Structural Image Evaluation Using Normalization Of Atrophy Research Articles

Dimethyl fumarate preserves brainstem and cervical spinal cord integrity in radiologically isolated syndrome.

The first randomized placebo-controlled therapeutic trial in radiologically isolated syndrome (RIS), ARISE, demonstrated that treatment with dimethyl fumarate (DMF) delayed the onset of a first clinical event related to CNS demyelination and was associated with a significant reduction in new and/or newly enlarging T2-weighted hyperintense lesions. The purpose of this study was to explore the effect of DMF on volumetric measures, including whole brain, thalamic, and subcortical gray matter volumes, brainstem and upper cervical spine three-dimensional (3D) volumes, and brainstem and upper cervical spine surface characteristics. Standardized 3T MRIs including 3D isotropicT1-weighted gradient echo images were acquired at baseline and end-of-study according to the ARISE study protocol. The acquired datawere analyzed using Structural Image Evaluation Using Normalization of Atrophy (SIENA), FreeSurfer v7.3, and an in-house pipeline for 3D conformational metrics. Multivariate mixed models for repeated measures were used to analyze rates of change in whole brain, thalamic, subcortical gray matter, as well as change in the 3D surface curvature of the dorsal pons and dorsal medulla and 3D volume change at the medulla-upper cervical spinal cord. The study population consisted of 64 RIS subjects (DMF:30, placebo:34). No significant difference was seen in whole brain, thalamic, or subcortical gray matter volumes in treated vs. untreated RIS patients. A significant difference was observed in dorsal pons curvature with the DMF group having a lower least squares mean change of -4.46 (standard estimate (SE): 3.77) when compared to placebo [6.94 (3.71)] (p = 0.036). In individuals that experienced a first clinical event,a greater reduction in medulla-upper cervical spinal cord volume (p = 0.044) and a decrease in surface curvature was observed at the dorsal medulla (p = 0.009) but not at the dorsal pons (p = 0.443). The benefit of disease-modifying therapy in RIS may extend to CNS structures impacted by neurodegeneration that is below the resolution of conventional volumetric measures.

Brain atrophy measurement over a MRI scanner change in multiple sclerosis

BackgroundA change in MRI hardware impacts brain volume measurements. The aim of this study was to use MRI data from multiple sclerosis (MS) patients and healthy control subjects (HCs) to statistically model how to adjust brain atrophy measures in MS patients after a major scanner upgrade. MethodsWe scanned 20 MS patients and 26 HCs before and three months after a major scanner upgrade (1.5 T Siemens Healthineers Magnetom Avanto to 3 T Siemens Healthineers Skyra Fit). The patient group also underwent standardized serial MRIs before and after the scanner change. Percentage whole brain volume changes (PBVC) measured by Structural Image Evaluation using Normalization of Atrophy (SIENA) in the HCs was used to estimate a corrective term based on a linear model. The factor was internally validated in HCs, and then applied to the MS group. ResultsMean PBVC during the scanner change was higher in MS than HCs (-4.1 ± 0.8 % versus −3.4 ± 0.6 %). A fixed corrective term of 3.4 (95% confidence interval: 3.13–3.67)% was estimated based on the observed average changes in HCs. Age and gender did not have a significant influence on this corrective term. After adjustment, a linear mixed effects model showed that the brain atrophy measures in MS during the scanner upgrade were not anymore associated with the scanner type (old vs new scanner; p = 0.29). ConclusionA scanner change affects brain atrophy measures in longitudinal cohorts. The inclusion of a corrective term based on changes observed in HCs helps to adjust for the known and unknown factors associated with a scanner upgrade on a group level.

