No evidence for an effect on brain atrophy rate of atorvastatin add-on to interferon ß1b therapy in relapsing-remitting multiple sclerosis (the ARIANNA study).

BACKGROUND: A previous phase 2 trial has suggested that statins might delay brain atrophy in secondary progressive multiple sclerosis. OBJECTIVES: The objective of this study was to evaluate the effect of atorvastatin add-on therapy on cerebral atrophy in relapsing-remitting multiple sclerosis. METHODS: This randomised, placebo-controlled study compared atorvastatin 40 mg or placebo add-on therapy to interferon ß1b for 24 months. Brain magnetic resonance imaging, multiple sclerosis functional composite score, Rao neuropsychological battery and expanded disability status scale were evaluated over 24 months. RESULTS: A total of 154 patients were randomly assigned, 75 in the atorvastatin and 79 in the placebo arms, with a comparable drop-out rate (overall 23.4%). Brain atrophy over 2 years was not different in the two arms (-0.38% and -0.32% for the atorvastatin and placebo groups, respectively). Relapse rate, expanded disability status scale, multiple sclerosis functional composite score or cognitive changes were not different in the two arms. Patients withdrawing from the study had a higher number of relapses in the previous 2 years (P=0.04) and a greater probability of relapsing within 12 months. CONCLUSIONS: Our results suggest that the combination of atorvastatin and interferon ß1b is not justified in early relapsing-remitting multiple sclerosis and adds to the body of evidence indicating an absence of significant radiological and clinical benefit of statins in relapsing-remitting multiple sclerosis.

SPECT imaging of GABA(A)/benzodiazepine receptors and cerebral perfusion in mild cognitive impairment.

PURPOSE: The involvement of neocortical and limbic GABA(A)/benzodiazepine (BZD) receptors in Alzheimer's disease (AD) is controversial and mainly reported in advanced stages. The status of these receptors in the very early stages of AD is unclear and has not been explored in vivo. Our aims were to investigate in vivo the integrity of cerebral cortical GABA(A)/BZD receptors in subjects with amnestic mild cognitive impairment (MCI) and to compare possible receptor changes to those in cerebral perfusion. METHODS: [(123)I]Iomazenil and [(99m)Tc]HMPAO SPECT images were acquired in 16 patients with amnestic MCI and in 14 normal elderly control subjects (only [(123)I]iomazenil imaging in 5, only [(99m)Tc]HMPAO imaging in 4, and both [(123)I]iomazenil and [(99m)Tc]HMPAO imaging in 5). Region of interest (ROI) analysis and voxel-based analysis were performed with cerebellar normalization. RESULTS: Neither ROI analysis nor voxel-based analysis showed significant [(123)I]iomazenil binding changes in MCI patients compared to control subjects, either as a whole group or when considering only those patients with MCI that converted to AD within 2 years of clinical follow-up. In contrast, the ROI analysis revealed significant hypoperfusion of the precuneus and posterior cingulate cortex in the whole group of MCI patients and in MCI converters as compared to control subjects. Voxel-based analysis showed similar results. CONCLUSION: These results indicate that in the very early stages of AD, neocortical and limbic neurons/synapses expressing GABA(A)/BZD receptors are essentially preserved. They suggest that in MCI patients functional changes precede neuronal/synaptic loss in neocortical posterior regions and that [(99m)Tc]HMPAO rCBF imaging is more sensitive than [(123)I]iomazenil GABA(A)/BZD receptor imaging in detecting prodromal AD.

Voxel-based analysis of gray matter relaxation rates shows different correlation patterns for cognitive impairment and physical disability in relapsing-remitting multiple sclerosis.

BACKGROUND: Regional analyses of markers of microstructural gray matter (GM) changes, including relaxation rates, have shown inconsistent correlations with physical and cognitive impairment in MS. OBJECTIVE: To assess voxelwise the correlation of the R1 and R2 relaxation rates with the physical and cognitive impairment in MS. METHODS: GM R1 and R2 relaxation rate maps were obtained in 241 relapsing-remitting MS patients by relaxometric segmentation of MRI studies. Correlations with the Expanded Disability Status Scale (EDSS) and the percentage of impaired cognitive test (Brief Repeatable Battery and Stroop Test, available in 186 patients) were assessed voxelwise, including voxel GM content as nuisance covariate to remove the effect of atrophy on the correlations. RESULTS: Extensive clusters of inverse correlation between EDSS and R2 were detected throughout the brain, while inverse correlations with R1 were mostly limited to perirolandic and supramarginal cortices. Cognitive impairment correlated negatively with R1, and to a lesser extent with R2, in the middle frontal, mesial temporal, midcingulate and medial parieto-occipital cortices. CONCLUSION: In relapsing-remitting MS patients, GM microstructural changes correlate diffusely with physical disability, independent of atrophy, with a preferential role of the sensorimotor cortices. Neuronal damage in the limbic system and dorsolateral prefrontal cortices correlates with cognitive dysfunction.

