Diagnostic value of 3D fluid attenuated inversion recovery sequence in multiple sclerosis

Diagnostic value of three-dimensional cube fluid attenuated inversion recovery imaging and its axial MIP reconstruction in multiple sclerosis

Background

Magnetic resonance imaging is regarded as one of the most important markers for multiple sclerosis. It can detect lesions in order to establish dissemination in time and space, which would aid in the diagnosis. Two-dimensional FLAIR is a standard sequence in MS routine imaging because it suppresses cerebrospinal fluid signal, increasing contrast between lesions and CSF and improving white matter lesion detection. Newer 3D FLAIR sequences are expected to offer even more benefits, such as improved MS lesions detection and higher resolution due to thinner slice thickness. We aimed to compare the role of 3D Cube FLAIR imaging (versus standard 2D FLAIR) in the assessment of white matter lesions in MS patients, as well as to test the convenience of using maximum intensity projection (MIP) on 3D FLAIR images for faster and easier evaluation.

Results

This study included 160 MS patients. A 1.5 T routine brain MRI scan was performed, which included a 2D FLAIR sequence, followed by a 3D-FLAIR sequence. All images were analyzed after 3D-FLAIR images were reformatted into axial MIP images. Lesions were counted in each sequence and classified into supra-tentorial (periventricular, deep white matter, and juxta-cortical), and infra-tentorial lesions, with the relative comparison of lesions numbers on 3D-FLAIR and MIP versus 2D-FLAIR expressed as a percentage increase or decrease. 3D FLAIR can significantly improve MS lesion detection in all areas of the brain when compared with 2D FLAIR results. At 2 mm reformatting, there is no difference in MS lesion detection between sagittal 3D FLAIR and axial MIP reconstruction, implying that the MIP algorithm can be used to simplify lesion detection by reducing the number of images while maintaining the same level of reliability.

Conclusion

3D FLAIR sequences should be added to conventional 2D FLAIR sequences in the MRI protocol when MS is suspected.

Automatic segmentation of white matter hyperintensities: validation and comparison with state-of-the-art methods on both Multiple Sclerosis and elderly subjects

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Automatic segmentation of MS lesions and age-related WMH from 3D T1 and T2-FLAIR.

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Comparison to consensus show improved performance of WHASA-3D compared to WHASA.

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WHASA-3D outperforms available state-of-the-art methods with their default settings.

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WHASA-3D could be a useful tool for clinical practice and clinical trials.

Different types of white matter hyperintensities (WMH) can be observed through MRI in the brain and spinal cord, especially Multiple Sclerosis (MS) lesions for patients suffering from MS and age-related WMH for subjects with cognitive disorders and/or elderly people. To better diagnose and monitor the disease progression, the quantitative evaluation of WMH load has proven to be useful for clinical routine and trials. Since manual delineation for WMH segmentation is highly time-consuming and suffers from intra and inter observer variability, several methods have been proposed to automatically segment either MS lesions or age-related WMH, but none is validated on both WMH types. Here, we aim at proposing the White matter Hyperintensities Automatic Segmentation Algorithm adapted to 3D T2-FLAIR datasets (WHASA-3D), a fast and robust automatic segmentation tool designed to be implemented in clinical practice for the detection of both MS lesions and age-related WMH in the brain, using both 3D T1-weighted and T2-FLAIR images. In order to increase its robustness for MS lesions, WHASA-3D expands the original WHASA method, which relies on the coupling of non-linear diffusion framework and watershed parcellation, where regions considered as WMH are selected based on intensity and location characteristics, and finally refined with geodesic dilation. The previous validation was performed on 2D T2-FLAIR and subjects with cognitive disorders and elderly subjects. 60 subjects from a heterogeneous database of dementia patients, multiple sclerosis patients and elderly subjects with multiple MRI scanners and a wide range of lesion loads were used to evaluate WHASA and WHASA-3D through volume and spatial agreement in comparison with consensus reference segmentations. In addition, a direct comparison on the MS database with six available supervised and unsupervised state-of-the-art WMH segmentation methods (LST-LGA and LPA, Lesion-TOADS, lesionBrain, BIANCA and nicMSlesions) with default and optimised settings (when feasible) was conducted. WHASA-3D confirmed an improved performance with respect to WHASA, achieving a better spatial overlap (Dice) (0.67 vs 0.63), a reduced absolute volume error (AVE) (3.11 vs 6.2 mL) and an increased volume agreement (intraclass correlation coefficient, ICC) (0.96 vs 0.78). Compared to available state-of-the-art algorithms on the MS database, WHASA-3D outperformed both unsupervised and supervised methods when used with their default settings, showing the highest volume agreement (ICC = 0.95) as well as the highest average Dice (0.58). Optimising and/or retraining LST-LGA, BIANCA and nicMSlesions, using a subset of the MS database as training set, resulted in improved performances on the remaining testing set (average Dice: LST-LGA default/optimized = 0.41/0.51, BIANCA default/optimized = 0.22/0.39, nicMSlesions default/optimized = 0.17/0.63, WHASA-3D = 0.58). Evaluation and comparison results suggest that WHASA-3D is a reliable and easy-to-use method for the automated segmentation of white matter hyperintensities, for both MS lesions and age-related WMH. Further validation on larger datasets would be useful to confirm these first findings.

