Prospective Deployment of Deep Learning Reconstruction Facilitates Highly Accelerated Upper Abdominal MRI.

RATIONALE AND OBJECTIVES: To compare a conventional T1 volumetric interpolated breath-hold examination (VIBE) with SPectral Attenuated Inversion Recovery (SPAIR) fat saturation and a deep learning (DL)-reconstructed accelerated VIBE sequence with SPAIR fat saturation achieving a 50 % reduction in breath-hold duration (hereafter, VIBE-SPAIRDL) in terms of image quality and diagnostic confidence. MATERIALS AND METHODS: This prospective study enrolled consecutive patients referred for upper abdominal MRI from November 2023 to December 2023 at a single tertiary center. Patients underwent upper abdominal MRI with acquisition of non-contrast and gadobutrol-enhanced conventional VIBE-SPAIR (fourfold acceleration, acquisition time 16 s) and VIBE-SPAIRDL (sixfold acceleration, acquisition time 8 s) on a 1.5 T scanner. Image analysis was performed by four readers, evaluating homogeneity of fat suppression, perceived signal-to-noise ratio (SNR), edge sharpness, artifact level, lesion detectability and diagnostic confidence. A statistical power analysis for patient sample size estimation was performed. Image quality parameters were compared by a repeated measures analysis of variance, and interreader agreement was assessed using Fleiss' κ. RESULTS: Among 450 consecutive patients, 45 patients were evaluated (mean age, 60 years ± 15 [SD]; 27 men, 18 women). VIBE-SPAIRDL acquisition demonstrated superior SNR (P < 0.001), edge sharpness (P < 0.001), and reduced artifacts (P < 0.001) with substantial to almost perfect interreader agreement for non-contrast (κ: 0.70-0.91) and gadobutrol-enhanced MRI (κ: 0.68-0.87). No evidence of a difference was found between conventional VIBE-SPAIR and VIBE-SPAIRDL regarding homogeneity of fat suppression, lesion detectability, or diagnostic confidence (all P > 0.05). CONCLUSION: Deep learning reconstruction of VIBE-SPAIR facilitated a reduction of breath-hold duration by half, while reducing artifacts and improving image quality. SUMMARY: Deep learning reconstruction of prospectively accelerated T1 volumetric interpolated breath-hold examination for upper abdominal MRI enabled a 50 % reduction in breath-hold time with superior image quality. KEY RESULTS: 1) In a prospective analysis of 45 patients referred for upper abdominal MRI, accelerated deep learning (DL)-reconstructed VIBE images with spectral fat saturation (SPAIR) showed better overall image quality, with better perceived signal-to-noise ratio and less artifacts (all P < 0.001), despite a 50 % reduction in acquisition time compared to conventional VIBE. 2) No evidence of a difference was found between conventional VIBE-SPAIR and accelerated VIBE-SPAIRDL regarding lesion detectability or diagnostic confidence.

Motivation and success factors in radiological research in Germany - results of a survey by the Methodology and Research Working Group of the German Radiological Society. / Motivation und Erfolgsfaktoren in der radiologischen Forschung in Deutschland ­ Ergebnisse einer Umfrage der AG Methodik und Forschung.

Investigation of motivation and identification of success factors in radiology research in Germany.Using a German online survey (54 questions, period: 3.5 months), demographic aspects, intrinsic and extrinsic success characteristics, as well as personal and organizational success factors were surveyed based on a career success model. The survey results were reported descriptively. The correlations between success factors and success characteristics were examined using linear, binary-logistic, and multinomial regression models.176 people (164 academically active, 10 not academically active) answered the survey. Most participants (80%, 139/174) worked at a university hospital. 32% had privatdozent or professor as their highest academic title (56/173). The researchers' main motivation was intrinsic interest in research (55%, 89/163), followed by a desire to increase their own career opportunities (25%, 41/163). The following were identified as factors for intrinsic success: i) support from department management (estimate=ß=0.26, p<0.001), ii) good work-life balance (ß=0.37, p<0.001), and iii) the willingness to pursue science even after reaching the career goal (ß=0.16, p<0.016). Relevant factors for extrinsic scientific success were mentoring, protected research time, and activities in professional societies.Researchers in German radiology are mainly intrinsically motivated. Factors known from the literature that determine intrinsic and extrinsic scientific success were confirmed in this study. Knowledge of these factors allows targeted systematic support and could thus increase scientific success in German radiology. · Main motivation for German radiology research is intrinsic interest, followed by career opportunities.. · Factors for intrinsic scientific success are good work-life balance and support by department management.. · Factors for extrinsic scientific success are mentoring, activities in professional societies, and protected research time.. · Wegner F, Heinrichs H, Stahlmann K et al. Motivation and success factors in radiological research in Germany - results of a survey by the Methodology and Research Working Group of the German Radiological Society. Fortschr Röntgenstr 2024; DOI 10.1055/a-2350-0023.

