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For lensed galaxy SGAS J111020.0+645950.8 at redshift z = 2.481, which is magnified by a factor of 28 ± 8, we analyze the morphology of star formation, as traced by rest-frame ultraviolet emission, in both the highly magnified source plane and simulations of how this galaxy would appear without lensing magnification. Were this galaxy not lensed, but rather drawn from a Hubble Space Telescope deep field, we would conclude that almost all its star formation arises from an exponential disk (Sérsic index of 1.0 ± 0.4) with an effective radius of measured from two-dimensional fitting to F606W using Galfit, and measured by fitting a radial profile to F606W elliptical isophotes. At the normal spatial resolution of the deep fields, there is no sign of clumpy star formation within SGAS J111020.0+645950.8. However, the enhanced spatial resolution enabled by gravitational lensing tells a very different story; much of the star formation arises in two dozen clumps with sizes of r = 30–50 pc spread across the 7 kpc length of the galaxy. The color and spatial distribution of the diffuse component suggests that still-smaller clumps are unresolved. Despite this clumpy, messy morphology, the radial profile is still well-characterized by an exponential profile. In this lensed galaxy, stars are forming in complexes with sizes well below 100 pc; such sizes are wholly unexplored by surveys of galaxy evolution at . [ABSTRACT FROM AUTHOR]

Objective: People commonly cope with chronic low back pain (cLBP) by ignoring and distraction. Can mindful interoceptive exposure to the pain sensation itself and its phenomenological components be an alternative approach?, Methods: Single-arm feasibility study in patients with cLBP using a 2-minute attention exercise guided by a smartphone app several times per day over 8 weeks. We assessed feasibility, pre/post pain, function, and psychological parameters using mixed methods: standard questionnaires, ecological momentary assessment, and exit interviews that included micro-phenomenology technique and subsequent reflexive thematic qualitative analysis., Results: We enrolled 31 participants, mostly female, mean age 48, the majority had pain for >5 years; 29 completed. Mean pain intensity [0-10] improved from 4.8 ±1.7 to 3.1 ±1.9 (p < .0001); mean PEG scores (intensity and interference with daily life; range 0-30) improved from 13.7 ±6.2 to 8.4 ±6.6 (p < .0001); pain impact (9 items incl physical function) 22.3 ±8.7 to 19.7 ±8.1 (p = .0010). Twenty-one of 29 improved PEG score ≥30%. There were significant improvements in PCS Rumination and MAIA Not-Worrying. Participants became aware of their usual habit of avoidance and the challenge of and resistance to focusing on pain. They were surprised how pain sensations varied over time, and that pain intensity and the threat value of pain could diminish by focusing on it. They described a variety of 3D pain shapes (e.g., football, pool ball, rod, nail, brick, stars) with a range of colors, transparency, temperature, and density that for some changed with mindful attention. Most struggled to find appropriate words for sensory awareness and attention regulation and found that the threat value of their pain diminished., Conclusions: Mindful interoceptive exposure to the sensations of their cLBP using a 2-minute attention exercise with a phone app-rather than ignoring and distracting from it-may be a beneficial intervention for cLBP., Trial Registration: ClinicalTrials.gov #NCT06186193., Competing Interests: Research reported in this publication was supported by the National Institute Of Arthritis And Musculoskeletal And Skin Diseases of the National Institutes of Health under Award Number U19AR076737. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Back Pain Consortium (BACPAC) Research Program is administered by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

This study investigated gender- and personality-specific differences in academic qualifications, research motivation, and options to increase the attractiveness of leadership positions in radiology.A validated questionnaire with 66 questions was distributed via the German Roentgen Society and individually sent to 4,500 radiologists in Germany. Participants were asked about their gender. Personality dimensions were assessed using the OCEAN (Big Five) model. Multivariable regression analyses were employed.Of 510 included participants (women 237 (46.5%)), men were four times more likely to have acquired an associated professorship (AP, Habilitation Privatdozent) ((odds ratio (OR) 4.39 (2.22-8.67)). Also, they planned to achieve an AP more frequently (OR 2.87 (1.47-5.61)). The only gender-specific motivator for an AP was the option to become eligible for the position of chief physician (men OR 2.56 (1.07-6.15)). Mentors increased the probability of acquiring an AP (OR 2.07 (1.13-3.80)) or striving for an AP (4.82 (2.39-9.73)). Female mentees were likelier to have female mentors (OR 4.62 (1.68-12.73)). To increase the attractiveness of leadership positions, female radiologists perceived gender balance at the management level (OR 3.32 (2.28-4.82)), top sharing (OR 2.22 (1.48-3.32)), and better work-life balance (OR 2.02 (1.19-3.43)) as more relevant than male radiologists. More pronounced openness (OR 1.62 (1.10-2.38)) and extroversion (OR 1.45 (1.07-1.97)) were positively associated with planning an AP. More pronounced agreeableness (OR 0.67 (0.50-0.91)) was negatively associated.Research motivation is mainly independent of gender. Academic qualification varies with gender and personality dimensions. Mentoring, female role models, top sharing, and better work-family compatibility could motivate women to pursue academic leadership. · Male radiologists are more frequently motivated to pursue an associated professorship by the option of becoming a chief physician.. · Openness and extroversion make pursuing an associated professorship more likely.. · Role models at the management level, top sharing, and flexible work time are more important for female radiologists.. · Molwitz I, Kemper C, Stahlmann K et al. Gender- and personality-specific differences in academic qualifications, research motivation, and attractiveness of leadership positions: a survey among radiologists from Germany. Fortschr Röntgenstr 2024; DOI 10.1055/a-2415-7337., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability of large WSI datasets have revolutionised WSI analysis. Therefore, the current state-of-the-art in WSI registration is unclear. To address this, we conducted the ACROBAT challenge, based on the largest WSI registration dataset to date, including 4,212 WSIs from 1,152 breast cancer patients. The challenge objective was to align WSIs of tissue that was stained with routine diagnostic immunohistochemistry to its H&E-stained counterpart. We compare the performance of eight WSI registration algorithms, including an investigation of the impact of different WSI properties and clinical covariates. We find that conceptually distinct WSI registration methods can lead to highly accurate registration performances and identify covariates that impact performances across methods. These results provide a comparison of the performance of current WSI registration methods and guide researchers in selecting and developing methods., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Philippe Weitz reports a relationship with Stratipath AB that includes: employment. Mattias Rantalainen reports a relationship with Stratipath AB that includes: equity or stocks. Johan Hartman reports a relationship with Stratipath AB that includes: equity or stocks. Kimmo Kartasalo reports a relationship with Clinsight AB that includes: equity or stocks. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Objectives: To distinguish histological subtypes of renal tumors using radiomic features and machine learning (ML) based on multiphase computed tomography (CT)., Material and Methods: Patients who underwent surgical treatment for renal tumors at two tertiary centers from 2012 to 2022 were included retrospectively. Preoperative arterial (corticomedullary) and venous (nephrogenic) phase CT scans from these centers, as well as from external imaging facilities, were manually segmented, and standardized radiomic features were extracted. Following preprocessing and addressing the class imbalance, a ML algorithm based on extreme gradient boosting trees (XGB) was employed to predict renal tumor subtypes using 10-fold cross-validation. The evaluation was conducted using the multiclass area under the receiver operating characteristic curve (AUC). Algorithms were trained on data from one center and independently tested on data from the other center., Results: The training cohort comprised n = 297 patients (64.3% clear cell renal cell cancer [RCC], 13.5% papillary renal cell carcinoma (pRCC), 7.4% chromophobe RCC, 9.4% oncocytomas, and 5.4% angiomyolipomas (AML)), and the testing cohort n = 121 patients (56.2%/16.5%/3.3%/21.5%/2.5%). The XGB algorithm demonstrated a diagnostic performance of AUC = 0.81/0.64/0.8 for venous/arterial/combined contrast phase CT in the training cohort, and AUC = 0.75/0.67/0.75 in the independent testing cohort. In pairwise comparisons, the lowest diagnostic accuracy was evident for the identification of oncocytomas (AUC = 0.57-0.69), and the highest for the identification of AMLs (AUC = 0.9-0.94) CONCLUSION: Radiomic feature analyses can distinguish renal tumor subtypes on routinely acquired CTs, with oncocytomas being the hardest subtype to identify., Clinical Relevance Statement: Radiomic feature analyses yield robust results for renal tumor assessment on routine CTs. Although radiologists routinely rely on arterial phase CT for renal tumor assessment and operative planning, radiomic features derived from arterial phase did not improve the accuracy of renal tumor subtype identification in our cohort., (© 2024. The Author(s).)

