Fluid-attenuated Inversion Recovery Sequences Research Articles

Simulated MRI Artifacts: Testing Machine Learning Failure Modes.

Objective. Seven types of MRI artifacts, including acquisition and preprocessing errors, were simulated to test a machine learning brain tumor segmentation model for potential failure modes. Introduction. Real-world medical deployments of machine learning algorithms are less common than the number of medical research papers using machine learning. Part of the gap between the performance of models in research and deployment comes from a lack of hard test cases in the data used to train a model. Methods. These failure modes were simulated for a pretrained brain tumor segmentation model that utilizes standard MRI and used to evaluate the performance of the model under duress. These simulated MRI artifacts consisted of motion, susceptibility induced signal loss, aliasing, field inhomogeneity, sequence mislabeling, sequence misalignment, and skull stripping failures. Results. The artifact with the largest effect was the simplest, sequence mislabeling, though motion, field inhomogeneity, and sequence misalignment also caused significant performance decreases. The model was most susceptible to artifacts affecting the FLAIR (fluid attenuation inversion recovery) sequence. Conclusion. Overall, these simulated artifacts could be used to test other brain MRI models, but this approach could be used across medical imaging applications.

Magnetic Resonance Imaging Evaluation of Perinatal Hypoxic Ischemic Encephalopathy: An Institutional Experience.

Background Hypoxic–ischemic encephalopathy (HIE) is the most commonly diagnosed neurological abnormality affecting children leading to severe neurological deficits and a cause of neonatal mortality. HIE constitutes a diagnostic challenge in the prematurely born and full-term neonates. HIE causes severe neurological deficit in children and many a times goes unnoticed in early stages. The various patterns of central nervous system (CNS) involvement in HIE are dependent on factors, such as severity and duration of hypoxia, and brain maturity in preterm and full-term patients. Magnetic resonance imaging (MRI) has prognostic significance in detecting patterns of HIE secondary to mild-to-moderate and severe hypoxias and the imaging findings are highly dependent on the time at which imaging is done. MRI helps determine the prognosis of brain development in patients with HIE. Objective This retrospective study elucidates the spectrum of MRI findings in preterm and full-term patients with HIE on MRI. Materials and Methods This retrospective descriptive study was conducted at a tertiary care center between April 2017 and May 2019 on 50 patients with a clinical diagnosis of HIE using a General Electric (GE) 1.5-Tesla MRI scanner. Various patterns of HIE were evaluated on MRI in preterm and full-term patients. Results This retrospective study evaluated MRI findings in 50 infants diagnosed with HIE. Eighteen (36%) were preterm and 32 (64%) were full-term patients. Thirty-five (70%) were male and 15 (30%) were female patients. In the current study, developmental delay was the most commonly associated clinical entity in both preterm and full-term patients. In preterm patients, periventricular leukomalacia was the most prevalent MRI finding, and in full-term patients, subcortical and periventricular white matter hyperintensities on T2-weighted and fluid-attenuated inversion recovery (FLAIR) sequences were most commonly encountered. Conclusion MRI is the primary imaging modality of choice in preterm and full-term patients with HIE, as it helps determine the severity of hypoxic–ischemic injury by understanding the pattern of brain involvement. In the current study, distinguishable patterns of MRI findings secondary to birth asphyxia and ischemic insult were elucidated in both preterm and full-term patients who are highly dependent on the level of brain maturity at the time of imaging. Regular MRI follow-up has a prognostic significance in HIE with accurate prediction of neurodevelopmental outcome on follow-up studies.

Magnetic resonance image-based brain tumour segmentation methods: A systematic review.

