Purpose:Percutaneous thermal tumor ablation is an established oncologic treatment, but rising case numbers and limited anesthesia resources increasingly restrict procedural capacity. Radiologist-guided analgosedation may offer a pragmatic alternative to general anesthesia for selected ablation procedures. This study evaluates the safety, technical success, and impact on procedural throughput of performing microwave (MWA) and radiofrequency ablation (RFA) of hepatic, renal, and osseous tumors under analgosedation with midazolam and S-ketamine. Materials and Methods:In this retrospective single-center study, 140 percutaneous tumor ablations performed in 115 patients under radiologist-guided analgosedation between January 2022 and July 2024 were analyzed. The primary endpoint was the occurrence of sedation-related complications. Secondary endpoints included technical success, ablation-related complications, and changes in procedural volume compared with ablations performed under general anesthesia. Technical success was defined as complete tumor ablation with an adequate safety margin. Results:Of 115 planned patients, 113 (98.3%) were completed as intended. No major complications occurred. One minor complication (subcapsular hepatic hematoma, CIRSE grade 1) was observed. Four patients (3.5%) experienced transient post-interventional vomiting. No respiratory, cardiovascular, or anaphylactic adverse events were recorded. Transitioning from general anesthesia to analgosedation resulted in a significant increase in procedural volume from 2.1 to 6.3 ablations per month (p < 0.05). Mean in-room time was significantly shorter under analgosedation compared with general anesthesia (42 ± 34 min vs. 98 ± 42 min; p < 0.05). Conclusion:Radiologist-guided analgosedation with midazolam and S-ketamine is a feasible and safe approach for percutaneous thermal ablation of liver, kidney, and bone tumors. It enables high technical success without increasing complication rates and can substantially expand procedural capacity where anesthesiology resources are limited. Adequate training, structured workflows, and robust emergency preparedness are essential for safe implementation. Key Points:· Given the limited resources available for anaesthesia and the increasing demand for minimally invasive therapeutic procedures, the question of alternative concepts arises.. · At present, there is a lack of scientific research on the feasibility of percutaneous thermal ablation under analgosedation.. · This study demonstrated that percutaneous thermal tumour ablation under analgosedation is an effective method of achieving complete tumour ablation without increasing the rate of complications.. · It was shown that the use of analgosedation with S-ketamine and midazolam could increase procedural number of percutaneous thermal ablation procedures and therefore could reduce waiting times.. Citation Format:· Beeskow AB, Struck MF, Elkilany A et al. Radiologist-guided Analgosedation with Ketamine/Midazolam: A Feasible Strategy to Expand Percutaneous Tumor Ablation Capacity. Rofo 2026; DOI 10.1055/a-2786-2622.

Abstract Background Kidney disease is characterized by microstructural alterations that currently require invasive biopsy for definitive assessment. However, it remains unclear to what extent radiomics features extracted from contrast-enhanced CT can non-invasively reflect kidney function and histopathological changes. Methods Between October 2020 and May 2025 all patients undergoing kidney biopsies and having CT scans prior to biopsy were retrospectively analyzed. A total of 49 patients (59% female, median age 60 years) were included. Of the included patients, 35 biopsies were performed in native kidneys (71%) and 14 in kidney allografts (29%). Contrast-enhanced CT images were used to extract radiomics parameters of the kidney. Kidney segmentation was performed using TotalSegmentator and radiomics feature extraction was conducted with PyRadiomics. Results Several associations were identified between the extracted radiomics features and kidney function as well as kidney tissue alterations. For the eGFR (CKD-EPI) the highest association was found for the radiomics feature Energy, which is a measurement of the intensity uniformity (ρ = 0.51, p < 0.001), while the first-order feature 90th Percentile showed the best performance in discriminating patients above and below an eGFR threshold of 15 mL/min/1.73 m² with an AUC of 0.83 (95% CI: 0.67-0.98, p = 0.001). Busyness correlated negatively with glomerulosclerosis (ρ = -0.38, p = 0.007), and Coarseness was positively associated with interstitial inflammation (ρ = 0.37, p = 0.008). Conclusions CT radiomics features are associated with kidney function as well as histopathological alterations observed in kidney biopsies. Further validation is needed in future studies.