FLAIR2 post-processing: improving MS lesion detection in standard MS imaging protocols

BACKGROUND

Technical improvements in magnetic resonance imaging (MRI) acquisition, such as higher field strength and optimized sequences, lead to better multiple sclerosis (MS) lesion detection and characterization. Multiplication of 3D-FLAIR with 3D-T2 sequences (FLAIR²) results in isovoxel images with increased contrast-to-noise ratio, increased white-gray-matter contrast, and improved MS lesion visualization without increasing MRI acquisition time. The current study aims to assess the potential of 3D-FLAIR² in detecting cortical/leucocortical (LC), juxtacortical (JC), and white matter (WM) lesions.

OBJECTIVE

To compare lesion detection of 3D-FLAIR² with state-of-the-art 3D-T2-FLAIR and 3D-T2-weighted images.

METHODS

We retrospectively analyzed MRI scans of thirteen MS patients, showing previously noted high cortical lesion load. Scans were acquired using a 3 T MRI scanner. WM, JC, and LC lesions were manually labeled and manually counted after randomization of 3D-T2, 3D-FLAIR, and 3D-FLAIR² scans using the ITK-SNAP tool.

RESULTS

LC lesion visibility was significantly improved by 3D-FLAIR² in comparison to 3D-FLAIR (4 vs 1; p = 0.018) and 3D-T2 (4 vs 1; p = 0.007). Comparing LC lesion detection in 3D-FLAIR² vs. 3D-FLAIR, 3D-FLAIR² detected on average 3.2 more cortical lesions (95% CI - 9.1 to 2.8). Comparing against 3D-T2, 3D-FLAIR² detected on average 3.7 more LC lesions (95% CI 3.3-10.7).

CONCLUSIONS

3D-FLAIR² is an easily applicable time-sparing MR post-processing method to improve cortical lesion detection. Larger sampled studies are warranted to validate the sensitivity and specificity of 3D-FLAIR².

Genetic diseases mimicking multiple sclerosis

Multiple sclerosis (MS) is an inflammatory neurodegenerative disorder manifesting as gradual or progressive loss of neurological functions. Most patients present with relapsing-remitting disease courses. Extensive research over recent decades has expounded our insights into the presentations and diagnostic features of MS. Groups of genetic diseases, CADASIL and leukodystrophies, for example, have been frequently misdiagnosed with MS due to some overlapping clinical and radiological features. The delayed identification of these diseases in late adulthood can lead to severe neurological complications. Herein we discuss genetic diseases that have the potential to mimic multiple sclerosis, with highlights on clinical identification and practicing pearls that may aid physicians in recognizing MS-mimics with genetic background in clinical settings.

Mitochondrial dysfunction and serum lactate as a biomarker for the progression and disability in MS and its correlation with the radiological findings

Objective: To study the serum lactate level in MS and to explore its correlation with the progression and disability in multiple sclerosis (MS), and the important role of mitochondrial dysfunction in the pathogenesis of MS.Methods: This case-control study included 80 participants, involved 50 MS patients and 30 normal healthy controls. Detailed history taking, complete neurological examination, and clinical evaluation of the disability using the Expanded Disability Status Scale (EDSS) were done for all patients. Level of serum lactate was measured in both groups and was correlated with EDSS, MS subtypes, MRI brain, and MRS findings.Results: Serum lactate in MS patients was about three and half times higher than serum lactate levels of healthy controls (22.87 ± 5.92 mg/dl versus 6.39 ± 0.9 6.39 ± 0.91, p < 0.001). Importantly, serum lactate values were increased in MS cases with a progressive course compared with MS cases with RR course. Also, there were linearly correlations linking serum lactate levels and the duration of MS (r = 0.342, P = 0.015), relapses numbers (r = 0.335, P = 0.022), and EDSS (r = 0.483, P < 0.001). Also, there were strong positive correlations between serum lactate and Lipid/Lactate (r = 0.461, P = 0.001), periventricular lesion (r = 0.453, P = 0.005), and moderate positive correlations between serum lactate and juxtacortical lesion (r = 0.351, P = 0.02), and infratentorial lesion (r = 0.355, P = 0.02).Conclusion: Measurement of serum lactate may be helpful in MS and this supports the hypothesis of the critical role of mitochondrial dysfunction and axonal damage in MS.Registration of Clinical Trial Research: ClinicalTrials.gov ID: NCT04210960.

