Dataset Information

New rapid, accurate T₂ quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients.

ABSTRACT:

Introduction

Quantitative T₂ mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve (EMC) algorithm to identify T₂ changes in normal-appearing brain regions of subjects with RRMS (N = 27) compared to age-matched controls (N = 38).

Methods

The EMC algorithm uses Bloch simulations to model T₂ decay curves in multi-spin-echo MRI sequences, independent of scanner, and scan-settings. T₂ values were extracted from normal-appearing white and gray matter brain regions using both expert manual regions-of-interest and user-independent FreeSurfer segmentation.

Results

Compared to conventional exponential T₂ modeling, EMC fitting provided more accurate estimations of T₂ with less variance across scans, MRI systems, and healthy individuals. Thalamic T₂ was increased 8.5% in RRMS subjects (p < 0.001) and could be used to discriminate RRMS from healthy controls well (AUC = 0.913). Manual segmentation detected both statistically significant increases (corpus callosum & temporal stem) and decreases (posterior limb internal capsule) in T₂ associated with RRMS diagnosis (all p < 0.05). In healthy controls, we also observed statistically significant T₂ differences for different white and gray matter structures.

Conclusions

The EMC algorithm precisely characterizes T₂ values, and is able to detect subtle T₂ changes in normal-appearing brain regions of RRMS patients. These presumably capture both axon and myelin changes from inflammation and neurodegeneration. Further, T₂ variations between different brain regions of healthy controls may correlate with distinct nervous tissue environments that differ from one another at a mesoscopic length-scale.

SUBMITTER: Shepherd TM

PROVIDER: S-EPMC5318543 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

New rapid, accurate T<sub>2</sub> quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients.

Shepherd Timothy M TM Kirov Ivan I II Charlson Erik E Bruno Mary M Babb James J Sodickson Daniel K DK Ben-Eliezer Noam N

NeuroImage. Clinical 20170203

<h4>Introduction</h4>Quantitative T<sub>2</sub> mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve (EMC) algorithm to identify T<sub>2</sub> changes in normal-appearing brain regions of subjects with RRMS (N = 27) compared to age-matched controls (N = 38).<h4>Methods</h4>The EMC algorithm uses Bloch simulations to model T<sub>2</sub> decay curves in multi-spin-echo MRI sequences ...[more]

PMID: 28239545

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Project description:One of our new major finding among the genes that contributes to MS susceptibility is ICSBP1. The so called disease modifying therapies like interferon-beta (IFN-β), possibly acting on the peripheral T-cells, reduce the disease activity and the clinical progression, with a MRI-detectable effect in preventing lesion burden and cerebral atrophy development in RR-MS. It suggests a critical role of peripheral blood mononuclear cells (PBMCs) immune response and modulation in developing inflammation in the brain. We tested the hypothesis that the genetic effect of the susceptible allele ICSBP1 can impact the gene expression profile of molecules belonging to the interferon pathway. We therefore interrogated the PBMC for changes in gene expression profile. We correlate those changes with the minor allele frequency for ICSBP1, performing independent quantitative trait analysis for each treatment category. Expression Quantitative Trait Loci Association with a p value < 0.05 have been used in follow up analysis. The regression coefficient of the Quantitative trait association represents the degree of correlation between the gene expression for each interrogated target gene and the minor allele frequency of the SNP for our gene of interest. This coefficient has been used as input in the subsequent Gene Set Enrichment Analysis performed in a pre-ranked approach. The resulting GSEA-SNP method rests on the assumption that SNPs underlying a disease phenotype might affect genes constituting a signaling pathway or genes with a common regulation. Therefore, GSEA-SNP can facilitate the identification of pathways or of underlying biological mechanisms. We used microarrays to capture gene expression profile of untreated subjects and of subjects under disease modyfing treatment (Interferon Beta and Glatiramer Acetate), in order to correlate gene expression and genotype data and in order to identify sets of genes specifically regulated in the different treatment categories.

Project description:ObjectiveTo characterize effects of alemtuzumab treatment on measures of disability improvement in patients with relapsing-remitting multiple sclerosis (RRMS) with inadequate response (≥1 relapse) to prior therapy.MethodsComparison of Alemtuzumab and Rebif Efficacy in Multiple Sclerosis (CARE-MS) II, a 2-year randomized, rater-blinded, active-controlled, head-to-head, phase 3 trial, compared efficacy and safety of alemtuzumab 12 mg with subcutaneous interferon-β-1a (SC IFN-β-1a) 44 μg in patients with RRMS. Prespecified and post hoc disability outcomes based on Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Sloan low-contrast letter acuity (SLCLA) are reported, focusing on improvement of preexisting disability in addition to slowing of disability accumulation.ResultsAlemtuzumab-treated patients were more likely than SC IFN-β-1a-treated patients to show improvement in EDSS scores (p < 0.0001) on all 7 functional systems. Significantly more alemtuzumab patients demonstrated 6-month confirmed disability improvement. The likelihood of improved vs stable/worsening MSFC scores was greater with alemtuzumab than SC IFN-β-1a (p = 0.0300); improvement in MSFC scores with alemtuzumab was primarily driven by the upper limb coordination and dexterity domain. Alemtuzumab-treated patients had more favorable changes from baseline in SLCLA (2.5% contrast) scores (p = 0.0014) and MSFC + SLCLA composite scores (p = 0.0097) than SC IFN-β-1a-treated patients.ConclusionsIn patients with RRMS and inadequate response to prior disease-modifying therapies, alemtuzumab provides greater benefits than SC IFN-β-1a across several disability outcomes, reflecting improvement of preexisting disabilities.Classification of evidenceThis study provides Class I evidence (based on rater blinding and a balance in baseline characteristics between arms) that alemtuzumab modifies disability measures favorably compared with SC IFN-β-1a.

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Dataset Information

New rapid, accurate T₂ quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients.

Introduction

Methods

Results

Conclusions

Publications

New rapid, accurate T<sub>2</sub> quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

New rapid, accurate T2 quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients.

Introduction

Methods

Results

Conclusions

Publications

New rapid, accurate T<sub>2</sub> quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

New rapid, accurate T₂ quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients.