Background Although preliminary evidence suggests that intermittent calorie restriction (ICR) exerts stronger effects on metabolic parameters, which may link obesity and major chronic diseases, compared with continuous calorie restriction (CCR), there is a lack of well-powered intervention studies. Objective We conducted a randomized controlled trial to test whether ICR, operationalized as the “5:2 diet,” has stronger effects on adipose tissue gene expression, anthropometric and body composition measures, and circulating metabolic biomarkers than CCR and a control regimen. Design One hundred and fifty overweight and obese nonsmokers [body mass index (kg/m2) ≥25 to <40, 50% women], aged 35–65 y, were randomly assigned to an ICR group (5 d without energy restriction and 2 d with 75% energy deficit, net weekly energy deficit ∼20%), a CCR group (daily energy deficit ∼20%), or a control group (no advice to restrict energy) and participated in a 12-wk intervention phase, a 12-wk maintenance phase, and a 26-wk follow-up phase. Results Loge relative weight change over the intervention phase was −7.1% ± 0.7% (mean ± SEM) with ICR, −5.2% ± 0.6% with CCR, and −3.3% ± 0.6% with the control regimen (Poverall < 0.001, PICR vs. CCR = 0.053). Despite slightly greater weight loss with ICR than with CCR, there were no significant differences between the groups in the expression of 82 preselected genes in adipose tissue implicated in pathways linking obesity to chronic diseases. At the final follow-up assessment (week 50), weight loss was −5.2% ± 1.2% with ICR, −4.9% ± 1.1% with CCR, and −1.7% ± 0.8% with the control regimen (Poverall = 0.01, PICR vs. CCR = 0.89). These effects were paralleled by proportional changes in visceral and subcutaneous adipose tissue volumes. There were no significant differences between ICR and CCR regarding various circulating metabolic biomarkers. Conclusion Our results on the effects of the “5:2 diet” indicate that ICR may be equivalent but not superior to CCR for weight reduction and prevention of metabolic diseases. This trial was registered at clinicaltrials.gov as NCT02449148.

BackroundNon-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.Methods143 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.ResultsNAFLD 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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (10.1186/s12876-018-0840-9) contains supplementary material, which is available to authorized users.

Objectives: Disseminated bone marrow (BM) involvement is frequent in multiple myeloma (MM). Whole-body magnetic resonance imaging (wb-MRI) enables to evaluate the whole BM. Reading of such whole-body scans is time-consuming, and yet radiologists can transfer only a small fraction of the information of the imaging data set to the report. This limits the influence that imaging can have on clinical decision-making and in research toward precision oncology. The objective of this feasibility study was to implement a concept for automatic, comprehensive characterization of the BM from wb-MRI, by automatic BM segmentation and subsequent radiomics analysis of 30 different BM spaces (BMS). Materials and Methods: This retrospective multicentric pilot study used a total of 106 wb-MRI from 102 patients with (smoldering) MM from 8 centers. Fifty wb-MRI from center 1 were used for training of segmentation algorithms (nnU-Nets) and radiomics algorithms. Fifty-six wb-MRI from 8 centers, acquired with a variety of different MRI scanners and protocols, were used for independent testing. Manual segmentations of 2700 BMS from 90 wb-MRI were performed for training and testing of the segmentation algorithms. For each BMS, 296 radiomics features were calculated individually. Dice score was used to assess similarity between automatic segmentations and manual reference segmentations. Results: The "multilabel nnU-Net" segmentation algorithm, which performs segmentation of 30 BMS and labels them individually, reached mean dice scores of 0.88 ± 0.06/0.87 ± 0.06/0.83 ± 0.11 in independent test sets from center 1/center 2/center 3-8 (interrater variability between radiologists, 0.88 ± 0.01). The subset from the multicenter, multivendor test set (center 3-8) that was of high imaging quality was segmented with high precision (mean dice score, 0.87), comparable to the internal test data from center 1. The radiomic BM phenotype consisting of 8880 descriptive parameters per patient, which result from calculation of 296 radiomics features for each of the 30 BMS, was calculated for all patients.Exemplary cases demonstrated connections between typical BM patterns in MM and radiomic signatures of the respective BMS. In plausibility tests, predicted size and weight based on radiomics models of the radiomic BM phenotype significantly correlated with patients' actual size and weight (P = 0.002 and P = 0.003, respectively). Conclusions: This pilot study demonstrates the feasibility of automatic, objective, comprehensive BM characterization from wb-MRI in multicentric data sets. This concept allows the extraction of high-dimensional phenotypes to capture the complexity of disseminated BM disorders from imaging. Further studies need to assess the clinical potential of this method for automatic staging, therapy response assessment, or prediction of biopsy results.

Background: Obesity can lead to ectopic pancreatic fat accumulation and increase the risk for type 2 diabetes. Smaller intervention trials have shown a decrease in pancreatic fat content (PFC) with weight loss, and we intended to investigate the effects of weight loss on PFC in a larger trial. Methods: Data from the HELENA-Trial, a randomized controlled trial (RCT) among 137 non-diabetic obese adults were used. The study cohort was classified into 4 quartiles based on weight change between baseline and 12 weeks post-intervention. Changes in PFC (baseline, 12 weeks and 50 weeks post-intervention) upon weight loss were analyzed by linear mixed models. Spearman’s coefficients were used to obtain correlations between anthropometric parameters, blood biochemical markers, and PFC. Results: At baseline, PFC only showed a significant correlation with visceral adipose tissue (VAT) (r = 0.41). Relative changes in PFC were significantly (p = 0.01) greater in Q4 (−30.8 ± 5.7%) than in Q1 (1.3 ± 6.7%). These differences remained similar after one year. However, when adjusting the statistical analyses for changes in VAT, the differences in PFC between Q1 and Q4 were no longer statistically significant. Conclusion: Weight loss is associated with a decrease in PFC. However, the reduction of PFC is not independent from reductions in VAT. Unlike VAT, PFC was not associated with metabolic biomarkers.

