Role of MRI in diagnosis and treatment of multiple sclerosis

Effects of MRI scanner manufacturers in classification tasks with deep learning models

Deep learning has become a leading subset of machine learning and has been successfully employed in diverse areas, ranging from natural language processing to medical image analysis. In medical imaging, researchers have progressively turned towards multi-center neuroimaging studies to address complex questions in neuroscience, leveraging larger sample sizes and aiming to enhance the accuracy of deep learning models. However, variations in image pixel/voxel characteristics can arise between centers due to factors including differences in magnetic resonance imaging scanners. Such variations create challenges, particularly inconsistent performance in machine learning-based approaches, often referred to as domain shift, where the trained models fail to achieve satisfactory or improved results when confronted with dissimilar test data. This study analyzes the performance of multiple disease classification tasks using multi-center MRI data obtained from three widely used scanner manufacturers (GE, Philips, and Siemens) across several deep learning-based networks. Furthermore, we investigate the efficacy of mitigating scanner vendor effects using ComBat-based harmonization techniques when applied to multi-center datasets of 3D structural MR images. Our experimental results reveal a substantial decline in classification performance when models trained on one type of scanner manufacturer are tested with data from different manufacturers. Moreover, despite applying ComBat-based harmonization, the harmonized images do not demonstrate any noticeable performance enhancement for disease classification tasks.

Improving the detection of new lesions in multiple sclerosis with a cascaded 3D fully convolutional neural network approach

Longitudinal magnetic resonance imaging (MRI) has an important role in multiple sclerosis (MS) diagnosis and follow-up. Specifically, the presence of new lesions on brain MRI scans is considered a robust predictive biomarker for the disease progression. New lesions are a high-impact prognostic factor to predict evolution to MS or risk of disability accumulation over time. However, the detection of this disease activity is performed visually by comparing the follow-up and baseline scans. Due to the presence of small lesions, misregistration, and high inter-/intra-observer variability, this detection of new lesions is prone to errors. In this direction, one of the last Medical Image Computing and Computer Assisted Intervention (MICCAI) challenges was dealing with this automatic new lesion quantification. The MSSEG-2: MS new lesions segmentation challenge offers an evaluation framework for this new lesion segmentation task with a large database (100 patients, each with two-time points) compiled from the OFSEP (Observatoire français de la sclérose en plaques) cohort, the French MS registry, including 3D T2-w fluid-attenuated inversion recovery (T2-FLAIR) images from different centers and scanners. Apart from a change in centers, MRI scanners, and acquisition protocols, there are more challenges that hinder the automated detection process of new lesions such as the need for large annotated datasets, which may be not easily available, or the fact that new lesions are small areas producing a class imbalance problem that could bias trained models toward the non-lesion class. In this article, we present a novel automated method for new lesion detection of MS patient images. Our approach is based on a cascade of two 3D patch-wise fully convolutional neural networks (FCNNs). The first FCNN is trained to be more sensitive revealing possible candidate new lesion voxels, while the second FCNN is trained to reduce the number of misclassified voxels coming from the first network. 3D T2-FLAIR images from the two-time points were pre-processed and linearly co-registered. Afterward, a fully CNN, where its inputs were only the baseline and follow-up images, was trained to detect new MS lesions. Our approach obtained a mean segmentation dice similarity coefficient of 0.42 with a detection F1-score of 0.5. Compared to the challenge participants, we obtained one of the highest precision scores (PPVL = 0.52), the best PPVL rate (0.53), and a lesion detection sensitivity (SensL of 0.53).

Direct imaging of white matter ultrashort T2∗ components at 7 Tesla

PURPOSE

To demonstrate direct imaging of the white matter ultrashort T₂^∗ components at 7 Tesla using inversion recovery (IR)-enhanced ultrashort echo time (UTE) MRI. To investigate its characteristics, potentials and limitations, and to establish a clinical protocol.

MATERIAL AND METHODS

The IR UTE technique suppresses long T₂^∗ signals within white matter by using adiabatic inversion in combination with dual-echo difference imaging. Artifacts arising at 7 T from long T₂^∗ scalp fat components were reduced by frequency shifting the IR pulse such that those frequencies were inverted likewise. For 8 healthy volunteers, the T₂^∗ relaxation times of white matter were then quantified. In 20 healthy volunteers, the UTE difference and fraction contrast were evaluated. Finally, in 6 patients with multiple sclerosis (MS), the performance of the technique was assessed.