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.

A straightforward procedure to build a non-toxic relaxometry phantom with desired T1 and T2 times at 3T.

OBJECTIVE: To prepare and analyze soy-lecithin-agar gels for non-toxic relaxometry phantoms with tissue-like relaxation times at 3T. METHODS: Phantoms mimicking the relaxation times of various tissues (gray and white matter, kidney cortex and medulla, spleen, muscle, liver) were built and tested with a clinical 3T whole-body MR scanner. Simple equations were derived to calculate the appropriate concentrations of soy lecithin and agar in aqueous solutions to achieve the desired relaxation times. Phantoms were tested for correspondence between measurements and calculated T1 and T2 values, reproducibility, spatial homogeneity, and temporal stability. T1 and T2 mapping techniques and a 3D T1-weighted sequence with high spatial resolution were applied. RESULTS: Except for the liver relaxation phantom, all phantoms were successfully and reproducibly produced. Good agreement was found between the targeted and measured relaxation times. The percentage deviations from the targeted relaxation times were less than 3% for T1 and less than 6.5% for T2. In addition, the phantoms were homogeneous and had little to no air bubbles. However, the phantoms were unstable over time: after a storage period of 4 weeks, mold growth and also changes in relaxation times were detected in almost all phantoms. CONCLUSION: Soy-lecithin-agar gels are a non-toxic material for the construction of relaxometry phantoms with tissue-like relaxation times. They are easy to prepare, inexpensive and allow independent adjustment of T1 and T2. However, there is still work to be done to improve the long-term stability of the phantoms.

Comparison of the accuracy of commercial two-point and multi-echo Dixon MRI for quantification of fat in liver, paravertebral muscles, and vertebral bone marrow.

PURPOSE: Excess fat accumulation contributes significantly to metabolic dysfunction and diseases. This study aims to systematically compare the accuracy of commercially available Dixon techniques for quantification of fat fraction in liver, skeletal musculature, and vertebral bone marrow (BM) of healthy individuals, investigating biases and sex-specific influences. METHOD: 100 healthy White individuals (50 women) underwent abdominal MRI using two-point and multi-echo Dixon sequences. Fat fraction (FF), proton density fat fraction (PDFF) and T2* values were calculated for liver, paravertebral muscles (PVM) and vertebral BM (Th8-L5). Agreement and systematic deviations were assessed using linear correlation and Bland-Altman plots. RESULTS: High correlations between FF and PDFF were observed in liver (r = 0.98 for women; r = 0.96 for men), PVM (r = 0.92 for women; r = 0.93 for men) and BM (r = 0.97 for women; r = 0.95 for men). Relative deviations between FF and PDFF in liver (18.92 % for women; 13.32 % for men) and PVM (1.96 % for women; 11.62 % for men) were not significant. Relative deviations in BM were significant (38.13 % for women; 27.62 % for men). Bias correction using linear models reduced discrepancies. T2* times were significantly shorter in BM (8.72 ms for women; 7.26 ms for men) compared to PVM (13.45 ms for women; 13.62 ms for men) and liver (29.47 ms for women; 26.35 ms for men). CONCLUSION: While no significant differences were observed for liver and PVM, systematic errors in BM FF estimation using two-point Dixon imaging were observed. These discrepancies - mainly resulting from organ-specific T2* times - have to be considered when applying two-point Dixon approaches for assessment of fat content. As suitable correction tools, linear models could provide added value in large-scale epidemiological cohort studies. Sex-specific differences in T2* should be considered.

