3D-FLAIR Sequences Research Articles

Integrating standard epilepsy protocol, ASL-perfusion, MP2RAGE/EDGE and the MELD-FCD classifier in the detection of subtle epileptogenic lesions: a 3 Tesla MRI pilot study.

Malformations of cortical development (MCDs) in children with focal epilepsy pose significant diagnostic challenges, and a precise radiological diagnosis is crucial for surgical planning. New MRI sequences and the use of artificial intelligence (AI) algorithms are considered very promising in this regard, yet studies evaluating the relative contribution of each diagnostic technique are lacking. The study was conducted using a dedicated "EPI-MCD MR protocol" with a 3 Tesla MRI scanner in patients with focal epilepsy and previously negative MRI. MRI sequences evaluated included 3D FLAIR, 3D T1 MPRAGE, T2 Turbo Spin Echo (TSE), 3D T1 MP2RAGE, and Arterial Spin Labelling (ASL). Two paediatric neuroradiologists scored each sequence for localisation and extension of the lesion. The MELD-FCD AI classifier's performance in identifying pathological findings was also assessed. We only included patients where a diagnosis of MCD was subsequently confirmed on histology and/or sEEG. The 3D FLAIR sequence showed the highest yield in detecting epileptogenic lesions, with 3D T1 MPRAGE, T2 TSE, and 3D T1 MP2RAGE sequences showing moderate to low yield. ASL was the least useful. The MELD-FCD classifier achieved a 69.2% true positive rate. In one case, MELD identified a subtle area of cortical dysplasia overlooked by the neuroradiologists, changing the management of the patient. The 3D FLAIR sequence is the most effective in the MRI-based diagnosis of subtle epileptogenic lesions, outperforming other sequences in localisation and extension. This pilot study emphasizes the importance of careful assessment of the value of additional sequences.

Radiomic detection of abnormal brain regions in tuberous sclerosis complex.

Radiomics refers to the extraction of quantitative information from medical images and is most commonly utilized in oncology to provide ancillary information for solid tumor diagnosis, prognosis, and treatment response. The traditional radiomic pipeline involves segmentation of volumes of interest with comparison to normal brain. In other neurologic disorders, such as epilepsy, lesion delineation may be difficult or impossible due to poor anatomic definition, small size, and multifocal or diffuse distribution. Tuberous sclerosis complex (TSC) is a rare genetic disease in which brain magnetic resonance imaging (MRI) demonstrates multifocal abnormalities with variable imaging and epileptogenic features. The purpose of this study was to develop a radiomic workflow for identification of abnormal brain regions in TSC, using a whole-brain atlas-based approach with generation of heatmaps based on signal deviation from normal controls. This was a retrospective pilot study utilizing high-resolution whole-brain 3D FLAIR MRI datasets from retrospective enrollment of tuberous sclerosis complex (TSC) patients and normal controls. Subjects underwent MRI including high-resolution 3D FLAIR sequences. Preprocessing included skull stripping, coregistration, and intensity normalization. Using the Brainnetome and Harvard-Oxford atlases, brain regions were parcellated into 318 discrete regions. Expert neuroradiologists spatially labeled all tubers in TSC patients using ITK-SNAP. The pyradiomics toolbox was used to extract 88 radiomic features based on IBSI guidelines, comparing tuber-affected and non-tuber-affected parenchyma in TSC patients, as well as normal brain tissue in control patients. For model training and validation, regions with tubers from 20 TSC patients and 30 normal control subjects were randomly divided into two training sets (80%) and two validation sets (20%). Additional model testing was performed on a separate group of 20 healthy controls. LASSO (least absolute shrinkage and selection operator) was used to perform variable selection and regularization to identify regions containing tubers. Relevant radiomic features selected by LASSO were combined to produce a radiomic score ω, defined as the sum of squared differences from average control group values. Region-specific ω scores were converted to heat maps and spatially coregistered with brain MRI to reflect overall radiomic deviation from normal. The proposed radiomic workflow allows for quantification of deviation from normal in 318 regions of the brain with the use of a summative radiomic score ω. This score can be used to generate spatially registered heatmaps to identify brain regions with radiomic abnormalities. The pilot study of TSC showed radiomic scores ω that were statistically different in regions containing tubers from regions without tubers/normal brain (p<0.0001). Our model exhibits an AUC of 0.81 (95% confidence interval: 0.78-0.84) on the testing set, and the best threshold obtained on the training set, when applied to the testing set, allows us to identify regions with tubers with a specificity of 0.91 and a sensitivity of 0.60. We describe a whole-brain atlas-based radiomic approach to identify abnormal brain regions in TSC patients. This approach may be helpful for identifying specific regions of interest based on relatively greater signal deviation, particularly in clinical scenarios with numerous or poorly defined anatomic lesions.

Compressed SENSitivity Encoding (SENSE): Qualitative and Quantitative Analysis.