INTRODUCTION:Computed tomography (CT) is the modality of choice to diagnose acute pulmonary embolism (PE). The present multicentric study aimed to demonstrate the prognostic role of mediastinal lymphadenopathy for short mortality within 30 days in patients with acute PE. METHODS:The investigated patient sample comprised 935 patients (411 female, 44%) with a mean age of 65.3 ± 16.3 years derived from three academic centers. Contrast-enhanced CT pulmonalis angiography was used to assess the presence of mediastinal lymphadenopathy. The primary end point of this study was 30-day mortality. The Simplified Pulmonary Embolism Severity Index (sPESI) was calculated as a clinical prognostic score. RESULTS:A total of 98 patients (10.5%) died within the 30-day observation period. Mediastinal lymphadenopathy was present in a total of 171 cases (18.3%). Mediastinal lymphadenopathy was associated with 30-day mortality with an odds ratio (OR) of 1.83 (95% confidence interval [CI], 1.12-2.92; p = 0.013 in univariable analysis) and 1.67 (95% CI, 1.01-2.69; p = 0.041 in multivariable analysis). CONCLUSION:Mediastinal lymphadenopathy represents an independent prognostic factor for 30-day mortality in patients with acute PE. The underlying pathophysiological mechanisms remain unclear and should be further investigated.

Risk stratification is an important tool in clinical decision-making, yet current approaches often fail to translate sophisticated survival analysis into actionable clinical criteria. We present a novel method for training any neural network architecture on any data modality to identify prognostically distinct patient groups by directly optimizing for survival heterogeneity across patient clusters. We evaluate the method in simulation experiments and demonstrate its utility in practice by applying it to two distinct cancer types: analyzing laboratory parameters from multiple myeloma (MM) patients using the CoMMpass dataset and computed tomography images from non-small cell lung cancer (NSCLC) patients using the Lung1 dataset. Post-hoc explainability analyses uncover clinically meaningful features determining group assignments, which align well with established risk factors in both cases. Our findings in MM were externally validated using the GMMG-MM5 study dataset, while the NSCLC findings were validated with data from our own institution, thus lending strong weight to the method’s utility. This pan-cancer, model-agnostic approach enables the discovery of novel prognostic signatures across diverse data types while providing interpretable results that promise to complement treatment personalization and clinical decision-making in oncology and beyond.

Abstract Background Postoperative abdominal wall dehiscence (AWD) or burst abdomen (BA) is a relevant complication after abdominal surgery that causes additional surgical procedures, prolonged hospital stays and long-term morbidity. Several underlying risk factors exist and have been described in literature and consist of surgical and medical factors. Recently, CT-derived body composition is of rising interest to provide new prognostic factors in surgical patients. The present study aims to explore the association between CT-defined body composition and postoperative BA. Materials and methods A database of patients who underwent abdominal surgery and developed post-operative wound infections in our institution between 2015 and 2018, was assembled. The subgroup of patients with BA was compared to a control group without BA. CT-defined body composition was evaluated in L3-level measuring skeletal muscle index (SMI) for sarcopenia assessment, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Clinical risk factors and CT-defined body composition were used to predict the occurrence of postoperative BA using discriminatory and binary logistic regression analyses. Results A total of 118 patients, 92 (78%) with BA and 26 (22%) without BA were included in the analysis. CT derived body composition parameters for visceral obesity and sarcopenia showed statistically significant differences between the two cohorts. Patients with burst abdomen showed higher VAT (157.6 cm² vs. 84.9 cm², p = 0.001) and a significantly lower SMI (46.9 cm²/m² vs. 53.8 cm²/m², p = 0.016). Consequently, visceral obesity and sarcopenia were significantly more frequent in patients with BA (p = 0.02 and 0.01, respectively). In the multivariable Firth’s penalized logistic regression, visceral obesity (OR = 4.87, 95% CI 1.32–21.91 p = 0.02), sarcopenia (OR = 5.94, 95% CI 1.65–26.68 p = 0.006), intestinal resection (OR = 9.33, 95% CI 2.33–55.65 p < 0.001) and length of the surgical wound (OR = 1.12, 95% CI 1.04–1.22 p = 0.001) were independently associated with the occurrence of burst abdomen. Conclusion CT-defined body composition with sarcopenia and visceral obesity are strongly associated with postoperative BA. This analysis should be further acknowledged as a potentially important risk factor in surgical care and could aid in clinical decision making.