Frequency shifts of free water signals from compact bone: Simulations and measurements using a UTE-FID sequence.

PURPOSE: Free water in cortical bone is either contained in nearly cylindrical structures (mainly Haversian canals oriented parallel to the bone axis) or in more spherically shaped pores (lacunae). Those cavities have been reported to crucially influence bone quality and mechanical stability. Susceptibility differences between bone and water can lead to water frequency shifts dependent on the geometric characteristics. The purpose of this study is to calculate and measure the frequency distribution of the water signal in MRI in dependence of the microscopic bone geometry. METHODS: Finite element modeling and analytical approaches were performed to characterize the free water components of bone. The previously introduced UTE-FID technique providing spatially resolved FID-spectra was used to measure the frequency distribution pixel-wise for different orientations of the bone axis. RESULTS: The frequency difference between free water in spherical pores and in canals parallel to B0 amounts up to approximately 100 Hz at 3T. Simulated resonance frequencies showed good agreement with the findings in UTE-FID spectra. The intensity ratio of the two signal components (parallel canals and spherical pores) was found to vary between periosteal and endosteal regions. CONCLUSION: Spatially resolved UTE-FID examinations allow the determination of the frequency distribution of signals from free water in cortical bone. This frequency distribution indicates the composition of the signal contributions from nearly spherical cavities and cylindrical canals which allows for further characterization of bone structure and status.

Reproducibility of diffusion-weighted magnetic resonance imaging in head and neck cancer assessed on a 1.5 T MR-Linac and comparison to parallel measurements on a 3 T diagnostic scanner.

BACKGROUND AND PURPOSE: Before quantitative imaging biomarkers (QIBs) acquired with magnetic resonance imaging (MRI) can be used for interventional trials in radiotherapy (RT), technical validation of these QIBs is necessary. The aim of this study was to assess the reproducibility of apparent diffusion coefficient (ADC) values, derived from diffusion-weighted (DW) MRI, in head and neck cancer using a 1.5 T MR-Linac (MRL) by comparison to a 3 T diagnostic scanner (DS). MATERIAL AND METHODS: DW-MRIs were acquired on MRL and DS for 15 head and neck cancer patients before RT and in week 2 and rigidly registered to the planning computed tomography. Mean ADC values were calculated for submandibular (SG) and parotid (PG) glands as well as target volumes (TV, gross tumor volume and lymph nodes), which were delineated based on computed tomography. Mean absolute ADC differences as well as within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs) were calculated for all volumes of interest. RESULTS: A total of 23 datasets were analyzed. Mean ADC difference (DS-MRL) for SG, PG and TV resulted in 142, 254 and 93·10-6 mm2/s. wCVs/ICCs, comparing MRL and DS, were determined as 13.7 %/0.26, 24.4 %/0.23 and 16.1 %/0.73 for SG, PG and TV, respectively. CONCLUSION: ADC values, measured on the 1.5 T MRL, showed reasonable reproducibility with an ADC underestimation in contrast to the DS. This ADC shift must be validated in further experiments and considered for future translation of QIB candidates from DS to MRL for response adaptive RT.

Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma. / Ermittlung aussagekräftiger Bildgebungsbiomarker: Klinische Anwendungen bei Mamma- und Prostatakarzinomen.