This study aimed to qualitatively and quantitatively evaluate T1-TSE, T2-TSE and 3D FLAIR sequences obtained with and without Compressed-SENSE technique by assessing the contrast (C), the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR). A total of 142 MRI images were acquired: 69 with Compressed-SENSE and 73 without Compressed-SENSE. All the MRI images were contoured, spatially aligned and co-registered using 3D Slicer Software. Two radiologists manually drew 12 regions of interests on three different structures of CNS: white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). C values were significantly higher in Compressed-SENSE T1-TSE compared to No Compressed-SENSE T1-TSE for three different structures of the CNS. C values were also significantly lower for Compressed-SENSE 3D FLAIR and Compressed-SENSE T2-TSE compared to the corresponding No Compressed-SENSE scans. While CNR values did not significantly differ in GM-WM between Compressed-SENSE and No Compressed-SENSE for the 3D FLAIR and T1-TSE sequences, the differences in GM-CSF and WM-CSF were always statistically significant. Compressed-SENSE for 3D T2 FLAIR, T1w and T2w sequences enables faster MRI acquisition, reducing scan time and maintaining equivalent image quality. Compressed-SENSE is very useful in specific medical conditions where lower SAR levels are required without sacrificing the acquisition of helpful diagnostic sequences.

Four-hour-delayed 3D-FLAIR MRIs in patients with acute unilateral peripheral vestibulopathy.

Conventionally, MRI aids in differentiating acute unilateral peripheral vestibulopathy/vestibular neuritis (AUPV/VN) from mimickers. Meanwhile, the diagnostic utility of MRIs dedicated to the inner ear remains to be elucidated for diagnosing AUPV/VN. We prospectively recruited 53 patients with AUPV/VN (mean age ± SD = 60 ± 15 years, 29 men). Initial MRIs were performed with a standard protocol, and an additional axial 3D-fluid-attenuated inversion recovery (3D-FLAIR) sequence was obtained 4 h after intravenous injection of gadoterate meglumine. Abnormal enhancement was defined as a signal intensity that exceeded the mean + 2SD value on the healthy side. The findings of neurotologic evaluation and MRIs were compared. Overall, the inter-rater agreement for gadolinium enhancement was 0.886 (Cohen's kappa coefficient). Enhancement was observed in 26 patients (49%), most frequently in the vestibule (n = 20), followed by the anterior (n = 12), horizontal (HC, n = 8), posterior canal (n = 5), and superior (n = 3) and inferior (n = 1) vestibular nerves. In multivariable logistic regression analysis, the enhancement was associated with decreased HC gain in video head-impulse tests (p = 0.036), increased interaural difference in ocular vestibular-evoked myogenic potentials (p = 0.001), and a longer onset-to-MRI time span (p = 0.024). The sensitivity and specificity were 92.3% and 81.5%, respectively, with an area under the curve of 0.90 for predicting gadolinium enhancement. Robust gadolinium enhancement was observed on 4-hour-delayed 3D-FLAIR images in nearly half of the patients with AUPV/VN, with a good correlation with the results of neurotologic evaluation. The positivity may be determined by the extent of vestibular deficit, timing of imaging acquisition, and possibly by the underlying etiology causing AUPV/VN. MRIs may aid in delineating the involved structures in AUPV/VN.

Non-contrast magnetic resonance evaluation of active multiple sclerosis lesions: Emerging role of quantitative synthetic magnetic resonance imaging.

The current study aims to explore the utility of novel synthetic MRI-derived quantitative parameters including myelin-correlated volume (MyC) in identifying active MS lesions without injecting gadolinium contrast. 43 MS patients underwent institutional MS protocol including 3D FLAIR and post-contrast 3D T1VIBE sequence on a 1.5T MR Scanner in addition to synthetic MRI sequence. MS plaques were categorised into enhancing (C) and non-enhancing (N) lesions. They were also sub-categorised based on location into periventricular WM lesions (P), deep WM lesions (D), infratentorial lesions (I) and cortical-juxtacortical (C) lesions. ROIs were placed on Synthetic FLAIR images in MS lesions and quantitative parameters of R1, R2, PD and myelin-correlated volume (MyC) obtained. Sensitivity and specificity for various cut-off values to differentiate enhancing from non-enhancing multiple sclerosis lesions were calculated by performing ROC curve analysis and logistic regression analysis. Contrast enhancing lesions demonstrated significantly higher mean R1, R2 values and lower mean PD values in comparison to non-enhancing lesions (p < 0.05) but with limited specificity. Region-wise analysis revealed high AUC values for mean R1 and R2 at cortical-juxtacortical lesions (p < 0.001) followed by periventricular lesions (p < 0.003) for differentiating enhancing from non-enhancing lesions with no significant contribution from MyC and PD values. Synthetic MRI-derived quantitative parameters of mean R1, R2, MyC and PD hold value in differentiating contrast enhancing and non-enhancing MS lesions without administering gadolinium-based contrast agent. However, the current study did not achieve significant specificity for establishing the same.