RESULTS

A frequency shift of -1.2 ppm of the IR pulse (i.e. towards the fat frequency) provided a good suppression of artifacts. With this, an ultrashort compartment of (68 ± 6) % with a T₂^∗ time of (147 ± 58) μs was quantified with a chemical shift of (-3.6 ± 0.5) ppm from water. Within healthy volunteers' white matter, a stable ultrashort T₂^∗ fraction contrast was calculated. For the MS patients, a significant fraction reduction in the identified lesions as well as in the normal-appearing white matter was observed.

CONCLUSIONS

The quantification results indicate that the observed ultrashort components arise primarily from myelin tissue. Direct IR UTE imaging of the white matter ultrashort T₂^∗ components is thus feasible at 7 T with high quantitative inter-subject repeatability and good detection of signal loss in MS.

Krizsan A, Forgács A, Berényi E, Balkay L. Effect of grey-level discretization on texture feature on different weighted MRI images of diverse disease groups

PURPOSE

Many studies of MRI radiomics do not include the discretization method used for the analyses, which might indicate that the discretization methods used are considered irrelevant. Our goals were to compare three frequently used discretization methods (lesion relative resampling (LRR), lesion absolute resampling (LAR) and absolute resampling (AR)) applied to the same data set, along with two different lesion segmentation approaches.

METHODS

We analyzed the effects of altering bin widths or bin numbers for the three different sampling methods using 40 texture indices (TIs). The impact was evaluated on brain MRI studies obtained for 71 patients divided into three different disease groups: multiple sclerosis (MS, N = 22), ischemic stroke (IS, N = 22), cancer patients (N = 27). Two different MRI acquisition protocols were considered for all patients, a T2- and a post-contrast 3D T1-weighted MRI sequence. Elliptical and manually drawn VOIs were employed for both imaging series. Three different types of gray-level discretization methods were used: LRR, LAR and AR. Hypothesis tests were done among all diseased and control areas to compare the TI values in these areas. We also did correlation analyses between TI values and lesion volumes.

RESULTS

In general, no significant differences were reported in the results when employing the AR and LAR discretization methods. It was found that employing 38 TIs introduced variation in the results when the number of bin parameters was altered, suggesting that both the degree and direction of monotonicity between each TI value and binning parameters were characteristic for each TI. Furthermore, while TIs were changing with altering binning values, no changes correlated to neither disease nor the MRI sequence. We found that most indices correlated weakly with the volume, while the correlation coefficients were independent of both diseases analyzed and MR contrast. Several cooccurrence-matrix based texture parameters show a definite higher correlation when employing the LRR discretization method However, with the best correlations obtained for the manually drawn VOI. Hypothesis tests among all disease and control areas (co-lateral hemisphere) revealed that the AR or LAR discretization techniques provide more suitable texture features than LRR. In addition, the manually drawn segmentation gave fewer significantly different TIs than the ellipsoid segmentations. In addition, the amount of TIs with significant differences was increasing with increasing the number of bins, or decreasing bin widths.

CONCLUSION

Our findings indicate that the AR discretization method may offer the best texture analysis in MR image assessments. Employing too many bins or too large bin widths might reduce the selection of TIs that can be used for differential diagnosis. In general, more statistically different TIs were observed for elliptical segmentations when compared to the manually drawn VOIs. In the texture analysis of MR studies, studies and publications should report on all important parameters and methods related to data collection, corrections, normalization, discretization, and segmentation.

Lesion load assessment among multiple sclerosis patient using DIR, FLAIR, and T2WI sequences

Background

Magnetic resonance imaging (MRI) is one of the diagnostic imaging modalities employing in lesion detection in neurological disorders such as multiple sclerosis (MS). Advances in MRI techniques such as double inversion recovery (DIR) made it more sensitive to distinguish lesions in the brain. To investigate the lesion load on different anatomical regions of the brain with MS using DIR, fluid attenuated inversion recovery (FLAIR) and T2-weighted imaging (T2WI) sequences. A total of 97 MS patients were included in our retrospective study, confirmed by neurologist. The patients were randomly selected from the major hospital in Saudi Arabia. All images were obtained using 3T Scanner (Siemens Skyra). The images from the DIR, FLAIR, and T2WI sequence were compared on axial planes with identical anatomic position and the number of lesions was assigned to their anatomical region.