BACKGROUND: Imaging biomarkers are quantitative parameters from imaging modalities, which are collected noninvasively, allow conclusions about physiological and pathophysiological processes, and may consist of single (monoparametric) or multiple parameters (bi- or multiparametric). METHOD: This review aims to present the state of the art for the quantification of multimodal and multiparametric imaging biomarkers. Here, the use of biomarkers using artificial intelligence will be addressed and the clinical application of imaging biomarkers in breast and prostate cancers will be explained. For the preparation of the review article, an extensive literature search was performed based on Pubmed, Web of Science and Google Scholar. The results were evaluated and discussed for consistency and generality. RESULTS AND CONCLUSION: Different imaging biomarkers (multiparametric) are quantified based on the use of complementary imaging modalities (multimodal) from radiology, nuclear medicine, or hybrid imaging. From these techniques, parameters are determined at the morphological (e. g., size), functional (e. g., vascularization or diffusion), metabolic (e. g., glucose metabolism), or molecular (e. g., expression of prostate specific membrane antigen, PSMA) level. The integration and weighting of imaging biomarkers are increasingly being performed with artificial intelligence, using machine learning algorithms. In this way, the clinical application of imaging biomarkers is increasing, as illustrated by the diagnosis of breast and prostate cancers. KEY POINTS: · Imaging biomarkers are quantitative parameters to detect physiological and pathophysiological processes.. · Imaging biomarkers from multimodality and multiparametric imaging are integrated using artificial intelligence algorithms.. · Quantitative imaging parameters are a fundamental component of diagnostics for all tumor entities, such as for mammary and prostate carcinomas.. CITATION FORMAT: · Bäuerle T, Dietzel M, Pinker K et al. Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma. Fortschr Röntgenstr 2024; 196: 354 - 362.

Mechanisms of weight loss-induced remission in people with prediabetes: a post-hoc analysis of the randomised, controlled, multicentre Prediabetes Lifestyle Intervention Study (PLIS).

BACKGROUND: Remission of type 2 diabetes can occur as a result of weight loss and is characterised by liver fat and pancreas fat reduction and recovered insulin secretion. In this analysis, we aimed to investigate the mechanisms of weight loss- induced remission in people with prediabetes. METHODS: In this prespecified post-hoc analysis, weight loss-induced resolution of prediabetes in the randomised, controlled, multicentre Prediabetes Lifestyle Intervention Study (PLIS) was assessed, and the results were validated against participants from the Diabetes Prevention Program (DPP) study. For PLIS, between March 1, 2012, and Aug 31, 2016, participants were recruited from eight clinical study centres (including seven university hospitals) in Germany and randomly assigned to receive either a control intervention, a standard lifestyle intervention (ie, DPP-based intervention), or an intensified lifestyle intervention for 12 months. For DPP, participants were recruited from 23 clinical study centres in the USA between July 31, 1996, and May 18, 1999, and randomly assigned to receive either a standard lifestyle intervention, metformin, or placebo. In both PLIS and DPP, only participants who were randomly assigned to receive lifestyle intervention or placebo and who lost at least 5% of their bodyweight were included in this analysis. Responders were defined as people who returned to normal fasting plasma glucose (FPG; <5·6 mmol/L), normal glucose tolerance (<7·8 mmol/L), and HbA1c less than 39 mmol/mol after 12 months of lifestyle intervention or placebo or control intervention. Non-responders were defined as people who had FPG, 2 h glucose, or HbA1c more than these thresholds. The main outcomes for this analysis were insulin sensitivity, insulin secretion, visceral adipose tissue (VAT), and intrahepatic lipid content (IHL) and were evaluated via linear mixed models. FINDINGS: Of 1160 participants recruited to PLIS, 298 (25·7%) had weight loss of 5% or more of their bodyweight at baseline. 128 (43%) of 298 participants were responders and 170 (57%) were non-responders. Responders were younger than non-responders (mean age 55·6 years [SD 9·9] vs 60·4 years [8·6]; p<0·0001). The DPP validation cohort included 683 participants who lost at least 5% of their bodyweight at baseline. Of these, 132 (19%) were responders and 551 (81%) were non-responders. In PLIS, BMI reduction was similar between responders and non-responders (responders mean at baseline 32·4 kg/m2 [SD 5·6] to mean at 12 months 29·0 kg/m2 [4·9] vs non-responders 32·1 kg/m2 [5·9] to 29·2 kg/m2 [5·4]; p=0·86). However, whole-body insulin sensitivity increased more in responders than in non-responders (mean at baseline 291 mL/[min × m2], SD 60 to mean at 12 months 378 mL/[min × m2], 56 vs 278 mL/[min × m2], 62, to 323 mL/[min × m2], 66; p<0·0001), whereas insulin secretion did not differ within groups over time or between groups (responders mean at baseline 175 pmol/mmol [SD 64] to mean at 12 months 163·7 pmol/mmol [60·6] vs non-responders 158·0 pmol/mmol [55·6] to 154·1 pmol/mmol [56·2]; p=0·46). IHL decreased in both groups, without a difference between groups (responders mean at baseline 10·1% [SD 8·7] to mean at 12 months 3·5% [3·9] vs non-responders 10·3% [8·1] to 4·2% [4·2]; p=0·34); however, VAT decreased more in responders than in non-responders (mean at baseline 6·2 L [SD 2·9] to mean at 12 months 4·1 L [2·3] vs 5·7 L [2·3] to 4·5 L [2·2]; p=0·0003). Responders had a 73% lower risk of developing type 2 diabetes than non-responders in the 2 years after the intervention ended. INTERPRETATION: By contrast to remission of type 2 diabetes, resolution of prediabetes was characterised by an improvement in insulin sensitivity and reduced VAT. Because return to normal glucose regulation (NGR) prevents development of type 2 diabetes, we propose the concept of remission of prediabetes in analogy to type 2 diabetes. We suggest that remission of prediabetes should be the primary therapeutic aim in individuals with prediabetes. FUNDING: German Federal Ministry for Education and Research via the German Center for Diabetes Research; the Ministry of Science, Research and the Arts Baden-Württemberg; the Helmholtz Association and Helmholtz Munich; the Cluster of Excellence Controlling Microbes to Fight Infections; and the German Research Foundation.

