Analysis of MRI-derived spleen iron in the UK Biobank identifies genetic variation linked to iron homeostasis and hemolysis.

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.

Liver shape analysis using statistical parametric maps at population scale.

BACKGROUND: Morphometric image analysis enables the quantification of differences in the shape and size of organs between individuals. METHODS: Here 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. RESULTS: We 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. CONCLUSIONS: The results suggest that this novel approach may greatly benefit studies aiming at better categorisation of pathologies associated with acute and chronic clinical conditions.

Kidney shape statistical analysis: associations with disease and anthropometric factors.

BACKGROUND: Organ measurements derived from magnetic resonance imaging (MRI) have the potential to enhance our understanding of the precise phenotypic variations underlying many clinical conditions. METHODS: We applied morphometric methods to study the kidneys by constructing surface meshes from kidney segmentations from abdominal MRI data in 38,868 participants in the UK Biobank. Using mesh-based analysis techniques based on statistical parametric maps (SPMs), we were able to detect variations in specific regions of the kidney and associate those with anthropometric traits as well as disease states including chronic kidney disease (CKD), type-2 diabetes (T2D), and hypertension. Statistical shape analysis (SSA) based on principal component analysis was also used within the disease population and the principal component scores were used to assess the risk of disease events. RESULTS: We show that CKD, T2D and hypertension were associated with kidney shape. Age was associated with kidney shape consistently across disease groups. Body mass index (BMI) and waist-to-hip ratio (WHR) were also associated with kidney shape for the participants with T2D. Using SSA, we were able to capture kidney shape variations, relative to size, angle, straightness, width, length, and thickness of the kidneys, within disease populations. We identified significant associations between both left and right kidney length and width and incidence of CKD (hazard ratio (HR): 0.74, 95% CI: 0.61-0.90, p < 0.05, in the left kidney; HR: 0.76, 95% CI: 0.63-0.92, p < 0.05, in the right kidney) and hypertension (HR: 1.16, 95% CI: 1.03-1.29, p < 0.05, in the left kidney; HR: 0.87, 95% CI: 0.79-0.96, p < 0.05, in the right kidney). CONCLUSIONS: The results suggest that shape-based analysis of the kidneys can augment studies aiming at the better categorisation of pathologies associated with chronic kidney conditions.

A randomised crossover trial: Exploring the dose-response effect of carbohydrate restriction on glycaemia in people with well-controlled type 2 diabetes.

BACKGROUND: 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. METHODS: This was a randomised crossover trial in participants with T2D (HbA1c: 6.6 ± 0.6%, 49 ± 0.9 mmol mol-1 ) testing five different 6-day eucaloric dietary treatments with varying carbohydrate content (10%, 15%, 20%, 25%, and 30% kcal). Diets exchanged %kcal from carbohydrate with fat, keeping protein constant at 15% kcal. Daily self-weighing was employed to ensure weight stability 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. Glycaemic control was assessed using a continuous glucose monitoring device. RESULTS: Twelve 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 L-1 vs. 7.6 ± 1.3 mmol L-1 [p = 0.28] and 8.1 ± 1.5 mmol L-1 vs. 8.5 ± 1.4 mmol L-1 [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: 0.4-1.1 kg over the 6 days) but adjusting for these differences did not influence the primary or secondary outcomes. CONCLUSIONS: Modest 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. SUMMARY: 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.

Neuroconductor: an R platform for medical imaging analysis.

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.

Ethnic differences in intrahepatic lipid and its association with hepatic insulin sensitivity and insulin clearance between men of black and white ethnicity with early type 2 diabetes.

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 <5 years. They underwent magnetic resonance imaging to quantify IHL, a hyperinsulinemic euglycaemic clamp with [6,6 2 H2 ] glucose infusion to assess hepatic insulin sensitivity and a hyperglycaemic clamp to assess insulin clearance. BWA men had lower IHL than WE men (3.7 [5.3] vs 6.6 [10.6]%, P = 0.03). IHL was inversely associated with basal hepatic insulin sensitivity in WE but not BWA men (BWA: r = -0.01, P = 0.96; WE: r = -0.72, P = 0.006) with a significant interaction by ethnicity (Pinteraction = 0.05); however, IHL was not associated with % suppression of endogenous glucose production by insulin in either ethnicity. IHL showed a trend to an association with insulin clearance in BWA only (BWA: r = -0.42, P = 0.09; WE: r = -0.14, P = 0.58). The lack of association between IHL and hepatic insulin sensitivity in BWA men indicates IHL may play a lesser detrimental role in T2D in BWA men.