An unenhanced 3D-FLAIR sequence using long repetition time and constant flip angle to image endolymphatic hydrops.

To evaluate a three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) sequence using a long repetition time (TR) and constant flip angle (CFA) in differentiating between perilymph and endolymph in a phantom study, and unenhanced endolymphatic hydrops (EH) imaging in a patient study. Three solutions in similar ion and protein concentrations with endolymph, perilymph, and cerebrospinal fluid were prepared for variable flip angle (VFA) 3D-FLAIR (TR 10,000 ms) and CFA (120°) 3D-FLAIR using different TR (10,000, 16,000, and 20,000 ms). Fifty-two patients with probable or definite Meniere's disease received unenhanced CFA (120°) 3D-FLAIR using a long TR (20,000 ms) and 4-h-delay enhanced CFA (120°) 3D-FLAIR (TR 16,000 ms). Image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of them were compared. Agreement in the evaluation of the EH degree between them was analyzed. In the phantom study, CNRs between perilymphatic and endolymphatic samples of VFA 3D-FLAIR (TR 10,000 ms) and CFA 3D-FLAIR (TR 10,000, 16,000, and 20,000 ms) were 6.66 ± 1.30, 17.90 ± 2.76, 23.87 ± 3.09, and 28.22 ± 3.15 (p < 0.001). In patient study, average score (3.65 ± 0.48 vs. 4.19 ± 0.40), SNR (34.56 ± 9.80 vs. 51.40 ± 11.27), and CNR (30.66 ± 10.55 vs. 45.08 ± 12.27) of unenhanced 3D-FLAIR were lower than enhanced 3D-FLAIR (p < 0.001). Evaluations of the two sequences showed excellent agreement in the cochlear and vestibule (Kappa value: 0.898 and 0.909). The CFA 3D-FLAIR sequence using a long TR could be used in unenhanced EH imaging with high accuracy. Unenhanced imaging of endolymphatic hydrops is valuable in the diagnosis and follow-up of patients, especially those who cannot receive contrast-enhanced MRI. Ion and protein concentration differences can be utilized in differentiating endolymph and perilymph on MRI. Endolymphatic and perilymphatic samples could be differentiated in vitro on this 3D-FLAIR sequence. This unenhanced 3D-FLAIR sequence is in excellent agreement with the enhanced constant flip angle 3D-FLAIR sequence.

MR imaging of endolymphatic hydrops in Ménière’s disease: feasibility at 1.5 T

BackgroundMénière’s disease is a chronic condition of the inner ear that causes vertigo, tinnitus and hearing loss. Its diagnosis relies on clinical criteria that are subjective and pure-tone audiometry results that are not specific. Its pathological substrate is endolymphatic hydrops. Its imaging was recently made possible by the late-enhanced 3D FLAIR sequence. This technique was primarily tested on 3 T. Our objective was to prove its feasibility using a 1.5 T magnet.MethodsWe conducted a prospective study including 30 patients who fulfilled the Bárány society criteria for Ménière’s disease. We performed the late-enhanced 3D FLAIR sequence on all patients. We used it to look for and grade endolymphatic hydrops in the utricle, the saccule and the cochlear canal using the Kahn method.ResultsWe found endolymphatic hydrops in all of the 30 patients who fulfilled the diagnostic criteria for Ménière’s disease. We had no false positives and only one false negative with a patient presenting with bilateral disease clinically but having endolymphatic hydrops only on one side. Thus, our correspondence rate between clinical and imaging findings was 97%.ConclusionsIt is possible to diagnose endolymphatic hydrops with the late-enhanced 3D FLAIR sequence using a 1.5 T MRI machine. Since Ménière’s disease diagnosis is sometimes tricky, imaging endolymphatic hydrops can aid in the diagnosis when the clinical picture is incomplete. It also helps guide invasive treatment plans. Feasibility at 1.5 T ensures broader access to the late-enhanced 3D FLAIR sequence. Beyond the scope of Ménière’s disease, this sequence offers the possibility to better understand pressure-related inner ear diseases.

Automatic lesion detection at Multiple Sclerosis patients – Comparison of 2D- and 3D-FLAIR-datasets

