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The basal ganglia are key structures for motor, cognitive and behavioral functions. They undergo several changes with aging and disease, such as Parkinson's or Huntington's disease, for example. Iron accumulation in basal ganglia is often related to these diseases, which is conventionally monitored by the transverse relaxation rate ( R2*). Quantitative susceptibility mapping (QSM) is a novel contrast mechanism in MRI produced by adding information taken from the phase of the MR signal to its magnitude. It has been shown to be more sensitive to subtle changes in Parkinson's disease. In order to be applied widely to various pathologies, its reproducibility must be evaluated in order to assess intra-subject variability and to disseminate into clinical and pharmaceutical studies. In this work, we studied the reproducibility and sensitivity of several QSM techniques. Fourteen subjects were scanned four times, and QSM and R2* images were reconstructed and registered. An atlas of the basal ganglia was used to automatically define regions of interest. We found that QSM measurements are indeed reproducible in the basal ganglia of healthy subjects and can be widely used as a replacement for R2* mapping in iron-rich regions. This reproducibility study could lead to several lines of research in relaxometry and susceptibility measurements, in vivo iron load evaluation as well as pharmacological assessment and biomarker development. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Mild cognitive impairment (MCI) in Parkinson's disease (PD) is a risk factor for dementia and thus, it is of interest to elucidate if specific patterns of atrophy in PD-MCI patients are associated with a higher risk of developing dementia. We aim to define pattern(s) of regional atrophy in PD-MCI patients who developed dementia during 31 months of follow-up using cortical thickness analysis Twenty-three PD-MCI patients and 18 controls underwent brain MRI and completed a neuropsychological examination at baseline, PD-MCI patients were followed after a 31 month follow-up in order to assess their progression to dementia. At follow up, 8 PD-MCI patients had converted to dementia (PD-MCI converters) whereas 15 remained as PD-MCI (PD-MCI non-converters). All patients were at least 60 years old and suffered PD ≥ 10 years. There were no baseline differences between the two groups of patients in clinical and neuropsychological variables. The cortex of PD-MCI converters was thinner than that of PD-MCI non-converters, bilaterally in the frontal, insula and the left middle temporal areas, also displaying a more widespread pattern of cortical thinning relative to the controls. This study shows that aged and long-term PD patients with MCI who convert to dementia in the short-mid term suffer a thinning of the cortex in several areas (frontal cortex, and middle temporal lobe and insula), even when their cognitive impairment was similar to that of PD-MCI non-converters. Thus, MRI analysis of cortical thickness may represent a useful measure to identify PD-MCI patients at a higher risk of developing dementia.

Objective: We employed diffusion-weighted magnetic resonance spectroscopy (DW-MRS), which allows to measure in vivo the diffusion properties of metabolites, to explore the functional neuro-axonal damage and the ongoing energetic dysregulation in multiple sclerosis (MS)., Methods: Twenty-five patients with MS and 18 healthy controls (HC) underwent conventional magnetic resonance imaging (MRI) and DW-MRS. The apparent diffusion coefficient (ADC) of total N-acetyl-aspartate (tNAA) and creatine-phosphocreatine (tCr) were measured in the parietal normal-appearing white matter (NAWM) and in the thalamic grey matter (TGM). Multiple regressions were used to compare metabolite ADCs between groups and to explore clinical correlations., Results: In patients compared with HCs, we found a reduction in ADC(tNAA) in the TGM, reflecting functional and structural neuro-axonal damage, and in ADC(tCr) in both NAWM and TGM, possibly reflecting a reduction in energy supply in neurons and glial cells. Metabolite ADCs did not correlate with tissue atrophy, lesional volume or metabolite concentrations, while in TGM metabolite ADCs correlated with clinical scores., Conclusion: DW-MRS showed a reduction in tCr diffusivity in the normal-appearing brain of patients with MS, which might reflect a state of ongoing energy dysregulation affecting neurons and/or glial cells. Reversing this energy dysregulation before neuro-axonal degeneration arises may become a key objective in future neuroprotective strategies.

