Voxel-wise body composition analysis using image registration of a three-slice CT imaging protocol: methodology and proof-of-concept studies.

BACKGROUND: Computed tomography (CT) is an imaging modality commonly used for studies of internal body structures and very useful for detailed studies of body composition. The aim of this study was to develop and evaluate a fully automatic image registration framework for inter-subject CT slice registration. The aim was also to use the results, in a set of proof-of-concept studies, for voxel-wise statistical body composition analysis (Imiomics) of correlations between imaging and non-imaging data. METHODS: The current study utilized three single-slice CT images of the liver, abdomen, and thigh from two large cohort studies, SCAPIS and IGT. The image registration method developed and evaluated used both CT images together with image-derived tissue and organ segmentation masks. To evaluate the performance of the registration method, a set of baseline 3-single-slice CT images (from 2780 subjects including 8285 slices) from the SCAPIS and IGT cohorts were registered. Vector magnitude and intensity magnitude error indicating inverse consistency were used for evaluation. Image registration results were further used for voxel-wise analysis of associations between the CT images (as represented by tissue volume from Hounsfield unit and Jacobian determinant) and various explicit measurements of various tissues, fat depots, and organs collected in both cohort studies. RESULTS: Our findings demonstrated that the key organs and anatomical structures were registered appropriately. The evaluation parameters of inverse consistency, such as vector magnitude and intensity magnitude error, were on average less than 3 mm and 50 Hounsfield units. The registration followed by Imiomics analysis enabled the examination of associations between various explicit measurements (liver, spleen, abdominal muscle, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), thigh SAT, intermuscular adipose tissue (IMAT), and thigh muscle) and the voxel-wise image information. CONCLUSION: The developed and evaluated framework allows accurate image registrations of the collected three single-slice CT images and enables detailed voxel-wise studies of associations between body composition and associated diseases and risk factors.

Short-term effects of obesity surgery versus low-energy diet on body composition and tissue-specific glucose uptake: a randomised clinical study using whole-body integrated 18F-FDG-PET/MRI.

AIMS/HYPOTHESIS: Obesity surgery (OS) and diet-induced weight loss rapidly improve insulin resistance. We aim to investigate the impact of either Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) surgery compared with a diet low in energy (low-calorie diet; LCD) on body composition, glucose control and insulin sensitivity, assessed both at the global and tissue-specific level in individuals with obesity but not diabetes. METHODS: In this parallel group randomised controlled trial, patients on a waiting list for OS were randomised (no blinding, sealed envelopes) to either undergo surgery directly or undergo an LCD before surgery. At baseline and 4 weeks after surgery (n=15, 11 RYGB and 4 SG) or 4 weeks after the start of LCD (n=9), investigations were carried out, including an OGTT and hyperinsulinaemic-euglycaemic clamps during which concomitant simultaneous whole-body [18F]fluorodeoxyglucose-positron emission tomography (PET)/MRI was performed. The primary outcome was HOMA-IR change. RESULTS: One month after bariatric surgery and initiation of LCD, both treatments induced similar reductions in body weight (mean ± SD: -7.7±1.4 kg and -7.4±2.2 kg, respectively), adipose tissue volume (7%) and liver fat content (2% units). HOMA-IR, a main endpoint, was significantly reduced following OS (-26.3% [95% CI -49.5, -3.0], p=0.009) and non-significantly following LCD (-20.9% [95% CI -58.2, 16.5). For both groups, there were similar reductions in triglycerides and LDL-cholesterol. Fasting plasma glucose and insulin were also significantly reduced only following OS. There was an increase in glucose AUC in response to an OGTT in the OS group (by 20%) but not in the LCD group. During hyperinsulinaemia, only the OS group showed a significantly increased PET-derived glucose uptake rate in skeletal muscle but a reduced uptake in the heart and abdominal adipose tissue. Both liver and brain glucose uptake rates were unchanged after surgery or LCD. Whole-body glucose disposal and endogenous glucose production were not significantly affected. CONCLUSIONS/INTERPRETATION: The short-term metabolic effects seen 4 weeks after OS are not explained by loss of body fat alone. Thus OS, but not LCD, led to reductions in fasting plasma glucose and insulin resistance as well as to distinct changes in insulin-stimulated glucose fluxes to different tissues. Such effects may contribute to the prevention or reversal of type 2 diabetes following OS. Moreover, the full effects on whole-body insulin resistance and plasma glucose require a longer time than 4 weeks. TRIAL REGISTRATION: ClinicalTrials.gov NCT02988011 FUNDING: This work was supported by AstraZeneca R&D, the Swedish Diabetes Foundation, the European Union's Horizon Europe Research project PAS GRAS, the European Commission via the Marie Sklodowska Curie Innovative Training Network TREATMENT, EXODIAB, the Family Ernfors Foundation, the P.O. Zetterling Foundation, Novo Nordisk Foundation, the Agnes and Mac Rudberg Foundation and the Uppsala University Hospital ALF grants.