Identification of radiomic biomarkers in a set of four skeletal muscle groups on Dixon MRI of the NAKO MR study.

In this work, we propose a processing pipeline for the extraction and identification of meaningful radiomics biomarkers in skeletal muscle tissue as displayed using Dixon-weighted MRI. Diverse and robust radiomics features can be identified that may be of aid in the accurate quantification e.g. varying degrees of sarcopenia in respective muscles of large cohorts. As such, the approach comprises the texture feature extraction from raw data based on well established approaches, such as a nnU-Net neural network and the Pyradiomics toolbox, a subsequent selection according to adequate conditions for the muscle tissue of the general population, and an importance-based ranking to further narrow the amount of meaningful features with respect to auxiliary targets. The performance was investigated with respect to the included auxiliary targets, namely age, body mass index (BMI), and fat fraction (FF). Four skeletal muscles with different fiber architecture were included: the mm. glutaei, m. psoas, as well as the extensors and adductors of the thigh. The selection allowed for a reduction from 1015 available texture features to 65 for age, 53 for BMI, and 36 for FF from the available fat/water contrast images considering all muscles jointly. Further, the dependence of the importance rankings calculated for the auxiliary targets on validation sets (in a cross-validation scheme) was investigated by boxplots. In addition, significant differences between subgroups of respective auxiliary targets as well as between both sexes were shown to be present within the ten lowest ranked features by means of Kruskal-Wallis H-tests and Mann-Whitney U-tests. The prediction performance for the selected features and the ranking scheme were verified on validation sets by a random forest based multi-class classification, with strong area under the curve (AUC) values of the receiver operator characteristic (ROC) of 73.03 ± 0.70 % and 73.63 ± 0.70 % for the water and fat images in age, 80.68 ± 0.30 % and 88.03 ± 0.89 % in BMI, as well as 98.36 ± 0.03 % and 98.52 ± 0.09 % in FF.

Longitudinal monitoring of Apparent Diffusion Coefficient (ADC) in patients with prostate cancer undergoing MR-guided radiotherapy on an MR-Linac at 1.5 T: a prospective feasibility study.

