Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal data

The main goal of this work was to assess the accuracy of several well-known methods which provide global (BSI and SIENA) or local (Jacobian integration) estimates of longitudinal atrophy in brain structures using Magnetic Resonance images. For that purpose, we have generated realistic simulated images which mimic the patterns of change obtained from a cohort of 19 real controls and 27 probable Alzheimer's disease patients. SIENA and BSI results correlate very well with gold standard data (BSI mean absolute error < 0.29%; SIENA < 0.44%). Jacobian integration was guided by both fluid and FFD-based registration techniques and resulting deformation fields and associated Jacobians were compared, region by region, with gold standard ones. The FFD registration technique provided more satisfactory results than the fluid one. Mean absolute error differences between volume changes given by the FFD-based technique and the gold standard were: sulcal CSF < 2.49%; lateral ventricles < 2.25%; brain < 0.36%; hippocampi < 1.42%

Simultaneous effects on parvalbumin-positive interneuron and dopaminergic system development in a transgenic rat model for sporadic schizophrenia

To date, unequivocal neuroanatomical features have been demonstrated neither for sporadic nor for familial schizophrenia. Here, we investigated the neuroanatomical changes in a transgenic rat model for a subset of sporadic chronic mental illness (CMI), which modestly overexpresses human full-length, non-mutant Disrupted-in-Schizophrenia 1 (DISC1), and for which aberrant dopamine homeostasis consistent with some schizophrenia phenotypes has previously been reported. Neuroanatomical analysis revealed a reduced density of dopaminergic neurons in the substantia nigra and reduced dopaminergic fibres in the striatum. Parvalbumin-positive interneuron occurrence in the somatosensory cortex was shifted from layers II/III to V/VI, and the number of calbindin-positive interneurons was slightly decreased. Reduced corpus callosum thickness confirmed trend-level observations from in vivo MRI and voxel-wise tensor based morphometry. These neuroanatomical changes help explain functional phenotypes of this animal model, some of which resemble changes observed in human schizophrenia post mortem brain tissues. Our findings also demonstrate how a single molecular factor, DISC1 overexpression or misassembly, can account for a variety of seemingly unrelated morphological phenotypes and thus provides a possible unifying explanation for similar findings observed in sporadic schizophrenia patients. Our anatomical investigation of a defined model for sporadic mental illness enables a clearer definition of neuroanatomical changes associated with subsets of human sporadic schizophrenia

Automatic quality control of cardiac MRI segmentation in large-scale population imaging

The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic processing tools such as image segmentation methods are employed to derive quantitative measures or biomarkers for further analyses. Manual inspection and visual QC of each segmentation result is not feasible at large scale. However, it is important to be able to detect when an automatic method fails to avoid inclusion of wrong measurements into subsequent analyses which could otherwise lead to incorrect conclusions. To overcome this challenge, we explore an approach for predicting segmentation quality based on reverse classification accuracy, which enables us to discriminate between successful and failed cases. We validate this approach on a large cohort of cardiac MRI for which manual QC scores were available. Our results on 7,425 cases demonstrate the potential for fully automatic QC in the context of large-scale population imaging such as the UK Biobank Imaging Study

Robust registration between cardiac MRI images and atlas for segmentation propagation

We propose a new framework to propagate the labels in a heart atlas to the cardiac MRI images for ventricle segmentations based on image registrations. The method employs the anatomical information from the atlas as priors to constrain the initialisation between the atlas and the MRI images using region based registrations. After the initialisation which minimises the possibility of local misalignments, a fluid registration is applied to fine-tune the labelling in the atlas to the detail in the MRI images. The heart shape from the atlas does not have to be representative of that of the segmented MRI images in terms of morphological variations of the heart in this framework. In the experiments, a cadaver heart atlas and a normal heart atlas were used to register to in-vivo data for ventricle segmentation propagations. The results have shown that the segmentations based on the proposed method are visually acceptable, accurate (surface distance against manual segmentations is 1.0 ± 1.0 mm in healthy volunteer data, and 1.6 ± 1.8 mm in patient data), and reproducible (0.7 ± 1.0 mm) for in-vivo cardiac MRI images. The experiments also show that the new initialisation method can correct the local misalignments and help to avoid producing unrealistic deformations in the nonrigid registrations with 21% quantitative improvement of the segmentation accuracy

Correlations of behavioral deficits with brain pathology assessed through longitudinal MRI and histopathology in the R6/1 mouse model of huntington's disease