Sensitive Detection of Infratentorial and Upper Cervical Cord Lesions in Multiple Sclerosis with Combined 3D FLAIR and T2-Weighted (FLAIR3) Imaging

BACKGROUND AND PURPOSE

Infratentorial and spinal cord lesions are important for diagnosing and monitoring multiple sclerosis, but they are difficult to detect on conventional MR imaging. We sought to improve the detection of infratentorial and upper cervical cord lesions using composite FLAIR3 images.

MATERIALS AND METHODS

3D T2-weighted FLAIR and 3D T2-weighted images were acquired in 30 patients with MS and combined using the FLAIR3 formula. FLAIR3 was assessed against 3D T2-FLAIR by comparing the number of infratentorial and upper cervical cord lesions per subject using the Wilcoxon signed rank test. Intrarater and interrater reliability was evaluated using the intraclass correlation coefficient. The number of patients with and without ≥1 visible infratentorial/spinal cord lesion on 3D T2-FLAIR versus FLAIR3 was calculated to assess the potential impact on the revised MS diagnostic criteria.

RESULTS

Compared with 3D T2-FLAIR, FLAIR3 detected significantly more infratentorial (mean, 4.6 ± 3.6 versus 2.0 ± 1.8, P < .001) and cervical cord (mean, 1.58 ± 0.94 versus 0.46 ± 0.45, P < .001) lesions per subject. FLAIR3 demonstrated significantly improved interrater reliability (intraclass correlation coefficient = 0.77 [95% CI, 0.63-0.87] versus 0.60 [95% CI, 0.40-0.76] with 3D T2-FLAIR, P = .019) and a tendency toward a higher intrarater reliability (0.86 [95% CI, 0.73-0.93] versus 0.79 [95% CI, 0.61-0.89], P = .23). In our cohort, 20%-30% (47%-67%) of the subjects with MS had  ≥ 1 infratentorial (cervical cord) lesion visible only on FLAIR3.

CONCLUSIONS

FLAIR3 provides higher sensitivity than T2-FLAIR for the detection of MS lesions in infratentorial brain parenchyma and the upper cervical cord.

Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks

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A fully automated segmentation of new or enlarged multiple sclerosis (MS) lesions.

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3D convolutional neural network (CNN) with U-net-like encoder-decoder architecture.

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Simultaneous processing of baseline and follow-up scan of the same patient.

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Trained on 3253 patient data from over 103 different MR scanners.

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Fast (<1min), robust algorithm with segmentation results in inter-rater variability.

The quantification of new or enlarged lesions from follow-up MRI scans is an important surrogate of clinical disease activity in patients with multiple sclerosis (MS). Not only is manual segmentation time consuming, but inter-rater variability is high. Currently, only a few fully automated methods are available. We address this gap in the field by employing a 3D convolutional neural network (CNN) with encoder-decoder architecture for fully automatic longitudinal lesion segmentation.

Input data consist of two fluid attenuated inversion recovery (FLAIR) images (baseline and follow-up) per patient. Each image is entered into the encoder and the feature maps are concatenated and then fed into the decoder. The output is a 3D mask indicating new or enlarged lesions (compared to the baseline scan). The proposed method was trained on 1809 single point and 1444 longitudinal patient data sets and then validated on 185 independent longitudinal data sets from two different scanners. From the two validation data sets, manual segmentations were available from three experienced raters, respectively. The performance of the proposed method was compared to the open source Lesion Segmentation Toolbox (LST), which is a current state-of-art longitudinal lesion segmentation method.

The mean lesion-wise inter-rater sensitivity was 62%, while the mean inter-rater number of false positive (FP) findings was 0.41 lesions per case. The two validated algorithms showed a mean sensitivity of 60% (CNN), 46% (LST) and a mean FP of 0.48 (CNN), 1.86 (LST) per case. Sensitivity and number of FP were not significantly different (p < 0.05) between the CNN and manual raters.