BACKGROUND: Hybrid MRI linear accelerators (MR-Linac) might enable individualized online adaptation of radiotherapy using quantitative MRI sequences as diffusion-weighted imaging (DWI). The purpose of this study was to investigate the dynamics of lesion apparent diffusion coefficient (ADC) in patients with prostate cancer undergoing MR-guided radiation therapy (MRgRT) on a 1.5T MR-Linac. The ADC values at a diagnostic 3T MRI scanner were used as the reference standard. PATIENTS AND AND METHODS: In this prospective single-center study, patients with biopsy-confirmed prostate cancer who underwent both an MRI exam at a 3T scanner (MRI3T) and an exam at a 1.5T MR-Linac (MRL) at baseline and during radiotherapy were included. Lesion ADC values were measured by a radiologist and a radiation oncologist on the slice with the largest lesion. ADC values were compared before vs. during radiotherapy (during the second week) on both systems via paired t-tests. Furthermore, Pearson correlation coefficient and inter-reader agreement were computed. RESULTS: A total of nine male patients aged 67 ± 6 years [range 60 - 67 years] were included. In seven patients, the cancerous lesion was in the peripheral zone, and in two patients the lesion was in the transition zone. Inter-reader reliability regarding lesion ADC measurement was excellent with an intraclass correlation coefficient of (ICC) > 0.90 both at baseline and during radiotherapy. Thus, the results of the first reader will be reported. In both systems, there was a statistically significant elevation of lesion ADC during radiotherapy (mean MRL-ADC at baseline was 0.97 ± 0.18 × 10-3 mm2/s vs. mean MRL-ADC during radiotherapy 1.38 ± 0.3 × 10-3 mm2/s, yielding a mean lesion ADC elevation of 0.41 ± 0.20 × 10-3 mm2/s, p < 0.001). Mean MRI3T-ADC at baseline was 0.78 ± 0.165 × 10-3 mm2/s vs. mean MRI3T-ADC during radiotherapy 0.99 ± 0.175 × 10-3 mm2/s, yielding a mean lesion ADC elevation of 0.21 ± 0.96 × 10-3 mm2/s p < 0.001). The absolute ADC values from MRL were consistently significantly higher than those from MRI3T at baseline and during radiotherapy (p < = 0.001). However, there was a strong positive correlation between MRL-ADC and MRI3T-ADC at baseline (r = 0.798, p = 0.01) and during radiotherapy (r = 0.863, p = 0.003). CONCLUSIONS: Lesion ADC as measured on MRL increased significantly during radiotherapy and ADC measurements of lesions on both systems showed similar dynamics. This indicates that lesion ADC as measured on the MRL may be used as a biomarker for evaluation of treatment response. In contrast, absolute ADC values as calculated by the algorithm of the manufacturer of the MRL showed systematic deviations from values obtained on a diagnostic 3T MRI system. These preliminary findings are promising but need large-scale validation. Once validated, lesion ADC on MRL might be used for real-time assessment of tumor response in patients with prostate cancer undergoing MR-guided radiation therapy.

Thoracic lymphatic anomalies in patients with univentricular hearts: correlation of morphologic findings in isotropic T2-weighted MRI with the outcome after fontan palliation.

Objectives: In this study we examined the correlation between the extent of thoracic lymphatic anomalies in patients after surgical palliation by total cavopulmonary connection (TCPC) and their outcome in terms of clinical and laboratory parameters. Materials and methods: We prospectively examined 33 patients after TCPC with an isotropic heavily T2-weighted MRI sequence on a 3.0 T scanner. Examinations were performed after a solid meal, slice thickness of 0.6 mm, TR of 2400 ms, TE of 692 ms, FoV of 460 mm, covering thoracic and abdominal regions. Findings of the lymphatic system were correlated with clinical and laboratory parameters obtained at the annual routine check-up. Results: Eight patients (group 1) showed type 4 lymphatic abnormalities. Twentyfive patients (group 2) presented less severe anomalies (type 1-3). In the treadmill CPET, group 2 reached step 7.0;6.0/8.0 vs. 6.0;3.5/6.8 in group 1 (p = 0.006*) and a distance of 775;638/854 m vs. 513;315/661 m (p = 0.006*). In the laboratory examinations, group 2 showed significantly lower levels of AST, ALT and stool calprotectin as compared to group 1. There were no significant differences in NT-pro-BNP, total protein, IgG, lymphocytes or platelets, but trends. A history of ascites showed 5/8 patients in group 1 vs. 4/25 patients in group 2 (p = 0.02*), PLE occurred in 4/8 patient in group 1 vs. 1/25 patients in group 2 (p = 0.008*). Conclusion: In the long-term follow-up after TCPC, patients with severe thoracic and cervical lymphatic abnormalities showed restrictions in exercise capacity, higher liver enzymes and an increased rate of symptoms of imminent Fontan-failure such as ascites and PLE.