Huntington's disease (HD) is caused by the expansion of a CAG repeat in the huntingtin (HTT) gene. The R6 mouse models of HD express a mutant version of exon 1 HTT and typically develop motor and cognitive impairments, a widespread huntingtin (HTT) aggregate pathology and brain atrophy. Unlike the more commonly used R6/2 mouse line, R6/1 mice have fewer CAG repeats and, subsequently, a less rapid pathological decline. Compared to the R6/2 line, fewer descriptions of the progressive pathologies exhibited by R6/1 mice exist. The association between the molecular and cellular neuropathology with brain atrophy, and with the development of behavioral phenotypes remains poorly understood in many models of HD. In attempt to link these factors in the R6/1 mouse line, we have performed detailed assessments of behavior and of regional brain abnormalities determined through longitudinal, in vivo magnetic resonance imaging (MRI), as well as an end-stage, ex vivo MRI study and histological assessment. We found progressive decline in both motor and non-motor related behavioral tasks in R6/1 mice, first evident at 11 weeks of age. Regional brain volumes were generally unaffected at 9 weeks, but by 17 weeks there was significant grey matter atrophy. This age-related brain volume loss was validated using a more precise, semi-automated Tensor Based morphometry assessment. As well as these clear progressive phenotypes, mutant HTT (mHTT) protein, the hallmark of HD molecular pathology, was widely distributed throughout the R6/1 brain and was accompanied by neuronal loss. Despite these seemingly concomitant, robust pathological phenotypes, there appeared to be little correlation between the three main outcome measures: behavioral performance, MRI-detected brain atrophy and histopathology. In conclusion, R6/1 mice exhibit many features of HD, but the underlying mechanisms driving these clear behavioral disturbances and the brain volume loss, still remain unclear. © 2013 Rattray et al

Inequitable access to substance abuse treatment services in Cape Town, South Africa

BACKGROUND:Despite high levels of substance use disorders in Cape Town, substance abuse treatment utilization is low among people from disadvantaged communities in Cape Town, South Africa. To improve substance abuse treatment utilization, it is important to identify any potential barriers to treatment initiation so that interventions to reduce these barriers can be implemented. To date, substance abuse research has not examined the factors associated with substance abuse treatment utilization within developing countries. Using the Behavioural Model of Health Services Utilization as an analytic framework, this study aimed to redress this gap by examining whether access to substance abuse treatment is equitable and the profile of variables associated with treatment utilization for people from poor communities in Cape Town, South Africa. METHODS: This study used a case-control design to compare 434 individuals with substance use disorders from disadvantaged communities who had accessed treatment with 555 controls who had not accessed treatment on a range of predisposing, treatment need and enabling/restricting variables thought to be associated with treatment utilization. A hierarchical logistic regression was conducted to assess the unique contribution that the need for treatment, predisposing and enabling/restricting variable blocks made on substance abuse treatment utilization. RESULTS: Findings revealed that non-need enabling/restricting variables accounted for almost equal proportions of the variance in service utilization as the need for treatment variables. These enabling/restricting variables also attenuated the influence of the treatment need and predisposing variables domains on chances of treatment utilization. Several enabling/restricting variables emerged as powerful partial predictors of utilization including competing financial priorities, geographic access barriers and awareness of treatment services. Perceived severity of drug use, a need for treatment variable) was also a partial predictor of utilization. CONCLUSIONS: Findings point to inequitable access to substance abuse treatment services among people from poor South African communities, with non-need factors being significant determinants of treatment utilization. In these communities, treatment utilization can be enhanced by (i) expanding the existing repertoire of services to include low threshold services that target individuals with less severe problems; (ii) providing food and transport vouchers as part of contingency management efforts, thereby reducing some of the financial and geographic access barriers; (iii) introducing community-based mobile outpatient treatment services that are geographically accessible; and (iv) employing community-based outreach workers that focus on improving awareness of where, when and how to access existing treatment services