There is a great need for a non-invasive methodology enabling the quantification of translocator protein overexpression in PET clinical imaging. [ 18 F]DPA-714 has emerged as a promising translocator protein radiotracer as it is fluorinated, highly specific and returned reliable quantification using arterial input function. Cerebellum gray matter was proposed as reference region for simplified quantification; however, this method cannot be used when inflammation involves cerebellum. Here we adapted and validated a supervised clustering (supervised clustering algorithm (SCA)) for [ 18 F]DPA-714 analysis. Fourteen healthy subjects genotyped for translocator protein underwent an [ 18 F]DPA-714 PET, including 10 with metabolite-corrected arterial input function and three for a test-retest assessment. Two-tissue compartmental modelling provided [Formula: see text] estimates that were compared to either [Formula: see text] or [Formula: see text] generated by Logan analysis (using supervised clustering algorithm extracted reference region or cerebellum gray matter). The supervised clustering algorithm successfully extracted a pseudo-reference region with similar reliability using classes that were defined using either all subjects, or separated into HAB and MAB subjects. [Formula: see text], [Formula: see text] and [Formula: see text] were highly correlated (ICC of 0.91 ± 0.05) but [Formula: see text] were ∼26% higher and less variable than [Formula: see text]. Reproducibility was good with 5% variability in the test-retest study. The clustering technique for [ 18 F]DPA-714 provides a simple, robust and reproducible technique that can be used for all neurological diseases.

The [ 11 C]PIB PET tracer, originally developed for amyloid imaging, has been recently repurposed to quantify demyelination and remyelination in multiple sclerosis (MS). Myelin PET imaging, however, is limited by its low resolution that deteriorates the quantification accuracy of white matter (WM) lesions. Here, we introduce a novel partial volume correction (PVC) method called Multiresolution-Multimodal Resolution-Recovery (MM-RR), which uses the wavelet transform and a synergistic statistical model to exploit MRI structural images to improve the resolution of [ 11 C]PIB PET myelin imaging. MM-RR performance was tested on a phantom acquisition and in a dataset comprising [ 11 C]PIB PET and MR T1- and T2-weighted images of 8 healthy controls and 20 MS patients. For the control group, the MM-RR PET images showed an average increase of 5.7% in WM uptake while the grey-matter (GM) uptake remained constant, resulting in +31% WM/GM contrast. Furthermore, MM-RR PET binding maps correlated significantly with the mRNA expressions of the most represented proteins in the myelin sheath (R 2  = 0.57 ± 0.09). In the patient group, MM-RR PET images showed sharper lesion contours and significant improvement in normal-appearing tissue/WM-lesion contrast compared to standard PET (contrast improvement > +40%). These results were consistent with MM-RR performances in phantom experiments.

The basal ganglia are key structures for motor, cognitive and behavioral functions. They undergo several changes with aging and disease, such as Parkinson's or Huntington's disease, for example. Iron accumulation in basal ganglia is often related to these diseases, which is conventionally monitored by the transverse relaxation rate (R 2 *). Quantitative susceptibility mapping (QSM) is a novel contrast mechanism in MRI produced by adding information taken from the phase of the MR signal to its magnitude. It has been shown to be more sensitive to subtle changes in Parkinson's disease. In order to be applied widely to various pathologies, its reproducibility must be evaluated in order to assess intra-subject variability and to disseminate into clinical and pharmaceutical studies. In this work, we studied the reproducibility and sensitivity of several QSM techniques. Fourteen subjects were scanned four times, and QSM and R 2 * images were reconstructed and registered. An atlas of the basal ganglia was used to automatically define regions of interest. We found that QSM measurements are indeed reproducible in the basal ganglia of healthy subjects and can be widely used as a replacement for R 2 * mapping in iron-rich regions. This reproducibility study could lead to several lines of research in relaxometry and susceptibility measurements, in vivo iron load evaluation as well as pharmacological assessment and biomarker development. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