BackgroundMultiple Sclerosis (MS) is a common autoimmune inflammatory disease of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) allows a sensitive assessment of the CNS and is established for diagnostic, prognostic and (therapy-) monitoring purposes. Especially lesion counting in T2- or Fluid Attenuated Inversion Recovery (FLAIR)-weighted images plays a decisive role in clinical routine. Software-packages allowing an automatic evaluation of image data are increasingly established aiming a faster and improved workflow. These programs allow e.g. the counting, spatial attribution and volumetry of MS-lesions in FLAIR-weighted images. Research has shown that 3D-FLAIR-sequences are superior to 2D-FLAIR-sequences in visual evaluation of lesion burden in MS. An influence on the automatic analysis is expectable but not yet systematically studied. This work will therefore investigate the influence of 2D- and 3D datasets on the results of an automatic assessment. Material and methodsIn this prospective study, 80 Multiple Sclerosis patients underwent a clinically indicated routine MRI examination. The clinical routine protocol already including a 3D-FLAIR sequence was adapted by an additional 2D-FLAIR sequence also conform to the 2021 MAGNIMS-CMSCNAIMS consensus recommendations. To obtain a quantitative analysis for assessment of amount, dissemination and volume of the lesions, the acquired MR images were post-processed using the CE-certified Software mdbrain (mediaire, Berlin, Germany). The resulting data were statistically analysed using the paired t-test for normally distributed data and the Wilcoxon-signed-rank-test for not normally distributed data respectively. Demographic data and data such as the subtype, duration, severity and therapy of the disease were collected, pseudonymized and evaluated. ResultsThere is a significant difference concerning the total number and lesion volume with more lesions being detected (2D: 29.7, +/- 20.22 sd; 3D: 40.1 +/- 31.67 sd; p < 0.0001) but lower total volume (2D: 6.24 +/- 6.11 sd; 3D: 5.39 +/- 6.37 sd; p < 0.0001) when using the 3D- sequence. Especially significantly more small lesions in the unspecific white matter and infratentorial region were detected by using the 3D-FLAIR sequence (p < 0.0001) compared to the 2D-FLAIR image. Main reason for the lower total volume in the 3D-FLAIR sequence was the calculated volume for periventricular lesions which was significantly beneath the calculated volume from the 2D-FLAIR sequence (p < 0.0001). ConclusionAutomatic lesion counting and volumetry is feasible with both 2D- and 3D-weightend FLAIR images. Still, it leads to partly significant differences even between two sequences that both are conform to the 2021 MAGNIMS-CMSCNAIMS consensus recommendations. This study contributes valuable insights into the impact of using different input data from the same patient for automated MS lesion evaluation.

Development and prospective clinical validation of a convolutional neural network for automated detection and segmentation of focal cortical dysplasias

PurposeFocal cortical dysplasias (FCDs) are a leading cause of drug-resistant epilepsy. Early detection and resection of FCDs have favorable prognostic implications for postoperative seizure freedom. Despite advancements in imaging methods, FCD detection remains challenging. House et al. (2021) introduced a convolutional neural network (CNN) for automated FCD detection and segmentation, achieving a sensitivity of 77.8%. However, its clinical applicability was limited due to a low specificity of 5.5%. The objective of this study was to improve the CNN’s performance through data-driven training and algorithm optimization, followed by a prospective validation on daily-routine MRIs. Material and methodsA dataset of 300 3 T MRIs from daily clinical practice, including 3D T1 and FLAIR sequences, was prospectively compiled. The MRIs were visually evaluated by two neuroradiologists and underwent morphometric assessment by two epileptologists. The dataset included 30 FCD cases (11 female, mean age: 28.1 ± 10.1 years) and a control group of 150 normal cases (97 female, mean age: 32.8 ± 14.9 years), along with 120 non-FCD pathological cases (64 female, mean age: 38.4 ± 18.4 years). The dataset was divided into three subsets, each analyzed by the CNN. Subsequently, the CNN underwent a two-phase-training process, incorporating subset MRIs and expert-labeled FCD maps. This training employed both classical and continual learning techniques. The CNN’s performance was validated by comparing the baseline model with the trained models at two training levels. ResultsIn prospective validation, the best model trained using continual learning achieved a sensitivity of 90.0%, specificity of 70.0%, and accuracy of 72.0%, with an average of 0.41 false positive clusters detected per MRI. For FCD segmentation, an average Dice coefficient of 0.56 was attained. The model’s performance improved in each training phase while maintaining a high level of sensitivity. Continual learning outperformed classical learning in this regard. ConclusionsOur study presents a promising CNN for FCD detection and segmentation, exhibiting both high sensitivity and specificity. Furthermore, the model demonstrates continuous improvement with the inclusion of more clinical MRI data. We consider our CNN a valuable tool for automated, examiner-independent FCD detection in daily clinical practice, potentially addressing the underutilization of epilepsy surgery in drug-resistant focal epilepsy and thereby improving patient outcomes.

Compressed Sensitivity Encoding Artificial Intelligence Accelerates Brain Metastasis Imaging by Optimizing Image Quality and Reducing Scan Time.

