Marco Battaglini

Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes

Objective: To assess the time course of brain atrophy and the difference across clinical subtypes in multiple sclerosis (MS). Methods: The percent brain volume change (PBVC) was computed on existing longitudinal (2 time points) T1-weighted MRI from untreated (trial and nontrial) patients with MS. Patients (n = 963) were classified as clinically isolated syndromes suggestive of MS (CIS, 16%), relapsing-remitting (RR, 60%), secondary progressive (SP, 15%), and primary progressive (9%) MS. The median length of follow-up was 14 months (range 12–68). Results: There was marked heterogeneity of the annualized PBVC (PBVC/y) across MS subtypes (p = 0.003), with higher PBVC/y in SP than in CIS (p = 0.003). However, this heterogeneity disappeared when data were corrected for the baseline normalized brain volume. When the MS population was divided into trial and nontrial subjects, the heterogeneity of PBVC/y across MS subtypes was present only in the second group, due to the higher PBVC/y values found in trial data in CIS (p = 0.01) and RR (p < 0.001). The estimation of the sample sizes required for demonstrating a reduction of brain atrophy in patients in a placebo-controlled trial showed that this was larger in patients with early MS than in those with the progressive forms of the disease. Conclusions: This first large study in untreated patients with multiple sclerosis (MS) with different disease subtypes shows that brain atrophy proceeds relentlessly throughout the course of MS, with a rate that seems largely independent of the MS subtype, when adjusting for baseline brain volume.

Evaluating and reducing the impact of white matter lesions on brain volume measurements

MR‐based measurements of brain volumes may be affected by the presence of white matter (WM) lesions. Here, we assessed how and to what extent this may happen for WM lesions of various sizes and intensities. After inserting WM lesions of different sizes and intensities into T1‐W brain images of healthy subjects, we assessed the effect on two widely used automatic methods for brain volume measurement such as SIENAX (segmentation‐based) and SIENA (registration‐based). To explore the relevance of partial volume (PV) estimation, we performed the experiments with two different PV models, implemented by the same segmentation algorithm (FAST) of SIENAX and SIENA. Finally, we tested potential solutions to this issue. The presence of WM lesions did not bias measurements for registration‐based method such as SIENA. By contrast, the presence of WM lesions affected segmentation‐based brain volume measurements such as SIENAx. The misclassification of both gray matter (GM) and WM volumes varied considerably with lesion size and intensity, especially when the lesion intensity was similar to that of the GM/WM interface. The extent to which the presence of WM lesions could affect tissue‐class measures was clearly driven by the PV modeling used, with the mixel‐type PV model giving a lower error in the presence of WM lesions. The tissue misclassification due to WM lesions was still present when they were masked out. By contrast, refilling the lesions with intensities matching the surrounding normal‐appearing WM ensured accurate tissue‐class measurements and thus represents a promising approach for accurate tissue classification and brain volume measurements. Hum Brain Mapp 33:2062–2071, 2012.

Cognitive assessment and quantitative magnetic resonance metrics can help to identify benign multiple sclerosis.

Background: The definition of benign multiple sclerosis (B-MS) is still controversial. This mainly takes into account the subject’s motor ability, with little or no relevance to other important features such as cognition. Moreover, no paraclinical markers are currently available to reliably identify patients who will remain benign in the long term. Objectives: To assess, by using quantitative magnetic resonance (MR) metrics, differences in tissue damage between B-MS patients after dividing them into two groups on the basis of their cognitive performance. Methods: Forty-seven B-MS patients (Expanded Disability Status Scale score ≤3.0 and disease duration ≥15 years) underwent neuropsychological assessment through the Rao Brief Repeatable Battery and the Stroop Test. At that time, B-MS patients underwent conventional brain MR and magnetization transfer (MT) imaging. White matter lesion load, global and regional brain volumes, and MT ratio (MTr) in lesions and normal-appearing brain were measured. Quantitative MR measures were compared in cognitively impaired (CI-MS) and cognitively preserved (CP-MS) patients and in 24 demographically matched healthy controls. Test performance was correlated with MR changes in specific cortical regions. Results: Eleven patients were classified as CI-MS, and 36 were classified as CP-MS. Both T2-weighted and T1-weighted lesion loads were higher (p = 0.05 and 0.001) in CI-MS than in CP-MS patients. Furthermore, CI-MS patients were characterized by more pronounced decrease in neocortical volume (p = 0.005) and cortical MTr (p = 0.02) values than CP-MS patients. Finally, test performance correlated significantly with MR changes in relevant cortical regions. Conclusions: Cognitive assessment and quantitative magnetic resonance can help to reliably identify benign multiple sclerosis patients.

Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis

Objective To assess whether it is feasible to establish specific cut-off values able to discriminate ‘physiological’ or ‘pathological’ brain volume rates in patients with multiple sclerosis (MS). Methods The study was based on the analysis of longitudinal MRI data sets of patients with MS (n=206, 87% relapsing–remitting, 7% secondary progressive and 6% primary progressive) and healthy controls (HC; n=35). Brain atrophy rates were computed over a mean follow-up of 7.5 years (range 1–12) for patients with MS and 6.3 years (range 1–12.5) for HC with the SIENA software and expressed as annualised per cent brain volume change (PBVC/y). A weighted (on the follow-up length) receiver operating characteristic analysis and the area under the curve (AUC) were used for statistics. Results The weighted PBVC/y was −0.51±0.27% in patients with MS and −0.27±0.15% in HC (p<0.0001). There was a significant age-related difference in PBVC/y between HC older and younger than 35 years of age (p=0.02), but not in patients with MS (p=0.8). The cut-off of PBVC/y, as measured by SIENA that could maximise the accuracy in discriminating patients with MS from HC, was −0.37%, with 67% sensitivity and 80% specificity. According to the observed distribution, values of PBVC/y as measured by SIENA that could define a pathological range were above −0.52% with 95% specificity, above −0.46% with 90% specificity and above −0.40% with 80% specificity. Conclusions Our evidence-based criteria provide values able to discriminate the presence or absence of ‘pathological’ brain volume loss in MS with high specificity. Such results could be of great value in a clinical setting, particularly in assessing treatment efficacy in MS.

Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis

Focal lesions and brain atrophy are the most extensively studied aspects of multiple sclerosis (MS), but the image acquisition and analysis techniques used can be further improved, especially those for studying within-patient changes of lesion load and atrophy longitudinally. Improved accuracy and sensitivity will reduce the numbers of patients required to detect a given treatment effect in a trial, and ultimately, will allow reliable characterization of individual patients for personalized treatment. Based on open issues in the field of MS research, and the current state of the art in magnetic resonance image analysis methods for assessing brain lesion load and atrophy, this paper makes recommendations to improve these measures for longitudinal studies of MS. Briefly, they are (1) images should be acquired using 3D pulse sequences, with near-isotropic spatial resolution and multiple image contrasts to allow more comprehensive analyses of lesion load and atrophy, across timepoints. Image artifacts need special attention given their effects on image analysis results. (2) Automated image segmentation methods integrating the assessment of lesion load and atrophy are desirable. (3) A standard dataset with benchmark results should be set up to facilitate development, calibration, and objective evaluation of image analysis methods for MS.

