Neocortical Atrophy, Third Ventricular Width, and Cognitive Dysfunction in Multiple Sclerosis

Department of Neurology, School of Medicine, State University of New York at Buffalo, 100 High Street, Buffalo, NY 14203, USA.
JAMA Neurology (Impact Factor: 7.42). 10/2006; 63(9):1301-6. DOI: 10.1001/archneur.63.9.1301
Source: PubMed


Cognitive dysfunction is common in multiple sclerosis (MS). Correlations are reported between atrophy and neuropsychological test results.
To determine if neocortical volume would supplant or supplement third ventricular width and other magnetic resonance imaging measures when predicting neuropsychological impairment.
Cross-sectional study.
University MS clinic.
Seventy-seven patients with relapsing-remitting MS, 42 patients with secondary progressive MS, and 27 healthy control subjects.
Brain atrophy and lesion burden measures were obtained in all patients. A subset of 82 patients and all controls underwent neuropsychological testing.
Patients with secondary progressive MS had more atrophy than patients with relapsing-remitting MS and controls. Neocortical volume was significantly correlated with all neuropsychological measures, with r values ranging from 0.29 to 0.58. Third ventricular width was retained in most stepwise regression analyses predicting cognitive impairment in patients with MS and distinguishing secondary progressive from relapsing-remitting courses of MS.
We confirm an association between neocortical volume and multiple cognitive domains in MS, although neocortical volume did not explain significantly more variance than other magnetic resonance imaging measures. Of the magnetic resonance imaging variables studied, third ventricular width was retained in most regression models.

9 Reads
  • Source
    • "In this context, an association between PASAT performance and MRI outcomes was shown in cross-sectional studies in patients with relapseremitting multiple sclerosis (RRMS) [15] [16] [17] [18] [19]; however this relationship has not been reported consistently in CIS patients [20] [21]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Repeated administration of Paced Auditory Serial Addition Test (PASAT) results in a considerable learning effect in short- or long-term follow-up studies. However, the relationship between PASAT learning and changes in magnetic resonance imaging (MRI) parameters is yet to be investigated. The aim of this study is to determine if change in brain MRI metrics predicts evolution of PASAT in high functioning clinically isolated syndrome (CIS) patients on disease-modifying treatment (DMT). This prospective 48-month observational study examined 128 CIS patients treated with 30μg of intramuscular interferon beta-1a once a week. The correlation between PASAT and MRI measures was assessed at baseline, at 6months and then annually over the 48-month follow up. Linear mixed model analysis adjusted for age, gender, education and DMT was used to model the temporal association between MRI measures and PASAT performance. MRI revealed 2.5% gray matter (GM) volume loss and 4.3 point increase in PASAT score over 48months. MS patients evidenced significantly greater PASAT score absolute change, had lower loss of GM volume (p=.008) but not significant change in cortical (p=.061), white matter (p=.086) or whole brain volumes (p=.879). The present study reveals a significant relationship between higher PASAT learning effect and less GM atrophy in CIS patients on DMT. These findings suggest that change in PASAT associated more with GM than WM pathology, and that treatment strategies oriented toward GM volume preservation may play an important role in prevention of cognitive deterioration in CIS patients. Copyright © 2014 Elsevier B.V. All rights reserved.
    Journal of the Neurological Sciences 10/2014; 347(1-2):229-234. DOI:10.1016/j.jns.2014.10.002 · 2.47 Impact Factor
  • Source
    • "MP-RAGE images were realigned to the anterior commissure-posterior commissure line and were resampled to 0.5- mm 3 voxels to improve the precision of the TVW measurement. Similar to published procedures (Benedict, Bruce, et al., 2006), we identified the axial slice where the third ventricle was most visible, manually marked the left and right boundaries of the ventricle on this slice, and calculated the distance in millimeters between these points to determine TVW. We have previously established high intra-and interrater reliability using this procedure (all rs Ͼ .96). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Objective: Executive deficits and slow processing speed (PS) are observed in persons with multiple sclerosis (MS). The question of whether executive deficits can be explained by slow PS was examined with neuropsychological measures and a neurostructural measure (brain atrophy). Method: Fifty MS patients were compared with 28 healthy controls (HCs) on tasks of executive functioning with and without a PS element (e.g., Trail Making Test and Wisconsin Card Sorting Test). Results: The MS group performed worse than HCs on speeded tasks of executive function. However, after controlling for speed, group differences on executive tasks disappeared. There were also no group differences on executive tasks with no PS demands. The effect of disease progression on executive task performance was assessed in the MS group. Higher atrophy in MS participants was associated with greater deficits on speeded executive tasks, but this association disappeared when controlling for PS. There was no association between atrophy and performance on nonspeeded executive tasks. Conclusions: Our results support the notion that executive deficits in MS may be explained by slow PS. These findings highlight the role of slowed PS as a primary impairment underlying other cognitive functions. Disentangling the relative contribution of PS to executive function is an important step toward the development of appropriate rehabilitation strategies for persons with MS.
    Rehabilitation Psychology 08/2014; 59(4). DOI:10.1037/a0037517 · 1.91 Impact Factor
  • Source
    • "[10] "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background Prevalence rates of cognitive impairment (CI) in multiple sclerosis (MS) vary between 40% and 80%. Differences in classification criteria for CI may explain this variance. Objective This study reviewed and compared classification criteria for CI in patients with early and late MS. Methods The paper consists of two parts: a systematic review of published classification criteria and the presentation of new data. Criteria were reviewed in respect to percentage of abnormal parameters and cut-offs concerning standard deviations. Thereafter, criteria were applied to cognitive data of 25 patients with early MS (duration ≤ 2y), 52 matched patients with late MS (≥ 12y), and 75 matched controls. The test battery assessed alertness, divided attention, mental flexibility, verbal and visual learning, memory, and visuospatial abilities. Results Seventy classification criteria were revealed and grouped into 20 distinct approaches that can be subdivided into three basic classification strategies. Most commonly, CI was defined as performing 1.5 SD or 2 SD below the normative mean in 18-30% of test parameters (n = 42). Other criteria utilized cognitive domains (n = 6), composite indices (n = 8), or combinations of cut-offs and strategies. The stringency of the criteria was correlated with the prevalence rate of CI (r = -.43) and disease duration (r = .48). In the new data, a substantial effect of classification criteria was found with a prevalence rate ranging from 0 to 68% in early and 4 to 81% in late MS. Increased rates of CI in patients vs. controls were found following 18 out of 20 criteria in the sample of late MS. In early MS, an increased rate of CI was only found following a liberal 1.5 SD cut-off criterion. Inter-rater reliability between all criteria was moderate. However, between criteria of comparable stringency the inter-rater reliability was found to be strong. Conclusion Classification based on different published criteria is not fully comparable and criteria need to be better homogenized.
    Journal of the Neurological Sciences 08/2014; 343(1-2). DOI:10.1016/j.jns.2014.05.042 · 2.47 Impact Factor
Show more