Broad-Spectrum Supramolecularly Reloadable Antimicrobial Coatings.

Antimicrobial surfaces limit the spread of infectious diseases. To date, there is no antimicrobial coating that has widespread use because of short-lived and limited spectrum efficacy, poor resistance to organic material, and/or cost. Here, we present a paint based on waterborne latex particles that is supramolecularly associated with quaternary ammonium compounds (QACs). The optimal supramolecular pairing was first determined by immobilizing selected ions on self-assembled monolayers exposing different groups. The QAC surface loading density was then increased by using polymer brushes. These concepts were adopted to develop inexpensive paints to be applied on many different surfaces. The paint could be employed for healthcare and food production applications. Its slow release of QAC allows for long-lasting antimicrobial action, even in the presence of organic material. Its efficacy lasts for more than 90 washes, and importantly, once lost, it can readily be restored by spraying an aqueous solution of the QAC. We mainly tested cetyltrimethylammonium as QAC as it is already used in consumer care products. Our antimicrobial paint is broad spectrum as it showed excellent antimicrobial efficiency against four bacteria and four viruses.

Effects of undergraduate ultrasound education on cross-sectional image understanding and visual-spatial ability - a prospective study.

INTRODUCTION/AIM: Radiological imaging is crucial in modern clinical practice and requires thorough and early training. An understanding of cross-sectional imaging is essential for effective interpretation of such imaging. This study examines the extent to which completing an undergraduate ultrasound course has positive effects on the development of visual-spatial ability, knowledge of anatomical spatial relationships, understanding of radiological cross-sectional images, and theoretical ultrasound competencies. MATERIAL AND METHODS: This prospective observational study was conducted at a medical school with 3rd year medical students as part of a voluntary extracurricular ultrasound course. The participants completed evaluations (7-level Likert response formats and dichotomous questions "yes/no") and theoretical tests at two time points (T1 = pre course; T2 = post course) to measure their subjective and objective cross-sectional imaging skills competencies. A questionnaire on baseline values and previous experience identified potential influencing factors. RESULTS: A total of 141 participants were included in the study. Most participants had no previous general knowledge of ultrasound diagnostics (83%), had not yet performed a practical ultrasound examination (87%), and had not attended any courses on sonography (95%). Significant subjective and objective improvements in competencies were observed after the course, particularly in the subjective sub-area of "knowledge of anatomical spatial relationships" (p = 0.009). Similarly, participants showed improvements in the objective sub-areas of "theoretical ultrasound competencies" (p < 0.001), "radiological cross-section understanding and knowledge of anatomical spatial relationships in the abdomen" (p < 0.001), "visual-spatial ability in radiological cross-section images" (p < 0.001), and "visual-spatial ability" (p = 0.020). CONCLUSION: Ultrasound training courses can enhance the development of visual-spatial ability, knowledge of anatomical spatial relationships, radiological cross-sectional image understanding, and theoretical ultrasound competencies. Due to the reciprocal positive effects of the training, students should receive radiology training at an early stage of their studies to benefit as early as possible from the improved skills, particularly in the disciplines of anatomy and radiology.

[Ultrasound supported identification of the ligamentum conicum in teaching head and neck sonography]. / Sonographisch gestützte Identifikation des Ligamentum conicum in der Kopf-Hals-Ultraschalllehre.

OBJECTIVE: Upper airway obstructions are usually acute emergencies. Coniotomy is the last option to secure the airway and can be supported by sonography. The aim of this study was to establish a training program to teach these skills. MATERIAL AND METHODS: The training consisted of theoretical training with an additional video presentation (10 minutes each) and practical training (45 minutes). Evaluations were completed before (T1) and after (T2) the training to measure prior experience and satisfaction with the training as well as subjective and objective competence levels. At T2, a practical test was also completed by n=113 participants. A standardized evaluation form was used to document the results of the practical test. RESULTS: A large proportion of the participants had neither seen a coniotomy (64.6%) nor performed one independently (79.6%). Significant improvement (T1 to T2) was measured with regard to the subjective assessment of competence (p<0.001). The training received positive ratings for all items tested (scale ranges 1-2). During practical tests, the participants achieved an average of 89.2% of the possible points and needed a mean of 101 ±23 seconds to identify the conic ligament. CONCLUSION: Structured training for sonographic identification of the conic ligament leads to significant improvement in the subjective assessment of competence and a high objective competence level in a short period of time. This type of training should be standardized in head and neck ultrasound training in the future.