Prostate cancer detection using quantitative T2 and T2 -weighted imaging: The effects of 5-alpha-reductase inhibitors in men on active surveillance.

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 < 0.001). 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.

The Effect of Dutasteride on Magnetic Resonance Imaging Defined Prostate Cancer: MAPPED-A Randomized, Placebo Controlled, Double-Blind Clinical Trial.

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 <0.0001). The most common adverse event was deterioration in erectile function, which was 25% in men randomized to dutasteride and 16% in men randomized to placebo. CONCLUSIONS: Dutasteride was associated with a significant reduction in prostate cancer volume on T2-weighted magnetic resonance imaging compared to placebo.

MRI findings in men on active surveillance for prostate cancer: does dutasteride make MRI visible lesions less conspicuous? Results from a placebo-controlled, randomised clinical trial.

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.

Single-dose serotonergic stimulation shows widespread effects on functional brain connectivity.

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<0.005, corrected) using a mixed effects model with cerebrospinal fluid, white matter, motion parameters, heart rate and respiration as covariates. Sertraline induced widespread effects on functional connectivity with multiple networks; the default mode network, the executive control network, visual networks, the sensorimotor network and the auditory network. A common factor among these networks was the involvement of the precuneus and posterior cingulate cortex. Cognitive and subjective measures were taken as well, but yielded no significant treatment effects, emphasizing the sensitivity of RS-fMRI to pharmacological challenges. The results are consistent with the existence of an extensive serotonergic system relating to multiple brain functions with a possible key role for the precuneus and cingulate.

Brain microstructure reveals early abnormalities more than two years prior to clinical progression from mild cognitive impairment to Alzheimer's disease.

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.

Automated identification of brain new lesions in multiple sclerosis using subtraction images.

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]: 0.77­0.87). 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.

MRI assessment of adipose tissue fatty acid composition in the UK Biobank and its association with diet and disease.

OBJECTIVE: This study aimed to assess the fatty acid (FA) composition of abdominal subcutaneous and visceral adipose tissue (ASAT and VAT, respectively) in the UK Biobank imaging cohort (N = 33,823) using magnetic resonance imaging (MRI). METHODS: We measured the fractions of saturated, monounsaturated, and polyunsaturated FA (fSFA, fMUFA, and fPUFA, respectively) in ASAT and VAT from multiecho MRI scans. We selected a subcohort of participants who followed a vegan and an omnivore diet (N = 36) to validate the effect of diet on adipose tissue. In the wider imaging cohort, we examined the relationships between adipose tissue FA composition and various traits related to disease and body size. RESULTS: We measured adipose tissue FA composition for over 33,000 participants, revealing higher fSFA and fPUFA and lower fMUFA in VAT (p < 0.00016). fMUFA and fPUFA were higher in ASAT and lower in VAT for women (p < 0.00016). Vegan participants exhibited lower fSFA in both ASAT and VAT (p < 0.00016). VAT fSFA and fMUFA showed significant associations with disease, as well as anthropometric variables. CONCLUSIONS: This extensive analysis revealed the relationships between adipose tissue FA composition and a range of factors in a diverse population, highlighting the importance of studying body adipose tissue beyond its quantity.

Precision MRI phenotyping of muscle volume and quality at a population scale.