P1894Serum light-chain neurofilament is associated with brain atrophy in patients with atrial fibrillation

Abstract Background and aims There is emerging evidence that atrial fibrillation (AF) is associated with cognitive dysfunction, increased risk for dementia and reduced brain volume independent of stroke, but the underlying mechanisms of these associations remain unclear. Here, we investigated the association of serum light-chain neurofilament (sNfL), a neuroaxonal injury biomarker, with brain atrophy in AF patients. Methods Explorative analysis from the Swiss-AF cohort study, a multicenter prospective observationalstudy which recruited patients aged ≥45 years with documented AF (NCT02105844). In baseline blood samples, sNfL concentrations were measured in duplicates using a single-molecule array assay. Brain MRI was obtained at baseline and at two years using a standardized protocol including a 3D T1-weighted MPRAGE sequence, on which Structural Image Evaluation using Normalization of Atrophy (SIENA) with optimized parameters for brain extraction was applied to calculate the two-year percentage whole brain volume change (PBVC). Results We included 245 Swiss-AF patients (median age 73, 73% male). Two-year PBVC was significantly associated with baseline sNfL in linear regression, with a 0.09% whole brain volume decrease per 10 pg/ml sNfL increase (95% CI [0.05–0.13], p<0.001). This association remained significant after adjustment for age, history of stroke and other vascular risk factors. Neurofilament and brain atrophy Conclusion Increasing baseline sNfL was predictive of higher two-year brain atrophy rates independent of stroke history in AF patients. This association might reflect a chronic neurodegenerative process in AF. Acknowledgement/Funding Swiss National Science Foundation

Contribution of normal aging to brain atrophy in MS.

ObjectiveTo identify the top brain regions affected by MS-specific atrophy (i.e., atrophy in excess of normal aging) and to test whether normal aging and MS-specific atrophy increase or decrease in these regions with age.MethodsSix hundred fifty subjects (2,790 MRI time points) were analyzed: 520 subjects with relapse-onset MS from a 5-year prospective cohort with annual standardized 1-mm 3D T1-weighted images (3DT1s; 2,483 MRIs) and 130 healthy controls with longitudinal 3DT1s (307 MRIs). Rates of change in all FreeSurfer regions (v5.3) and Structural Image Evaluation Using Normalization of Atrophy (SIENA) were estimated with mixed-effects models. All FreeSurfer regions were ranked by the MS-specific atrophy slope/standard error ratio (βMS × time/SEβMS × time). In the top regions, age was added as an effect modifier to test whether MS-specific atrophy varied by age.ResultsThe top-ranked regions were all gray matter structures. For SIENA, normal aging increased from 0.01%/y at age 30 years to −0.31%/y at age 60 years (−0.11% ± 0.032%/decade, p < 0.01), whereas MS-specific atrophy decreased from −0.38%/y at age 30 years to −0.12%/y at age 60 years (0.09% ± 0.035%/decade, p = 0.01). Similarly, in the thalamus, normal aging increased from −0.15%/y at age 30 years to −0.62%/y at age 60 years (−0.16% ± 0.079%/decade, p < 0.05), and MS-specific atrophy decreased from −0.59%/y at age 30 years to −0.05%/y at age 60 years (0.18% ± 0.08%/decade, p < 0.05). In the putamen and caudate, normal aging and MS-specific atrophy did not vary by age.ConclusionsFor SIENA and thalamic atrophy, the contribution of normal aging increases with age, but does not change in the putamen and caudate. This may have substantial implications to understand the biology of brain atrophy in MS.

Central Slab versus Whole Brain to Measure Brain Atrophy in Multiple Sclerosis

Background: Structural Image Evaluation using Normalization of Atrophy (SIENA) is used to measure brain atrophy in multiple sclerosis (MS). However, brain extraction is prone to artefacts in the upper and lower parts of the brain. To overcome these shortcomings, some pivotal MS trials used a central slab instead of the whole brain as input for SIENA. The aim of this study was to compare the internal consistency and statistical dispersion of atrophy measures, associations with clinical outcomes and required sample sizes in clinical trials between these two approaches. Methods: Brain volume change was assessed using SIENA in 119 MS patients with 5-years follow-up on 3D T1-weighted Magnetization Prepared Rapid Gradient Echo datasets using the whole brain or a central slab ranging from –10 to +60 mm Montreal Neurological Institute atlas coordinates. The statistical analysis included the quartile coefficient of dispersion, partial correlations with clinical outcomes and sample size calculations. Clinical outcome measures comprised the Expanded Disability Status Scale, MS Functional Composite and Symbol Digit Modalities Test. Results: Annualized brain atrophy rates were higher using central slab than whole brain as input for SIENA (–0.51 ± 0.49 vs. –0.37 ± 0.39% per year, p < 0.001). Central and whole brain volume change showed comparable statistical dispersion and similarly correlated with clinical outcomes at 5-years follow-up. Sample size calculations estimated 14% fewer patients required to detect a given treatment effect when using the central slab instead of the whole brain option in SIENA. Conclusion: Central slab and whole brain SIENA produced comparable statistical dispersion with similar associations to clinical outcomes.