Accelerating the image acquisition speed of MR imaging without compromising the image quality is challenging. This study aimed to evaluate the feasibility of contrast-enhanced (CE) 3D T1WI and CE 3D-FLAIR sequences reconstructed with compressed sensitivity encoding artificial intelligence (CS-AI) for detecting brain metastases (BM) and explore the optimal acceleration factor (AF) for clinical BM imaging. Fifty-one patients with cancer with suspected BM were included. Fifty participants underwent different customized CE 3D-T1WI or CE 3D-FLAIR sequence scans. Compressed SENSE encoding acceleration 6 (CS6), a commercially available standard sequence, was used as the reference standard. Quantitative and qualitative methods were used to evaluate image quality. The SNR and contrast-to-noise ratio (CNR) were calculated, and qualitative evaluations were independently conducted by 2 neuroradiologists. After exploring the optimal AF, sample images were obtained from 1 patient by using both optimized sequences. Quantitatively, the CNR of the CS-AI protocol for CE 3D-T1WI and CE 3D-FLAIR sequences was superior to that of the CS protocol under the same AF (P < .05). Compared with reference CS6, the CS-AI groups had higher CNR values (all P < .05), with the CS-AI10 scan having the highest value. The SNR of the CS-AI group was better than that of the reference for both CE 3D-T1WI and CE 3D-FLAIR sequences (all P < .05). Qualitatively, the CS-AI protocol produced higher image quality scores than did the CS protocol with the same AF (all P < .05). In contrast to the reference CS6, the CS-AI group showed good image quality scores until an AF of up to 10 (all P < .05). The CS-AI10 scan provided the optimal images, improving the delineation of normal gray-white matter boundaries and lesion areas (P < .05). Compared with the reference, CS-AI10 showed reductions in scan time of 39.25% and 39.93% for CE 3D-T1WI and CE 3D-FLAIR sequences, respectively. CE 3D-T1WI and CE 3D-FLAIR sequences reconstructed with CS-AI for the detection of BM may provide a more effective alternative reconstruction approach than CS. CS-AI10 is suitable for clinical applications, providing optimal image quality and a shortened scan time.

Clinical Analysis of 3D-Fluid Attenuated Inversion Recovery and T1volume interpolated body examination Sequences on Delayed Gadolinium-Enhanced Scanning in Ramsay Hunt Syndrome.

Through the clinical analysis of 4 clinically confirmed cases of delayed gadolinium enhancement of Ramsay Hunt syndrome 3D-Fluid Attenated Inversion Recovery'and 'T1volume interpolated body examination (3D-FLAIR and T1VIBE) sequences, the more suitable sequences and pathologically damaged tissue sites of deep tissues of Ramsay Hunt syndrome by magnetic resonance imaging gadolinium enhancement were preliminarily explored. From October 2020 to March 2021, 4 clinically confirmed patients with Ramsay Hunt syndrome, 2 males and 2 females, aged 27-63, were continuously collected in the hospital otology clinic. Siemens Avento 1.5T magnetic resonance imaging 3D-FLAIR and T1VIBE sequencedelayed gadolinium enhancement scans and serological laboratory tests were performed, respectively, and corresponding antiviral and antiinflammatory therapy was given. The magnetic resonance imaging gadolinium enhancement of 4 cases of Ramsay Hunt syndrome was as follows: 3D-FLAIR sequence delay of 4.5 hours scanning 4 patients labyrinthine and/or middle ear signal was enhanced at the same time as the healthy side; T1VIBE sequence scanning disease in 3 cases of vestibular nerve development was enhanced than the healthy side, 2 cases of facial nerve development was enhanced than the healthy side, and 2 cases of cochlear nerve development was enhanced than the healthy side. All 4 patients were cured with related treatment. Through the comparison of 3D-FAIR and T1VIBE sequence of 4.5 hours delay before intravenous gadolinium injection and 4.5 hours delay after intravenous gadolinium injection in 4 patients with Ramsay Hunt syndrome, it was found that (i) 3D-FLAIR sequence delay of 4.5 hours scan was more likely to show whether the inner ear labyrinth barrier permeability increased and (ii) Ramsay Hunt syndrome deep ear tissue damage can be manifested as labyrinthitis, vestibular cochlear neuritis, facial neuritis, and otitis media.

Iterative Denoising Accelerated 3D FLAIR Sequence for Hydrops MR Imaging at 3T.

3D FLAIR sequences have become the criterion standard for identifying endolymphatic hydrops, but scan time remains an important limitation to their widespread use. Our purpose was to evaluate the diagnostic performance and image quality of an accelerated 3D FLAIR sequence combined with an iterative denoising algorithm. This was a retrospective study performed on 30 patients with clinical suspicion of endolymphatic hydrops who underwent 3T MR imaging 4 hours after gadolinium injection using two 3D FLAIR sequences. The first (conventional FLAIR) was accelerated with a conventional turbo factor of 187. The second was accelerated with an increased turbo factor of 263, resulting in a 33% scan time reduction (5 minutes 36 seconds versus 8 minutes 15 seconds, respectively). A sequence was reconstructed in-line immediately after the accelerated 3D FLAIR acquisition from the same raw data with iterative denoising (accelerated-FLAIR iterative denoising). The signal intensity ratio image quality score and endolymphatic hydrops diagnosis were evaluated. The mean signal intensity ratio for symptomatic and asymptomatic ears of accelerated-FLAIR iterative denoising was significantly higher than the mean SNR of conventional FLAIR (29.5 versus 19 and 25.9 versus 16.3, P < .001). Compared with the conventional FLAIR sequence, the image-quality score was higher with accelerated-FLAIR iterative denoising (mean image-quality score, 3.8 [SD, 0.4] versus 3.3 [SD, 0.6] for accelerated-FLAIR iterative denoising and conventional FLAIR, respectively, P = .003). There was no significant difference in the diagnosis of endolymphatic hydrops between the 2 sequences. Interreader agreement was good-to-excellent. The iterative denoising algorithm applied to an accelerated 3D FLAIR sequence for exploration of endolymphatic hydrops enabled significantly reducing the scan time without compromising image quality and diagnostic performance.