Spleen volume is independently associated with non-alcoholic fatty liver disease, liver volume and liver fibrosis.

Non-alcoholic fatty liver disease (NAFLD) can lead to irreversible liver damage manifesting in systemic effects (e.g., elevated portal vein pressure and splenomegaly) with increased risk of deadly outcomes. However, the association of spleen volume with NAFLD and related type 2-diabetes (T2D) is not fully understood. The UK Biobank contains comprehensive health-data of 500,000 participants, including clinical data and MR images of >40,000 individuals. The present study estimated the spleen volume of 37,066 participants through automated deep learning-based image segmentation of neck-to-knee MR images. The aim was to investigate the associations of spleen volume with NAFLD, T2D and liver fibrosis, while adjusting for natural confounders. The recent redefinition and new designation of NAFLD to metabolic dysfunction-associated steatotic liver disease (MASLD), promoted by major organisations of studies on liver disease, was not employed as introduced after the conduct of this study. The results showed that spleen volume decreased with age, correlated positively with body size and was smaller in females compared to males. Larger spleens were observed in subjects with NAFLD and T2D compared to controls. Spleen volume was also positively and independently associated with liver fat fraction, liver volume and the fibrosis-4 score, with notable volumetric increases already at low liver fat fractions and volumes, but not independently associated with T2D. These results suggest a link between spleen volume and NAFLD already at an early stage of the disease, potentially due to initial rise in portal vein pressure.

Overfeeding polyunsaturated fat compared with saturated fat does not differentially influence lean tissue accumulation in individuals with overweight: a randomized controlled trial.

BACKGROUND: Fatty acids may influence lean tissue volume and skeletal muscle function. We previously reported in young lean participants that overfeeding PUFA compared with SFA induced greater lean tissue accumulation despite similar weight gain. OBJECTIVES: In a double-blind randomized controlled trial, we aimed to investigate if the differential effects of overfeeding SFA and PUFA on lean tissue accumulation could be replicated in individuals with overweight and identify potential determinants. Further, using substitution models, we investigated associations between SFA and PUFA concentrations with lean tissue volume in a large population-based sample (UK Biobank). METHODS: Sixty-one males and females with overweight [BMI (kg/m2): 27.3 (interquartile range (IQR), 25.4-29.3); age: 43 (IQR, 36-48)] were overfed SFA (palm oil) or n-6 (ω-6) PUFA (sunflower oil) for 8 wk. Lean tissue was assessed by MRI. We had access to n = 13,849 participants with data on diet, covariates, and MRI measurements of lean tissue, as well as 9119 participants with data on circulating fatty acids in the UK Biobank. RESULTS: Body weight gain mean (SD) was similar in PUFA (2.01 ± 1.90 kg) and SFA (2.31 ± 1.38 kg) groups. Lean tissue increased to a similar extent [0.54 ± 0.93 L and 0.67 ± 1.21 L for PUFA and SFA groups, respectively, with a difference between groups of 0.07 (-0.21, 0.35)]. We observed no differential effects on circulating amino acids, myostatin, or IL-15 and no clear determinants of lean tissue accumulation. Similar nonsignificant results for SFA and PUFA were observed in UK Biobank, but circulating fatty acids demonstrated ambiguous and sex-dependent associations. CONCLUSIONS: Overfeeding SFA or PUFA does not differentially affect lean tissue accumulation during 8 wk in individuals with overweight. A lack of dietary fat type-specific effects on lean tissue is supported by specified substitution models in a large population-based cohort consuming their habitual diet. This trial was registered at clinicaltrials.gov identifier as NCT02211612.

