Trajectories of glycaemic traits exhibit sex-specific associations with hepatic iron and fat content: Results from the KORA-MRI study.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) represents a major disease burden in the population. While the bidirectional association between NAFLD and diabetes is established, little is known about the association of hepatic iron content and glycaemia. Moreover, analyses of sex-specific effects and of dynamic changes in glycaemia are scarce. METHODS: We investigated 7-year sex-specific trajectories of glycaemia and related traits (HbA1c, fasting glucose, fasting insulin, HOMA-IR, 2-h glucose and cross-sectional 2-h insulin) in a sample from a population-based cohort (N = 365; 41.1% female). Hepatic iron and fat content were assessed by 3T-Magnetic Resonance Imaging (MRI). Two-step multi-level models adjusted for glucose-lowering medication and confounders were applied. RESULTS: In women and men, markers of glucose metabolism correlated with hepatic iron and fat content. Deterioration of glycaemia was associated with increased hepatic iron content in men (normoglycaemia to prediabetes: beta = 2.21 s-1 , 95% CI [0.47, 3.95]). Additionally, deterioration of glycaemia (e.g. prediabetes to diabetes: 1.27 log(%), [0.84, 1.70]) and trajectories of glucose, insulin and HOMA-IR were significantly associated with hepatic fat content in men. Similarly, deterioration of glycaemia as well as trajectories of glucose, insulin and HOMA-IR was significantly associated with increased hepatic fat content in women (e.g. trajectory of fasting insulin: 0.63 log(%), [0.36, 0.90]). CONCLUSIONS: Unfavourable 7-year trajectories of markers of glucose metabolism are associated with increased hepatic fat content, particularly in women, whereas the association with hepatic iron content was less clear. Monitoring changes of glycaemia in the sub-diabetic range might enable early identification of hepatic iron overload and steatosis.

Association of lumbar vertebral bone marrow and paraspinal muscle fat composition with intervertebral disc degeneration: 3T quantitative MRI findings from the population-based KORA study.

OBJECTIVE: To assess the association of lumbar bone marrow adipose tissue fat fraction (BMAT-FF) and paraspinal muscle proton density fat fraction (PDFF) and their interplay with intervertebral disc degeneration (IVDD). METHODS: In this retrospective cross-sectional study based on a prospective population-based cohort, BMAT-FF and PDFF of asymptomatic individuals were calculated based on 3T-MRI dual-echo and multi-echo Dixon VIBE sequences. IVDD was assessed at motion segments L1 to L5 and dichotomized based on Pfirrmann grade ≥ 4 and/or presence of other severe degenerative changes or spinal abnormalities at least at one segment. Pearson's correlation coefficients were calculated for BMAT-FF and PDFF. Univariable and multivariable logistic regression models for IVDD were calculated. RESULTS: Among 335 participants (mean age: 56.2 ± 9.0 years, 43.3% female), the average BMI was 27.7 ± 4.5 kg/m2 and the prevalence of IVDD was high (69.9%). BMAT-FF and PDFF were significantly correlated (r = 0.31-0.34; p < 0.001). The risk for IVDD increased with higher PDFF (OR = 1.45; CI 1.03, 2.04) and BMAT-FF (OR = 1.56; CI 1.16, 2.11). Pairwise combinations of PDFF and BMAT-FF quartiles revealed a lower risk for IVDD in individuals in the lowest BMAT-FF and PDFF quartile (OR = 0.21; CI 0.1, 0.48). Individuals in the highest BMAT-FF and PDFF quartile showed an increased risk for IVDD (OR = 5.12; CI 1.17, 22.34) CONCLUSION: Lumbar BMAT-FF and paraspinal muscle PDFF are correlated and represent both independent and additive risk factors for IVDD. Quantitative MRI measurements of paraspinal myosteatosis and vertebral bone marrow fatty infiltration may serve as imaging biomarkers to assess the individual risk for IVDD. KEY POINTS: • Fat composition of the lumbar vertebral bone marrow is positively correlated with paraspinal skeletal muscle fat. • Higher fat-fractions of lumbar vertebral bone marrow and paraspinal muscle are both independent as well as additive risk factors for intervertebral disc degeneration. • Quantitative magnetic resonance imaging measurements of bone marrow and paraspinal muscle may serve as imaging biomarkers for intervertebral disc degeneration.