Background Dual-layer spectral CT reconstructs virtual monoenergetic images (VMI) at selectable photon energies from one contrast-enhanced acquisition. Low-energy VMI sharpen iodine-based tumour conspicuity, but contrast-to-noise (CNR), signal-to-noise (SNR), tumour-to-reference ratio (TRR), iodine concentration and effective atomic number (Z_eff) have not been jointly quantified across the VMI range in primary head and neck malignancy. Methods In this retrospective single-centre study, 56 patients (n = 40 males, 71.4%) with a median age of 69 years with histologically confirmed primary head and neck malignancy underwent contrast-enhanced dual-layer spectral CT (Philips Spectral CT 7500). Tumour attenuation, SNR, CNR, TRR, iodine concentration and Z_eff were measured at 40, 50, 60, 70 and 120 keV in mean-tumour, maximum intratumoral enhancement and ipsilateral-muscle ROIs, and compared by Friedman test with Bonferroni-corrected pairwise Wilcoxon tests. Subgroup analyses by p16 status and anatomical site were exploratory and uncorrected. Results CNR declined linearly from 9.74 (IQR 6.49–14.92) at 40 keV to 0.89 (− 0.22–2.07) at 120 keV (Friedman p < 0.001; Kendall's W = 0.80; all pairwise p < 0.001). TRR followed the same trajectory (2.37 to 1.13; W = 0.87). SNR peaked at 50 keV (16.60), falling to 7.93 at 120 keV. Tumour iodine (2.67 vs 0.72 mg/mL) and Z_eff (8.65 vs 7.69) exceeded muscle values (both p < 0.001) and were keV-independent by construction. CNR at 40 keV was lower in p16-positive than p16-negative tumours (median 4.89 vs 10.20; uncorrected p = 0.029). Conclusions Tumour-to-muscle contrast on dual-layer spectral CT is steeply energy-dependent: 40 keV maximizes CNR, 50 keV gives the best contrast/noise compromise, and the advantage is largely lost above 70 keV. A weaker low-energy contrast was observed in the nine p16-positive tumours and requires prospective confirmation.

Background:Sarcopenia can be assessed by cross-sectional imaging and is a prognostic imaging marker in several diseases and tumor entities. First reports demonstrated a significant impact of the presence of sarcopenia on the outcome of portal vein embolization (PVE). The present analysis sought to investigate the effect of computed tomography (CT)-defined sarcopenia in patients undergoing PVE based on a meta-analysis. Methods:MEDLINE library was screened for papers analyzing the association between CT-defined sarcopenia/low skeletal muscle mass and the treatment outcome of PVE up to February 2026. The primary endpoints of the systematic review were the increase or the volume or the growth rate per week of mean future liver remnant (FLR) in % between the groups stratified by sarcopenia. The random-effect model was used for the statistical analysis. Results:The meta-analysis comprised a total of seven studies with 599 patients with different malignant tumors undergoing PVE. For the effect of the future liver remnant volume (FLRV), the pooled mean difference (MD) between the sarcopenic and non-sarcopenic group was 2.70% [95% confidence interval (CI): 0.31-5.09], P=0.03, favoring non-sarcopenia. For the effect of the FLRV increase in %, the pooled MD between the sarcopenic and non-sarcopenic group was 10.87% (95% CI: 3.45-18.30), P=0.004. The pooled correlation coefficient between the skeletal muscle index (SMI) and the liver growth rate after PVE was 0.40 (95% CI: 0.17-0.63), P<0.001. Conclusions:No statistically effects were identified for the impact on resection rate, 90-day mortality and postoperative liver failure. CT-defined sarcopenia has a statistically but not clinically impact on the FLR in patients undergoing PVE.

ABSTRACT Background In uterine cervical cancer (UCC), reduced muscle mass and radiodensity have been linked to unfavourable clinical outcomes. Our aim was to elucidate the associations between body composition (BC) and intratumoural immune cells in patients with UCC. Methods In this retrospective study, BC was analysed in 61 patients with UCC using staging computed tomography. The parameters of BC were skeletal muscle area (SMA), skeletal muscle radiodensity, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and intramuscular adipose tissue (IMAT). The radiodensities of VAT, SAT and IMAT were also estimated. Tumour specimens underwent histopathological analysis to quantify stromal and intratumoural CD45‐positive cells. Associations between body composition parameters and tumour immune cell infiltration were analysed using ANOVA. Results Patients with low muscle radiodensity (myosteatosis) had a lower proportion of stromal CD45‐positive cells than patients with normal muscle radiodensity (21.6% ± 21.90% vs. 34.85% ± 25.55%; p = 0.04). High levels of SAT were associated with lower scores for tumour‐infiltrating CD45 cells (p = 0.03). High IMAT radiodensity was associated with lower stromal CD45 scores (p = 0.02). Conclusions Myosteatosis, high SAT and increased IMAT radiodensity were associated with reduced stromal and intratumoural immune cell infiltration in patients with UCC. These body composition parameters may serve as prognostic markers and should be explored in risk stratification.