Improved automated tumor segmentation in whole-body 3D scans using multi-directional 2D projection-based priors.

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end-to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

Spatial mapping of tumor heterogeneity in whole-body PET-CT: a feasibility study.

BACKGROUND: Tumor heterogeneity is recognized as a predictor of treatment response and patient outcome. Quantification of tumor heterogeneity across all scales may therefore provide critical insight that ultimately improves cancer management. METHODS: An image registration-based framework for the study of tumor heterogeneity in whole-body images was evaluated on a dataset of 490 FDG-PET-CT images of lung cancer, lymphoma, and melanoma patients. Voxel-, lesion- and subject-level features were extracted from the subjects' segmented lesion masks and mapped to female and male template spaces for voxel-wise analysis. Resulting lesion feature maps of the three subsets of cancer patients were studied visually and quantitatively. Lesion volumes and lesion distances in subject spaces were compared with resulting properties in template space. The strength of the association between subject and template space for these properties was evaluated with Pearson's correlation coefficient. RESULTS: Spatial heterogeneity in terms of lesion frequency distribution in the body, metabolic activity, and lesion volume was seen between the three subsets of cancer patients. Lesion feature maps showed anatomical locations with low versus high mean feature value among lesions sampled in space and also highlighted sites with high variation between lesions in each cancer subset. Spatial properties of the lesion masks in subject space correlated strongly with the same properties measured in template space (lesion volume, R = 0.986, p < 0.001; total metabolic volume, R = 0.988, p < 0.001; maximum within-patient lesion distance, R = 0.997, p < 0.001). Lesion volume and total metabolic volume increased on average from subject to template space (lesion volume, 3.1 ± 52 ml; total metabolic volume, 53.9 ± 229 ml). Pair-wise lesion distance decreased on average by 0.1 ± 1.6 cm and maximum within-patient lesion distance increased on average by 0.5 ± 2.1 cm from subject to template space. CONCLUSIONS: Spatial tumor heterogeneity between subsets of interest in cancer cohorts can successfully be explored in whole-body PET-CT images within the proposed framework. Whole-body studies are, however, especially prone to suffer from regional variation in lesion frequency, and thus statistical power, due to the non-uniform distribution of lesions across a large field of view.

Automatic segmentation of large-scale CT image datasets for detailed body composition analysis.

BACKGROUND: Body composition (BC) is an important factor in determining the risk of type 2-diabetes and cardiovascular disease. Computed tomography (CT) is a useful imaging technique for studying BC, however manual segmentation of CT images is time-consuming and subjective. The purpose of this study is to develop and evaluate fully automated segmentation techniques applicable to a 3-slice CT imaging protocol, consisting of single slices at the level of the liver, abdomen, and thigh, allowing detailed analysis of numerous tissues and organs. METHODS: The study used more than 4000 CT subjects acquired from the large-scale SCAPIS and IGT cohort to train and evaluate four convolutional neural network based architectures: ResUNET, UNET++, Ghost-UNET, and the proposed Ghost-UNET++. The segmentation techniques were developed and evaluated for automated segmentation of the liver, spleen, skeletal muscle, bone marrow, cortical bone, and various adipose tissue depots, including visceral (VAT), intraperitoneal (IPAT), retroperitoneal (RPAT), subcutaneous (SAT), deep (DSAT), and superficial SAT (SSAT), as well as intermuscular adipose tissue (IMAT). The models were trained and validated for each target using tenfold cross-validation and test sets. RESULTS: The Dice scores on cross validation in SCAPIS were: ResUNET 0.964 (0.909-0.996), UNET++ 0.981 (0.927-0.996), Ghost-UNET 0.961 (0.904-0.991), and Ghost-UNET++ 0.968 (0.910-0.994). All four models showed relatively strong results, however UNET++ had the best performance overall. Ghost-UNET++ performed competitively compared to UNET++ and showed a more computationally efficient approach. CONCLUSION: Fully automated segmentation techniques can be successfully applied to a 3-slice CT imaging protocol to analyze multiple tissues and organs related to BC. The overall best performance was achieved by UNET++, against which Ghost-UNET++ showed competitive results based on a more computationally efficient approach. The use of fully automated segmentation methods can reduce analysis time and provide objective results in large-scale studies of BC.