Improving the SIENA performance using BEaST brain extraction

We present an improved image analysis pipeline to detect the percent brain volume change (PBVC) using SIENA (Structural Image Evaluation, using Normalization, of Atrophy) in populations with Alzheimer’s dementia. Our proposed approach uses the improved brain extraction mask from BEaST (Brain Extraction based on nonlocal Segmentation Technique) instead of the conventional BET (Brain Extraction Tool) for SIENA. We compared four varying options of BET as well as BEaST and applied these five methods to analyze scan-rescan MRIs in ADNI from 332 subjects, longitudinal ADNI MRIs from the same 332 subjects, their repeat scans over time, and OASIS longitudinal MRIs from 123 subjects. The results showed that BEaST brain masks were consistent in scan-rescan reproducibility. The cross-sectional scan-rescan error in the absolute percent brain volume difference measured by SIENA was smallest (p≤0.0187) with the proposed BEaST-SIENA. We evaluated the statistical power in terms of effect size, and the best performance was achieved with BEaST-SIENA (1.2789 for ADNI and 1.095 for OASIS). The absolute difference in PBVC between scan-dataset (volume change from baseline to year-1) and rescan-dataset (volume change from baseline repeat scan to year-1 repeat scan) was also the smallest with BEaST-SIENA compared to the BET-based SIENA and had the highest correlation when compared to the BET-based SIENA variants. In conclusion, our study shows that BEaST was robust in terms of reproducibility and consistency and that SIENA’s reproducibility and statistical power are improved in multiple datasets when used in combination with BEaST.

Teriflunomide slows BVL in relapsing MS: A reanalysis of the TEMSO MRI data set using SIENA.

Objective:To assess, using structural image evaluation using normalization of atrophy (SIENA), the effect of teriflunomide, a once-daily oral immunomodulator, on brain volume loss (BVL) in patients with relapsing forms of MS enrolled in the phase 3 TEMSO study.Methods:TEMSO MR scans were analyzed (study personnel masked to treatment allocation) using SIENA to assess brain volume changes between baseline and years 1 and 2 in patients treated with placebo or teriflunomide. Treatment group comparisons were made via rank analysis of covariance.Results:Data from 969 patient MRI visits were included in this analysis: 808 patients had baseline and year 1 MRI; 709 patients had baseline and year 2 MRI. Median percentage BVL from baseline to year 1 and year 2 for placebo was 0.61% and 1.29%, respectively, and for teriflunomide 14 mg, 0.39% and 0.90%, respectively. BVL was lower for teriflunomide 14 mg vs placebo at year 1 (36.9% relative reduction, p = 0.0001) and year 2 (30.6% relative reduction, p = 0.0001). Teriflunomide 7 mg was also associated with significant reduction in BVL vs placebo over the 2-year study. The significant effects of teriflunomide 14 mg on BVL were observed in both patients with and without on-study disability worsening.Conclusions:The significant reduction of BVL vs placebo over 2 years achieved with teriflunomide is consistent with its effects on delaying disability worsening and suggests a neuroprotective potential.Classification of evidence:Class II evidence shows that teriflunomide treatment significantly reduces BVL over 2 years vs placebo.ClinicalTrials.gov identifier:NCT00134563.

