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Trials investigating the role of carbohydrate restriction in the management of glycaemia in type 2 diabetes (T2D) have been confounded by multiple factors, including degree of calorie restriction and dietary protein content, as well as by no clear definition of a low-carbohydrate diet. The present study aimed 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 at the same time as controlling for confounding factors.This was a randomised crossover trial in participants with T2D (HbA1c: 6.6 ± 0.6%, 49 ± 0.9 mmol molTwelve participants completed the study. There were no differences in 24-h and post-prandial sensor glucose concentrations between the 30 and 10%kcal doses (7.4 ± 1.1 mmol LModest changes in dietary carbohydrate content in the absence of weight loss at the same time as keeping dietary protein intake constant do not appear to influence glucose concentrations in people with well-controlled T2D.This study randomised people with T2D to receive five different doses of carbohydrate from 10% to 30% of calories in random order to see what effect it had on their blood glucose. more...

BackgroundMagnetic resonance imaging (MRI) enables direct measurements of muscle volume and quality, allowing for an in-depth understanding of their associations with anthropometric traits, and health conditions. However, it is unclear which muscle measurements: total muscle volume, regional measurements or measurements of muscle quality, such as intermuscular adipose tissue (IMAT) or proton density fat fraction (PDFF), are most informative to detect changes and associations with relevant health outcomes such as sarcopenia and frailty.MethodsWe developed a pipeline to automatically segment and extract image-derived phenotypes (IDPs) including total and regional muscle volumes and measures of muscle quality, and applied it to the neck-to-knee Dixon images in 44,520 UK Biobank participants. We also segmented paraspinal muscle from 2D quantitative MRI to quantify muscle PDFF and iron concentration. We performed linear regression to assess associations with anthropometric and lifestyle factors. We further applied logistic regression to investigate the association between these IDPs and sarcopenia and frailty.ResultsAll muscle measurements were negatively associated with age, waist-to-hip ratio, and Townsend deprivation index, with p-values below the Bonferroni-corrected threshold (p<5.7 × 10−5) while they were positively associated with body mass index, alcohol intake, hand grip strength, physical activity and were significantly higher in men (p<5.7 × 10−5). Additionally, IMAT, (corrected for muscle volume) and paraspinal muscle PDFF were significantly higher in female compared with male participants (p<5.7 × 10−5). In sarcopenia, muscle volume IDPs were most informative, particularly total muscle showing odds ratios (OR) of 0.361 and 95% confidence intervals (CI)= 0.332-0.392,p<5.7 × 10−5, while for frailty, muscle quality was most informative, particularly mid-thigh IMAT/Muscle ratio (OR = 1.328, 95% CI = 1.304-1.353,p<5.7 × 10−5).ConclusionsOur fully automated method enables the quantification of muscle volumes and quality suitable for large population-based studies. While the choice of muscle measurements is important particularly when investigating associations with health conditions, most provide consistent differences relating to the detection of age, sex, body composition and lifestyle changes on muscularity. more...

BackgroundMorphometric image analysis enables the quantification of differences in the shape and size of organs between individuals.MethodsHere we have applied morphometric methods to the study of the liver by constructing surface meshes from liver segmentations from abdominal MRI images in 33,434 participants in the UK Biobank. Based on these three-dimensional mesh vertices, we evaluated local shape variations and modelled their association with anthropometric, phenotypic and clinical conditions, including liver disease and type-2 diabetes.ResultsWe found that age, body mass index, hepatic fat and iron content, as well as, health traits were significantly associated with regional liver shape and size. Interaction models in groups with specific clinical conditions showed that the presence of type-2 diabetes accelerates age-related changes in the liver, while presence of liver fat further increased shape variations in both type-2 diabetes and liver disease.ConclusionsThe results suggest that this novel approach may greatly benefit studies aiming at better categorisation of pathologies associated with acute and chronic clinical conditions. more...

Features extracted from cardiac MRI (CMR) are correlated with cardiovascular disease outcomes such as aneurysm, and have a substantial heritable component. To determine whether disease-relevant measurements are feasible in non-cardiac specific MRI, and to explore their associations with disease outcomes, and genetic and environmental risk factors. We segmented the heart, aorta, and vena cava from abdominal MRI scans using deep learning, and generated six image-derived phenotypes (IDP): heart volume, four aortic and one vena cava cross-sectional areas (CSA), from 44,541 UK Biobank participants. We performed genome- and phenome-wide association studies, and constructed a polygenic risk score for each phenotype. We demonstrated concordance between our IDPs and related IDPs from CMR, the current gold standard. We replicated previous findings related to sex differences and age-related changes in heart and vessel dimensions. We identified a significant association between infrarenal descending aorta CSA and incident abdominal aortic aneurysm, and between heart volume and several cardiovascular disorders. In a GWAS, we identified 72 associations at 59 loci (15 novel). We derived a polygenic risk score for each trait and demonstrated an association with TAA diagnosis, pointing to a potential screening method for individuals at high-risk of this condition. We demonstrated substantial genetic correlation with cardiovascular traits including aneurysms, varicose veins, dysrhythmia, and cardiac failure. Finally, heritability enrichment analysis implicated vascular tissue in the heritability of these traits. Our work highlights the value of non-specific MRI for exploring cardiovascular disease risk in cohort studies. more...