Structured reporting for efficient epidemiological and in-hospital prevalence analysis of pulmonary embolisms. / Strukturierte Befundung zur effizienten Erhebung von epidemiologischen Daten und Analyse der innerklinischen Prävalenz bei Lungenarterienembolien.

Structured reporting (SR) not only offers advantages regarding report quality but, as an IT-based method, also the opportunity to aggregate and analyze large, highly structured datasets (data mining). In this study, a data mining algorithm was used to calculate epidemiological data and in-hospital prevalence statistics of pulmonary embolism (PE) by analyzing structured CT reports.All structured reports for PE CT scans from the last 5 years (n = 2790) were extracted from the SR database and analyzed. The prevalence of PE was calculated for the entire cohort and stratified by referral type and clinical referrer. Distributions of the manifestation of PEs (central, lobar, segmental, subsegmental, as well as left-sided, right-sided, bilateral) were calculated, and the occurrence of right heart strain was correlated with the manifestation.The prevalence of PE in the entire cohort was 24% (n = 678). The median age of PE patients was 71 years (IQR 58-80), and the sex distribution was 1.2/1 (M/F). Outpatients showed a lower prevalence of 23% compared to patients from regular wards (27%) and intensive care units (30%). Surgically referred patients had a higher prevalence than patients from internal medicine (34% vs. 22%). Patients with central and bilateral PEs had a significantly higher occurrence of right heart strain compared to patients with peripheral and unilateral embolisms.Data mining of structured reports is a simple method for obtaining prevalence statistics, epidemiological data, and the distribution of disease characteristics, as demonstrated by the PE use case. The generated data can be helpful for multiple purposes, such as for internal clinical quality assurance and scientific analyses. To benefit from this, consistent use of SR is required and is therefore recommended. · SR-based data mining allows simple epidemiologic analyses for PE.. · The prevalence of PE differs between outpatients and inpatients.. · Central and bilateral PEs have an increased risk of right heart strain.. · Jorg T, Halfmann MC, Graafen D et al. Structured reporting for efficient epidemiological and in-hospital prevalence analysis of pulmonary embolisms. Fortschr Röntgenstr 2024; DOI 10.1055/a-2301-3349.

Shoulder and Knee Arthroscopy Access Point: Prospective Comparison of Sonographic and Palpatory Detection - Which Method is Better for Novices?

Purpose Arthroscopy is one of the most common interventions in orthopedics. Hence it is important to train users early in order to ensure the safest possible identification of access portals (AP). This prospective study aimed to compare a palpatory (PalpMethod) with a sonographic (SonoMethod) method for AP location in the shoulder and knee joints. Materials and Methods The study included trainee doctors (n=68) attending workshops (lasting approx. 90 minutes). In these workshops a teaching video initially demonstrated the PalpMethod and SonoMethod of AP identification. An experienced operator first marked the access portals on the test subject with a UV pen (determined ideal point [DIP]). Adhesive film was then affixed to the puncture regions. Subsequently participants marked on shoulders and knees first the point determined by palpation, then the point determined by sonography. Analysis involved DIP visualization with a UV lamp and employed a coordinate system around the central DIP. In addition, participants completed an evaluation before and after the workshop. Results The analysis included 324 measurements (n=163 shoulders and n= 161 knees). The majority of participants had not previously attended any courses on manual examination (87.9%) or musculoskeletal ultrasound (93.9%). Overall, the markings participants made on the shoulder using the SonoMethod were significantly closer to the DIP than those made by the PalpMethod (Palp 18.8mm ± 14.5mm vs. Sono 11.2mm ± 7.2mm; p<0.001). On the knee, however, the markings made by the PalpMethod were significantly closer to the DIP overall (Palp 8.0mm ± 3.2mm vs. Sono 12.8mm ± 5.2mm; p<0.001). Conclusion The results show that the SonoMethod produces more accurate markings on the shoulder, while the PalpMethod is superior for the knee.

Value of vendor-agnostic deep learning image denoising in brain computed tomography: A multi-scanner study.