Metabolomics profiling of visceral and abdominal subcutaneous adipose tissue in colorectal cancer patients: results from the ColoCare study.

PURPOSE: Underlying mechanisms of the relationship between body fatness and colorectal cancer remain unclear. This study investigated associations of circulating metabolites with visceral (VFA), abdominal subcutaneous (SFA), and total fat area (TFA) in colorectal cancer patients. METHODS: Pre-surgery plasma samples from 212 patients (stage I-IV) from the ColoCare Study were used to perform targeted metabolomics. VFA, SFA, and TFA were quantified by computed tomography scans. Partial correlation and linear regression analyses of VFA, SFA, and TFA with metabolites were computed and corrected for multiple testing. Cox proportional hazards were used to assess 2-year survival. RESULTS: In patients with metastatic tumors, SFA and TFA were statistically significantly inversely associated with 16 glycerophospholipids (SFA: pFDR range 0.017-0.049; TFA: pFDR range 0.029-0.048), while VFA was not. Doubling of ten of the aforementioned glycerophospholipids was associated with increased risk of death in patients with metastatic tumors, but not in patients with non-metastatic tumors (phet range: 0.00044-0.049). Doubling of PC ae C34:0 was associated with ninefold increased risk of death in metastatic tumors (Hazard Ratio [HR], 9.05; 95% confidence interval [CI] 2.17-37.80); an inverse association was observed in non-metastatic tumors (HR 0.17; 95% CI 0.04-0.87; phet = 0.00044). CONCLUSION: These data provide initial evidence that glycerophospholipids in metastatic colorectal cancer are uniquely associated with subcutaneous adiposity, and may impact overall survival.

Bone marrow fat fraction assessment in regard to physical activity: KORA FF4-3-T MR imaging in a population-based cohort.

OBJECTIVES: To establish the effect of different degrees and kinds of physical activity on bone marrow fat (BMAT) content at different anatomical locations in a population-based cohort study undergoing whole-body MR imaging. METHODS: Subjects of the KORA FF4 study without known cardiovascular disease underwent BMAT fat fraction (FF) quantification in L1 and L2 vertebrae and femoral heads/necks (hip) via a 2-point T1-weighted VIBE Dixon sequence. BMAT-FF was calculated as mean value (fat image) divided by mean value (fat + water image). Physical activity was determined by self-assessment questionnaire regarding time spent exercising, non-exercise walking, non-exercise cycling, and job-related physical activity. RESULTS: A total of 385 subjects (96% of 400 available; 56 ± 9.1 years; 58% male) were included in the analysis. Exercise was distributed quite evenly (29% > 2 h/week; 31% ~ 1 h/week (regularly); 15% ~ 1 h/week (irregularly); 26% no physical activity). BMAT-FF was 52.6 ± 10.2% in L1, 56.2 ± 10.3% in L2, 87.4 ± 5.9% in the right hip, and 87.2 ± 5.9% in the left hip (all p < 0.001). Correlation of BMAT-FF between spine and hip was only moderate (r 0.42 to 0.46). Spinal BMAT-FF, but not hip BMAT-FF, was inversely associated with exercise > 2 h/week (p ≤ 0.02 vs. p ≥ 0.35, respectively). These associations remained significant after adjusting for age, gender, waist circumference, and glucose tolerance. No coherent association was found between BMAT-FF and physical activity in the less active groups. CONCLUSIONS: In our study, exercise was inversely correlated with vertebral BMAT-FF, but not hip BMAT-FF, when exercising for more than 2 h per week. Physical activity seems to affect the spine at least preferentially compared to the hip. KEY POINTS: • In our population-based cohort, at least 2 h of physical activity per week were required to show lower levels of bone marrow adipose tissue fat fraction in MRI. • Physical activity seems to affect bone marrow adipose tissue at least preferentially at the spine in contrast to the proximal femur.

Anthropometric and blood parameters for the prediction of NAFLD among overweight and obese adults.