SEE MUTHURAMAN ET AL DOI101093/AWW164 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Primary orthostatic tremor is characterized by high frequency tremor affecting the legs and trunk during the standing position. Cerebellar defects were suggested in orthostatic tremor without direct evidence. We aimed to characterize the anatomo-functional defects of the cerebellar motor pathways in orthostatic tremor. We used multimodal neuroimaging to compare 17 patients with orthostatic tremor and 17 age- and gender-matched healthy volunteers. Nine of the patients with orthostatic tremor underwent repetitive transcranial stimulation applied over the cerebellum during five consecutive days. We quantified the duration of standing position and tremor severity through electromyographic recordings. Compared to healthy volunteers, grey matter volume in patients with orthostatic tremor was (i) increased in the cerebellar vermis and correlated positively with the duration of the standing position; and (ii) increased in the supplementary motor area and decreased in the lateral cerebellum, which both correlated with the disease duration. Functional connectivity between the lateral cerebellum and the supplementary motor area was abnormally increased in patients with orthostatic tremor, and correlated positively with tremor severity. After repetitive transcranial stimulation, tremor severity and functional connectivity between the lateral cerebellum and the supplementary motor area were reduced. We provide an explanation for orthostatic tremor pathophysiology, and demonstrate the functional relevance of cerebello-thalamo-cortical connections in tremor related to cerebellar defects., (© The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Quantitative in vivo imaging of myelin loss and repair in patients with multiple sclerosis (MS) is essential to understand the pathogenesis of the disease and to evaluate promyelinating therapies. Selectively binding myelin in the central nervous system white matter, Pittsburgh compound B ([ 11 C]PiB) can be used as a positron emission tomography (PET) tracer to explore myelin dynamics in MS., Methods: Patients with active relapsing-remitting MS (n = 20) and healthy controls (n = 8) were included in a longitudinal trial combining PET with [ 11 C]PiB and magnetic resonance imaging. Voxel-wise maps of [ 11 C]PiB distribution volume ratio, reflecting myelin content, were derived. Three dynamic indices were calculated for each patient: the global index of myelin content change; the index of demyelination; and the index of remyelination., Results: At baseline, there was a progressive reduction in [ 11 C]PiB binding from the normal-appearing white matter to MS lesions, reflecting a decline in myelin content. White matter lesions were characterized by a centripetal decrease in the tracer binding at the voxel level. During follow-up, high between-patient variability was found for all indices of myelin content change. Dynamic remyelination was inversely correlated with clinical disability (p = 0.006 and beta-coefficient = -0.67 with the Expanded Disability Status Scale; p = 0.003 and beta-coefficient = -0.68 with the MS Severity Scale), whereas no significant clinical correlation was found for the demyelination index., Interpretation: [ 11 C]PiB PET allows quantification of myelin dynamics in MS and enables stratification of patients depending on their individual remyelination potential, which significantly correlates with clinical disability. This technique should be considered to assess novel promyelinating drugs. Ann Neurol 2016;79:726-738., (© 2016 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association.)

An accurate in vivo measure of myelin content is essential to deepen our insight into the mechanisms underlying demyelinating and dysmyelinating neurological disorders, and to evaluate the effects of emerging remyelinating treatments. Recently [(11)C]PIB, a positron emission tomography (PET) tracer originally conceived as a beta-amyloid marker, has been shown to be sensitive to myelin changes in preclinical models and humans. In this work, we propose a reference-region methodology for the voxelwise quantification of brain white-matter (WM) binding for [(11)C]PIB. This methodology consists of a supervised procedure for the automatic extraction of a reference region and the application of the Logan graphical method to generate distribution volume ratio (DVR) maps. This approach was assessed on a test-retest group of 10 healthy volunteers using a high-resolution PET tomograph. The [(11)C]PIB PET tracer binding was shown to be up to 23% higher in WM compared with gray matter, depending on the image reconstruction. The DVR estimates were characterized by high reliability (outliers <1%) and reproducibility (intraclass correlation coefficient (ICC) >0.95). [(11)C]PIB parametric maps were also found to be significantly correlated (R(2)>0.50) to mRNA expressions of the most represented proteins in the myelin sheath. On the contrary, no correlation was found between [(11)C]PIB imaging and nonmyelin-associated proteins.

