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Background There is convincing evidence that daily whole almond consumption lowers blood LDL cholesterol concentrations, but effects on other cardiometabolic risk factors such as endothelial function and liver fat are still to be determined. Objectives We aimed to investigate whether isoenergetic substitution of whole almonds for control snacks with the macronutrient profile of average snack intakes, had any impact on markers of cardiometabolic health in adults aged 30–70 y at above-average risk of cardiovascular disease (CVD). Methods The study was a 6-wk randomized controlled, parallel-arm trial. Following a 2-wk run-in period consuming control snacks (mini-muffins), participants consumed either whole roasted almonds (n = 51) or control snacks (n = 56), providing 20% of daily estimated energy requirements. Endothelial function (flow-mediated dilation), liver fat (MRI/magnetic resonance spectroscopy), and secondary outcomes as markers of cardiometabolic disease risk were assessed at baseline and end point. Results Almonds, compared with control, increased endothelium-dependent vasodilation (mean difference 4.1%-units of measurement; 95% CI: 2.2, 5.9), but there were no differences in liver fat between groups. Plasma LDL cholesterol concentrations decreased in the almond group relative to control (mean difference −0.25 mmol/L; 95% CI: −0.45, −0.04), but there were no group differences in triglycerides, HDL cholesterol, glucose, insulin, insulin resistance, leptin, adiponectin, resistin, liver function enzymes, fetuin-A, body composition, pancreatic fat, intramyocellular lipids, fecal SCFAs, blood pressure, or 24-h heart rate variability. However, the long-phase heart rate variability parameter, very-low-frequency power, was increased during nighttime following the almond treatment compared with control (mean difference 337 ms2; 95% CI: 12, 661), indicating greater parasympathetic regulation. Conclusions Whole almonds consumed as snacks markedly improve endothelial function, in addition to lowering LDL cholesterol, in adults with above-average risk of CVD. This trial was registered at clinicaltrials.gov as NCT02907684.

Intrahepatic lipid (IHL) is linked with reduced hepatic insulin sensitivity and insulin clearance. Despite their high risk for type 2 diabetes (T2D), there have been limited investigations of these relationships in black populations. We investigated these relationships in 18 white European (WE) and 18 black West African (BWA) men with T2D

AimsThe role of carbohydrate restriction in the management of glycaemia in type 2 diabetes (T2D) has been a subject of immense debate and controversy partly due to low-carbohydrate trials being confounded by multiple factors including degree of calorie restriction, dietary protein content, and by no clear definition of a low-carbohydrate diet. The current study sought to provide insight into the relationship between carbohydrate restriction and glycaemia by testing the effect of varying doses of carbohydrate on continuous glucose concentrations within a range of intakes defined as low-carbohydrate while controlling for confounding factors.MethodsThis was a randomised crossover trial in participants with T2D testing 5 different 6-day eucaloric, isocaloric dietary treatments with varying carbohydrate contents (10%, 15%, 20%, 25%, and 30% kcal). Diets were kept isocaloric by exchanging %kcal from carbohydrate with predominantly unsaturated fat, keeping protein constant at 15% kcal. Daily self-weighing was employed to ensure participants maintained their weight throughout each treatment arm. Between dietary treatments, participants underwent a washout period of at least 7 days and were advised to maintain their habitual diet. Glycemic control was assessed using a continuous glucose monitoring device that was placed while the participant was on their normal diet, and was worn for the 6 days of each treatment.Results12 participants completed the study. There were no differences in 24-hour and postprandial sensor glucose concentrations between the 30%kcal and 10%kcal doses (7.4 ± 1.1mmol/L vs 7.6 ± 1.4mmol/L (P=0.28) and 8.0 ± 1.4mmol/L vs 8.3 ± 1.3mmol/L (P=0.28) respectively). In our exploratory analyses we did not find any dose-response relationship between carbohydrate intake and glycaemia. A small amount of weight loss occurred in each treatment arm (range: 0.4 to 1.1kg over the 6 days) but adjusting for these differences did not influence the primary or secondary outcomes.ConclusionsModest changes in dietary carbohydrate content in the absence of weight loss while keeping dietary protein intake constant do not appear to influence glucose concentrations in people with T2D.Trial RegistrationISRCTN 11067343.

To understand the causal role of adiposity and ectopic fat in type 2 diabetes and cardiometabolic diseases, we aimed to identify two clusters of adiposity genetic variants: one with “adverse” metabolic effects (UFA) and the other with, paradoxically, “favorable” metabolic effects (FA). We performed a multivariate genome-wide association study using body fat percentage and metabolic biomarkers from UK Biobank and identified 38 UFA and 36 FA variants. Adiposity-increasing alleles were associated with an adverse metabolic profile, higher risk of disease, higher CRP, and higher fat in subcutaneous and visceral adipose tissue, liver, and pancreas for UFA and a favorable metabolic profile, lower risk of disease, higher CRP and higher subcutaneous adipose tissue but lower liver fat for FA. We detected no sexual dimorphism. The Mendelian randomization studies provided evidence for a risk-increasing effect of UFA and protective effect of FA for type 2 diabetes, heart disease, hypertension, stroke, nonalcoholic fatty liver disease, and polycystic ovary syndrome. FA is distinct from UFA by its association with lower liver fat and protection from cardiometabolic diseases; it was not associated with visceral or pancreatic fat. Understanding the difference in FA and UFA may lead to new insights in preventing, predicting, and treating cardiometabolic diseases.