BACKROUND: Non-alcoholic fatty liver disease (NAFLD) comprises non-progressive steatosis and non-alcoholic steatohepatitis (NASH), the latter of which may cause cirrhosis and hepatocellular carcinoma (HCC). As NAFLD detection is imperative for the prevention of its complications, we evaluated whether a combination of blood-based biomarkers and anthropometric parameters can be used to predict NAFLD among overweight and obese adults. METHODS: 143 overweight or obese non-smokers free of diabetes (50% women, age: 35-65 years) were recruited. Anthropometric indices and routine biomarkers of metabolism and liver function were measured to predict magnetic resonance (MR) - derived NAFLD by multivariable logistic regression models. In addition, we evaluated to which degree the use of more novel biomarkers (adiponectin, leptin, resistin, C-reactive protein, TNF-α, IL-6, IL-8 and interferon-γ) could improve prediction models. RESULTS: NAFLD was best predicted by a combination of age, sex, waist circumference, ALT, HbA1c, and HOMA-IR at an area under the receiver operating characteristic curve (AUROC) of 0.87 (95% CI: 0.81, 0.93) before and 0.85 (95% CI: 0.78, 0.91) after internal bootstrap validation. The use of additional biomarkers of inflammation and metabolism did not improve NAFLD prediction. Previously published indices predicted NAFLD at AUROCs between 0.71 and 0.82. CONCLUSIONS: The AUROC of > 0.8 obtained by our regression model suggests the feasibility of a non-invasive detection of NAFLD by anthropometry and circulating biomarkers, even though further increments in the capacity of prediction models may be needed before NAFLD indices can be applied in routine clinical practice.

Hypodense liver lesions in patients with hepatic steatosis: do we profit from dual-energy computed tomography?

PURPOSE: To evaluate dual-energy CT (DECT) imaging of hypodense liver lesions in patients with hepatic steatosis, having a high incidence in the general population and among cancer patients receiving chemotherapy. METHODS: One hundred and five patients with hepatic steatosis (liver parenchyma <40 HU) underwent contrast-enhanced DECT with reconstruction of pure iodine (PI), optimum contrast (OC), 80 kVp, and 120 kVp-equivalent data sets. Image noise (IN), lesion to liver signal to noise (SNR) and contrast to noise (CNR) ratios were quantitatively analysed; image quality was rated on a 5-point scale (1, excellent; 2, good; 3, fair; 4, poor; 5, non-diagnostic) by two independent reviewers. RESULTS: In 21 patients with hypodense liver lesions, IN was lowest in PI followed by 120 kVp-equivalent and OC, and highest in 80 kVp. SNR was highest in PI (1.30), followed by 120 kVp-equivalent (0.72) and 80 kVp (0.63), and lowest in OC (0.55). CNR was highest in 120 kVp-equivalent (4.95), followed by OC (4.55) and 80 kVp (4.14), and lowest in PI (3.63). The 120 kVp-equivalent series exhibited best overall qualitative image score (1.88), followed by OC (1.98), 80 kVp (3.00) and PI (3.67). CONCLUSION: In our study, the 120 kVp-equivalent series was best suited for visualization of hypodense lesions within steatotic liver parenchyma, while using DECT currently seems to offer no additional diagnostic advantage. KEY POINTS: • Hepatic steatosis has high incidence in the general population and following chemotherapy. • Hypodense liver lesions can be obscured by steatotic liver parenchyma in CT. • Low kV p -CT shows no advantage in detecting hypodense lesions in steatotic livers. • Additional DECT image information does not improve visualization of hypodense lesions in steatosis. • 120 kV p -equivalent imaging yields best quantitative and qualitative image analysis results.

A retrieval-augmented chatbot based on GPT-4 provides appropriate differential diagnosis in gastrointestinal radiology: a proof of concept study.