A Fully Automatic Method to Segment Choroid Plexuses in Multiple Sclerosis Using Conventional MRI Sequences.

Choroid plexus (CP) volume has been recently proposed as a proxy for brain neuroinflammation in multiple sclerosis (MS). To develop and validate a fast automatic method to segment CP using routinely acquired brain T1-weighted and FLAIR MRI. Retrospective. Fifty-five MS patients (33 relapsing-remitting, 22 progressive; mean age = 46.8 ± 10.2 years; 31 women) and 60 healthy controls (HC; mean age = 36.1 ± 12.6 years, 33 women). 3D T2-weighted FLAIR and 3D T1-weighted gradient echo sequences at 3.0 T. Brain tissues were segmented on T1-weighted sequences and a Gaussian Mixture Model (GMM) was fitted to FLAIR image intensities obtained from the ventricle masks of the SIENAX. A second GMM was then applied on the thresholded and filtered ventricle mask. CP volumes were automatically determined and compared with those from manual segmentation by two raters (with 3 and 10 years' experience; reference standard). CP volumes from previously published automatic segmentation methods (freely available Freesurfer [FS] and FS-GMM) were also compared with reference standard. Expanded Disability Status Scale (EDSS) score was assessed within 3 days of MRI. Computational time was assessed for each automatic technique and manual segmentation. Comparisons of CP volumes with reference standard were evaluated with Bland Altman analysis. Dice similarity coefficients (DSC) were computed to assess automatic CP segmentations. Volume differences between MS and HC for each method were assessed with t-tests and correlations of CP volumes with EDSS were assessed with Pearson's correlation coefficients (R). A P value <0.05 was considered statistically significant. Compared to manual segmentation, the proposed method had the highest segmentation accuracy (mean DSC = 0.65 ± 0.06) compared to FS (mean DSC = 0.37 ± 0.08) and FS-GMM (0.58 ± 0.06). The percentage CP volume differences relative to manual segmentation were -0.1% ± 0.23, 4.6% ± 2.5, and -0.48% ± 2 for the proposed method, FS, and FS-GMM, respectively. The Pearson's correlations between automatically obtained CP volumes and the manually obtained volumes were 0.70, 0.54, and 0.56 for the proposed method, FS, and FS-GMM, respectively. A significant correlation between CP volume and EDSS was found for the proposed automatic pipeline (R = 0.2), for FS-GMM (R = 0.3) and for manual segmentation (R = 0.4). Computational time for the proposed method (32 ± 2 minutes) was similar to the manual segmentation (20 ± 5 minutes) but <25% of the FS (120 ± 15 minutes) and FS-GMM (125 ± 15 minutes) methods. This study developed an accurate and easily implementable method for automatic CP segmentation in MS using T1-weighted and FLAIR MRI. 1 TECHNICAL EFFICACY: Stage 4.

Tinnitus, Aural Fullness, and Hearing Loss in a Patient with Acoustic Neuroma and Pituitary Macroadenoma

We report the case of a 51-year-old woman with multiple otologic and vestibular symptoms. She presented with two different types of tinnitus in her right ear, vertigo, and fluctuating aural symptoms in the left ear. She also complained of disequilibrium; chronic headache; hyperhidrosis; amenorrhea; insomnia; broadened hands and feet; and widened, thickened, and stubby fingers. The patient underwent careful collection of medical history, otomiscroscopy, pure tone audiometry, tympanometry, reflex threshold measurements, vestibular assessments, blood tests, magnetic resonance imaging (MRI), and cone beam computed tomography (CBTC) of the head. The audiogram showed: (1) a mild low-to-mid frequency conductive hearing loss, and a sharply sloping sensorineural hearing loss above 4000 Hz in the right ear; (2) a mild low-frequency sensorineural hearing loss in the left ear. MRI with 3D FLAIR sequences detected an acoustic neuroma (7.4 mm × 5.2 mm) in the middle-third of the right internal auditory canal, a pituitary macroadenoma (13 mm × 10 mm × 10 mm) and left saccular hydrops. The CBCT scan documented an outbreak of otosclerosis (3 mm) around the fissula ante fenestram in the right ear. Therefore, acoustic neuroma (right ear), growth hormone-secreting macroadenoma of the pituitary gland, Menière’s disease (left ear), and otosclerosis (right ear) were diagnosed/strongly suspected. A watch-and-wait strategy was adopted for acoustic neuroma and otosclerosis, while transsphenoidal surgery was successfully performed to remove the pituitary macroadenoma. This case report confirms that multiple otologic disorders can occur simultaneously in the same patient, requiring prompt audiological and imaging evaluations.