Introduction: Magnetic 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 volume measurements: total muscle volume, regional measurements, measurements of muscle quality: intermuscular adipose tissue (IMAT) or proton density fat fraction (PDFF), are most informative and associate with relevant health conditions such as dynapenia and frailty. Methods: We have measured image-derived phenotypes (IDPs) including total and regional muscle volumes and measures of muscle quality, derived from the neck-to-knee Dixon images in 44,520 UK Biobank participants. We further segmented paraspinal muscle from 2D quantitative MRI to quantify muscle PDFF and iron concentration. We defined dynapenia based on grip strength below sex-specific cut-off points and frailty based on five criteria (weight loss, exhaustion, grip strength, low physical activity and slow walking pace). We used logistic regression to investigate the association between muscle volume and quality measurements and dynapenia and frailty. Results: Muscle volumes were significantly higher in male compared with female participants, even after correcting for height while, IMAT (corrected for muscle volume) and paraspinal muscle PDFF were significantly higher in female compared with male participants. From the overall cohort, 7.6% (N = 3,261) were identified with dynapenia, and 1.1% (N = 455) with frailty. Dynapenia and frailty were positively associated with age and negatively associated with physical activity levels. Additionally, reduced muscle volume and quality measurements were associated with both dynapenia and frailty. In dynapenia, muscle volume IDPs were most informative, particularly total muscle exhibiting odds ratios (OR) of 0.392, while for frailty, muscle quality was found to be most informative, in particular thigh IMAT volume indexed to height squared (OR = 1.396), both with p-values below the Bonferroni-corrected threshold (p<8.8×10-5). Conclusion: Our fully automated method enables the quantification of muscle volumes and quality suitable for large population-based studies. For dynapenia, muscle volumes particularly those including greater body coverage such as total muscle are the most informative, whilst, for frailty, markers of muscle quality were the most informative IDPs. These results suggest that different measurements may have varying diagnostic values for different health conditions.

Genetic Evidence for Distinct Biological Mechanisms That Link Adiposity to Type 2 Diabetes: Toward Precision Medicine.

We aimed to unravel the mechanisms connecting adiposity to type 2 diabetes. We used MR-Clust to cluster independent genetic variants associated with body fat percentage (388 variants) and BMI (540 variants) based on their impact on type 2 diabetes. We identified five clusters of adiposity-increasing alleles associated with higher type 2 diabetes risk (unfavorable adiposity) and three clusters associated with lower risk (favorable adiposity). We then characterized each cluster based on various biomarkers, metabolites, and MRI-based measures of fat distribution and muscle quality. Analyzing the metabolic signatures of these clusters revealed two primary mechanisms connecting higher adiposity to reduced type 2 diabetes risk. The first involves higher adiposity in subcutaneous tissues (abdomen and thigh), lower liver fat, improved insulin sensitivity, and decreased risk of cardiometabolic diseases and diabetes complications. The second mechanism is characterized by increased body size and enhanced muscle quality, with no impact on cardiometabolic outcomes. Furthermore, our findings unveil diverse mechanisms linking higher adiposity to higher disease risk, such as cholesterol pathways or inflammation. These results reinforce the existence of adiposity-related mechanisms that may act as protective factors against type 2 diabetes and its complications, especially when accompanied by reduced ectopic liver fat.

Dynamic contrast-enhanced magnetic resonance imaging for characterising nasopharyngeal carcinoma: comparison of semiquantitative and quantitative parameters and correlation with tumour stage.

OBJECTIVES: To evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for characterising nasopharyngeal carcinoma (NPC). METHODS: 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. RESULTS: 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 < 0.001). Forty-three patients had chemoradiation, one palliative chemotherapy and one radiotherapy only. In the four patients with poor outcome, k el, E R, MaxEn and iAUC tended to be higher. CONCLUSIONS: Neovasculature in higher T stage NPC exhibits some parameters of increased permeability and perfusion. Thus, DCE-MRI may be helpful as an adjunctive technique in evaluating NPC. KEY POINTS: • The correct assessment of nasopharyngeal carcinoma (NPC) is important for planning treatment. • Neovasculature in higher T stage NPC exhibits increased permeability and perfusion. • Correlation between quantitative and semi-quantitative analysis validates the robustness of DCE-MRI. • DCE-MRI may be helpful as an adjunctive parameter in evaluating NPC.

Artifact-free fat-water separation in Dixon MRI using deep learning.

