Comparison between gadolinium-enhanced 2D T1-weighted gradient-echo and spin-echo sequences in the detection of active multiple sclerosis lesions on 3.0T MRI.

OBJECTIVES: To compare the sensitivity of enhancing multiple sclerosis (MS) lesions in gadolinium-enhanced 2D T1-weighted gradient-echo (GRE) and spin-echo (SE) sequences, and to assess the influence of visual conspicuity and laterality on detection of these lesions. METHODS: One hundred MS patients underwent 3.0T brain MRI including gadolinium-enhanced 2D T1-weighted GRE and SE sequences. The two sets of contrast-enhanced scans were evaluated in random fashion by three experienced readers. Lesion conspicuity was assessed by the image contrast ratio (CR) and contrast-to-noise ratio (CNR). The intracranial region was divided into four quadrants and the impact of lesion location on detection was assessed in each slice. RESULTS: Six hundred and seven gadolinium-enhancing MS lesions were identified. GRE images were more sensitive for lesion detection (0.828) than SE images (0.767). Lesions showed a higher CR in SE than in GRE images, whereas the CNR was higher in GRE than SE. Most misclassifications occurred in the right posterior quadrant. CONCLUSIONS: The gadolinium-enhanced 2D T1-weighted GRE sequence at 3.0T MRI enables detection of enhancing MS lesions with higher sensitivity and better lesion conspicuity than 2D T1-weighted SE. Hence, we propose the use of gadolinium-enhanced GRE sequences rather than SE sequences for routine scanning of MS patients at 3.0T. KEY POINTS: • 2D SE and GRE sequences are useful for detecting active MS lesions. • Which of these sequences is more sensitive at high field remains uncertain. • GRE sequence showed better sensitivity for detecting active MS lesions than SE. • We propose GRE sequence for detecting active MS lesions at 3.0T.

Lesion filling effect in regional brain volume estimations: a study in multiple sclerosis patients with low lesion load.

INTRODUCTION: Regional brain volume estimation in multiple sclerosis (MS) patients is prone to error due to white matter lesions being erroneously segmented as grey matter. The Lesion Segmentation Toolbox (LST) is an automatic tool that estimates a lesion mask based on 3D T2-FLAIR images and then uses this mask to fill the structural MRI image. The goal of this study was (1) to test the LST for estimating white matter lesion volume in a cohort of MS patients using 2D T2-FLAIR images, and (2) to evaluate the performance of the optimized LST on image segmentation and the impact on the calculated grey matter fraction (GMF). METHODS: The study included 110 patients with a clinically isolated syndrome and 42 with a relapsing-remitting MS scanned on a 3.0-T MRI system. In a subset of consecutively selected patients, the lesion mask was semi-manually delineated over T2-FLAIR images. After establishing the optimized LST parameters, the corresponding regional fractions were calculated for the original, filled, and masked images. RESULTS: A high agreement (intraclass correlation coefficient (ICC) = 0.955) was found between the (optimized) LST and the semi-manual lesion volume estimations. The GMF was significantly smaller when lesions were masked (mean difference -0.603, p < 0.001) or when the LST filling technique was used (mean difference -0.598, p < 0.001), compared to the GMF obtained from the original image. CONCLUSION: LST lesion volume calculation seems reliable. GMFs are significantly reduced when a method to correct the contribution of MS lesions is used, and it may have an impact in assessing GMF differences between clinical cohorts.

Estimation of the density of veins from susceptibility-weighted imaging by using Mamdani fuzzy-type rule-based system. Investigating the neurovascular coupling in migraine.

