrier, proportional to the frequency and duration of the epileptic activity (Amato et al., 2001 [2]). Such changes may also be reflected on T2- weighted and T2-Fluid-Attenuated Inversion Recovery (FLAIR) sequences of MRI. Herein, we present a case of a transient FLAIR cerebrospinal fluid (CSF) hyperintensity on the second MRI brain in a patient with focal status epilepticus. This imaging finding led to diagnostic confusion and was initially thought to represent subarachnoid hemorrhage. However, lumbar puncture, brain computed tomography (CT), and a follow-up brain MRI ruled out that possibility and other CSF pathologies. We concluded that the transient FLAIR changes in the second brain MRI were related to a rare imaging pitfall caused by Gadolinium enhancement of CSF on the FLAIR sequence, popularly referred to as hyperintense acute reperfusion marker (HARM).

Hyperintense vessels on imaging account for neurological function independent of lesion volume in acute ischemic stroke

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Studies have revealed variable significance of FLAIR hyperintense vessels (FHV).

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We found number and location of FHV are associated with functional deficits.

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Functional measures correlated with FHV independently of lesion volume.

In acute ischemic stroke, reported relationships between lesion metrics and behavior have largely focused on lesion volume and location. However, hypoperfusion has been shown to correlate with deficits in the acute stage. Hypoperfusion is typically identified using perfusion imaging in clinical settings, which requires contrast. Unfortunately, contrast is contraindicated for some individuals. An alternative method has been proposed to identify hypoperfusion using hyperintense vessels on fluid-attenuated inversion recovery (FLAIR) imaging. This study aimed to validate the clinical importance of considering hypoperfusion when accounting for behavior in acute stroke and demonstrate the clinical utility of scoring the presence of hyperintense vessels to quantify it.

One hundred and fifty-three participants with acute ischemic stroke completed a battery of commonly-used neurological and behavioral measures. Clinical MRIs were used to determine lesion volume and to score the presence of hyperintense vessels seen on FLAIR images to estimate severity of hypoperfusion in six different vascular regions. National Institutes of Health Stroke Scale (NIHSS) scores, naming accuracy (left hemisphere strokes), and language content produced during picture description were examined in relation to lesion volume, hypoperfusion, and demographic variables using correlational analyses and multivariable linear regression.

Results showed that lesion volume and hypoperfusion, in addition to demographic variables, were independently associated with performance on NIHSS, naming, and content production. Specifically, hypoperfusion in the frontal lobe independently correlated with NIHSS scores, while hypoperfusion in parietal areas independently correlated with naming accuracy and content production.

These results correspond to previous reports associating hypoperfusion with function, confirming that hypoperfusion is an important consideration—beyond lesion volume—when accounting for behavior in acute ischemic stroke. Quantifying hypoperfusion using FLAIR hyperintense vessels can be an essential clinical tool when other methods of identifying hypoperfusion are unavailable or time prohibitive.

FLAIR MRI biomarkers of the normal appearing brain matter are related to cognition

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Normal appearing brain matter (NABM) biomarkers in FLAIR MRI are related to cognition.

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NABM texture in FLAIR MRI is correlated to mean diffusivity (MD) in dMRI.

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Analysis conducted on large multicentre FLAIR MRI dataset: 1400 subjects, 87 centers.

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NABM biomarkers vary differently across age and MoCA categories.

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Biomarkers showed differences in patients with AD dementia and vascular disease.

A novel biomarker panel was proposed to quantify macro and microstructural biomarkers from the normal-appearing brain matter (NABM) in multicentre fluid-attenuation inversion recovery (FLAIR) MRI. The NABM is composed of the white and gray matter regions of the brain, with the lesions and cerebrospinal fluid removed. The primary hypothesis was that NABM biomarkers from FLAIR MRI are related to cognitive outcome as determined by MoCA score. There were three groups of features designed for this task based on 1) texture: microstructural integrity (MII), macrostructural damage (MAD), microstructural damage (MID), 2) intensity: median, skewness, kurtosis and 3) volume: NABM to ICV volume ratio. Biomarkers were extracted from over 1400 imaging volumes from more than 87 centres and unadjusted ANOVA analysis revealed significant differences in means of the MII, MAD, and NABM volume biomarkers across all cognitive groups. In an adjusted ANCOVA model, a significant relationship between MoCA categories was found that was dependent on subject age for MII, MAD, intensity, kurtosis and NABM volume biomarkers. These results demonstrate that structural brain changes in the NABM are related to cognitive outcome (with different relationships depending on the age of the subjects). Therefore these biomarkers have high potential for clinical translation. As a secondary hypothesis, we investigated whether texture features from FLAIR MRI can quantify microstructural changes related to how “structured” or “damaged” the tissue is. Based on correlation analysis with diffusion weighted MRI (dMRI), it was shown that FLAIR MRI texture biomarkers (MII and MAD) had strong correlations to mean diffusivity (MD) which is related to tissue degeneration in the GM and WM regions. As FLAIR MRI is routinely collected for clinical neurological examinations, novel biomarkers from FLAIR MRI could be used to supplement current clinical biomarkers and for monitoring disease progression. Biomarkers could also be used to stratify patients into homogeneous disease subgroups for clinical trials, or to learn more about mechanistic development of dementia disease.