Results

Comparing the lesion load measurement at various brain anatomical regions showed a significant difference among those three methods (p < 0.05).

Conclusion

DIR is a valuable MRI sequence for better delineation, greater contrast measurements and the increasing total number of MS lesions in MRI, compared with FLAIR, and T2WI and DIR revealed more intracortical lesions as well; therefore, in MS patients, it is recommended to add DIR sequence in daily routine imaging sequences.

Hyperpolarized carbon-13 magnetic resonance spectroscopic imaging: a clinical tool for studying tumour metabolism

Glucose metabolism in tumours is reprogrammed away from oxidative metabolism, even in the presence of oxygen. Non-invasive imaging techniques can probe these alterations in cancer metabolism providing tools to detect tumours and their response to therapy. Although Positron Emission Tomography with (18F)2-fluoro-2-deoxy-D-glucose (18F-FDG PET) is an established clinical tool to probe cancer metabolism, it has poor spatial resolution and soft tissue contrast, utilizes ionizing radiation and only probes glucose uptake and phosphorylation and not further downstream metabolism. Magnetic Resonance Spectroscopy (MRS) has the capability to non-invasively detect and distinguish molecules within tissue but has low sensitivity and can only detect selected nuclei. Dynamic Nuclear Polarization (DNP) is a technique which greatly increases the signal-to-noise ratio (SNR) achieved with MR by significantly increasing nuclear spin polarization and this method has now been translated into human imaging. This review provides a brief overview of this process, also termed Hyperpolarized Carbon-13 Magnetic Resonance Spectroscopic Imaging (HP 13C-MRSI), its applications in preclinical imaging, an outline of the current human trials that are ongoing, as well as future potential applications in oncology.

Metabolic changes in normal appearing white matter in multiple sclerosis patients using multivoxel magnetic resonance spectroscopy imaging

Demyelination and axonal degeneration caused by multiple sclerosis (MS) exist in the white matter and not only in the lesion area. Magnetic resonance spectroscopy (MRS) could provide a unique insight into metabolic changes in the normal appearing white matter (NAWM). To evaluate the subtle axonal degeneration and delineate the spatial distribution of metabolite abnormalities in the NAWM in patients with MS. A total of 17 clinically definite relapsing-remitting MS (RRMS) patients and 21 healthy controls were enrolled in this study. 2D 1H magnetic resonance spectroscopic imaging (MRSI) performed at 3 Tesla was used to measure metabolite concentrations in the frontal-parietal-occipital NAWM. Ratios of N-acetyl-aspartate (NAA) and choline (Cho) to creatine (Cr) and Cho to NAA were calculated in each voxel. MS patients showed decreased NAA/Cr and increased Cho/NAA ratios in the NAWM compared to healthy controls. In the parietal NAWM, the extent of NAA/Cr decrease was significantly higher than that in the frontal and parietal-occipital NAWM. Decreased NAA in the NAWM would provide useful metabolic information for evaluation of disease progression in MS. The high extent of NAA decrease in the parietal NAWM helps improve the accuracy of the prediction.

Impairment of Smooth Pursuit as a Marker of Early Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is a diffuse disease that disrupts wide-ranging cerebral networks. The control of saccades and smooth pursuit are similarly dependent upon widespread networks, with the assessment of pursuit offering an opportunity to examine feedback regulation. We sought to characterize pursuit deficits in MS and to examine their relationship with disease duration.

METHODS

Twenty healthy controls, 20 patients with a clinically isolated syndrome (CIS), and 40 patients with clinically definite MS (CDMS) participated. Thirty-six trials of Rashbass' step-ramp paradigm of smooth pursuit, evenly split by velocity (8.65°, 17.1°, and 25.9°/s) and ramp direction (left/right), were performed. Four parameters were measured: latency of pursuit onset, closed-loop pursuit gain, number of saccades, and summed saccade amplitudes during pursuit. For CDMS patients, these were correlated with disease duration and Expanded Disability Status Scale (EDSS) score.