Essential tremor is a movement disorder characterized by tremor during voluntary movements, mainly affecting the upper limbs. The cerebellum and its connections to the cortex are known to be involved in essential tremor, but no task-free intrinsic signatures of tremor related to structural cerebellar defects have so far been found in the cortical motor network. Here we used voxel-based morphometry, tractography and resting-state functional MRI at 3 T to compare structural and functional features in 19 patients with essential tremor and homogeneous symptoms in the upper limbs, and 19 age- and gender-matched healthy volunteers. Both structural and functional abnormalities were found in the patients' cerebellum and supplementary motor area. Relative to the healthy controls, the essential tremor patients' cerebellum exhibited less grey matter in lobule VIII and less effective connectivity between each cerebellar cortex and the ipsilateral dentate nucleus. The patient's supplementary motor area exhibited (i) more grey matter; (ii) a lower amplitude of low-frequency fluctuation of the blood oxygenation level-dependent signal; (iii) less effective connectivity between each supplementary motor area and the ipsilateral primary motor hand area, and (iv) a higher probability of connection between supplementary motor area fibres and the spinal cord. Structural and functional changes in the supplementary motor area, but not in the cerebellum, correlated with clinical severity. In addition, changes in the cerebellum and supplementary motor area were interrelated, as shown by a correlation between the lower amplitude of low-frequency fluctuation in the supplementary motor area and grey matter loss in the cerebellum. The structural and functional changes observed in the supplementary motor area might thus be a direct consequence of cerebellar defects: the supplementary motor area would attempt to reduce tremor in the motor output by reducing its communication with M1 hand areas and by directly modulating motor output via its corticospinal projections.See Raethjen and Muthuraman (doi:10.1093/brain/awv238) for a scientific commentary on this article., (© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Neurodegenerative diseases such as Alzheimer's disease present subtle anatomical brain changes before the appearance of clinical symptoms. Manual structure segmentation is long and tedious and although automatic methods exist, they are often performed in a cross-sectional manner where each time-point is analyzed independently. With such analysis methods, bias, error and longitudinal noise may be introduced. Noise due to MR scanners and other physiological effects may also introduce variability in the measurement. We propose to use 4D non-linear registration with spatio-temporal regularization to correct for potential longitudinal inconsistencies in the context of structure segmentation. The major contribution of this article is the use of individual template creation with spatio-temporal regularization of the deformation fields for each subject. We validate our method with different sets of real MRI data, compare it to available longitudinal methods such as FreeSurfer, SPM12, QUARC, TBM, and KNBSI, and demonstrate that spatially local temporal regularization yields more consistent rates of change of global structures resulting in better statistical power to detect significant changes over time and between populations.

