Objectives:Alterations in neural language networks are common in patients with brain tumors, yet their nature varies substantially across individuals. By reducing data to group-level averages, conventional analyses fail to capture such heterogeneity, obscuring patient-specific information. Methods:The present study applied a resting-state connectivity fingerprinting approach to characterize language network alterations at the single-subject level, yielding individualized connectivity profiles ("fingerprints"). Fingerprints of 27 right-handed patients with a left-hemisphere brain tumor affecting language-relevant areas were assessed at three time points (preoperative, immediate postoperative and three-month follow-up). Connectivity patterns were compared to a normative reference derived from 30 healthy participants and linked to language performance. Results:Fingerprints remained temporally stable in healthy individuals. In patients, fingerprints revealed distinct, patient-specific deviations from the typical network structure with highly heterogeneous changes over time. Three main findings emerged: (1) patients with language deficits showed greater deviations from the typical fingerprint than those without deficits; (2) significant associations between larger deviations and poorer language performance were confined to the immediate postoperative phase, likely reflecting surgery- or treatment-related influences or differences in the (mal)adaptivity of reorganization over time; (3) in high-grade glioma, exploratory analyses provided preliminary evidence for an adaptive contribution of the contralesional hemisphere immediately after surgery. Conclusions:The findings support connectivity fingerprinting as a promising approach for characterizing patient-specific network patterns and monitoring functional reorganization processes relevant to language function at the single-subject level. With continued methodological refinement, this approach holds potential for contributing to more individualized clinical decision-making within the context of personalized medicine.

Background: Navigated repetitive TMS (nrTMS) is widely used for non-invasive mapping of cortical functions. Methodological improvement might be achieved by optimizing coil positioning based on electric-field modeling and augmented reality (AR)-guided neuronavigation to enhance spatial targeting accuracy and stimulation-induced language errors. Therefore, we compared electric-field-optimized, AR-guided nrTMS with conventional nrTMS using manually planned coil positioning. Methods: Twenty-eight healthy subjects underwent two MRI-guided left hemispheric nrTMS language mapping sessions. Each session used 10 Hz stimulation at a 100% resting motor threshold applied for 1.5 s per region of interest (ROI) during a synchronized object naming task. ROIs were defined according to the Corina cortical parcellation system. Manually defined and electric-field-optimized coil placements obtained using SimNIBS (v4.1.0) were applied; the optimized session was assisted by AR goggles. The primary outcome was the quantitative and categorical differences in cortical regions mapped as language-eloquent. Resting-state fMRI was acquired to provide a reference for comparing nrTMS-derived language maps. Outcomes: Electric-field-optimized nrTMS did not result in an increase in positively mapped ROIs. A different distribution of language errors was observed between sessions. Manual mapping roughly followed the extracted resting-state language and motor networks, whereas electric-field-optimized mapping might correspond less. Optimized coil positions were not always practically feasible. AR guidance improved target location accuracy. Conclusions: While AR was a useful addition to the TMS experiment, electric-field optimization did not translate into significant behavioral differences. However, altered distribution of language errors can give insight into underlying neurophysiological processes of rTMS.

PURPOSE:This study investigates the causal mechanisms underlying radiology report generation by analyzing how clinical information and prior imaging examinations contribute to annotation shifts. We systematically estimate why and how biases manifest, providing insights into the data generation process that influences radiology reporting. METHODS:This retrospective study analyzes 172,380 chest X-ray reports from 45,561 distinct patients in the MIMIC-IV CXR database. The study focuses on conditional effects for the diseases pneumonia, pleurisy, heart failure, rib fracture, and COPD. Propensity score matching is employed to balance the treatment and control groups, followed by logistic regression and neural network models to estimate causal effects. Statistical analysis involves calculating risk differences and 95% confidence intervals to determine significance (p ≤ 0.05). Sensitivity analysis is deployed to estimate the robustness of the effect estimates. RESULTS:The inclusion of clinical questions significantly influences the reporting of key observational findings. For instance, the probability of mentioning cardiomegaly increases by 15% (p ≤ 0.05) when a clinical question is posed conditioned on rib fracture. Similar effects are observed for support devices across multiple diseases. However, the impact of clinical information varies by disease. For instance, in the presence of clinical questions, the mention of pneumonia increases significantly for one disease, while for others there is no significant effect. CONCLUSION:This study demonstrates how annotation bias in radiology reports arises from clinical context and prior imaging access. Understanding these causal mechanisms is essential for mitigating biases in dataset curation, ensuring more reliable AI models, and improving the generalizability of multimodal medical imaging systems.