Comparison between audio-vestibular findings and contrast-enhanced MRI of inner ear in patients with unilateral Ménière's disease.

The diagnosis of Ménière's disease (MD), characterized by idiopathic endolymphatic hydrops (ELH), remains a clinical priority. Many ancillary methods, including the auditory and vestibular assessments, have been developed to identify ELH. The newly emerging delayed magnetic resonance imaging (MRI) of the inner ear after intratympanic gadolinium (Gd) has been used for identifying ELH in vivo. We aimed to investigate the concordance of audio-vestibular and radiological findings in patients with unilateral MD. In this retrospective study, 70 patients with unilateral definite MD underwent three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) sequences following intratympanic application of Gd. Audio-vestibular evaluations were performed, including pure tone audiometry, electrocochleogram (ECochG), glycerol test, caloric test, cervical and ocular vestibular evoked myogenic potentials (VEMPs), and video head impulse test (vHIT). The relationship between imaging signs of ELH and audio-vestibular results was investigated. The incidence of radiological ELH was higher than that of neurotological results, including the glycerol test, caloric test, VEMPs, and vHIT. Poor or slight agreement was observed between audio-vestibular findings and radiological ELH in cochlear and/or vestibular (kappa values <0.4). However, the pure tone average (PTA) in the affected side significantly correlated with the extent of both cochlear (r = 0.26795, p = 0.0249) and vestibular (r = 0.2728, p = 0.0223) hydrops. Furthermore, the degree of vestibular hydrops was also positively correlated with course duration (r = 0.2592, p = 0.0303) and glycerol test results (r = 0.3944, p = 0.0061) in the affected side. In the diagnosis of MD, contrast-enhanced MRI of the inner ear is advantageous in detecting ELH over the conventional audio-vestibular evaluations, which estimates more than hydropic dilation of endolymphatic space.

Usefulness of a Rim-Enhancing Pattern on the Contrast-Enhanced 3D-FLAIR Sequence and MRI Characteristics for Distinguishing Meningioma and Malignant Dural-Based Tumor.

Meningiomas are the most common type of extra-axial dural-based tumors; however, malignant dural-based tumors can mimic meningiomas on imaging. The aim of this study was to determine the efficacy of differentiating meningiomas from malignant dural-based tumors by using rim-enhancement patterns on a contrast-enhanced FLAIR sequence and MR imaging characteristics. This retrospective study included 102 patients with meningiomas and 31 patients with malignant dural-based tumors who underwent pretreatment MR imaging. The rim-enhancement patterns on contrast-enhanced FLAIR and MR imaging characteristics, including the dural tail sign, hyperostosis, bony destruction, leptomeningeal enhancement, peritumoral edema, T2-weighted signal intensity, and tumor enhancement were evaluated. Complete rim enhancement of the tumor-brain interface on contrast-enhanced FLAIR (contrast-enhanced-FLAIR rim sign) was present in most meningiomas (91/102, 89.2%) and at significantly greater frequency than in malignant dural-based tumors (2/31, 6.5%) (P < .001). Complete contrast-enhanced FLAIR rim enhancement provided high sensitivity (89.2%), specificity (93.5%), and accuracy (90.2%) for diagnosing meningioma. Additionally, hyperostosis was an MR imaging characteristic that suggested a diagnosis of meningioma. In contrast, bony destruction with cortical breakthrough and leptomeningeal enhancement suggested malignant dural-based tumors. There were limitations of meningiomas of <2.0 cm or at cavernous sinus locations that did not demonstrate contrast-enhanced FLAIR rim enhancement. The rim-enhancement pattern on contrast-enhanced FLAIR could help differentiate meningiomas and malignant dural-based tumors. The presence of complete rim enhancement on contrast-enhanced FLAIR was a robust predictive sign for meningioma.

Роль МРТ в диагностике болезни Меньера

The article deals with the methods of visualization of the structures of the inner ear. An analysis of studies aimed at determining the possibilities of using MRI in the diagnosis of Meniere’s disease was carried out. We examined 13 patients with significant Meniere’s disease. The patients were intravenously injected with a gadolinium-based contrast agent. After 4 hours, an MRI of the brain was performed on a Philips Ingenia magnetic resonance imaging scanner with a magnetic field strength of 1.5 Tesla using the 3D-FLAIR sequence. The diagnosis of Meniere’s disease was confirmed in 11 patients.