Effect of fingolimod on diffuse brain tissue damage in relapsing-remitting multiple sclerosis patients

BackgroundMultiple sclerosis (MS) affects all areas of the brain resulting in both focal and diffuse damage. In Phase 3 clinical trials, fingolimod showed significant reductions in both focal lesions and rate of brain volume loss (BVL) in patients with relapsing-remitting MS. ObjectiveTo investigate if the effects of fingolimod 0.5mg on BVL are mediated exclusively through its effects on focal damage or if fingolimod also acts independently in reducing diffuse damage. MethodsThis was a pooled post-hoc analysis of patients from two Phase 3 studies (FREEDOMS [N=1272] and FREEDOMS II [N=1083]), with no evidence of focal disease activity as defined by absence of gadolinium-enhancing lesions at baseline and new active lesions and clinical relapses at follow-up. The percent brain volume change (PBVC), as a measure of diffuse tissue damage, was assessed at Month (M) 12 and M24 by using the Structural Image Evaluation using Normalization of Atrophy (SIENA) method. A regression analysis was performed in the pooled intent-to-treat (ITT) population to quantify the treatment effect of fingolimod on BVL vs. placebo (PBO) in the overall population (unadjusted model), and whether this effect is sustained after adjusting for new active lesions and on-study relapses (adjusted model). ResultsOf 1088 patients, 638 (PBO, n=127; fingolimod, n=511) at M12 and 450 patients (PBO, n=68; fingolimod, n=382) at M24 showed no focal activity. Fingolimod significantly reduced PBVC by 65.5% over 12M (fingolimod vs. PBO: −0.16 vs. −0.45; p=0.001) and by 48.2% over 24M (−0.42 vs. −0.81; p=0.004). An absolute difference in PBVC of −0.27% (p<0.001) in favor of fingolimod vs. PBO over 24M was still evident in the pooled ITT population, after adjusting for active lesions and on-study relapses. The regression model suggests that 54% (−0.27%/−0.51%) of effects of fingolimod on PBVC are independent of its effects on visible focal damage. ConclusionsThe effect of fingolimod on diffuse damage is partly independent of its treatment effect on focal damage, suggesting that both inflammatory and neurodegenerative components of MS are affected.

Progressive Brain Atrophy and Cortical Thinning in Schizophrenia after Commencing Clozapine Treatment.

Despite evidence that clozapine may be neuroprotective, there are few longitudinal magnetic resonance imaging (MRI) studies that have specifically explored an association between commencement of clozapine treatment for schizophrenia and changes in regional brain volume or cortical thickness. A total of 33 patients with treatment-resistant schizophrenia and 31 healthy controls matched for age and gender underwent structural MRI brain scans at baseline and 6-9 months after commencing clozapine. MRI images were analyzed using SIENA (Structural Image Evaluation, using Normalization, of Atrophy) and FreeSurfer to investigate changes over time in brain volume and cortical thickness respectively. Significantly greater reductions in volume were detected in the right and left medial prefrontal cortex and in the periventricular area in the patient group regardless of treatment response. Widespread further cortical thinning was observed in patients compared with healthy controls. The majority of patients improved symptomatically and functionally over the study period, and patients who improved were more likely to have less cortical thinning of the left medial frontal cortex and the right middle temporal cortex. These findings demonstrate on-going reductions in brain volume and progressive cortical thinning in patients with schizophrenia who are switched to clozapine treatment. It is possible that this gray matter loss reflects a progressive disease process irrespective of medication use or that it is contributed to by switching to clozapine treatment. The clinical improvement of most patients indicates that antipsychotic-related gray matter volume loss may not necessarily be harmful or reflect neurotoxicity.

Effect of scanner in longitudinal studies of brain volume changes

To evaluate the effects of drift in scanner hardware and inter-scanner variability on global and regional brain volume changes using longitudinal data obtained on two scanners of the exact same model. A total of 208 subjects (70 females and 138 males, mean age = 56.5 ± 10.1 years) were scanned twice, at an interval of approximately 2 years (mean interval = 1.9 ± 0.15 years), using two 3.0 Tesla (T) scanners of the exact same model. The subjects were divided into four groups according to the combination of scanners used. The effects of scanner drift and inter-scanner variability on global and regional brain volume changes were evaluated using voxel-based morphometry (VBM) and structural image evaluation using normalization of atrophy (SIENA). The mean whole brain volume calculated using VBM increased by 17.2 ± 29.3 mL, and the changes were significantly different between groups. The mean percentage brain volume change (PBVC) calculated using SIENA was -0.46 ± 0.71 %, and did not differ between groups. VBM showed several regions with a significant increase or decrease in volume; however, SIENA showed that edge displacement values were negative in most regions. Even with scanners of the exact same model, scanner drift, and inter-scanner variability can cancel out actual longitudinal brain volume change. SIENA, which corrects for differences in imaging geometry using the outer skull surface for both time points, can reduce the effects of scanner drift and inter-scanner variability on longitudinal morphometric results.