Introduction: Chronic low back pain (cLBP) poses significant challenges, often addressed through avoidance or distraction. Emerging evidence suggests that mind-body interventions, like our novel Mind Your Pain (MyP) smartphone mobile application, may offer relief. We conducted a single-arm, mixed-methods neuroimaging study to assess the degree to which treatment response to our 8-week intervention, as measured by the reduction in the Pain, Enjoyment of Life and General Activity Scale (PEG), was associated with enhanced pain-related insula activation over time., Methods: Twenty-nine individuals with cLBP completed patient-reported assessments, qualitative sensory testing (QST) measures, and neuroimaging pre- and post-MyP. Functional MRI data during experimental heat pain on the left forearm were collected and analyzed, comparing responders (≥50% reduction in PEG scores) and non-responders., Results: MyP led to significant decreases in PEG scores overall. Furthermore, MyP responders exhibited increased pain-related activation in key brain regions, including the contralateral posterior insula, bilateral ventral anterior insula, ventral anterior cingulate, dorsolateral prefrontal cortex, and nucleus accumbens. Although baseline behavioral and sensory measures did not differ between the two responder groups, baseline neural differences related to the impact of the endogenous back pain were observed., Discussion: MyP appears to modify pain response and underlying neural circuitry, suggesting neural changes in interoception may serve as biomarkers for mind-body interventions in cLBP. This study highlights the potential of MyP as a novel approach for cLBP management, warranting further investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (© 2024 Strigo, Guerra, Torrisi, Murphy, Toor, Goldman, Alter, Vu, Hecht, Lotz, Simmons and Mehling.)

Background Context: There are a number of risk factors- from biological, psychological, and social domains- for non-specific chronic low back pain (cLBP). Many cLBP treatments target risk factors on the assumption that the targeted factor is not just associated with cLBP but is also a cause (i.e, a causal risk factor). In most cases this is a strong assumption, primarily due to the possibility of confounding variables. False assumptions about the causal relationships between risk factors and cLBP likely contribute to the generally marginal results from cLBP treatments., Purpose: The objectives of this study were to a) using rigorous confounding control compare associations between modifiable causal risk factors identified by Mendelian randomization (MR) studies with associations in a cLBP population and b) estimate the association of these risk factors with cLBP outcomes., Study Design/setting: Cross sectional analysis of a longitudinal, online, observational study., Patient Sample: 1,376 participants in BACKHOME, a longitudinal observational e-Cohort of U.S. adults with cLBP that is part of the NIH Back Pain Consortium (BACPAC) Research Program., Outcome Measures: Pain, Enjoyment of Life, and General Activity (PEG) Scale., Methods: Five risk factors were selected based on evidence from MR randomization studies: sleep disturbance, depression, BMI, alcohol use, and smoking status. Confounders were identified using the ESC-DAG approach, a rigorous method for building directed acyclic graphs based on causal criteria. Strong evidence for confounding was found for age, female sex, education, relationship status, financial strain, anxiety, fear avoidance and catastrophizing. These variables were used to determine the adjustment sets for the primary analysis. Potential confounders with weaker evidence were used for a sensitivity analysis., Results: Participants had the following characteristics: age 54.9 ± 14.4 years, 67.4% female, 60% never smokers, 29.9% overweight, 39.5% obese, PROMIS sleep disturbance T-score 54.8 ± 8.0, PROMIS depression T-score 52.6 ± 10.1, Fear-avoidance Beliefs Questionnaire 11.6 ± 5.9, Patient Catastrophizing Scale 4.5 ± 2.6, PEG 4.4 ± 2.2. In the adjusted models alcohol use, sleep disturbance, depression, and obesity were associated with PEG, after adjusting for confounding variables identified via a DAG constructed using a rigorous protocol. The adjusted effect estimates- the expected change in the PEG outcome for every standard deviation increase or decrease in the exposure (or category shift for categorical exposures) were the largest for sleep disturbance and obesity. Each SD increase in the PROMIS sleep disturbance T-score resulted in a mean 0.77 (95% CI: 0.66, 0.88) point increase in baseline PEG score. Compared to participants with normal BMI, adjusted mean PEG score was slightly higher by 0.37 points (95% CI: 0.09, 0.65) for overweight participants, about 0.8 to 0.9 points higher for those in obesity classes I and II, and 1.39 (95% CI: 0.98, 1.80) points higher for the most obese participants. Each SD increase in the PROMIS depression T-score was associated with a mean 0.28 (95% CI: 0.17, 0.40) point increase in baseline PEG score, while each SD decrease in number of alcoholic drinks per week resulted in a mean 0.12 (95%CI: 0.01, 0.23) increase in baseline PEG score in the adjusted model., Conclusions: Several modifiable causal risk factors for cLBP - alcohol use, sleep disturbance, depression, and obesity- are associated with PEG, after adjusting for confounding variables identified via a DAG constructed using a rigorous protocol. Convergence of our findings for sleep disturbance, depression, and obesity with the results from MR studies, which have different designs and biases, strengthens the evidence for causal relationships between these risk factors and cLBP (1). The estimated effect of change in a risk factors on change in PEG were the largest for sleep disturbance and obesity. Future analyses will evaluate these relationships with longitudinal data.