BackgroundImage segmentation is an essential step in the analysis and subsequent characterisation of brain tumours through magnetic resonance imaging. In the literature, segmentation methods are empowered by open-access magnetic resonance imaging datasets, such as the brain tumour segmentation dataset. Moreover, with the increased use of artificial intelligence methods in medical imaging, access to larger data repositories has become vital in method development.PurposeTo determine what automated brain tumour segmentation techniques can medical imaging specialists and clinicians use to identify tumour components, compared to manual segmentation.MethodsWe conducted a systematic review of 572 brain tumour segmentation studies during 2015–2020. We reviewed segmentation techniques using T1-weighted, T2-weighted, gadolinium-enhanced T1-weighted, fluid-attenuated inversion recovery, diffusion-weighted and perfusion-weighted magnetic resonance imaging sequences. Moreover, we assessed physics or mathematics-based methods, deep learning methods, and software-based or semi-automatic methods, as applied to magnetic resonance imaging techniques. Particularly, we synthesised each method as per the utilised magnetic resonance imaging sequences, study population, technical approach (such as deep learning) and performance score measures (such as Dice score).Statistical testsWe compared median Dice score in segmenting the whole tumour, tumour core and enhanced tumour.ResultsWe found that T1-weighted, gadolinium-enhanced T1-weighted, T2-weighted and fluid-attenuated inversion recovery magnetic resonance imaging are used the most in various segmentation algorithms. However, there is limited use of perfusion-weighted and diffusion-weighted magnetic resonance imaging. Moreover, we found that the U-Net deep learning technology is cited the most, and has high accuracy (Dice score 0.9) for magnetic resonance imaging-based brain tumour segmentation.ConclusionU-Net is a promising deep learning technology for magnetic resonance imaging-based brain tumour segmentation. The community should be encouraged to contribute open-access datasets so training, testing and validation of deep learning algorithms can be improved, particularly for diffusion- and perfusion-weighted magnetic resonance imaging, where there are limited datasets available.

Detailed insight into magnetic resonance assessment of Ménière’s disease – description of methodology and imaging findings in a case series

PurposeThe study aimed to describe the methodology and detailed interpretation of magnetic resonance imaging (MRI) in patients with Ménière’s disease (MD).Material and methodsMRIs were performed on a 3T scanner. The three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) sequence 4 hours after a double dose of intravenous contrast was added to the standard MRI protocol in patients with clinically diagnosed MD. MRI findings of 7 patients with unilateral MD were analysed using 2 qualitative grading systems by Barath and Bernaerts.ResultsIn MRI, the following changes in the group of patients with MD were observed: lack of endolymphatic hydrops (cases #1 and #7), various grades of cochlear hydrops (cases #2 and #3), various grades of vestibular hydrops (cases #4, #5, and #6), endolymphatic hydrops herniation into the semi-circular canal (case #6), and more robust perilymphatic enhancement (case #7).ConclusionsIn patients with MD, endolymphatic hydrops can be studied on MRI using 3D-FLAIR delayed post-contrast images. The qualitative grading system may be easily used in endolymphatic hydrops assessment. Recently described new radiological signs of MD such as increased perilymphatic enhancement of the cochlea and an extra low-grade VH may increase MD diagnosis sensitivity. MRI not only supports the clinical diagnosis of MD but also may help to understand its pathophysiology.

Clinical Value of 3D-FLAIR MRI in Idiopathic Sudden Sensorineural Hearing Loss

Three-dimensional fluid-attenuated inversion recovery sequence magnetic resonance imaging (3D-FLAIR MRI) has been used in the diagnosis of inner ear diseases. However, the relevance of 3D-FLAIR MRI appearances with multiple features and prognosis of patients with idiopathic sudden sensorineural hearing loss (ISSNHL) remains unclear. This study was a retrospective trial. We recruited 1300 patients with unilateral ISSNHL hospitalized from May 2017 to January 2019. They were divided into four groups according to their 3D-FLAIR MRI appearances: normal (n = 739), inner ear hemorrhage (n = 218), increased protein content (n = 288), and blood-labyrinth barrier damage (n = 55). The correlation between 3D-FLAIR MRI appearances and the degree or type of deafness of the participants was analyzed. There was a statistical difference in the deafness side (p < 0.001) and vestibular dysfunction (p < 0.001) among the four groups. There was a statistical difference in the duration of treatment (p < 0.001) and the incidence of dizziness or vertigo (p < 0.001) for patients among these groups. The degree of deafness in the patients in the inner ear hemorrhage group was significantly more severe than that of the patients in the other three groups (p < 0.001). 3D-FLAIR MRI appearances were correlated with the prognosis of patients with ISSNHL.

HLA-DQA1*04:01 is related to a higher multiple sclerosis lesion load on T2/Flair MRI sequences.