Background Magnetic resonance (MR) diffusion tensor imaging (DTI) is a new, non-invasive method to investigate arterial vessel walls. High resolution diffusion weighted imaging (DWI) in combination with a two-dimensional (2D) diffusion gradient sampling scheme has recently been demonstrated as feasible for evaluating diffusivity in the vessel wall of human carotids. We aimed to identify associations of altered diffusivity in human carotids with presence or absence of cardiovascular disease, body mass index (BMI), sex and age in a clinical setting. Methods In this single center case-control study we used DWI in combination with a 2D gradient in a 3 T MRI scanner to evaluate diffusivity parameters in carotid vessel walls of clinical patients with known cardiovascular disease (n = 17) and healthy controls (n = 21). We used a read-out segmented EPI (rs-EPI) sequence for DWI. Results A group comparison showed significantly decreased fractional anisotropy (FA) in patients older than 60 years (p < 0.001) and in patients with a BMI higher than 25 (p = 0.019). Patients with cardiovascular disease had higher values for mean diffusivity (p = 0.005) than patients without cardiovascular disease. A multiple linear regression analysis showed age and sex to be associated with FA. Conclusion Two-dimensional vessel wall DTI of human carotids is feasible for clinical research. Besides patient age, we identified Sex, BMI, or the presence of cardiovascular disease as relevant factors for carotid vessel wall diffusivity. Decreased FA values might indicate early-stage atherosclerosis and vascular ageing.

BACKGROUND:Walking impairment is one of the most debilitating symptoms of multiple sclerosis (MS). A better understanding of brain mechanisms underlying successful gait training could help to improve development of targeted therapy. We therefore investigated changes in brain activation associated with improvements in walking function after rhythmic-cued gait training. METHODS:Thirty-one people with MS (pwMS; median EDSS = 2.5, range:2.0-5.0) and 17 age- and sex-matched healthy controls (HC) completed behavioural and MRI assessments at baseline and post-intervention (four weeks after baseline). All included pwMS received a four-week actual and/or imagined gait training with rhythmic-auditory cueing, while HC received no intervention. All participants performed a bipedal ankle plantar- and dorsiflexion and a corresponding motor-imagery task during fMRI. PwMS displaying a > 5 % walking distance increase in the 2-Minute Walk Test (2MWT) from baseline to post-intervention were defined as responders. RESULTS:Responders did not differ from non-responders in terms of demographics, clinical variables, and walking function at baseline. Responders, non-responders, and HC showed similar movement-related brain activation at baseline. At post-intervention, responders showed decreased brain activation within the premotor cortex, precuneus, and middle frontal gyrus during the movement task. Stronger decreases within these areas were associated with higher walking function improvements in all pwMS after controlling for potential confounders. No association was observed between walking function and motor imagery-related brain activation changes. CONCLUSION:Improved walking function after rhythmic-cued gait training was associated with reduced brain activation in motor planning and attention areas. This suggests a more efficient recruitment of areas subserving motor function after successful training.