Contrast-enhanced weighted-T1 and FLAIR sequences in MRI of meningeal lesions

Magnetic resonance imaging (MRI) is widely used in meningeal lesions due to rapid and accurate diagnosis and prevention of serious complications. The aim of the present study was to compare these two sequences after injection of a contrast agent into meningeal lesions. This is a descriptive-analytical study that was performed in 2018-2020 on patients referred to the radiology ward with detection of any meningeal involvements in the MRI images. In addition to T1-W, FLAIR sequence imaging was also performed. Images were initially evaluated by two expert radiologists and a neurologist. The diagnostic values of the sequences were compared. Overall, a total number of 147 patients with meningeal lesions in their brain MRI entered the study. 57.1% of cases (84 patients) had an infectious etiology and 42.9% (63 patients) had a tumoral etiology. T1-W images without contrast were able to diagnose 78 cases of meningitis (92.8% of them), and FLAIR sequences could diagnose 82 patients (97.6% of them). Without contrast injection on MRI, the diagnostic value of T1-W sequence was higher than FLAIR sequence for tumoral lesions (P < 0.01). The enhancement degree of T1-W was higher for tumoral findings (P < 0.01). In contrast, the enhancement degree of the FLAIR sequence was higher for infectious findings, which was also statistically significant (P = 0.015). FLAIR sequences had 92% sensitivity and 85% specificity for diagnosis of brain inflammatory diseases. Similar analysis showed that T1 sequence had 82% sensitivity and 73% specificity for diagnosis of brain inflammatory diseases.

HARM revisited: Etiology of subarachnoid hyperintensities in brain FLAIR MRI

BACKGROUND

The hyperintense acute reperfusion marker (HARM) describes a phenomenon with a hyperintense signal in the subarachnoid space in Fluid-Attenuated Inversion Recovery (FLAIR) magnetic resonance imaging (MRI) sequences, presumably based on blood-brain barrier breakdown in acute stroke with reperfusion. However, this imaging phenomenon was described in other medical conditions.

AIM

Determination of the prevalence and associated clinical findings of this phenomenon in a large sample of patients with different neurological conditions.

METHODS

This is retrospective, single-center, observational study of 23,948 cerebral MRIs acquired in a Neurological University Clinic over 5 years. The prevalence of HARM, the underlying diagnosis, and damage pattern were examined by chart analysis; MRI was analyzed regarding the type of acute lesions, extent of microangiopathic lesions, and whether gadolinium-based contrast agent (GBCA) was given.

RESULTS

Among the MRI data, 84 images (0.35%) from 61 patients were HARM-positive without a subarachnoid signal abnormality in any other sequence. Etiologies were heterogeneous; 35 patients had a cerebrovascular disease (CVD; 19 patients received recanalization therapy), 12 patients had an inflammatory central nervous system (CNS) disease and 14 patients had epilepsy. GBCA was applied to 64% of the patients.

CONCLUSION

HARM was a rare radiological finding in a range of different neurological pathologies, not limited to stroke, or to previous reperfusion therapy and was not dependent on previous GBCA administration. Our data suggest that the term is too narrow in terms of the concepts of the underlying pathology. We propose to use the term FLAIR Subarachnoid Hyperintensity ("FLASH") phenomenon which might better reflect the observation that the radiological sign can be associated with a variety of central neurological conditions without a straightforward association with therapy.

Optimization of magnetization transfer contrast for EPI FLAIR brain imaging

PURPOSE

To evaluate the impact of magnetization transfer (MT) on brain tissue contrast in turbo-spin-echo (TSE) and EPI fluid-attenuated inversion recovery (FLAIR) images, and to optimize an MT-prepared EPI FLAIR pulse sequence to match the tissue contrast of a clinical reference TSE FLAIR protocol.

METHODS

Five healthy volunteers underwent 3T brain MRI, including single slice TSE FLAIR, multi-slice TSE FLAIR, EPI FLAIR without MT-preparation, and MT-prepared EPI FLAIR with variations of the MT-preparation parameters, including number of preparation pulses, pulse amplitude, and resonance offset. Automated co-registration and gray matter (GM) versus white matter (WM) segmentation was performed using a T1-MPRAGE acquisition, and the GM versus WM signal intensity ratio (contrast ratio) was calculated for each FLAIR acquisition.

