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Objectives: Deep learning reconstruction of magnetic resonance imaging (MRI) allows to either improve image quality of accelerated sequences or to generate high-resolution data. We evaluated the interaction of conventional acceleration and Deep Resolve Boost (DRB)-based reconstruction techniques of a single-shot echo-planar imaging (ssEPI) diffusion-weighted imaging (DWI) on image quality features in cerebral 3 T brain MRI and compared it with a state-of-the-art DWI sequence., Materials and Methods: In this prospective study, 24 patients received a standard of care ssEPI DWI and 5 additional adapted ssEPI DWI sequences, 3 of those with DRB reconstruction. Qualitative analysis encompassed rating of image quality, noise, sharpness, and artifacts. Quantitative analysis compared apparent diffusion coefficient (ADC) values region-wise between the different DWI sequences. Intraclass correlations, paired sampled t test, Wilcoxon signed rank test, and weighted Cohen κ were used., Results: Compared with the reference standard, the acquisition time was significantly improved in accelerated DWI from 75 seconds up to 50% (39 seconds; P < 0.001). All tested DRB-reconstructed sequences showed significantly improved image quality, sharpness, and reduced noise (P < 0.001). Highest image quality was observed for the combination of conventional acceleration and DL reconstruction. In singular slices, more artifacts were observed for DRB-reconstructed sequences (P < 0.001). While in general high consistency was found between ADC values, increasing differences in ADC values were noted with increasing acceleration and application of DRB. Falsely pathological ADCs were rarely observed near frontal poles and optic chiasm attributable to susceptibility-related artifacts due to adjacent sinuses., Conclusions: In this comparative study, we found that the combination of conventional acceleration and DRB reconstruction improves image quality and enables faster acquisition of ssEPI DWI. Nevertheless, a tradeoff between increased acceleration with risk of stronger artifacts and high-resolution with longer acquisition time needs to be considered, especially for application in cerebral MRI., Competing Interests: Conflicts of interest and sources of funding: Thomas Benkert is an employee of Siemens Healthineers and works in the department for MR Application Predevelopment. Ralph Strecker is an employee of EMEA Scientific Partnerships for Siemens Healthineers and works as a collaboration manager. Thomas Benkert and Ralph Strecker had no control over the data at any time and provided technical information only. None of the other authors declare any conflict of interest, including Caroline Wilpert and Alexander Rau, who were in charge of all data at any given time point. No funding was obtained., (Copyright © 2025 Wolters Kluwer Health, Inc. All rights reserved.)

Background: The low clinically approved doses of gadolinium-based contrast agents (GBCA) do not generate sufficient enhancement on CT for diagnostic purposes. Photon-counting detector (PCD) CT offers improved spectral resolution and could potentially enable visualization of hepatocyte-specific GBCA given their associated high gadolinium concentrations within hepatocytes. Objective: To investigate the potential of gadoxetate disodium in combination with PCD CT and low-keV VMI reconstructions to achieve an increase in attenuation in a phantom. Methods: A series of solutions was prepared of diluted gadoxetate disodium (concentrations of 0.250-2.5 μmol/ml, corresponding with doses of 25-200 μmol/kg, respectively). These solutions, along with deionized water, were evaluated in an anthropomorphic abdominal phantom using a clinical PCD-CT scanner; virtual monoenergetic images (VMI) at 40, 50, 60, and 70 keV, along with virtual noncontrast (VMC) images, were generated. Attenuation measurements were obtained; a linear regression model combined these values with previously reported in vivo data to estimate hepatic enhancement and CNR across doses. Results: Attenuation increased with increasing concentration at a given energy level and with decreasing energy level for a given concentration; VNC images had lowest attenuation. The maximum attenuation reached was 45.2 HU for a concentration of 2.5 μmol/ml at 40 keV. A concentration of 0.25 μmol/ml had attenuation at 40 keV of 13.0 HU. The model yielded estimated in vivo hepatic enhancement at 40 keV of 4.9 HU for a dose of 25 μmol/kg, 19.9 HU for 100 μmol/kg, and 30.8 HU for 200 μmol/kg; corresponding CNRs were 0.13, 0.52, and 0.81, respectively. Conclusion: The combination of gadoxetate disodium and PCD CT could theoretically allow appreciable hepatic enhancement at a 200-μmol/kg dose; such effect was not observed for the clinically approved 25 μmol/kg dose. Clinical Impact: PCD CT achieved attenuation increases for gadoxetate disodium at considerably lower doses than previously documented for CT of GBCA, albeit approximately 8-times greater than clinical doses and thus too high for clinical use. Additional research exploiting PCD-CT technology could seek to reduce further doses required for sufficient visualization into a clinically feasible range, to potentially allow CT using a liver-specific agent.

Purpose: To evaluate the feasibility of aortoiliac CT-Angiography (CTA) using dual-source photon-counting detector (PCD)-CT with minimal iodine dose., Methods: This IRB-approved, single-center prospective study enrolled patients with indications for aortoiliac CTA from December 2022 to March 2023. All scans were performed using a first-generation dual-source PCD-CT. Images were acquired with fast pitch and full spectral capabilities (collimation 144 × 0.4 mm). The contrast protocol included a mixture of sodium chloride and iodinated contrast agent (Iopromide, total iodine dose: 9.5-9.8 g). Virtual monoenergetic images (VMIs) were reconstructed at 40, 50, 60, and 68 keV. Two blinded radiologists evaluated image quality on a 4-point scale. Attenuation was measured across eight regions in the aorta and iliac arteries, and contrast-to-noise ratio (CNR) was calculated. Statistical comparisons were performed using repeated measures ANOVA and Bonferroni post-hoc tests., Results: The final cohort consisted of 39 subjects (mean age: 69.6 ± 9.6 years; 30.8 % female). VMI at 40 keV provided significantly higher attenuation: 478 ± 114 HU, compared to 50 keV (331 ± 74 HU), 60 keV (241 ± 51 HU), and 68 keV (190 ± 48 HU) (p < 0.01). This translated in increased CNR for 40 keV reconstructions (11.8 ± 3.9), followed by 50 keV (9.1 ± 3.0), 60 keV (7.0 ± 2.3), and 68 keV (6.1 ± 1.9) (p < 0.01). Subjective image quality was rated excellent at 40 keV (4 [3,4]), though associated with highest noise (38 ± 7.4 HU, p = 0.02)., Conclusion: Aortoiliac CTA using dual-source PCD-CT at 40 keV achieved high attenuation and CNR, enabling effective imaging with only 9.8 g of iodine., 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 © 2025 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objective: Fatty infiltration of skeletal muscle (Myosteatosis) is associated with increased frailty, decreased muscle and mobility function, which seems fairly prevalent in multiple myeloma (MM) patients. This study aimed to determine the prognostic value of myosteatosis assessed by CT for progression-free survival (PFS) and overall survival (OS)., Materials and Methods: This IRB-approved cohort study included patients with newly diagnosed MM who were treated at a single university hospital and received CT at baseline. Geriatric assessment was performed via International Myeloma Working Group frailty score and Revised Myeloma Comorbidity Index. Myosteatosis was determined through measurement of paravertebral muscle radiodensity. Statistical analyses included uni- and multivariable Cox proportional hazard models and the Kaplan-Meier-method., Results: A total of 226 newly diagnosed MM patients (median age: 65 years [range: 29-89], 63% males, mean BMI: 25 [14-42]) were analyzed. The prevalence of myosteatosis was 51%. Muscle radiodensity was significantly decreased in individuals with International Staging System stage III vs. I (p < 0.001), indicating higher fatty muscle infiltration in patients with advanced disease. Both PFS and OS were significantly decreased in patients with myosteatosis (PFS: median 32.0 months (95% CI 20.5.5-42.2) vs. 66.4 months without myosteatosis (95% CI 42.5-not reached), p < .001); OS: median 58.6 (95% CI 51.3-90.2) vs. not reached, p < .001). Myosteatosis remained an independent predictor of OS in multivariable analyses (HR: 1.98; 95%-CI: 1.20-3.27)., Conclusion: Myosteatosis seems fairly prevalent in patients with newly diagnosed MM and associated with impaired overall survival. Prospective clinical trials are required to better understand the role of myosteatosis in MM patients., Competing Interests: Declarations. Conflict of interest: The authors declare that they have no conflict of interest. Disclosures: None., (© 2024. The Author(s).)

