Low Lesion Load Research Articles

Optical Coherence Tomography Advanced Parameters in Patients With Multiple Sclerosis: Ophthalmological and Neurological Assessments

PurposeTo evaluate ophthalmological, neurological, radiological, and laboratory data in patients with multiple sclerosis (MS) and to identify new ophthalmological factors that could be helpful as biomarkers of the disease, potentially leading to an earlier prediction of disease course and disability progression. DesignRetrospective, cross-sectional-study. MethodsBest-corrected visual acuity (BCVA), ophthalmological biomicroscopy of the anterior segment and fundus, structural optical coherence tomography (OCT) with retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC), and OCT Angiography (OCTA) with vascular density (VD) were performed. The following clinical and neuro-radiological features were assessed: MS phenotype, disease duration, clinical severity, type of treatment, and T2-weighted lesion load plus T1-weighted Gd+-enhancing lesion number on the last brain and spinal cord MRI. ResultsOne hundred and six patients (212 eyes) were analyzed. Sixty-six of them (62.2 %) had MS and 40 (37.8%) were matched healthy controls (HCs). patients with MS showed lower RNFL, GCC, and VD in the radial peripapillary capillary plexus than controls in both eyes (p<0.05). By Performing a logistic regression with a distinct MS outcome for both eyes, we were able to demonstrate that the value that was most predictive of MS was the average GCC thickness (p=0.009). Regression analysis demonstrated that patients with a higher T2-weighted lesions showed a lower RNFL thickness value and reduced GCC and VD values than those with a low lesion load (p<0.01 and p<0.05, respectively). Similarly, relapsing MS patients showed lower RNFL values (p<0.05). ConclusionsSeveral OCT- and OCTA-optic nerve parameters could be useful prognostic biomarkers for the MS disease course in clinical practice. However, it is necessary to do additional research with larger sample sizes in order to validate these findings.

Association of Circumscribed Subcortical Gray and White Matter Lesions With Apraxic Deficits in Patients With Left Hemisphere Stroke.

Apraxia is commonly attributed to left hemisphere (LH) lesions of the cortical fronto-temporo-parietal praxis networks or white matter lesions causing disconnections between cortical nodes. By contrast, the contribution of lesions to the subcortical gray matter, that is, basal ganglia or thalamus, to apraxic deficits remains controversial. Here, we investigate whether damage to these subcortical gray matter structures (i.e., caudate nucleus, putamen, globus pallidus, and thalamus) or the adjacent white matter tracts was associated with apraxic deficits. We identified patients with distinct subcortical lesions with and without apraxia from a large retrospective sample of subacute LH ischemic stroke patients (n = 194). To test which subcortical structures (caudate nucleus, putamen, globus pallidus, thalamus, and adjacent white matter tracts), when lesioned, contributed to apraxic deficits, we statistically compared the proportion of lesioned voxels within subcortical gray and white matter structures between the apraxic and nonapraxic patients. Of the 194 stroke patients screened, 39 (median age = 65 years, range 30-82 years; median time poststroke at the apraxia assessment = 7 days, range 1-44 days) had lesions confined to subcortical regions (gray and white matter). Eleven patients showed apraxic deficits when imitating gestures or pantomiming object use. Region-wise statistical lesion comparison (controlled for lesion size) revealed a more significant proportion of damage ('lesion load') in the caudate nucleus in apraxic stroke patients (mean difference = 6.9%, 95% CI 0.4-13.3, p = 0.038, η p 2 = 0.11). By contrast, apraxic patients had lower lesion load in the globus pallidus (mean difference = 9.9%, 95% CI 0.1-19.8, p = 0.048, η p 2 = 0.10), whereas the lesion load in other subcortical structures (putamen, thalamus, and adjacent white matter tracts) did not differ significantly between the apraxic and nonapraxic patients. These findings provide new insights into the subcortical anatomy of apraxia after LH stroke, suggesting a specific contribution of caudate nucleus lesions to apraxic deficits.