RESULTS

Closed-loop pursuit gain was significantly lower in CIS than controls at all speeds. CDMS gain was lower than controls at medium pursuit velocity. CDMS patients also displayed longer pursuit latency than controls at all velocities. All patients accumulated increased summed saccade amplitudes at slow and medium pursuit speeds, and infrequent high-amplitude saccades at the fast speed. No pursuit variable significantly correlated with EDSS or disease duration in CDMS patients.

CONCLUSION

Smooth pursuit is significantly compromised in MS from onset. Low pursuit gain and increased saccadic amplitudes may be robust markers of disseminated pathology in CIS and in more advanced MS. Pursuit may be useful in measuring early disease.

GRAPE: a graphical pipeline environment for image analysis in adaptive magnetic resonance imaging

PURPOSE

We present a platform, GRAphical Pipeline Environment (GRAPE), to facilitate the development of patient-adaptive magnetic resonance imaging (MRI) protocols.

METHODS

GRAPE is an open-source project implemented in the Qt C++ framework to enable graphical creation, execution, and debugging of real-time image analysis algorithms integrated with the MRI scanner. The platform provides the tools and infrastructure to design new algorithms, and build and execute an array of image analysis routines, and provides a mechanism to include existing analysis libraries, all within a graphical environment. The application of GRAPE is demonstrated in multiple MRI applications, and the software is described in detail for both the user and the developer.

RESULTS

GRAPE was successfully used to implement and execute three applications in MRI of the brain, performed on a 3.0-T MRI scanner: (i) a multi-parametric pipeline for segmenting the brain tissue and detecting lesions in multiple sclerosis (MS), (ii) patient-specific optimization of the 3D fluid-attenuated inversion recovery MRI scan parameters to enhance the contrast of brain lesions in MS, and (iii) an algebraic image method for combining two MR images for improved lesion contrast.

CONCLUSIONS

GRAPE allows graphical development and execution of image analysis algorithms for inline, real-time, and adaptive MRI applications.

Individual Assessment of Brain Tissue Changes in MS and the Effect of Focal Lesions on Short-Term Focal Atrophy Development in MS: A Voxel-Guided Morphometry Study

We performed voxel-guided morphometry (VGM) investigating the mechanisms of brain atrophy in multiple sclerosis (MS) related to focal lesions. VGM maps detect regional brain changes when comparing 2 time points on high resolution T1-weighted (T1w) magnetic resonace imaging (MRI). Two T1w MR datasets from 92 relapsing-remitting MS patients obtained 12 months apart were analysed with VGM. New lesions and volume changes of focal MS lesions as well as in the surrounding tissue were identified by visual inspection on colour coded VGM maps. Lesions were dichotomized in active and inactive lesions. Active lesions, defined by either new lesions (NL) (volume increase > 5% in VGM), chronic enlarging lesions (CEL) (pre-existent T1w lesions with volume increase > 5%), or chronic shrinking lesions (CSL) (pre-existent T1w lesions with volume reduction > 5%) in VGM, were accompanied by tissue shrinkage in surrounding and/or functionally related regions. Volume loss within the corpus callosum was highly correlated with the number of lesions in its close proximity. Volume loss in the lateral geniculate nucleus was correlated with lesions along the optic radiation. VGM analysis provides strong evidence that all active lesion types (NL, CEL, and CSL) contribute to brain volume reduction in the vicinity of lesions and/or in anatomically and functionally related areas of the brain.

A comparison of linear and nonlinear stability parameters in different clinical forms of multiple sclerosis

Background

Multiple sclerosis (MS) is one of the neurological diseases that affect the ability of subjects to stand and walk. The stability of MS subjects has been evaluated in various studies, mostly based on linear approach. Based on this approach it is controversial weather stability of MS subjects differ from normal or not. Therefore, the aim of this study was to evaluate stability in three groups of MS subjects (spastic, ataxic and ataxic-spastic) using both linear and non-linear approaches.