Purpose: Directional deep brain stimulation (dDBS) relies on electrodes steering the stimulation field in a specific direction. Post implantation, however, the intended and real orientation of the lead frequently deviates e.g. due to torque of the electrode. The orientation is assessed by postoperative imaging such as C-arm cone-beam CT (CBCT) using 3D rotational fluoroscopy and multi-slice CT (MSCT). The objective is to determine the effect of different X-ray systems such as CBCT and MSCT, and scan acquisition parameters on effective radiation doses., Material and Methods: We retrospectively investigated the dose area product (DAP) and dose length product (DLP) of patients who underwent both CBCT and MSCT after dDBS surgery. These metrics were then converted into the effective dose by established conversion coefficients. For CBCT, the feasible dose optimization by collimation was virtually assessed. Univariate analysis was performed to determine differences., Results: Among 88 patients median effective dose was 0.20 ± 0.07 mSv in CBCT and 2.11 ± 0.33 mSv in MSCT (p < 0.001). The field of view (FOV) in CBCT can be collimated in craniocaudal orientation by 33.6 % and mediolaterally by 60.8 %. This optimized collimation implies an effective dose reduction of 76 % (p < 0.001). Comparison of the effective dose of MSCT vs. CBCT revealed a significant dose reduction by 90.3 % (p < 0.001), whereas optimal collimation by 97.7 % (p < 0.001)., Conclusions: For assessment of dDBS orientation, CBCT had significantly lower radiation doses compared to MSCT. Optimized collimation in CBCT allows for a further substantial dose reduction. Moreover, the proposed approach is applicable on other neuroimaging procedures such as 3D visualization of treated intracranial aneurysm., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Unrelated: V.A.C. receives a collaborative grant from BrainLab (Munich, Germany). He is a consultant for Ceregate (Munich, Germany), Cortec (Freiburg, Germany), ALEVA (Lausanne, Switzerland) and Inbrain (Barcelona, Spain). He has an ongoing IIT with Boston Scientific (USA) and has received personal honoraria and travel support for lecture work from Boston Scientific (USA), UNEEG and PRECISIS. HU is co-editor of Clinical Neuroradiology, member of the Advisory Board of Biogen and received honoraria for lectures from Biogen, Eisai, and mbits. P.C.R. has received research support from Else Kröner-Fresenius Foundation, Fraunhofer Foundation (ATTRACT), German Ministry for Economic Affairs and Energy, and Medical Faculty of the University of Freiburg. He has received personal honoraria for lectures or advice from Fraunhofer Foundation and is a consultant for Boston Scientific, Brainlab, and Inomed. BEAS receives a research grant from Ceregate (Hamburg, Germany) and honoraria as a consultant for Precisis (Heidelberg, Germany), both unrelated to the submitted work. AR was supported by Berta-Ottenstein-Programme for Clinician Scientists, Faculty of Medicine, University of Freiburg. 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 © 2025 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Physical activity supports weight regulation and metabolic health, but its timing in relation to obesity and diabetes remains unclear. We aimed to assess the diurnal timing of physical activity and its association with obesity and diabetes., Methods: We cross-sectionally analyzed hip-worn accelerometry data from 61,116 participants aged 20-75 in the German National Cohort between 2015 and 2019. We divided physical activity into sex- and age-standardized quartiles of total morning (06:00-11:59), afternoon (12:00-17:59), evening (18:00-23:59), and nighttime (00:00-06:00) physical activity. Using multivariable logistic regression, we estimated associations of physical activity timing with obesity (BMI ≥ 30.0 kg/m 2 ) and diabetes (self-reported or HbA1c ≥ 6.5%). We accounted for sex, age, study region, education, employment, risky alcohol use, smoking, night shift work, and sleep duration., Results: High afternoon (top vs. bottom quartile, OR: 0.36, 95% CI: 0.33-0.38) and evening physical activity (OR: 0.45, 95% CI: 0.42-0.48) showed lower obesity odds than high morning activity (OR: 0.71, 95% CI: 0.66-0.76), whereas nighttime activity increased obesity odds (OR: 1.58, 95% CI: 1.48-1.68). Associations were similar for diabetes, with the lowest odds for afternoon (OR: 0.47, 95% CI: 0.42-0.53), followed by evening (OR: 0.56, 95% CI: 0.50-0.62) and morning activity (OR: 0.80, 95% CI: 0.71-0.89), and higher odds for nighttime activity (OR: 1.43, 95% CI: 1.29-1.58). Findings were not modified by employment status, night shift work, and sleep duration., Conclusions: Our cross-sectional findings require longitudinal corroboration but suggest afternoon and evening activity provide greater metabolic health benefits than morning activity, while nighttime activity is discouraged., Competing Interests: Competing interests: The authors declare no competing interests. Ethics approval and consent to participate: The NAKO obtained ethics approval from all local committees of the study centers (original ethics approval of the leading ethics committee of the Bayerische Landesaerztekammer with protocol code 13023). All participants provided written informed consent. This study was conducted in line with the Declaration of Helsinki and the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guideline for cross-sectional studies., (© 2025. The Author(s).)

This experimental phantom study investigates current standard of care protocols in cone beam computed tomography (CBCT), energy-integrating-detector (EID) CT, and photon-counting-detector (PCD) CT regarding their potential in delineation of dental root canals. Artificial accessory canals (diameters: 1000, 600, 400, 300 and 200 μm) were drilled into three bovine teeth mounted on a bovine rib as a jaw substitute. The phantom was scanned in two dental CBCTs, two EID-CTs and a PCD-CT using standard clinical protocols. Scans from a micro-CT served as reference standard. Spatial resolution was evaluated via line profiles through the canals, whereby visibility compared to surrounding noise and compared to the ground truth were assessed. PCD-CT was able to delineate all artificial canals down to 200 μm diameter. In CBCT and EID-CT canals could only be reliably detected down to 300 μm. Also, PCD-CT showed a considerably smaller width-divergence from the ground trough with 4.4% at 1000 μm and 35.1% at 300 μm compared to CBCT (13.5 and 72.9%) and EID-CT (10.1 and 115.7%). PCD-CT provided superior resolution, accurate size measurement, and enhanced detection of small dental root canals, thereby offering improvements in diagnostic capabilities compared to CBCT and EID-CT systems., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Competing Interests: Disclosure The authors report no conflicts of interest in this work.

Objective: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2 DL ) and a conventional T2-w FSE Dixon sequence (T2 STD ) for breast magnetic resonance imaging (MRI)., Materials and Methods: This prospective study was conducted between November 2022 and April 2023 using a 3T scanner. Both T2 DL and T2 STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2 DL and T2 STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed., Results: Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2 DL compared to 266 s ± 0 for T2 STD . SNR and CNR were significantly higher in T2 DL ( P < 0.001). T2 DL was associated with higher image quality scores, reduced noise, and fewer artifacts ( P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2 DL ( P ≤ 0.008), except for bone marrow, which scored higher in T2 STD ( P < 0.001). Scores for conspicuity, sharpness/margins, and microstructure of cysts and breast cancers were higher in T2 DL ( P ≤ 0.002). Diagnostic confidence for cysts was improved with T2 DL ( P < 0.001). Readers significantly preferred T2 DL over T2 STD in side-by-side comparisons ( P < 0.001)., Conclusion: T2 DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2 STD . This led to fewer artifacts and improved overall image quality. Thus, T2 DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations., Competing Interests: Ralph Strecker, Marcel Dominic Nickel and Elisabeth Weiland are employees of Siemens Healthineers and work in the department for MR Application Predevelopment. Ralph Strecker is an employee of EMEA Scientific Partnerships for Siemens Healthineers and works as a collaboration manager. Employees of Siemens Healthineers had no control over the data at any time and provided technical information only. None of the other authors declare any conflict of interest, including Caroline Wilpert, who was in charge of all data at any given time point., (Copyright © 2025 The Korean Society of Radiology.)

Purpose: The study aimed to assess the feasibility and image quality of dual-source photon-counting detector computed tomography (PCD-CT) in evaluating small-sized coronary artery stents with respect to different acquisition modes in a phantom model., Methods: Utilizing a phantom setup mimicking the average patient's water-equivalent diameter, we examined six distinct coronary stents inflated in a silicon tube, with stent sizes ranging from 2.0 to 3.5 mm, applying four different CT acquisition modes of a dual-source PCD-CT scanner: "high-pitch," "sequential," "spiral" (each with collimation of 144 × 0.4 mm and full spectral information), and "ultra-high-resolution (UHR)" (collimation of 120 × 0.2 mm and no spectral information). Image quality and diagnostic confidence were assessed using subjective measures, including a 4-point visual grading scale (4 = excellent; 1 = non-diagnostic) utilized by two independent radiologists, and objective measures, including the full width at half maximum (FWHM)., Results: A total of 24 scans were acquired, and all were included in the analysis. Among all CT acquisition modes, the highest image quality was obtained for the UHR mode [median score: 4 (interquartile range (IQR): 3.67-4.00)] ( P = 0.0015, with 37.5% rated as "excellent"), followed by the sequential mode [median score: 3.5 (IQR: 2.84-4.00)], P = 0.0326 and the spiral mode [median score: 3.0 (IQR: 2.53-3.47), P > 0.05]. The lowest image quality was observed for the high-pitch mode [median score: 2 (IQR: 1- 3), P = 0.028]. Similarly, diagnostic confidence for evaluating stent patency was highest for UHR and lowest for high-pitch ( P < 0.001, respectively). Measurement of stent dimensions was accurate for all acquisition modes, with the UHR mode showing highest robustness (FWHM for sequential: 0.926 ± 0.061 vs. high-pitch: 0.990 ± 0.083 vs. spiral: 0.962 ± 0.085 vs. UHR: 0.941 ± 0.036, P = non-significant, respectively)., Conclusion: Assessing small-sized coronary stents using PCD-CT technology is feasible. The UHR mode offers superior image quality and diagnostic confidence, while all modes show consistent and accurate measurements., Clinical Significance: These findings highlight the potential of PCD-CT technology, particularly the UHR mode, to enhance non-invasive coronary stent evaluation. Confirmatory research is necessary to influence the guidelines, which recommend cardiac CT only for stents of 3 mm or larger., Competing Interests: Fabian Bamberg Siemens Healthineers AG (unrestricted research grant, speaker’s bureau), Christopher L. Schlett Siemens Healthineers AG (speaker’s bureau), Muhammad Taha Hagar Siemens Healthineers AG (speaker‘s bureau). Other authors have nothing to disclose.