New or enlarged lesions counted by the CNN algorithm appeared to be comparable with manual expert ratings. The proposed algorithm seems to outperform currently available approaches, particularly LST. The high inter-rater variability in case of manual segmentation indicates the complexity of identifying new or enlarged lesions. An automated CNN-based approach can quickly provide an independent and deterministic assessment of new or enlarged lesions from baseline to follow-up scans with acceptable reliability.

Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines

MRI has improved the diagnostic work-up of multiple sclerosis, but inappropriate image interpretation and application of MRI diagnostic criteria contribute to misdiagnosis. Some diseases, now recognized as conditions distinct from multiple sclerosis, may satisfy the MRI criteria for multiple sclerosis (e.g. neuromyelitis optica spectrum disorders, Susac syndrome), thus making the diagnosis of multiple sclerosis more challenging, especially if biomarker testing (such as serum anti-AQP4 antibodies) is not informative. Improvements in MRI technology contribute and promise to better define the typical features of multiple sclerosis lesions (e.g. juxtacortical and periventricular location, cortical involvement). Greater understanding of some key aspects of multiple sclerosis pathobiology has allowed the identification of characteristics more specific to multiple sclerosis (e.g. central vein sign, subpial demyelination and lesional rims), which are not included in the current multiple sclerosis diagnostic criteria. In this review, we provide the clinicians and researchers with a practical guide to enhance the proper recognition of multiple sclerosis lesions, including a thorough definition and illustration of typical MRI features, as well as a discussion of red flags suggestive of alternative diagnoses. We also discuss the possible place of emerging qualitative features of lesions which may become important in the near future.

Neuroprotective effects of exercise in people with progressive multiple sclerosis (Exercise PRO-MS): study protocol of a phase II trial

Background

Neurodegeneration, rather than inflammation, plays a key role in the progressive phase of multiple sclerosis (MS). Current disease modifying treatment options for people with progressive MS (PMS) do not specifically target neurodegeneration. Preliminary evidence suggests that exercise therapy might have neuroprotective effects. However, neuroprotective effect studies of exercise interventions in PMS are scarce and the possible mode of action underlying neuroprotective effects of exercise are unknown and need to be elucidated. The main aim of this phase II trial is to assess whether progressive resistance training (PRT) and high intensity interval training (HIIT), can slow down neurodegeneration in people with PMS.

Methods

In a single-blinded phase II clinical trial with an extended baseline period, 60 people with PMS will be randomly assigned to PRT or HIIT. The participants should have had a relapse onset of MS with confirmed disease progression, however still ambulatory. The duration of the study is 48 weeks, consisting of 16 weeks baseline period (no intervention), 16 weeks intervention and 16 weeks follow-up. Patient-tailored training will be performed 3 times per week for one hour in groups, led by an experienced physiotherapist. The primary outcome measure is neurodegeneration, measured as whole brain atrophy on magnetic resonance imaging (MRI). Secondary outcome parameters will include other biomarkers associated with neurodegeneration (i.e. regional brain atrophy, lesion load, white matter integrity, resting state functional connectivity, blood biomarkers (brain derived neurotrophic factor (BDNF) and serum neurofilament light (sNFL)), patient functioning (physical and cognitive) and cardiovascular risk factors.

Discussion

Besides the primary outcome measures, this study will examine a large variety of biomarkers associated with neurodegeneration after an exercise intervention. Combining outcome parameters may help to elucidate the mode of action underlying neuroprotective effects of exercise.

Trial registration

This trial is prospectively registered at the Dutch Trial Registry (number NL8265, date 06-01-2020).

Optimizing 3D FLAIR to detect MS lesions: pushing past factory settings for precise results

BACKGROUND

To assess the diagnostic value of three 3D FLAIR sequences with differing repetition-times (TR) at 3-Tesla when detecting multiple sclerosis (MS) lesions.

METHODS

In this prospective study, approved by the institutional review board, 27 patients with confirmed MS were prospectively included. One radiologist performed manual segmentations of all high-signal intensity lesions using three 3D FLAIR data sets with different TR of 4800 ms ("FLAIR₄₈₀₀"), 8000 ms ("FLAIR₈₀₀₀") and 10,000 ms ("FLAIR_10,000") and two radiologists double-checked it. The main judgment criterion was the overall number of lesions; secondary objectives were the assessment of lesion location, as well as measuring contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). A non-parametric Wilcoxon's test was used to compare the differing FLAIR.