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. more...

The spleen plays a key role in iron homeostasis. It is the largest filter of the blood and performs iron reuptake from old or damaged erythrocytes. Despite this role, spleen iron concentration has not been measured in a large, population-based cohort. In this study, we quantify spleen iron in 41,764 participants of the UK Biobank by using magnetic resonance imaging and provide a reference range for spleen iron in an unselected population. Through genome-wide association study, we identify associations between spleen iron and regulatory variation at two hereditary spherocytosis genes, ANK1 and SPTA1. Spherocytosis-causing coding mutations in these genes are associated with lower reticulocyte volume and increased reticulocyte percentage, while these common alleles are associated with increased expression of ANK1 and SPTA1 in blood and with larger reticulocyte volume and reduced reticulocyte percentage. As genetic modifiers, these common alleles may explain mild spherocytosis phenotypes that have been observed clinically. Our genetic study also identifies a signal that co-localizes with a splicing quantitative trait locus for MS4A7, and we show this gene is abundantly expressed in the spleen and in macrophages. The combination of deep learning and efficient image processing enables non-invasive measurement of spleen iron and, in turn, characterization of genetic factors related to the lytic phase of the erythrocyte life cycle and iron reuptake in the spleen. more...

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 more...

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. more...

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. more...

Image-derived phenotypes of abdominal organs from magnetic resonance imaging reveal variations in volume and shape and may be used to model changes in a normal versus pathological organ and improve diagnosis. Computational atlases of anatomical organs provide many advantages in quantifying and modeling differences in shape and size of organs for population imaging studies. Here we made use of liver segmentations derived from Dixon MRI for 2,730 UK Biobank participants to create 3D liver meshes. We computed the signed distances between a reference and subject-specific meshes to define the surface-to-surface (S2S) phenotype. We employed mass univariate regression analysis to compare the S2S values from the liver meshes to image-derived phenotypes specific to the liver, such as proton density fat fraction and iron concentration while adjusting for age, sex, ethnicity, body mass index and waist-to-hip ratio. Vertex-based associations in the 3D liver mesh were extracted and threshold-free cluster enhancement was applied to improve the sensitivity and stability of the statistical parametric maps. Our findings show that the 3D liver meshes are a robust method for modeling the association between anatomical, anthropometric, and phenotypic variations across the liver. This approach may be readily applied to different clinical conditions as well as extended to other abdominal organs in a larger population. more...

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions. Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy. Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status. We show that these traits have a substantial heritable component (8–44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported. Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits. more...

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 more...

Cardiometabolic diseases are an increasing global health burden. While well established socioeconomic, environmental, behavioural, and genetic risk factors have been identified, our understanding of the drivers and mechanisms underlying these complex diseases remains incomplete. A better understanding is required to develop more effective therapeutic interventions. Magnetic resonance imaging (MRI) has been used to assess organ health in a number of studies, but large-scale population-based studies are still in their infancy. Using 38,683 abdominal MRI scans in the UK Biobank, we used deep learning to systematically quantify parameters from individual organs (liver, pancreas, spleen, kidneys, lungs and adipose depots), and demonstrate that image derived phenotypes (volume, fat and iron content) reflect organ health and disease. We show that these traits have a substantial heritable component (8%-44%), and identify 93 independent genome-wide significant associations, including 3 associations with liver fat and one with liver iron that have not previously been reported, and 73 in traits that have not previously been studied. Overall our work demonstrates the utility of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues of the abdomen, and to generate new insights into the genetic architecture of complex traits. more...

We present an automated method for estimation of proton density fat fraction and iron concentration in the pancreas using both structural and quantitative imaging data present in the UK Biobank abdominal MRI acquisition protocol. Our method relies on automatic segmentation of 3D T1-weighted MRI data using a convolutional neural network and extracting the location of the multi -echo slice through the segmented volume. We finally estimate the fat and iron content in the pancreas using the extracted segmentation as a mask on the multi-echo data. Our segmentation model achieves a mean dice similarity coefficient of 0.842±0.071 on unseen data, which is comparable to the current state of the art for 3D segmentation of the pancreas. The proposed method is efficient and robust and enables an enhanced analysis of spatial distribution of proton density fat fraction and iron concentration over the current practice of manually placing regions of interest on often ambiguous multi-echo data. more...

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. more...

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. more...