Neuropsychological and MRI measures predict short-term evolution in benign multiple sclerosis

Objective: To assess whether neuropsychological tests and MRI measures could be used as predictors of short-term disease evolution in a population of patients with benign multiple sclerosis (B-MS). Background: The definition of B-MS is controversial. Recent data suggest that neuropsychological tests and MRI measures can provide valuable information for a more correct definition and interpretation of B-MS. Methods: Sixty-three patients with B-MS (Expanded Disability Status Scale [EDSS] ≤3.0 and disease duration ≥15 years) underwent neuropsychological assessment using the Raos Brief Repeatable Neuropsychological Battery and the Stroop Test. At that time, conventional brain MRI and magnetization transfer (MT) imaging was performed. White matter lesion load, global and regional brain volumes, and MT ratio in lesions and normal-appearing brain were measured. After a mean follow-up of 5 years, patients still having an EDSS score ≤3.5 were classified as still benign, whereas patients who had developed a secondary progressive course or who had an EDSS score ≥4.0 were defined as no longer benign (NLB). Results: At end of follow-up, 29% of patients were classified as NLB. Male gender (hazard ratio [HR] = 2.9; 95% confidence interval [CI] 1.2–7.5; p = 0.02), number of neuropsychological tests failed (HR = 1.4; 95% CI 1.1–1.7; p = 0.003), and T1-weighted lesions (HR = 1.3; 95% CI 1.1–1.5; p = 0.002) were related to NLB status. In a model including these 3 variables, the NLB status was predicted with an accuracy of 82%. Conclusions: Cognitive assessment and MRI metrics can predict short-term disease evolution in benign multiple sclerosis (B-MS). This information can be useful to correctly identify patients with B-MS.

Acute metabolic brain changes following traumatic brain injury and their relevance to clinical severity and outcome

Background: Conventional MRI can provide critical information for care of patients with traumatic brain injury (TBI), but MRI abnormalities rarely correlate to clinical severity and outcome. Previous magnetic resonance spectroscopy studies have reported clinically relevant brain metabolic changes in patients with TBI. However, these changes were often assessed a few to several days after the trauma, with a consequent variation of the metabolic pattern due to temporal changes. Methods: Proton magnetic resonance spectroscopic imaging (1H-MRSI) examinations were performed in 10 patients with TBI 48–72 h after the trauma, to obtain early measurements of central brain levels of N-acetylaspartate (NAA), choline (Cho), creatine (Cr) and lactate (La). Metabolite values were expressed as ratios to (1) a metabolic pattern, given by the sum of the resonance intensities of all metabolites detected in the same voxel and (2) intravoxel Cr. Results: NAA ratios were found to be significantly lower in patients with TBI than in normal controls. In contrast, Cho ratios were significantly higher in patients with TBI than in normal controls. Increased La levels were found in 5 of 10 patients with TBI. Both NAA and La values correlated closely with those of the Glasgow Coma Scale at presentation (r = 0.73 and −0.62, respectively; p<0.01 for both) and the Glasgow Outcome Scale at 3 months (r = −0.79 and 0.79, respectively; p<0.01 for both). Conclusion: Spectroscopic measures of neuro-axonal damage occurring soon after a brain trauma are clinically relevant. Significant increases in cerebral La level also may be detected when 1H-MRSI is performed early after the trauma and, at this stage, can represent a reliable index of injury severity and disease outcome in patients with TBI.

Imaging distribution and frequency of cortical lesions in patients with multiple sclerosis.

Background: The presence of cortical lesions (CLs) and their topographic distribution in the brains of patients with multiple sclerosis (MS) have been clearly shown by recent histopathologic studies. CLs can also be assessed in vivo, with less sensitivity, by using specific MRI sequences. MRI-based lesion probability maps (LPMs) may partially overcome this lack of sensitivity and provide unique information on the spatial distribution and frequency of CLs in MS. Methods: A total of 149 patients with MS (103 relapsing-remitting [RR] and 46 primary progressive [PP]) underwent an MRI examination, which included the double inversion recovery (DIR) sequence for CL assessment. CL masks were then obtained for each patient and a cortical LPM (cLPM) was created for each MS subtype. Results: CLs were mainly distributed in the frontal (RR = 51.8%; PP = 50.5%) and temporal (RR = 30.4%; PP = 35.5%) lobes, with a prominent involvement of the motor (RR = 37.8%; PP = 30.6%) and anterior cingulate (RR = 9.2%; PP = 10.6%) cortices. The extent of brain lobe affected by CLs was higher in RR than in PP patients. The frequency of CL occurrence was higher in PP than in RR patients. Both measurements, however, did not show differences between the 2 MS subtypes at voxel-wise analysis. Conclusions: Patients with RRMS and PPMS share more similarities than differences in terms of CL number, volume, topographic distribution, and frequency. The similarities between histopathologic data and the findings reported here suggest that DIR images can accurately illustrate the focal pathology occurring in the cortical regions of patients with MS, providing clinically relevant information.