Method

Seventeen healthy and 36 subjects with MS participated in this study. The MS group presenting with spastic, ataxic and ataxic-spastic (each group consisted of 12 subjects) participated in the study. The stability of the subjects was evaluated using Kistler force plate. The difference between stability of the subjects was evaluated using the Multi Analysis of Variance and significant value was set at P < 0.05.

Result

There was a significant difference in the mean value of Approximate Entropy (ApEn) in anterior-posterior direction between normal (0.66 ± 0.13) and ataxic (0.85 ± 0.12) and ataxic-spastic (0.90 ± 0.12) subjects (P < 0.05) and no difference between normal and spastic groups (0.76 ± 0.13). The results of both linear and nonlinear approaches confirmed that both ataxic and ataxic-spastic subjects had more instability than normal subjects. Although, the mean values of stability parameters increased in spastic compared to normal, the difference was not statistically significant.

Conclusion

Subjects with ataxic and ataxic-spastic MS disorder had difficulty in controlling their stability during quiet standing. The results of this study also confirmed that spasticity of muscles surrounding the hip and knee joints did not influence standing stability in patients with spastic MS.

Magnetic Resonance Imaging as a Major Milestone in Multiple Sclerosis Diagnosis and Treatment

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system. Magnetic resonance imaging (MRI) has played a unique role in the diagnosis and management of patients with MS. In recent years, there have been considerable changes in the diagnostic criteria for MS as MRI-based studies have demonstrated their power in the earlier and more accurate diagnosis of the disease. Moreover, MRI metrics have become key supportive outcome measures for evaluating the efficacy of experimental treatments in randomized controlled trials. MRI can also be used as a prognostic tool in patients with clinically isolated syndrome (CIS). Conventional MR techniques including proton density, T1/T2-weighted images, and FLAIR sequences are now accepted in standard protocols for diagnostic and treatment outcome measures in clinical trials for MS. Radiological features may show a similarity between radiologically isolated syndrome and MS. Approximately two-thirds of individuals with RIS exhibit radiological progression and one-third develop neurological symptoms during mean follow-up times of up to five years. However, a current challenge in the global application of established criteria for RIS involves the accurate classification of subjects with incidentally identified anomalies that are highly characteristic of MS, in comparison to those categorized in medical parlance as possessing "unidentified bright objects" or nonspecific T2-hyperintensities, which are commonly identified in patients with migraine headache who fulfill the spatial dissemination requirements for MS. The need for systematically acquired data for improvements in the classification of radiologically isolated syndrome (RIS) and the generation of risk algorithms are critically important, providing a basis for scientifically supported management and most importantly, minimizing the number of improperly classified subjects exposed to unnecessary medical testing, MS treatments, and psychological harm. In addition, brain atrophy is a common finding that can now be quantitatively assessed by MR volumetric measures. Further, integrated strategies that combine MRI and clinical markers in scoring systems have provided a potentially useful approach for the management of patients with MS.

Diffusion fMRI detects white-matter dysfunction in mice with acute optic neuritis

Optic neuritis is a frequent and early symptom of multiple sclerosis (MS). Conventional magnetic resonance (MR) techniques provide means to assess multiple MS-related pathologies, including axonal injury, demyelination, and inflammation. A method to directly and non-invasively probe white-matter function could further elucidate the interplay of underlying pathologies and functional impairments. Previously, we demonstrated a significant 27% activation-associated decrease in the apparent diffusion coefficient of water perpendicular to the axonal fibers (ADC⊥) in normal C57BL/6 mouse optic nerve with visual stimulation using diffusion fMRI. Here we apply this approach to explore the relationship between visual acuity, optic nerve pathology, and diffusion fMRI in the experimental autoimmune encephalomyelitis (EAE) mouse model of optic neuritis. Visual stimulation produced a significant 25% (vs. baseline) ADC⊥ decrease in sham EAE optic nerves, while only a 7% (vs. baseline) ADC⊥ decrease was seen in EAE mice with acute optic neuritis. The reduced activation-associated ADC⊥ response correlated with post-MRI immunohistochemistry determined pathologies (including inflammation, demyelination, and axonal injury). The negative correlation between activation-associated ADC⊥ response and visual acuity was also found when pooling EAE-affected and sham groups under our experimental criteria. Results suggest that reduction in diffusion fMRI directly reflects impaired axonal-activation in EAE mice with optic neuritis. Diffusion fMRI holds promise for directly gauging in vivo white-matter dysfunction or therapeutic responses in MS patients.