The influence of white matter lesions on the electric field in transcranial electric stimulation

BackgroundTranscranial direct current stimulation (tDCS) is a promising tool to enhance therapeutic efforts, for instance, after a stroke. The achieved stimulation effects exhibit high inter-subject variability, primarily driven by perturbations of the induced electric field (EF). Differences are further elevated in the aging brain due to anatomical changes such as atrophy or lesions. Informing tDCS protocols by computer-based, individualized EF simulations is a suggested measure to mitigate this variability. ObjectiveWhile brain anatomy in general and specifically atrophy as well as stroke lesions are deemed influential on the EF in simulation studies, the influence of the uncertainty in the change of the electrical properties of the white matter due to white matter lesions (WMLs) has not been quantified yet. MethodsA group simulation study with 88 subjects assigned into four groups of increasing lesion load was conducted. Due to the lack of information about the electrical conductivity of WMLs, an uncertainty analysis was employed to quantify the variability in the simulation when choosing an arbitrary conductivity value for the lesioned tissue. ResultsThe contribution of WMLs to the EF variance was on average only one tenth to one thousandth of the contribution of the other modeled tissues. While the contribution of the WMLs significantly increased (p≪.01) in subjects exhibiting a high lesion load compared to low lesion load subjects, typically by a factor of 10 and above, the total variance of the EF didnot change with the lesion load. ConclusionOur results suggest that WMLs do not perturb the EF globally and can thus be omitted when modeling subjects with low to medium lesion load. However, for high lesion load subjects, the omission of WMLs may yield less robust local EF estimations in the vicinity of the lesioned tissue. Our results contribute to the efforts of accurate modeling of tDCS for treatment planning.

Advanced methodology for multiple sclerosis lesion exploring: Towards a computer aided diagnosis system

Abstract The exploration and diagnosis of severe neuropathologies is one of the essential tasks that could be reinforced and aided by advanced techniques in medical imagery. Cortex lesions and tumors are examples of pathologies where Magnetic Resonance Imagery modalities are the essential tools for exploration and tracking. Our main added value in this research field was focused on Multiple Sclerosis lesions exploration aiming to offer a clinical computer aided tool capable of helping clinicians during their daily explorations. An automatic method for brain segmentation and Multiple Sclerosis lesion exploration was in fact attentively conceived and tested. Firstly, the brain segmentation was performed using an atlas based Gaussian mixture model, followed by the calculation of a probabilistic lesion map on which an empirical threshold, characterized by a set of constraints, was applied together with a lesion refinement algorithm in order to create a binary lesion mask. The approach was applied to four clinical databases. Compared to various existing methods, the approach showed its efficiency in differentiating normal brain tissues with averages of 0.78 ± 0.04 , 0.85 ± 0.04 and 0.89 ± 0.04 for Dice, sensitivity and specificity, respectively. Besides, it proved the possibility of accurately identifying lesions even in noisy images, and low lesion load, giving averages of 0.75 ± 0.04 , 0.90 ± 0.08 and 0.75 ± 0 . 12 for the previous metrics, respectively. Furthermore, it is able to distinguish between the lesion center and the contiguous dirty white matter, which was carefully validated by clinicians. As a perspective, our approach could be extended to explore other neuropathologies such as Alzheimer’s or Parkinson’s diseases.

Partial volume-aware assessment of multiple sclerosis lesions.

White-matter lesion count and volume estimation are key to the diagnosis and monitoring of multiple sclerosis (MS). Automated MS lesion segmentation methods that have been proposed in the past 20 years reach their limits when applied to patients in early disease stages characterized by low lesion load and small lesions. We propose an algorithm to automatically assess MS lesion load (number and volume) while taking into account the mixing of healthy and lesional tissue in the image voxels due to partial volume effects. The proposed method works on 3D MPRAGE and 3D FLAIR images as obtained from current routine MS clinical protocols. The method was evaluated and compared with manual segmentation on a cohort of 39 early-stage MS patients with low disability, and showed higher Dice similarity coefficients (median DSC = 0.55) and higher detection rate (median DR = 61%) than two widely used methods (median DSC = 0.50, median DR < 45%) for automated MS lesion segmentation. We argue that this is due to the higher performance in segmentation of small lesions, which are inherently prone to partial volume effects.