Objectives: To develop an automatic segmentation model for solid renal tumors on contrast-enhanced CTs and to visualize segmentation with associated confidence to promote clinical applicability., Materials and Methods: The training dataset included solid renal tumor patients from two tertiary centers undergoing surgical resection and receiving CT in the corticomedullary or nephrogenic contrast media (CM) phase. Manual tumor segmentation was performed on all axial CT slices serving as reference standard for automatic segmentations. Independent testing was performed on the publicly available KiTS 2019 dataset. Ensembles of neural networks (ENN, DeepLabV3) were used for automatic renal tumor segmentation, and their performance was quantified with DICE score. ENN average foreground entropy measured segmentation confidence (binary: successful segmentation with DICE score > 0.8 versus inadequate segmentation ≤ 0.8)., Results: N = 639/n = 210 patients were included in the training and independent test dataset. Datasets were comparable regarding age and sex (p > 0.05), while renal tumors in the training dataset were larger and more frequently benign (p < 0.01). In the internal test dataset, the ENN model yielded a median DICE score = 0.84 (IQR: 0.62-0.97, corticomedullary) and 0.86 (IQR: 0.77-0.96, nephrogenic CM phase), and the segmentation confidence an AUC = 0.89 (sensitivity = 0.86; specificity = 0.77). In the independent test dataset, the ENN model achieved a median DICE score = 0.84 (IQR: 0.71-0.97, corticomedullary CM phase); and segmentation confidence an accuracy = 0.84 (sensitivity = 0.86 and specificity = 0.81). ENN segmentations were visualized with color-coded voxelwise tumor probabilities and thresholds superimposed on clinical CT images., Conclusions: ENN-based renal tumor segmentation robustly performs in external test data and might aid in renal tumor classification and treatment planning., Clinical Relevance Statement: Ensembles of neural networks (ENN) models could automatically segment renal tumors on routine CTs, enabling and standardizing downstream image analyses and treatment planning. Providing confidence measures and segmentation overlays on images can lower the threshold for clinical ENN implementation., Key Points: Ensembles of neural networks (ENN) segmentation is visualized by color-coded voxelwise tumor probabilities and thresholds. ENN provided a high segmentation accuracy in internal testing and in an independent external test dataset. ENN models provide measures of segmentation confidence which can robustly discriminate between successful and inadequate segmentations., (© 2024. The Author(s).)

Introduction: Understanding individual patient preferences for chronic low back pain (cLBP) outcomes is essential for targeting available therapeutic options; yet tools to elicit patient outcome preferences are limited., Objective: To develop and test a choice-based conjoint (CBC) measure, commonly used in behavioral economics research, to elicit what outcomes patients with cLBP want to achieve and avoid., Design: We developed a survey-based CBC measure to allow patients to make risk/benefit trade-off choices between possible treatment outcomes. After extensive literature, clinician, and patient input, our measure included seven attributes: fatigue, anxiety/depression, difficulty thinking/making decisions, pain intensity, physical abilities, change in pain, and ability to enjoy life despite pain. Random-parameters logit models were used to estimate strength of preferences, and latent class analysis was used to identify patient characteristics associated with distinct preference., Setting: Online study using the Sawtooth web-based platform., Participants: Two hundred eleven individuals with cLBP recruited from online advertising as well as at clinical sites across multiple academic and private institutions., Interventions: Not applicable., Results: The most valued outcome was the highest level of physical activity (β = 1.6-1.98; p < .001), followed by avoiding cognitive difficulties (β = -1.48; p < .001). Avoidance of severe pain was comparable to avoiding constant fatigue and near-constant depression/anxiety (β = -0.99, -1.02); p < .001). There was an association between preferences and current pain/disability status; patients with higher pain had a stronger preference to avoid severe pain, whereas those with higher disability have stronger preferences for achieving physical activity. The latent class analysis identified two distinct groups: (1) more risk-seeking and willing to accept worse outcomes (56%); and (2) more risk-averse with a stronger preference for achieving maximum benefits (44%)., Conclusions: Our study illuminated cLBP patient preferences for treatment outcomes and heterogeneity in these preferences. Patients stressed the importance of reaching high physical activity and avoiding cognitive declines, even over a desire to avoid pain. More work is needed to understand patient preferences to aid informed, shared decisions., (© 2023 The Authors. PM&R published by Wiley Periodicals LLC on behalf of American Academy of Physical Medicine and Rehabilitation.)

Introduction: Modic changes (MC) are bone marrow lesions of vertebral bones, which can be detected with magnetic resonance imaging (MRI) adjacent to degenerated intervertebral discs. Defined by their appearance on T1 and T2 weighted images, there are three interconvertible types: MC1, MC2, and MC3. The inter-observer variability of the MRI diagnosis is high, therefore a diagnostic serum biomarker complementing the MRI to facilitate diagnosis and follow-up would be of great value., Methods: We used a highly sensitive and reproducible proteomics approach: DIA/SWATH-MS to find serum biomarkers in a subset of the Northern Finland Birth Cohort 1966. Separately, we measured a panel of factors involved in inflammation and angiogenesis to confirm some potential biomarkers published before with an ELISA-based method called V-Plex., Results: We found neither an association between the serum concentrations of the proteins detected with DIA/SWATH-MS with the presence of MC, nor a correlation with the size of the MC lesions. We did not find any association between the factors measured with the V-Plex and the presence of MC or their size., Conclusion: Altogether, our study suggests that a robust and generally usable biomarker to facilitate the diagnosis of MC cannot readily be found in serum., Competing Interests: All authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 The Author(s). JOR Spine published by Wiley Periodicals LLC on behalf of Orthopaedic Research Society.)