To evaluate the effect of a vendor-agnostic deep learning denoising (DLD) algorithm on diagnostic image quality of non-contrast cranial computed tomography (ncCT) across five CT scanners.This retrospective single-center study included ncCT data of 150 consecutive patients (30 for each of the five scanners) who had undergone routine imaging after minor head trauma. The images were reconstructed using filtered back projection (FBP) and a vendor-agnostic DLD method. Using a 4-point Likert scale, three readers performed a subjective evaluation assessing the following quality criteria: overall diagnostic image quality, image noise, gray matter-white matter differentiation (GM-WM), artifacts, sharpness, and diagnostic confidence. Objective analysis included evaluation of noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and an artifact index for the posterior fossa.In subjective image quality assessment, DLD showed constantly superior results compared to FBP in all categories and for all scanners (p<0.05) across all readers. The objective image quality analysis showed significant improvement in noise, SNR, and CNR as well as for the artifact index using DLD for all scanners (p<0.001).The vendor-agnostic deep learning denoising algorithm provided significantly superior results in the subjective as well as in the objective analysis of ncCT images of patients with minor head trauma concerning all parameters compared to the FBP reconstruction. This effect has been observed in all five included scanners. · Significant improvement of image quality for 5 scanners due to the vendor-agnostic DLD. · Subjects were patients with routine imaging after minor head trauma. · Reduction of artifacts in the posterior fossa due to the DLD. · Access to improved image quality even for older scanners from different vendors. · Kapper C, Müller L, Kronfeld A et al. Value of vendor-agnostic deep learning image denoising in brain computed tomography: A multi-scanner study. Fortschr Röntgenstr 2024; DOI 10.1055/a-2290-4781.

Thoracic skeletal muscle mass predicts mortality in patients with surgery for pleural empyema: A case control study.

BACKGROUND: This study investigated the role of the thoracic skeletal muscle mass as a marker of sarcopenia on postoperative mortality in pleural empyema. METHODS: All consecutive patients (n = 103) undergoing surgery for pleural empyema in a single tertiary referral center between January 2020 and December 2022 were eligible for this study. Thoracic skeletal muscle mass index (TSMI) was determined from preoperative computed tomography scans. The impact of TSMI and other potential risk factors on postoperative in-hospital mortality was retrospectively analyzed. RESULTS: A total of 97 patients were included in this study. The in-hospital mortality rate was 13.4%. In univariable analysis, low values for preoperative TSMI (p = 0.020), low preoperative levels of thrombocytes (p = 0.027) and total serum protein (p = 0.046) and higher preoperative American Society of Anesthesiologists (ASA) category (p = 0.007) were statistically significant risk factors for mortality. In multivariable analysis, only TSMI (p = 0.038, OR 0.933, 95% CI: 0.875-0.996) and low thrombocytes (p = 0.031, OR 0.944, 95% CI: 0.988-0.999) remained independent prognostic factors for mortality. CONCLUSIONS: TSMI was a significant prognostic risk factor for postoperative mortality in patients with pleural empyema. TSMI may be suitable for risk stratification in this disease with high morbidity and mortality, which may have further implications for the selection of the best treatment strategy.

A novel reporting workflow for automated integration of artificial intelligence results into structured radiology reports.

OBJECTIVES: Artificial intelligence (AI) has tremendous potential to help radiologists in daily clinical routine. However, a seamless, standardized, and time-efficient way of integrating AI into the radiology workflow is often lacking. This constrains the full potential of this technology. To address this, we developed a new reporting pipeline that enables automated pre-population of structured reports with results provided by AI tools. METHODS: Findings from a commercially available AI tool for chest X-ray pathology detection were sent to an IHE-MRRT-compliant structured reporting (SR) platform as DICOM SR elements and used to automatically pre-populate a chest X-ray SR template. Pre-populated AI results could be validated, altered, or deleted by radiologists accessing the SR template. We assessed the performance of this newly developed AI to SR pipeline by comparing reporting times and subjective report quality to reports created as free-text and conventional structured reports. RESULTS: Chest X-ray reports with the new pipeline could be created in significantly less time than free-text reports and conventional structured reports (mean reporting times: 66.8 s vs. 85.6 s and 85.8 s, respectively; both p < 0.001). Reports created with the pipeline were rated significantly higher quality on a 5-point Likert scale than free-text reports (p < 0.001). CONCLUSION: The AI to SR pipeline offers a standardized, time-efficient way to integrate AI-generated findings into the reporting workflow as parts of structured reports and has the potential to improve clinical AI integration and further increase synergy between AI and SR in the future. CRITICAL RELEVANCE STATEMENT: With the AI-to-structured reporting pipeline, chest X-ray reports can be created in a standardized, time-efficient, and high-quality manner. The pipeline has the potential to improve AI integration into daily clinical routine, which may facilitate utilization of the benefits of AI to the fullest. KEY POINTS: • A pipeline was developed for automated transfer of AI results into structured reports. • Pipeline chest X-ray reporting is faster than free-text or conventional structured reports. • Report quality was also rated higher for reports created with the pipeline. • The pipeline offers efficient, standardized AI integration into the clinical workflow.