Unlabelled: Translocator protein (TSPO) is expressed at a low level in healthy brain and is upregulated during inflammatory processes that may occur in neurodegenerative diseases. Thus, TSPO may be a suitable in vivo indicator of neurodegeneration. Here, we quantified the (18)F-DPA-714 radioligand in healthy TSPO-genotyped volunteers and developed a method to eliminate the need for invasive arterial blood sampling., Methods: Ten controls (7 high-affinity binders [HABs] and 3 mixed-affinity binders [MABs]) underwent (18)F-DPA-714 PET with arterial and venous sampling. (18)F-DPA-714 binding was quantified with a metabolite-corrected arterial plasma input function, using the 1- and 2-tissue-compartment models (TCMs) as well as the Logan analysis to estimate total volume distribution (V(T)) in the regions of interest. Alternative quantification methods were tested, including tissue-to-plasma ratio or population-based input function approaches normalized by late time points of arterial or venous samples., Results: The distribution pattern of (18)F-DPA-714 was consistent with the known distribution of TSPO in humans, with the thalamus displaying the highest binding and the cerebellum the lowest. The 2-TCM best described the regional kinetics of (18)F-DPA-714 in the brain, with good identifiability (percentage coefficient of variation < 5%). For each region of interest, V(T) was 47.6% ± 6.3% higher in HABs than in MABs, and estimates from the 2-TCM and the Logan analyses were highly correlated. Equilibrium was reached at 60 min after injection. V(T) calculated with alternative methods using arterial samples was strongly and significantly correlated with that calculated by the 2-TCM. Replacement of arterial with venous sampling in these methods led to a significant but lower correlation., Conclusion: Genotyping of subjects is a prerequisite for a reliable quantification of (18)F-DPA-714 PET images. The 2-TCM and the Logan analyses are accurate methods to estimate (18)F-DPA-714 V(T) in the human brain of both HAB and MAB individuals. Population-based input function and tissue-to-plasma ratio with a single arterial sample are promising alternatives to classic arterial plasma input function. Substitution with venous samples is promising but still requires methodologic improvements., (© 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.)

Severe cognitive impairment involving multiple cognitive domains can occur early during the course of multiple sclerosis (MS). We investigated resting state functional connectivity changes in large-scale brain networks and related structural damage underlying cognitive dysfunction in patients with early MS. Patients with relapsing MS (3-5 years disease duration) were prospectively assigned to two groups based on a standardized neuropsychological evaluation: (1) cognitively impaired group (CI group, n = 15), with abnormal performances in at least 3 tests; (2) cognitively preserved group (CP group, n = 20) with normal performances in all tests. Patients and age-matched healthy controls underwent a multimodal 3T magnetic resonance imaging (MRI) including anatomical T1 and T2 images, diffusion imaging and resting state functional MRI. Structural MRI analysis revealed that CI patients had a higher white matter lesion load compared to CP and a more severe atrophy in gray matter regions highly connected to networks involved in cognition. Functional connectivity measured by integration was increased in CP patients versus controls in attentional networks (ATT), while integration was decreased in CI patients compared to CP both in the default mode network (DMN) and ATT. An anatomofunctional study within the DMN revealed that functional connectivity was mostly altered between the medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC) in CI patients compared to CP and controls. In a multilinear regression model, functional correlation between MPFC and PCC was best predicted by PCC atrophy. Disconnection in the DMN and ATT networks may deprive the brain of compensatory mechanisms required to face widespread structural damage., (Copyright © 2014 Wiley Periodicals, Inc.)

Grey matter (GM) atrophy occurs early in primary progressive MS (PPMS), but it is unknown whether its progression involves different brain regions at different rates, as is seen in other neurodegenerative diseases. We aimed to investigate the temporal and regional evolution of GM volume loss over 5years and its relationship with disability progression in early PPMS. We studied 36 patients with PPMS within five years from onset and 19 age and gender-matched healthy controls with clinical and imaging assessments at study entry and yearly for 3years and then at 5years. Patients were scored on the expanded disability status scale (EDSS) and MS Functional Composite (MSFC) at each time-point. An unbiased longitudinal voxel-based morphometry approach, based on high-dimensional spatial alignment within-subject, was applied to the serial imaging data. The rate of local (voxel-wise) volume change per year was compared between groups and its relationship with clinical outcomes was assessed. Patients deteriorated significantly during the five years follow-up. Patients showed a greater decline of GM volume (p<0.05, FWE-corrected) bilaterally in the cingulate cortex, thalamus, putamen, precentral gyrus, insula and cerebellum when compared to healthy controls over five years, although the rate of volume loss varied across the brain, and was the fastest in the cingulate cortex. Significant (p<0.05, FWE-corrected) volume loss was detected in the left insula, left precuneus, and right cingulate cortex in patients at three years, as compared to baseline, whilst the bilateral putamen and the left superior temporal gyrus showed volume loss at five years. In patients, there was a relationship between a higher rate of volume loss in the bilateral cingulate cortex and greater clinical disability, as measured by the MSFC, at five years (Pearson's r=0.49, p=0.003). Longitudinal VBM demonstrated that the progression of GM atrophy in PPMS occurs at different rates in different regions across the brain. The involvement of the cingulate cortex occurs early in the disease course, continues at a steady rate throughout the follow-up period and is associated with patient outcome. These findings provide new insights into the characteristics of GM atrophy across the brain in MS, and have potential consequences for the selection of brain atrophy as an outcome measure in neuroprotective clinical trials., (© 2013 Elsevier Inc. All rights reserved.)