Brain tissue volumes and relaxation rates in multiple sclerosis: implications for cognitive impairment.

OBJECTIVE: Both normal gray matter atrophy and brain tissue relaxation rates, in addition to total lesion volume, have shown significant correlations with cognitive test scores in multiple sclerosis (MS). Aim of the study was to assess the relative contributions of macro- and microstructural changes of both normal and abnormal brain tissues, probed, respectively, by their volumes and relaxation rates, to the cognitive status and physical disability of MS patients. METHODS: MRI studies from 241 patients with relapsing-remitting MS were retrospectively analyzed by fully automated multiparametric relaxometric segmentation. Ordinal backward regression analysis was applied to the resulting volumes and relaxation rates of both normal (gray matter, normal-appearing white matter and CSF) and abnormal (T2-weighted lesions) brain tissues, controlling for age, sex and disease duration, to identify the main independent contributors to the cognitive status, as measured by the percentage of failed tests at a cognitive test battery (Rao's Brief Repeatable Battery and Stroop test, available in 186 patients), and to the physical disability, as assessed by the Expanded Disability Status Scale (EDSS). RESULTS: The R1 relaxation rate (a putative marker of tissue disruption) of the MS lesions appeared the single most significant contributor to cognitive impairment (p < 0.001). On the contrary, the EDSS appeared mainly affected by the decrease in R2 of the gray matter (p < 0.0001), (possibly influenced by cortical plaques, edema and inflammation). CONCLUSIONS: In RR-MS the tissue damage in white matter lesions appears the single main determinant of the cognitive status of patients, likely through disconnection phenomena, while the physical disability appears related to the involvement of gray matter.

Diffusion volume (DV) measurement in endometrial and cervical cancer: A new MRI parameter in the evaluation of the tumor grading and the risk classification.

PURPOSE: A new MRI parameter representative of active tumor burden is proposed: diffusion volume (DV), defined as the sum of all the voxels within a tumor with apparent diffusion coefficient (ADC) values within a specific range. The aims of the study were: (a) to calculate DV on ADC maps in patients with cervical/endometrial cancer; (b) to correlate DV with histological grade (G) and risk classification; (c) to evaluate intra/inter-observer agreement of DV calculation. MATERIALS AND METHODS: Fifty-three patients with endometrial (n=28) and cervical (n=25) cancers underwent pelvic MRI with DWI sequences. Both endometrial and cervical tumors were classified on the basis of G (G1/G2/G3) and FIGO staging (low/medium/high-risk). A semi-automated segmentation procedure was used to calculate the DV. A freehand closed ROI outlined the whole visible tumor on the most representative slice of ADC maps defined as the slice with the maximum diameter of the solid neoplastic component. Successively, two thresholds were generated on the basis of the mean and standard deviation (SD) of the ADC values: lower threshold (LT="mean minus three SD") and higher threshold (HT="mean plus one SD"). The closed ROI was expanded in 3D, including all the contiguous voxels with ADC values in the range LT-HT × 10-3mm(2)/s. A Kruskal-Wallis test was used to assess the differences in DV among G and risk groups. Intra-/inter-observer variability for DV measurement was analyzed according to the method of Bland and Altman and the intraclass-correlation-coefficient (ICC). RESULTS: DV values were significantly different among G and risk groups in both endometrial (p<0.05) and cervical cancers (p ≤ 0.01). For endometrial cancer, DV of G1 (mean ± sd: 2.81 ± 3.21 cc) neoplasms were significantly lower than G2 (9.44 ± 9.58 cc) and G3 (11.96 ± 8.0 cc) ones; moreover, DV of low risk cancers (5.23 ± 8.0 cc) were significantly lower than medium (7.28 ± 4.3 cc) and high risk (14.7 ± 9.9 cc) ones. For cervical cancer, DV of G1 (0.31 ± 0.13 cc) neoplasms was significantly lower than G3 (40.68 ± 45.65 cc) ones; moreover, DV of low risk neoplasms (6.98 ± 8.08 cc) was significantly lower than medium (21.7 ± 17.13 cc) and high risk (62.9 ± 51.12 cc) ones and DV of medium risk neoplasms was significantly lower than high risk ones. The intra-/inter-observer variability for DV measurement showed an excellent correlation for both cancers (ICC ≥ 0.86). CONCLUSIONS: DV is an accurate index for the assessment of G and risk classification of cervical/endometrial cancers with low intra-/inter-observer variability.

A Novel Multiparametric Approach to 3D Quantitative MRI of the Brain.