A whole-body diffusion MRI normal atlas: development, evaluation and initial use.

BACKGROUND: Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task. METHODS: Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture. RESULTS: Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information about healthy tissue deviations in an automated tumour segmentation task gave numerical improvements in the segmentation metrics Dice score, sensitivity and precision. CONCLUSIONS: Whole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses.

Diet composition, nutrient substitutions and circulating fatty acids in relation to ectopic and visceral fat depots.

BACKGROUND & AIMS: Short-term randomized trials have demonstrated that replacing saturated fat (SFA) with polyunsaturated fat (PUFA) causes a reduction or prevention of liver fat accumulation, but population-based studies on diet and body fat distribution are limited. We investigated cross-sectional associations between diet, circulating fatty acids and liver fat, visceral adipose tissue (VAT), intermuscular adipose tissue (IMAT) and other fat depots using different energy-adjustment models. METHODS: Sex-stratified analyses of n = 9119 (for serum fatty acids) to 13 849 (for nutrients) participants in UK Biobank were conducted. Fat depots were assessed by MRI, circulating fatty acids by NMR spectroscopy and diet by repeated 24-h recalls. Liver fat, VAT and IMAT were primary outcomes; total adipose tissue (TAT) and abdominal subcutaneous adipose tissue (ASAT) were secondary outcomes. Three a priori defined models were constructed: the all-components model, standard model and leave-one-out model (main model including specified nutrient substitutions). Imiomics (MRI-derived) was used to confirm and visualize associations. RESULTS: In women, substituting carbohydrates and free sugars with saturated fat (SFA) was positively associated with liver fat (ß (95% CI) = 0.19 (0.02, 0.36) and ß (95% CI) = 0.20 (0.05-0.35), respectively) and IMAT (ß (95% CI) = 0.07 (0.00, 0.14) and ß (95% CI) = 0.08 (0.02, 0.13), respectively), whereas substituting animal fat with plant fat was inversely associated with IMAT, ASAT and TAT. In the all-components and standard models, SFA and animal fat were positively associated with liver fat, IMAT and VAT whereas plant fat was inversely associated with IMAT in women. Few associations were observed in men. Circulating polyunsaturated fatty acids (PUFA) were inversely associated with liver fat, IMAT and VAT in both men and women, whereas SFA and monounsaturated fatty acids were positively associated. CONCLUSIONS: Type of dietary fat may be an important determinant of ectopic fat in humans consuming their habitual diet. Plant fat and PUFA should be preferred over animal fat and SFA. This is corroborated by circulating fatty acids and overall consistent through different energy adjustment models. TWITTER SUMMARY: In UK Biobank, intake of saturated- and animal fat were positively whereas biomarkers of polyunsaturated fat were inversely associated with liver-, visceral- and intermuscular fat. Type of dietary fat may be a determinant of ectopic fat, a risk factor for cardiometabolic disease.

Mediating role of atherogenic lipoproteins in the relationship between liver fat and coronary artery calcification.