BACKGROUND: We investigated the potential of an imaging-aware GPT-4-based chatbot in providing diagnoses based on imaging descriptions of abdominal pathologies. METHODS: Utilizing zero-shot learning via the LlamaIndex framework, GPT-4 was enhanced using the 96 documents from the Radiographics Top 10 Reading List on gastrointestinal imaging, creating a gastrointestinal imaging-aware chatbot (GIA-CB). To assess its diagnostic capability, 50 cases on a variety of abdominal pathologies were created, comprising radiological findings in fluoroscopy, MRI, and CT. We compared the GIA-CB to the generic GPT-4 chatbot (g-CB) in providing the primary and 2 additional differential diagnoses, using interpretations from senior-level radiologists as ground truth. The trustworthiness of the GIA-CB was evaluated by investigating the source documents as provided by the knowledge-retrieval mechanism. Mann-Whitney U test was employed. RESULTS: The GIA-CB demonstrated a high capability to identify the most appropriate differential diagnosis in 39/50 cases (78%), significantly surpassing the g-CB in 27/50 cases (54%) (p = 0.006). Notably, the GIA-CB offered the primary differential in the top 3 differential diagnoses in 45/50 cases (90%) versus g-CB with 37/50 cases (74%) (p = 0.022) and always with appropriate explanations. The median response time was 29.8 s for GIA-CB and 15.7 s for g-CB, and the mean cost per case was $0.15 and $0.02, respectively. CONCLUSIONS: The GIA-CB not only provided an accurate diagnosis for gastrointestinal pathologies, but also direct access to source documents, providing insight into the decision-making process, a step towards trustworthy and explainable AI. Integrating context-specific data into AI models can support evidence-based clinical decision-making. RELEVANCE STATEMENT: A context-aware GPT-4 chatbot demonstrates high accuracy in providing differential diagnoses based on imaging descriptions, surpassing the generic GPT-4. It provided formulated rationale and source excerpts supporting the diagnoses, thus enhancing trustworthy decision-support. KEY POINTS: • Knowledge retrieval enhances differential diagnoses in a gastrointestinal imaging-aware chatbot (GIA-CB). • GIA-CB outperformed the generic counterpart, providing formulated rationale and source excerpts. • GIA-CB has the potential to pave the way for AI-assisted decision support systems.

MRI-based adrenal gland volume is associated with cardiovascular alterations in individuals without prior cardiovascular disease.

Aim of this study was to analyse the associations of cardiovascular health and adrenal gland volume as a rather new imaging biomarker of chronic hypothalamic-pituitary-adrenal (HPA) axis activation. The study population originates from the KORA population-based cross-sectional prospective cohort. 400 participants without known cardiovascular disease underwent a whole-body MRI. Manual segmentation of adrenal glands was performed on VIBE-Dixon gradient-echo sequence. MRI based evaluation of cardiac parameters was achieved semi-automatically. Cardiometabolic risk factors were obtained through standardized interviews and medical examination. Univariate and multivariate associations were derived. Bi-directional causal mediation analysis was performed. 351 participants were eligible for analysis (56 ± 9.1 years, male 58.7%). In multivariate analysis, significant associations were observed between adrenal gland volume and hypertension (outcome hypertension: Odds Ratio = 1.11, 95% CI [1.01, 1.21], p = 0.028), left ventricular remodelling index (LVRI) (outcome LVRI: ß = 0.01, 95% CI [0.00, 0.02], p = 0.011), and left ventricular (LV) wall thickness (outcome LV wall thickness: ß = 0.06, 95% CI [0.02, 0.09], p = 0.005). In bi-directional causal mediation analysis adrenal gland volume had a borderline significant mediating effect on the association between hypertension and LVRI (p = 0.052) as well as wall thickness (p = 0.054). MRI-based assessment of adrenal gland enlargement is associated with hypertension and LV remodelling. Adrenal gland volume may serve as an indirect cardiovascular imaging biomarker.

Serum metabolite signatures of cardiac function and morphology in individuals from a population-based cohort.

BACKGROUND: Changes in serum metabolites in individuals with altered cardiac function and morphology may exhibit information about cardiovascular disease (CVD) pathway dysregulations and potential CVD risk factors. We aimed to explore associations of cardiac function and morphology, evaluated using magnetic resonance imaging (MRI) with a large panel of serum metabolites. METHODS: Cross-sectional data from CVD-free individuals from the population-based KORA cohort were analyzed. Associations between 3T-MRI-derived left ventricular (LV) function and morphology parameters (e.g., volumes, filling rates, wall thickness) and markers of carotid plaque with metabolite profile clusters and single metabolites as outcomes were assessed by adjusted multinomial logistic regression and linear regression models. RESULTS: In 360 individuals (mean age 56.3 years; 41.9% female), 146 serum metabolites clustered into three distinct profiles that reflected high-, intermediate- and low-CVD risk. Higher stroke volume (relative risk ratio (RRR): 0.53, 95%-CI [0.37; 0.76], p-value < 0.001) and early diastolic filling rate (RRR: 0.51, 95%-CI [0.37; 0.71], p-value < 0.001) were most strongly protectively associated against the high-risk profile compared to the low-risk profile after adjusting for traditional CVD risk factors. Moreover, imaging markers were associated with 10 metabolites in linear regression. Notably, negative associations of stroke volume and early diastolic filling rate with acylcarnitine C5, and positive association of function parameters with lysophosphatidylcholines, diacylphosphatidylcholines, and acylalkylphosphatidylcholines were observed. Furthermore, there was a negative association of LV wall thickness with alanine, creatinine, and symmetric dimethylarginine. We found no significant associations with carotid plaque. CONCLUSIONS: Serum metabolite signatures are associated with cardiac function and morphology even in individuals without a clinical indication of CVD.

Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics.

OBJECTIVES: Achieving a consensus on a definition for different aspects of radiomics workflows to support their translation into clinical usage. Furthermore, to assess the perspective of experts on important challenges for a successful clinical workflow implementation. MATERIALS AND METHODS: The consensus was achieved by a multi-stage process. Stage 1 comprised a definition screening, a retrospective analysis with semantic mapping of terms found in 22 workflow definitions, and the compilation of an initial baseline definition. Stages 2 and 3 consisted of a Delphi process with over 45 experts hailing from sites participating in the German Research Foundation (DFG) Priority Program 2177. Stage 2 aimed to achieve a broad consensus for a definition proposal, while stage 3 identified the importance of translational challenges. RESULTS: Workflow definitions from 22 publications (published 2012-2020) were analyzed. Sixty-nine definition terms were extracted, mapped, and semantic ambiguities (e.g., homonymous and synonymous terms) were identified and resolved. The consensus definition was developed via a Delphi process. The final definition comprising seven phases and 37 aspects reached a high overall consensus (> 89% of experts "agree" or "strongly agree"). Two aspects reached no strong consensus. In addition, the Delphi process identified and characterized from the participating experts' perspective the ten most important challenges in radiomics workflows. CONCLUSION: To overcome semantic inconsistencies between existing definitions and offer a well-defined, broad, referenceable terminology, a consensus workflow definition for radiomics-based setups and a terms mapping to existing literature was compiled. Moreover, the most relevant challenges towards clinical application were characterized. CRITICAL RELEVANCE STATEMENT: Lack of standardization represents one major obstacle to successful clinical translation of radiomics. Here, we report a consensus workflow definition on different aspects of radiomics studies and highlight important challenges to advance the clinical adoption of radiomics. KEY POINTS: Published radiomics workflow terminologies are inconsistent, hindering standardization and translation. A consensus radiomics workflow definition proposal with high agreement was developed. Publicly available result resources for further exploitation by the scientific community.

Novel measures for the diagnosis of hepatic steatosis using contrast-enhanced computer tomography images.

PURPOSE: Hepatic steatosis is often diagnosed non-invasively. Various measures and accompanying diagnostic thresholds based on contrast-enhanced CT and virtual non-contrast images have been proposed. We compare these established criteria to novel and fully automated measures. METHOD: CT data sets of 197 patients were analyzed. Regions of interest (ROIs) were manually drawn for the liver, spleen, portal vein, and aorta to calculate four established measures of liver-fat. Two novel measures capturing the deviation between the empirical distributions of HU measurements across all voxels within the liver and spleen were calculated. These measures were calculated with both manual ROIs and using fully automated organ segmentations. Agreement between the different measures was evaluated using correlational analysis, as well as their ability to discriminate between fatty and healthy liver. RESULTS: Established and novel measures of fatty liver were at a high level of agreement. Novel methods were statistically indistinguishable from the established ones when taking established diagnostic thresholds or physicians' diagnoses as ground truth and this high performance level persisted for automatically selected ROIs. CONCLUSION: Automatically generated organ segmentations led to comparable results as manual ROIs, suggesting that the implementation of automated methods can prove to be a valuable tool for incidental diagnosis. Differences in the distribution of HU measurements across voxels between liver and spleen can serve as surrogate markers for the liver-fat-content. Novel measures do not exhibit a measurable disadvantage over established methods based on simpler measures such as across-voxel averages in a population with low incidence of fatty liver.

Analysis of volume and topography of adipose tissue in the trunk: Results of MRI of 11,141 participants in the German National Cohort.