The genetic predisposition to multiple sclerosis (MS) is associated with HLA alleles, especially HLA-DRB1*15:01. To identify associations between findings in magnetic resonance imaging (MRI) and genetic features in a Brazilian cohort of patients with MS. We retrospectively studied data from 95 consecutive patients with MS. Two independent observers who were blinded to the clinical data identified black holes and enhanced lesions on T1 MRI sequences, and counted and measured contrast-enhanced lesions on T2 and Flair (fluid attenuation inversion recovery) sequences. Cases were classified according to lesion size, number, and volume. The HLA-DRB1, HLA-DQB1, and HLA-DQA1 alleles, and the rs4774, rs3087456, rs6897932, rs731236, and rs1033182 single nucleotide polymorphisms were identified by polymerase chain reaction amplification with sequence-specific primers using the One Lambda Inc. Kit, Canoga Park, CA, USA. Patients with the HLA-DQA1*04:01 allele had lesion load (adjusted for age, sex, and MS duration) above median compared with patients with other HLA-DQA1 alleles (p=0.02). There were no differences among all the other HLA alleles and single nucleotide polymorphisms and lesion load. The correlation of the HLA-DQA1*04:01 allele with a higher lesion load on T2/Flair MRI sequences suggests that the presence of this allele is associated with the risk of greater MS severity.

Effects of blood pressure on white matter lesions and brain volumes in hypertensive and normotensive subjects.

There is a direct relationship between cardiovascular dysfunction and risk factors and the development of the diseased brain. Such an affiliation has been made clear by decades of comprehensive studies associating poor cardiovascular health with adverse neurological events such as stroke, brain atrophy, and dementia. Hypertension and its subsequent pathological hallmarks can ultimately lead to cognitive dysfunction such as Alzheimer's disease. Although benefits of hypertension (HTN) treatment are indisputable, the target blood pressure value remains under debate. Our group performed a cross-sectional (n = 376) and longitudinal (n = 188) study of subjects that were approximately 60% women (age 68.5 ± 7/4 years, mean age 70.7±6.9 years) without any clinically demonstrable signs of dementia or stroke. Subjects were split into hypertensive (n = 169) and normotensive (n = 207) cohorts. MR images were obtained on a 3T system using fluid attenuation inversion recovery (FLAIR) and arterial spinal labeling (ASL) sequences. Linear modeling was performed in hypertensive and normotensive cohorts to investigate the relationship between blood pressure, white matter lesion (WML) development and hippocampal brain volume changes. Subjects in the hypertensive cohort showed a quadratic relationship between systolic blood pressure and WML, with the lowest amounts of WML being measured in subjects with readings at approximately 124 mmHg. Additionally, the hypertensive cohort also exhibited a quadratic relationship between diastolic blood pressure and hippocampal brain volume; subjects with readings at approximately 79 mmHg showing the largest volumes. Longitudinally, among hypertensive individuals both baseline SBP (β= 0.34, p=0.01) and DBP (β= -0.29, p=0.03) were related to WML changes over time (entire model F2,82 =3.9, p=0.024). While it is evident that higher blood pressure ultimately results in increased neuropathology across all subjects, it appears that in the hypertensive group there is a valley of mid-range blood pressures displaying less pathology in the brain.

Infantile Ascending Hereditary Spastic Paralysis with Extrapyramidal and Extraocular Manifestations Associated with a Novel ALS2 Mutation.

Infantile Ascending Hereditary Spastic Paralysis with Extrapyramidal and Extraocular Manifestations Associated with a Novel ALS2 Mutation.

Study on the Correlation Between Ischemic Leukoaraiosis and Cerebral Large Artery Stenosis Using the Stages of the Preinfarction Period Based on the Result of Computed Tomography Perfusion.

The influence of cerebral large artery stenosis (CLAS) on ischemic leukoaraiosis (LA) remains elusive. Based on the proposed stages of the preinfarction period, this study aimed to adopt the staging system to assess the correlation between ischemic LA and CLAS. Patients with unilateral CLAS ≥50% and without cerebral stroke were screened. The severity and distribution of stenosis were evaluated on computed tomography angiography images. The degree of regional cerebral perfusion was rated according to the stages of preinfarction period: 0=normal, 1=stage Ia, 2=stage Ib, 3=stage IIa, 4=stage IIb. Stage I included stage Ia and stage Ib. Stage II included stage IIa and stage IIb. LA was scored with Fazakas scale on T2-weighted image and/or fluid-attenuated inversion recovery sequences. The cohort consisted of 212 patients (mean age, 66.89±11.39 y), including 145 (68.40%) males. CLAS severity and distribution did not differ between patients with and without LA (P>0.05). Normal, stage I, and stage II had significantly different incidences of LA and hemispheric LA scores in the left and right hemispheres (P<0.05). The degree of regional cerebral perfusion was independently associated with LA in the left (P=0.0094) and right hemispheres (P=0.0091). Ischemic LA is not directly related to CLAS but is independently associated with the degree of CLAS-induced cerebral hypoperfusion. The stages of the preinfarction period are helpful in identifying people at high risk of LA progression.