Non-alcoholic fatty liver disease (NAFLD) is associated with increased secretion of apoB-containing lipoproteins and increased risk of coronary heart disease (CHD). ApoB-containing lipoproteins include low-density lipoproteins (LDLs) and triglyceride-rich lipoproteins (TRLs); and since both LDLs and TRLs are causally related to CHD, they may mediate a portion of the increased risk of atherosclerosis seen in people with NAFLD. In a cohort of 4161 middle aged men and women, we performed mediation analysis in order to quantify the mediating effect of apoB-containing lipoproteins in the relationship between liver fat and atherosclerosis-as measured by coronary artery calcium score (CACS). We found plasma apoB to mediate 17.6% (95% CI 11-24) of the association between liver fat and CACS. Plasma triglycerides and TRL-cholesterol (both proximate measures of TRL particles) mediated 22.3% (95% CI 11-34) and 21.6% (95% CI 10-33) of the association respectively; whereas LDL-cholesterol mediated 5.4% (95% CI 2.0-9.4). In multivariable models, the mediating effect of TRL-cholesterol and plasma triglycerides showed, again, a higher degree of mediation than LDL-cholesterol, corroborating the results seen in the univariable models. In summary, we find around 20% of the association between liver fat and CACS to be mediated by apoB-containing lipoproteins. In addition, we find that TRLs mediate the majority of this effect whereas LDLs mediate a smaller effect. These results explain part of the observed CAD-risk burden for people with NAFLD and further suggest that TRL-lowering may be particularly beneficial to mitigate NAFLD-associated coronary artery disease risk.

Interleukin-33 inhibits glucose uptake in human adipocytes and its expression in adipose tissue is elevated in insulin resistance and type 2 diabetes.

OBJECTIVE: Interleukin-33 (IL-33) is associated with obesity-related inflammation. We aim to investigate IL-33 expression in subcutaneous adipose tissue (SAT) in type 2 diabetes (T2D) subjects and its effects on human adipocyte glucose uptake. METHODS: Expression of IL-33 was analysed in SAT from cohort studies including subjects with and without obesity and T2D and correlated with insulin resistance and obesity markers. Magnetic resonance imaging (MRI) of tissue fat volumes was performed. We investigated the effects of IL-33 treatment on ex vivo adipocyte glucose uptake. RESULTS: T2D subjects had higher IL-33 gene and protein expression in SAT than the control subjects. IL-33 mRNA expression was positively correlated with markers of dysglycemia (e.g. HbA1c), insulin resistance (e.g. HOMA-IR) and adiposity (BMI, visceral adipose tissue volume, liver and pancreas fat %). In multiple linear regression analyses, insulin resistance and T2D status were the strongest predictors of IL-33, independent of BMI. IL-33 mRNA expression was negatively correlated with expression of genes regulating adipocyte glucose uptake, lipid storage, and adipogenesis (e.g.glucose transporter 1 and 4 (GLUT1/4), fatty acid binding protein 4 (FABP4), and PPARG). Additionally, incubation of SAT with IL-33 reduced adipocyte glucose uptake and GLUT4 gene and protein expression. CONCLUSIONS: Our findings suggest that T2D subjects have higher IL-33 gene and protein expressionin SATthan control subjects, which is associated with insulin resistance and reduced gene expression of lipid storage and adipogenesis markers. IL-33 may reduce adipocyte glucose uptake. This opens up a potential pharmacological route for reversing insulin resistance in T2D and prediabetes.

Whole body FDG PET/MR for progression free and overall survival prediction in patients with relapsed/refractory large B-cell lymphomas undergoing CAR T-cell therapy.