RESULTS

The FLAIR₈₀₀₀ and FLAIR_10,000 detected significantly more overall lesions per patient as compared with the FLAIR₄₈₀₀ [116.1 (± 61.7) (p = 0.02) and 115.8 (± 56.3) (p = 0.03) versus 99.2 (± 66.9), respectively]. The FLAIR₈₀₀₀ and FLAIR_10,000 detected four and eight times more cortical or juxta-cortical lesions per patient as compared with FLAIR₄₈₀₀ [1.6 (± 2.2) (p = 0.001) and 4.1 (± 5.9) (p = 6 × 10^-5) versus 0.4 (± 1.1), respectively]. CNR was significantly correlated to the TR value. It was significantly higher with FLAIR_10,000 than it was with FLAIR₈₀₀₀ and FLAIR₄₈₀₀ [16.3 (± 3.5) versus 15 (± 2.4) (p = 0.01) and 12 (± 2.2) (p = 2 × 10^-6), respectively] CONCLUSION: An optimized 3D FLAIR with a long TR significantly improved both overall lesion detection and CNR in MS patients as compared to a 3D FLAIR with factory settings.

Improving Detection of Multiple Sclerosis Lesions in the Posterior Fossa Using an Optimized 3D-FLAIR Sequence at 3T

BACKGROUND AND PURPOSE

There is no consensus regarding the best MR imaging sequence for detecting MS lesions. The aim of our study was to assess the diagnostic value of optimized 3D-FLAIR in the detection of infratentorial MS lesions compared with an axial T2-weighted imaging, a 3D-FLAIR with factory settings, and a 3D double inversion recovery sequence.

MATERIALS AND METHODS

In this prospective study, 27 patients with confirmed MS were included. Two radiologists blinded to clinical data independently read the following sequences: axial T2WI, 3D double inversion recovery, standard 3D-FLAIR with factory settings, and optimized 3D-FLAIR. The main judgment criterion was the overall number of high-signal-intensity lesions in the posterior fossa; secondary objectives were the assessment of the reading confidence and the measurement of the contrast. A nonparametric Wilcoxon test was used to compare the MR images.

RESULTS

Twenty-two patients had at least 1 lesion in the posterior fossa. The optimized FLAIR sequence detected significantly more posterior fossa lesions than any other sequence: 7.5 versus 5.8, 4.8, and 4.1 (P values of .04, .03, and .03) with the T2WI, the double inversion recovery, and the standard FLAIR, respectively. The reading confidence index was significantly higher with the optimized FLAIR, and the contrast was significantly higher with the optimized FLAIR than with the standard FLAIR and the double inversion recovery.

CONCLUSIONS

An optimized 3D-FLAIR sequence improved posterior fossa lesion detection in patients with MS.

Follow-up MRI in multiple sclerosis patients: automated co-registration and lesion color-coding improves diagnostic accuracy and reduces reading time

OBJECTIVES

In multiple sclerosis (MS), the heterogeneous and numerous appearances of lesions may impair diagnostic accuracy. This study investigates if a combined automated co-registration and lesion color-coding method (AC) improves assessment of MS follow-up MRI compared with conventional reading (CR).

METHODS

We retrospectively assessed 70 follow-up MRI of 53 patients. Heterogeneous datasets of diverse scanners and institutions were used. Two readers determined presence of (a) progression, (b) regression, (c) mixed change, or (d) stable disease between the two examinations using corresponding FLAIR sequences in CR and AC-assisted reading. Consensus reference reading was provided by two blinded radiologists. Kappa statistics tested interrater agreement, McNemar's test dichotomous variables, and Wilcoxon's test continuous variables (statistical significance p ≤ 0.05).

RESULTS

The cohort comprised 41 female and 12 male patients with a mean age of 40 (± 14) years. Average rating time was reduced from 78 (± 36) to 44 (±22) s with the AC approach (p < 0.001). The time needed to start and match datasets with AC was 14 (± 1) s. Compared with CR, AC improved interrater agreement, both between raters (0.52 vs. 0.67) and between raters and consensus reference reading (0.47/0.5 vs. 0.83/0.78). Compared with CR, the diagnostic accuracy increased from 67 to 90% (reader 1, p < 0.01) and from 70 to 87% (reader 2, p < 0.05) in the AC-assisted reading.

CONCLUSIONS

Compared with CR, automated co-registration and lesion color-coding of MS-associated FLAIR-lesions in follow-up MRI increased diagnostic accuracy and reduced the time required for follow-up evaluation significantly. The AC algorithm therefore appears to be helpful to improve MS follow-up assessments in clinical routine.