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.

Automated shape-independent assessment of the spatial distribution of proton density fat fraction in vertebral bone marrow.

This work proposes a method for automatic standardized assessment of bone marrow volume and spatial distribution of the proton density fat fraction (PDFF) in vertebral bodies. Intra- and interindividual variability in size and shape of vertebral bodies is a challenge for comparable interindividual evaluation and monitoring of changes in the composition and distribution of bone marrow due to aging and/or intervention. Based on deep learning image segmentation, bone marrow PDFF of single vertebral bodies is mapped to a cylindrical template and corrected for the inclination with respect to the horizontal plane. The proposed technique was applied and tested in a cohort of 60 healthy (30 males, 30 females) individuals. Obtained bone marrow volumes and mean PDFF values are comparable to former manual and (semi-)automatic approaches. Moreover, the proposed method allows shape-independent characterization of the spatial PDFF distribution inside vertebral bodies.

The role of hepatokines in NAFLD.

Non-alcoholic fatty liver disease (NAFLD) is not only a consequence of insulin resistance, but it is also an important cause of insulin resistance and major non-communicable diseases (NCDs). The close relationship of NAFLD with visceral obesity obscures the role of fatty liver from visceral adiposity as the main pathomechanism of insulin resistance and NCDs. To overcome this limitation, in analogy to the concept of adipokines, in 2008 we introduced the term hepatokines to describe the role of fetuin-A in metabolism. Since then, several other hepatokines were tested for their effects on metabolism. Here we address the dysregulation of hepatokines in people with NAFLD. Then, we discuss pathophysiological mechanisms of cardiometabolic diseases specifically related to NAFLD by focusing on hepatokine-related organ crosstalk. Finally, we propose how the determination of major hepatokines and adipokines can be used for pathomechanism-based clustering of insulin resistance in NAFLD and visceral obesity to better implement precision medicine in clinical practice.

Lower Hepatic Fat Is Associated With Improved Insulin Secretion in a High-Risk Prediabetes Subphenotype During Lifestyle Intervention.

The objective of this work was to investigate whether impaired insulin secretion can be restored by lifestyle intervention in specific subphenotypes of prediabetes. We assigned 1,045 participants from the Prediabetes Lifestyle Intervention Study (PLIS) to six recently established prediabetes clusters. Insulin secretion was assessed by a C-peptide-based index derived from oral glucose tolerance tests and modeled from three time points during a 1-year intervention. We also analyzed the change of glycemia, insulin sensitivity, and liver fat. All prediabetes high-risk clusters (cluster 3, 5, and 6) had improved glycemic traits during the lifestyle intervention, whereas insulin secretion only increased in clusters 3 and 5 (P < 0.001); however, high liver fat in cluster 5 was associated with a failure to improve insulin secretion (Pinteraction < 0.001). Thus, interventions to reduce liver fat have the potential to improve insulin secretion in a defined subgroup of prediabetes.

Soy lecithin: A beneficial substance for adjusting the ADC in aqueous solutions to the values of biological tissues.