Psoas muscle measurements are frequently used as markers of sarcopenia and predictors of health. Manually measured cross-sectional areas are most commonly used, but there is a lack of consistency regarding the position of the measurementand manual annotations are not practical for large population studies. We have developed a fully automated method to measure iliopsoas muscle volume (comprised of the psoas and iliacus muscles) using a convolutional neural network. Magnetic resonance images were obtained from the UK Biobank for 5,000 male and female participants, balanced for age, gender and BMI. Ninety manual annotations were available for model training and validation. The model showed excellent performance against out-of-sample data (dice score coefficient of 0.912 +/- 0.018). Iliopsoas muscle volumes were successfully measured in all 5,000 participants. Iliopsoas volume was greater in male compared with female subjects. There was a small but significant asymmetry between left and right iliopsoas muscle volumes. We also found that iliopsoas volume was significantly related to height, BMI and age, and that there was an acceleration in muscle volume decrease in men with age. Our method provides a robust technique for measuring iliopsoas muscle volume that can be applied to large cohorts., Julie Fitzpatrick and Nicolas Basty are joint first authors

Background T2 -weighted imaging (T2 -WI) information has been used in a qualitative manner in the assessment of prostate cancer. Quantitative derivatives (T2 relaxation time) can be generated from T2 -WI. These outputs may be useful in helping to discriminate clinically significant prostate cancer from background signal. Purpose/hypothesis To investigate changes in quantitative T2 parameters in lesions and noncancerous tissue of men on active surveillance for prostate cancer taking dutasteride 0.5 mg or placebo daily for 6 months. Study type Retrospective. Population/subjects Forty men randomized to 6 months of daily dutasteride (n = 20) or placebo (n = 20). Field strength/sequence Multiparametric 3T MRI at baseline and 6 months. This included a multiecho MR sequence for quantification of the T2 relaxation times, in three regions of interest (index lesion, noncancerous peripheral [PZ] and transitional [TZ] zones). A synthetic signal contrast (T2 Q contrast) between lesion and noncancerous tissue was assessed using quantitative T2 values. Signal contrast was calculated using the T2 -weighted sequence (T2 W contrast). Assessment Two radiologists reviewed the scans in consensus according to Prostate Imaging Reporting and Data System (PI-RADS v. 2) guidelines. Statistical tests Wilcoxon and Mann-Whitney U-tests, Spearman's correlation. Results When compared to noncancerous tissue, shorter T2 values were observed within lesions at baseline (83.5 and 80.5 msec) and 6 months (81.5 and 81.9 msec) in the placebo and dutasteride arm, respectively. No significant differences for T2 W contrast at baseline and after 6 months were observed, both in the placebo (0.40 [0.29-0.49] vs. 0.43 [0.25-0.49]; P = 0.881) and dutasteride arm (0.35 [0.24-0.47] vs. 0.37 [0.22-0.44]; P = 0.668). There was a significant, positive correlation between the T2 Q contrast and the T2 W contrast values (r = 0.786; P Data conclusion The exposure to antiandrogen therapy did not significantly influence the T2 contrast or the T2 relaxation values in men on active surveillance for prostate cancer. Level of evidence 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1646-1653.

Objective. To determine if the perfusion parameters by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of regional nodal metastasis are helpful in characterizing nodal status and to understand the relationship with those of primary tumor of nasopharyngeal carcinoma (NPC). Materials and Methods. Newly diagnosed patients imaged between August 2010 and January 2014 and who were found to have enlarged retropharyngeal/cervical lymph nodes suggestive of nodal disease were recruited. DCE-MRI was performed. Three quantitative parameters, Ktrans, ve, and kep, were calculated for the largest node in each patient. Kruskal-Wallis test was used to evaluate the difference in the parameters of the selected nodes of different N stages. Spearman’s correlation was used to evaluate the relationship between the DCE-MRI parameters in nodes and in primary tumors. Results. Twenty-six patients (7 females; 25~67 years old) were enrolled. Ktrans was significantly different among the patients of N stages (N1, n=3; N2, n=17; N3, n=6), P=0.015. Median values (range) for N1, N2, and N3 were 0.24 min−1 (0.17~0.26 min−1), 0.29 min−1 (0.17~0.46 min−1), and 0.46 min−1 (0.29~0.70 min−1), respectively. There was no significant correlation between the parameters in nodes and primary tumors. Conclusion. DCE-MRI may play a distinct role in characterizing the metastatic cervical lymph nodes of NPC.