Competing Interests: The authors declare that they have no conflict of interest.

Background : To validate the automated quantification of cardiac chamber volumes and myocardial mass on non-contrast chest CT using cardiac MR (CMR) as a reference. Methods : We retrospectively included 53 consecutive patients who received non-contrast chest CT and CMR within three weeks. A deep learning model created cardiac segmentations on axial soft-tissue reconstructions from CT, covering all four cardiac chambers and the left ventricular myocardium. Segmentations on CMR cine short-axis and long-axis images served as a reference. Standard estimates of diagnostic accuracy were calculated for ventricular volumes at end-diastole and end-systole (LVEDV, LVESV, RVEDV, RVESV), left ventricular mass (LVM), and atrial volumes (LA, RA) at ventricular end-diastole. A qualitative assessment noted segmentation issues. Results : The deep learning model generated CT measurements for 52 of the 53 patients (98%). Based on CMR measurements, the average LVEDV was 166 ± 64 mL, RVEDV was 144 ± 51 mL, and LVM was 115 ± 39 g. The CT measurements correlated well with CMR measurements for LVEDV, LVESV, and LVM (ICC = 0.85, ICC = 0.84, and ICC = 0.91; all p < 0.001) and RVEDV and RVESV (ICC = 0.79 and ICC= 0.78; both p < 0.001), and moderately well with LA and RA (ICC = 0.74 and ICC = 0.61; both p < 0.001). Absolute agreements likewise favored LVEDV, LVM, and RVEDV. ECG-gating did not relevantly influence the results. The CT results correctly identified 7/15 LV and 1/1 RV as dilated (one and six false positives, respectively). Major qualitative issues were found in three cases (6%). Conclusions : Automated cardiac chamber volume and myocardial mass quantification on non-contrast chest CT produced viable measurements in this retrospective sample. Relevance Statement : An automated cardiac assessment on non-contrast chest CT provides quantitative morphological data on the heart, enabling a preliminary organ evaluation that aids in incidentally identifying at-risk patients who may benefit from a more targeted diagnostic workup.

In radiology, technological progress has led to an enormous increase in data volumes. To effectively use these data during diagnostics or subsequent clinical evaluations, they have to be aggregated at a central location and be meaningfully retrievable in context. Radiology data warehouses undertake this task: they integrate diverse data sources, enable patient-specific and examination-specific evaluations, and thus offer numerous benefits in patient care, education, and clinical research.The international standard Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) is particularly suitable for the implementation of such a data warehouse. FHIR allows for easy and fast data access, supports modern web-based frontends, and offers high interoperability due to the integration of medical ontologies such as SNOMED-CT or RadLex. Furthermore, FHIR has a robust data security concept. Because of these properties, FHIR has been selected by the Medical Informatics Initiative (MII) as the data standard for the core data set and is intended to be promoted as an international standard in the European Health Data Space (EHDS).Implementing the FHIR standard in radiology data warehouses is therefore a logical and sensible step towards data-driven medicine. · A data warehouse is essential for data-driven medicine, clinical care, and research purposes.. · Data warehouses enable efficient integration of AI results and structured report templates.. · Fast Healthcare Interoperability Resources (FHIR) is a suitable standard for a data warehouse.. · FHIR provides an interoperable data standard, supported by proven web technologies.. · FHIR improves semantic consistency and facilitates secure data exchange.. · Arnold P, Pinto dos Santos D, Bamberg F et al. FHIR - Overdue Standard for Radiology Data Warehouses. Fortschr Röntgenstr 2024; DOI 10.1055/a-2462-2351., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Background: The introduction of photon-counting detector computed tomography (PCD-CT) heralds a new generation of cardiac imaging., Objectives: This review discusses the current scientific literature to determine the incremental value of PCD-CT in cardiac imaging., Methods: Discussion of currently available literature regarding cardiac PCD-CT from a radiological perspective., Results: Since its market introduction in 2021, numerous studies have explored the advantages of this new technology in the field of cardiac imaging, including improved image quality through superior spatial resolution, a higher contrast-to-noise ratio, reduced artifacts, and lower radiation dose., Conclusion: While preliminary studies have been promising, it remains to be seen how the advantages of PCD-CT will affect clinical guidelines for cardiac CT., Competing Interests: Einhaltung ethischer Richtlinien. Interessenkonflikt: T. Emrich erhielt ein Referentenhonorar und Reisekostenunterstützung von Siemens, sowie institutionelle Forschungsunterstützung von Siemens sowie Beratertätig bei Circle Cardiovascular Imaging. M.T. Hagar: Siemens Healthineers speaker’s bureau. C.L. Schlett: Siemens Healthineers and Bayer Healthcare speaker’s bureau. Y.C. Layer wurde durch eine Forschungsförderung von Siemens Healthcare unterstützt. A. Varga-Szemes erhält institutionelle Forschungsunterstützung und/oder persönliche Honorare von Elucid Bioimaging und Siemens. D. Kravchenko, M. Vecsey-Nagy, G. Tremamunno und F. Bamberg geben an, dass kein Interessenkonflikt besteht. Für diesen Beitrag wurden von den Autor/-innen keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Competing Interests: Einhaltung ethischer Richtlinien. Interessenkonflikt: E. See ist kooptiertes Vorstandsmitglied des Forums Junge Radiologie (FJR) der Deutschen Röntgengesellschaft e. V. (DRG); Stellv. Vorsitzende der AG Gesundheitspolitische Verantwortung der DRG; Vertreterin im Bündnis Junge Ärztinnen und Ärzte für das FJR und die DRG; Mitglied im Workshop Mutterschutz der Ärztekammer Nordrhein für die DRG; Delegierte der Landesärztekammer Hessen (Liste der Fachärztinnen und Fachärzte); Mitglied im Ausschuss Ärztliche Weiterbildung der Landesärztekammer Hessen. Bis 03/2024 Mitglied der Tarifkommission und der Clearingstelle Arbeiten in der Schwangerschaft für den TV‑Ä der Unikliniken Hessen. A. Ljimani ist stellvertretende Vorsitzende des Netzwerkes Diversity@DRG und aktives Mitglied des Netzwerkes Radiologinnen@DRG. E. See, C. Herold, F. Bamberg und A. Ljimani geben an, dass kein Interessenkonflikt besteht. Für diesen Beitrag wurden von den Autor/-innen keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien.