BACKGROUND AND PURPOSE:Wall enhancement of untreated intracranial aneurysms on MR imaging is thought to predict aneurysm instability. Wall enhancement or enhancement of the aneurysm cavity in coiled intracranial aneurysms is discussed controversially in the literature regarding potential healing mechanisms or adverse inflammatory reactions. Our aim was to compare the occurrence of aneurysm wall enhancement and cavity enhancement between completely occluded intracranial aneurysms and recanalized aneurysms after initially complete coil embolization. MATERIALS AND METHODS:In this single-center cross-sectional study, we evaluated intracranial aneurysms after successful coil embolization for aneurysm recanalization, wall enhancement, and cavity enhancement with 3T MR imaging. We then compared the incidence of wall enhancement and cavity enhancement of completely occluded aneurysms with aneurysms with recanalization using the χ2 test and performed a multivariate linear regression analysis with recanalization size as an independent variable. RESULTS:We evaluated 59 patients (mean age, 54.7 [SD, 12.4] years; 48 women) with 60 intracranial aneurysms and found a significantly higher incidence of wall enhancement in coiled aneurysms with recanalization (n=38) compared with completely occluded aneurysms (n = 22, P = .036). In addition, there was a significantly higher incidence of wall enhancement in aneurysms with recanalization of >3 mm (P = .003). In a multivariate linear regression analysis, wall enhancement (P = .010) and an increase of overall aneurysm size after embolization (P < .001) were significant predictors of recanalization size (corrected R 2= 0.430, CI 95%). CONCLUSIONS:The incidence of aneurysm wall enhancement is increased in coiled intracranial aneurysms with recanalization and is associated with recanalization size.

Background: Knowledge about factors that are associated with post -stroke cognitive outcome is important to identify patients with high risk for impairment. We therefore investigated the associations of white matter integrity and functional connectivity (FC) within the brain 's default -mode network (DMN) in acute stroke patients with cognitive outcome three months post -stroke. Methods: Patients aged between 18 and 85 years with an acute symptomatic MRI-proven unilateral ischemic middle cerebral artery infarction, who had received reperfusion therapy, were invited to participate in this longitudinal study. All patients underwent brain MRI within 24 -72 h after symptom onset, and participated in a neuropsychological assessment three months post -stroke. We performed hierarchical regression analyses to explore the incremental value of baseline white matter integrity and FC beyond demographic, clinical, and macrostructural information for cognitive outcome. Results: The study cohort comprised 34 patients (mean age: 64 +/- 12 years, 35% female). The initial median National Institutes of Health Stroke Scale (NIHSS) score was 10, and significantly improved three months poststroke to a median NIHSS = 1 ( p < .001). Nonetheless, 50% of patients showed cognitive impairment three months post -stroke. FC of the non-lesioned anterior cingulate cortex of the affected hemisphere explained 15% of incremental variance for processing speed ( p = .007), and fractional anisotropy of the non-lesioned cingulum of the affected hemisphere explained 13% of incremental variance for cognitive flexibility ( p = .033). Conclusions: White matter integrity and functional MRI markers of the DMN in acute stroke explain incremental variance for post -stroke cognitive outcome beyond demographic, clinical, and macrostructural information.

Transcranial magnetic stimulation (TMS) has emerged as a promising neuromodulation technique with both therapeutic and diagnostic applications. As accurate coil placement is known to be essential for focal stimulation, computational models have been established to help find the optimal coil positioning by maximizing electric fields at the cortical target. While these numerical simulations provide realistic and subject-specific field distributions, they are computationally demanding, precluding their use in real-time applications. In this paper, we developed a novel multi-task deep neural network which simultaneously predicts the optimal coil placement for a given cortical target as well as the associated TMS-induced electric field. Trained on large amounts of preceding numerical optimizations, the Attention U-Net-based neural surrogate provided accurate coil optimizations in only 35 ms, a fraction of time compared to the state-of-the-art numerical framework. The mean errors on the position estimates were below 2 mm, i.e., smaller than previously reported manual coil positioning errors. The predicted electric fields were also highly correlated (r> 0.97) with their numerical references. In addition to healthy subjects, we validated our approach also in glioblastoma patients. We first statistically underlined the importance of using realistic heterogeneous tumor conductivities instead of simply adopting values from the surrounding healthy tissue. Second, applying the trained neural surrogate to tumor patients yielded similar accurate positioning and electric field estimates as in healthy subjects. Our findings provide a promising framework for future real-time electric field-optimized TMS applications.

