Modeling MR Imaging Enhancing-Lesion Volumes in Multiple Sclerosis: Application in Clinical Trials

Elskamp, I.J. van den; Knol, D.L.; Uitdehaag, Bernard M. J.; Barkhof, Frederik

doi:10.3174/ajnr.a2691

Cited by 3 publications

(3 citation statements)

References 18 publications

(15 reference statements)

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“…Given the volumetric nature of lesion load, we used a cube root transformation for linearity and to reduce variance (Woo et al, 1999; van den Elskamp et al, 2011). Naming ability was linearly related to lesion loads, so transformations were not applied for those regressions.…”

Section: Methodsmentioning

confidence: 99%

Predicting speech fluency and naming abilities in aphasic patients

Wang

Marchina

Norton

et al. 2013

Front. Hum. Neurosci.

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There is a need to identify biomarkers that predict degree of chronic speech fluency/language impairment and potential for improvement after stroke. We previously showed that the Arcuate Fasciculus lesion load (AF-LL), a combined variable of lesion site and size, predicted speech fluency in patients with chronic aphasia. In the current study, we compared lesion loads of such a structural map (i.e., AF-LL) with those of a functional map [i.e., the functional gray matter lesion load (fGM-LL)] in their ability to predict speech fluency and naming performance in a large group of patients. The fGM map was constructed from functional brain images acquired during an overt speaking task in a group of healthy elderly controls. The AF map was reconstructed from high-resolution diffusion tensor images also from a group of healthy elderly controls. In addition to these two canonical maps, a combined AF-fGM map was derived from summing fGM and AF maps. Each canonical map was overlaid with individual lesion masks of 50 chronic aphasic patients with varying degrees of impairment in speech production and fluency to calculate a functional and structural lesion load value for each patient, and to regress these values with measures of speech fluency and naming. We found that both AF-LL and fGM-LL independently predicted speech fluency and naming ability; however, AF lesion load explained most of the variance for both measures. The combined AF-fGM lesion load did not have a higher predictability than either AF-LL or fGM-LL alone. Clustering and classification methods confirmed that AF lesion load was best at stratifying patients into severe and non-severe outcome groups with 96% accuracy for speech fluency and 90% accuracy for naming. An AF-LL of greater than 4 cc was the critical threshold that determined poor fluency and naming outcomes, and constitutes the severe outcome group. Thus, surrogate markers of impairments have the potential to predict outcomes and can be used as a stratifier in experimental studies.

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Section: Methodsmentioning

confidence: 99%

Predicting speech fluency and naming abilities in aphasic patients

Wang

Marchina

Norton

et al. 2013

Front. Hum. Neurosci.

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“…The development of disease-modifying drugs (DMDs) for multiple sclerosis (MS) has been based on their observed effects on clinical outcomes, including the rate of relapse and the accumulation of permanent disability [ 1 , 2 ]. Aside from these clinical parameters, changes in brain lesion burden have been commonly used to monitor the in vivo effects of DMDs based on conventional MRI, which serves as a potential surrogate marker in MS trials.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Disease-Modifying Drugs on Brain Atrophy in Relapsing-Remitting Multiple Sclerosis: A Meta-Analysis

et al. 2016

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BackgroundThe quantification of brain atrophy in relapsing-remitting multiple sclerosis (RRMS) may serve as a marker of disease progression and treatment response. We compared the association between first-line (FL) or second-line (SL) disease-modifying drugs (DMDs) and brain volume changes over time in RRMS.Materials and MethodsWe reviewed clinical trials in RRMS between January 1, 1995 and June 1, 2014 that assessed the effect of DMDs and reported data on brain atrophy in Medline, Embase, the Cochrane database and meeting abstracts. First, we designed a meta-analysis to directly compare the percentage brain volume change (PBVC) between FLDMDs and SLDMDs at 24 months. Second, we conducted an observational and longitudinal linear regression analysis of a 48-month follow-up period. Sensitivity analyses considering PBVC between 12 and 48 months were also performed.ResultsAmong the 272 studies identified, 117 were analyzed and 35 (18,140 patients) were included in the analysis. Based on the meta-analysis, atrophy was greater for the use of an FLDMD than that of an SLDMD at 24 months (primary endpoint mean difference, -0.86; 95% confidence interval: -1.57–-0.15; P = 0.02). Based on the linear regression analysis, the annual PBVC significantly differed between SLDMDs and placebo (-0.27%/y and -0.50%/y, respectively, P = 0.046) but not between FLDMDs (-0.33%/y) and placebo (P = 0.11) or between FLDMDs and SLDMDs (P = 0.49). Based on sensitivity analysis, the annual PBVC was reduced for SLDMDs compared with placebo (-0.14%/y and -0.56%/y, respectively, P<0.001) and FLDMDs (-0.46%/y, P<0.005), but no difference was detected between FLDMDs and placebo (P = 0.12).ConclusionsSLDMDs were associated with reduced PBVC slope over time in RRMS, regardless of the period considered. These results provide new insights into the mechanisms underlying atrophy progression in RRMS.

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“…Since the output of the LL equation is a volumetric measurement, the cube root of left AF-LL was used for all correlations and regressions. 35,36 In addition, we correlated lesion/ROI overlap ratios for left hemisphere ROIs with CC ROI FA values to determine whether the degree of left hemisphere lesion/ROI overlap could predict CC white matter integrity. Two-tailed independent t tests assuming unequal variance were run between patient and control groups comparing FA values for each right hemisphere and CC ROI that significantly predicted both speech fluency measures.…”

Section: Statistical Analyses All Statistical Analyses Were Done In mentioning

confidence: 99%

Right hemisphere structures predict poststroke speech fluency

et al. 2016

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Objective: We sought to determine via a cross-sectional study the contribution of (1) the right hemisphere's speech-relevant white matter regions and (2) interhemispheric connectivity to speech fluency in the chronic phase of left hemisphere stroke with aphasia.Methods: Fractional anisotropy (FA) of white matter regions underlying the right middle temporal gyrus (MTG), precentral gyrus (PreCG), pars opercularis (IFGop) and triangularis (IFGtri) of the inferior frontal gyrus, and the corpus callosum (CC) was correlated with speech fluency measures. A region within the superior parietal lobule (SPL) was examined as a control. FA values of regions that significantly predicted speech measures were compared with FA values from healthy ageand sex-matched controls.

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Modeling MR Imaging Enhancing-Lesion Volumes in Multiple Sclerosis: Application in Clinical Trials

Cited by 3 publications

References 18 publications

Predicting speech fluency and naming abilities in aphasic patients

Predicting speech fluency and naming abilities in aphasic patients

The Effect of Disease-Modifying Drugs on Brain Atrophy in Relapsing-Remitting Multiple Sclerosis: A Meta-Analysis

Right hemisphere structures predict poststroke speech fluency

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