RESULTS

Without MT preparation, EPI FLAIR showed poor tissue contrast (contrast ratio = 0.98), as did single slice TSE FLAIR. Multi-slice TSE FLAIR provided high tissue contrast (contrast ratio = 1.14). MT-prepared EPI FLAIR closely approximated the contrast of the multi-slice TSE FLAIR images for two combinations of the MT-preparation parameters (contrast ratio = 1.14). Optimized MT-prepared EPI FLAIR provided a 50% reduction in scan time compared to the reference TSE FLAIR acquisition.

CONCLUSION

Optimized MT-prepared EPI FLAIR provides comparable brain tissue contrast to the multi-slice TSE FLAIR images used in clinical practice.

Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia

BACKGROUND

White matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer's disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research.

METHODS

We used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS).

RESULTS

Across tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice's coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions.

CONCLUSION

To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.

Morphometric evaluation of traumatic axonal injury and the correlation with post-traumatic cerebral atrophy and functional outcome

INTRODUCTION

Imaging plays a crucial role in the diagnosis, prognosis and follow-up of traumatic brain injury. Whereas computed tomography plays a pivotal role in the acute setting, magnetic resonance imaging is best suited to detect the true extent of traumatic brain injury, and more specifically diffuse axonal injury. Post-traumatic brain atrophy is a well-known complication of traumatic brain injury.

PURPOSE

This study investigated the correlation between diffuse axonal injury detected with fluid-attenuated inversion recovery and susceptibility-weighted imaging magnetic resonance imaging, post-traumatic brain atrophy and functional outcome (Glasgow outcome scale - extended).

MATERIALS AND METHODS

Twenty patients with a closed head injury and diffuse axonal injury detected with fluid-attenuated inversion recovery and susceptibility-weighted imaging were included. The total volumes of the diffuse axonal injury fluid-attenuated inversion recovery lesions were determined for each subject's initial (<14 days) and follow-up magnetic resonance scan (average: day 303 ± 83 standard deviation). The different brain volumes were automatically quantified using a validated and both US Food and Drug Administration-cleared and CE-marked machine learning algorithm (icobrain). The number of susceptibility-weighted imaging lesions and functional outcome scores (Glasgow outcome scale - extended) were retrieved from the Collaborative European NeuroTrauma Effectiveness Research Traumatic Brain Injury dataset.

RESULTS

The volumetric fluid-attenuated inversion recovery diffuse axonal injury lesion load showed a significant inverse correlation with functional outcome (Glasgow outcome scale - extended) (r = -0.57; P = 0.0094) and white matter volume change (r = -0.50; P = 0.027). In addition, white matter volume change correlated significantly with the Glasgow outcome scale - extended score (P = 0.0072; r = 0.58). Moreover, there was a strong inverse correlation between longitudinal fluid-attenuated inversion recovery lesion volume change and whole brain volume change (r = -0.63; P = 0.0028). No significant correlation existed between the number of diffuse axonal injury susceptibility-weighted imaging lesions, brain atrophy and functional outcome.

CONCLUSIONS

Volumetric analysis of diffuse axonal injury on fluid-attenuated inversion recovery imaging and automated brain atrophy calculation are potentially useful tools in the clinical management and follow-up of traumatic brain injury patients with diffuse axonal injury.

A deep learning algorithm for white matter hyperintensity lesion detection and segmentation

PURPOSE

White matter hyperintensity (WMHI) lesions on MR images are an important indication of various types of brain diseases that involve inflammation and blood vessel abnormalities. Automated quantification of the WMHI can be valuable for the clinical management of patients, but existing automated software is often developed for a single type of disease and may not be applicable for clinical scans with thick slices and different scanning protocols. The purpose of the study is to develop and validate an algorithm for automatic quantification of white matter hyperintensity suitable for heterogeneous MRI data with different disease types.

METHODS

We developed and evaluated "DeepWML", a deep learning method for fully automated white matter lesion (WML) segmentation of multicentre FLAIR images. We used MRI from 507 patients, including three distinct white matter diseases, obtained in 9 centres, with a wide range of scanners and acquisition protocols. The automated delineation tool was evaluated through quantitative parameters of Dice similarity, sensitivity and precision compared to manual delineation (gold standard).

RESULTS

The overall median Dice similarity coefficient was 0.78 (range 0.64 ~ 0.86) across the three disease types and multiple centres. The median sensitivity and precision were 0.84 (range 0.67 ~ 0.94) and 0.81 (range 0.64 ~ 0.92), respectively. The tool's performance increased with larger lesion volumes.

CONCLUSION

DeepWML was successfully applied to a wide spectrum of MRI data in the three white matter disease types, which has the potential to improve the practical workflow of white matter lesion delineation.