Objective: This study performed individual-centric, data-driven calculations of propensity for coronary heart disease (CHD) and type 2 diabetes (T2D), utilizing magnetic resonance imaging-acquired body composition measurements, for sub-phenotyping of obesity and nonalcoholic fatty liver disease (NAFLD).Methods: A total of 10,019 participants from the UK Biobank imaging substudy were included and analyzed for visceral and abdominal subcutaneous adipose tissue, muscle fat infiltration, and liver fat. An adaption of the k-nearest neighbors algorithm was applied to the imaging variable space to calculate individualized CHD and T2D propensity and explore metabolic sub-phenotyping within obesity and NAFLD. Results: The ranges of CHD and T2D propensity for the whole cohort were 1.3% to 58.0% and 0.6% to 42.0%, respectively. The diagnostic performance, area under the receiver operating characteristic curve (95% CI), using disease propensities for CHD and T2D detection was 0.75 (0.73-0.77) and 0.79 (0.77-0.81). Exploring individualized disease propensity, CHD phenotypes, T2D phenotypes, comorbid phenotypes, and metabolically healthy phenotypes were found within obesity and NAFLD. Conclusions: The adaptive k-nearest neighbors algorithm allowed an individual-centric assessment of each individual’s metabolic phenotype moving beyond discrete categorizations of body composition. Within obesity and NAFLD, this may help in identifying which comorbidities a patient may develop and conse- quently enable optimization of treatment. Funding agencies: Pfizer Inc.

The aim of this study was to test whether bilinear and nonlinear effective connectivity (EC) measures of working memory fMRI data can differentiate between patients with schizophrenia (SZ) and healthy controls (HC). We applied bilinear and nonlinear Dynamic Causal Modeling (DCM) for the analysis of verbal working memory in 16 SZ and 21 HC. The connection strengths with nonlinear modulation between the dorsolateral prefrontal cortex (DLPFC) and the ventral tegmental area/substantia nigra (VTA/SN) were evaluated. We used Bayesian Model Selection at the group and family levels to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging was used to assess the connection strengths with nonlinear modulation. The DCM analyses revealed that SZ and HC used different bilinear networks despite comparable behavioral performance. In addition, the connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area showed differences between SZ and HC. The adoption of different functional networks in SZ and HC indicated neurobiological alterations underlying working memory performance, including different connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area. These novel findings may increase our understanding of connectivity in working memory in schizophrenia.

Purpose To propose and evaluate a new automated method for the identification of new/enlarging multiple sclerosis (MS) lesions on subtracted images (SI). The subtraction of serially acquired images has shown great potential in assessing new/enlarging brain magnetic resonance imaging (MRI) lesions in MS patients. However, this approach relies on the manual definition of lesions, which is labor-intensive and subject to operator-dependent variability. Materials and Methods An overestimated mask of candidate SI lesions was created and then these hyperintense voxel clusters were filtered using specific constraints for extent, shape, and intensity. The method was tested on normal and pathological MRI datasets. Results The automated method did not detect hyperintense voxels on SI of healthy controls. SI lesions were identified manually and automatically in a multicenter MS dataset of 19 patients with paired MRI over 36 weeks. Sensitivity of the method was high (0.91) and in agreement with the results of manually defined SI lesions (Cohen's k = 0.82, 95% confidence interval [CI]: 0.77–0.87). On a second multicenter MS dataset of 103 patients with paired MRI over 76 weeks, the number of SI lesions detected automatically correlated with the number of gadolinium-enhancing lesions (r = 0.74). Conclusion The proposed method is robust, accurate, and sensitive and may be used with confidence in Phase II MS trials. J. Magn. Reson. Imaging 2014;39:1543–1549. © 2013 Wiley Periodicals, Inc.

Objectives To investigate changes in the Apparent Diffusion Coefficient (ADC) using diffusion-weighted imaging (DWI) in men on active surveillance for prostate cancer taking dutasteride 0.5 mg or placebo. Methods We analysed 37 men, randomised to 6 months of daily dutasteride (n = 18) or placebo (n = 19), undergoing 3T multi-parametric Magnetic Resonance Imaging (mpMRI) scans at baseline and 6 months. Images were reviewed blind to treatment allocation and clinical information. Mean ADC of peripheral (PZ) and transition (TZ) zones, and MR-suspicious lesions were compared between groups over 6 months. Conspicuity was defined as the PZ divided by tumour ADC, and its change over 6 months was assessed. Results A decrease in mean conspicuity in the dutasteride group (but not the controls) was seen over 6 months (1.54 vs 1.38; p = 0.025). Absolute changes in ADC and conspicuity were significantly different between placebo and dutasteride groups at 6 months: (-0.03 vs 0.08, p = 0.033) and (0.11 vs –0.16, p = 0.012), as were percentage changes in the same parameters: (-2.27% vs 8.56% p = 0.048) and (9.25% vs -9.89% p = 0.013). Conclusions Dutasteride was associated with increased tumour ADC and reduced conspicuity. A lower threshold for triggering biopsy might be considered in men on dutasteride undergoing mpMRI for prostate cancer. Key points • Dutasteride increases ADC and reduces conspicuity in small mpMRI-visible prostate cancers. • Knowledge of dutasteride exposure is important in the interpretation of prostate mpMRI. • A lower threshold for triggering biopsy may be appropriate on dutasteride.

