Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Within neuroimaging research, a number of recent studies have discussed the impact of between-study differences in volumetric findings that are thought to result from the use of different segmentation tools to generate brain volumes. Here, processing pipelines for seven automated tools that can be used to segment grey matter within the brain are presented. The protocol provides an initial step for researchers aiming to find the most accurate method for generating grey matter volumes from T1-weighted MRI scans. Steps to undertake detailed visual quality control are also included in the manuscript. This protocol covers a range of potential segmentation tools and encourages users to compare the performance of these tools within a subset of their data before selecting one to apply to a full cohort. Furthermore, the protocol may be further generalized to the segmentation of other brain regions

Dynamics of Cortical Degeneration Over a Decade in Huntington's Disease

BACKGROUND: Characterizing changing brain structure in neurodegeneration is fundamental to understanding longterm effects of pathology and ultimately providing therapeutic targets. It is well established that Huntington’s disease (HD) gene carriers undergo progressive brain changes during the course of disease, yet the long-term trajectory of cortical atrophy is not well defined. Given that genetic therapies currently tested in HD are primarily expected to target the cortex, understanding atrophy across this region is essential. METHODS: Capitalizing on a unique longitudinal dataset with a minimum of 3 and maximum of 7 brain scans from 49 HD gene carriers and 49 age-matched control subjects, we implemented a novel dynamical systems approach to infer patterns of regional neurodegeneration over 10 years. We use Bayesian hierarchical modeling to map participant- and group-level trajectories of atrophy spatially and temporally, additionally relating atrophy to the genetic marker of HD (CAG-repeat length) and motor and cognitive symptoms. RESULTS: We show, for the first time, that neurodegenerative changes exhibit complex temporal dynamics with substantial regional variation around the point of clinical diagnosis. Although widespread group differences were seen across the cortex, the occipital and parietal regions undergo the greatest rate of cortical atrophy. We have established links between atrophy and genetic markers of HD while demonstrating that specific cortical changes predict decline in motor and cognitive performance. CONCLUSIONS: HD gene carriers display regional variability in the spatial pattern of cortical atrophy, which relates to genetic factors and motor and cognitive symptoms. Our findings indicate a complex pattern of neuronal loss, which enables greater characterization of HD progression

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker

Objective Huntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real‐life clinical diagnosis in HD. Method A multivariate machine learning approach was applied to resting‐state and structural magnetic resonance imaging scans from 19 premanifest HD gene carriers (preHD, 8 of whom developed clinical disease in the 5 years postscanning) and 21 healthy controls. A classification model was developed using cross‐group comparisons between preHD and controls, and within the preHD group in relation to “estimated” and “actual” proximity to disease onset. Imaging measures were modeled individually, and combined, and permutation modeling robustly tested classification accuracy. Results Classification performance for preHDs versus controls was greatest when all measures were combined. The resulting polymarker predicted converters with high accuracy, including those who were not expected to manifest in that time scale based on the currently adopted statistical models. Interpretation We propose that a holistic multivariate machine learning treatment of brain abnormalities in the premanifest phase can be used to accurately identify those patients within 5 years of developing motor features of HD, with implications for prognostication and preclinical trials

Comparison of Rain-Fast Bait Stations Versus Foliar Bait Sprays for Control of Oriental Fruit Fly, Bactrocera dorsalis, in Papaya Orchards in Hawaii

Bait stations represent an environmentally friendly attract-and-kill approach to fruit fly population suppression. Recently a novel, visually attractive, rain-fast bait station was developed in Hawaii for potential use against multiple species of pestiferous fruit flies. Here, we compared the efficacy of GF-120 NF Naturalyte Fruit Fly Bait applied either as foliar sprays or onto bait stations in reducing female oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), population density and level of fruit infestation in commercial papaya orchards in Hawaii. Trapping and infestation data were used as indicators of the effectiveness of the two bait application methods. For the first 10 weeks of the study, captures of female B. dorsalis in monitoring traps were significantly greater in control plots than in plots treated with foliar sprays or bait stations. Six weeks after the first bait spray, incidence of infestation (i.e. number of fruit with one or more B. dorsalis larvae) of quarter to half-ripe papaya fruit was reduced by 71.4% and 63.1% for plots with bait stations and foliar sprays, respectively, as compared to control plots. Twelve weeks after first spray, incidence of infestation was reduced by only 54.5% and 45.4% for plots with bait stations and foliar sprays, respectively, as compared to control plots. About 42% less GF-120 was used in orchard plots with bait stations compared to those subject to foliar sprays. The impact of field sanitation on the outcome is also discussed. The results indicate that bait stations can provide a simple, efficient, and economical method of applying insecticidal baits to control fruit flies and a safer alternative to foliar sprays

A Multi-Study Model-Based Evaluation of the Sequence of Imaging and Clinical Biomarker Changes in Huntington's Disease

