Daniel García-Lorenzo

Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging

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.

Prediction of Alzheimer's disease in subjects with mild cognitive impairment from the ADNI cohort using patterns of cortical thinning.

Predicting Alzheimers 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.

Brain networks disconnection in early multiple sclerosis cognitive deficits: an anatomofunctional study.

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. Hum Brain Mapp 35:4706–4717, 2014.

Trimmed-Likelihood Estimation for Focal Lesions and Tissue Segmentation in Multisequence MRI for Multiple Sclerosis

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 coeruleus/subcoeruleus complex in idiopathic rapid eye movement sleep behaviour disorder

Idiopathic rapid eye movement sleep behaviour disorder is characterized by nocturnal violence, increased muscle tone during rapid eye movement sleep and the lack of any other neurological disease. However, idiopathic rapid eye movement sleep behaviour disorder can precede parkinsonism and dementia by several years. Using 3 T magnetic resonance imaging and neuromelanin-sensitive sequences, we previously found that the signal intensity was reduced in the locus coeruleus/subcoeruleus area of patients with Parkinsons disease and rapid eye movement sleep behaviour disorder. Here, we studied the integrity of the locus coeruleus/subcoeruleus complex with neuromelanin-sensitive imaging in 21 patients with idiopathic rapid eye movement sleep behaviour disorder and compared the results with those from 21 age- and gender-matched healthy volunteers. All subjects underwent a clinical examination, motor, cognitive, autonomous, psychological, olfactory and colour vision tests, and rapid eye movement sleep characterization using video-polysomnography and 3 T magnetic resonance imaging. The patients more frequently had preclinical markers of alpha-synucleinopathies, including constipation, olfactory deficits, orthostatic hypotension, and subtle motor impairment. Using neuromelanin-sensitive imaging, reduced signal intensity was identified in the locus coeruleus/subcoeruleus complex of the patients with idiopathic rapid eye movement sleep behaviour. The mean sensitivity of the visual analyses of the signal performed by neuroradiologists who were blind to the clinical diagnoses was 82.5%, and the specificity was 81% for the identification of idiopathic rapid eye movement sleep behaviour. The results confirm that this complex is affected in idiopathic rapid eye movement sleep behaviour (to the same degree as it is affected in Parkinsons disease). Neuromelanin-sensitive imaging provides an early marker of non-dopaminergic alpha-synucleinopathy that can be detected on an individual basis.

Multiple Sclerosis Lesion Segmentation Using an Automatic Multimodal Graph Cuts

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.

Dynamic Imaging of Individual Remyelination Profiles in Multiple Sclerosis

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 ([11C]PiB) can be used as a positron emission tomography (PET) tracer to explore myelin dynamics in MS.

Temporal and spatial evolution of grey matter atrophy in primary progressive multiple sclerosis

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 5 years 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 3 years and then at 5 years. 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 (Pearsons 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.

Optimized Quantification of Translocator Protein Radioligand 18F-DPA-714 Uptake in the Brain of Genotyped Healthy Volunteers

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 18F-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 18F-DPA-714 PET with arterial and venous sampling. 18F-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 (VT) 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 18F-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 18F-DPA-714 in the brain, with good identifiability (percentage coefficient of variation < 5%). For each region of interest, VT 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. VT 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 18F-DPA-714 PET images. The 2-TCM and the Logan analyses are accurate methods to estimate 18F-DPA-714 VT 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.

Magnetic Resonance Imaging Predictors of Executive Functioning in Patients with Pediatric-Onset Multiple Sclerosis

Executive functions (EFs) are vulnerable to disruption in pediatric-onset multiple sclerosis (MS) patients. We describe the pattern and correlates of executive dysfunction in 34 adolescents with MS on neuropsychological tests and the parent version of the Behavior Rating Inventory of Executive Function (BRIEF). The adolescents with MS performed lower than age-matched controls in several areas of executive functioning, with 44% of patients being impaired on the Trail Making Test-Part B. On the BRIEF, problems in working memory and planning/organization were identified in the patient group compared with controls, particularly in patients with a younger age at disease onset. Task performance and parent-ratings of EF skills were strongly related to whole brain and regional brain volume metrics and, to a lesser extent, T(2)-weighted lesion volume. Working memory and attention switching are at greatest risk of impairment. Results support the inclusion of neuropsychological assessment alongside parent-report measures of EF skills in childhood-onset MS.