Estimating nocturnal stroke onset times by magnetic resonance imaging in the WAKE-UP trial

Background Fluid-attenuated inversion recovery (FLAIR) sequences have gained a role to guide treatment of patients with unknown time of stroke symptom onset. Evolution of signal intensities in FLAIR is associated with time since stroke onset with continuous linear increases. Aims Estimating symptom onset during night-sleep in patients from the WAKE-UP trial based on relative signal intensities FLAIR (FLAIR-rSI) from acute stroke lesions an independent dataset (PRE-FLAIR study). Methods FLAIR-rSI was quantified in stroke lesions in PRE-FLAIR and WAKE-UP. The PRE-FLAIR study was a multicenter observational trial establishing FLAIR as a surrogate parameter for time since stroke onset. WAKE-UP was a randomized controlled trial that revealed a benefit for alteplase in patients selected based on a DWI-FLAIR mismatch. Stroke onset times were recorded in PRE-FLAIR and used to fit a linear regression model with FLAIR-rSI, adjusted for patient age and lesion volume. The model was applied to FLAIR-rSI of stroke lesions to estimate onset times in those patients enrolled in WAKE-UP who had symptom onset during night-sleep. Results FLAIR-rSI was quantified in 399 patients from PRE-FLAIR. Linear regression indicated a significant association of age ( p = 0.001), lesion volume ( p = 0.005) and FLAIR-rSI ( p &lt; 0.001) with time since symptom onset (adjusted R2 = 0.179). In 813 patients from WAKE-UP, distribution of times of last seen well, symptom recognition and MRI examination were recorded. Median times of last seen well were 1 h before midnight (IQR 2.4 h) and symptom recognition 7 h after midnight (IRQ 2.2 h). Based on the FLAIR-rSI profiles, we estimated median stroke onset 6.1 h after midnight (IQR 2.7 h). Conclusion Nocturnal strokes during night-sleep may predominantly occur during the early morning hours. Our results are in line with evidence of characteristic diurnal patterns of cardiovascular events.

Acute posterior reversible encephalopathy syndrome (PRES) in setting of interferon-beta use: case presentation with reduction of edema in 72\u2009h after cessation of interferon-beta therapy with sub-clinical inflammation

BackgroundPosterior reversible encephalopathy syndrome (PRES) represents a transient change in mental status with associated vasogenic edema of cortical and subcortical brain structures. It is often attributed to multifactorial etiology including hypertension and altered hemodynamics and disruption of vessel integrity. Patients with autoimmune disease and certain immune modulator therapies are at greater risk.Case presentationA 54-year-old female with past medical history of well-controlled multiple sclerosis on interferon-beta since 2013, presented with witnessed tonic colonic seizure. She also was noted to demonstrate left gaze deviation and left-sided hemiparesis. MRI fluid-attenuated inversion recovery sequence showed hyperintensity of the subcortical U fibers, concentrated in the occipital, parietal lobes and frontal lobes. Systolic blood pressure was 160 mmHg on arrival. The patient was started on seizure prophylxis and Interferon beta was discontinued. The patient’s mentation, seizures and hemiapresis significantly improved in next 72 h with tight blood pressure control, and had notble improvement on MRI imaging and inflammatory markers. Lumbar puncture CSF results were devoid of infectious and autoimmune pathology.ConclusionsA middle-aged female with multiple sclerosis who was on chronic IFN-beta presented to the emergency room with a witnessed tonic-clonic seizure, with MRI T2 FLAIR imaging consistent with PRES. She had notable clinical improvement with decreased edema on imaging and improved inflammatory markers 72 h after cessation of IFN-beta therapy.

A Semi-Supervised Learning Framework to Leverage Proxy Information for Stroke MRI Analysis.