Voxel-wise assessment of progression of regional brain atrophy in relapsing-remitting multiple sclerosis

OBJECTIVE To perform voxel-wise assessments of regional brain atrophy state and rate in subjects with relapsing-remitting (RR) multiple sclerosis (MS). BACKGROUND Recently, attention has focused on defining the tissue compartments and regions within which brain atrophy occurs. These regional measures of brain volume changes may help to better define the nature of the pathology underlying MS. In this context, specific regional measures of grey matter (GM) volume changes can be obtained by using the voxel-based morphometry (VBM) approach. METHODS Fifty-nine subjects with RR MS underwent conventional MRI at baseline and after a mean follow-up period of 3 years. Cross-sectionally, two VBM analyses (SPM-VBM, based on the Statistical Parametric Mapping software package, and FSL-VBM, based on the FMRIB Software Library tools) were performed to assess cortical GM volumes in RR MS patients compared to 25 age- and sex-matched normal controls (NC). Longitudinally, FSL-VBM and the regional extension of the SIENA method (SIENAr) were both used to assess regional brain atrophy rate in the RR MS patients and its relationship with increases in T(2)-weighted white matter (WM) lesion volume over the follow-up period. RESULTS Widespread decrease in cortical GM volume was found in the RR MS patients compared to NC. Both SPM-VBM and FSL-VBM showed similar involvement of cortical regions (frontal, temporal, parietal, occipital lobes and insula), with a close correlation between the numbers of significant voxels obtained with the two different procedures (r=0.73, p<0.001). After 3-year follow-up, both FSL-VBM and SIENAr showed a further significant reduction in GM volume in the lateral frontal and parietal cortices, bilaterally. Regional volume changes also appeared significantly pronounced in correspondence to the increase in T(2)-weighted WM lesion volume over the follow-up period. CONCLUSIONS By using different methodologies, we showed similar widespread tissue loss in the cerebral cortex of patients with RR MS. This brain tissue loss further progresses over time, particularly in the fronto-parietal cortex and seems to be partially dependent upon the increase of lesion load.

Cortical lesions in radiologically isolated syndrome

Objective: To assess the presence of cortical lesions (CLs) as detected by MRI in subjects with radiologically isolated syndrome (RIS). Methods: Fifteen subjects with RIS underwent an MRI examination, including a double inversion recovery sequence for CL assessment. T2-hyperintense white matter (WM) lesion volume (LV) and normalized volumes of brain and cortex were also obtained. Results: Thirty-four CLs were identified in 6 of 15 (40%) subjects with RIS and predominantly distributed in frontotemporal lobes. CLs were frequent in subjects with RIS with immunoglobulin G oligoclonal bands on CSF, cervical cord lesions, and dissemination in time on brain MRI. WM LV was higher in subjects with CLs than in those without CLs (11.5 ± 10.1 vs 3.9 ± 2.8 cm3, p = 0.04). Indeed, CL number and volume correlated with WM LV (r = 0.57, p = 0.03 and r = 0.61, p = 0.01). All subjects with CLs were classified in a previous study as having a very high probability of having relapsing-remitting multiple sclerosis (MS) on a logistic regression analysis of quantitative MRI indices. Conclusions: We found CLs in subjects with RIS, a condition characterized by the unanticipated MRI finding of WM lesions highly suggestive of MS in the absence of a clinical scenario. CLs were mainly localized to the frontotemporal lobes and were associated with important markers of evolution to MS.