This research addresses the assessment of adipose tissue (AT) and spatial distribution of visceral (VAT) and subcutaneous fat (SAT) in the trunk from standardized magnetic resonance imaging at 3 T, thereby demonstrating the feasibility of deep learning (DL)-based image segmentation in a large population-based cohort in Germany (five sites). Volume and distribution of AT play an essential role in the pathogenesis of insulin resistance, a risk factor of developing metabolic/cardiovascular diseases. Cross-validated training of the DL-segmentation model led to a mean Dice similarity coefficient of >0.94, corresponding to a mean absolute volume deviation of about 22 ml. SAT is significantly increased in women compared to men, whereas VAT is increased in males. Spatial distribution shows age- and body mass index-related displacements. DL-based image segmentation provides robust and fast quantification of AT (≈15 s per dataset versus 3 to 4 hours for manual processing) and assessment of its spatial distribution from magnetic resonance images in large cohort studies.

Changes in Kidney Fat upon Dietary-Induced Weight Loss.

As the metabolic role of kidney fat remains unclear, we investigated the effects of dietary weight loss on kidney fat content (KFC) and its connection to kidney function and metabolism. Overweight or obese participants (n = 137) of a dietary intervention trial were classified into quartiles of weight loss in a post hoc manner. Kidney sinus (KSF) and cortex fat (KCF) were measured by magnetic resonance imaging at baseline, week 12 and week 50. Weight loss effects on KFC were evaluated by linear mixed models. Repeated measures correlations between KFC, other body fat measures and metabolic biomarkers were obtained. KSF, but not KCF, decreased significantly across weight loss quartiles at week 12 (quartile 4: -21.3%; p = 0.02) and 50 (-22.0%, p = 0.001), which remained significant after adjusting for VAT. There were smaller improvements regarding creatinine (-2.5%, p = 0.02) at week 12, but not week 50. KSF, but not KCF, correlated with visceral (rrm = 0.38) and subcutaneous fat volumes (rrm = 0.31) and liver fat content (rrm = 0.32), as well as diastolic blood pressure and biomarkers of lipid, glucose and liver metabolism. Dietary weight loss is associated with decreases in KSF, but not KCF, which suggests that KSF may be the metabolically relevant ectopic fat depot of the kidney. KSF may be targeted for obesity-related disease prevention.

Changes in aortic diameter induced by weight loss: The HELENA trial- whole-body MR imaging in a dietary intervention trial.

Obesity-related metabolic disorders such as hypertension, hyperlipidemia and chronic inflammation have been associated with aortic dilatation and resulting in aortic aneurysms in many cases. Whether weight loss may reduce the risk of aortic dilatation is not clear. In this study, the diameter of the descending thoracic aorta, infrarenal abdominal aorta and aortic bifurcation of 144 overweight or obese non-smoking adults were measured by MR-imaging, at baseline, and 12 and 50 weeks after weight loss by calorie restriction. Changes in aortic diameter, anthropometric measures and body composition and metabolic markers were evaluated using linear mixed models. The association of the aortic diameters with the aforementioned clinical parameters was analyzed using Spearman`s correlation. Weight loss was associated with a reduction in the thoracic and abdominal aortic diameters 12 weeks after weight loss (predicted relative differences for Quartile 4: 2.5% ± 0.5 and -2.2% ± 0.8, p < 0.031; respectively). Furthermore, there was a nominal reduction in aortic diameters during the 50-weeks follow-up period. Aortic diameters were positively associated with weight, visceral adipose tissue, glucose, HbA1c and with both systolic and diastolic blood pressure. Weight loss induced by calorie restriction may reduce aortic diameters. Future studies are needed to investigate, whether the reduction of aortic diameters via calorie restriction may help to prevent aortic aneurysms.

Calorie restriction improves metabolic state independently of gut microbiome composition: a randomized dietary intervention trial.