Treating acute ischemic stroke (AIS) patients is a time-sensitive endeavor, as therapies target areas experiencing ischemia to prevent irreversible damage to brain tissue. Depending on how an AIS is progressing, thrombolytics such as tissue-plasminogen activator (tPA) may be administered within a short therapeutic window. The underlying conditions for optimal treatment are varied. While previous clinical guidelines only permitted tPA to be administered to patients with a known onset within 4.5 hours, clinical trials demonstrated that patients with signal intensity differences between diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) sequences in an MRI study can benefit from thrombolytic therapy. This intensity difference, known as DWI-FLAIR mismatch, is prone to high inter-reader variability. Thus, a paradigm exists where onset time serves as a weak proxy for DWI-FLAIR mismatch. In this study, we sought to detect DWI-FLAIR mismatch in an automated fashion, and we compared this to assessments done by three expert neuroradiologists. Our approach involved training a deep learning model on MRI to classify tissue clock and leveraging time clock as a weak proxy label to supplement training in a semi-supervised learning (SSL) framework. We evaluate our deep learning model by testing it on an unseen dataset from an external institution. In total, our proposed framework was able to improve detection of DWI-FLAIR mismatch, achieving a top ROC-AUC of 74.30%. Our study illustrated that incorporating clinical proxy information into SSL can improve model optimization by increasing the fidelity of unlabeled samples included in the training process.

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study

Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology. In this multicentre, retrospective cohort study, we used MRI examinations to train and validate a dCNN for synthesising post-contrast T1-weighted sequences from pre-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery sequences. We used MRI scans with availability of these sequences from 775 patients with glioblastoma treated at Heidelberg University Hospital, Heidelberg, Germany (775 MRI examinations); 260 patients who participated in the phase 2 CORE trial (1083 MRI examinations, 59 institutions); and 505 patients who participated in the phase 3 CENTRIC trial (3147 MRI examinations, 149 institutions). Separate training runs to rank the importance of individual sequences and (for a subset) diffusion-weighted imaging were conducted. Independent testing was performed on MRI data from the phase 2 and phase 3 EORTC-26101 trial (521 patients, 1924 MRI examinations, 32 institutions). The similarity between synthetic and true contrast enhancement on post-contrast T1-weighted MRI was quantified using the structural similarity index measure (SSIM). Automated tumour segmentation and volumetric tumour response assessment based on synthetic versus true post-contrast T1-weighted sequences was performed in the EORTC-26101 trial and agreement was assessed with Kaplan-Meier plots. The median SSIM score for predicting contrast enhancement on synthetic post-contrast T1-weighted sequences in the EORTC-26101 test set was 0·818 (95% CI 0·817-0·820). Segmentation of the contrast-enhancing tumour from synthetic post-contrast T1-weighted sequences yielded a median tumour volume of 6·31 cm3 (5·60 to 7·14), thereby underestimating the true tumour volume by a median of -0·48 cm3 (-0·37 to -0·76) with the concordance correlation coefficient suggesting a strong linear association between tumour volumes derived from synthetic versus true post-contrast T1-weighted sequences (0·782, 0·751-0·807, p<0·0001). Volumetric tumour response assessment in the EORTC-26101 trial showed a median time to progression of 4·2 months (95% CI 4·1-5·2) with synthetic post-contrast T1-weighted and 4·3 months (4·1-5·5) with true post-contrast T1-weighted sequences (p=0·33). The strength of the association between the time to progression as a surrogate endpoint for predicting the patients' overall survival in the EORTC-26101 cohort was similar when derived from synthetic post-contrast T1-weighted sequences (hazard ratio of 1·749, 95% CI 1·282-2·387, p=0·0004) and model C-index (0·667, 0·622-0·708) versus true post-contrast T1-weighted MRI (1·799, 95% CI 1·314-2·464, p=0·0003) and model C-index (0·673, 95% CI 0·626-0·711). Generating synthetic post-contrast T1-weighted MRI from pre-contrast MRI using dCNN is feasible and quantification of the contrast-enhancing tumour burden from synthetic post-contrast T1-weighted MRI allows assessment of the patient's response to treatment with no significant difference by comparison with true post-contrast T1-weighted sequences with administration of GBCAs. This finding could guide the application of dCNN in radiology to potentially reduce the necessity of GBCA administration. Deutsche Forschungsgemeinschaft.