International audience; PURPOSE: Dutasteride, which is licensed for symptomatic benign prostatic hyperplasia, has been associated with a lower progression rate of low risk prostate cancer. We evaluated the effect of dutasteride on prostate cancer volume as assessed by T2-weighted magnetic resonance imaging.MATERIALS AND METHODS: In this randomized, double-blind, placebo controlled trial, men with biopsy proven, low-intermediate risk prostate cancer (up to Gleason 3 + 4 and PSA up to 15 ng/ml) who had visible lesion of 0.2 ml or greater on T2-weighted magnetic resonance imaging sequences were randomized to daily dutasteride 0.5 mg or placebo for 6 months. Lesion volume was assessed at baseline, and 3 and 6 months with image guided biopsy to the lesion at study exit. The primary end point was the percent reduction in lesion volume over 6 months. This trial was registered with the European Clinical Trials register (EudraCT 2009-102405-18).RESULTS: A total of 42 men were recruited between June 2010 and January 2012. In the dutasteride group, the average volumes at baseline and 6 months were 0.55 and 0.38 ml, respectively and the average reduction was 36%. In the placebo group, the average volumes at baseline and 6 months were 0.65 and 0.76 ml, respectively, and the average reduction was -12%. The difference in percent reductions between the groups was 48% (95% CI 27.4-68.3, p

To evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for characterising nasopharyngeal carcinoma (NPC). Forty-five newly diagnosed NPC patients were recruited. The initial enhancement rate (E R ), contrast transfer rate (k ep ), elimination rate (k el ), maximal enhancement (MaxEn) and initial area under the curve (iAUC) were calculated from semiquantitative analysis. The K trans (volume transfer constant), v e (volume fraction) and k ep were calculated from quantitative analysis. Student’s t-test was used to evaluate the differences among tumour stages. Pearson’s correlation between the two sets of k ep was performed. Comparing tumours of T1/2 stage (n = 18) and T3/4 stage (n = 27), MaxEn (P = 0.030) and iAUC (P = 0.039) were both significantly different; however, the iAUC was the only independent variable with 69.6 % sensitivity and 76.5 % specificity respectively; v e was also significantly different (P = 0.010) with 69.6 % sensitivity and 70.6 % specificity respectively. No significant difference was found among N stages. The two sets of k ep s were highly correlated (r = 0.809, P

Item does not contain fulltext Patterns of brain atrophy measured by magnetic resonance structural imaging have been utilized as significant biomarkers for diagnosis of Alzheimer's disease (AD). However, brain atrophy is variable across patients and is non-specific for AD in general. Thus, automatic methods for AD classification require a large number of structural data due to complex and variable patterns of brain atrophy. In this paper, we propose an incremental method for AD classification using cortical thickness data. We represent the cortical thickness data of a subject in terms of their spatial frequency components, employing the manifold harmonic transform. The basis functions for this transform are obtained from the eigenfunctions of the Laplace-Beltrami operator, which are dependent only on the geometry of a cortical surface but not on the cortical thickness defined on it. This facilitates individual subject classification based on incremental learning. In general, methods based on region-wise features poorly reflect the detailed spatial variation of cortical thickness, and those based on vertex-wise features are sensitive to noise. Adopting a vertex-wise cortical thickness representation, our method can still achieve robustness to noise by filtering out high frequency components of the cortical thickness data while reflecting their spatial variation. This compromise leads to high accuracy in AD classification. We utilized MR volumes provided by Alzheimer's Disease Neuroimaging Initiative (ADNI) to validate the performance of the method. Our method discriminated AD patients from Healthy Control (HC) subjects with 82% sensitivity and 93% specificity. It also discriminated Mild Cognitive Impairment (MCI) patients, who converted to AD within 18 months, from non-converted MCI subjects with 63% sensitivity and 76% specificity. Moreover, it showed that the entorhinal cortex was the most discriminative region for classification, which is consistent with previous pathological findings. In comparison with other classification methods, our method demonstrated high classification performance in both categories, which supports the discriminative power of our method in both AD diagnosis and AD prediction.

Here we report the first multi-center clinical trial in Alzheimer's disease (AD) using fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) measures of brain glucose metabolism as the primary outcome. We contrasted effects of 12 months treatment with the PPARγ agonist Rosiglitazone XR versus placebo in 80 mild to moderate AD patients. Secondary objectives included testing for reduction in the progression of brain atrophy and improvement in cognition. Active treatment was associated with a sustained but not statistically significant trend from the first month for higher mean values in Kiindex and CMRgluindex, novel quantitative indices related to the combined forward rate constant for [18F]FDG uptake and to the rate of cerebral glucose utilization, respectively. However, neither these nor another analytical approach recently validated using data from the Alzheimer's Disease Neuroimaging Initiative indicated that active treatment decreased the progression of decline in brain glucose metabolism. Rates of brain atrophy were similar between active and placebo groups and measures of cognition also did not suggest clear group differences. Our study demonstrates the feasibility of using [18F]FDG-PET as part of a multi-center therapeutics trial. It suggests that Rosiglitazone is associated with an early increase in whole brain glucose metabolism, but not with any biological or clinical evidence for slowing progression over a 1 year follow up in the symptomatic stages of AD.