Unilateral decrease in inner ear signal in fluid-attenuated inversion recovery sequences in previously suspected canine idiopathic vestibular syndrome

The aetiology of canine idiopathic vestibular syndrome (IVS) remains unclear. In human medicine, characteristic magnetic resonance imaging (MRI) techniques are used to demonstrate differences in endolymph composition between affected and unaffected inner ears. The purpose of this study was to determine whether similar MRI techniques could help to detect changes in the inner ears of canine IVS patients. Medical records from two veterinary referral clinics were reviewed retrospectively. Dogs were included if they had a diagnosis of IVS, obvious lateralisation of clinical signs, and an MRI of the vestibular system. A region of interest (ROI) was manually outlined by defining the anatomical area of the inner ear in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images. In order to calculate the ratio of FLAIR suppression of each ear, the mean grey value of the ROI was determined in both sequences. If a unilateral decrease in suppression was identified, it was compared with the direction of clinical signs. In total, 80 dogs were included in the study. There was a significantly lower degree of suppression on the affected compared to the unaffected side (0.8886 vs. 0.9348, respectively; P = 0.0021). In 92.5% of cases, there was agreement between the most suppressed side on MRI and the direction of clinical signs. This study provides preliminary evidence about the appearance of endolymph on MRI of dogs with IVS. Further studies are needed to investigate associations between the severity of MRI changes and prognosis.

MRI as a first-line imaging modality in acute ischemic stroke: a sustainable concept

Background:

Computed tomography (CT) scans are the first-line imaging technique in acute stroke patients based on the argument of rapid feasibility. Using magnetic resonance imaging (MRI) as the first-line imaging technique is the exception to the rule, although it provides much more diagnostic information and avoids exposure to radiation. We evaluated whether an MRI-based acute stroke concept is fast, suitable, and useful to improve recanalization rates and patient outcomes.

Methods:

We performed a retrospective observational cohort study comparing patients treated at a comprehensive stroke center (Ulm/Germany) applying an MRI-based acute stroke concept with patients recorded in a large comprehensive stroke registry in Baden-Württemberg (Germany). We analyzed the quality indicators of acute stroke treatment, patient’s outcome, and the rate of transient ischemic attack (TIA) at discharge.

Results:

A total of 2182 patients from Ulm and 82,760 patients from the Baden-Württemberg (BW) stroke registry (including 29,575 patients of comprehensive stroke centers (BWc)) were included. Intravenous thrombolysis rate was higher in Ulm than in BW or the BWc stroke centers (Ulm 27.4% versus BW 20.9% versus BWc 26.1; p < 0.01), while a door-to-needle time <30 min could be achieved more frequently (Ulm 73.6% versus BW 44.1% versus BWc 47.1%; p < 0.01). Thrombectomy rate in patients with a proximal vascular occlusion was higher (Ulm 69.2% versus BW 50.7% versus BWc 59.3; p < 0.01). The number of TIA diagnoses was lower (Ulm 16.2% versus BW 24.6% versus BWc 19.9%; p < 0.01). More patients showed a shift to a favorable outcome (Ulm 21.1% versus BW 16.9% versus BWc 15.3; p < 0.01). Complication rates were similar.

Conclusions:

The MRI-based acute stroke concept is suitable, fast and seems to be beneficial. The time-dependent quality indicators were better both in comparison to all stroke units and to the comprehensive stroke units in the area. Based on the MRI concept, high rates of recanalization procedures and fewer TIA diagnoses could be observed. In addition, there was a clear trend towards an improved clinical outcome. A clinical trial comparing the effects of CT and MRI as the primary imaging technique in otherwise identical stroke unit settings is warranted.

Volume of White Matter Hyperintensities, and Cerebral Micro-Bleeds

PURPOSE

In the past years the significance of white matter hyperintensities (WMH) has gained raising attention because it is considered a marker of severity of different pathologies. Another condition that in the last years has been assessed in the neuroradiology field is cerebral microbleeds (CMB). The purpose of this work was to evaluate the association between the volume of WMH and the presence and characteristics of CMB.

MATERIAL AND METHODS

Sixty-five consecutive (males 45; median age 70) subjects were retrospectively analyzed with a 1.5 Tesla scanner. WMH volume was quantified with a semi-automated procedure considering the FLAIR MR sequences whereas the CMB were studied with the SWI technique and CMBs were classified as absent (grade 1), mild (grade 2; total number of CMBs: 1-2), moderate (grade 3; total number of CMBs: 3-10), and severe (grade 4; total number of CMBs: >10). Moreover, overall number of CMBs and the maximum diameter were registered.

RESULTS

Prevalence of CMBs was 30.76% whereas WMH 81.5%. Mann-Whitney test showed a statistically significant difference in WMH volume between subjects with and without CMBs (p < 0.001). Pearson analysis showed significant correlation between CMB grade, number and maximum diameter and WMH. The better ROC area under the curve (Az) was obtained by the hemisphere volume with a 0.828 (95% CI from 0.752 to 0,888; SD = 0.0427; p value = 0.001). The only parameters that showed a statistically significant association in the logistic regression analysis were Hemisphere volume of WMH (p = 0.001) and Cholesterol LDL (p = 0.0292).