Recent advances in deep learning and natural language processing (NLP) have opened many new opportunities for automatic text understanding and text processing in the medical field. This is of great benefit as many clinical downstream tasks rely on information from unstructured clinical documents. However, for low-resource languages like German, the use of modern text processing applications that require a large amount of training data proves to be difficult, as only few data sets are available mainly due to legal restrictions. In this study, we present an information extraction framework that was initially pre-trained on real-world computed tomographic (CT) reports of head examinations, followed by domain adaptive fine-tuning on reports from different imaging examinations. We show that in the pre-training phase, the semantic and contextual meaning of one clinical reporting domain can be captured and effectively transferred to foreign clinical imaging examinations. Moreover, we introduce an active learning approach with an intrinsic strategic sampling method to generate highly informative training data with low human annotation cost. We see that the model performance can be significantly improved by an appropriate selection of the data to be annotated, without the need to train the model on a specific downstream task. With a general annotation scheme that can be used not only in the radiology field but also in a broader clinical setting, we contribute to a more consistent labeling and annotation process that also facilitates the verification and evaluation of language models in the German clinical setting.

Objective:In contrast to the rising amount of financial investments for research and development in medical technology worldwide is the lack of usability and clinical readiness of the produced systems. We evaluated an augmented reality (AR) setup under development for preoperative perforator vessel mapping for elective autologous breast reconstruction.Methods:In this grant-supported research pilot, we used magnetic resonance angiography data (MR-A) of the trunk to superimpose the scans on the corresponding patients with hands-free AR goggles to identify regions-of-interest for surgical planning. Perforator location was assessed using MR-A imaging (MR-A projection) and Doppler ultrasound data (3D distance) and confirmed intraoperatively in all cases. We evaluated usability (System Usability Scale, SUS), data transfer load and documented personnel hours for software development, correlation of image data, as well as processing duration to clinical readiness (time from MR-A to AR projections per scan).Results:All perforator locations were confirmed intraoperatively, and we found a strong correlation between MR-A projection and 3D distance measurements (Spearman r = 0.894). The overall usability (SUS) was 67 ± 10 (=moderate to good). The presented setup for AR projections took 173 min to clinical readiness (=availability on AR device per patient).Conclusion:In this pilot, we calculated development investments based on project-approved grant-funded personnel hours with a moderate to good usability outcome resulting from some limitations: assessment was based on one-time testing with no previous training, a time lag of AR visualizations on the body and difficulties in spatial AR orientation. The use of AR systems can provide new opportunities for future surgical planning, but has more potential for educational (e.g., patient information) or training purposes of medical under- and postgraduates (spatial recognition of imaging data associated with anatomical structures and operative planning). We expect future usability improvements with refined user interfaces, faster AR hardware and artificial intelligence-enhanced visualization techniques.

Objectives: Telomeres are DNA-protein complexes at the ends of linear chromosomes that protect against DNA degradation. Telomeres shorten during normal cell divisions and therefore, telomere length is an indicator of mitotic-cell age. In humans, telomere shortening is a potential biomarker for disease risk, progression and premature death. Physical activity has been associated with longer leukocyte telomere length (LTL) in some studies. In the current study the relationship between LTL, thigh muscle mass and adipose tissue distribution was explored.Methods: We performed anthropometric measurements and magnetic resonance imaging (MRI) measurements of the thigh in 149 healthy subjects (77 male, 72 female). LTL was measured using qPCR. Additionally, the subjects answered a questionnaire concerning their training behaviour.Results: In male subjects, LTL was significantly associated with thigh muscle mass, independent of age and body mass index (p=0.006). In addition, a slight association of LTL with weekly endurance units in the male group was found. These relations could not be observed in females.Conclusions: In conclusion, we observed a sex-specific association of LTL and thigh muscle mass in healthy males. The reason of this sex-specific association is currently unclear, but could be related to different training effects and/or hormonal pathways in men and women.