APOE epsilon4 is the best-established genetic risk factor for sporadic Alzheimer's disease (AD). However, while homozygotes show greater disease susceptibility and earlier age of onset than heterozygotes, they may not show faster rates of clinical progression. We hypothesize that there are differential APOE epsilon4 allele-load dependent influences on neuropathology across the brain. Our aim was to define the relationship between APOE epsilon4 allele load and regionally-specific brain cortical atrophy in Alzheimer's Disease (AD). For this reason voxel-based morphometry (VBM) was performed using T1-weighted MR images from 83 AD patients, contrasting regional cortical grey matter by APOE epsilon4 load according to either dominant or genotypic models. Patients fulfilled NINCDS-ADRDA criteria and were genotyped for APOE epsilon4 (15 epsilon4/epsilon4, 39 epsilon4/- and 29-/-). We observed that grey matter volume (GMV) decreased additively with increasing allele load in the medial (MTL) and anterior temporal lobes bilaterally. By contrast, a 2 degree-of-freedom genotypic model suggested a dominant effect of the APOE epsilon4 allele in the left temporal lobe. Brain regions showing a significant APOE epsilon4 allele load effect on GMV in AD included only some of those typically described as having greatest amyloid plaque deposition and atrophy. Temporal regions appeared to show a dominant effect of APOE epsilon4 allele load instead of the additive effect previously strongly associated with age of onset. Regional variations with allele load may be related to different mechanisms for effects of APOE epsilon4 load on susceptibility and disease progression.

Introduction: 18 FDG Positron Emission Tomography/Computerised Tomography (PET/CT) imaging may be a useful tool to study lung inflammation in Chronic Obstructive Pulmonary Disease (COPD). Method: The aim of this study was to establish the optimum protocol for 18 FDG-PET/CT imaging of lung inflammation in COPD in combination with quantitative CT analysis of emphysema. 20 moderate-to-severe COPD patients underwent dynamic PET imaging combined with blood sampling to determine the localised plasma activity time curve twice, 4 weeks apart. Patlak analysis of the time-activity curves for CT - derived lung lobes allowed us to generate images of slope (influx constant Ki) and intercept (initial volume of distribution). Results: The signal from PET lung imaging was reproducible as corroborated by Bland Altman plotting (fig 1a). Interestingly the rate of uptake of the tracer as a marker of lung inflammation is related to lung density as measured by full inspiratory phase of the CT scanning (p value

Introduction and aims: Although primarily a lung disease, chronic obstructive pulmonary disease (COPD) is now recognised to have extra-pulmonary effects on distant organs, the “systemic effects” and co-morbidities of COPD. Aim of this study was to quantify vascular inflammation in 20 COPD ex-smokers and 4 healthy controls (non-smokers) using combined 18F-labelled fluorodeoxyglucose positron emission tomography/ computerised tomography(18FDG PET/CT) scan. Methodology: We quantified vascular inflammation in the above subjects. Region of interests (ROIs) were drawn around the aorta and the mean and maximum aortic standardised uptake values (SUVs) were obtained from the pixel activity within each ROIs at 50 minutes scan time-point. This was correlated with systemic markers of inflammation (C-reactive protein, fibrinogen and neutrophil count). Results: COPD patients had higher levels of systemic inflammatory markers and showed a non-significant increase in mean aortic SUV than the healthy controls (COPD: 2.59 ± 0.42; Control: 2.28 ± 0.43, p =0.189) (Fig 1b). There was a significant positive correlation between aortic inflammation quantified by SUV mean and serum C-reactive protein (CRP) in combined group of COPD and controls (r= 0.674, p=0.01) (Fig 1a). Conclusion: Compared to healthy controls the COPD group showed evidence of enhanced systemic inflammation and may also have increased vascular specific inflammation.

Objective\ud \ud Individuals carrying rare, but biologically informative genetic variants provide a unique opportunity to model major mental illness and inform understanding of disease mechanisms. The rarity of such variations means that their study involves small group numbers, however they are amongst the strongest known genetic risk factors for major mental illness and are likely to have large neural effects. DISC1 (Disrupted in Schizophrenia 1) is a gene containing one such risk variant, identified in a single Scottish family through its disruption by a balanced translocation of chromosomes 1 and 11; t(1;11) (q42.1;q14.3).\ud Method\ud \ud Within the original pedigree, we examined the effects of the t(1;11) translocation on white matter integrity, measured by fractional anisotropy (FA). This included family members with (n = 7) and without (n = 13) the translocation, along with a clinical control sample of patients with psychosis (n = 34), and a group of healthy controls (n = 33).\ud Results\ud \ud We report decreased white matter integrity in five clusters in the genu of the corpus callosum, the right inferior fronto-occipital fasciculus, acoustic radiation and fornix. Analysis of the mixed psychosis group also demonstrated decreased white matter integrity in the above regions. FA values within the corpus callosum correlated significantly with positive psychotic symptom severity.\ud Conclusions\ud \ud We demonstrate that the t(1;11) translocation is associated with reduced white matter integrity in frontal commissural and association fibre tracts. These findings overlap with those shown in affected patients with psychosis and in DISC1 animal models and highlight the value of rare but biologically informative mutations in modeling psychosis.