Foundational models, pretrained on a large scale, have demonstrated substantial success across non-medical domains. However, training these models typically requires large, comprehensive datasets, which contrasts with the smaller and more specialized datasets common in biomedical imaging. Here we propose a multi-task learning strategy that decouples the number of training tasks from memory requirements. We trained a universal biomedical pretrained model (UMedPT) on a multi-task database including tomographic, microscopic and X-ray images, with various labeling strategies such as classification, segmentation and object detection. The UMedPT foundational model outperformed ImageNet pretraining and previous state-of-the-art models. For classification tasks related to the pretraining database, it maintained its performance with only 1% of the original training data and without fine-tuning. For out-of-domain tasks it required only 50% of the original training data. In an external independent validation, imaging features extracted using UMedPT proved to set a new standard for cross-center transferability., (© 2024. The Author(s).)

Introduction: The scapholunate interosseous ligament is pivotal for wrist stability, and its impairment can result in instability and joint degeneration. This study explores the application of real-time MRI for dynamic assessment of the scapholunate joint during wrist motion with the objective of determining its diagnostic value in efficacy in contrast to static imaging modalities., Materials and Methods: Ten healthy participants underwent real-time MRI scans during wrist ab/adduction and fist-clenching maneuvers. Measurements were obtained at proximal, medial, and distal landmarks on both dynamic and static images with statistical analyses conducted to evaluate the reliability of measurements at each landmark and the concordance between dynamic measurements and established static images. Additionally, inter- and intraobserver variabilities were evaluated., Results: Measurements of the medial landmarks demonstrated the closest agreement with static images and exhibited the least scatter. Distal landmark measurements showed a similar level of agreement but with increased scatter. Proximal landmark measurements displayed substantial deviation, which was accompanied by an even greater degree of scatter. Although no significant differences were observed between the ab/adduction and fist-clenching maneuvers, both inter- and intraobserver variabilities were significant across all measurements., Conclusions: This study highlights the potential of real-time MRI in the dynamic assessment of the scapholunate joint particularly at the medial landmark. Despite promising results, challenges such as measurement variability need to be addressed. Standardization and integration with advanced image processing methods could significantly enhance the accuracy and reliability of real-time MRI, paving the way for its clinical implementation in dynamic wrist imaging studies.

To assess epidemiology, clinical presentation, treatment and overall survival of adult patients with renal sarcomas, the 2004-2016 SEER and NCDB databases were queried for adult patients diagnosed with renal sarcoma, calculating average annual age-adjusted incidence rates (AAIR) and average annual percentage change (AAPC) as well as overall survival (OS). In n = 1279 included renal sarcoma patients, AAIR remained constant over the study period (average 0.53 cases/1million; AAPC = 0.7, p = 0.6). Leiomyosarcoma (AAIR 0.14 cases/1 million) and malignant rhabdoid tumors (0.06 cases/1 million) were most common. Sarcoma histiotypes demonstrated considerable heterogeneity regarding demographic and cancer-related variables. Patients presented with advanced local extent (T3 33.3%; T4 14.2%) or distant metastases (29.1%) and commonly underwent surgical resection (81.6%). Longer OS was independently associated with younger age, female sex, lower comorbidity index, low T stage, negative surgical margins, absence of tumor necrosis or distant metastases and leiomyosarcoma histiotype (multivariable p < 0.05 each). Treatment efficacy varied according to sarcoma histiotype (interaction p < 0.001). Accounting for 0.25% of renal malignancies, renal sarcomas include 43 histiotypes with distinct epidemiology, clinical presentation, outcomes and sensitivity to systemic therapy, thereby reflecting soft-tissue sarcoma behavior. Renal sarcoma treatment patterns follow recommendations by renal cancer guidelines with surgical resection as the cornerstone of therapy., (© 2024. The Author(s).)

In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed for volumetric analysis (via segmentation) of the left ventricle in real-time free-breathing CMR at rest and under exercise stress. Data from healthy volunteers (n = 15) for cine and real-time free-breathing CMR at rest and under exercise stress were analyzed retrospectively. Exercise stress was performed using an ergometer in the supine position. Segmentations of two deep learning methods, a commercially available technique (comDL) and an openly available network (nnU-Net), were compared to a reference model created via the manual correction of segmentations obtained with comDL. Segmentations of left ventricular endocardium (LV), left ventricular myocardium (MYO), and right ventricle (RV) are compared for both end-systolic and end-diastolic phases and analyzed with Dice's coefficient. The volumetric analysis includes the cardiac function parameters LV end-diastolic volume (EDV), LV end-systolic volume (ESV), and LV ejection fraction (EF), evaluated with respect to both absolute and relative differences. For cine CMR, nnU-Net and comDL achieve Dice's coefficients above 0.95 for LV and 0.9 for MYO, and RV. For real-time CMR, the accuracy of nnU-Net exceeds that of comDL overall. For real-time CMR at rest, nnU-Net achieves Dice's coefficients of 0.94 for LV, 0.89 for MYO, and 0.90 for RV and the mean absolute differences between nnU-Net and the reference are 2.9 mL for EDV, 3.5 mL for ESV, and 2.6% for EF. For real-time CMR under exercise stress, nnU-Net achieves Dice's coefficients of 0.92 for LV, 0.85 for MYO, and 0.83 for RV and the mean absolute differences between nnU-Net and reference are 11.4 mL for EDV, 2.9 mL for ESV, and 3.6% for EF. Deep learning methods designed or trained for cine CMR segmentation can perform well on real-time CMR. For real-time free-breathing CMR at rest, the performance of deep learning methods is comparable to inter-observer variability in cine CMR and is usable for fully automatic segmentation. For real-time CMR under exercise stress, the performance of nnU-Net could promise a higher degree of automation in the future., (© 2024. The Author(s).)