Automated structural imaging analysis detects premanifest Huntington's disease neurodegeneration within 1 year

Intense efforts are underway to evaluate neuroimaging measures as biomarkers for neurodegeneration in premanifest Huntington's disease (preHD). We used a completely automated longitudinal analysis method to compare structural scans in preHD individuals and controls. Using a 1-year longitudinal design, we analyzed T(1) -weighted structural scans in 35 preHD individuals and 22 age-matched controls. We used the SIENA (Structural Image Evaluation, using Normalization, of Atrophy) software tool to yield overall percentage brain volume change (PBVC) and voxel-level changes in atrophy. We calculated sample sizes for a hypothetical disease-modifying (neuroprotection) study. We found significantly greater yearly atrophy in preHD individuals versus controls (mean PBVC controls, -0.149%; preHD, -0.388%; P = .031, Cohen's d = .617). For a preHD subgroup closest to disease onset, yearly atrophy was more than 3 times that of controls (mean PBVC close-to-onset preHD, -0.510%; P = .019, Cohen's d = .920). This atrophy was evident at the voxel level in periventricular regions, consistent with well-established preHD basal ganglia atrophy. We estimated that a neuroprotection study using SIENA would only need 74 close-to-onset individuals in each arm (treatment vs placebo) to detect a 50% slowing in yearly atrophy with 80% power. Automated whole-brain analysis of structural MRI can reliably detect preHD disease progression in 1 year. These results were attained with a readily available imaging analysis tool, SIENA, which is observer independent, automated, and robust with respect to image quality, slice thickness, and different pulse sequences. This MRI biomarker approach could be used to evaluate neuroprotection in preHD.

Gray matter atrophy rate as a marker of disease progression in AD

Global gray matter (GM) atrophy rates were quantified from magnetic resonance imaging (MRI) over 6- and 12-month intervals in 37 patients with Alzheimer's disease (AD) and 19 controls using: (1) nonlinear registration and integration of Jacobian values, and (2) segmentation and subtraction of serial GM volumes. Sample sizes required to power treatment trials using global GM atrophy rate as an outcome measure were estimated and compared between the 2 techniques, and to global brain atrophy measures quantified using the boundary shift integral (brain boundary shift integral; BBSI) and structural image evaluation, using normalization, of atrophy (SIENA). Increased GM atrophy rates (approximately 2% per year) were observed in patients compared with controls. Although mean atrophy rates provided by Jacobian integration were smaller than those from segmentation and subtraction of GM volumes, measurement variance was reduced. The number of patients required per treatment arm to detect a 20% reduction in GM atrophy rate over a 12-month follow-up (90% power) was 202 (95% confidence interval [CI], 118–423) using Jacobian integration and 2047 (95% CI 271 to > 10 000) using segmentation and subtraction. Comparable sample sizes for whole brain atrophy were 240 (95% CI, 142–469) using the BBSI and 196 (95% CI, 110–425) using SIENA. Jacobian integration could be useful for measuring GM atrophy rate in Alzheimer's disease as a marker of disease progression and treatment efficacy.

Effects of gradient non‐linearity correction and intensity non‐uniformity correction in longitudinal studies using structural image evaluation using normalization of atrophy (SIENA)

To evaluate the effects of gradient nonlinearity correction and intensity nonuniformity correction on longitudinal (two-year) changes in global and regional brain volumes. A total of 208 subjects (70 females and 138 males, age range = 38.1-83.0 years) were included in this study. Each subject was scanned twice, at an interval of approximately two years (range = 1.5-2.3 years). Three-dimensional fast spoiled-gradient recalled acquisition in the steady state (3D-FSPGR) images corrected for gradient nonlinearity and/or intensity nonuniformity were compared with uncorrected 3D-FSPGR images with use of structural image evaluation using normalization of atrophy 2.6 (SIENA). The mean absolute deviations of percentage brain volume change (PBVC) values in the gradient nonlinearity +/- intensity nonuniformity corrected images were significantly less than that in the uncorrected images, and the difference in the mean absolute deviation of PBVC was the most significant between the uncorrected images and the images corrected for both gradient nonlinearity and intensity nonuniformity. Voxel-wise comparisons showed large significant differences between the uncorrected images and the corrected images. Correction for gradient nonlinearity and intensity nonuniformity reduces the variance of measured longitudinal changes in brain volumes and will improve accuracy for detecting subtle brain changes.