CONCLUSION

In conclusion, the results of this study suggest the presence of a significant correlation between CMBs and volume of WMH. No differences were found between the different vascular territories.

Implementation of emergent MRI for wake-up stroke: a single-center experience

PURPOSE

Recent updates in national guidelines for management of acute ischemic stroke in patients of unknown time of symptom onset ("wake-up" strokes) incorporate, for the first time, use of emergent MRI. In this retrospective case series, we analyze our experience at a Comprehensive Stroke Center implementing a new workflow including MRI in this clinical setting. This study also describes "DWI-FLAIR" mismatch, a critical concept for the interpretation of emergent brain MRIs performed for wake-up strokes.

METHODS

Over a 14-month period, all brain MRIs for wake-up stroke were identified. The imaging was analyzed by two board-certified, fellowship-trained neuroradiologists, and a diagnosis of DWI-FLAIR mismatch was made by consensus. Process metrics assessed included interval between last known well time and brain imaging, interval between CT and MRI, and interval between brain MRI and interpretation.

RESULTS

Sixteen patients with a history of "wake-up stroke" were identified. Thirteen of the 16 patients (81.3%) were found to have a DWI-FLAIR mismatch, suggesting infarct < 4.5 h old. The mean time between last known well and MRI was 7.89 h with mean interval between CT and MRI of 1.83 h. Forty-six percent of patients with DWI-FLAIR mismatch received intravenous thrombolysis.

CONCLUSION

In this "real world" assessment of incorporation of emergent MRI for wake-up strokes, there were several key factors to successful implementation of this new workflow, including effective and accurate description of MRI findings; close collaboration amongst stakeholders; 24/7 availability of MRI; and 24/7 onsite coverage by neurology and radiology physicians.

FLAIRectomy in Supramarginal Resection of Glioblastoma Correlates With Clinical Outcome and Survival Analysis: A Prospective, Single Institution, Case Series

BACKGROUND

Extent of tumor resection (EOTR) in glioblastoma surgery plays an important role in improving survival.

OBJECTIVE

To analyze the efficacy, safety and reliability of fluid-attenuated inversion-recovery (FLAIR) magnetic resonance (MR) images used to guide glioblastoma resection (FLAIRectomy) and to volumetrically measure postoperative EOTR, which was correlated with clinical outcome and survival.

METHODS

A total of 68 glioblastoma patients (29 males, mean age 65.8) were prospectively enrolled. Hyperintense areas on FLAIR images, surrounding gadolinium-enhancing tissue on T1-weighted MR images, were screened for signal changes suggesting tumor infiltration and evaluated for supramaximal resection. The surgical protocol included 5-aminolevulinic acid (5-ALA) fluorescence, neuromonitoring, and intraoperative imaging tools. 5-ALA fluorescence intensity was analyzed and matched with the different sites on navigated MR, both on postcontrast T1-weighted and FLAIR images. Volumetric evaluation of EOTR on T1-weighted and FLAIR sequences was compared.

RESULTS

FLAIR MR volumetric evaluation documented larger tumor volume than that assessed on contrast-enhancing T1 MR (72.6 vs 54.9 cc); residual tumor was seen in 43 patients; postcontrast T1 MR volumetric analysis showed complete resection in 64 cases. O6-methylguanine-DNA methyltransferase promoter was methylated in 8/68 (11.7%) cases; wild type Isocytrate Dehydrogenase-1 (IDH-1) was found in 66/68 patients. Progression free survival and overall survival (PFS and OS) were 17.43 and 25.11 mo, respectively. Multiple regression analysis showed a significant correlation between EOTR based on FLAIR, PFS (R2 = 0.46), and OS (R2 = 0.68).

CONCLUSION

EOTR based on FLAIR and 5-ALA fluorescence is feasible. Safety of resection relies on the use of neuromonitoring and intraoperative multimodal imaging tools. FLAIR-based EOTR appears to be a stronger survival predictor compared to gadolinium-enhancing, T1-based resection.

Value of Contrast-Enhanced FLAIR Images for the Depiction of Papilledema

Teaching Point: Contrast-enhanced FLAIR images have unsurpassed value for the radiological depiction of hypertensive papilledema. FLAIR acquisition should therefore be performed after intravenous contrast, especially in the of work-up of intracranial hypertension and/or tumor.

Volume of White Matter Hyperintensities, and Cerebral Micro-Bleeds

PURPOSE

In the past years the significance of white matter hyperintensities (WMH) has gained raising attention because it is considered a marker of severity of different pathologies. Another condition that in the last years has been assessed in the neuroradiology field is cerebral microbleeds (CMB). The purpose of this work was to evaluate the association between the volume of WMH and the presence and characteristics of CMB.