Purpose: To investigate if GPT-4 improves the accuracy, consistency, and trustworthiness of a context-aware chatbot to provide personalized imaging recommendations from American College of Radiology (ACR) appropriateness criteria documents using semantic similarity processing: In addition, we sought to enable auditability of the output by revealing the information source the decision relies on., Material and Methods: We refined an existing chatbot that incorporated specialized knowledge of the ACR guidelines by upgrading GPT-3.5-Turbo to its successor GPT-4 by OpenAI, using the latest version of LlamaIndex, and improving the prompting strategy. This chatbot was compared to the previous version, generic GPT-3.5-Turbo and GPT-4, and general radiologists regarding the performance in applying the ACR appropriateness guidelines., Results: The refined context-aware chatbot performed superior to the previous version using GPT-3.5-Turbo, generic chatbots GPT-3.5-Turbo and GPT-4, and general radiologists in providing "usually or may be appropriate" recommendations according to the ACR guidelines (all p < 0.001). It also outperformed GPT-3.5-Turbo and general radiologists in respect to "usually appropriate" recommendations (both p < 0.001). Moreover, the consistency in correct answers was higher with 78 % consistent correct "usually appropriate" answers and 94 % for "usually or may be appropriate" recommendations. In all cases, the same source documents were chosen, ensuring transparency., Conclusion: Our study demonstrates the significance of context awareness in ensuring the use of appropriate knowledge and proposes a strategy to enhance trust in chatbot-based outputs to provide transparency. The improvements in accuracy, consistency, and source transparency address trust issues and enhance the clinical decision support process., Abbreviations: ACR, American College of Radiology; accGPT, appropriateness criteria context aware GPT; accGPT-4, appropriateness criteria context aware GPT using GPT-4; GPT, generative pre-trained transformer; LLM, Large Language Model., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: AR received grants from Berta-Ottenstein-Programme for Clinician Scientists, Faculty of Medicine, University of Freiburg., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Manually extracted imaging-based body composition measures from a single-slice area (A) have shown associations with clinical outcomes in patients with cardiometabolic disease and cancer. With advances in artificial intelligence, fully automated volumetric (V) segmentation approaches are now possible, but it is unknown whether these measures carry prognostic value to predict mortality in the general population. Here, we developed and tested a deep learning framework to automatically quantify volumetric body composition measures from whole-body magnetic resonance imaging (MRI) and investigated their prognostic value to predict mortality in a large Western population., Methods: The framework was developed using data from two large Western European population-based cohort studies, the UK Biobank (UKBB) and the German National Cohort (NAKO). Body composition was defined as (i) subcutaneous adipose tissue (SAT), (ii) visceral adipose tissue (VAT), (iii) skeletal muscle (SM), SM fat fraction (SMFF), and (iv) intramuscular adipose tissue (IMAT). The prognostic value of the body composition measures was assessed in the UKBB using Cox regression analysis. Additionally, we extracted body composition areas for every level of the thoracic and lumbar spine (i) to compare the proposed volumetric whole-body approach to the currently established single-slice area approach on the height of the L3 vertebra and (ii) to investigate the correlation between volumetric and single slice area body composition measures on the level of each vertebral body., Findings: In 36,317 UKBB participants (mean age 65.1 ± 7.8 years, age range 45-84 years; 51.7% female; 1.7% [634/36,471] all-cause deaths; median follow-up 4.8 years), Cox regression revealed an independent association between V SM (adjusted hazard ratio [aHR]: 0.88, 95% confidence interval [CI] [0.81-0.91], p = 0.00023), V SMFF (aHR: 1.06, 95% CI [1.02-1.10], p = 0.0043), and V IMAT (aHR: 1.19, 95% CI [1.05-1.35], p = 0.0056) and mortality after adjustment for demographics (age, sex, BMI, race) and cardiometabolic risk factors (alcohol consumption, smoking status, hypertension, diabetes, history of cancer, blood serum markers). This association was attenuated when using traditional single-slice area measures. Highest correlation coefficients (R) between volumetric and single-slice area body composition measures were located at vertebra L5 for SAT (R = 0.820) and SMFF (R = 0.947), at L3 for VAT (R = 0.892), SM (R = 0.944), and at L4 for IMAT (R = 0.546) (all p < 0.0001). A similar pattern was found in 23,725 NAKO participants (mean age 53.9 ± 8.3 years, age range 40-75; 44.9% female)., Interpretation: Automated volumetric body composition assessment from whole-body MRI predicted mortality in a large Western population beyond traditional clinical risk factors. Single slice areas were highly correlated with volumetric body composition measures but their association with mortality attenuated after multivariable adjustment. As volumetric body composition measures are increasingly accessible using automated techniques, identifying high-risk individuals may help to improve personalised prevention and lifestyle interventions., Funding: This project was conducted using data from the German National Cohort (NAKO) (www.nako.de). The NAKO is funded by the Federal Ministry of Education and Research (BMBF) [project funding reference numbers: 01ER1301A/B/C, 01ER1511D, and 01ER1801A/B/C/D], federal states of Germany and the Helmholtz Association, the participating universities and the institutes of the Leibniz Association. This research has been conducted using the UK Biobank Resource under Application Number 80337. MJ was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)-518480401. VKR was funded by American Heart Association Career Development Award 935176 and National Heart, Lung, and Blood Institute-K01HL168231., Competing Interests: Declaration of interests Vineet K. Raghu: Grants or contracts from any entity: Norn Group, Johnson and Johnson Innovation, National Academy of Medicine. Tobias Pischon: Leadership in board: Member of the board of directors of the NAKO e.V., who are leading the NAKO study (unpaid position). Hans-Ulrich Kauczor: Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: Siemens Healthineers, Philips, Boehringer Ingelheim Participation on a Data Safety Monitoring Board or Advisory Board: Median, contextflow. Christopher L. Schlett: Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: Siemens Healthineers, Bayer Healthcare. Michael T. Lu: Grants or contracts from any entity: American Heart Association, AstraZeneca, Ionis, Johnson & Johnson Innovation, Kowa Pharmaceuticals America, MedImmune, National Academy of Medicine, National Heart, Lung, and Blood Institute, and Risk Management Foundation of the Harvard Medical Institutions. Fabian Bamberg: Grants or contracts from any entity: Siemens Healthineers, Bayer Healthcare Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: Siemens Healthineers, Bayer Healthcare. Leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid: German Roentgen Society. Jakob Weiss: Consulting fees: Onc.AI., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: For characterizing health states, fat distribution is more informative than overall body size. We used population-based whole-body magnetic resonance imaging (MRI) to identify distinct body composition subphenotypes and characterize associations with cardiovascular disease (CVD) risk., Methods: Bone marrow, visceral, subcutaneous, cardiac, renal, hepatic, skeletal muscle and pancreatic adipose tissue were measured by MRI in n = 299 individuals from the population-based KORA cohort. Body composition subphenotypes were identified by data-driven k-means clustering. CVD risk was calculated by established scores., Results: We identified five body composition subphenotypes, which differed substantially in CVD risk factor distribution and CVD risk. Compared to reference subphenotype I with favorable risk profile, two high-risk phenotypes, III&V, had a 3.8-fold increased CVD risk. High-risk subphenotype III had increased bone marrow and skeletal muscle fat (26.3 % vs 11.4 % in subphenotype I), indicating ageing effects, whereas subphenotype V showed overall high fat contents, and particularly elevated pancreatic fat (25.0 % vs 3.7 % in subphenotype I), indicating metabolic impairment. Subphenotype II had a 2.7-fold increased CVD risk, and an unfavorable fat distribution, probably smoking-related, while BMI was only slightly elevated. Subphenotype IV had a 2.8-fold increased CVD risk with comparably young individuals, who showed high blood pressure and hepatic fat (17.7 % vs 3.0 % in subphenotype I)., Conclusions: Whole-body MRI can identify distinct body composition subphenotypes associated with different degrees of cardiometabolic risk. Body composition profiling may enable a more comprehensive risk assessment than individual fat compartments, with potential benefits for individualized prevention., 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 © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Since the approval of the first dual-source photon-counting detector CT (PCD-CT) in the fall of 2021, significant insights have been gained in its application for cardiovascular imaging. This review aims to provide a comprehensive overview of the current state of knowledge and the growing body of research literature, illustrating innovative applications and perspectives through case examples.We conducted a structured literature review, identifying relevant studies via Google Scholar and PubMed, using the keywords "photon-counting detector", "cardiovascular CT", "cardiac CT", and "ultra-high-resolution CT". We analyzed studies published since January 2015. Additionally, we integrated our own clinical experiences and case examples.In addition to the well-known benefit of increased temporal resolution offered by dual-source scanners, dual-source PCD-CT provides three key advantages: 1) Optimized geometric dose efficiency with an improved contrast-to-noise ratio, 2) intrinsic spectral sensitivity, and 3) the ability for ultrahigh-resolution CT. This technology enables improved image quality or radiation dose reduction in established cardiovascular protocols. Its use in non-invasive cardiac diagnostics for obese patients, those with a high plaque burden, or after stent implantation appears technically feasible, potentially expanding the scope of CT. The spectral sensitivity also allows tailored image acquisition, reducing metallic artifacts and contrast agent doses in patients with renal impairment. Early studies and clinical experience support these potential applications of PCD-CT in cardiovascular diagnostics, suggesting workflow optimization and improved patient management.However, challenges remain, including high costs, large data volumes, somewhat longer reconstruction times, and technical difficulties in combining spectral sensitivity with ultra-high resolution. Prospective randomized studies with clinical endpoints are lacking to confirm the clear advantage over conventional scanners. Future research should focus on endpoint-based studies and robust cost-benefit analyses to evaluate the potential of this technology and facilitate its evidence-based integration in clinical practice. · Photon-counting detector CT represents a technological advancement in computed tomography.. · Spectral sensitivity enhances iodine signal and minimizes artifacts.. · Ultra-high-resolution CT allows precise imaging, even in stents and advanced sclerosis.. · This technology must be validated through endpoint-based, randomized studies.. · Hagar MT, Schlett CL, Oechsner T et al. Photon-Counting Detector CT: Advances and Clinical Applications in Cardiovascular Imaging. Fortschr Röntgenstr 2024; DOI 10.1055/a-2452-0288., Competing Interests: MTH Speakers’ bureau (Siemens Healthineers) CLS Speakers’ bureau (Siemens Healthineers) AVS Unrestricted research grant, speakers’ bureau (Siemens Healthineers) TE Unrestricted research grant, speakers’ bureau (Siemens Healthineers) XC Is an employee of Siemens Healthineers FB Unrestricted research grant, speakers’ bureau (Siemens Healthineers, Bayer Healthcare) All other authors declare no potential conflicts of interest., (Thieme. All rights reserved.)