Short-chain fatty acids (SCFAs) are circulating metabolites generated by gut microbiota. Recently, a link between age-related muscle loss and gut microbiota has been described, and SCFAs could play a mediating role in this relationship. Acetic, propionic, and butyric acid are the abundant forms and are considered to have health benefits, less is known about valeric and caproic acid.In a cross-sectional study including 155 healthy volunteers, we investigated the relationship between muscle area, as well as intramuscular adipose tissue measured by magnet resonance imaging and circulating SCFAs. SCFAs and additional parameters were measured from serum and sport activities recorded by means of a questionnaire.We found a significant positive association between valeric acid (VA) levels and the thigh cross-sectional muscle area in males. This relationship was independent of age, BMI and weekly training times and was not observed in females. No associations between other SCFAs and the thigh muscle cross-sectional area were observed.To our knowledge, this is the first human study demonstrating a significant relationship between thigh muscle mass and VA, supporting the thesis of the “gut–muscle axis” with VA as a possible interacting player, on the one hand, affected by sex differences, on the other.### Competing Interest StatementThe authors have declared no competing interest.### Funding StatementThe author(s) received no specific funding for this work.### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:. This study was approved by the local Ethics Committee of the Medical University Graz (approval num-ber: EK-Nr. 29-585 ex 16/17).I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesAll relevant data are within the manuscript and its Supporting Information files.* CA : caproic acid (C6) FFA : free fatty acids GC-EI/MS : gas chromatograph-electron impact-mass spectrometer IMAT : intramuscular adipose tissue MA : muscle area MRI : magnet resonance imaging MTBE : methyl tert-butyl ether SCFA : short-chain fatty acids SMA : spinal muscular atrophy SMN : survival motoneuron VA : valeric acid (C5)

Background: PCSK9 antibodies strongly reduce LDL cholesterol. The effects of PCSK9 antibodies on triglyceride metabolism are less pronounced. The present study aimed to investigate in detail the effects of alirocumab on triglycerides, triglyceride-rich lipoproteins, and lipase regulators. Methods: A total of 24 patients with an indication for treatment with PCSK9 antibodies were recruited. There were two visits at the study site: the first before initiation of treatment with alirocumab and the second after 10 weeks of treatment. Fat-tolerance tests, nuclear magnetic resonance spectroscopy, and enzyme-linked immunosorbent assays were performed to analyze lipid metabolism. Results: A total of 21 participants underwent the first and second investigation. Among these, two participants only received alirocumab twice and 19 patients completed the trial per protocol. All of them had atherosclerotic vascular disease. There was no significant effect of alirocumab treatment on fasting triglycerides, post-prandial triglycerides, or lipoprotein-lipase regulating proteins. Total, large, and small LDL particle concentrations decreased, while the HDL particle concentration increased (all p < 0.001). Mean total circulating PCSK9 markedly increased in response to alirocumab treatment (p < 0.001). Whereas PCSK9 increased more than three-fold in all 19 compliant patients, it remained unchanged in those two patients with two injections only. Conclusion: Significant effects of alirocumab on triglyceride metabolism were not detectable in the ALIROCKS trial. The total circulating PCSK9 concentration might be a useful biomarker to differentiate non-adherence from non-response to PCSK9 antibodies.