Chemical-shift encoded MRI (CSE-MRI) is a widely used technique for the study of body composition and metabolic disorders, where derived fat and water signals enable the quantification of adipose tissue and muscle. The UK Biobank is acquiring whole-body Dixon MRI (a specific implementation of CSE-MRI) for over 100,000 participants. Current processing methods associated with large whole-body volumes are time intensive and prone to artifacts during fat-water separation performed by the scanner, making quantitative analysis challenging. The most common artifacts are fat-water swaps, where the labels are inverted at the voxel level. It is common for researchers to discard swapped data (generally around 10%), which is wasteful and may lead to unintended biases. Given the large number of whole-body Dixon MRI acquisitions in the UK Biobank, thousands of swaps are expected to be present in the fat and water volumes from image reconstruction performed on the scanner. If they go undetected, errors will propagate into processes such as organ segmentation, and dilute the results in population-based analyses. There is a clear need for a robust method to accurately separate fat and water volumes in big data collections like the UK Biobank. We formulate fat-water separation as a style transfer problem, where swap-free fat and water volumes are predicted from the acquired Dixon MRI data using a conditional generative adversarial network, and introduce a new loss function for the generator model. Our method is able to predict highly accurate fat and water volumes free from artifacts in the UK Biobank. We show that our model separates fat and water volumes using either single input (in-phase only) or dual input (in-phase and opposed-phase) data, with the latter producing superior results. Our proposed method enables faster and more accurate downstream analysis of body composition from Dixon MRI in population studies by eliminating the need for visual inspection or discarding data due to fat-water swaps. Supplementary Information: The online version contains supplementary material available at 10.1186/s40537-022-00677-1.

Abdominal imaging associates body composition with COVID-19 severity.

The main drivers of COVID-19 disease severity and the impact of COVID-19 on long-term health after recovery are yet to be fully understood. Medical imaging studies investigating COVID-19 to date have mostly been limited to small datasets and post-hoc analyses of severe cases. The UK Biobank recruited recovered SARS-CoV-2 positive individuals (n = 967) and matched controls (n = 913) who were extensively imaged prior to the pandemic and underwent follow-up scanning. In this study, we investigated longitudinal changes in body composition, as well as the associations of pre-pandemic image-derived phenotypes with COVID-19 severity. Our longitudinal analysis, in a population of mostly mild cases, associated a decrease in lung volume with SARS-CoV-2 positivity. We also observed that increased visceral adipose tissue and liver fat, and reduced muscle volume, prior to COVID-19, were associated with COVID-19 disease severity. Finally, we trained a machine classifier with demographic, anthropometric and imaging traits, and showed that visceral fat, liver fat and muscle volume have prognostic value for COVID-19 disease severity beyond the standard demographic and anthropometric measurements. This combination of image-derived phenotypes from abdominal MRI scans and ensemble learning to predict risk may have future clinical utility in identifying populations at-risk for a severe COVID-19 outcome.

Improving the accuracy of fatty liver index to reflect liver fat content with predictive regression modelling.

BACKGROUND: The fatty liver index (FLI) is frequently used as a non-invasive clinical marker for research, prognostic and diagnostic purposes. It is also used to stratify individuals with hepatic steatosis such as non-alcoholic fatty liver disease (NAFLD), and to detect the presence of type 2 diabetes or cardiovascular disease. The FLI is calculated using a combination of anthropometric and blood biochemical variables; however, it reportedly excludes 8.5-16.7% of individuals with NAFLD. Moreover, the FLI cannot quantitatively predict liver fat, which might otherwise render an improved diagnosis and assessment of fatty liver, particularly in longitudinal studies. We propose FLI+ using predictive regression modelling, an improved index reflecting liver fat content that integrates 12 routinely-measured variables, including the original FLI. METHODS AND FINDINGS: We evaluated FLI+ on a dataset from the UK Biobank containing 28,796 individual estimates of proton density fat fraction derived from magnetic resonance imaging across normal to severe levels and interpolated to align with the original FLI range. The results obtained for FLI+ outperform the original FLI by delivering a lower mean absolute error by approximately 47%, a lower standard deviation by approximately 20%, and an increased adjusted R2 statistic by approximately 49%, reflecting a more accurate representation of liver fat content. CONCLUSIONS: Our proposed model predicting FLI+ has the potential to improve diagnosis and provide a more accurate stratification than FLI between absent, mild, moderate and severe levels of hepatic steatosis.