BACKGROUND AND PURPOSE: An impaired neurovascular coupling has been described as a possible player in neurodegeneration and cognitive decline. Migraine is a recurrent and incapacitating disorder that starts early in life and has shown neurovascular coupling abnormalities. Despite its high prevalence, the physiology and underlying mechanisms are poorly understood. In this context, new biomarkers from magnetic resonance imaging (MRI) are needed to bring new knowledge into the field. The aim of this study was to determine the vein density from Susceptibility-Weighted Imaging (SWI) MRI, in subjects with migraine and healthy controls; and to assess whether it relates to Resting-State functional MRI (RS-fMRI). MATERIALS AND METHODS: The cohort included 30 healthy controls and 70 subjects with migraine (26 episodic, 44 chronic) who underwent a brain 3.0 T MRI. Clinical characteristics were also collected. Maps of density of veins were generated based on a Mamdani Fuzzy-Type Rule-Based System from the SWI MRI. Mean values of vein density were obtained in grey (GM) and white matter (WM) Freesurfer lobar parcellations. The Amplitude of Low-Frequency Fluctuations (ALFF) image was calculated for the RS-fMRI, and the mean values over the parcellated GM lobes were estimated. Differences between groups were assessed through and analysis of variance (age, sex, education and anxiety as covariates; p < 0.05), followed by post-hoc comparisons. Associations were run between clinical and MRI-derived variables. RESULTS: When comparing the density of veins in GM, no differences between groups were found, neither associations with clinical variables. The density of veins was significantly higher in the WM of the occipital lobe for subjects with chronic migraine compared to controls (30%, p < 0.05). WM vein density in either frontal, temporal or cingulate regions was associated with clinical variables such as headache days, disability scores, and cognitive impairment (r between 0.25 and 0.41; p < 0.05). Mean values of ALFF did not differ significantly between controls and subjects with migraine. Strong significant associations between vein density and ALFF measures were obtained in most GM lobes for healthy subjects (r between 0.50 and 0.67; p < 0.05), instead, vein density in WM was significantly associated with ALFF for subjects with migraine (r between 0.32 and 0.58; p < 0.05). CONCLUSIONS: Results point towards an increase in vein density in subjects with migraine, when compared to healthy controls. In addition, the association between GM vein density and ALFF found in healthy subjects was lost in migraine. Taken together, these results support the idea of abnormalities in the neurovascular coupling in migraine. Quantitative SWI MRI indicators in migraine might be an interesting target that may contribute to its comprehension.

A single-center, randomized, double-blind, placebo-controlled study of interferon beta-1b on primary progressive and transitional multiple sclerosis.

Inflammation and neurodegeneration may have differential impacts on disease evolution in the different forms of multiple sclerosis. However, a beneficial effect of immunomodulatory drugs should not be ruled out in primary progressive multiple sclerosis. Our aim is to investigate the safety and efficacy of interferon beta-1b in primary progressive multiple sclerosis. We conducted a double-blind, stratified, randomized, parallel group, phase II pilot study where patients with primary progressive multiple sclerosis or 'transitional' forms of multiple sclerosis received interferon beta-1b at doses of 8 MIU or placebo for 24 months. The main objective of the study was to investigate the safety and tolerability of interferon beta-1b. The primary efficacy variable was the time to neurological deterioration (Expanded Disability Status Scale) confirmed at 3 months. Seventy-three patients were included and three dropped out the study. More patients in the treatment arm had at least one related adverse event (94.4% versus 45.9%; p < 0.001); no other significant differences in safety endpoints were observed. Time to neurological deterioration was not different between trial arms (log-rank test, p = 0.3135). Statistically significant differences favoring treatment were observed for the Multiple Sclerosis Functional Composite score at several timepoints, T1 and T2 lesion volume changes at 12 and 24 months, mean number of active lesions and proportion of patients with active lesions at 24 months. We conclude that interferon beta-1b is safe and well tolerated in patients with primary progressive multiple sclerosis and transitional multiple sclerosis. Positive effects of interferon beta on secondary clinical and magnetic resonance imaging outcomes were observed, but a beneficial effect on Expanded Disability Status Scale progression was not demonstrated.

Cervical Cord Atrophy and Long-Term Disease Progression in Patients with Primary-Progressive Multiple Sclerosis.

BACKGROUND AND PURPOSE: Cervical cord atrophy has been associated with clinical disability in multiple sclerosis and is proposed as an outcome measure of neurodegeneration. The aim of this study was to quantify the development of cervical cord atrophy and to evaluate its association with disability progression in patients with primary-progressive multiple sclerosis. MATERIALS AND METHODS: Thirty-one patients with primary-progressive multiple sclerosis underwent 1.5T brain and spinal cord MR imaging at baseline and 6-7 years later. The cervical spinal cord from C1 to C5 was segmented to evaluate the normalized overall cross-sectional area and the cross-sectional area of C2-C3, C3-C4, and C4-C5. The annualized rates of normalized cross-sectional area loss were also evaluated. To estimate clinical progression, we determined the Expanded Disability Status Scale score at baseline and at 2 and 14 years after baseline to compute the normalized area under the curve of the Expanded Disability Status Scale and the Expanded Disability Status Scale changes from baseline to the follow-up time points. Associations between the cord cross-sectional area and brain MR imaging and clinical measures were also investigated. Finally, the value of all these measures for predicting long-term disability was evaluated. RESULTS: Some normalized cross-sectional area measurements showed moderate correlations with the normalized area under the curve of the Expanded Disability Status Scale, ranging from -0.439 to -0.359 (P < .05). Moreover, the annualized rate of the normalized mean cross-sectional area loss and the baseline Expanded Disability Status Scale were independent predictors of long-term disability progression. CONCLUSIONS: These data indicate that development of cervical cord atrophy is associated with progression of disability and is predictive of this event in patients with primary-progressive MS.