KEY POINTS

• Automated co-registration and lesion color-coding increases diagnostic accuracy in the assessment of MRI follow-up examinations in patients with multiple sclerosis. • Automated co-registration and lesion color-coding reduces reading time of MRI follow-up examinations in patients with multiple sclerosis. • Automated co-registration and lesion color-coding improved interrater agreement in the assessment of MRI follow-up examinations in patients with multiple sclerosis.

Structural and functional MRI correlates of T2 hyperintensities of brain white matter in young neurologically asymptomatic adults

OBJECTIVES

Although white matter hyperintensities (WMHs) are quite commonly found incidentally, their aetiology, structural characteristics, and functional consequences are not entirely known. The purpose of this study was to quantify WMHs in a sample of young, neurologically asymptomatic adults and evaluate the structural and functional correlations of lesion load with changes in brain volume, diffusivity, and functional connectivity.

METHODS

MRI brain scan using multimodal protocol was performed in 60 neurologically asymptomatic volunteers (21 men, 39 women, mean age 34.5 years). WMHs were manually segmented in 3D FLAIR images and counted automatically. The number and volume of WMHs were correlated with brain volume, resting-state functional MRI (rs-fMRI), and diffusion tensor imaging (DTI) data. Diffusion parameters measured within WMHs and normally appearing white matter (NAWM) were compared.

RESULTS

At least 1 lesion was found in 40 (67%) subjects, median incidence was 1 lesion (interquartile range [IQR] = 4.5), and median volume was 86.82 (IQR = 227.23) mm³. Neither number nor volume of WMHs correlated significantly with total brain volume or volumes of white and grey matter. Mean diffusivity values within WMHs were significantly higher compared with those for NAWM, but none of the diffusion parameters of NAWM were significantly correlated with WMH load. Both the number and volume of WMHs were correlated with the changes of functional connectivity between several regions of the brain, mostly decreased connectivity of the cerebellum.

CONCLUSIONS

WMHs are commonly found even in young, neurologically asymptomatic adults. Their presence is not associated with brain atrophy or global changes of diffusivity, but the increasing number and volume of these lesions correlate with changes of brain connectivity, and especially that of the cerebellum.

KEY POINTS

• White matter hyperintensities (WMHs) are commonly found in young, neurologically asymptomatic adults. • The presence of WMHs is not associated with brain atrophy or global changes of white matter diffusivity. • The increasing number and volume of WMHs correlate with changes of brain connectivity, and especially with that of the cerebellum.

Three-dimensional MRI sequences in MS diagnosis and research

The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).

Value of fluid-attenuated inversion recovery MRI data analyzed by the lesion segmentation toolbox in amyotrophic lateral sclerosis

Background

MRI fluid‐attenuated inversion recovery (FLAIR) studies reported hyperintensity in the corticospinal tract and corpus callosum of patients with amyotrophic lateral sclerosis (ALS).

Purpose

To evaluate the lesion segmentation toolbox (LST) for the objective quantification of FLAIR lesions in ALS patients.

Study Type

Retrospective.

Population

Twenty‐eight ALS patients (eight females, mean age: 50 range: 24–73, mean ALSFRS‐R sum score: 36) were compared with 31 age‐matched healthy controls (12 females, mean age: 45, range: 25–67). ALS patients were treated with riluzole and additional G‐CSF (granulocyte‐colony stimulating factor) on a named patient basis.

Field Strength/Sequence

1.5 T, FLAIR, T₁‐weighted MRI.

Assessment

The lesion prediction algorithm (LPA) of the LST enabled the extraction of individual binary lesion maps, total lesion volume (TLV), and number (TLN). Location and overlap of FLAIR lesions across patients were investigated by registration to FLAIR average space and an atlas. ALS‐specific functional rating scale revised (ALSFRS‐R), disease progression, and survival since diagnosis served as clinical correlates.

Statistical Tests

Univariate analysis of variance (ANOVA), repeated‐measures ANOVA, t‐test, Bravais‐Pearson correlation, Chi‐square test of independence, Kaplan–Meier analysis, Cox‐regression analysis.

Results

Both ALS patients and healthy controls exhibited FLAIR alterations. TLN significantly depended on age (F(1,54) = 24.659, P < 0.001) and sex (F(1,54) = 5.720, P = 0.020). ALS patients showed higher TLN than healthy controls depending on sex (F(1, 54) = 5.076, P = 0.028). FLAIR lesions were small and most pronounced in male ALS patients. FLAIR alterations were predominantly detected in the superior and posterior corona radiata, anterior capsula interna, and posterior thalamic radiation. Patients with pyramidal tract (PT) lesions exhibited significantly inferior survival than patients without PT lesions (P = 0.013). Covariate age exhibited strong prognostic value for survival (P = 0.015).