MATERIAL AND METHODS

Sixty-five consecutive (males 45; median age 70) subjects were retrospectively analyzed with a 1.5 Tesla scanner. WMH volume was quantified with a semi-automated procedure considering the FLAIR MR sequences whereas the CMB were studied with the SWI technique and CMBs were classified as absent (grade 1), mild (grade 2; total number of CMBs: 1-2), moderate (grade 3; total number of CMBs: 3-10), and severe (grade 4; total number of CMBs: >10). Moreover, overall number of CMBs and the maximum diameter were registered.

RESULTS

Prevalence of CMBs was 30.76% whereas WMH 81.5%. Mann-Whitney test showed a statistically significant difference in WMH volume between subjects with and without CMBs (p < 0.001). Pearson analysis showed significant correlation between CMB grade, number and maximum diameter and WMH. The better ROC area under the curve (Az) was obtained by the hemisphere volume with a 0.828 (95% CI from 0.752 to 0,888; SD = 0.0427; p value = 0.001). The only parameters that showed a statistically significant association in the logistic regression analysis were Hemisphere volume of WMH (p = 0.001) and Cholesterol LDL (p = 0.0292).

CONCLUSION

In conclusion, the results of this study suggest the presence of a significant correlation between CMBs and volume of WMH. No differences were found between the different vascular territories.

Influence of supramarginal resection on survival outcomes after gross-total resection of IDH-wild-type glioblastoma

OBJECTIVE

The authors' goal was to use a multicenter, observational cohort study to determine whether supramarginal resection (SMR) of FLAIR-hyperintense tumor beyond the contrast-enhanced (CE) area influences the overall survival (OS) of patients with isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma after gross-total resection (GTR).

METHODS

The medical records of 888 patients aged ≥ 18 years who underwent resection of GBM between January 2011 and December 2017 were reviewed. Volumetric measurements of the CE tumor and surrounding FLAIR-hyperintense tumor were performed, clinical variables were obtained, and associations with OS were analyzed.

RESULTS

In total, 101 patients with newly diagnosed IDH-wt GBM who underwent GTR of the CE tumor met the inclusion criteria. In multivariate analysis, age ≥ 65 years (HR 1.97; 95% CI 1.01-2.56; p < 0.001) and contact with the lateral ventricles (HR 1.59; 95% CI 1.13-1.78; p = 0.025) were associated with shorter OS, but preoperative Karnofsky Performance Status ≥ 70 (HR 0.47; 95% CI 0.27-0.89; p = 0.006), MGMT promotor methylation (HR 0.63; 95% CI 0.52-0.99; p = 0.044), and increased percentage of SMR (HR 0.99; 95% CI 0.98-0.99; p = 0.02) were associated with longer OS. Finally, 20% SMR was the minimum percentage associated with beneficial OS (HR 0.56; 95% CI 0.35-0.89; p = 0.01), but > 60% SMR had no significant influence (HR 0.74; 95% CI 0.45-1.21; p = 0.234).

CONCLUSIONS

SMR is associated with improved OS in patients with IDH-wt GBM who undergo GTR of CE tumor. At least 20% SMR of the CE tumor was associated with beneficial OS, but greater than 60% SMR had no significant influence on OS.

Diffusion-weighted MRI and FLAIR sequence for differentiation of hydatid cysts and simple cysts in the liver

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DWI signal characteristics are useful in differentiating between hydatid cysts and simple cysts.

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ADC values (b600 and b1000) can distinguish hydatid cyst and simple cyst.

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FLAIR sequence contributes to the differentiation of type 2 hydatid and simple cysts.

Purpose

The contribution of DWI and FLAIR to the differential diagnosis of type 1, 2, and 3 hydatid cysts and simple liver cysts was investigated according to the Gharbi classification. This study is the first report using FLAIR sequence for the differential diagnosis of liver hydatid cysts in this regard.

Methods

A total of 82 hydatid cysts and 40 simple cysts were scanned with DWI (in b600-b1000 values) and FLAIR sequence. In 64 patients included in the study, a total of 122 cystic lesions were diagnosed histopathologically or during follow-up. FLAIR and DWI signal characteristics were evaluated, and ADC values were calculated.

Results

The mean ADC value of hydatid cysts on DWI (b600) was 3.07 ± 0.41 × 10⁻³ s/mm², while it was 3.91 ± 0.51 × 10⁻³ s/mm² for simple cysts and the difference was statistically significant (p < 0.05). On b1000 DWI, the mean ADC values of hydatid and simple cysts were 2.99 ± 0.38 × 10⁻³ s/mm² and 3.43 ± 0:29 × 10⁻³ s/mm², respectively (p < 0.05). The qualitative evaluation of the signal intensity on b600−1000 DWI demonstrated the difference between the simple and hydatid cyst groups (p < 0.05). Type 2 hydatid cysts alone were distinguished from type 2–3 hydatid and simple cysts by FLAIR (p < 0.05).