In Parkinson's disease, rapid eye movement sleep behaviour disorder is an early non-dopaminergic syndrome with nocturnal violence and increased muscle tone during rapid eye movement sleep that can precede Parkinsonism by several years. The neuronal origin of rapid eye movement sleep behaviour disorder in Parkinson's disease is not precisely known; however, the locus subcoeruleus in the brainstem has been implicated as this structure blocks muscle tone during normal rapid eye movement sleep in animal models and can be damaged in Parkinson's disease. Here, we studied the integrity of the locus coeruleus/subcoeruleus complex in patients with Parkinson's disease using combined neuromelanin-sensitive, structural and diffusion magnetic resonance imaging approaches. We compared 24 patients with Parkinson's disease and rapid eye movement sleep behaviour disorder, 12 patients without rapid eye movement sleep behaviour disorder and 19 age- and gender-matched healthy volunteers. All subjects underwent clinical examination and characterization of rapid eye movement sleep using video-polysomnography and multimodal imaging at 3 T. Using neuromelanin-sensitive imaging, reduced signal intensity was evident in the locus coeruleus/subcoeruleus area in patients with Parkinson's disease that was more marked in patients with than those without rapid eye movement sleep behaviour disorder. Reduced signal intensity correlated with the percentage of abnormally increased muscle tone during rapid eye movement sleep. The results confirmed that this complex is affected in Parkinson's disease and showed a gradual relationship between damage to this structure, presumably the locus subcoeruleus, and abnormal muscle tone during rapid eye movement sleep, which is the cardinal marker of rapid eye movement sleep behaviour disorder. In longitudinal studies, the technique may also provide early markers of non-dopaminergic Parkinson's disease pathology to predict the occurrence of Parkinson's disease.

Predicting Alzheimer's disease (AD) in individuals with some symptoms of cognitive decline may have great influence on treatment choice and disease progression. Structural magnetic resonance imaging (MRI) has the potential of revealing early signs of neurodegeneration in the human brain and may thus aid in predicting and diagnosing AD. Surface-based cortical thickness measurements from T1-weighted MRI have demonstrated high sensitivity to cortical gray matter changes. In this study we investigated the possibility for using patterns of cortical thickness measurements for predicting AD in subjects with mild cognitive impairment (MCI). We used a novel technique for identifying cortical regions potentially discriminative for separating individuals with MCI who progress to probable AD, from individuals with MCI who do not progress to probable AD. Specific patterns of atrophy were identified at four time periods before diagnosis of probable AD and features were selected as regions of interest within these patterns. The selected regions were used for cortical thickness measurements and applied in a classifier for testing the ability to predict AD at the four stages. In the validation, the test subjects were excluded from the feature selection to obtain unbiased results. The accuracy of the prediction improved as the time to conversion from MCI to AD decreased, from 70% at 3 years before the clinical criteria for AD was met, to 76% at 6 months before AD. By inclusion of test subjects in the feature selection process, the prediction accuracies were artificially inflated to a range of 73% to 81%. Two important results emerge from this study. First, prediction accuracies of conversion from MCI to AD can be improved by learning the atrophy patterns that are specific to the different stages of disease progression. This has the potential to guide the further development of imaging biomarkers in AD. Second, the results show that one needs to be careful when designing training, testing and validation schemes to ensure that datasets used to build the predictive models are not used in testing and validation., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Magnetic resonance (MR) imaging is often used to characterize and quantify multiple sclerosis (MS) lesions in the brain and spinal cord. The number and volume of lesions have been used to evaluate MS disease burden, to track the progression of the disease and to evaluate the effect of new pharmaceuticals in clinical trials. Accurate identification of MS lesions in MR images is extremely difficult due to variability in lesion location, size and shape in addition to anatomical variability between subjects. Since manual segmentation requires expert knowledge, is time consuming and is subject to intra- and inter-expert variability, many methods have been proposed to automatically segment lesions. The objective of this study was to carry out a systematic review of the literature to evaluate the state of the art in automated multiple sclerosis lesion segmentation. From 1240 hits found initially with PubMed and Google scholar, our selection criteria identified 80 papers that described an automatic lesion segmentation procedure applied to MS. Only 47 of these included quantitative validation with at least one realistic image. In this paper, we describe the complexity of lesion segmentation, classify the automatic MS lesion segmentation methods found, and review the validation methods applied in each of the papers reviewed. Although many segmentation solutions have been proposed, including some with promising results using MRI data obtained on small groups of patients, no single method is widely employed due to performance issues related to the high variability of MS lesion appearance and differences in image acquisition. The challenge remains to provide segmentation techniques that work in all cases regardless of the type of MS, duration of the disease, or MRI protocol, and this within a comprehensive, standardized validation framework. MS lesion segmentation remains an open problem., (Copyright © 2012 Elsevier B.V. All rights reserved.)