BACKGROUND: To find semi-quantitative and quantitative Positron Emission Tomography/Magnetic Resonance (PET/MR) imaging metrics of both tumor and non-malignant lymphoid tissue (bone marrow and spleen) for Progression Free Survival (PFS) and Overall Survival (OS) prediction in patients with relapsed/refractory (r/r) large B-cell lymphoma (LBCL) undergoing Chimeric Antigen Receptor (CAR) T-cell therapy. METHODS: A single-center prospective study of 16 r/r LBCL patients undergoing CD19-targeted CAR T-cell therapy. Whole body 18F-fluorodeoxyglucose (FDG) PET/MR imaging pre-therapy and 3 weeks post-therapy were followed by manual segmentation of tumors and lymphoid tissues. Semi-quantitative and quantitative metrics were extracted, and the metric-wise rate of change (Δ) between post-therapy and pre-therapy calculated. Tumor metrics included maximum Standardized Uptake Value (SUVmax), mean SUV (SUVmean), Metabolic Tumor Volume (MTV), Tumor Lesion Glycolysis (TLG), structural volume (V), total structural tumor burden (Vtotal) and mean Apparent Diffusion Coefficient (ADCmean). For lymphoid tissues, metrics extracted were SUVmean, mean Fat Fraction (FFmean) and ADCmean for bone marrow, and SUVmean, V and ADCmean for spleen. Univariate Cox regression analysis tested the relationship between extracted metrics and PFS and OS. Survival curves were produced using Kaplan-Meier analysis and compared using the log-rank test, with the median used for dichotomization. Uncorrected p-values < 0.05 were considered statistically significant. Correction for multiple comparisons was performed, with a False Discovery Rate (FDR) < 0.05 considered statistically significant. RESULTS: Pre-therapy (p < 0.05, FDR < 0.05) and Δ (p < 0.05, FDR > 0.05) total tumor burden structural and metabolic metrics were associated with PFS and/or OS. According to Kaplan-Meier analysis, a longer PFS was reached for patients with pre-therapy MTV ≤ 39.5 ml, ΔMTV≤1.35 and ΔTLG≤1.35. ΔSUVmax was associated with PFS (p < 0.05, FDR > 0.05), while ΔADCmean was associated with both PFS and OS (p < 0.05, FDR > 0.05). ΔADCmean > 0.92 gave longer PFS and OS in the Kaplan-Meier analysis. Pre-therapy bone marrow SUVmean was associated with PFS (p < 0.05, FDR < 0.05) and OS (p < 0.05, FDR > 0.05). For bone marrow FDG uptake, patient stratification was possible pre-therapy (SUVmean ≤ 1.8). CONCLUSIONS: MTV, tumor ADCmean and FDG uptake in bone marrow unaffected by tumor infiltration are possible PET/MR parameters for prediction of PFS and OS in r/r LBCL treated with CAR T-cells. TRIAL REGISTRATION: EudraCT 2016-004043-36.

An image registration method for voxel-wise analysis of whole-body oncological PET-CT.

Whole-body positron emission tomography-computed tomography (PET-CT) imaging in oncology provides comprehensive information of each patient's disease status. However, image interpretation of volumetric data is a complex and time-consuming task. In this work, an image registration method targeted towards computer-aided voxel-wise analysis of whole-body PET-CT data was developed. The method used both CT images and tissue segmentation masks in parallel to spatially align images step-by-step. To evaluate its performance, a set of baseline PET-CT images of 131 classical Hodgkin lymphoma (cHL) patients and longitudinal image series of 135 head and neck cancer (HNC) patients were registered between and within subjects according to the proposed method. Results showed that major organs and anatomical structures generally were registered correctly. Whole-body inverse consistency vector and intensity magnitude errors were on average less than 5 mm and 45 Hounsfield units respectively in both registration tasks. Image registration was feasible in time and the nearly automatic pipeline enabled efficient image processing. Metabolic tumor volumes of the cHL patients and registration-derived therapy-related tissue volume change of the HNC patients mapped to template spaces confirmed proof-of-concept. In conclusion, the method established a robust point-correspondence and enabled quantitative visualization of group-wise image features on voxel level.

Determinants of hyperglucagonemia in pediatric non-alcoholic fatty liver disease.

Objective: Over the years, non-alcoholic fatty liver (NAFLD) disease has progressed to become the most frequent chronic liver disease in children and adolescents. The full pathology is not yet known, but disease progression leads to cirrhosis and hepatocellular carcinoma. Risk factors included hypercaloric diet, obesity, insulin resistance and genetics. Hyperglucagonemia appears to be a pathophysiological consequence of hepatic steatosis, thus, the hypothesis of the study is that hepatic fat accumulation leads to increased insulin resistance and impaired glucagon metabolism leading to hyperglucagonemia in pediatric NAFLD. Methods: 132 children and adolescents between 10 and 18 years, with varying degrees of obesity, were included in the study. Using Magnetic Resonance Imaging (MRI) average liver fat was determined, and patients were stratified as NAFLD (>5% liver fat content) and non-NAFLD (<5%). All patients underwent a standardized oral glucose tolerance test (OGTT). Additionally, anthropometric parameters (height, weight, BMI, waist circumference, hip circumference) such as lab data including lipid profile (triglycerides, HDL, LDL), liver function parameters (ALT, AST), uric acid, glucose metabolism (fasting insulin and glucagon, HbA1c, glucose 120 min) and indices evaluating insulin resistance (HIRI, SPISE, HOMA-IR, WBISI) were measured. Results: Children and adolescents with NAFLD had significantly higher fasting glucagon values compared to the non-NAFLD cohort (p=0.0079). In the NAFLD cohort univariate analysis of fasting glucagon was associated with BMI-SDS (p<0.01), visceral adipose tissue volume (VAT) (p<0.001), average liver fat content (p<0.001), fasting insulin concentration (p<0.001), triglycerides (p<0.001) and HDL (p=0.034). This correlation equally applied to all insulin indices HOMA-IR, WBISI, HIRI (all p<0.001) and SPISE (p<0.002). Multivariate analysis (R² adjusted 0.509) for the same subgroup identified HIRI (p=0.003) and VAT volume (p=0.017) as the best predictors for hyperglucagonemia. Average liver fat content is predictive in pediatric overweight and obesity but not NAFLD. Conclusions: Children and adolescents with NAFLD have significantly higher fasting plasma glucagon values, which were best predicted by hepatic insulin resistance and visceral adipose tissue, but not average liver fat content.