Understanding the order and progression of change in biomarkers of neurodegeneration is essential to detect the effects of pharmacological interventions on these biomarkers. In Huntington’s disease (HD), motor, cognitive and MRI biomarkers are currently used in clinical trials of drug efficacy. Here for the first time we use directly compare data from three large observational studies of HD (total N = 532) using a probabilistic event-based model (EBM) to characterise the order in which motor, cognitive and MRI biomarkers become abnormal. We also investigate the impact of the genetic cause of HD, cytosine-adenine-guanine (CAG) repeat length, on progression through these stages. We find that EBM uncovers a broadly consistent order of events across all three studies; that EBM stage reflects clinical stage; and that EBM stage is related to age and genetic burden. Our findings indicate that measures of subcortical and white matter volume become abnormal prior to clinical and cognitive biomarkers. Importantly, CAG repeat length has a large impact on the timing of onset of each stage and progression through the stages, with a longer repeat length resulting in earlier onset and faster progression. Our results can be used to help design clinical trials of treatments for Huntington’s disease, influencing the choice of biomarkers and the recruitment of participants

An image-based model of brain volume biomarker changes in Huntington's disease

Objective: Determining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine-grained model of temporal progression of Huntington's disease from premanifest through to manifest stages. Methods: We employ a probabilistic event-based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track-HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides. Results: The model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross-validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow-up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers. Interpretation: We used a data-driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event-based model, to provide new insight into Huntington's disease progression and to support fine-grained patient stratification for future precision medicine in Huntington's disease

Area-Wide Suppression of the Mediterranean Fruit Fly, Ceratitis capitata, and the Oriental Fruit Fly, Bactrocera dorsalis, in Kamuela, Hawaii

The United States Department of Agriculture's Agricultural Research Service initiated an area-wide fruit fly management program in Hawaii in 2000. The first demonstration site was established in Kamuela, Hawaii, USA. This paper documents suppression of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), and the oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), in a 40 km2 area containing urban, rural and agricultural zones during a 6 year period. The suppression techniques included sanitation, GF-120 NF Naturalyte Fruit Fly Bait sprays, male annihilation, Biolure® traps, and parasitoids against C. capitata and B. dorsalis. In addition, small numbers of sterile males were released against B. dorsalis. Substantial reductions in fruit infestation levels were achieved for both species (90.7 and 60.7% for C. capitata and B. dorsalis, respectively) throughout the treatment period. Fruit fly captures in the 40 km2 treatment area were significantly lower during the 6 year period than those recorded in three non-treated areas. The strategy of combining suppression techniques in an area-wide approach is discussed

Bisphosphonate-related osteonecrosis of jaw (BRONJ): an anti-angiogenic side-effect?

Bisphosphonates are recommended in the treatment of osteoporosis and some cancers, in which case they prevent the appearance of bone metastasis. The patients taking bisphosphonates are at increased risk of developing bisphosphonate-related osteonecrosis of jaw (BRONJ) which is characterised by the presence of an un-healing wound after dental surgery. BRONJ might represent an anti-angiogenic side effect. However, the real number of patients with BRONJ might be higher than currently recorded. Considering the differential diagnosis which includes various primary and secondary cancers, a correct histopathological diagnosis is very important. The morphological criteria for diagnosis of BRONJ are highlighted in this material.Virtual Slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1813972972323288. © 2012 Petcu et al.; licensee BioMed Central Ltd

Multimodal characterization of the visual network in Huntington's disease gene carriers

Objective A sensorimotor network structural phenotype predicted motor task performance in a previous study in Huntington’s disease (HD) gene carriers. We investigated in the visual network whether structure – function – behaviour relationship patterns, and the effects of the HD mutation, extended beyond the sensorimotor network. Methods We used multimodal visual network MRI structural measures (cortical thickness and white matter connectivity), plus visual evoked potentials and task performance (Map Search; Symbol Digit Modalities Test) in healthy controls and HD gene carriers. Results Using principal component (PC) analysis, we identified a structure – function relationship common to both groups. PC scores differed between groups indicating white matter disorganization (higher RD, lower FA) and slower, and more disperse, VEP signal transmission (higher VEP P100 latency and lower VEP P100 amplitude) in HD than controls while task performance was similar. Conclusions HD may be associated with reduced white matter organization and efficient visual network function but normal task performance. Significance These findings indicate that structure – function relationships in the visual network, and the effects of the HD mutation, share some commonalities with those in the sensorimotor network. However, implications for task performance differ between the two networks suggesting the influence of network specific factors

Brain-derived neurotrophic factor in cerebrospinal fluid and plasma is not a biomarker for Huntington's disease

Brain-derived neurotrophic factor (BDNF) is implicated in the survival of striatal neurons. BDNF function is reduced in Huntington’s disease (HD), possibly because mutant huntingtin impairs its cortico-striatal transport, contributing to striatal neurodegeneration. The BDNF trophic pathway is a therapeutic target, and blood BDNF has been suggested as a potential biomarker for HD, but BDNF has not been quantified in cerebrospinal fluid (CSF) in HD. BDNF in CSF and plasma in the HD-CSF cohort (20 pre-manifest and 40 manifest HD mutation carriers and 20 age and gender-matched controls) were quantified using conventional ELISAs and an ultra-sensitive immunoassay. BDNF concentration was below the limit of detection of the conventional ELISAs, raising doubt about previous CSF reports in neurodegeneration. Using the ultra-sensitive method, BDNF concentration was quantifiable in all samples but did not differ between controls and HD mutation carriers in CSF or plasma, was not associated with clinical scores or MRI brain volumetric measures, and had poor ability to discriminate controls from HD mutation carriers, and premanifest from manifest HD. BDNF in CSF and plasma is unlikely to be a biomarker of HD progression, and urge caution in interpreting studies where conventional ELISA was used to quantify CSF BDNF