Background: Despite the fervent scientific effort, a state-of-the art assessment of the different causes of hypoxemia (shunt, ventilation-perfusion mismatch, and diffusion limitation) in COVID-19 acute respiratory distress syndrome (ARDS) is currently lacking. In this study, the authors hypothesized a multifactorial genesis of hypoxemia and aimed to measure the relative contribution of each of the different mechanism and their relationship with the distribution of tissue and blood within the lung., Methods: In this cross-sectional study, the authors prospectively enrolled 10 patients with COVID-19 ARDS who had been intubated for less than 7 days. The multiple inert gas elimination technique (MIGET) and a dual-energy computed tomography (DECT) were performed and quantitatively analyzed for both tissue and blood volume. Variables related to the respiratory mechanics and invasive hemodynamics (PiCCO [Getinge, Sweden]) were also recorded., Results: The sample (51 ± 15 yr; Pao2/Fio2, 172 ± 86 mmHg) had a mortality of 50%. The MIGET showed a shunt of 25 ± 16% and a dead space of 53 ± 11%. Ventilation and perfusion were mismatched (LogSD, Q, 0.86 ± 0.33). Unexpectedly, evidence of diffusion limitation or postpulmonary shunting was also found. In the well aerated regions, the blood volume was in excess compared to the tissue, while the opposite happened in the atelectasis. Shunt was proportional to the blood volume of the atelectasis (R2 = 0.70, P = 0.003). V˙A/Q˙T mismatch was correlated with the blood volume of the poorly aerated tissue (R2 = 0.54, P = 0.016). The overperfusion coefficient was related to Pao2/Fio2 (R2 = 0.66, P = 0.002), excess tissue mass (R2 = 0.84, P < 0.001), and Etco2/Paco2 (R2 = 0.63, P = 0.004)., Conclusions: These data support the hypothesis of a highly multifactorial genesis of hypoxemia. Moreover, recent evidence from post-mortem studies (i.e., opening of intrapulmonary bronchopulmonary anastomosis) may explain the findings regarding the postpulmonary shunting. The hyperperfusion might be related to the disease severity., (Copyright © 2023 American Society of Anesthesiologists. All Rights Reserved.)

Background: Tools, such as the STarTBack Screening Tool (SBT), have been developed to identify risks of progressing to chronic disability in low back pain (LBP) patients in the primary care population. However, less is known about predictors of change in function after treatment in the specialty care population., Objective: We pursued a retrospective observational cohort study involving LBP patients seen in a multidisciplinary specialty clinic to assess which features can predict change in function at follow-up., Methods: The SBT was administered at initial visit, and a variety of patient characteristics were available in the chart including the presence of chronic overlapping pain conditions (COPCs). Patient Reported Outcomes Measurement Information System-10 (PROMIS-10) global physical health (PH) and global mental health (MH) were measured at baseline and at pragmatic time points during follow-up. Linear regression was used to estimate adjusted associations between available features and changes in PROMIS scores., Results: 241 patients were followed for a mean of 17.0 ± 7.5 months. Mean baseline pain was 6.7 (SD 2.1), PROMIS-10 global MH score was 44.8 (SD 9.3), and PH score was 39.4 (SD 8.6). 29.7% were low-risk on the SBT, 41.8% were medium-risk, and 28.5% were high-risk. Mean change in MH and PH scores from baseline to the follow-up questionnaire were 0.86 (SD 8.11) and 2.39 (SD 7.52), respectively. Compared to low-risk patients, high-risk patients had a mean 4.35 points greater improvement in their MH score (p= 0.004) and a mean 3.54 points greater improvement in PH score (p= 0.006). Fewer COPCs also predicted greater improvement in MH and PH., Conclusions: SBT and the presence of COPC, which can be assessed at initial presentation to a specialty clinic, can predict change in PROMIS following treatment. Effort is needed to identify other factors that can help predict change in function after treatment in the specialty care setting.

Introduction: Overweight and obesity lead to numerous complications and their treatment. The associated costs represent a health and sociopolitical burden. Therefore, the development of overweight and obesity is of great importance for health policy., Methods: The Gutenberg Health Study (GHS), a population-based observational study of individuals aged 35-74 years in the city of Mainz and the district of Mainz-Bingen, examined current data on the prevalence and development of overweight and obesity and their association with concomitant diseases and medication use., Results: Among men, 48.1% were overweight and 26.3% had obesity. Among women, these proportions were 32.1% and 24.1%, respectively. Elevated body mass index (BMI) was associated with numerous complications, particularly insulin resistance and type 2 diabetes, arterial hypertension, elevated triglycerides and low HDL cholesterol, and cardiovascular disease. Accordingly, medications to treat these conditions were used significantly more often in individuals with elevated BMI. During the 10-year observation period, mean weight increased in the population. Both men and women had a moderate but significant increase in BMI compared to men and women of the same age at baseline. Individual weight changes over the 10-year observation period, on the other hand, were age-dependent. In the two younger age decades, weight gain was observed, while in the oldest age decade, mean body weight decreased., Conclusion: These current data confirm that overweight and obesity are associated with relevant complications and that these complications lead to significant use of appropriate medications. The study also suggests that there is a significant trend toward increased prevalence of obesity (BMI ≥30) over the 10-year period., (© 2023 The Author(s). Published by S. Karger AG, Basel.)

Background: Diagnostic accuracy of endomyocardial biopsy could improve if clinically safe magnetic resonance (MR)-compatible bioptomes were available. We explored two novel MR-compatible cardiac bioptomes for performance, safety, and clinical viability, employing in vivo minipig trials and phase-contrast synchrotron radiation computed microtomography (SRµCT)., Methods: Analysis of ex vivo obtained pig endomyocardial biopsies was performed using phase-contrast SRµCT and conventional two-dimensional histology. The technical performance was evaluated by measuring volume, inner and outer integrities, compression, and histological diagnostic value in 3 sets (6 per set) of biopsies for each experimental bioptome. The bioptomes were tested in vivo in 3 healthy minipigs per bioptome. The clinical feasibility was evaluated by procedural and cutting success as well as histological diagnostic value., Results: The bioptome with the 'grind-grind' design achieved similar values to control in compression (p = 0.822), inner (p = 0.628), and outer (p = 0.507), integrities ex vivo. It showed a better performance in the in vivo real-time MRI setting demonstrating a higher cutting success (91.7%) than the 'grind-anvil' (86.2%) design. In both ex vivo and in vivo evaluations, the 'grind-grind' design displayed sufficient diagnostic value (83% and 95%). The 'grind-anvil' design showed adequate diagnostic value both ex vivo and in vivo (78% and 87.5%) but was not comparable to control according to the three-dimensional (3D) analysis., Conclusion: A novel MR-compatible bioptome was identified as plausible in a clinical setting. Additionally, SRµCT and subsequent 3D structural analysis could be valuable in the label-free investigation of myocardial tissue at a micrometer level., Relevance Statement: Implementation of MR-guided biopsy can improve animal studies on structural myocardial changes at any point in an experimental setup. With further improvements in guiding catheters, MR-guided biopsy, using the new bioptome, has a potential to increase quality and diagnostic accuracy in patients both with structural and inflammatory cardiomyopathies., Key Points: • Novel MR-compatible bioptomes show promise for a clinical application. • SRµCT enabled detailed analysis of endomyocardial biopsies. • The bioptomes showed adequate in vivo performance without major complications., (© 2023. The Author(s).)