Objective: Imaging biomarkers of bone, muscle, and fat by magnetic resonance imaging (MRI) may depict osteopenia, sarcopenia, and adiposity as the three different conditions of osteosarcopenic adiposity (OSA). Methods: Subjects from a prospective, population-based case-control study underwent a health assessment and 3 Tesla whole-body MRI scan. Imaging biomarkers of bone (bone marrow fat-fraction (BMFF)), skeletal muscle (skeletal muscle FF (SMFF)), and fat (total adipose tissue (TAT)) were determined. Participants were allocated to one phenotype according to the OSA complex. Results: Among 363 participants forming the study cohort, 81 (22.3%, 48.1% males, 62.4 ± 6.9 years) were allocated into the OSA subgroup. Participants with an OSA phenotype were significantly older compared to all remaining subjects and showed the highest grades of SMFF (all p < 0.005). Together with subjects from the osteopenic sarcopenia group, OSA subjects exhibited the highest amounts of BMFF and together with the three other adiposity-containing subgroups also exhibited the highest BMIs. The highest prevalence of an impaired glucose tolerance as well as significantly higher blood pressure, blood dyslipidemia, and hepatic steatosis was found in the OSA subgroup (all p < 0.005). Conclusions: MR biomarkers of bone, skeletal muscle and fat are feasible for body composition phenotyping and may allow for targeted risk stratification in suspected OSA syndrome.

Purpose: Large language models (LLMs) such as ChatGPT have shown significant potential in radiology. Their effectiveness often depends on prompt engineering, which optimizes the interaction with the chatbot for accurate results. Here, we highlight the critical role of prompt engineering in tailoring the LLMs' responses to specific medical tasks., Materials and Methods: Using a clinical case, we elucidate different prompting strategies to adapt the LLM ChatGPT using GPT4 to new tasks without additional training of the base model. These approaches range from precision prompts to advanced in-context methods such as few-shot and zero-shot learning. Additionally, the significance of embeddings, which serve as a data representation technique, is discussed., Results: Prompt engineering substantially improved and focused the chatbot's output. Moreover, embedding of specialized knowledge allows for more transparent insight into the model's decision-making and thus enhances trust., Conclusion: Despite certain challenges, prompt engineering plays a pivotal role in harnessing the potential of LLMs for specialized tasks in the medical domain, particularly radiology. As LLMs continue to evolve, techniques like few-shot learning, zero-shot learning, and embedding-based retrieval mechanisms will become indispensable in delivering tailored outputs., Key Points: · Large language models might impact radiological practice and decision-masking.. · However, implementation and performance are dependent on the assigned task.. · Optimization of prompting strategies can substantially improve model performance.. · Strategies for prompt engineering range from precision prompts to zero-shot learning.., Citation Format: · Russe MF, Reisert M, Bamberg F et al. Improving the use of LLMs in radiology through prompt engineering: from precision prompts to zero-shot learning . Fortschr Röntgenstr 2024; 196: 1166 - 1170., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Objectives: To establish and evaluate an ultra-fast MRI screening protocol for prostate cancer (PCa) in comparison to the standard multiparametric (mp) protocol, reducing scan time and maintaining adequate diagnostic performance., Materials and Methods: This prospective single-center study included consecutive biopsy-naïve patients with suspected PCa between December 2022 and March 2023. A PI-RADSv2.1 conform mpMRI protocol was acquired in a 3 T scanner (scan time: 25 min 45 sec). In addition, two deep-learning (DL) accelerated sequences (T2- and diffusion-weighted) were acquired, serving as a screening protocol (scan time: 3 min 28 sec). Two readers evaluated image quality and the probability of PCa regarding PI-RADSv2.1 scores in two sessions. The diagnostic performance of the screening protocol with mpMRI serving as the reference standard was derived. Inter- and intra-reader agreements were evaluated using weighted kappa statistics., Results: We included 77 patients with 97 lesions (mean age: 66 years; SD: 7.7). Diagnostic performance of the screening protocol was excellent with a sensitivity and specificity of 100%/100% and 89%/98% (cut-off ≥ PI-RADS 4) for reader 1 (R1) and reader 2 (R2), respectively. Mean image quality was 3.96 (R1) and 4.35 (R2) for the standard protocol vs. 4.74 and 4.57 for the screening protocol (p < 0.05). Inter-reader agreement was moderate (κ: 0.55) for the screening protocol and substantial (κ: 0.61) for the multiparametric protocol., Conclusion: The ultra-fast screening protocol showed similar diagnostic performance and better imaging quality compared to the mpMRI in under 15% of scan time, improving efficacy and enabling the implementation of screening protocols in clinical routine., Clinical Relevance Statement: The ultra-fast protocol enables examinations without contrast administration, drastically reducing scan time to 3.5 min with similar diagnostic performance and better imaging quality. This facilitates patient-friendly, efficient examinations and addresses the conflict of increasing demand for examinations at currently exhausted capacities., Key Points: Time-consuming MRI protocols are in conflict with an expected increase in examinations required for prostate cancer screening. An ultra-fast MRI protocol shows similar performance and better image quality compared to the standard protocol. Deep-learning acceleration facilitates efficient and patient-friendly examinations, thus improving prostate cancer screening capacity., (© 2024. The Author(s).)

First small sample studies indicate that disturbances of spinal morphology may impair craniospinal flow of cerebrospinal fluid and result in neurodegeneration. The aim of this study was to evaluate the association of cervical spinal canal width and scoliosis with grey matter, white matter, ventricular and white matter hyperintensity volumes of the brain in a large study sample. Four hundred participants underwent whole-body 3 T magnetic resonance imaging. Grey matter, white matter and ventricular volumes were quantified using a warp-based automated brain volumetric approach. Spinal canal diameters were measured manually at the cervical vertebrae 2/3 level. Scoliosis was evaluated using manual measurements of the Cobb angle. Linear binomial regression analyses of measures of brain volumes and spine anatomy were performed while adjusting for age, sex, hypertension, cholesterol levels, body mass index, smoking and alcohol consumption. Three hundred eighty-three participants were included [57% male; age: 56.3 (±9.2) years]. After adjustment, smaller spinal canal width at the cervical vertebrae 2/3 level was associated with lower grey matter ( P = 0.034), lower white matter ( P = 0.012) and higher ventricular ( P = 0.006, inverse association) volume. Participants with scoliosis had lower grey matter ( P = 0.005), lower white matter ( P = 0.011) and larger brain ventricular ( P = 0.003) volumes than participants without scoliosis. However, these associations were attenuated after adjustment. Spinal canal width at the cervical vertebrae 2/3 level and scoliosis were not associated with white matter hyperintensity volume before and after adjustment ( P > 0.864). In our study, cohort smaller spinal canal width at the cervical vertebrae 2/3 level and scoliosis were associated with lower grey and white matter volumes and larger ventricle size. These characteristics of the spine might constitute independent risk factors for neurodegeneration., Competing Interests: The authors report no competing interests. The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Long-term exposure to traffic-related air pollution (TRAP) is associated with cardiometabolic disease; however, its role in subclinical stages of disease development is unclear. Thus, we aimed to explore this association in a cross-sectional analysis, with cardiometabolic phenotypes derived from magnetic resonance imaging (MRI). Phenotypes of the left (LV) and right cardiac ventricle, whole-body adipose tissue (AT), and organ-specific AT were obtained by MRI in 400 participants of the KORA cohort. Land-use regression models were used to estimate residential long-term exposures to TRAP, e.g., nitrogen dioxides (NO 2 ) or particle number concentration (PNC). Associations between TRAP and MRI phenotypes were modeled using linear regression. Participants' mean age was 56 ± 9 years, and 42% were female. Long-term exposure to TRAP was associated with decreased LV wall thickness; a 6.0 μg/m 3 increase in NO 2 was associated with a -1.9% [95% confidence interval: -3.7%; -0.1%] decrease in mean global LV wall thickness. Furthermore, we found associations between TRAP and increased cardiac AT. A 2,242 n/cm 3 increase in PNC was associated with a 4.3% [-1.7%; 10.4%] increase in mean total cardiac AT. Associations were more pronounced in women and in participants with diabetes. Our exploratory study indicates that long-term exposure to TRAP is associated with subclinical cardiometabolic disease states, particularly in metabolically vulnerable subgroups.