International audience; OBJECTIVE: To evaluate the percentage change in volume of prostate cancer, as assessed by T2-weighted MRI, following exposure to dutasteride (Avodart) 0.5mg daily for six months. PATIENTS AND METHODS: MRI in Primary Prostate cancer after Exposure to Dutasteride (MAPPED) is a double-blind, placebo-controlled trial, supported by GlaxoSmithKline (GSK). Men with prostate cancer suitable for active surveillance (low-intermediate risk prostate cancer on biopsy), and a visible lesion on T2-weighted MRI of at least 0.2 cc, were eligible for consideration. Forty-two men were randomised to 6 months of daily dutasteride 0.5mg or placebo. Multi-parametric MRI (mpMRI) scans were performed at baseline, 3 and 6 months. The percentage changes in cancer volume over time will be compared between the dutasteride and placebo groups. Planned analyses will examine the association between tumour volume and characteristics (perfusion and contrast washout) as seen on mpMRI, HistoScan ultrasound and biopsy histopathology in both groups. DISCUSSION: MAPPED is the first randomised controlled trial to use mpMRI to look at the effect of dutasteride on the volume of prostate cancer. If dutasteride is shown to reduce the volume of prostate cancer, it might be considered as an adjunct for men on active surveillance. Analysis of the placebo arm will allow us to comment on the short-term natural variability of the MR appearance in men who are not receiving any treatment. CONCLUSION: MAPPED will evaluate the short-term effect of dutasteride on prostate cancer volume, as assessed by mpMRI, in men undergoing active surveillance for low or intermediate risk prostate cancer. The study completed recruitment in January 2012.

Diffusion imaging is a promising marker of microstructural damage in neurodegenerative disorders, but interpretation of its relationship with underlying neuropathology can be complex. Here, we examined both volumetric and brain microstructure abnormalities in 13 amnestic patients with mild cognitive impairment (MCI), who progressed to probable Alzheimer's disease (AD) no earlier than 2 years after baseline scanning, in order to focus on early, and hence more sensitive, imaging markers. We compared them to 22 stable amnestic MCI patients with similar cognitive performance and episodic memory impairment but who did not show progression of symptoms for at least 3 years. Significant group differences were mainly found in the volume and microstructure of the left hippocampus, while white matter group differences were also found in the body of the fornix, left fimbria, and superior longitudinal fasciculus (SLF). Diffusion index abnormalities in the SLF were the sign of a subtle microstructural injury not detected by standard atrophy measures in the corresponding gray matter regions. The microstructural measure obtained in the left hippocampus using diffusion imaging showed the most substantial differences between the two groups and was the best single predictor of future progression to AD. An optimal prediction model (91% accuracy, 85% sensitivity, 96% specificity) was obtained by combining MRI measures and CSF protein biomarkers. These results highlight the benefit of using the information of brain microstructural damage, in addition to traditional gray matter volume, to detect early, subtle abnormalities in MCI prior to clinical progression to probable AD and, in combination with CSF markers, to accurately predict such progression.

Defining cases and controls on the basis of biomarkers rather than clinical diagnosis may reduce sample sizes required for genetic studies. The aim of this study was to assess whether characterizing case/control status on the basis of cerebrospinal fluid (CSF) profile would increase power to replicate known genetic associations for Alzheimer's disease (AD). Independent of clinical diagnosis, Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects with 2 CSF biomarkers for AD (Aβ1-42 < 192 pg/mL and tau phosphorylated at threonine 181 (p-tau) > 23 pg/mL, "CSF-positive") were compared with those without CSF evidence for AD (Aβ1-42 > 192 pg/mL and 181-phosphorylated tau < 23 pg/mL, "CSF-negative"). Minor allele frequency (MAF) and odds ratios (ORs) between these 2 groups were calculated for 7 single-nucleotide polymorphisms (SNPs) of interest. Two hundred thirty-two individuals were CSF-positive and 94 CSF-negative. There were no differences in age (74.7 ± 7.2 vs. 75.0 ± 6.5 years, p = 0.7), but significant differences in Mini Mental State Examination (MMSE) (25.9 ± 2.6 vs. 28.2 ± 1.7, p < 0.001) between the CSF-positive and CSF-negative groups. Significant differences in MAF (p < 0.05, uncorrected) were seen for CR1 (rs1408077; OR, 1.59; 95% confidence interval [CI], 1.01-2.49), PICALM (rs541458; OR, 0.68, 95% CI, 0.47-0.98), TOMM40 (rs2075650; OR, 4.30; 95% CI, 2.61-7.06); and possession of 1 or more APOE ε4 alleles (OR, 9.84; 95% CI, 5.48-17.67). These results suggest that using biomarkers of AD pathology to define case and control status may increase power in genetic association studies