Objectives:There is evidence of involvement of the venous system in multiple sclerosis (MS). If this bears also an association with the frequency and extent of developmental venous anomalies (DVA) still has to be determined. We therefore investigated this in patients with different phenotypes of MS and in comparison, to a control population.Methods:We analyzed the contrast-enhanced T1-weighted MR scans of 431 patients (clinically isolated syndrome-CIS, n = 108; MS, n = 323) and of 162 control individuals for the presence of a DVA. We also measured the size of the DVA and draining vein and compared the DVA frequency between MS phenotypes.Results:A DVA was found in 38 (8.8 %) of patients with CIS or MS and in 11 (6.8%) controls (p = 0.4). DVA frequency was highest in CIS (14.8%) and lowest in progressive MS (4.0%). The mean cranio-caudal and axial extension of the DVA was significantly lower in MS patients than controls (p < 0.05).Conclusions:The frequency of DVA in MS patients is comparable to that in controls. Whether DVA size and appearance may change over time will have to be investigated in a longitudinal manner and with larger sample size.

When developing artificial intelligence (AI) software for applications in radiology, the underlying research must be transferable to other real-world problems. To verify to what degree this is true, we reviewed research on AI algorithms for computed tomography of the head. A systematic review was conducted according to the preferred reporting items for systematic reviews and meta-analyses. We identified 83 articles and analyzed them in terms of transparency of data and code, pre-processing, type of algorithm, architecture, hyperparameter, performance measure, and balancing of dataset in relation to epidemiology. We also classified all articles by their main functionality (classification, detection, segmentation, prediction, triage, image reconstruction, image registration, fusion of imaging modalities). We found that only a minority of authors provided open source code (10.15%, n 0 7), making the replication of results difficult. Convolutional neural networks were predominantly used (32.61%, n = 15), whereas hyperparameters were less frequently reported (32.61%, n = 15). Data sets were mostly from single center sources (84.05%, n = 58), increasing the susceptibility of the models to bias, which increases the error rate of the models. The prevalence of brain lesions in the training (0.49 ± 0.30) and testing (0.45 ± 0.29) datasets differed from real-world epidemiology (0.21 ± 0.28), which may overestimate performances. This review highlights the need for open source code, external validation, and consideration of disease prevalence.

Even though whole-body MRI becomes more accessible, its use is still restricted by technical limitations such as field of view and resolution. To minimize artifacts caused by respiratory motion, the acquisition time can be reduced to a feasible breath-hold by decreasing the image size. Conversely, a series of acquisitions is required to cover a larger extent. While the method is effective for individual acquisitions, different respiratory states introduce artifacts when a composite image is reconstructed from the series. In this paper, we propose a deformable registration method for low-overlapping MRI to compensate for such artifacts and facilitate seamless mosaicing. Based on an unsupervised learning-based model, our method generalizes well to different modalities and target anatomies. We demonstrate this on a dataset of 16 abdominal MRI series from a medical use case as well as synthetic image pairs generated from a large heterogeneous dataset, with 13% to 24% overlap. The evaluation shows an improved Dice Similarity Coefficient (DSC) for target structures in the overlap region by +0.14 (from 0.73) for real and +0.21 (from 0.68) for synthetic image pairs. Our method is fast and robust and may be applied to various mosaicing tasks.

Introduction Motor imagery (MI) refers to the mental rehearsal of a physical action without muscular activity. Our previous studies showed that MI combined with rhythmic-auditory cues improved walking, fatigue and quality of life (QoL) in people with multiple sclerosis (pwMS). Largest improvements were seen after music and verbally cued MI. It is unclear whether actual cued gait training achieves similar effects on walking as cued MI in pwMS. Furthermore, in pwMS it is unknown whether any of these interventions leads to changes in brain activation. The purpose of this study is therefore to compare the effects of imagined and actual cued gait training and a combination thereof on walking, brain activation patterns, fatigue, cognitive and emotional functioning in pwMS. Methods and analysis A prospective double-blind randomised parallel multicentre trial will be conducted in 132 pwMS with mild to moderate disability. Randomised into three groups, participants will receive music, metronome and verbal cueing, plus MI of walking (1), MI combined with actual gait training (2) or actual gait training (3) for 30 min, 4× per week for 4 weeks. Supported by weekly phone calls, participants will practise at home, guided by recorded instructions. Primary endpoints will be walking speed (Timed 25-Foot Walk) and distance (2 min Walk Test). Secondary endpoints will be brain activation patterns, fatigue, QoL, MI ability, anxiety, depression, cognitive functioning, music-induced motivation-to-move, pleasure, arousal and self-efficacy. Data will be collected at baseline, postintervention and 3-month follow-up. MRI reference values will be generated using 15 matched healthy controls. Ethics and dissemination This study follows the Standard Protocol Items: Recommendations for Interventional Trials-PRO Extension. Ethical approval was received from the Ethics Committees of the Medical Universities of Innsbruck (1347/2020) and Graz (33-056 ex 20/21), Austria. Results will be disseminated via national and international conferences and published in peer-reviewed journals. Trial registration number DRKS00023978.