CT-guided High-Dose-Rate Brachytherapy versus Transarterial Chemoembolization in Patients with Unresectable Hepatocellular Carcinoma.

Background CT-guided high-dose-rate (HDR) brachytherapy (hereafter, HDR brachytherapy) has been shown to be safe and effective for patients with unresectable hepatocellular carcinoma (HCC), but studies comparing this therapy with other local-regional therapies are scarce. Purpose To compare patient outcomes of HDR brachytherapy and transarterial chemoembolization (TACE) in patients with unresectable HCC. Materials and Methods This multi-institutional retrospective study included consecutive treatment-naive adult patients with unresectable HCC who underwent either HDR brachytherapy or TACE between January 2010 and December 2022. Overall survival (OS) and progression-free survival (PFS) were compared between patients matched for clinical and tumor characteristics by propensity score matching. Not all patients who underwent TACE had PFS available; thus, a different set of patients was used for PFS and OS analysis for this treatment. Hazard ratios (HRs) were calculated from Kaplan-Meier survival curves. Results After propensity matching, 150 patients who underwent HDR brachytherapy (median age, 71 years [IQR, 63-77 years]; 117 males) and 150 patients who underwent TACE (OS analysis median age, 70 years [IQR, 63-77 years]; 119 male; PFS analysis median age, 68 years [IQR: 63-76 years]; 119 male) were analyzed. Hazard of death was higher in the TACE versus HDR brachytherapy group (HR, 4.04; P < .001). Median estimated PFS was 32.8 months (95% CI: 12.5, 58.7) in the HDR brachytherapy group and 11.6 months (95% CI: 4.9, 22.7) in the TACE group. Hazard of disease progression was higher in the TACE versus HDR brachytherapy group (HR, 2.23; P < .001). Conclusion In selected treatment-naive patients with unresectable HCC, treatment with CT-guided HDR brachytherapy led to improved OS and PFS compared with TACE. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Chapiro in this issue.

Ultrahigh-Spatial-Resolution Photon-counting Detector CT Angiography of Coronary Artery Disease for Stenosis Assessment.

Background Coronary CT angiography is a first-line test in coronary artery disease but is limited by severe calcifications. Photon-counting-detector (PCD) CT improves spatial resolution. Purpose To investigate the effect of improved spatial resolution on coronary stenosis assessment and reclassification. Materials and Methods Coronary stenoses were evaluated prospectively in a vessel phantom (in vitro) containing two stenoses (25%, 50%), and retrospectively in patients (in vivo) who underwent ultrahigh-spatial-resolution cardiac PCD CT (from July 2022 to April 2023). Images were reconstructed at standard resolution (section thickness, 0.6 mm; increment, 0.4 mm; Bv44 kernel), high spatial resolution (section thickness, 0.4 mm; increment, 0.2 mm; Bv44 kernel), and ultrahigh spatial resolution (section thickness, 0.2; increment, 0.1 mm; Bv64 kernel). Percentages of diameter stenosis (DS) were compared between reconstructions. In vitro values were compared with the manufacturer specifications of the phantom and patient results were assessed regarding effects on Coronary Artery Disease Reporting and Data System (CAD-RADS) reclassification. Results The in vivo sample included 114 patients (mean age, 68 years ± 9 [SD]; 71 male patients). In vitro percentage DS measurements were more accurate with increasing spatial resolution for both 25% and 50% stenoses (mean bias for standard resolution, high spatial resolution, and ultrahigh spatial resolution, respectively: 10.1%, 8.0%, and 2.3%; P < .001). In vivo results confirmed decreasing median percentage DS with increasing spatial resolution for calcified stenoses (n = 161) (standard resolution, high spatial resolution, and ultrahigh spatial resolution, respectively: 41.5% [IQR, 27.3%-58.2%], 34.8% [IQR, 23.7%-55.1%], and 26.7% [IQR, 18.6%-44.3%]; P < .001), whereas noncalcified (n = 13) and mixed plaques (n = 19) did not show evidence of a difference (P ≥ .88). Ultrahigh-spatial-resolution reconstructions led to reclassification of 62 of 114 (54.4%) patients to lower CAD-RADS category than that assigned using standard resolution. Conclusion In vivo and in vitro coronary stenosis assessment improved for calcified stenoses by using ultrahigh-spatial-resolution PCD CT reconstructions, leading to lower percentage DS compared with standard resolution and clinically relevant rates of reclassification. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by McCollough in this issue.