Data Conclusion

LST enables the objective quantification of FLAIR alterations and is a potential prognostic biomarker for ALS.

Level of Evidence: 3

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2019;50:552–559.

Comparing lesion detection of infratentorial multiple sclerosis lesions between T2-weighted spin-echo, 2D-FLAIR, and 3D-FLAIR sequences

PURPOSE

Infratentorial lesions in patients with multiple sclerosis are associated with long-term disability. Two-dimensional fluid-attenuated inversion recovery demonstrates poor infratentorial lesion detection when compared to T2-weighted spin echo. Evidence of improved detection with 3D fluid-attenuated inversion recovery has been conflicting. This study compares the infratentorial lesion detection performance, observer performance, and signal and contrast properties between T2-weighted spin echo, 2D, and 3D fluid-attenuated inversion recovery.

METHODS

Two board-certified radiologists independently reviewed and counted infratentorial lesions from 85 brain MRIs in patients with clinically definite multiple sclerosis and concurrent 3D, 2D fluid-attenuated inversion recovery, and T2-weighted spin echo sequences. Contrast-to-noise and signal-to-noise ratios were measured for 25 MRIs. Wilcoxon signed-rank test was used for pairwise comparisons of the combined average infratentorial lesion count, contrast-to-noise, and signal-to-noise ratios, and was adjusted for three pairwise comparisons using Bonferroni correction. A corrected p value < 0.05 was considered statistically significant.

RESULTS

The number of lesions on 3D fluid-attenuated inversion recovery was significantly higher than those on 2D (p < 0.001) and T2-weighted spin echo (p < 0.001). Results of contrast-to-noise and signal-to-noise ratios were overall mixed and predominantly not concordant with lesion count findings, with T2-weighted spin echo demonstrating the highest signal-to-noise ratios and contrast-to-noise ratio of lesion compared with white matter but the lowest contrast-to-noise ratio of lesion compared with gray matter.

CONCLUSION

The 3D fluid-attenuated inversion recovery sequence addresses the disadvantage of poor infratentorial lesion detection on 2D, while still maintaining the advantage over T2-weighted spin echo in the detection of lesions adjacent to the cerebrospinal fluid.

Cerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging

The cerebellum plays a key role in movement control and in cognition and cerebellar involvement is described in several neurodegenerative diseases. While conventional magnetic resonance imaging (MRI) is widely used for brain and cerebellar morphologic evaluation, advanced MRI techniques allow the investigation of cerebellar microstructural and functional characteristics. Volumetry, voxel-based morphometry, diffusion MRI based fiber tractography, resting state and task related functional MRI, perfusion, and proton MR spectroscopy are among the most common techniques applied to the study of cerebellum. In the present review, after providing a brief description of each technique’s advantages and limitations, we focus on their application to the study of cerebellar injury in major neurodegenerative diseases, such as multiple sclerosis, Parkinson’s and Alzheimer’s disease and hereditary ataxia. A brief introduction to the pathological substrate of cerebellar involvement is provided for each disease, followed by the review of MRI studies exploring structural and functional cerebellar abnormalities and by a discussion of the clinical relevance of MRI measures of cerebellar damage in terms of both clinical status and cognitive performance.

MRI FLAIR lesion segmentation in multiple sclerosis: Does automated segmentation hold up with manual annotation?

Introduction

Magnetic resonance imaging (MRI) has become key in the diagnosis and disease monitoring of patients with multiple sclerosis (MS). Both, T2 lesion load and Gadolinium (Gd) enhancing T1 lesions represent important endpoints in MS clinical trials by serving as a surrogate of clinical disease activity. T2- and fluid-attenuated inversion recovery (FLAIR) lesion quantification - largely due to methodological constraints – is still being performed manually or in a semi-automated fashion, although strong efforts have been made to allow automated quantitative lesion segmentation. In 2012, Schmidt and co-workers published an algorithm to be applied on FLAIR sequences. The aim of this study was to apply the Schmidt algorithm on an independent data set and compare automated segmentation to inter-rater variability of three independent, experienced raters.