Comparative study of RNFL,GCA (macular ganglionnar cells) OCT alteration and MRI lesions in a population of multiple sclerosis patients (MS) with a recent history (less than 4 years)

AbstractPurpose Spectral domain OCT allows measuring peripapillary retinal nerve fiber layer and macular ganglionar cells and inner plexiform layers (GCA). Previous studies established alterations of these layers in ON.The aim of this study was to evaluate eyes without ON‐ and to compare GCA and RNFL lesions.Methods We studied 48 eyes from 24 patients with authentified MS.On 48 eyes,8 eyes had clinically proven optic neuritis in previous years. Patients with ON in the last 6 months, or with elevated intra ocular pressure,high myopia,or macular pathology were excluded.All had clinical exam and OCT measurement (Zeiss Cirrus).Results The 8 eyes with history of ON showed clear thinning of both GCA and RNFL (p&lt;&lt;0,05 with both).With the 40 other eyes,11 showed abnormalities with OCT,29 had normal OCT.In those 11 eyes,both OCT measurements ( RNFL and GCA) showed a thickness loss, but higher with GCA with a better statistical correlation ( p= 0,037 versus p=0,062).Futhermore, more dials were involved in GCA versus RNFL in the thinning topography for 7 eyes out this 11 eyes group.We ran a screening for IRM abnormalities for all 24 patients, categorizing them in three groups (high, medium and low lesion load) without any clear association to the OCT alterations.Conclusion This study confirmed acquired ganglion cells alterations,remaining after ON,in patients who had a complete visual function recovery.It showed GCA or RNFL abnormalities in one quarter of patient without ON history.GCA seems to have greater sensitivity than RNFL ,but further studies on biggest population are necessary to precise specificity an sensitivity of these two measures.

Patients’ Stratification and Correlation of Brain Magnetic Resonance Imaging Parameters with Disability Progression in Multiple Sclerosis

Aims: The objective was to correlate the change in the lesion load (LL) and brain atrophy in patients with multiple sclerosis (MS) with progression of clinical disability, represented by the Expanded Disability Status Scale (EDSS), and to test if stratification of patients according to magnetic resonance imaging (MRI) criteria can increase the predictive ability of MRI for MS clinical development. Methods: 181 patients with clinically definite relapsing-remitting MS underwent MRI for a period of up to 5 years. Grouping of patients according to the LL value at the study entry revealed a substantial increase in the Spearman rank correlation coefficient R. Results: For the low LL cohort of patients, we found a statistically significant correlation (R up to –0.71 with p < 0.01) of a later increase in the EDSS score (years 4 and 5) with increased brain atrophy in the first 2 years. For the high LL group, we found a statistically significant correlation (R up to 0.72 with p < 0.01) of a later increase in the EDSS score (years 4 and 5) with an increase in the LL value in the first year. Conclusions: We conclude that stratification of patients according to the MRI criterion (LL) can increase the predictive ability of MRI.