Intravascular Large B-Cell Lymphoma (IVLBCL) Presenting with CNS Involvement in Patient with Chronic Lymphocytic Leukemia

Background: Intravascular lymphoma (IVL) is a rare, often fatal disease characterized by intraluminal proliferation of lymphoid cells within blood vessels. Intravascular Large B-Cell Lymphoma (IVLBCL) is frequently found in different organs, but the skin and central nervous system (CNS) are the most affected ones. Routine radiological examination and additional diagnostic tools, such as high-resolution, three-dimensional (3D) FLAIR sequence, T2-weighted (T2W) and T1-weighted (T1W) contrast-enhanced magnetic resonance imaging (MRI), MRI diffusion and perfusion imaging studies are useful to confirm the diagnosis in cases where it is not easy to perform histopathological examinations [1]. 1.2. Case Report: We present a clinical case of a 63-year-old female patient who presented with progressive cognitive deficit as mild motor aphasia, acalculia, agraphia, dyslexia and mild ideomotor apraxia without any signs of other organ involvement. It was known that the patient had 5-year anamnesis of chronic lymphocytic leukemia, stage II and splanchnic venous thrombosis 2 months ago. Blood biochemical analysis without any significant change, except leukocytosis in full blood count (leukocytes 15,2 x 10*9/L, where neutrophils were in normal range, but lymphocytes were increased). Head magnetic resonance imaging (MRI) showed pathological signal areas on the left parietal lobe with hypointense signal on contrast-enhanced T1-weighted, hyperintense signal on contrast-enhanced T2-weighted and FLAIR-weighted MRI images with restricted diffusion and slightly lower ADC value. Magnetic resonance perfusion imaging studies did not show an increase in cerebral blood flow or in cerebral blood volume. In this case, the patient’s diagnosis was made based on typical radiological features. 1.3. Conclusions: Intravascular large B-cell lymphoma is a rare subtype of extra nodal large B-cell lymphoma with an aggressive clinical course. The diagnosis is challenging, as it presents without any obvious tumour mass or lymphadenopathy. [2] As the clinical presentation is variable without specific characteristics, mostly biopsy or even autopsy confirms the definite diagnosis. But in some cases, the diagnosis can be made by typical radiological findings in the restricted availability of brain biopsy.

Reliability of Endolymphatic Hydrops Qualitative Assessment in Magnetic Resonance Imaging

The study aimed to compare the consistency of MRI interpretation of endolymphatic hydrops qualitative assessment of inner ear structures performed by independent observers. MRI with a delayed post-contrast 3D-FLAIR sequence was performed to visualize EH in patients suspected of having or diagnosed with MD. The scans were analyzed independently by three observers. In total, 220 ears were evaluated and, of these, 75 had definite MD, five probable MD, 67 with other Menieriform symptoms, and 73 were asymptomatic. Significant differences in cochlear endolymphatic hydrops (CoEH) grading between all observers were observed. On the Barath scale of vestibular endolymphatic hydrops (VEH), differences were found between the radiologists and otorhinolaryngologist in grading. No differences were noted in VEH on the Bernaerts scale and increased perilymphatic enhancement. Our study showed that evaluation of vestibular endolymphatic hydrops is repeatable between observers and easy to learn. It proved that Bernaerts' modification increased the sensitivity of EH diagnosis. Both parameters, CoEH and VEH, may serve as a differentiation method of EH from normal ears. The distinction between normal and hydropic ears is much easier to perform than EH grading. Therefore, it may be used to diagnose MD rather than EH staging.

Comparison of an optimized 3D-real IR and a 3D-FLAIR with a constant flip angle in the evaluation of endolymphatic hydrops

PurposeTo evaluate an optimized 3D-real IR sequence with a longer TR (16,000 ms) based on the modulated flip angle technique in refocused imaging with extended echo train (MATRIX) for the endolymphatic hydrops (EH) after intravenous (IV) single-dose gadolinium (Gd) administration, and compare it with a heavily T2-weighted 3D-FLAIR sequence with a constant flip angle. MethodThe 3D-FLAIR and 3D-real IR sequences were performed in forty patients with definite Meniere’s disease (MD) four hours after IV Gd administration. Image qualities of the two sequences were rated and compared. Contrast-to-noise ratios (CNRs) and signal-to-noise ratios (SNRs) of the two sequences were measured for quantitative comparison. EH was graded on the images of the two sequences by two radiologists. ResultsScores and CNRs of the 3D-real IR were significantly higher than those of the 3D-FLAIR (P < 0.05). SNRs of the two sequences were comparable between the two groups. 3D-real IR had a higher inter- and intra-observer reliability for the grading of cochlear and vestibular EH than 3D-FLAIR. Using 3D-real IR sequence, the detection rate of EH of the whole labyrinth was higher than using 3D-FLAIR (86.6 % vs 73.3 %, p = 0.031). In the patients with unilateral MD, SNRs in the affected sides were significantly higher than the unaffected sides (P < 0.05). ConclusionsThe optimized 3D-real IR with a longer TR is a robust sequence with an improved depiction of EH after IV administration of single-dose Gd. Compared with 3D-FLAIR, it may allow a more precise evaluation and grading of EH.