We present a new automatic method for segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. The method performs tissue classification using a model of intensities of the normal appearing brain tissues. In order to estimate the model, a trimmed likelihood estimator is initialized with a hierarchical random approach in order to be robust to MS lesions and other outliers present in real images. The algorithm is first evaluated with simulated images to assess the importance of the robust estimator in presence of outliers. The method is then validated using clinical data in which MS lesions were delineated manually by several experts. Our method obtains an average Dice similarity coefficient (DSC) of 0.65, which is close to the average DSC obtained by raters (0.66).

The subthalamic nucleus (STN) has become an effective target of deep-brain stimulation (DBS) in severely disabled patients with advanced Parkinson's disease (PD). Clinical studies have reported DBS-induced adverse effects on cognitive functions, mood, emotion and behavior. STN DBS seems to interfere with the limbic functions of the basal ganglia, but the limbic effects of STN DBS are controversial. We measured prospectively resting regional cerebral metabolism (rCMb) with 18-fluorodeoxyglucose and PET, and resting regional cerebral blood flow (rCBF) with HMPAO and SPECT in six patients with Parkinson's disease. We compared PET and SPECT 1 month before and 3 months after STN DBS. On cerebral MRI, 13 regions of interest (ROI) were manually delineated slice by slice in frontal and limbic lobes. We obtained mean rCBF and rCMb values for each ROI and the whole brain. We normalized rCBF and rCMB values to ones for the whole brain volume, which we compared before and following STN DBS. No significant difference emerged in the SPECT analysis. PET analysis revealed a significant decrease in rCMb following STN DBS in the superior frontal gyri and left and right dorsolateral prefrontal cortex (p < 0.05). A non-significant decrease in rCMb in the left anterior cingulate gyrus appeared following STN DBS (p = 0.075). Our prospective SPECT and PET study revealed significantly decreased glucose metabolism of the two superior frontal gyri without any attendant perfusion changes following STN DBS. These results suggest that STN DBS may change medial prefrontal function and therefore the integration of limbic information, either by disrupting emotional processes within the STN, or by hampering the normal function of a limbic circuit.

Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains. We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in MRI. We replace the manual interaction with a robust EM-based approach in order to discriminate between MS lesions and the Normal Appearing Brain Tissues (NABT). Evaluation is performed in synthetic and real images showing good agreement between the automatic segmentation and the target segmentation. We compare our algorithm with the state of the art techniques and with several manual segmentations. An advantage of our algorithm over previously published ones is the possibility to semi-automatically improve the segmentation due to the Graph Cuts interactive feature.