PURPOSE: To test soy lecithin as a substance added to water for the construction of MRI phantoms with tissue-like diffusion coefficients. The performance of soy lecithin was assessed for the useable range of adjustable ADC values, the degree of non-Gaussian diffusion, simultaneous effects on relaxation times, and spectral signal properties. METHODS: Aqueous soy lecithin solutions of different concentrations (0%, 0.5%, 1%, 2%, 3% …, 10%) and soy lecithin-agar gels were prepared and examined on a 3 Tesla clinical scanner at 18.5° ± 0.5°C. Echoplanar sequences (b values: 0-1000/3000 s/mm2 ) were applied for ADC measurements. Quantitative relaxometry and MRS were performed for assessment of T1 , T2 , and detectable spectral components. RESULTS: The presence of soy lecithin significantly restricts the diffusion of water molecules and mimics the nearly Gaussian nature of diffusion observed in tissue (for b values <1000 s/mm2 ). ADC values ranged from 2.02 × 10-3  mm2 /s to 0.48 × 10-3  mm2 /s and cover the entire physiological range reported on biological tissue. Measured T1 /T2 values of pure lecithin solutions varied from 2685/2013 to 668/133 ms with increasing concentration. No characteristic signals of soy lecithin were observed in the MR spectrum. The addition of agar to the soy lecithin solutions allowed T2 values to be well adjusted to typical values found in parenchymal tissue without affecting the soy lecithin-controlled ADC value. CONCLUSION: Soy lecithin is a promising substance for the construction of diffusion phantoms with tissue-like ADC values. It provides several advantages over previously proposed substances, in particular a wide range of adjustable ADC values, the lack of additional 1 H-signals, and the possibility to adjust ADC and T2 values (by adding agar) almost independently of each other.

Classification-guided Neural Network-based Correction of Magnetic Resonance-related Gradient Artifact Residuals in Simultaneously Recorded Surface Electromyography.

Spontaneous muscular activities can be studied by simultaneous recordings of surface electromyography (sEMG) and diffusion-weighted magnetic resonance imaging (DW-MRI). For reliable assessment of the spontaneous activity rate in sEMG data during active MR imaging, it is necessary to have a decent gradient artifact (GA) correction algorithm enabling the detection of small spontaneous activities with an amplitude of few microvolts. In this work, a neural network with weak label annotations during the training process is utilized for enhanced correction of GA residuals in the sEMG recordings. Based on sEMG signal decomposition and class-activation maps from the neural network classification, the amount of GA residuals is iteratively decreased in the sEMG signal. This leads to a reduction of the false-positive rate in automated spontaneous activity detection. Quality of GA residual correction is therefore estimated by using a specialized second neural network model. Clinical relevance- This work establishes an improved GA residual correction for simultaneously recorded sEMG data during MRI to enhance the ability for small spontaneous activity detection.

Repeatability of diffusion-weighted magnetic resonance imaging in head and neck cancer at a 1.5 T MR-Linac.

BACKGROUND AND PURPOSE: Functional information acquired through diffusion-weighted magnetic resonance imaging (DW-MRI) may be beneficial for personalized head and neck cancer (HNC) radiotherapy. Technical validation is required before DW-MRI based radiotherapy interventions can be realized clinically. The aim of this study was to assess the repeatability of apparent diffusion coefficients (ADC) derived from DW-MRI in HNC using echo-planar imaging (EPI) on a 1.5 T MR-Linac. MATERIAL AND METHODS: A total of eleven HNC patients underwent test/retest DW-MRI scans at least once per week during fractionated radiotherapy at the MR-Linac. An EPI DW-MRI test scan (b = 0, 150, 500 s/mm2) was acquired before the start of adaptive MR-guided radiotherapy in addition to an identical retest scan after irradiation. Volumes-of-interest (VOI) were defined manually for parotid (PTs) and submandibular glands (SMs), gross tumor volume (GTV) and lymph nodes (LNs). Mean ADC was calculated for all VOI in all test/retest scans. Absolute/relative repeatability coefficients (RCs/relRCs) as well as intraclass correlation coefficients (ICCs) were determined for all VOIs. RESULTS: A total of 81 datasets were analyzed. Mean test ADC values were 1380/1416, 950/1010, 1520 and 1344 · 10-6 mm2/s for left/right SM and PT, GTV and LNs, respectively. Accordingly, RC (relRC) values were determined as 271/281 (19.4/21.8%) and 138/155 (13.3/15.2%), 457 (31.3%) and 310 · 10-6 mm2/s (23.5%). ICC resulted in 0.80/0.87, 0.97/0.94, 0.75 and 0.83 for left/right SM and PT, GTV and LNs, respectively. CONCLUSION: The repeatability of ADC derived from EPI DW-MRI at the 1.5 T MR-Linac appears reasonable to be used for future biologically adapted MR-guided radiotherapy.