BACKGROUND/AIM:To integrate the results of studies on interventional metrics of cone-beam computed-tomography (CBCT) guidance and fluoroscopy guidance in transjugular intrahepatic portosystemic shunt (TIPS) placement in a meta-analysis. MATERIALS AND METHODS:A systemic literature search was conducted in PubMed, Ovid/Medline, Cumulative Index to Nursing and Allied Health Literature, Web of Science and Google Scholar. Inclusion criteria were original research articles in English, comparison of CBCT and fluoroscopy guided TIPS placements and reporting of outcome parameters (procedure time, fluorotime, radiation exposure). Study quality was assessed by modified Downs-and-Black checklist. Heterogeneity was evaluated using forest plots, I2, and considering study differences. A meta-analysis was conducted to combine the outcome effect using mean difference (MD) between CBCT and fluoroscopy guided TIPS placements. RESULTS:In this meta-analysis, five studies with 218 patients and TIPS placements were included. Study quality was limited with 12±0 points for procedure time, fluorotime and dose area product (DAP). Heterogeneity was indicated in procedure time (I2=48.7%), fluorotime (I2=44.2%) and DAP (I2=55.4%). By application of random-effects model, procedure time and fluorotime of TIPS placements were not significantly different between CBCT and fluoroscopy guidance with an overall MD of -14.43min [95% confidence interval (CI)=-38.82 to 9.97 min; p=0.16] and -6.23 min (95% CI=-22.27 to 9.80 min; p=0.24). DAP was not significant between TIPS placement under CBCT and fluoroscopy guidance with a MD of 27.44 Gy*cm2 (95% CI=-10.47 to 65.34 Gy*cm2; p=0.11). CONCLUSION:CBCT guidance tends to accelerate fluoroscopy and procedure times with slightly elevated DAP compared to fluoroscopy guidance in TIPS placements. Evidence is limited by the small number of feasibility studies. Further investigations need standardized reporting, especially for procedural complications and shunt patency.

Chimeric antigen receptor (CAR) T-cell therapy has transformed the treatment of relapsed or refractory multiple myeloma (RRMM), yet outcomes remain heterogenous. The prognostic role of body composition in this context is unknown. We retrospectively analyzed 108 RRMM patients treated with anti-B-cell maturation antigen (BCMA) CAR T-cell therapy. Pre-treatment Computed tomography imaging was utilized to quantify total adipose tissue (TAT), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle area to assess sarcopenia. Longitudinal flow cytometric and single-cell multi-omic analyses were conducted to characterize the quantitative and qualitative influences of body composition on the immune microenvironment. Patients with BMI < 25 kg/m(2) experienced significantly worse overall survival (OS) compared to high-BMI patients. Reduced TAT, primarily driven by low SAT, was associated with inferior OS, diminished response, and elevated soluble BCMA. Sarcopenia independently predicted poorer OS, while progression-free survival was unaffected by the respective parameters. Low SAT and sarcopenia correlated with lower bystander T-cell counts at leukapheresis. Longitudinal T-cell receptor sequencing and single-cell transcriptomics revealed diminished cytotoxic and interferon signaling, reduced T-cell clonality, and increased oxidative phosphorylation activity following CAR T-cell infusion. Our findings identify low SAT and sarcopenia as prognostic biomarkers that influence survival, therapeutic response, and immunometabolic profiles. Their quantification through standard imaging techniques offers a cost-effective strategy for early risk stratification and individualized management in CAR T-cell therapy.

BACKGROUND:Computed tomography (CT)-defined bone mineral density (BMD) is a promising quantitative imaging marker that reflects the overall condition of patients, which was demonstrated in several diseases. OBJECTIVE:The present multicentric study aimed to demonstrate the prognostic role of BMD in patients with acute PE. METHODS AND RESULTS:The investigated patient sampled was comprised of 829 patients (355 female, 42.8%) with a mean age of 64.1 ± 15.8 years. The primary endpoint of this study was 30-day mortality. The simplified pulmonary embolism index (sPESI) was calculated as a clinical prognostic score. Logistic binary regression analyses were used to test the associations between BMD and 30-day mortality. A total of 94 patients (11.3%) died within the 30-day observation period. A weak inverse association was identified between BMD and sPESI score (r = -0.21, p <0.0001). Low BMD showed an association with 30-day mortality with an odds ratio (OR) of 2.26 (95% confidence interval [CI], 1.24 - 4.10; p = 0.008 in univariable analysis) and 2.39 (95% CI, 1.24 -4.44; p = 0.007) in multivariable analysis. CONCLUSION:Using the threshold value of 75 HU, bone mineral density is a prognostic factor in patients with acute pulmonary embolism. However, this threshold value is lower than the values previously proposed for diagnosing osteoporosis.