Magnetic Resonance properties of tissues can be quantified in several respects: relaxation processes, density of imaged nuclei, magnetism of environmental molecules, etc. In this paper, we propose a new comprehensive approach to obtain 3D high resolution quantitative maps of arbitrary body districts, mainly focusing on the brain. The theory presented makes it possible to map longitudinal (R1), pure transverse (R2) and free induction decay ([Formula: see text]) rates, along with proton density (PD) and magnetic susceptibility (χ), from a set of fast acquisition sequences in steady-state that are highly insensitive to flow phenomena. A novel denoising scheme is described and applied to the acquired datasets to enhance the signal to noise ratio of the derived maps and an information theory approach compensates for biases from radio frequency (RF) inhomogeneities, if no direct measure of the RF field is available. Finally, the results obtained on sample brain scans of healthy controls and multiple sclerosis patients are presented and discussed.

Improving Signal-to-Noise Ratio in Susceptibility Weighted Imaging: A Novel Multicomponent Non-Local Approach.

In susceptibility-weighted imaging (SWI), the high resolution required to obtain a proper contrast generation leads to a reduced signal-to-noise ratio (SNR). The application of a denoising filter to produce images with higher SNR and still preserve small structures from excessive blurring is therefore extremely desirable. However, as the distributions of magnitude and phase noise may introduce biases during image restoration, the application of a denoising filter is non-trivial. Taking advantage of the potential multispectral nature of MR images, a multicomponent approach using a Non-Local Means (MNLM) denoising filter may perform better than a component-by-component image restoration method. Here we present a new MNLM-based method (Multicomponent-Imaginary-Real-SWI, hereafter MIR-SWI) to produce SWI images with high SNR and improved conspicuity. Both qualitative and quantitative comparisons of MIR-SWI with the original SWI scheme and previously proposed SWI restoring pipelines showed that MIR-SWI fared consistently better than the other approaches. Noise removal with MIR-SWI also provided improvement in contrast-to-noise ratio (CNR) and vessel conspicuity at higher factors of phase mask multiplications than the one suggested in the literature for SWI vessel imaging. We conclude that a proper handling of noise in the complex MR dataset may lead to improved image quality for SWI data.

Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: from atlas to dose-volume histograms.

PURPOSE: To implement and evaluate a magnetic resonance imaging atlas-based automated segmentation (MRI-ABAS) procedure for cortical and sub-cortical grey matter areas definition, suitable for dose-distribution analyses in brain tumor patients undergoing radiotherapy (RT). PATIENTS AND METHODS: 3T-MRI scans performed before RT in ten brain tumor patients were used. The MRI-ABAS procedure consists of grey matter classification and atlas-based regions of interest definition. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm was applied to structures manually delineated by four experts to generate the standard reference. Performance was assessed comparing multiple geometrical metrics (including Dice Similarity Coefficient - DSC). Dosimetric parameters from dose-volume-histograms were also generated and compared. RESULTS: Compared with manual delineation, MRI-ABAS showed excellent reproducibility [median DSCABAS=1 (95% CI, 0.97-1.0) vs. DSCMANUAL=0.90 (0.73-0.98)], acceptable accuracy [DSCABAS=0.81 (0.68-0.94) vs. DSCMANUAL=0.90 (0.76-0.98)], and an overall 90% reduction in delineation time. Dosimetric parameters obtained using MRI-ABAS were comparable with those obtained by manual contouring. CONCLUSIONS: The speed, reproducibility, and robustness of the process make MRI-ABAS a valuable tool for investigating radiation dose-volume effects in non-target brain structures providing additional standardized data without additional time-consuming procedures.

An MRI digital brain phantom for validation of segmentation methods.

Knowledge of the exact spatial distribution of brain tissues in images acquired by magnetic resonance imaging (MRI) is necessary to measure and compare the performance of segmentation algorithms. Currently available physical phantoms do not satisfy this requirement. State-of-the-art digital brain phantoms also fall short because they do not handle separately anatomical structures (e.g. basal ganglia) and provide relatively rough simulations of tissue fine structure and inhomogeneity. We present a software procedure for the construction of a realistic MRI digital brain phantom. The phantom consists of hydrogen nuclear magnetic resonance spin-lattice relaxation rate (R1), spin-spin relaxation rate (R2), and proton density (PD) values for a 24 × 19 × 15.5 cm volume of a "normal" head. The phantom includes 17 normal tissues, each characterized by both mean value and variations in R1, R2, and PD. In addition, an optional tissue class for multiple sclerosis (MS) lesions is simulated. The phantom was used to create realistic magnetic resonance (MR) images of the brain using simulated conventional spin-echo (CSE) and fast field-echo (FFE) sequences. Results of mono-parametric segmentation of simulations of sequences with different noise and slice thickness are presented as an example of possible applications of the phantom. The phantom data and simulated images are available online at http://lab.ibb.cnr.it/.