Intercenter agreement of brain atrophy measurement in multiple sclerosis patients using manually‐edited SIENA and SIENAX

To investigate intercenter agreement of brain volume (change) measurement in multiple sclerosis (MS) using structural image evaluation using normalization of atrophy (SIENA) and the cross-sectional version of SIENA (SIENAX) with additional manual editing to correct for inadequate brain extraction. Baseline and follow-up T1-weighted MR images of 20 MS patients were dispatched to five centers. Each center performed fully-automated and manually-edited analyses for SIENAX, yielding normalized brain volume (NBV), and SIENA, yielding percentage brain volume change (PBVC). Intercenter agreement was assessed with the concordance correlation coefficient (CCC). Intercenter agreement was perfect for fully automated NBV and PBVC (both CCC = 1.0), and remained substantial upon manual editing (CCC = 0.94 for NBV, CCC = 0.95 for PBVC). Mean NBV values for each center decreased significantly after manual editing (overall mean NBV = 1605.3 cm(3) vs. 1651.1 cm(3) without manual editing; t = -4.58, P < 0.001). Total variance in PBVC decreased significantly by a factor of 1.8 after manual editing (sigma(2) = 2.82 before, and sigma(2) = 1.54 after manual editing, P < 0.05). Substantial intercenter agreement was found for manually-edited SIENAX and SIENA, suggesting that measurements from multiple centers may be pooled. Manual editing reduces overestimation of NBV, and is likely to increase statistical power for PBVC.

Longitudinal Changes in Global Brain Volume between 79 and 409 Days after Traumatic Brain Injury: Relationship with Duration of Coma

Neuropathological and experimental animal studies indicate that traumatic brain injury (TBI) results in long-term, neurodegenerative changes. Structural image evaluation using normalization of atrophy (SIENA) offers an automated analysis of the subtle changes in percent brain volume change (%BVC) associated with TBI. In the present study, SIENA was used to evaluate %BVC in individuals who had sustained a mild to severe TBI. We obtained three-dimensional (3D) T1-weighted anatomical magnetic resonance imaging (MRI) scans approximately 79 days and again 409 days post-injury. TBI patients (n = 37) displayed significantly greater decline in %BVC (-1.43%) relative to a normal comparison group (+0.1%, n = 30). Greater %BVC was associated with longer duration of post-injury coma. These results confirm previous findings from cross-sectional studies and argue that the brain undergoes continued structural change for several months post-injury.

Cerebral Atrophy Measurement in Clinically Isolated Syndromes and Relapsing Remitting Multiple Sclerosis: A Comparison of Registration‐Based Methods

Brain atrophy is a proposed marker of disease progression in multiple sclerosis (MS). Many magnetic resonance imaging-based methods of atrophy quantification exist, but their relative sensitivity and precision is unclear. Our aim was to compare atrophy rates from the brain boundary shift integral (BBSI), structural image evaluation, using normalization of atrophy (SIENA) (both registration-based methods) and segmented brain volume difference, in patients with clinically isolated syndromes (CIS), relapsing remitting MS (RRMS), and controls. Thirty-seven CIS patients, 30 with early RRMS and 16 controls had T1-weighted volumetric imaging at baseline and 1 year. Brain atrophy rates were determined using segmented brain volume difference, BBSI, and SIENA. BBSI and SIENA were more precise than subtraction of segmented brain volumes and were more sensitive distinguishing RRMS subjects from controls. A strong correlation was observed between BBSI and SIENA. Atrophy rates were greater in CIS and RRMS subjects than controls (RRMS P < .001). With all methods, significantly greater atrophy rates were observed in CIS patients who developed clinically definite MS relative to subjects who did not. Registration-based techniques are more precise and sensitive than segmentation-based methods in measuring brain atrophy, with BBSI and SIENA providing comparable results.