Conclusions

ADC values can distinguish between hydatid cyst and simple cyst. FLAIR contributes to the differentiation of type 2 hydatid and simple cysts.

Semi-Supervised Learning in Medical MRI Segmentation: Brain Tissue with White Matter Hyperintensity Segmentation Using FLAIR MRI

White-matter hyperintensity (WMH) is a primary biomarker for small-vessel cerebrovascular disease, Alzheimer's disease (AD), and others. The association of WMH with brain structural changes has also recently been reported. Although fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) provide valuable information about WMH, FLAIR does not provide other normal tissue information. The multi-modal analysis of FLAIR and T1-weighted (T1w) MRI is thus desirable for WMH-related brain aging studies. In clinical settings, however, FLAIR is often the only available modality. In this study, we thus propose a semi-supervised learning method for full brain segmentation using FLAIR. The results of our proposed method were compared with the reference labels, which were obtained by FreeSurfer segmentation on T1w MRI. The relative volume difference between the two sets of results shows that our proposed method has high reliability. We further evaluated our proposed WMH segmentation by comparing the Dice similarity coefficients of the reference and the results of our proposed method. We believe our semi-supervised learning method has a great potential for use for other MRI sequences and will encourage others to perform brain tissue segmentation using MRI modalities other than T1w.

Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review

Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for detecting, characterizing and monitoring brain tumors but definitive diagnosis still relies on surgical pathology. Machine learning has been applied to the analysis of MRI data in glioma research and has the potential to change clinical practice and improve patient outcomes. This systematic review synthesizes and analyzes the current state of machine learning applications to glioma MRI data and explores the use of machine learning for systematic review automation. Various datapoints were extracted from the 153 studies that met inclusion criteria and analyzed. Natural language processing (NLP) analysis involved keyword extraction, topic modeling and document classification. Machine learning has been applied to tumor grading and diagnosis, tumor segmentation, non-invasive genomic biomarker identification, detection of progression and patient survival prediction. Model performance was generally strong (AUC = 0.87 ± 0.09; sensitivity = 0.87 ± 0.10; specificity = 0.0.86 ± 0.10; precision = 0.88 ± 0.11). Convolutional neural network, support vector machine and random forest algorithms were top performers. Deep learning document classifiers yielded acceptable performance (mean 5-fold cross-validation AUC = 0.71). Machine learning tools and data resources were synthesized and summarized to facilitate future research. Machine learning has been widely applied to the processing of MRI data in glioma research and has demonstrated substantial utility. NLP and transfer learning resources enabled the successful development of a replicable method for automating the systematic review article screening process, which has potential for shortening the time from discovery to clinical application in medicine.

Plasma hydrogen sulfide: A biomarker of Alzheimer's disease and related dementias

While heart disease remains a common cause of mortality, cerebrovascular disease also increases with age, and has been implicated in Alzheimer's disease and related dementias (ADRD). We have described hydrogen sulfide (H₂S), a signaling molecule important in vascular homeostasis, as a biomarker of cardiovascular disease. We hypothesize that plasma H₂S and its metabolites also relate to vascular and cognitive dysfunction in ADRD. We used analytical biochemical methods to measure plasma H₂S metabolites and MRI to evaluate indicators of microvascular disease in ADRD. Levels of total H₂S and specific metabolites were increased in ADRD versus controls. Cognition and microvascular disease indices were correlated with H₂S levels. Total plasma sulfide was the strongest indicator of ADRD, and partially drove the relationship between cognitive dysfunction and white matter lesion volume, an indicator of microvascular disease. Our findings show that H₂S is dysregulated in dementia, providing a potential biomarker for diagnosis and intervention.

Interpretation of fluid-attenuated inversion recovery vascular hyperintensity in stroke

Fluid-attenuation inversion recovery (FLAIR) vascular hyperintensity (FVH) is a common presentation on brain magnetic resonance images of patients with acute ischemic stroke. This sign is known as a sluggish collateral flow. Although FVH represents the large ischemic penumbra and collateral circulation, the clinical significance of FVH has not been established. Varying protocols for FLAIR, treatment differences, and heterogeneity of endpoints across studies have complicated the interpretation of FVH in patients with acute stroke. In this review article, we describe the mechanism of FVH, as well as its association with functional outcome, perfusion-weighted images, and large artery stenosis. In addition, we review the technological variables that affect FVH and discuss the future perspectives.