Background:There is limited evidence that imaging biomarkers can predict subsequent response to therapy. Such prognostic and/or predictive biomarkers would facilitate development of personalised medicine. We hypothesised that pre-treatment measurement of the heterogeneity of tumour vascular enhancement could predict clinical outcome following combination anti-angiogenic and cytotoxic chemotherapy in colorectal cancer (CRC) liver metastases.Methods:Ten patients with 26 CRC liver metastases had two dynamic contrast-enhanced MRI (DCE-MRI) examinations before starting first-line bevacizumab and FOLFOX-6. Pre-treatment biomarkers of tumour microvasculature were computed and a regression analysis was performed against the post-treatment change in tumour volume after five cycles of therapy. The ability of the resulting linear model to predict tumour shrinkage was evaluated using leave-one-out validation. Robustness to inter-visit variation was investigated using data from a second baseline scan.Results:In all, 86% of the variance in post-treatment tumour shrinkage was explained by the median extravascular extracellular volume (v e), tumour enhancing fraction (E F), and microvascular uniformity (assessed with the fractal measure box dimension, d 0) (R 2 0.86, P0.00005). Other variables, including baseline volume were not statistically significant. Median prediction error was 12%. Equivalent results were obtained from the second scan.Conclusion:Traditional image analyses may over-simplify tumour biology. Measuring microvascular heterogeneity may yield important prognostic and/or predictive biomarkers. © 2011 Cancer Research UK All rights reserved.

To assess whether single-time-point and longitudinal volumetric magnetic resonance (MR) imaging measures provide predictive prognostic information in patients with amnestic mild cognitive impairment (MCI).This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Written informed consent was obtained from all participants or the participants' legal guardians. Cross-validated discriminant analyses of MR imaging measures were performed to differentiate 164 Alzheimer disease (AD) cases from 203 healthy control cases. Separate analyses were performed by using data from MR images obtained at one time point or by combining single-time-point measures with 1-year change measures. Resulting discriminant functions were applied to 317 MCI cases to derive individual patient risk scores. Risk of conversion to AD was estimated as a continuous function of risk score percentile. Kaplan-Meier survival curves were computed for risk score quartiles. Odds ratios (ORs) for the conversion to AD were computed between the highest and lowest quartile scores.Individualized risk estimates from baseline MR examinations indicated that the 1-year risk of conversion to AD ranged from 3% to 40% (average group risk, 17%; OR, 7.2 for highest vs lowest score quartiles). Including measures of 1-year change in global and regional volumes significantly improved risk estimates (P = 001), with the risk of conversion to AD in the subsequent year ranging from 3% to 69% (average group risk, 27%; OR, 12.0 for highest vs lowest score quartiles).Relative to the risk of conversion to AD conferred by the clinical diagnosis of MCI alone, MR imaging measures yield substantially more informative patient-specific risk estimates. Such predictive prognostic information will be critical if disease-modifying therapies become available.http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101975/-/DC1.

Amyloid-β accumulation in the brain is thought to be one of the earliest events in Alzheimer's disease, possibly leading to synaptic dysfunction, neurodegeneration and cognitive/functional decline. The earliest detectable changes seen with neuroimaging appear to be amyloid-β accumulation detected by (11)C-labelled Pittsburgh compound B positron emission tomography imaging. However, some individuals tolerate high brain amyloid-β loads without developing symptoms, while others progressively decline, suggesting that events in the brain downstream from amyloid-β deposition, such as regional brain atrophy rates, play an important role. The main purpose of this study was to understand the relationship between the regional distributions of increased amyloid-β and the regional distribution of increased brain atrophy rates in patients with mild cognitive impairment. To simultaneously capture the spatial distributions of amyloid-β and brain atrophy rates, we employed the statistical concept of parallel independent component analysis, an effective method for joint analysis of multimodal imaging data. Parallel independent component analysis identified significant relationships between two patterns of amyloid-β deposition and atrophy rates: (i) increased amyloid-β burden in the left precuneus/cuneus and medial-temporal regions was associated with increased brain atrophy rates in the left medial-temporal and parietal regions; and (ii) in contrast, increased amyloid-β burden in bilateral precuneus/cuneus and parietal regions was associated with increased brain atrophy rates in the right medial temporal regions. The spatial distribution of increased amyloid-β and the associated spatial distribution of increased brain atrophy rates embrace a characteristic pattern of brain structures known for a high vulnerability to Alzheimer's disease pathology, encouraging for the use of (11)C-labelled Pittsburgh compound B positron emission tomography measures as early indicators of Alzheimer's disease. These results may begin to shed light on the mechanisms by which amyloid-β deposition leads to neurodegeneration and cognitive decline and the development of a more specific Alzheimer's disease-specific imaging signature for diagnosis and use of this knowledge in the development of new anti-therapies for Alzheimer's disease.

BACKGROUND Restless legs syndrome (RLS) is a common neurological disorder the pathophysiology of which is incompletely understood. Four studies have examined structural differences between the brains of RLS patients and healthy controls, using voxel-based morphometry (VBM). All 4 studies have provided different results. METHODS Optimized VBM was used to search for structural differences in gray matter density. Sixteen RLS patients naive to dopaminergic drugs and 16 age- and sex-matched controls received structural T1-weighted MR scans. Structural data were analyzed using FSL-VBM. RESULTS No difference in gray matter density was detected between the two groups (voxel-wise significance: no significant voxels at P= .89 (whole brain Family Wise Error (FWE) corrected); no significant voxels at P < .05 (whole brain False Discovery Rate (FDR) corrected; smallest achievable FDR threshold .99). CONCLUSION/DISCUSSION The present study did not replicate (confirm) previous findings of structural brain changes in RLS, but instead supported the findings of a recent study showing a lack of gray matter alteration in an elderly RLS population. More specifically, the results do not support neuronal loss as an underlying disease mechanism in RLS. Potential limitations in the application of VBM are also discussed.