The central vein sign in multiple sclerosis lesions: Susceptibility relaxation optimization from a routine MRI multiecho gradient echo sequence.

The white matter lesion central vein sign (CVS) is an emerging biomarker for multiple sclerosis (MS) differential diagnosis. Currently, CVS is detected on susceptibility weighted imaging (SWI) with suboptimal contrast. We developed an imaging method called susceptibility relaxation optimization (SRO) to improve CVS visualization. This was a retrospective study of MS patients who had MRI in June 2018 with routine 3D multiecho gradient echo (GRE) and T2-weighted fluid-attenuated inversion recovery (FLAIR) sequences. SRO and SWI images were reconstructed from GRE data. MS lesions were identified on FLAIR image. The CVS detection rate, the image quality score of CVS conspicuity (range 0-3), and central vein-to-lesion contrast were compared between SRO and SWI images. In 20 MS patients (mean age 45 ± 9 years; 15 women), SRO significantly increased CVS detection rate compared to SWI (53.3%, 274/514 vs. 32.9%, 169/514; p<.001, McNemar's test). The median image quality score for SRO was 2 compared to 1 for SWI (p<.001, Wilcoxon signed-rank test). The median overall image quality score for SRO was 7 compared to 6 for SWI (p = .003; Wilcoxon signed-rank test). Central vein-to-lesion contrast was 0.12 ± 0.12 in SRO compared to 0.031 ± 0.075 in SWI (p<.001, t-test). SRO yields better central vein contrast and increases CVS detection rate compared to SWI.

White-Matter Hyperintensity Load and Differences in Resting-State Network Connectivity Based on Mild Cognitive Impairment Subtype.

“Mild cognitive impairment” (MCI) is a diagnosis characterised by deficits in episodic memory (aMCI) or in other non-memory domains (naMCI). Although the definition of subtypes is helpful in clinical classification, it provides little insight on the variability of neurofunctional mechanisms (i.e., resting-state brain networks) at the basis of symptoms. In particular, it is unknown whether the presence of a high load of white-matter hyperintensities (WMHs) has a comparable effect on these functional networks in aMCI and naMCI patients. This question was addressed in a cohort of 123 MCI patients who had completed an MRI protocol inclusive of T1-weighted, fluid-attenuated inversion recovery (FLAIR) and resting-state fMRI sequences. T1-weighted and FLAIR images were processed with the Lesion Segmentation Toolbox to quantify whole-brain WMH volumes. The CONN toolbox was used to preprocess all fMRI images and to run an independent component analysis for the identification of four large-scale haemodynamic networks of cognitive relevance (i.e., default-mode, salience, left frontoparietal, and right frontoparietal networks) and one control network (i.e., visual network). Patients were classified based on MCI subtype (i.e., aMCI vs. naMCI) and WMH burden (i.e., low vs. high). Maps of large-scale networks were then modelled as a function of the MCI subtype-by-WMH burden interaction. Beyond the main effects of MCI subtype and WMH burden, a significant interaction was found in the salience and left frontoparietal networks. Having a low WMH burden was significantly more associated with stronger salience-network connectivity in aMCI (than in naMCI) in the right insula, and with stronger left frontoparietal-network connectivity in the right frontoinsular cortex. Vice versa, having a low WMH burden was significantly more associated with left-frontoparietal network connectivity in naMCI (than in aMCI) in the left mediotemporal lobe. The association between WMH burden and strength of connectivity of resting-state functional networks differs between aMCI and naMCI patients. Although exploratory in nature, these findings indicate that clinical profiles reflect mechanistic interactions that may play a central role in the definition of diagnostic and prognostic statuses.

FLAIR vascular hyperintensity, an early sign of stroke (case report)

BackgroundGenerally, Diffusion-weighted MR imaging (DWI) is known to be more sensitive in diagnosis of acute stroke than other MR sequences. However, fluid attenuated inversion recovery (FLAIR) MR sequence founded to be sometimes more sensitive compared to DWI for the diagnosis of hyperacute stroke.Case presentationAn 84 years old female patient brought to ER by ambulance due to loss of speech, dizziness and confusion. Neurological examination showed that the patient can raise her left hand and leg while partially moving her right hand and right leg. The patient had slurred speech. Provisional diagnosis was acute stroke and the patient admitted in the hospital. Non contrast CT scan of the brain was done, was negative for stroke. Then MRI was done showed no areas of restricted diffusion at the DWI sequence or ADC map. Prominent high signal vessels at the left temporal region and on Sylvian fissure were noticed on FLAIR sequence that might have suggested early sign of ischemic vascular insult.ConclusionsArterial hyperintensity on FLAIR images can precede diffusion abnormalities and may provide a clue to the early detection of impending infarction.