Erratum for: MIMIR: Deep Regression for Automated Analysis of UK Biobank MRI Scans.

[This corrects the article DOI: 10.1148/ryai.210178.].

ESR2 expression in subcutaneous adipose tissue is related to body fat distribution in women, and knockdown impairs preadipocyte differentiation.

Oestrogen receptor 2 (ESR2) expression has been shown to be higher in subcutaneous adipose tissue (SAT) from postmenopausal compared to premenopausal women. The functional significance of altered ESR2 expression is not fully known. This study investigates the role of ESR2 for adipose tissue lipid and glucose metabolism. SAT biopsies were obtained from 44 female subjects with or without T2D. Gene expression of ESR2 and markers of adipose function and metabolism was assessed. ESR2 knockdown was performed using CRISPR/Cas9 in preadipocytes isolated from SAT of females, and differentiation rate, lipid storage, and glucose uptake were measured.ESR2 expression was inversely correlated with measures of central obesity and expression of some fatty acid oxidation markers, and positively correlated with lipid storage and glucose transport markers. Differentiation was reduced in ESR2 knockdown preadipocytes. This corresponded to reduced expression of markers of differentiation and lipogenesis. Glucose uptake was reduced in knockdown adipocytes.Our results indicate that ESR2 deficiency in women is associated with visceral adiposity and impaired subcutaneous adipocyte differentiation as well as glucose and lipid utilization. High ESR2 expression, as seen after menopause, could be a contributing factor to SAT expansion. This may support a possible target to promote a healthy obesity phenotype.

MIMIR: Deep Regression for Automated Analysis of UK Biobank MRI Scans.

UK Biobank (UKB) has recruited more than 500 000 volunteers from the United Kingdom, collecting health-related information on genetics, lifestyle, blood biochemistry, and more. Ongoing medical imaging of 100 000 participants with 70 000 follow-up sessions will yield up to 170 000 MRI scans, enabling image analysis of body composition, organs, and muscle. This study presents an experimental inference engine for automated analysis of UKB neck-to-knee body 1.5-T MRI scans. This retrospective cross-validation study includes data from 38 916 participants (52% female; mean age, 64 years) to capture baseline characteristics, such as age, height, weight, and sex, as well as measurements of body composition, organ volumes, and abstract properties, such as grip strength, pulse rate, and type 2 diabetes status. Prediction intervals for each end point were generated based on uncertainty quantification. On a subsequent release of UKB data, the proposed method predicted 12 body composition metrics with a 3% median error and yielded mostly well-calibrated individual prediction intervals. The processing of MRI scans from 1000 participants required 10 minutes. The underlying method used convolutional neural networks for image-based mean-variance regression on two-dimensional representations of the MRI data. An implementation was made publicly available for fast and fully automated estimation of 72 different measurements from future releases of UKB image data. Keywords: MRI, Adipose Tissue, Obesity, Metabolic Disorders, Volume Analysis, Whole-Body Imaging, Quantification, Supervised Learning, Convolutional Neural Network (CNN) © RSNA, 2022.