Pharmacokinetic parameters from dynamic contrast-enhanced MRI (DCE-MRI) were used to assess the perfusion effects due to treatment response using a tyrosine kinase inhibitor. A Bayesian hierarchical model (BHM) is proposed, as an alternative to voxel-wise estimation procedures, to test for a treatment effect while explicitly modeling known sources of variability.Nine subjects from a randomized, blinded, placebo-controlled, multicenter, phase II study of lapatinib were examined before and after treatment. Kinetic parameters were estimated, with an extended compartmental model and subject-specific arterial input function, on a voxel-by-voxel basis.The group treated with lapatinib had a decrease in median K(trans) of 0.17 min⁻¹, when averaged across all voxels in the tumor ROIs, compared with no change in the placebo group based on nonlinear regression. A hypothesis test of equality between pre- and posttreatment K (trans) could not be rejected against a one-sided alternative (P = 0.09). Equality between median K(trans) in placebo and lapatinib groups posttreatment could also not be rejected using the BHM (P = 0.32). Across all scans acquired in the study, estimates of K(trans) at one site were greater on average than those at the other site by including a site effect in the BHM. The inter-voxel variability is of similar order (within 15%) when compared to the inter-patient variability.Though the study contained a small number of subjects and no significant difference was found, the Bayesian hierarchical model provided estimates of variability from known sources in the study and confidence intervals for all estimated parameters. We believe the BHM provides a straightforward and thorough interrogation of the imaging data at the level of voxels, patients or sites in this multicenter clinical study.

Replications of the association between APOE-e4 allele load and regional brain atrophy in Alzheimer's disease (AD) patients hold promise for future studies testing relationships between other disease risk gene variants and brain structure. A polymorphism, rs10868366, in the Golgi phosphoprotein 2 gene, GOLM1, was recently identified as an AD risk factor in a genome-wide association study. In a subset of the same AD cohort, we used voxel-based morphometry to test for association between the disease risk genotype and reduced regional gray matter (GM) volume in AD patients (n = 72). A mean 14% reduction in GM volume was observed in the left frontal gyrus with the higher risk GG genotype. A similar association was observed in an independent, dataset of nondemented subjects (n = 278), although with a smaller effect (1%). This replicated association with GM structural variation suggests that GOLM1 polymorphisms may be related to cognitive phenotypes. The greater effect size in AD patients also suggests that the GG genotype could be a risk factor for the expression of cognitive deficits in AD.

MRI time series experiments produce a wealth of information contained in two or three spatial dimensions that evolve over time. Such experiments can, for example, localize brain response to pharmacological stimuli, but frequently the spatiotemporal characteristics of the cerebral response are unknown a priori and variable, and thus difficult to evaluate using hypothesis-based methods alone. Here we used features in the temporal dimension to group voxels with similar time courses based on a nonparametric discrete wavelet transform (DWT) representation of each time course. Applying the DWT to each voxel decomposes its temporal information into coefficients associated with both time and scale. Discarding scales in the DWT that are associated with high-frequency oscillations (noise) provided a straight-forward data reduction step and decreased the computational burden. Optimization-based clustering was then applied to the remaining wavelet coefficients in order to produce a finite number of voxel clusters. This wavelet-based cluster analysis (WCA) was evaluated using two representative classes of MRI neuroimaging experiments. In perfusion-weighted MRI, following occlusion of the middle cerebral artery (MCAO), WCA differentiated healthy tissue and different regions within the ischemic hemisphere. Following an acute cocaine challenge, WCA localized subtle differences in the pharmacokinetic profile of the cerebral response. We conclude that WCA provides a robust method for blind analysis of time series image data.

Item does not contain fulltext Hippocampal injury in the Alzheimer's disease (AD) pathological process is region-specific and magnetic resonance imaging (MRI)-based measures of localized hippocampus (HP) atrophy are known to detect region-specific changes associated with clinical AD, but it is unclear whether these measures provide information that is independent of that already provided by measures of total HP volume. Therefore, this study assessed the strength of association between localized HP atrophy measures and AD-related measures including cerebrospinal fluid (CSF) amyloid beta and tau concentrations, and cognitive performance, in statistical models that also included total HP volume as a covariate. A computational technique termed localized components analysis (LoCA) was used to identify 7 independent patterns of HP atrophy among 390 semiautomatically delineated HP from baseline magnetic resonance imaging of participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among cognitively normal participants, multiple measures of localized HP atrophy were significantly associated with CSF amyloid concentration, while total HP volume was not. In addition, among all participants, localized HP atrophy measures and total HP volume were both independently and additively associated with CSF tau concentration, performance on numerous neuropsychological tests, and discrimination between normal, mild cognitive impairment (MCI), and AD clinical diagnostic groups. Together, these results suggest that regional measures of hippocampal atrophy provided by localized components analysis may be more sensitive than total HP volume to the effects of AD pathology burden among cognitively normal individuals and may provide information about HP regions whose deficits may have especially profound cognitive consequences throughout the AD clinical course. 01 juni 2012