Abstract Background Medical education could benefit from the introduction of novel teaching techniques. The present study aimed to assess the effect of a gamified mobile app (LuluRad) to improve pneumothorax detection on chest radiographs (CXRs). Methods In this prospective, single-center randomized trial, third-year medical students were individually randomized using a coin toss to app-based learning (n = 60) or script-based learning (n = 66). Participants completed pre- and post-learning intervention CXR pneumothorax tests. The primary study outcome was pre/post diagnostic accuracy change between the app-based and script-based group. Secondary endpoints were changes in sensitivity and specificity. Results In the app group, accuracy increased from 50.8% to 65.0% (p = 0.015) and sensitivity from 53.3% to 67.2% (p = 0.022), while specificity did not change significantly (p = 0.068). In the script group, accuracy did not significantly change (p = 0.132), sensitivity decreased from 64.1% to 41.9% (p < 0.001), and specificity increased from 39.4% to 51.0% (p = 0.006). Between-group change scores demonstrated greater increases in accuracy (Δ + 14.2 vs. − 5.3% points (pp); p < 0.001) and sensitivity (Δ + 13.9 vs. − 22.2 pp; p < 0.001) in the app group, while specificity did not change significantly between groups (p = 0.378). Conclusion App-based learning was associated with greater increases in pneumothorax detection accuracy compared with conventional self-study among third-year medical students. Given the study design, these findings should be considered exploratory. While confirmation in larger studies is required, this approach appears promising and may represent a valuable adjunct to traditional teaching. Trial registration This trial was not prospectively registered due to its educational study design and the absence of any potential harm or disadvantage for participants.

Computed tomography (CT) is a first line imaging tool for staging of esophageal cancer (EC). Previous studies have shown promising results of the prognostic relevance of vessel calcifications quantified by CT, especially coronary and aortic calcifications, in oncological patients. The aim of this study was to analyze the prognostic relevance of aortic calcification assessed in staging CT in patients with EC undergoing curative treatment. All patients with EC treated with neoadjuvant therapy followed by curative resection at the University of Leipzig Medical Center, a tertiary care hospital, were retrospectively evaluated between 2016 and 2023. A total of 89 patients were included in the analysis. Abdominal aorta and iliac artery calcification volume was measured in a semi-automated fashion at baseline before neoadjuvant therapy using staging CT images. The primary endpoint was overall survival and disease-free survival was assessed as a secondary endpoint. For statistical analysis group differences were calculated using the Mann-Whitney-U test. Kaplan-Meier curves and multivariable Cox regression analysis were used to test the effect of aortic calcification volume and clinical variables on mortality. In univariable Cox regression, higher abdominal aortic calcification volume was significantly associated with shorter overall survival (Hazard ratio (HR) 1.259 per 1 cm³, 95

The advent of machine and deep learning in the medical domain has led to significant advancements in diagnostic workflows and clinical decision-making, making rigorous evaluation of novel techniques essential for their integration into clinical practice. In this work, we introduce a Bayesian hierarchical Beta-Binomial modeling framework for estimating the effect of novel techniques in binary classification, with a particular focus on multireader, multicase study designs, motivated by applications in medical imaging. Some challenges in this context include, small sample sizes (i.e., only few readers particicipating in the study), pronounced overdispersion due to heterogeneity in reader performance, and class-imbalanced datasets. Addiotionally, the actual effect size of the novel technique may be small, further complicating robust estimation of model parameters. The proposed model explicitly accounts for overdispersion, addresses class imbalance within the test cohort, and incorporates prior information to regularize population-level parameter estimates across readers. Through simulation studies, the approach demonstrates improved robustness and lower estimation error compared to classical linear models, especially under high overdispersion and low sample sizes. Application to a real-world study of chest X-ray imaging with and without Bone Suppression Imaging enhancement illustrates the model's practical utility and highlights the importance of accounting for overdispersion and prior information in study design and analysis.