Three - dimensional fluid attenuated inversion recovery sequence on 3 tesla magnetic resonace imaging in cranial nerve pathologies: Two case reports

Three - dimensional fluid attenuated inversion recovery sequence (3D-FLAIR) was introduced as a practical sequence which helps to reduce the cerebrospinal fluid pulsation and flow artefacts of conventional 2D acquisition and brings contiguous slices, ability in reformatting in variable planes which are typical features of 3D acquisition. 3D - FLAIR has been applied on assessing several neurologic pathologies. In this article, we introduce the application of 3D - FLAIR sequence without contrast enhancement on detecting abnormalities of cranial nerve pathology by presenting two cases, acute vestibular neuritis and facial nerve palsy. We suggest that 3D - FLAIR is the relatively useful sequence in detecting cranial nerve pathologies.

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.

Comparison of Phase-Sensitive Inversion Recovery and Conventional Magnetic Resonance Imaging for Detection of Cortical Plaques in MS Patients

Background: Precise detection and classification of intracortical (IC) lesions in multiple sclerosis (MS) patients are very important for understanding their role in disease progression and determining their effects on the clinical presentations of the disease. Objectives: This study aimed to evaluate the efficacy of phase-sensitive inversion recovery (PSIR) in delineation of cortical lesions in MS patients. Patients and Methods: This cross-sectional, single-center study was performed among 38 patients with the mean age of 31 years, who were recruited from December 2018 to August 2020. All MS patients underwent magnetic resonance imaging (MRI), using a 1.5-Tesla scanner. Two expert neuroradiologists interpreted the fluid-attenuated inversion recovery (FLAIR), T2-weighted turbo spin echo (T2W-TSE), and PSIR images. The lesions were classified as purely IC, mixed gray/white matter (WM) [leukocortical (LC)], and juxtacortical (JC). The number of lesions in each region was compared between the FLAIR, T2W-TSE, and PSIR sequences. Results: The number of cortical lesions (IC and LC) was significantly higher in PSIR compared to T2W-TSE and Fluid attenuated inversion recovery (FLAIR) (P &lt; 0.001), while the number of JC lesions was lower; in other words, the mean number of plaques was higher in T2W-TSE and FLAIR as compared to PSIR. Conclusion: The PSIR sequence significantly improved the delineation of cortical lesions and could be useful in monitoring cortical injuries and disease progression in MS patients.

Magnetic resonance imaging findings in focal-onset status epilepticus.

Magnetic resonance imaging (MRI) is commonly used in the diagnostic work-up for status epilepticus (SE). The purpose of this study was to characterize MRI features in SE patients and determine their association with clinical and electroencephalography (EEG) findings. The mid-term consequences of baseline MRI features were also analysed. This is a prospective study including consecutive patients with SE who underwent brain MRI within 240h after SE onset. The MRI protocol included T1-weighted (T1WI), T2-weighted (T2W), fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI) sequences. Follow-up MRI was performed after SE resolution in some patients. Sixty patients (56.7% men, mean age 58.3years) were included. SE-related MRI abnormalities were seen in 31 (51.7%), manifesting as hyperintensities on T2W/FLAIR imaging (58.1%) and DWI (74.2%) sequences. Hippocampal and pulvinar involvement was seen in 58.0% and 25.8% of patients, respectively. MRI abnormalities were associated with a longer SE duration (p=0.013) and the presence of lateralized periodic discharges (LPDs) on EEG (p<0.001). Amongst the 33 follow-up MRIs, nine (27.3%) showed mesial temporal sclerosis (MTS), which was associated with severe clinical status (p=0.031), hippocampal oedema (p=0.001) and LPDs (p=0.001) at baseline. A poorer clinical outcome was associated with baseline T2W/FLAIR imaging hyperintensities (p=0.003). MRI showed abnormalities in more than half of SE patients. A longer SE duration and LPDs on EEG were associated with SE-related MRI abnormalities and the development of MTS.