PET imaging in multiple sclerosis

Positron emission tomography (PET) is a non-invasive technique for quantitative imaging of biochemical and physiological processes in animals and humans. PET uses probes labeled with a radioactive isotope, called PET tracers, which can bind to or be converted by a specific biological target and thus can be applied to detect and monitor different aspects of diseases. The number of applications of PET imaging in multiple sclerosis is still limited. Clinical studies using PET are basically focused on monitoring changes in glucose metabolism and the presence of activated microglia/macrophages in sclerotic lesions. In preclinical studies, PET imaging of targets for other processes, like demyelination and remyelination, has been investigated and may soon be translated to clinical applications. Moreover, more PET tracers that could be relevant for MS are available now, but have not been studied in this context yet. In this review, we summarize the PET imaging studies performed in multiple sclerosis up to now. In addition, we will identify potential applications of PET imaging of processes or targets that are of interest to MS research, but have yet remained largely unexplored.

Multiple sclerosis: clinical features and MRI findings in Northern China

BACKGROUND

Reports in Asian populations suggest that ethnic and geographical differences may influence susceptibility to multiple sclerosis (MS) and its clinical behaviors. Here, we sought to retrospectively survey clinical characteristics and MRI data in Chinese subjects with MS.

METHODS

We conducted a retrospective analysis in 117 patients with MS. The patients were divided into subgroups with optic-spinal form of multiple sclerosis (OSMS; n = 42) and classical multiple sclerosis (CMS; n = 75). Clinical characteristics, MRI finding and expanded disability status scale (EDSS) score were compared between the two groups.

RESULTS

In 117 MS patients, 64.1% patients were classified as having CMS and 35.9% OSMS forms. White blood cell counts of OSMS patients were significantly higher than those of CMS patients (P <0.05). The longitudinal fusion lesions of spinal cord on MRI were statistically significant between groups (P <0.05). Spinal cord MRI showed that MS lesions were longer, and revealed spinal cord swelling in patients with CMS, but atrophy in patients with OSMS. The EDSS score at five years was significantly higher in patients with OSMS than in those with CMS (P <0.05). Relapse rates of patients with OSMS were also higher than those of patients with CMS (P <0.01) within one to three years.

CONCLUSIONS

OSMS accounts for a higher proportion of MS populations in Northern China than in Western countries. MRI showed a longitudinally extensive spinal cord lesion in patients with OSMS and spinal cord swelling at onset.

Pathological correlates of magnetic resonance imaging texture heterogeneity in multiple sclerosis

OBJECTIVE

To analyze the texture of T2-weighted magnetic resonance imaging (MRI) of postmortem multiple sclerosis (MS) brain, and to determine whether and how MRI texture correlates with tissue pathology.

METHODS

Ten brain samples from 3 subjects with MS were examined. Areas of complete, partial, or no loss of Luxol fast blue (myelin) and Bielschowsky (axons) staining were marked on histological images, and matched on corresponding MRI as lesions, diffusely abnormal white matter (DAWM), and normal-appearing white matter (NAWM). The number of CD45(+) cells (inflammation) was also counted. MRI texture was computed using polar Stockwell transform and compared to histology.

RESULTS

Thirty-four lesions, 17 DAWM regions, and 36 NAWM regions were identified. After mixed effects modeling, MRI texture heterogeneity was greater in lesions than in DAWM (p < 0.001) and NAWM (p < 0.001), and was greater in DAWM than in NAWM (p < 0.001); the number of CD45+ cells was greater in both lesions (p < 0.001) and DAWM (p = 0.005) than in NAWM. In MRI, a gradient of texture heterogeneity was detected in lesions, with gradual tapering toward perilesional NAWM. Moreover, besides univariate correlation with histological markers, texture heterogeneity correlated independently with normalized myelin density (p < 0.01) when random effects were considered. Within sample, MRI texture correlated with myelin and axonal density in 7 of 10 samples (p < 0.01).

INTERPRETATION

Texture analysis performed on routine clinical magnetic resonance images may be a potential measure of tissue integrity. Tissues with more severe myelin and axonal pathology are associated with greater texture heterogeneity.