Background: There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with the progression of insulin resistance. With advances in artificial intelligence, automated and accurate algorithms have become feasible to fill this gap., Methods: In this retrospective study, we developed and tested a fully automated deep learning model using data from two prospective cohort studies (German National Cohort [NAKO] and Cooperative Health Research in the Region of Augsburg [KORA]) to quantify myosteatosis on whole-body T1-weighted Dixon magnetic resonance imaging as (1) intramuscular adipose tissue (IMAT; the current standard) and (2) quantitative skeletal muscle (SM) fat fraction (SMFF). Subsequently, we investigated the two measures for their discrimination of and association with impaired glucose metabolism beyond baseline demographics (age, sex and body mass index [BMI]) and cardiometabolic risk factors (lipid panel, systolic blood pressure, smoking status and alcohol consumption) in asymptomatic individuals from the KORA study. Impaired glucose metabolism was defined as impaired fasting glucose or impaired glucose tolerance (140-200 mg/dL) or prevalent diabetes mellitus., Results: Model performance was high, with Dice coefficients of ≥0.81 for IMAT and ≥0.91 for SM in the internal (NAKO) and external (KORA) testing sets. In the target population (380 KORA participants: mean age of 53.6 ± 9.2 years, BMI of 28.2 ± 4.9 kg/m 2 , 57.4% male), individuals with impaired glucose metabolism (n = 146; 38.4%) were older and more likely men and showed a higher cardiometabolic risk profile, higher IMAT (4.5 ± 2.2% vs. 3.9 ± 1.7%) and higher SMFF (22.0 ± 4.7% vs. 18.9 ± 3.9%) compared to normoglycaemic controls (all P ≤ 0.005). SMFF showed better discrimination for impaired glucose metabolism than IMAT (area under the receiver operating characteristic curve [AUC] 0.693 vs. 0.582, 95% confidence interval [CI] [0.06-0.16]; P < 0.001) but was not significantly different from BMI (AUC 0.733 vs. 0.693, 95% CI [-0.09 to 0.01]; P = 0.15). In univariable logistic regression, IMAT (odds ratio [OR] = 1.18, 95% CI [1.06-1.32]; P = 0.004) and SMFF (OR = 1.19, 95% CI [1.13-1.26]; P < 0.001) were associated with a higher risk of impaired glucose metabolism. This signal remained robust after multivariable adjustment for baseline demographics and cardiometabolic risk factors for SMFF (OR = 1.10, 95% CI [1.01-1.19]; P = 0.028) but not for IMAT (OR = 1.14, 95% CI [0.97-1.33]; P = 0.11)., Conclusions: Quantitative SMFF, but not IMAT, is an independent predictor of impaired glucose metabolism, and discrimination is not significantly different from BMI, making it a promising alternative for the currently established approach. Automated methods such as the proposed model may provide a feasible option for opportunistic screening of myosteatosis and, thus, a low-cost personalized risk assessment solution., (© 2024 The Author(s). Journal of Cachexia, Sarcopenia and Muscle published by Wiley Periodicals LLC.)

Background: Artificial intelligence (AI) is increasingly finding its way into routine radiological work., Objective: Presentation of the current advances and applications of AI along the entire radiological patient journey., Methods: Systematic literature review of established AI techniques and current research projects, with reference to consensus recommendations., Results: The applications of AI in radiology cover a wide range, starting with AI-supported scheduling and indications assessment, extending to AI-enhanced image acquisition and reconstruction techniques that have the potential to reduce radiation doses in computed tomography (CT) or acquisition times in magnetic resonance imaging (MRI), while maintaining comparable image quality. These include computer-aided detection and diagnosis, such as fracture recognition or nodule detection. Additionally, methods such as worklist prioritization and structured reporting facilitated by large language models enable a rethinking of the reporting process. The use of AI promises to increase the efficiency of all steps of the radiology workflow and an improved diagnostic accuracy. To achieve this, seamless integration into technical workflows and proven evidence of AI systems are necessary., Conclusion: Applications of AI have the potential to profoundly influence the role of radiologists in the future., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Left atrial (LA) physiology and hemodynamics are intimately connected to cardiac and lung function in health and disease. This study examined the relationship between MRI-based left atrial (LA) size and function with MRI-based lung volume and pulmonary function testing (PFT) parameters in the population-based KORA study cohort of 400 participants without overt cardiovascular disease. MRI quantification assessed LA size/function in sequences with and without ECG synchronization, alongside lung volume. Regression analysis explored the relationship of LA with MRI lung volume and PFT parameters. Among 378 participants (average age 56.3 ± 9.2 years; 42.3% women), non-gated LA size averaged 16.8 cm 2 , while maximal and minimal LA size from gated measurements were 19.6 cm 2 and 11.9 cm 2 respectively. The average MRI-derived lung volume was 4.0 L, with PFT showing a total lung capacity of 6.2 L, residual lung volume of 2.1 L, and forced vital capacity of 4.1 L. Multivariate regression analysis, adjusted for age, gender, and cardiovascular risk factors, revealed an inverse association between maximum LA size, non-gated LA, and LA area fraction with lung volume (ß = - 0.03, p = 0.006; ß = - 0.03, p = 0.021; ß = - 0.01, p = 0.012), with no significant association with PFT parameters. This suggests that MRI-based assessment may offer greater sensitivity in detecting subclinical LA impairment than PFT., (© 2024. The Author(s).)

Purpose: To assess the image quality and impact on acquisition time of a novel deep learning based T2 Dixon sequence (T2 DL ) of the spine., Methods: This prospective, single center study included n = 44 consecutive patients with a clinical indication for lumbar MRI at our university radiology department between September 2022 and March 2023. MRI examinations were performed on 1.5-T and 3-T scanners (MAGNETOM Aera and Vida; Siemens Healthineers, Erlangen, Germany) using dedicated spine coils. The MR study protocol consisted of our standard clinical protocol, including a T2 weighted standard Dixon sequence (T2 std ) and an additional T2 DL acquisition. The latter used a conventional sampling pattern with a higher parallel acceleration factor. The individual contrasts acquired for Dixon water-fat separation were then reconstructed using a dedicated research application. After reconstruction of the contrast images from k-space data, a conventional water-fat separation was performed to provide derived water images. Two readers with 6 and 4 years of experience in interpreting MSK imaging, respectively, analyzed the images in a randomized fashion. Regarding overall image quality, banding artifacts, artifacts, sharpness, noise, and diagnostic confidence were analyzed using a 5-point Likert scale (from 1 = non-diagnostic to 5 = excellent image quality). Statistical analyses included the Wilcoxon signed-rank test and weighted Cohen's kappa statistics., Results: Forty-four patients (mean age 53 years (±18), male sex: 39 %) were prospectively included. Thirty-one examinations were performed on 1.5 T and 13 examinations on 3 T scanners. A sequence was successfully acquired in all patients. The total acquisition time of T2 DL was 93 s at 1.5-T and 86 s at 3-T, compared to 235 s, and 257 s, respectively for T2 std (reduction of acquisition time: 60.4 % at 1.5-T, and 66.5 % at 3-T; p < 0.01). Overall image quality was rated equal for both sequences (median T2 DL : 5[3 -5], and median T2 std : 5 [2 -5]; p = 0.57). T2 DL showed significantly reduced noise levels compared to T2 std (5 [4 -5] versus 4 [3 -4]; p < 0.001). In addition, sharpness was rated to be significantly higher in T2 DL (5 [4 -5] versus 4 [3 -5]; p < 0.001). Although T2 DL displayed significantly more banding artifacts (5 [2 -5] versus 5 [4 -5]; p < 0.001), no significant impact on readers diagnostic confidence between sequences was noted (T2 std : 5 [2 -5], and T2 DL : 5 [3 -5]; p = 0.61). Substantial inter-reader and intrareader agreement was observed for T2 DL overall image quality (κ: 0.77, and κ: 0.8, respectively)., Conclusion: T2 DL is feasible, yields an image quality comparable to the reference standard while substantially reducing the acquisition time., 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 © 2024. Published by Elsevier B.V.)

