Regional lobar atrophy predicts memory impairment in multiple sclerosis

Department of Neurology, SUNY Buffalo School of Medicine, Buffalo, NY 14203, USA.
American Journal of Neuroradiology (Impact Factor: 3.59). 09/2005; 26(7):1824-31.
Source: PubMed


In recent studies, measures of whole brain atrophy were strongly correlated with neuropsychological testing, explaining more variance than measures of lesion burden in patients with multiple sclerosis. The relationship between regional lobar atrophy and cognitive impairment is yet to be examined. We endeavored to assess the clinical significance of regional lobar atrophy in multiple sclerosis.
In a cross-sectional study, we evaluated 31 patients with multiple sclerosis with brain MR imaging and neuropsychological testing. Impairment was determined by comparison with demographically matched healthy controls. MR imaging generated measures of lesion burden (fluid-attenuated inversion recovery hyperintense volume), general atrophy (brain parenchymal fraction), central atrophy (lateral ventricle volume), and lobar atrophy (regional brain parenchymal fraction of frontal, temporal, parietal, and occipital lobes in each hemisphere). Neuropsychological testing emphasized measures of processing speed and memory, because these are commonly affected in multiple sclerosis.
Patients with multiple sclerosis showed significant atrophy and impairment on all neuropsychological tests. Regional atrophy accounted for the most variance in all regression models predicting memory performance. Left temporal atrophy was the primary predictor of auditory/verbal memory (partial r's = 0.55-0.61), and both left and right temporal atrophy predicted visual/spatial memory performance (partial r's = 0.51-0.67). Models predicting learning consistency retained frontal lobe atrophy measures (partial r's = 0.44-0.68). Central and general atrophy measures were the primary predictors in modeling processing speed (partial r's = 0.42-0.64).
Regional atrophy accounts for more variance than lesion burden, whole brain atrophy, or lateral ventricle volume in predicting multiple sclerosis-associated memory dysfunction.

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    • "Studies evaluating atrophy and SDMT found a moderate-to-strong correlation between these two variables as r-values ranged from −0.40 to −0.73, indicating that greater atrophy was associated with poorer SDMT performance. All 10 studies [20–23, 25, 27, 33, 34, 39, 54] assessing patients with mixed MS subtypes reported correlations, eight of which were significant [20–23, 27, 33, 34, 39] and one [25] in which the statistical significance was not reported. In studies on RRMS patients, only two [21, 24] of seven [13, 18, 21, 24, 30, 47, 48] studies reported significant correlation between brain atrophy and SDMT. "
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    ABSTRACT: Objectives. To examine relationships between conventional MRI measures and the paced auditory serial addition test (PASAT) and symbol digit modalities test (SDMT). Methods. A systematic literature review was conducted. Included studies had ≥30 multiple sclerosis (MS) patients, administered the SDMT or PASAT, and measured T2LV or brain atrophy. Meta-analysis of MRI/information processing speed (IPS) correlations, analysis of MRI/IPS significance tests to account for reporting bias, and binomial testing to detect trends when comparing correlation strengths of SDMT versus PASAT and T2LV versus atrophy were conducted. Results. The 39 studies identified frequently reported only significant correlations, suggesting reporting bias. Direct meta-analysis was only feasible for correlations between SDMT and T2LV (r = -0.45, P < 0.001) and atrophy in patients with mixed-MS subtypes (r = -0.54, P < 0.001). Familywise Holm-Bonferroni testing found that selective reporting was not the source of at least half of significant results reported. Binomial tests (P = 0.006) favored SDMT over PASAT in strength of MRI correlations. Conclusions. A moderate-to-strong correlation exists between impaired IPS and MRI in mixed MS populations. Correlations with MRI were stronger for SDMT than for PASAT. Neither heterogeneity among populations nor reporting bias appeared to be responsible for these findings.
    Full-text · Article · Mar 2014
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    • "The involvement of certain area of gray matter and the association with specific domain have been investigated. In a group of RRMS and SPMS patients it has been shown that temporal lobe atrophy is associated with a poor outcome in memory performance while whole brain or central atrophy is more related to processing speed performance [74]. Another study about regional atrophy showed a correlation between hippocampal atrophy and a poor performance in memory-coding test [75]. "
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    ABSTRACT: Multiple sclerosis (MS) is an immune-mediated disease affecting central nervous system (CNS). Although MS is classically considered a white matter (WM) disease, the involvement of gray matter (GM) in the pathogenic process has been confirmed by pathology studies and MRI studies. Impairment of cognitive domains such as memory, mental processing speed, attention, and executive function can occur from the early stage of the disease and tends to worsen over time, despite stable physical symptoms. WM demyelination is moderately correlated with CI, suggesting that probably WM abnormalities alone cannot fully explain the extent of clinical symptoms in MS, including CI. Several MRI techniques have shown the involvement of GM in MS and the association between GM damage, physical disability, and CI. The aim of this review is to provide an overview of CI and GM damage assessed by structural brain MRI.
    Full-text · Article · Jan 2014
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    • "Cognitive impairment is among the main symptoms, affecting about half of all MS patients, and lower processing speed and defective retrieval from recent memory storage are frequently observed [4] [5] [6]. Impairment of cognitive functioning is correlated with brain atrophy revealed with MRI [7] [8]. Memory has multiple regional atrophy correlates, including deep gray matter [9], cerebral cortex volume [8], and medial temporal lobe volume [10] [11]. "
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    ABSTRACT: The CVLT-II provides standardized scores for each of the List A five learning trials, so that the clinician can compare the patient's raw trials 1-5 scores with standardized ones. However, frequently, a patient's raw scores fluctuate making a proper interpretation difficult. The CVLT-II does not offer any other methods for classifying a patient's learning and memory status on the background of the learning curve. The main objective of this research is to illustrate that discriminant analysis provides an accurate assessment of the learning curve, if suitable predictor variables are selected. Normal controls were ninety-eight healthy volunteers (78 females and 20 males). A group of MS patients included 365 patients (266 females and 99 males) with clinically defined multiple sclerosis. We show that the best predictor variables are coefficients B3 and B4 of our mathematical model B3 ∗ exp(-B2  ∗  (X - 1)) + B4  ∗  (1 - exp(-B2  ∗  (X - 1))) because discriminant functions, calculated separately for B3 and B4, allow nearly 100% correct classification. These predictors allow identification of separate impairment of readiness to learn or ability to learn, or both.
    Full-text · Article · Apr 2012
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