Significance: Although the registration of restained sections allows nucleus-level alignment that enables a direct analysis of interacting biomarkers, consecutive sections only allow the transfer of region-level annotations. The latter can be achieved at low computational cost using coarser image resolutions., Purpose: In digital histopathology, virtual multistaining is important for diagnosis and biomarker research. Additionally, it provides accurate ground truth for various deep-learning tasks. Virtual multistaining can be obtained using different stains for consecutive sections or by restaining the same section. Both approaches require image registration to compensate for tissue deformations, but little attention has been devoted to comparing their accuracy., Approach: We compared affine and deformable variational image registration of consecutive and restained sections and analyzed the effect of the image resolution that influences accuracy and required computational resources. The registration was applied to the automatic nonrigid histological image registration (ANHIR) challenge data (230 consecutive slide pairs) and the hyperparameters were determined. Then without changing the parameters, the registration was applied to a newly published hybrid dataset of restained and consecutive sections (HyReCo, 86 slide pairs, 5404 landmarks)., Results: We obtain a median landmark error after registration of 6.5    μ m (HyReCo) and 24.1    μ m (ANHIR) between consecutive sections. Between restained sections, the median registration error is 2.2 and 0.9    μ m in the two subsets of the HyReCo dataset. We observe that deformable registration leads to lower landmark errors than affine registration in both cases ( p < 0.001 ), though the effect is smaller in restained sections., Conclusion: Deformable registration of consecutive and restained sections is a valuable tool for the joint analysis of different stains., (© 2023 The Authors.)

In 2019, the National Health Interview survey found that nearly 59% of adults reported pain some, most, or every day in the past 3 months, with 39% reporting back pain, making back pain the most prevalent source of pain, and a significant issue among adults. Often, identifying a direct, treatable cause for back pain is challenging, especially as it is often attributed to complex, multifaceted issues involving biological, psychological, and social components. Due to the difficulty in treating the true cause of chronic low back pain (cLBP), an over-reliance on opioid pain medications among cLBP patients has developed, which is associated with increased prevalence of opioid use disorder and increased risk of death. To combat the rise of opioid-related deaths, the National Institutes of Health (NIH) initiated the Helping to End Addiction Long-TermSM (HEAL) initiative, whose goal is to address the causes and treatment of opioid use disorder while also seeking to better understand, diagnose, and treat chronic pain. The NIH Back Pain Consortium (BACPAC) Research Program, a network of 14 funded entities, was launched as a part of the HEAL initiative to help address limitations surrounding the diagnosis and treatment of cLBP. This paper provides an overview of the BACPAC research program's goals and overall structure, and describes the harmonization efforts across the consortium, define its research agenda, and develop a collaborative project which utilizes the strengths of the network. The purpose of this paper is to serve as a blueprint for other consortia tasked with the advancement of pain related science., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Academy of Pain Medicine.)

Background: Chronic low back pain (cLBP) is a complex with a heterogenous clinical presentation. A better understanding of the factors that contribute to cLBP is needed for accurate diagnosis, optimal treatment, and identification of mechanistic targets for new therapies. The Back Pain Consortium (BACPAC) Research Program provides a unique opportunity in this regard, as it will generate large clinical datasets, including a diverse set of harmonized measurements. The Theoretical Model Working Group was established to guide BACPAC research and to organize new knowledge within a mechanistic framework. This article summarizes the initial work of the Theoretical Model Working Group. It includes a three-stage integration of expert opinion and an umbrella literature review of factors that affect cLBP severity and chronicity., Methods: During Stage 1, experts from across BACPAC established a taxonomy for risk and prognostic factors (RPFs) and preliminary graphical depictions. During Stage 2, a separate team conducted a literature review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to establish working definitions, associated data elements, and overall strength of evidence for identified RPFs. These were subsequently integrated with expert opinion during Stage 3., Results: The majority (∼80%) of RPFs had little strength-of-evidence confidence, whereas seven factors had substantial confidence for either a positive association with cLBP (pain-related anxiety, serum C-reactive protein, diabetes, and anticipatory/compensatory postural adjustments) or no association with cLBP (serum interleukin 1-beta / interleukin 6, transversus muscle morphology/activity, and quantitative sensory testing)., Conclusion: This theoretical perspective will evolve over time as BACPAC investigators link empirical results to theory, challenge current ideas of the biopsychosocial model, and use a systems approach to develop tools and algorithms that disentangle the dynamic interactions among cLBP factors., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Academy of Pain Medicine.)

Osteoarthritis (OA) is a common degenerative joint disease that affects millions of people worldwide. Magnetic resonance imaging (MRI) has emerged as a powerful tool for the evaluation and monitoring of OA due to its ability to visualize soft tissues and bone with high resolution. This review aims to provide an overview of the current state of MRI in OA, with a special focus on the knee, including protocol recommendations for clinical and research settings. Furthermore, new developments in the field of musculoskeletal MRI are highlighted in this review. These include compositional MRI techniques, such as T2 mapping and T1rho imaging, which can provide additional important information about the biochemical composition of cartilage and other joint tissues. In addition, this review discusses semiquantitative joint assessment based on MRI findings, which is a widely used method for evaluating OA severity and progression in the knee. We analyze the most common scoring methods and discuss potential benefits. Techniques to reduce acquisition times and the potential impact of deep learning in MR imaging for OA are also discussed, as these technological advances may impact clinical routine in the future.