OBJECTIVES: The ATTIS study aimed to investigate whether substituting almonds for typical snacks (high in refined starch, free sugars and saturated fats, and low in fibre) influenced cardiometabolic risk factors. Primary outcomes, endothelial function and liver fat, were measured in healthy adults aged 30–70 y who were habitual snackers and at moderate risk of developing cardiovascular disease (CVD). It was hypothesized that snacking on almonds would improve endothelial function and decrease liver fat. METHODS: Following a 2-week run-in period consuming control snacks, a 6-week parallel arm trial was conducted where participants were randomized to isoenergetic treatments: 1) control snacks (mini-muffins) replicating an average snack nutrient profile, calculated from snack foods identified in 4-d food diaries from a national dietary intake database, or 2) dry-roasted whole almonds, providing 20% estimated energy requirement. Endothelial function (via flow-mediated dilation (FMD)); abdominal subcutaneous and visceral fat, and liver, muscle and pancreatic fat (via MRI/MRS); day- and night-time heart rate variability (HRV) and 24 h ambulatory blood pressure (ABP); blood biomarkers of insulin sensitivity and lipid profile; and fecal short chain fatty acids (SCFA) were assessed at baseline and endpoint. A total of 107 participants (75 F, 32 M; mean age 56.2 y, SD 10.4) were randomized and 105 subjects completed the trial. RESULTS: Almonds significantly increased FMD (mean difference 4.1%, 95% CI 2.2, 5.9), the long-phase HRV index, night-time very-low frequency power (mean difference 337 ms(2), 95% CI 12, 661) and plasma oleic acid levels (mean difference 228 μmol, 95% CI 7, 449) relative to control adjusted for baseline BMI and baseline dependent outcome values, but there were no treatment differences in ABP and subcutaneous, visceral, liver, muscle and pancreatic fat. Plasma LDL cholesterol levels were significantly decreased by almonds (mean difference −0.25 mmol/L, 95% CI −0.45, −0.04), but no differences were found in other blood lipids, insulin sensitivity, nor fecal SCFA levels. CONCLUSIONS: These novel findings suggest almonds may be cardioprotective by increasing availability of nitric oxide and improving cardiac autonomic function, in addition to their well-established LDL cholesterol-lowering properties. FUNDING SOURCES: Almond Board of California. more...

The problem of classifying subjects into risk categories is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of these algorithms is to predict dichotomous responses (e.g. healthy/at risk) based on several features. Similarly to statistical inference models, also ML models are subject to the common problem of class imbalance. Therefore, they are affected by the majority class increasing the false-negative rate. In this paper, we built and evaluated eighteen ML models classifying approximately 4300 female participants from the UK Biobank into three categorical risk statuses based on responses for the discretised visceral adipose tissue values from magnetic resonance imaging. We also examined the effect of sampling techniques on classification modelling when dealing with class imbalance. Results showed that the use of sampling techniques had a significant impact. They not only drove an improvement in predicting patients risk status but also facilitated an increase in the information contained within each variable. Based on domain experts criteria, the three best models for classification were finally identified. These encouraging results will guide further developments of classification models for predicting visceral adipose tissue without the need for a costly scan. more...

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. more...

The serotonergic system is widely distributed throughout the central nervous system. It is well known as a mood regulating system, although it also contributes to many other functions. With resting state functional magnetic resonance imaging (RS-fMRI) it is possible to investigate whole brain functional connectivity. We used this non-invasive neuroimaging technique to measure acute pharmacological effects of the selective serotonin reuptake inhibitor sertraline (75 mg) in 12 healthy volunteers. In this randomized, double blind, placebo-controlled, crossover study, RS-fMRI scans were repeatedly acquired during both visits (at baseline and 3, 5, 7 and 9h after administering sertraline or placebo). Within-group comparisons of voxelwise functional connectivity with ten functional networks were examined (p more...

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. more...

TTo investigate changes in quantitative TRetrospective.Forty men randomized to 6 months of daily dutasteride (n = 20) or placebo (n = 20).Multiparametric 3T MRI at baseline and 6 months. This included a multiecho MR sequence for quantification of the TTwo radiologists reviewed the scans in consensus according to Prostate Imaging Reporting and Data System (PI-RADS v. 2) guidelines.Wilcoxon and Mann-Whitney U-tests, Spearman's correlation.When compared to noncancerous tissue, shorter TThe exposure to antiandrogen therapy did not significantly influence the T4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1646-1653. more...

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. more...

Neuroconductor (https://neuroconductor.org) is an open-source platform for rapid testing and dissemination of reproducible computational imaging software. The goals of the project are to: (i) provide a centralized repository of R software dedicated to image analysis, (ii) disseminate software updates quickly, (iii) train a large, diverse community of scientists using detailed tutorials and short courses, (iv) increase software quality via automatic and manual quality controls, and (v) promote reproducibility of image data analysis. Based on the programming language R (https://www.r-project.org/), Neuroconductor starts with 51 inter-operable packages that cover multiple areas of imaging including visualization, data processing and storage, and statistical inference. Neuroconductor accepts new R package submissions, which are subject to a formal review and continuous automated testing. We provide a description of the purpose of Neuroconductor and the user and developer experience. more...