Local mechanical properties of white matter structures in the human brain

The noninvasive measurement of the mechanical properties of brain tissue using magnetic resonance elastography (MRE) has emerged as a promising method for investigating neurological disorders. To date, brain MRE investigations have been limited to reporting global mechanical properties, though quantification of the stiffness of specific structures in the white matter architecture may be valuable in assessing the localized effects of disease. This paper reports the mechanical properties of the corpus callosum and corona radiata measured in healthy volunteers using MRE and atlas-based segmentation. Both structures were found to be significantly stiffer than overall white matter, with the corpus callosum exhibiting greater stiffness and less viscous damping than the corona radiata. Reliability of both local and global measures was assessed through repeated experiments, and the coefficient of variation for each measure was less than 10%. Mechanical properties within the corpus callosum and corona radiata demonstrated correlations with measures from diffusion tensor imaging pertaining to axonal microstructure.

Contrast-enhanced MR imaging in neuroimaging

MR imaging without and with gadolinium-based contrast agents (GBCAs) is an important imaging tool for defining normal anatomy and characteristics of lesions. GBCAs have been used in contrast-enhanced MR imaging in defining and characterizing lesions of the central nervous system for more than 20 years. The combination of unenhanced and GBCA-enhanced MR imaging is the clinical gold standard for the noninvasive detection and delineation of most intracranial and spinal lesions. MR imaging has a high predictive value that rules out neoplasm and most inflammatory and demyelinating processes of the central nervous system.

A perceptually relevant channelized joint observer (PCJO) for the detection-localization of parametric signals

Many numerical observers have been proposed in the framework of task-based approach for medical image quality assessment. However, the existing numerical observers are still limited in diagnostic tasks: the detection task has been largely studied, while the localization task concerning one signal has been little studied and the localization of multiple signals has not been studied yet. In addition, most existing numerical observers need a priori knowledge about all the parameters of the underdetection signals, while only a few of them need at least two signal parameters. In this paper, we propose a novel numerical observer called the perceptually relevant channelized joint observer (PCJO), which cannot only detect but also localize multiple signals with unknown amplitude, orientation, size and location. We validated the PCJO for predicting human observer task performance by conducting a clinically relevant free-response subjective experiment in which six radiologists (including two experts) had to detect and localize multiple sclerosis (MS) lesions on magnetic resonance (MR) images. By using the jackknife alternative free-response operating characteristic (JAFROC) as the figure of merit (FOM), the detection-localization task performance of the PCJO was evaluated and then compared to that of the radiologists and two other numerical observers--channelized hotelling observer (CHO) and Goossenss CHO for detecting asymmetrical signals with random orientations. Overall, the results show that the PCJO performance was closer to that of the experts than to that of the other radiologists. The JAFROC1 FOMs of the PCJO (around 0.75) are not significantly different from those of the two experts (0.7672 and 0.7110), while the JAFROC1 FOMs of the numerical observers mentioned above (always over 0.84) outperform those of the experts. This indicates that the PCJO is a promising method for predicting radiologists' performance in the joint detection-localization task.

Translocator protein 18 kDa (TSPO) expression in multiple sclerosis patients

Translocator protein (18 kDa) (TSPO) is a marker of inflammation in the brain. Positron emission tomography (PET) scans with ligands for this receptor show increased expression of TSPO in many neuropathologic conditions. However, expression of TSPO in the periphery and its possible correlation to central nervous system (CNS) inflammation has been largely unstudied. In this paper PBR28, a recently synthesized ligand for TSPO that is shown to have 80-fold higher specific binding than its predecessor PK11195, is used to quantify peripheral TSPO. Data presented in this study show that monocytes account for the majority of TSPO measured in peripheral blood mononuclear cells (PBMC), and that TSPO expression is stable over time in healthy individuals. Previous studies show that areas of increased PBR28 binding in the brains of multiple sclerosis (MS) patients correlate with active demylinating lesions found during magnetic resonance imaging (MRI). To measure peripheral TSPO expression in an inflammatory disease of the CNS, PBR28 is used in an in vitro radioligand binding assay to measure the amount of TSPO in the PBMC of MS and healthy donor cohorts. Surprisingly, MS patients are found to have a significantly lower amount of peripheral TSPO than healthy donors. We suggest that TSPO protein expression is a potential peripheral biomarker of MS, more research is needed to determine if peripheral TSPO expression may also be altered in other neuroinflammatory conditions.