Objective: We developed and used a discrete-choice measure to study patient preferences with regard to the risks and benefits of nonsurgical treatments when they are making treatment selections for chronic low back pain., Methods: "CAPER TREATMENT" (Leslie Wilson) was developed with standard choice-based conjoint procedures (discrete-choice methodology that mimics an individual's decision-making process). After expert input and pilot testing, our final measure had 7 attributes (chance of pain relief, duration of relief, physical activity changes, treatment method, treatment type, treatment time burden, and risks of treatment) with 3-4 levels each. Using Sawtooth software (Sawtooth Software, Inc., Provo, UT, USA), we created a random, full-profile, balanced-overlap experimental design. Respondents (n = 211) were recruited via an emailed online link and completed 14 choice-based conjoint choice pairs; 2 fixed questions; and demographic, clinical, and quality-of-life questions. Analysis was performed with random-parameters multinomial logit with 1000 Halton draws., Results: Patients cared most about the chance of pain relief, followed closely by improving physical activity, even more than duration of pain relief. There was comparatively less concern about time commitment and risks. Gender and socioeconomic status influenced preferences, especially with relation to strength of expectations for outcomes. Patients experiencing a low level of pain (Pain, Enjoyment, and General Activity Scale [PEG], question 1, numeric rating scale score<4) had a stronger desire for maximally improved physical activity, whereas those in a high level of pain (PEG, question 1, numeric rating scale score>6) preferred both maximum and more limited activity. Highly disabled patients (Oswestry Disability Index score>40) demonstrated distinctly different preferences, placing more weight on achieving pain control and less on improving physical activity., Conclusions: Individuals with chronic low back pain were willing to trade risks and inconveniences for better pain control and physical activity. Additionally, different preference phenotypes exist, which suggests a need for clinicians to target treatments to particular patients., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: To evaluate work expectations of radiologists at different career levels, their fulfillment, prevalence of exhaustion, and exhaustion-associated factors., Methods: A standardized digital questionnaire was distributed internationally to radiologists of all career levels in the hospital and in ambulatory care via radiological societies and sent manually to 4500 radiologists of the largest German hospitals between December 2020 and April 2021. Statistics were based on age- and gender-adjusted regression analyses of respondents working in Germany (510 out of 594 total respondents)., Results: The most frequent expectations were "joy at work" (97%) and a "good working atmosphere" (97%), which were considered fulfilled by at least 78%. The expectation of a "structured residency within the regular time interval" (79%) was more frequently judged fulfilled by senior physicians (83%, odds ratio (OR) 4.31 [95% confidence interval (95% CI) 1.95-9.52]), chief physicians (85%, 6.81 [95% CI 1.91-24.29]), and radiologists outside the hospital (88%, 7.59 [95% CI 2.40-24.03]) than by residents (68%). Exhaustion was most common among residents (physical exhaustion: 38%; emotional exhaustion: 36%), in-hospital specialists (29%; 38%), and senior physicians (30%; 29%). In contrast to paid extra hours, unpaid extra hours were associated with physical exhaustion (5-10 extra hours: OR 2.54 [95% CI 1.54-4.19]). Fewer opportunities to shape the work environment were related to a higher probability of physical (2.03 [95% CI 1.32-3.13]) and emotional (2.15 [95% CI 1.39-3.33]) exhaustion., Conclusions: While most radiologists enjoy their work, residents wish for more training structure. Ensuring payment of extra hours and employee empowerment may help preventing burnout in high-risk groups., Key Points: • Most important work expectations of radiologists who work in Germany are "joy at work," a "good working atmosphere," "support for further qualification," and a "structured residency within the regular time interval," with the latter containing potential for improvement according to residents. • Physical and emotional exhaustion are common at all career levels except for chief physicians and for radiologists who work outside the hospital in ambulatory care. • Exhaustion as a major burnout criterion is associated with unpaid extra hours and reduced opportunities to shape the work environment., (© 2023. The Author(s).)

The purpose of this study was to evaluate the impact of breast density on the diagnostic performance of cone-beam breast-CT (CBBCT) in comparison to full-field digital mammography (FFDM) for the detection of microcalcifications. This retrospective IRB-approved study was conducted between December 2015 and March 2017 and enrolled 171 women with Breast Imaging Reporting and Data System category 4 or 5 lesions on FFDM and additional CBBCT; 56 of which were ineligible. The inclusion was restricted to 83 women (90 breasts, 90 lesions) with microcalcifications. All lesions underwent histology or were monitored by FFDM and a clinical examination at least 2 years after enrollment. Two breast radiologists independently read each data set twice. Sensitivity, specificity and area under the curve were compared between the modalities. Thirty-two breasts (35.5%) were grouped as non-dense breasts (American College of Radiology types a/b) and 58 breasts (64.5%) as dense breasts (American College of Radiology types c/d). Histopathological assessment was performed in 61 of 90 breast lesions (32 malignant, 1 high-risk and 28 benign). Area under the curve was larger for FFDM than for CBBCT (P = .085). The sensitivity was significantly higher for FFDM compared to CBBCT (P = .009). The specificity showed no significant differences comparing FFDM (both readers: 0.62) versus CBBCT (reader 1: 0.76, reader 2: 0.60; P = .192). Inter-observer-reliability on BI-RADS readings was almost perfect for FFDM and moderate for CBBCT (κ = 0.84, κ = 0.54, respectively). Intra-observer agreement was substantial to almost perfect for both methods and readers. Compared with FFDM, CBBCT demonstrated non-comparable results for microcalcification detection in dense and non-dense breasts., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.)