Methods

MRI data of 50 patients with RRMS were randomly selected from a larger pool of MS patients attending the MS Clinic at the Brain and Mind Centre, University of Sydney, Australia. MRIs were acquired on a 3.0T GE scanner (Discovery MR750, GE Medical Systems, Milwaukee, WI) using an 8 channel head coil. We determined T2-lesion load (total lesion volume and total lesion number) using three versions of an automated segmentation algorithm (Lesion growth algorithm (LGA) based on SPM8 or SPM12 and lesion prediction algorithm (LPA) based on SPM12) as first described by Schmidt et al. (2012). Additionally, manual segmentation was performed by three independent raters. We calculated inter-rater correlation coefficients (ICC) and dice coefficients (DC) for all possible pairwise comparisons.

Results

We found a strong correlation between manual and automated lesion segmentation based on LGA SPM8, regarding lesion volume (ICC = 0.958 and DC = 0.60) that was not statistically different from the inter-rater correlation (ICC = 0.97 and DC = 0.66). Correlation between the two other algorithms (LGA SPM12 and LPA SPM12) and manual raters was weaker but still adequate (ICC = 0.927 and DC = 0.53 for LGA SPM12 and ICC = 0.949 and DC = 0.57 for LPA SPM12). Variability of both manual and automated segmentation was significantly higher regarding lesion numbers.

Conclusion

Automated lesion volume quantification can be applied reliably on FLAIR data sets using the SPM based algorithm of Schmidt et al. and shows good agreement with manual segmentation.

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Fully automated and manual MS lesion segmentation on FLAIR images were compared.

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Automated FLAIR lesion volume segmentation holds up with manual annotation.

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When using DC and ICC, SPM8 based algorithm performed better than recent updates.

Revised Recommendations of the Consortium of MS Centers Task Force for a Standardized MRI Protocol and Clinical Guidelines for the Diagnosis and Follow-Up of Multiple Sclerosis

An international group of neurologists and radiologists developed revised guidelines for standardized brain and spinal cord MR imaging for the diagnosis and follow-up of MS. A brain MR imaging with gadolinium is recommended for the diagnosis of MS. A spinal cord MR imaging is recommended if the brain MR imaging is nondiagnostic or if the presenting symptoms are at the level of the spinal cord. A follow-up brain MR imaging with gadolinium is recommended to demonstrate dissemination in time and ongoing clinically silent disease activity while on treatment, to evaluate unexpected clinical worsening, to re-assess the original diagnosis, and as a new baseline before starting or modifying therapy. A routine brain MR imaging should be considered every 6 months to 2 years for all patients with relapsing MS. The brain MR imaging protocol includes 3D T1-weighted, 3D T2-FLAIR, 3D T2-weighted, post-single-dose gadolinium-enhanced T1-weighted sequences, and a DWI sequence. The progressive multifocal leukoencephalopathy surveillance protocol includes FLAIR and DWI sequences only. The spinal cord MR imaging protocol includes sagittal T1-weighted and proton attenuation, STIR or phase-sensitive inversion recovery, axial T2- or T2*-weighted imaging through suspicious lesions, and, in some cases, postcontrast gadolinium-enhanced T1-weighted imaging. The clinical question being addressed should be provided in the requisition for the MR imaging. The radiology report should be descriptive, with results referenced to previous studies. MR imaging studies should be permanently retained and available. The current revision incorporates new clinical information and imaging techniques that have become more available.

Novel Magnetic Resonance Imaging Techniques in Brain Tumors

Magnetic resonance imaging is a powerful, noninvasive imaging technique with exquisite sensitivity to soft tissue composition. Magnetic resonance imaging is primary tool for brain tumor diagnosis, evaluation of drug response assessment, and clinical monitoring of the patient during the course of their disease. The flexibility of magnetic resonance imaging pulse sequence design allows for a variety of image contrasts to be acquired, including information about magnetic resonance-specific tissue characteristics, molecular dynamics, microstructural organization, vascular composition, and biochemical status. The current review highlights recent advancements and novel approaches in MR characterization of brain tumors.

The Technical and Clinical Features of 3D-FLAIR in Neuroimaging

In clinical MR neuroimaging, 3D fluid-attenuated inversion recovery (3D-FLAIR) with a variable-flip-angle turbo spin echo sequence is becoming popular. There are more than 100 reports regarding 3D-FLAIR in the PubMed database. In this article, the technical and clinical features of 3D-FLAIR for neuroimaging are reviewed and summarized. 3D-FLAIR allows thinner slices with multi-planar reformation capability, a higher flow sensitivity, high sensitivity to subtle T1 changes in fluid, images without cerebrospinal fluid (CSF) inflow artifacts, and a 3D dataset compatible with computer-aided analysis. In addition, 3D-FLAIR can be obtained within a clinically reasonable scan time. It is important for radiologists to be familiar with the features of 3D-FLAIR and to provide useful information for patients.