The importance of long-term data in multiple sclerosis

■ Abstract Natural history studies provide important information on the prognosis of multiple sclerosis and on risk factors for long-term outcome and thus help orientate treatment decisions and design clinical trials. Before the introduction of disease-modifying treatment, large longitudinal natural history studies described the typical clinical course of multiple sclerosis and identified landmark events in disease progression, for example that 50 % of patients with relapsing-remitting multiple sclerosis are unable to walk unaided 15 years after disease onset. A large observational natural history study performed in Barcelona following outcome after the first presentation with a clinically isolated syndrome revealed that patients presenting initially with optic neuritis were less likely to progress to clinically definite multiple sclerosis than other patients. This finding could be explained by a lower lesion load on cranial MRI. Initial lesion load also appeared to be an important determinant of future disability. These and other similar data suggest that the development of lesions early in the disease process has an important influence on long-term disability. Since the advent of disease-modifying treatments in multiple sclerosis, this natural history can also help define criteria for determining treatment failure. An analysis of a cohort of patients treated with β-interferons revealed that progression of EDSS disability scores during the first two years of treatment could predict treatment failure at six years (three points worsening in EDSS score since treatment initiation) with an accuracy of 92 %. Early progression of EDSS scores was itself associated with early accumulation of lesion load visible on MRI. Rate of accumulation of lesion load after first symptom presentation may thus be a useful marker of poor prognosis that could be considered an indicator of the need for intensive treatment. Initial long-term outcome data obtained with immunomodulatory treatments is consistent with the notion that these treatments improve the long-term prognosis. If this is confirmed, then a first step towards the goal of limiting irreversible disability in patients with multiple sclerosis will have been made.

Unified Approach for Multiple Sclerosis Lesion Segmentation on Brain MRI

The presence of large number of false lesion classification on segmented brain MR images is a major problem in the accurate determination of lesion volumes in multiple sclerosis (MS) brains. In order to minimize the false lesion classifications, a strategy that combines parametric and nonparametric techniques is developed and implemented. This approach uses the information from the proton density (PD)- and T2-weighted and fluid attenuation inversion recovery (FLAIR) images. This strategy involves CSF and lesion classification using the Parzen window classifier. Image processing, morphological operations, and ratio maps of PD- and T2-weighted images are used for minimizing false positives. Contextual information is exploited for minimizing the false negative lesion classifications using hidden Markov random field-expectation maximization (HMRF-EM) algorithm. Lesions are delineated using fuzzy connectivity. The performance of this algorithm is quantitatively evaluated on 23 MS patients. Similarity index, percentages of over, under, and correct estimations of lesions are computed by spatially comparing the results of present procedure with expert manual segmentation. The automated processing scheme detected 80% of the manually segmented lesions in the case of low lesion load and 93% of the lesions in those cases with high lesion load.

Multiple sclerosis: a study of chemokine receptors and regulatory T cells in relation to MRI variables.

Magnetic resonance imaging (MRI) remains the most valuable tool for monitoring disease activity and progression in patients with multiple sclerosis (MS), a chronic demyelinating disease of the central nervous system (CNS) with presumably autoimmune etiology. Chemokine receptors have been implicated in MS as key molecules directing inflammatory cells into the CNS. Regulatory (CD4+CD25+) T cells (Tr cells) are important in suppressing autoimmunity, and their absolute or functional deficit could be expected in MS. In the present study, venous blood was obtained from MS patients concurrent with MRI examination of the brain, and expression of chemokine receptors CCR1, CCR2, CCR5, CXCR3 and CXCR4 by CD4 T cells and monocytes, proportions of Tr cells, as well as expression of CD45RO, CD95, CTLA-4, HLA-DR and interleukin (IL)-10 by Tr cells and non-Tr (CD25-) CD4 T cells was analyzed by flow cytometry. Surface expression of CXCR3 by CD4 T cells was downregulated in the group of patients with high lesion load (LL) on T2-weighted images and gadolinium (Gd)-enhancing lesions on T1-weighted images, compared to the group with high LL and no Gd-enhancing lesions, and to the group with low LL, suggesting internalization of CXCR3 due to the release of its chemokine ligand (IP-10/CXCL10) from active MS lesions. Proportions of Tr cells amongst all CD4 T cells, and expression of IL-10 by Tr cells were increased in the patients with high LL and Gd-enhancing lesions. These results suggest that there is correlation between MRI parameters, chemokine receptor expression and the status of circulating Tr cells in MS, but further studies need to discriminate between pathogenetically relevant and bystander phenomena.