Purpose: The aim of this study was to assess the clinical feasibility of magnetic resonance imaging (MRI) T1 mapping using T1FLASH for assessment of prostate lesions., Methods: Participants with clinical suspicion for prostate cancer (PCa) were prospectively enrolled between October 2021 and April 2022 with multiparametric prostate MRI (mpMRI) acquired on a 3 T scanner. In addition, T1 mapping was accomplished using a single-shot T1FLASH technique with inversion recovery, radial undersampling, and iterative reconstruction. Regions of interest (ROIs) were manually placed on radiologically identified prostate lesions and representative reference regions of the transitional zone (TZ), benign prostate hyperplasia nodules, and peripheral zone (PZ). Mean T1 relaxation times and apparent diffusion coefficient (ADC) values (b = 50/b = 1400 s/mm 2 ) were measured for each ROI. Participants were included in the study if they underwent ultrasound/MRI fusion-guided prostate biopsy for radiologically or clinically suspected PCa. Histological evaluation of biopsy cores served as reference standard, with grading of PCa according to the International Society of Urological Pathology (ISUP). ISUP grades 2 and above were considered clinically significant PCa for the scope of this study. Histological results of prostate biopsy cores were anatomically mapped to corresponding mpMRI ROIs using biopsy plans. T1 relaxation times and ADC values were compared across prostate regions and ISUP groups. Across different strata, T1 relaxation time, ADC values, and diagnostic accuracy (area under the curve [AUC]) were compared using statistical methods accounting for clustered data., Results: Of 67 eligible participants, a total of 40 participants undergoing ultrasound/MRI fusion-guided prostate biopsy were included. Multislice T1 mapping was successfully performed in all participants at a median acquisition time of 2:10 minutes without evident image artifacts. A total of 71 prostate lesions was radiologically identified (TZ 49; PZ 22). Among those, 22 were histologically diagnosed with PCa (ISUP groups 1/2/3/4 in n = 3/15/3/1 cases, respectively). In the TZ, T1 relaxation time was statistically significantly lower for PCa compared with reference regions ( P = 0.029) and benign prostate hyperplasia nodules ( P < 0.001). Similarly, in the PZ, PCa demonstrated shorter T1 relaxation times versus reference regions ( P < 0.001). PCa also showed a trend toward shorter T1 relaxation times (median, 1.40 seconds) compared with radiologically suspicious lesions with benign histology (median, 1.47 seconds), although statistical significance was not reached ( P = 0.066). For discrimination of PCa from reference regions and benign prostate lesions, T1 relaxation times and ADC values demonstrated AUC = 0.80 and AUC = 0.83, respectively ( P = 0.519). Discriminating PCa from radiologically suspicious lesions with benign histology, T1 relaxation times and ADC values showed AUC = 0.69 and AUC = 0.62, respectively ( P = 0.446)., Conclusions: T1FLASH-based T1 mapping yields robust results for quantification of prostate T1 relaxation time at a short examination time of 2:10 minutes without evident image artifacts. Associated T1 relaxation times could aid in discrimination of significant and nonsignificant PCa. Further studies are warranted to confirm these results in a larger patient cohort, to assess the additional benefit of T1FLASH maps in conjunction with mpMRI sequences in the setting of deep learning, and to evaluate the robustness of T1FLASH maps compared with potentially artifact-prone diffusion-weighted imaging sequences., Competing Interests: Conflicts of interest and sources of funding: Francesco Giganti is a recipient of the 2020 Young Investigator Award (20YOUN15) funded by the Prostate Cancer Foundation/CRIS Cancer Foundation. Francesco Giganti reports consulting fees from Lucida Medical LTD outside of the submitted work. The authors have no further conflict of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: To assess artifact burden and image quality of different MRI T1 mapping techniques of the prostate., Methods: Participants with suspected prostate cancer (PCa) were prospectively enrolled from June-October 2022 and examined with multiparametric prostate MRI (mpMRI; 3 T scanner; T1wi, T2wi, DWI und DCE). T1 mapping was performed before and after administration of gadolinium-based contrast-agent (GBCA) using (i) a modified Look-Locker inversion (MOLLI) technique and (ii) a novel single-shot T1FLASH inversion recovery technique. T2wi, DWI, T1FLASH and MOLLI sequences were systematically examined regarding prevalence of artifacts and image quality using a 5-point Likert-Scale., Results: A total of n = 100 patients were included (median age: 68 years). T1FLASH maps (pre-and post-GBCA) showed metal artifacts in 7% of cases and susceptibility artifacts in 1%. For MOLLI maps, pre-GBCA metal and susceptibility artifacts were documented in 6.5% of cases each. MOLLI maps post-GBCA showed artifacts in 59% of cases resulting primarily from urinary GBCA excretion and GBCA accumulation at the bladder base (p < 0.01 versus T1FLASH post-GBCA). Image quality for T1FLASH pre-GBCA was rated at a mean 4.9+/-0.4 and for MOLLI at 4.8+/-0.6 (p = 0.14). Post-GBCA image quality was rated at a mean 4.9+/-0.4 for T1FLASH and at 3.7+/-1.1 for MOLLI (p < 0.001)., Conclusions: T1FLASH maps provide a fast and robust method for quantification of T1 relaxation times of the prostate. T1FLASH is suitable for T1 mapping of the prostate following administration of contrast agents, while MOLLI T1 mapping is impaired through GBCA accumulation at the bladder base leading to severe image artifacts and reduced image quality., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Introduction: Multi-professional interdisciplinary tumor boards (ITB) are essential institutions to discuss all newly diagnosed, relapsed or complex cancer patients in a team of specialists to find an optimal cancer care plan for each individual patient with regard to national and international clinical practice guidelines, patient´s preference and comorbidities. In a high-volume cancer center, entity-specific ITBs take place at least once a week discussing a large number of patients. To a high level of expertise and dedication, this also requires an enormous amount of time for physicians, cancer specialists and administrative support colleagues, especially for radiologists, pathologists, medical oncologists and radiation oncologists, who must attend all cancer-specific boards according to certification requirements., Methods: In this 15-month prospective German single-center analysis, we examined the established structures of 12 different cancer-specific ITBs at the certified Oncology Center and demonstrate tools helping to optimize processes before, during and after the boards for optimal, time-saving procedures., Results: By changing pathways, introducing revised registration protocols and new digital supports we could show that the workload of preparation by radiologists and pathologists could be reduced significantly by 22.9% (p=<0.0001) and 52.7% (p=<0.0001), respectively. Furthermore, two questions were added to all registration forms about the patient´s need for specialized palliative care support that should lead to more awareness and early integration of specialized help., Discussion: There are several ways to reduce the workload of all ITB team members while maintaining high quality recommendations and adherence to national and international guidelines., Competing Interests: AS has received payment or honoraria for lectures, presentations, speaker’s bureaus, manuscript writing, or educational events from AstraZeneca, Bayer, BMS, Eisai, Ipsen, Merck, MSD, Pfizer, and Roche; has consultancy or advisory roles for AstraZeneca, Bayer, BMS, Eisai, Ipsen, Merck, MSD, Pfizer, and Roche; and has received travel support from BMS. CK is a member of the advisory board for BI, Roche, Bayer, and Novartis. K-MT has received honoraria from BMS, MSD, Roche, Novartis, Pierre Fabre, Sun Pharma, LEO, Almirall, Galderma, and Candela; has consultancy or advisory roles for BMS, MSD, Roche, Novartis, Pierre Fabre, Sun Pharma, LEO, and Almirall; and has received travel support from BMS, MSD, Roche, Novartis, Pierre Fabre, and LEO. MH is part of the advisory board for AstraZeneca, Roche, and BMS. JuG has received lecture fees from Merck Sharp & Dohme and Roche Diagnostics. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Braulke, Kober, Arndt, Papendick, Strauss, Kramm, Thoms, König, Gaedcke, Gallwas, Wulf, Szuszies, Wulf, Rödel, Wolfer, Malinova, Overbeck, Hinterthaner, Lotz, Nauck, Ernst, Stadelmann, Ströbel, Ellenrieder, Asendorf and Rieken.)