A fuzzy approach for feature extraction of brain tissues in Non-Contrast CT / Un enfoque difuso para la extracción de características de tejidos cerebrales en TC no contrastada

Abstract: In neuroimaging, brain tissue segmentation is a fundamental part of the techniques that seek to automate the detection of pathologies, the quantification of tissues or the evaluation of the progress of a treatment. Because of its wide availability, lower cost than other imaging techniques, fast execution and proven efficacy, Non-contrast Cerebral Computerized Tomography (NCCT) is the most used technique in emergency room for neuroradiology examination, however, most research on brain segmentation focuses on MRI due to the inherent difficulty of brain tissue segmentation in NCCT. In this work, three brain tissues were characterized: white matter, gray matter and cerebrospinal fluid in NCCT images. Feature extraction of these structures was made based on the radiological attenuation index denoted by the Hounsfield Units using fuzzy logic techniques. We evaluated the classification of each tissue in NCCT images and quantified the feature extraction technique in synthetic images from real tissues with a sensitivity of 92% and a specificity of 96% for images from cases with slice thickness of 1 mm, and 96% and 98% respectively for those of 1.5 mm, demonstrating the ability of the method as feature extractor of brain tissues.

Resumen: En neuroimagen, la segmentación de tejidos cerebrales es una parte fundamental de las técnicas que buscan automatizar la detección de patologías, la cuantificación de tejidos o la evaluación del progreso de un tratamiento. Debido a su amplia disponibilidad, menor costo que otras técnicas de imagen, rápida ejecución y eficacia probada, la tomografía computarizada cerebral sin contraste (TCNC) es la técnica mayormente utilizada en emergencias para el examen neurorradiológico, sin embargo, la dificultad inherente que representa la segmentación de los tejidos cerebrales, hace que la mayoría de las investigaciones sobre la segmentación del cerebro se centren en la resonancia magnética. En este trabajo se realizó la caracterización de tres tejidos cerebrales: sustancia blanca, sustancia gris y líquido cefalorraquídeo en imágenes TCNC. Dichas estructuras fueron caracterizadas con base en el índice de atenuación radiológica denotadas por las Unidades Hounsfield utilizando técnicas de lógica difusa. Se evaluó la caracterización de cada tejido en diversos cortes de TCNC y se cuantificó la técnica de extracción de características en imágenes sintéticas a partir de tejidos reales con una sensibilidad de 92% y una especificidad de 96% para tejidos en cortes de 1 mm de grosor y 96% y 98% para los de 1.5 mm demostrando la habilidad del método como extractor de características de los tejidos cerebrales.

Fuzzy approach toward reducing false positives in the detection of small multiple sclerosis lesions in magnetic resonance images.

The large number of false positives that result when automatic algorithms are considered for segmenting small multiple sclerosis lesions in magnetic resonance imaging hampers the posterior evaluation of lesion load. To address this problem we propose a fuzzy system which can improve the differentiation between true and false positive detections in proton density- and T2-weighted images. On the basis of an earlier work, which was focused on the detection of hyperintense regions in MR brain images, the system here presented introduces fuzzy restrictions derived from the regional analysis of the main features in such regions. Results show a reduction to a 3.6% in the number of false detections while preserving most of the true detections obtained using previous algorithm.

Biexponential analysis of diffusion-tensor imaging of the brain in patients with cirrhosis before and after liver transplantation.

BACKGROUND AND PURPOSE: DTI has shown increased MD of water molecules in the brain of patients with cirrhosis, consistent with low-grade edema. This study further characterizes this edema by using biexponential analysis of DTI data, a technique that may differentiate cytotoxic and vasogenic edema. MATERIALS AND METHODS: A total of 41 patients with cirrhosis awaiting liver transplantation and 16 healthy controls were studied by DTI by using a single-shot echo-planar technique with 11 b-values (range, 0-7500 s/mm(2)) and 6 noncollinear directions. Measurements were fitted to biexponential function to determine MD and FA for the fast and slow diffusion components. Regions of interest were selected in the parietal white matter and corticospinal tract. The assessment was repeated 1 year after liver transplantation in 24 of these patients. RESULTS: In parietal white matter, patients with cirrhosis showed an increase in fast MD and a decrease in fast FA that normalized after liver transplantation. In the corticospinal tract, there was an increase in fast and slow MD that normalized after transplantation, and a decrease in FA that persisted posttransplantation. There was no association of DTI parameters with minimal HE (n =12). CONCLUSIONS: Biexponential analysis of DTI supports the presence of edema in the brain of patients with cirrhosis that reverts after transplantation. In parietal white matter, the increase in brain water was mainly located in the interstitial compartment, while the corticospinal tract showed a mixed pattern (intra- and extracellular). In addition, the findings on posttransplantation were consistent with microstructural damage along the corticospinal tract.