Purpose: CT perfusion (CTP) is a valuable tool in suspected acute ischemic stroke. A substantial variability of the delay between contrast injection and bolus arrival in the brain is conceivable. We investigated the distribution of the peak positions of the concentration time curves measured in an artery (arterial input function, AIF) and - in cases with ischemia - also measured in the penumbra., Methods: We report on 2624 perfusion scans (52 % female, mean age 72.2 ± 14.4 years) with stroke present in 1636 cases. From the attenuation time curves of the AIF and the penumbra, we calculated the respective bolus peak positions and investigated the distribution of the peak positions. Further, we analyzed the bolus peak positions for associations with age., Results: The bolus peaked significantly later in older patients, both in the AIF and in the penumbra (all p < 0.001). In the whole cohort, we found a significant association of age with the bolus peak position of the AIF (ρ = 0.334; p < 0.001). In patients with stroke, age was also associated to the peak position of the AIF (ρ = 0.305; p < 0.001), and the penumbra (ρ = 0.246, p < 0.001). However, a substantial range of peak positions of the AIF and penumbra was noted across all age ranges., Conclusions: This study revealed a strong age-dependency of the contrast bolus arrival in both healthy and ischemic tissue. This variability makes non-uniform sampling schemes, which have been suggested to reduce radiation dose, problematic, as they might not always optimally capture the bolus in all cases., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: EK is a shareholder of and receives fees from VEObrain GmbH, Freiburg, Germany. HU is co-editor of Clinical Neuroradiology, member of the Advisory Board of Biogen and received honoraria for lectures from Biogen, Eisai, and mbits. AR received grants from Berta-Ottenstein-Programme for Clinician Scientists, Faculty of Medicine, University of Freiburg., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background Prostate MRI for the detection of clinically significant prostate cancer (csPCa) is standardized by the Prostate Imaging Reporting and Data System (PI-RADS), currently in version 2.1. A systematic review and meta-analysis infrastructure with a 12-month update cycle was established to evaluate the diagnostic performance of PI-RADS over time. Purpose To provide estimates of diagnostic accuracy and cancer detection rates (CDRs) of PI-RADS version 2.1 categories for prostate MRI, which is required for further evidence-based patient management. Materials and Methods A systematic search of PubMed, Embase, Cochrane Library, and multiple trial registers (English-language studies published from March 1, 2019, to August 30, 2022) was performed. Studies that reported data on diagnostic accuracy or CDRs of PI-RADS version 2.1 with csPCa as the primary outcome were included. For the meta-analysis, pooled estimates for sensitivity, specificity, and CDRs were derived from extracted data at the lesion level and patient level. Sensitivity and specificity for PI-RADS greater than or equal to 3 and PI-RADS greater than or equal to 4 considered as test positive were investigated. In addition to individual PI-RADS categories 1-5, subgroup analyses of subcategories (ie, 2+1, 3+0) were performed. Results A total of 70 studies (11 686 lesions, 13 330 patients) were included. At the patient level, with PI-RADS greater than or equal to 3 considered positive, meta-analysis found a 96% summary sensitivity (95% CI: 95, 98) and 43% specificity (95% CI: 33, 54), with an area under the summary receiver operating characteristic (SROC) curve of 0.86 (95% CI: 0.75, 0.93). For PI-RADS greater than or equal to 4, meta-analysis found an 89% sensitivity (95% CI: 85, 92) and 66% specificity (95% CI: 58, 74), with an area under the SROC curve of 0.89 (95% CI: 0.85, 0.92). CDRs were as follows: PI-RADS 1, 6%; PI-RADS 2, 5%; PI-RADS 3, 19%; PI-RADS 4, 54%; and PI-RADS 5, 84%. The CDR was 12% (95% CI: 7, 19) for transition zone 2+1 lesions and 19% (95% CI: 12, 29) for 3+0 lesions ( P = .12). Conclusion Estimates of diagnostic accuracy and CDRs for PI-RADS version 2.1 categories are provided for quality benchmarking and to guide further evidence-based patient management. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Tammisetti and Jacobs in this issue.

Background CT-derived fractional flow reserve (CT-FFR) and dynamic CT myocardial perfusion imaging enhance the specificity of coronary CT angiography (CCTA) for ruling out coronary artery disease (CAD). However, evidence on comparative diagnostic value remains scarce. Purpose To compare the diagnostic accuracy of CCTA plus CT-FFR, CCTA plus CT perfusion, and sequential CCTA plus CT-FFR and CT perfusion for detecting hemodynamically relevant CAD with that of invasive angiography. Materials and Methods This secondary analysis of a prospective study included patients with chest pain referred for invasive coronary angiography at nine centers from July 2016 to September 2019. CCTA and CT perfusion were performed with third-generation dual-source CT scanners. CT-FFR was assessed on-site. Independent core laboratories analyzed CCTA alone, CCTA plus CT perfusion, CCTA plus CT-FFR, and a sequential approach involving CCTA plus CT-FFR and CT perfusion for the presence of hemodynamically relevant stenosis. Invasive coronary angiography with invasive fractional flow reserve was the reference standard. Diagnostic accuracy metrics and the area under the receiver operating characteristic curve (AUC) were compared with the Sign test and DeLong test. Results Of the 105 participants (mean age, 64 years ± 8 [SD]; 68 male), 49 (47%) had hemodynamically relevant stenoses at invasive coronary angiography. CCTA plus CT-FFR and CCTA plus CT perfusion showed no evidence of a difference for participant-based sensitivities (90% vs 90%, P > .99), specificities (77% vs 79%, P > .99) and vessel-based AUCs (0.84 [95% CI: 0.77, 0.91] vs 0.83 [95% CI: 0.75, 0.91], P = .90). Both had higher participant-based specificity than CCTA alone (54%, both P < .001) without evidence of a difference in sensitivity between CCTA (94%) and CCTA plus CT perfusion ( P = .50) or CCTA plus CT-FFR ( P = .63). The sequential approach combining CCTA plus CT-FFR with CT perfusion achieved higher participant-based specificity than CCTA plus CT-FFR (88% vs 77%, P = .03) without evidence of a difference in participant-based sensitivity (88% vs 90%, P > .99) and vessel-based AUC (0.85 [95% CI: 0.77, 0.93], P = .78). Compared with CCTA plus CT perfusion, the sequential approach showed no evidence of a difference in participant-based sensitivity ( P > .99), specificity ( P = .06), or vessel-based AUC ( P = .54). Conclusion There was no evidence of a difference in diagnostic accuracy between CCTA plus CT-FFR and CCTA plus CT perfusion for detecting hemodynamically relevant CAD. A sequential approach combining CCTA plus CT-FFR with CT perfusion led to improved participant-based specificity with no evidence of a difference in sensitivity compared with CCTA plus CT-FFR. ClinicalTrials.gov registration no.: NCT02810795 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Sinitsyn in this issue.

Background: To evaluate T1ρ relaxation mapping in patients with symptomatic talar osteochondral lesions (OLT) and healthy controls (HC) at rest, with axial loading and traction., Methods: Participants underwent 3-T ankle magnetic resonance imaging at rest and with 500 N loading and 120 N traction, without axial traction for a subcohort of 17/29 HC. We used a fast low-angle shot sequence with variable spin-lock intervals for monoexponential T1ρ fitting. Cartilage was manually segmented to extract T1ρ values., Results: We studied 29 OLT patients (age 31.7 ± 7.5 years, 15 females, body mass index [BMI] 25.0 ± 3.4 kg/m 2 ) and 29 HC (age 25.2 ± 4.3 years, 17 females, BMI 22.5 ± 2.3 kg/m 2 . T1ρ values of OLT (50.4 ± 3.4 ms) were higher than those of intact cartilage regions of OLT patients (47.2 ± 3.4 ms; p = 0.003) and matched HC cartilage (48.1 ± 3.3 ms; p = 0.030). Axial loading and traction induced significant T1ρ changes in the intact cartilage regions of patients (loading, mean difference -1.1 ms; traction, mean difference 1.4 ms; p = 0.030 for both) and matched HC cartilage (-2.2 ms, p = 0.003; 2.3 ms, p = 0.030; respectively), but not in the OLT itself (-1.3 ms; p = 0.150; +1.9 ms; p = 0.150; respectively)., Conclusion: Increased T1ρ values may serve as a biomarker of cartilage degeneration in OLT. The absence of load- and traction-induced T1ρ changes in OLT compared to intact cartilage suggests that T1ρ may reflect altered biomechanical properties of hyaline cartilage., Trial Registration: DRKS, DRKS00024010. Registered 11 January 2021, https://drks.de/search/de/trial/DRKS00024010 ., Relevance Statement: T1ρ mapping has the potential to evaluate compositional and biomechanical properties of the talar cartilage and may improve therapeutic decision-making in patients with osteochondral lesions., Key Points: T1ρ values in osteochondral lesions increased compared to intact cartilage. Significant load- and traction-induced T1ρ changes were observed in visually intact regions and in healthy controls but not in osteochondral lesions. T1ρ may serve as an imaging biomarker for biomechanical properties of cartilage., (© 2024. The Author(s).)