Objectives: Despite the extensive number of publications in the field of radiomics, radiomics algorithms barely enter large-scale clinical application. Supposedly, the low external generalizability of radiomics models is one of the main reasons, which hinders the translation from research to clinical application. The objectives of this study were to investigate reproducibility of radiomics features (RFs) in vivo under variation of patient positioning, magnetic resonance imaging (MRI) sequence, and MRI scanners, and to identify a subgroup of RFs that shows acceptable reproducibility across all different acquisition scenarios.Materials and Methods: Between November 30, 2020 and February 16, 2021, 55 patients with monoclonal plasma cell disorders were included in this prospective, bi-institutional, single-vendor study. Participants underwent one reference scan at a 1.5 T MRI scanner and several retest scans: once after simple repositioning, once with a second MRI protocol, once at another 1.5 T scanner, and once at a 3 T scanner. Radiomics feature from the bone marrow of the left hip bone were extracted, both from original scans and after different image normalizations. Intraclass correlation coefficient (ICC) was used to assess RF repeatability and reproducibility. Results: Fifty-five participants (mean age, 59 ± 7 years; 36 men) were enrolled. For T1-weighted images after muscle normalization, in the simple test-retest experiment, 110 (37%) of 295 RFs showed an ICC ≥0.8: 54 (61%) of 89 first-order features (FOFs), 35 (95%) of 37 volume and shape features, and 21 (12%) of 169 texture features (TFs). When the retest was performed with different technical settings, even after muscle normalization, the number of FOF/TF with an ICC ≥0.8 declined to 58/13 for the second protocol, 29/7 for the second 1.5 T scanner, and 49/7 for the 3 T scanner, respectively. Twenty-five (28%) of the 89 FOFs and 6 (4%) of the 169 TFs from muscle-normalized T1-weighted images showed an ICC ≥0.8 throughout all repeatability and reproducibility experiments. Conclusions: In vivo, only few RFs are reproducible with different MRI sequences or different MRI scanners, even after application of a simple image normalization. Radiomics features selected by a repeatability experiment only are not necessarily suited to build radiomics models for multicenter clinical application. This study isolated a subset of RFs, which are robust to variations in MRI acquisition observed in scanners from 1 vendor, and therefore are candidates to build reproducible radiomics models for monoclonal plasma cell disorders for multicentric applications, at least when centers are equipped with scanners from this vendor.

Although intermittent calorie restriction (ICR) has become popular as an alternative weight loss strategy to continuous calorie restriction (CCR), there is insufficient evidence on diet quality during ICR and on its feasibility over longer time periods. Thus, we compared dietary composition and adherence between ICR and CCR in a follow-up analysis of a randomized trial. A total of 98 participants with overweight or obesity [BMI (kg/m2) 25–39.9, 35–65 years, 49% females] were randomly assigned to ICR, operationalized as a “5:2 diet” (energy intake: ~100% on five non-restricted (NR) days, ~25% on two restricted (R) days), or CCR (daily energy intake: ~80%). The trial included a 12-week (wk) intervention phase, and follow-up assessments at wk24, wk50 and wk102. Apart from a higher proportion of energy intake from protein with ICR vs. CCR during the intervention (wk2: p < 0.001; wk12: p = 0.002), there were no significant differences with respect to changes in dietary composition over time between the groups, while overall adherence to the interventions appeared to be good. No significant difference between ICR and CCR regarding weight change at wk102 was observed (p = 0.63). However, self-reported adherence was worse for ICR than CCR, with 71.1% vs. 32.5% of the participants reporting not to or only rarely have followed the regimen to which they were assigned between wk50 and wk102. These results indicate that within a weight management setting, ICR and CCR were equivalent in achieving modest weight loss over two years while affecting dietary composition in a comparable manner.

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.

Background: Preliminary evidence suggests that weight loss among obese has differential metabolic effects depending on the presence of non-alcoholic fatty liver disease (NAFLD). We assessed whether NAFLD predisposes to differential changes in liver fat content, liver function, and metabolic parameters upon diet-induced weight loss in a 50-week intervention trial. Methods: 143 overweight and obese non-smokers underwent a 12-week dietary intervention and a 38-week follow-up. Diet-induced changes in anthropometric measures, circulating biomarkers, and magnetic resonance (MR)-derived liver fat content and adipose tissue volumes were evaluated by mixed linear models stratifying by NAFLD at baseline. Results: The prevalence of NAFLD at baseline was 52%. Diet-induced weight loss after 12 (NAFLD: 4.8 ± 0.5%, No NAFLD: 5.1 ± 0.5%) and 50 weeks (NAFLD: 3.5 ± 0.7%, No NAFLD: 3.5 ± 0.9%) was similar in both groups, while the decrease in liver fat was significantly greater in the NAFLD group (week 12: 32.9 ± 9.5% vs. 6.3 ± 4.0%; week 50: 23.3 ± 4.4% vs. 5.0 ± 4.2%). Decreases in biomarkers of liver dysfunction (GGT, ALT, AST) and HOMA IR were also significantly greater in the NAFLD group. Other metabolic parameters showed no significant differences. Conclusion: Our data suggest that individuals with NAFLD show greater improvements of liver function and insulin sensitivity after moderate diet-induced weight loss than individuals without NAFLD.