Manifestations of early brain recovery associated with abstinence from alcoholism

Chronic alcohol abuse results in morphological, metabolic, and functional brain damage which may, to some extent, be reversible with early effects upon abstinence. Although morphometric, spectroscopic, and neuropsychological indicators of cerebral regeneration have been described previously, the overall amount and spatial preference of early brain recovery attained by abstinence and its associations with other indicators of regeneration are not well established. We investigated global and local brain volume changes in a longitudinal two-timepoint study with T1-weighted MRI at admission and after short-term (6-7 weeks) sobriety follow-up in 15 uncomplicated, recently detoxified alcoholics. Volumetric brain gain was related to metabolic and neuropsychological recovery. On admission and after short-term abstinence, structural image evaluation using normalization of atrophy (SIENA), its voxelwise statistical extension to multiple subjects, proton MR spectroscopy (1H-MRS), and neuropsychological tests were applied. Upon short-term sobriety, 1H-MRS levels of cerebellar choline and frontomesial N-acetylaspartate (NAA) were significantly augmented. Automatically detected global brain volume gain amounted to nearly two per cent on average and was spatially significant around the superior vermis, perimesencephalic, periventricular and frontal brain edges. It correlated positively with the percentages of cerebellar and frontomesial choline increase, as detected by 1H-MRS. Moreover, frontomesial NAA gains were associated with improved performance on the d2-test of attention. In 10 age- and gender-matched healthy control subjects, no significant brain volume or metabolite changes were observed. Although cerebral osmotic regulations may occur initially upon sobriety, significant increases of cerebellar choline and frontomesial NAA levels detected at stable brain water integrals and creatine concentrations, serum electrolytes and red blood cell indices in our patient sample suggest that early brain recovery through abstinence does not simply reflect rehydration. Instead, even the adult human brain and particularly its white matter seems to possess genuine capabilities for regrowth. Our findings emphasize metabolic as well as regionally distinct morphological capacities for partial brain recovery from toxic insults of chronic alcoholism and substantiate early measurable benefits of therapeutic sobriety. Further understanding of the precise mechanisms of this recovery may become a valuable model of brain regeneration with relevance for other disorders.

Brain volume changes in CADASIL

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited small vessel disease causing stroke and subcortical vascular dementia. Recent studies in sporadic subcortical ischemic vascular disease have drawn attention to brain atrophy as a clinically important marker of disease progression. However, little is known about the role of brain atrophy and its clinical correlates in CADASIL. The authors determined the normalized brain volume (NBV) and percent brain volume change (PBVC) over 2 years in 76 CADASIL subjects (45.1 +/- 9.7 years) using the SIENA (structural image evaluation using normalization of atrophy) software and its adaptation for cross-sectional measurements (SIENAX). Baseline assessments included systolic blood pressure (SBP), homocysteine levels, BMI, and APOE genotyping. T2-lesion volumes and clinical scales were assessed at both time points. The NBV significantly correlated with all clinical scores (Rankin, NIH Stroke Scale, Barthel, structured interview for the diagnosis of Alzheimer dementia and multi-infarct dementia, Mattis dementia rating scale) at both time points independently of age and sex. PBVC correlated with changes of all clinical scores (all p < 0.01) except for the Mattis dementia rating scale (p = 0.10). In a linear regression model, age (p < 0.001), male sex (p < 0.01), and SBP (p = 0.07) were the main risk factors for a lower NBV at baseline. Age (p < 0.001) and SBP (p = 0.01) were risk factors for brain volume loss during follow-up. Sample size estimates showed that the number of individuals needed to demonstrate a treatment effect in a trial can be reduced when PBVC is used as an endpoint. This study identifies brain atrophy as an important aspect of the disease process in CADASIL and establishes significant correlations with multiple clinical aspects including cognition. Age and systolic blood pressure are risk factors for brain volume loss during follow-up. Percent brain volume change seems promising as an adjunct outcome measure in future interventional trials.