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. more...

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 more...

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 more...

Though mild cognitive impairment is an intermediate clinical state between healthy aging and Alzheimer's disease (AD), there are very few whole-brain voxel-wise diffusion MRI studies directly comparing changes in healthy control, mild cognitive impairment (MCI) and AD subjects. Here we report whole-brain findings from a comprehensive study of diffusion tensor indices and probabilistic tractography obtained in a very large population of healthy controls, MCI and probable AD subjects. As expected from the literature, all diffusion indices converged to show that the cingulum bundle, the uncinate fasciculus, the entire corpus callosum and the superior longitudinal fasciculus are the most affected white matter tracts in AD. Significant differences between MCI and AD were essentially confined to the corpus callosum. More importantly, we introduce for the first time in a degenerative disorder an application of a recently developed tensor index, the "mode" of anisotropy, as well as probabilistic crossing-fibre tractography. The mode of anisotropy specifies the type of anisotropy as a continuous measure reflecting differences in shape of the diffusion tensor ranging from planar (e.g., in regions of crossing fibres from two fibre populations of similar density or regions of "kissing" fibres) to linear (e.g., in regions where one fibre population orientation predominates), while probabilistic crossing-fibre tractography allows to accurately trace pathways from a crossing-fibre region. Remarkably, when looking for whole-brain diffusion differences between MCI patients and healthy subjects, the only region with significant abnormalities was a region of crossing fibres in the centrum semiovale, showing an increased mode of anisotropy. The only white matter region demonstrating a significant difference in correlations between neuropsychological scores and a diffusion measure (mode of anisotropy) across the three groups was the same region of crossing fibres. Further examination using probabilistic tractography established explicitly and quantitatively that this previously unreported increase of mode and co-localised increase of fractional anisotropy was explained by a relative preservation of motor-related projection fibres (at this early stage of the disease) crossing the association fibres of the superior longitudinal fasciculus. These findings emphasise the benefit of looking at the more complex regions in which spared and affected pathways are crossing to detect very early alterations of the white matter that could not be detected in regions consisting of one fibre population only. Finally, the methods used in this study may have general applicability for other degenerative disorders and, beyond the clinical sphere, they could contribute to a better quantification and understanding of subtle effects generated by normal processes such as visuospatial attention or motor learning. more...

Variational Bayes (VB) has been proposed as a method to facilitate calculations of the posterior distributions for linear models, by providing a fast method for Bayesian inference by estimating the parameters of a factorized approximation to the posterior distribution. Here a VB method for nonlinear forward models with Gaussian additive noise is presented. In the case of noninformative priors the parameter estimates obtained from this VB approach are identical to those found via nonlinear least squares. However, the advantage of the VB method lies in its Bayesian formulation, which permits prior information to be included in a hierarchical structure and measures of uncertainty for all parameter estimates to be obtained via the posterior distribution. Unlike other Bayesian methods VB is only approximate in comparison with the sampling method of MCMC. However, the VB method is found to be comparable and the assumptions made about the form of the posterior distribution reasonable. Practically, the VB approach is substantially faster than MCMC as fewer calculations are required. Some of the advantages of the fully Bayesian nature of the method are demonstrated through the extension of the noise model and the inclusion of Automatic Relevance Determination (ARD) within the VB algorithm. © 2008 IEEE. more...

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. more...

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. more...

Dynamic contrast-enhanced MRI is becoming a standard tool for imaging-based trials of anti-vascular/angiogenic agents in cancer. So far, however, biomarkers derived from DCE-MRI parameter maps have largely neglected the fact that the maps have spatial structure and instead focussed on distributional summary statistics. Such statistics - e.g., biomarkers based on median values - neglect the spatial arrangement of parameters, which may carry important diagnostic and prognostic information. This article describes two types of heterogeneity biomarker that are sensitive to both parameter values and their spatial arrangement. Methods based on Renyi fractal dimensions and geometrical properties are developed, both of which attempt to describe the complexity of DCE-MRI parameter maps. Experiments using simulated data show that the proposed biomarkers are sensitive to changes that distribution-based summary statistics cannot detect and demonstrate that heterogeneity biomarkers could be applied in the drug trial setting. An experiment using 23 DCE-MRI parameter maps of gliomas - a class of tumour that is graded on the basis of heterogeneity - shows that the proposed heterogeneity biomarkers are able to differentiate between low- and high-grade tumours. Magn Reson Med, 2009. © 2009 Wiley-Liss, Inc. more...

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. more...