Background: Short-term effects of alirocumab on vascular function have hardly been investigated. Moreover, there is a scarce of reliable non-invasive methods to evaluate atherosclerotic changes of the vasculature. The ALIROCKS trial was performed to address these issues using standard ultrasound-based procedures and a completely novel magnetic resonance-based imaging technique. Methods: A total of 24 patients with an indication for treatment with PCSK9 antibodies were recruited. There were 2 visits to the study site, the first before initiation of treatment with alirocumab and the second after 10 weeks of treatment. The key outcome measures included the change of carotid vessel wall fractional anisotropy, a novel magnetic resonance-based measure of vascular integrity, and the changes of carotid intima-media thickness and flow-dependent dilatation of the brachial artery measured with ultrasound. Results: A total of 19 patients completed the trial, 2 patients stopped treatment, 3 patients did not undergo the second visit due to the COVID pandemic. All of them had atherosclerotic vascular disease. Their mean (standard deviation) LDL-cholesterol concentration was 154 (85) mg/dL at baseline and was reduced by 76 (44) mg/dL in response to alirocumab treatment (p < 0.001, n = 19). P-selectin and vascular endothelial growth factors remained unchanged. Flow-dependent dilatation of the brachial artery (+41%, p = 0.241, n = 18), carotid intima-media thickness (p = 0.914, n = 18), and fractional anisotropy of the carotid artery (p = 0.358, n = 13) also did not significantly change. Conclusion: Despite a nominal amelioration for flow-dependent dilatation, significant effects of short-term treatment with alirocumab on vascular function were not detectable. More work would be needed to evaluate, whether fractional anisotropy may be useful in clinical atherosclerosis research.

Osteocalcin, in its non-carboxylated form, has a positive effect on glucose metabolism. Additionally, osteocalcin levels are related to body composition, especially muscle mass. The relation to the distribution of different adipose tissue types, such as subcutaneous, intermuscular, and visceral adipose tissue, is unclear. This study aimed to investigate associations between serum osteocalcin and the distribution of subcutaneous and intermuscular adipose tissue of the mid-thigh. Furthermore, the influence of different training methods on osteocalcin levels was investigated. We performed adipose tissue quantification of subcutaneous adipose tissue (SAT) and intramuscular adipose tissue (IMAT) using MRI measurements of the mid-thigh in 128 volunteers (63 male/65 female). Laboratory analysis included blood lipid panel, serum insulin, adiponectin, and osteocalcin measurements. The main observation was a significant correlation of total serum osteocalcin (TOC) and the distribution of adipose tissue of the mid-thigh (SAT/(SAT + IMAT)) (cc = −0.29/p-value = 0.002), as well as the cross-sectional muscle area (MA), increasing with the weekly resistance training duration in males. Additionally, TOC (p-value = 0.01) and MA (p-value = 0.03) were negatively related to serum insulin. The significant relationship between TOC and SAT/(SAT + IMAT) is a new finding and confirms the negative influence of IMAT on glucose metabolism in a sex-specific approach. We could substantiate this by the negative relation of TOC with serum insulin.