Risk factors for progression of brain atrophy in aging

To determine the rate of brain atrophy in neurologically asymptomatic elderly and to investigate the impact of baseline variables including conventional cerebrovascular risk factors, APOE epsilon4, and white matter hyperintensity (WMH) on its progression. We assessed the brain parenchymal fraction at baseline and subsequent annual brain volume changes over 6 years for 201 participants (F/M = 96/105; 59.8 +/- 5.9 years) in the Austrian Stroke Prevention Study from 1.5-T MRI scans using SIENA (structural image evaluation using normalization of atrophy)/SIENAX (an adaptation of SIENA for cross-sectional measurement)(www.fmrib.ox.ac.uk/fsl). Hypertension, cardiac disease, diabetes mellitus, smoking, and regular alcohol intake were present in 64 (31.8%), 60 (29.9%), 5 (2.5%), 70 (39.3%), and 40 (20.7%) subjects, respectively. Plasma levels of fasting glucose (93.7 +/- 18.6 mg/dL), glycated hemoglobin A (HbA1c; 5.6 +/- 0.7%), total cholesterol (228.3 +/- 40.3 mg/dL), and triglycerides (127.0 +/- 75.2 mg/dL) were determined. WMH was rated as absent (n = 56), punctate (n = 120), early confluent (n = 14), and confluent (n = 11). The baseline brain parenchymal fraction of the entire cohort was 0.80 +/- 0.02 with a mean annual brain volume change of -0.40 +/- 0.29%. Univariate analysis demonstrated a higher rate of brain atrophy in older subjects (p = 0.0001), in those with higher HbA1c (p = 0.0001), higher body mass index (p = 0.02), high alcohol intake (p = 0.04), severe WMH (p = 0.03), and in APOE epsilon4 carriers (p = 0.07). Multivariate analysis suggested that baseline brain parenchymal fraction, HbA1c, and WMH score explain a major proportion of variance in the rates of brain atrophy in the cohort (corrected R2 = 0.27; p = 0.0001). Neurologically asymptomatic elderly experience continuing brain volume loss, which appears to accelerate with age. Glycated hemoglobin A (HbA1c) was identified as a risk factor for a greater rate of brain atrophy. Clustering of factors associated with the so-called metabolic syndrome in subjects with high HbA1c suggests a link between this syndrome and late-life brain tissue loss.

Grey and white matter volume changes in early primary progressive multiple sclerosis: a longitudinal study

We have recently reported brain atrophy in the early stages of primary progressive multiple sclerosis (PPMS), affecting both grey and white matter (GM and WM). However, to date no clinical or radiological predictors of GM and WM atrophy have been identified. The aim was to investigate short-term changes in GM and WM volumes and to assess the predictive value of demographic, clinical and radiological variables in order to gain a better understanding of the pathological substrate underlying these changes. Thirty-one subjects with PPMS within 5 years of symptom onset were studied at baseline and after 1 year. At baseline, patients underwent neurological examination and were scored on the Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Functional Composite. They had 3D inversion-prepared fast spoiled gradient recalled (FSPGR), dual-echo and triple-dose post-contrast T1-weighted spin echo MRI scans. Proton density and enhancing lesion loads were determined. The 3DFSPGR sequence was repeated after 1 year and brain volume changes were calculated using two techniques, SPM99 (statistical parametric mapping) and SIENA (structural image evaluation, using normalization, of atrophy). Stepwise linear regression models were applied to baseline variables to identify independent predictors of atrophy development. Using SPM99, a decrease in brain parenchymal fraction (-1.03%; P < 0.001) and GM fraction (-1.49%; P < 0.001) was observed. The number of enhancing lesions independently predicted decrease in brain parenchymal fraction (P = 0.019) and decrease in WM fraction (P = 0.002). No independent predictors of GM fraction decrease were found. A mean brain volume change of -0.63% (range -4.27% to +1.18%; P = 0.002) was observed using SIENA, which was independently predicted by EDSS (P = 0.004). Global and GM atrophy can be detected over a 1-year period in early PPMS. The former may be predicted by the degree of inflammation, while the latter seems to be independent of it. SIENA and SPM-based methods appear to provide complementary information.