Association between alanine aminotransferase as surrogate of fatty liver disease and physical activity and sedentary time in adolescents with obesity.

To compare patterns of sedentary (SED) time (more sedentary, SED + vs less sedentary, SED-), moderate to vigorous physical activity (MVPA) time (more active, MVPA + vs less active, MVPA-), and combinations of behaviors (SED-/MVPA + , SED-/MVPA-, SED + /MVPA + , SED + /MVPA-) regarding nonalcoholic fatty liver diseases (NAFLD) markers. This cross-sectional study included 134 subjects (13.4 ± 2.2 years, body mass index (BMI) 98.9 ± 0.7 percentile, 48.5% females) who underwent 24-h/7-day accelerometry, anthropometric, and biochemical markers (alanine aminotransferase (ALT) as first criterion, and aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), AST/ALT ratio as secondary criteria). A subgroup of 39 patients underwent magnetic resonance imaging-liver fat content (MRI-LFC). Hepatic health was better in SED- (lower ALT, GGT, and MRI-LFC (p < 0.05), higher AST/ALT (p < 0.01)) vs SED + and in MVPA + (lower ALT (p < 0.05), higher AST/ALT (p < 0.01)) vs MVPA- groups after adjustment for age, gender, and Tanner stages. SED-/MVPA + group had the best hepatic health. SED-/MVPA- group had lower ALT and GGT and higher AST/ALT (p < 0.05) in comparison with SED + /MVPA + group independently of BMI. SED time was positively associated with biochemical (high ALT, low AST/ALT ratio) and imaging (high MRI-LFC) markers independently of MVPA. MVPA time was associated with biochemical markers (low ALT, high AST/ALT) but these associations were no longer significant after adjustment for SED time. CONCLUSION: Lower SED time is associated with better hepatic health independently of MVPA. Reducing SED time might be a first step in the management of pediatric obesity NAFLD when increasing MVPA is not possible. WHAT IS KNOWN: • MVPA and SED times are associated with cardiometabolic risks in youths with obesity. • The relationships between NAFLD markers and concomitant MVPA and SED times have not been studied in this population. WHAT IS NEW: • Low SED time is associated with healthier liver enzyme profiles and LFC independent of MVPA. • While low SED/high MVPA is the more desirable pattern, low SED/low MVPA pattern would have healthier liver enzyme profile compared with high MVPA/high SED, independent of BMI, suggesting that reducing SED time irrespective of MVPA is needed to optimize liver health.

Intake of Ultra-Processed Food and Ectopic-, Visceral- and Other Fat Depots: A Cross-Sectional Study.

Introduction: The purpose of this study was to investigate associations between intake of ultra-processed food (UPF) and liver fat, pancreas fat and visceral adipose tissue (VAT) but also subcutaneous adipose tissue (SAT), VAT/SAT ratio and total fat mass. Materials and Methods: Cross-sectional analysis of n = 286 50-year old men and women. Energy percentage (%E) from UPF was calculated from a semi-quantitative food frequency questionnaire. Food items were categorized according to the NOVA-classification system and fat depots were assessed using magnetic resonance imaging (MRI) and bioelectrical impedance analysis (BIA). Associations were analyzed using linear regression, adjusted for sex, education, physical activity, smoking, dietary factors and BMI. Results: Mean intake of UPF was 37.8 ± 10.2 %E and the three largest contributors to this were crisp- and wholegrain breads and spreads, indicating overall healthy food choices. Consumption of UPF was associated with higher intake of energy, carbohydrates and fiber and lower intake of protein and polyunsaturated fat but no differences were observed for total fat, saturated fat (SFA), monounsaturated fat, sugar or alcohol between tertiles of UPF. Intake of UPF was positively associated with liver- and pancreas fat, VAT, VAT/SAT and inversely associated with total fat mass in crude models. The association for VAT remained after full adjustment (ß = 0.01 (95% CI: 0.002, 0.02), P = 0.02) and was driven by women. Conclusion: Energy intake from UPF is not associated with ectopic fat, SAT or total fat after adjustment for multiple confounders in this population having overall healthy food habits. However, a positive association between UPF and VAT was observed which was driven by women.