The spatial distribution of radiodense breast tissue: a longitudinal study

Introduction Mammographic breast density is one of the strongest known markers of susceptibility to breast cancer. To date research into density has relied on a single measure ( for example, percent density (PD)) summarising the average level of density for the whole breast, with no consideration of how the radiodense tissue may be distributed. This study aims to investigate the spatial distribution of density within the breast using 493 mammographic images from a sample of 165 premenopausal women (similar to 3 medio-lateral oblique views per woman).Methods Each breast image was divided into 48 regions and the PD for the whole breast ( overall PD) and for each one of its regions ( regional PD) was estimated. The spatial autocorrelation ( Moran's I value) of regional PD for each image was calculated to investigate spatial clustering of density, whether the degree of clustering varied between a woman's two breasts and whether it was affected by age and other known density correlates.Results The median Moran's / value for 165 women was 0.31 (interquartile range: 0.26, 0.37), indicating a clustered pattern. High-density areas tended to cluster in the central regions of the breast, regardless of the level of overall PD, but with considerable between-woman variability in regional PD. The degree of clustering was similar between a woman's two breasts (mean within-woman difference in Moran's / values between left and right breasts = 0.00 (95% confidence interval (CI) = -0.01, 0.01); P = 0.76) and did not change with aging (mean within-woman difference in I values between screens taken on average 8 years apart = 0.01 (95% CI = -0.01, 0.02); P = 0.30). Neither parity nor age at first birth affected the level of spatial autocorrelation of density, but increasing body mass index (BMI) was associated with a decrease in the degree of spatial clustering.Conclusions This study is the first to demonstrate that the distribution of radiodense tissue within the breast is spatially autocorrelated, generally with the high-density areas clustering in the central regions of the breast. The degree of clustering was similar within a woman's two breasts and between women, and was little affected by age or reproductive factors although it declined with increasing BMI

Validation analysis of the novel imaging-based prognostic radiomic signature in patients undergoing primary surgery for advanced high-grade serous ovarian cancer (HGSOC)

Background Predictive models based on radiomics features are novel, highly promising approaches for gynaecological oncology. Here, we wish to assess the prognostic value of the newly discovered Radiomic Prognostic Vector (RPV) in an independent cohort of high-grade serous ovarian cancer (HGSOC) patients, treated within a Centre of Excellence, thus avoiding any bias in treatment quality. Methods RPV was calculated using standardised algorithms following segmentation of routine preoperative imaging of patients (n = 323) who underwent upfront debulking surgery (01/2011-07/2018). RPV was correlated with operability, survival and adjusted for well-established prognostic factors (age, postoperative residual disease, stage), and compared to previous validation models. Results The distribution of low, medium and high RPV scores was 54.2% (n = 175), 33.4% (n = 108) and 12.4% (n = 40) across the cohort, respectively. High RPV scores independently associated with significantly worse progression-free survival (PFS) (HR = 1.69; 95% CI:1.06–2.71; P = 0.038), even after adjusting for stage, age, performance status and residual disease. Moreover, lower RPV was significantly associated with total macroscopic tumour clearance (OR = 2.02; 95% CI:1.56–2.62; P = 0.00647). Conclusions RPV was validated to independently identify those HGSOC patients who will not be operated tumour-free in an optimal setting, and those who will relapse early despite complete tumour clearance upfront. Further prospective, multicentre trials with a translational aspect are warranted for the incorporation of this radiomics approach into clinical routine

Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI

PURPOSE: We propose a fully automated method for detection and segmentation of the abnormal tissue associated with brain tumour (tumour core and oedema) from Fluid- Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Imaging (MRI). METHODS: The method is based on superpixel technique and classification of each superpixel. A number of novel image features including intensity-based, Gabor textons, fractal analysis and curvatures are calculated from each superpixel within the entire brain area in FLAIR MRI to ensure a robust classification. Extremely randomized trees (ERT) classifier is compared with support vector machine (SVM) to classify each superpixel into tumour and non-tumour. RESULTS: The proposed method is evaluated on two datasets: (1) Our own clinical dataset: 19 MRI FLAIR images of patients with gliomas of grade II to IV, and (2) BRATS 2012 dataset: 30 FLAIR images with 10 low-grade and 20 high-grade gliomas. The experimental results demonstrate the high detection and segmentation performance of the proposed method using ERT classifier. For our own cohort, the average detection sensitivity, balanced error rate and the Dice overlap measure for the segmented tumour against the ground truth are 89.48 %, 6 % and 0.91, respectively, while, for the BRATS dataset, the corresponding evaluation results are 88.09 %, 6 % and 0.88, respectively. CONCLUSIONS: This provides a close match to expert delineation across all grades of glioma, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management

Correlates of Obsessive–Compulsive Disorder in a Sample of HIV-Positive, Methamphetamine-using Men Who have Sex with Men

Substance use has been identified as a risk factor for elevated levels of obsessive–compulsive disorder (OCD). This study examined methamphetamine use and sexual risk behaviors as correlates of OCD in a sample of 245 HIV-positive men having sex with men (MSM) in San Diego, CA. In a logistic regression analysis, OCD was associated with greater frequency of methamphetamine use, more depressive symptoms, seeking out risky venues and risky sexual partners when “high” on methamphetamine, and reporting fewer sex acts in the past 2 months. These data suggest the need for increased awareness and understanding of the role that OCD may play in the drug use behaviors and risky sexual practices of methamphetamine users