BACKGROUND: The gut microbiota has been suggested to play a significant role in the development of overweight and obesity. However, the effects of calorie restriction on gut microbiota of overweight and obese adults, especially over longer durations, are largely unexplored. METHODS: Here, we longitudinally analyzed the effects of intermittent calorie restriction (ICR) operationalized as the 5:2 diet versus continuous calorie restriction (CCR) on fecal microbiota of 147 overweight or obese adults in a 50-week parallel-arm randomized controlled trial, the HELENA Trial. The primary outcome of the trial was the differential effects of ICR versus CCR on gene expression in subcutaneous adipose tissue. Changes in the gut microbiome, which are the focus of this publication, were defined as exploratory endpoint of the trial. The trial comprised a 12-week intervention period, a 12-week maintenance period, and a final follow-up period of 26 weeks. RESULTS: Both diets resulted in ~5% weight loss. However, except for Lactobacillales being enriched after ICR, post-intervention microbiome composition did not significantly differ between groups. Overall weight loss was associated with significant metabolic improvements, but not with changes in the gut microbiome. Nonetheless, the abundance of the Dorea genus at baseline was moderately predictive of subsequent weight loss (AUROC of 0.74 for distinguishing the highest versus lowest weight loss quartiles). Despite the lack of consistent intervention effects on microbiome composition, significant study group-independent co-variation between gut bacterial families and metabolic biomarkers, anthropometric measures, and dietary composition was detectable. Our analysis in particular revealed associations between insulin sensitivity (HOMA-IR) and Akkermansiaceae, Christensenellaceae, and Tanerellaceae. It also suggests the possibility of a beneficial modulation of the latter two intestinal taxa by a diet high in vegetables and fiber, and low in processed meat. CONCLUSIONS: Overall, our results suggest that the gut microbiome remains stable and highly individual-specific under dietary calorie restriction. TRIAL REGISTRATION: The trial, including the present microbiome component, was prospectively registered at ClinicalTrials.gov NCT02449148 on May 20, 2015.

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine.

Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow. An interdisciplinary, multicentric team of medical experts and computer scientists designed a pipeline, comprising AI-based tools for the automated detection, quantification and characterization of the most common pulmonary, metabolic, cardiovascular and musculoskeletal comorbidities in chest computed tomography (CT). To provide a comprehensive evaluation of each patient, a multidimensional workflow was established with algorithms operating synchronously on a decentralized Joined Imaging Platform (JIP). The results of each patient are transferred to a dedicated database and summarized as a structured report with reference to available reference values and annotated sample images of detected pathologies. Hence, this tool allows for the comprehensive, large-scale analysis of imaging-biomarkers of comorbidities in chest CT, first in science and then in clinical routine. Moreover, this tool accommodates the quantitative analysis and classification of each pathology, providing integral diagnostic and prognostic value, and subsequently leading to improved preventive patient care and further possibilities for future studies.

Distribution and Associated Factors of Hepatic Iron-A Population-Based Imaging Study.

Hepatic iron overload can cause severe organ damage; therefore, an early diagnosis and the identification of potential risk factors is crucial. We aimed to investigate the sex-specific distribution of hepatic iron content (HIC) in a population-based cohort and identify relevant associated factors from a panel of markers. We analyzed N = 353 participants from a cross-sectional sample (KORA FF4) who underwent whole-body magnetic resonance imaging. HIC was assessed by single-voxel spectroscopy with a high-speed T2-corrected multi-echo technique. A large panel of markers, including anthropometric, genetic, and laboratory values, as well as behavioral risk factors were assessed. Relevant factors associated with HIC were identified by variable selection based on LASSO regression with bootstrap resampling. HIC in the study sample (mean age at examination: 56.0 years, 58.4% men) was significantly lower in women (mean ± SD: 39.2 ± 4.1 s-1) than in men (41.8 ± 4.7 s-1, p < 0.001). Relevant factors associated with HIC were HbA1c as well as prediabetes for men and visceral adipose tissue as well as age for women. Hepatic fat, alcohol consumption, and genetic risk score for iron levels were associated with HIC in both sexes. In conclusion, there are sex-specific associations of HIC with markers of body composition, glucose metabolism, and alcohol consumption.

Association of Habitual Dietary Intake with Liver Iron-A Population-Based Imaging Study.