Multicentric non-enhancing lesions in glioblastoma: A retrospective study

Glioblastoma (GBM) typically presents as a single lesion. Multicentric GBM are defined as well separated lesions on MRI (enhancing and non-enhancing). Multicentric GBM with non-enhancing lesions (MNE-GBM) are rarely described in literature. We aimed at describing the radiologic characteristics, treatment, and clinical course of those patients. The institutional neuropathological database was searched for GBM patients diagnosed between 1/1/2015 and 31/05/2018. All pre-operative MRI brain scans were reviewed to identify patients with MNE-GBM. Electronic medical records and follow-up MRI scans were reviewed to assess progression-free survival (PFS) and overall survival (OS). Out of 149 adult patients with newly diagnosed GBM, 12 met the inclusion criteria of MNE-GBM, all of them presented at least one enhancing lesion. Median follow-up for the MNE-GBM patients was 16.1 months. At last follow-up, all patients had recurrence (median PFS 7.6 months) and eleven patients had deceased. Median OS was 16.2 months (95% CI, 4.1-27.5). Eleven patients received radiotherapy concomitant with temozolomide as initial treatment. Radiation field included all the disease foci (enhancing and non-enhancing lesions) in 8 patients, five of them progressed within the non-enhancing lesion. Three patients did not receive radiation for the entire non-enhancing lesions, and two of them progressed within the non-irradiated areas. In conclusion, MNE-GBM is not rare, and has high risk of aggressive progression within the separate non-enhancing lesion.

FLAIR hyperintensity along the brainstem surface in leptomeningeal metastases: a case series and literature review

Background

The incidence of leptomeningeal metastasis (LM) is underestimated because of its non-specific signs and the low sensitivity of clinical diagnostic modalities. Cerebrospinal magnetic resonance (MR) imaging with and without contrast enhancement (CE) is a gold standard for the neuroradiological assessment of patients with suspected LM. Previous studies suggested that some LM cases show changes of the brainstem surface on non-contrast MR images without or before the appearance of abnormalities on CE images. We assessed the features of this non-contrast MR finding in a cohort of LM patients in this retrospective single-institution study.

Methods

We reviewed head MR images and clinical data of 142 consecutive patients in whom the final diagnosis was LM.

Results

We found that 11 of these 142 patients (7.7%) with LM had band-like hyperintensity on the brainstem surface on non-enhanced FLAIR images, which looked like bloomy rind on cheese. Three of seven patients who were examined using diffusion-weighted imaging showed restricted diffusion in the corresponding lesion site. The above-mentioned 11 patients included 10 women and 1 man, with a median age of 61 years. All 11 patients had primary lung adenocarcinoma. Seven patients had symptomatic hydrocephalus. Ten patients had EGFR-mutated and one had ALK-rearrangement adenocarcinomas. Before the diagnosis of LM, 10 patients had undergone systemic therapy with EGFR-TKI or pemetrexed, and 1 patient with ALK inhibitor and bevacizumab.

Conclusions

We present a series of patients with bloomy rind sign that is non-enhancing LM reliably detected by FLAIR hyperintensity on the brainstem surface. This finding is rare, but may reflect the spread of cancer cells in both the leptomeningeal membrane and the surface of the brain parenchyma specifically in patients with lung adenocarcinomas. Further study is needed to determine the clinical significance of this sign, and the pathophysiological factors associated with it may be clarified by analyzing serial MR images in a larger cohort of patients treated for LM.

Improving FLAIR SAR efficiency at 7T by adaptive tailoring of adiabatic pulse power through deep learning B 1 + estimation

PURPOSE

The purpose of this study is to demonstrate a method for specific absorption rate (SAR) reduction for 2D T₂ -FLAIR MRI sequences at 7 T by predicting the required adiabatic radiofrequency (RF) pulse power and scaling the RF amplitude in a slice-wise fashion.

METHODS

We used a time-resampled frequency-offset corrected inversion (TR-FOCI) adiabatic pulse for spin inversion in a T₂ -FLAIR sequence to improve B 1 + homogeneity and calculated the pulse power required for adiabaticity slice-by-slice to minimize the SAR. Drawing on the implicit B 1 + inhomogeneity in a standard localizer scan, we acquired 3D AutoAlign localizers and SA2RAGE B 1 + maps in 28 volunteers. Then, we trained a convolutional neural network (CNN) to estimate the B 1 + profile from the localizers and calculated pulse scale factors for each slice. We assessed the predicted B 1 + profiles and the effect of scaled pulse amplitudes on the FLAIR inversion efficiency in oblique transverse, sagittal, and coronal orientations.

RESULTS

The predicted B 1 + amplitude maps matched the measured ones with a mean difference of 9.5% across all slices and participants. The slice-by-slice scaling of the TR-FOCI inversion pulse was most effective in oblique transverse orientation and resulted in a 1 min and 30 s reduction in SAR induced delay time while delivering identical image quality.

CONCLUSION

We propose a SAR reduction technique based on the estimation of B 1 + profiles from standard localizer scans using a CNN and show that scaling the inversion pulse power slice-by-slice for FLAIR sequences at 7T reduces SAR and scan time without compromising image quality.