Background: Obesity is associated with alterations in the hypothalamic-pituitary-adrenal (HPA) axis. Effects of glucocorticoids on adipose tissues appear to depend on the specific adipose depot, in which they take place. In this study, we aimed to investigate the role of MRI-based adrenal gland volume as an imaging marker in association with different adipose tissue compartments., Methods: The study cohort derives from the population-based research platform KORA (Cooperative Health Research in the Augsburg Region, Germany) MRI sub-study, a cross-sectional sub-study investigating the interactions between subclinical metabolic changes and cardiovascular disease in a study sample of 400 participants. Originally, eligible subjects underwent a whole-body MRI. MRI-based segmentations were performed manually and semi-automatically for adrenal gland volume, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), epi- and pericardial fat and renal sinus fat. Hepatic and pancreatic lipid content were measured as pancreatic proton density fraction (PDFF) and MR-spectroscopic hepatic fat fraction (HFF). Multivariable linear regression analyses were performed., Results: A number of 307 participants (56.2 ± 9.1 years, 60.3% male, 14.3% with type 2 diabetes (T2DM), 30.6% with obesity, 34.2% with hypertension) were included. In multivariable analyses, strong positive associations between adrenal gland volume and VAT, total adipose tissue (TAT) as well as HFF persisted after extensive step-wise adjustment for possible metabolic confounders (VAT: beta = 0.31, 95%-CI [0.71, 0.81], p < 0.001; TAT: beta = 0.14, 95%-CI [0.06, 0.23], p < 0.001; HFF: beta = 1.17, 95%-CI [1.04, 1.31], p = 0.009). In contrast, associations between adrenal gland volume and SAT were attenuated in multivariate analysis after adjusting for BMI. Associations between pancreatic PDFF, epi- and pericardial fat and renal sinus fat were mediated to a great extent by VAT (pancreatic PDFF: 72%, epicardial adipose tissue: 100%, pericardial adipose tissue: 100%, renal sinus fat: 81.5%)., Conclusion: Our results found MRI-based adrenal gland volume as a possible imaging biomarker of unfavorable adipose tissue distribution, irrespective of metabolic risk factors. Thus, adrenal gland volume may serve as a potential MRI-based biomarker of metabolic changes and contributes to an individual characterization of metabolic states and individual risk stratification. Future studies should elucidate in a longitudinal study design, if and how HPA axis activation may trigger unfavorable adipose tissue distribution and whether and to which extent this is involved in the pathogenesis of manifest metabolic syndrome., (© 2024. The Author(s).)

Objective: Accurate locoregional staging is crucial for effective breast cancer treatment. Photon-counting computed tomography (PC-CT) is an emerging technology with high spatial resolution and the ability to depict uptake of contrast agents in tissues, making it a promising tool for breast cancer imaging. The aim of this study was to establish the feasibility of locoregional staging of breast cancer through contrast-enhanced thoracic PC-CT, assess its diagnostic performance, and compare it with that of digital mammography (DM)., Materials and Methods: Patients with newly diagnosed breast cancer, DM, and indication of thoracic CT staging were prospectively enrolled in this clinical cohort study over a period of 6 months. Participants underwent contrast-enhanced thoracic PC-CT and breast magnetic resonance imaging in prone position. After blinding to patient data, 2 radiologists independently rated PC-CT and DM regarding the following 6 characteristics: (1) diameter of the largest mass lesion, (2) infiltration of cutis/pectoral muscle/thoracic wall, (3) number of mass lesions, (4) presence/absence of adjacent ductal carcinoma in situ (DCIS), (5) tumor conspicuity, and (6) diagnostic confidence. Reference standard was generated from consensus reading of magnetic resonance imaging combined with all histopathological/clinical data by an independent adjudication committee applying TNM eighth edition., Results: Among 32 enrolled female subjects (mean ± SD age, 59 ± 13.0 years), diagnostic accuracy for T-classification was higher for PC-CT compared with DM (0.94 vs 0.50, P < 0.01). Moreover, the correlation of the number of detected tumor masses with the reference standard was stronger for PC-CT than for DM (0.72 vs 0.50, P < 0.01). We observed that PC-CT significantly ( P < 0.04) outperformed DM regarding not only sensitivity (0.83 and 0.25, respectively) but also specificity (0.99 and 0.80, respectively) for adjacent DCIS. The κ values for interreader reliability were higher for PC-CT compared with DM (mean 0.88 vs 0.54, respectively; P = 0.01)., Conclusions: Photon-counting computed tomography outperformed DM in T-classification and provided higher diagnostic accuracy for the detection of adjacent DCIS. Therefore, opportunistic locoregional staging of breast cancer in contrast-enhanced thoracic PC-CT is feasible and could overcome limitations of DM with the potential to improve patient management., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Objectives: To determine the diagnostic accuracy of ultra-high-resolution photon-counting detector CT angiography (UHR PCD-CTA) for evaluating coronary stent patency compared to invasive coronary angiography (ICA)., Methods: Consecutive, clinically referred patients with prior coronary stent implantation were prospectively enrolled between August 2022 and March 2023 and underwent UHR PCD-CTA (collimation, 120 × 0.2 mm). Two radiologists independently analyzed image quality of the in-stent lumen using a 5-point Likert scale, ranging from 1 ("excellent") to 5 ("non-diagnostic"), and assessed all coronary stents for the presence of in-stent stenosis (≥ 50% lumen narrowing). The diagnostic accuracy of UHR PCD-CTA was determined, with ICA serving as the standard of reference., Results: A total of 44 coronary stents in 18 participants (mean age, 83 years ± 6 [standard deviation]; 12 women) were included in the analysis. In 3/44 stents, both readers described image quality as non-diagnostic, whereas reader 2 noted a fourth stent to have non-diagnostic image quality. In comparison to ICA, UHR PCD-CTA demonstrated a sensitivity, specificity, and accuracy of 100% (95% CI [confidence interval] 47.8, 100), 92.3% (95% CI 79.1, 98.4), and 93.2% (95% CI 81.3, 98.6) for reader 1 and 100% (95% CI 47.8, 100), 87.2% (95% CI 72.6, 95.7), and 88.6% (95% CI 75.4, 96.2) for reader 2, respectively. Both readers observed a 100% negative predictive value (36/36 stents and 34/34 stents). Stent patency inter-reader agreement was 90.1%, corresponding to a substantial Cohen's kappa value of 0.72., Conclusions: UHR PCD-CTA enables non-invasive assessment of coronary stent patency with high image quality and diagnostic accuracy., Clinical Relevance Statement: Ultra-high-resolution photon-counting detector CT angiography represents a reliable and non-invasive method for assessing coronary stent patency. Its high negative predictive value makes it a promising alternative over invasive coronary angiography for the rule-out of in-stent stenosis., Key Points: • CT-based evaluation of coronary stent patency is limited by stent-induced artifacts and spatial resolution. • Ultra-high-resolution photon-counting detector CT accurately evaluates coronary stent patency compared to invasive coronary angiography. • Photon-counting detector CT represents a promising method for the non-invasive rule-out of in-stent stenosis., (© 2024. The Author(s).)

Objective: To qualitatively and quantitatively evaluate the 2.5-year MRI outcome after Matrix-associated autologous chondrocyte implantation (MACI) at the patella, reconstruction of the medial patellofemoral ligament (MPFL), and combined procedures., Methods: In 66 consecutive patients (age 22.8 ± 6.4years) with MACI at the patella (n = 16), MPFL reconstruction (MPFL; n = 31), or combined procedures (n = 19) 3T MRI was performed 2.5 years after surgery. For morphological MRI evaluation WORMS and MOCART scores were obtained. In addition quantitative cartilage T2 and T1rho relaxation times were acquired. Several clinical scores were obtained. Statistical analyses included descriptive statistics, Mann-Whitney-U-tests and Pearson correlations., Results: WORMS scores at follow-up (FU) were significantly worse after combined procedures (8.7 ± 4.9) than after isolated MACI (4.3 ± 3.6, P = 0.005) and after isolated MPFL reconstruction (5.3 ± 5.7, P = 0.004). Bone marrow edema at the patella in the combined group was the only (non-significantly) worsening WORMS parameter from pre- to postoperatively. MOCART scores were significantly worse in the combined group than in the isolated MACI group (57 ± 3 vs 88 ± 9, P < 0.001). Perfect defect filling was achieved in 26% and 69% of cases in the combined and MACI group, respectively (P = 0.031). Global and patellar T2 values were higher in the combined group (Global T2: 34.0 ± 2.8ms) and MACI group (35.5 ± 3.1ms) as compared to the MPFL group (31.1 ± 3.2ms, P < 0.05). T2 values correlated significantly with clinical scores (P < 0.005). Clinical Cincinnati scores were significantly worse in the combined group (P < 0.05)., Conclusion: After combined surgery with patellar MACI and MPFL reconstruction inferior MRI outcomes were observed than after isolated procedures. Therefore, patients with need for combined surgery may be at particular risk for osteoarthritis., (© 2024. The Author(s), under exclusive licence to International Skeletal Society (ISS).)