Iron-related disorders of the liver can result in serious health conditions, such as liver cirrhosis. Evidence on the role of modifiable lifestyle factors like nutrition in liver iron storage is lacking. Thus, we aimed to assess the association of habitual diet with liver iron content (LIC). We investigated 303 participants from the population-based KORA-MRI study who underwent whole-body magnetic resonance imaging (MRI). Dietary habits were evaluated using repeated 24 h food lists and a food frequency questionnaire. Sex-stratified multiple linear regression models were applied to quantify the association between nutrition variables of interest and LIC, adjusting for liver fat content (LFC), energy intake, and age. Mean age of participants was 56.4 ± 9.0 years and 44.2% were female. Mean LIC was 1.23 ± 0.12 mg/g dry weight, with higher values in men than in women (1.26 ± 0.13 and 1.20 ± 0.10 mg/g, p < 0.001). Alcohol intake was positively associated with LIC (men: ß = 1.94; women: ß = 4.98, p-values < 0.03). Significant negative associations with LIC were found for fiber (ß = -5.61, p < 0.001) and potassium (ß = -0.058, p = 0.034) for female participants only. Furthermore, LIC was highly correlated with liver fat content in both sexes. Our findings suggests that there are sex-specific associations of habitual dietary intake and LIC. Alcohol, fiber, and potassium may play a considerable role in liver iron metabolism.

Impact of progressive resistance training on CT quantified muscle and adipose tissue compartments in pancreatic cancer patients.

OBJECTIVES: Loss of body weight is often seen in pancreatic cancer and also predicts poor prognosis. Thus, maintaining muscle mass is an essential treatment goal. The primary aim was to investigate whether progressive resistance training impacts muscle and adipose tissue compartments. Furthermore, the effect of body composition on overall survival (OS) was investigated. METHODS: In the randomized SUPPORT-study, 65 patients were assigned to 6-month resistance training (2x/week) or a usual care control group. As secondary endpoint, muscle strength of the upper and lower extremities was assessed before and after the intervention period. Routine CT scans were assessed on lumbar L3/4 level for quantification of total-fat-area, visceral-fat-area, subcutaneous-fat-area, intramuscular-fat-area, visceral-to-subcutaneous fat ratio (VFR), muscle-area (MA), muscle-density and skeletal-muscle-index (SMI). OS data were retrieved. RESULTS: Of 65 patients, 53 had suitable CT scans at baseline and 28 completed the intervention period with suitable CT scans. There were no significant effects observed of resistance training on body composition (p>0.05; effect sizes ω2p <0.02). Significant moderate to high correlations were found between MA and muscle strength parameters (r = 0.57-0.85; p<0.001). High VFR at baseline was a predictor of poor OS (VFR≥1.3 vs. <1.3; median OS 14.6 vs. 45.3 months; p = 0.012). Loss of muscle mass was also a predictor of poor OS (loss vs. gain of SMI; median OS 24.6 vs. 50.8 months; p = 0.049). CONCLUSION: There is anabolic potential in patients with resectable pancreatic cancer. A progressive resistance training may help patients to maintain their muscle mass and avoid muscle depletion. CT-quantified muscle mass at the level of L3/4 showed a good correlation to muscle strength. Therefore, maintaining muscle mass and muscle strength through structured resistance training could help patients to maintain their physical functioning. A high VFR at baseline and a high loss of muscle mass are predictors of poor OS. Registered on ClinicalTrials.gov (NCT01977066).

Dietary Factors in Relation to Liver Fat Content: A Cross-sectional Study.

Non-alcoholic fatty liver disease (NAFLD) can lead to functional liver impairment and severe comorbidities. Beyond energy balance, several dietary factors may increase NAFLD risk, but human studies are lacking. The aim of this cross-sectional study was to investigate the associations between food consumption (47 food groups, derived Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diet quality scores) and liver fat content (continuous scale and NAFLD, i.e., >5% liver fat content). Liver fat content was measured by magnetic resonance imaging (MRI) in 136 individuals (BMI: 25-40 kg/m2, age: 35-65, 50.7% women) and food intake was recorded by food frequency questionnaires (FFQs). Associations between food items and liver fat were evaluated by multi-variable regression models. Intakes of cake and cookies as well legumes were inversely associated with liver fat content, while positive associations with intakes of high-fat dairy and cheese were observed. Only cake and cookie intake also showed an inverse association with NAFLD. This inverse association was unexpected, but not affected by adjustment for reporting bias. Both diet quality scores were inversely associated with liver fat content and NAFLD. Thus, as smaller previous intervention studies, our results suggest that higher diet quality is related to lower liver fat, but larger trials with iso-caloric interventions are needed to corroborate these findings.