Longitudinal assessment of antisaccades in patients with multiple sclerosis

We have previously demonstrated that assessment of antisaccades (AS) provides not only measures of motor function in multiple sclerosis (MS), but measures of cognitive control processes in particular, attention and working memory. This study sought to demonstrate the potential for AS measures to sensitively reflect change in functional status in MS. Twenty-four patients with relapsing-remitting MS and 12 age-matched controls were evaluated longitudinally using an AS saccade task. Compared to control subjects, a number of saccade parameters changed significantly over a two year period for MS patients. These included saccade error rates, latencies, and accuracy measures. Further, for MS patients, correlations were retained between OM measures and scores on the PASAT, which is considered the reference task for the cognitive evaluation of MS patients. Notably, EDSS scores for these patients did not change significantly over this period. These results demonstrate that OM measures may reflect disease evolution in MS, in the absence of clinically evident changes as measured using conventional techniques. With replication, these markers could ultimately be developed into a cost-effective, non-invasive, and well tolerated assessment tool to assist in confirming progression early in the disease process, and in measuring and predicting response to therapy.

Progressive multifocal leukoencephalopathy: a review of the neuroimaging features and differential diagnosis

Progressive multifocal leukoencephalopathy (PML) is an uncommon and often fatal demyelinating disease of human central nervous system, which is caused by reactivation of the polyomavirus JC (JCV). PML generally occurs in patients with profound immunosuppression such as AIDS patients. Recently, a number of PML cases have been associated with administration of natalizumab for treatment of multiple sclerosis (MS) patients. Diagnosis and management of PML became a major concern after its occurrence in multiple sclerosis patients treated with natalizumab. Diagnosis of PML usually rests on neuroimaging in the appropriate clinical context and is further confirmed by cerebrospinal fluid polymerase chain reaction (PCR) for JCV DNA. Treatment with antiretroviral therapies in HIV-seropositive patients or discontinuing natalizumab in MS patients with PML may lead to the development of immune reconstitution inflammatory syndrome (IRIS) which presents with deterioration of the previous symptoms and may lead to death. In patients under treatment with monoclonal antibodies in routine practice, or new ones in ongoing clinical trials, differentiating PML from new MS lesions on brain MRI is critical for both the neurologists and neuroradiologists. In this review, we discuss the clinical features, neuroimaging manifestations of PML, IRIS and neuroimaging clues to differentiate new MS lesions from PML. In addition, various neuroimaging features of PML on the non-conventional MR techniques such as diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and MR spectroscopy (MRS) are discussed.

Superparamagnetic iron oxide nanoparticles: promises for diagnosis and treatment of multiple sclerosis

Smart superparamagnetic iron oxide nanoparticles (SPIONs) are the most promising candidate for theragnosis (i.e., diagnosis and treatment) of multiple sclerosis. A deep understanding of the dynamics of the in vivo neuropathology of multiple sclerosis can be achieved by improving the efficiency of various medical techniques (e.g., positron emission tomography and magnetic resonance imaging) using multimodal SPIONs. In this Review, recent advances and challenges in the development of smart SPIONs for theragnostic applications are comprehensively described. In addition, critical outlines of emerging developments are provided from the points of view of both clinicians and nanotechnologists.

Neurofilament proteins as body fluid biomarkers of neurodegeneration in multiple sclerosis

Biomarkers of axonal degeneration have the potential to improve our capacity to predict and monitor neurological outcome in multiple sclerosis (MS) patients. Neurofilament proteins, one of the major proteins expressed within neurons and axons, have been detected in cerebrospinal fluid and blood samples from MS patients and are now being actively investigated for their utility as prognostic indicators of disease progression in MS. In this paper, we summarize the current literature on neurofilament structure, assembly, and degeneration and discuss their potential utility as biomarkers for monitoring neurological decline in MS. We also discuss the need to further develop sensitive methods for assaying neurofilaments in blood to improve clinical applicability.