Magnetic Removal of Micro- and Nanoplastics from Water-from 100 nm to 100 µm Debris Size.

Clean water is one of the most important resources of the planet but human-made contamination with diverse pollutants increases continuously. Microplastics (<5 mm diameter) which can have severe impacts on the environment, are present worldwide. Degradation processes lead to nanoplastics (<1 µm), which are potentially even more dangerous due to their increased bioavailability. State-of-the-art wastewater treatment plants show a deficit in effectively eliminating micro- and nanoplastics (MNP) from water, particularly in the case of nanoplastics. In this work, the magnetic removal of three different MNP types across three orders of magnitude in size (100 nm-100 µm) is investigated systematically. Superparamagnetic iron oxide nanoparticles (SPIONs) tend to attract oppositely charged MNPs and form aggregates that can be easily collected by a magnet. It shows that especially the smallest fractions (100-300 nm) can be separated in ordinary high numbers (1013  mg-1 SPION) while the highest mass is removed for MNP between 2.5 and 5 µm. The universal trend for all three types of MNP can be fitted with a derived model, which can make predictions for optimizing SPIONs for specific size ranges in the future.

Feature-Tracking Strain Parameters Differ Between Highly Accelerated and Conventional Acquisitions: A Multisoftware Assessment.

BACKGROUND: Cardiac magnetic resonance imaging protocols have been adapted to fit the needs for faster, more efficient acquisitions, resulting in the development of highly accelerated, compressed sensing-based (CS) sequences. The aim of this study was to evaluate intersoftware and interacquisition differences for postprocessing software applied to both CS and conventional cine sequences. MATERIALS AND METHODS: A total of 106 individuals (66 healthy volunteers, 40 patients with dilated cardiomyopathy, 51% female, 38±17 y) underwent cardiac magnetic resonance at 3T with retrospectively gated conventional cine and CS sequences. Postprocessing was performed using 2 commercially available software solutions and 1 research prototype from 3 different developers. The agreement of clinical and feature-tracking strain parameters between software solutions and acquisition types was assessed by Bland-Altmann analyses and intraclass correlation coefficients. Differences between softwares and acquisitions were assessed using Kruskal-Wallis analysis of variances. In addition, receiver operating characteristic curve-derived cutoffs were used to evaluate whether sequence-specific cutoffs influence disease classification. RESULTS: There were significant intersoftware ( P <0.002 for all except LV end-diastolic volume per body surface area) and interacquisition differences ( P <0.02 for all except end-diastolic volume per body surface area from Neosoft, left ventricular mass per body surface area from cvi42 and TrufiStrain and global circumferential strain from Neosoft). However, the intraclass correlation coefficients between acquisitions were strong-to-excellent for all parameters (all ≥0.81). In comparing individual softwares to a pooled mean, Bland-Altmann analyses revealed smaller magnitudes of bias for cine acquisition than for CS acquisition. In addition, the application of conventional cutoffs to CS measurements did not result in the false reclassification of patients. CONCLUSION: Significantly lower magnitudes of strain and volumetric parameters were observed in retrospectively gated CS acquisitions, despite strong-to-excellent agreement amongst software solutions and acquisition types. It remains important to be aware of the acquisition type in the context of follow-up examinations, where different cutoffs might lead to misclassifications.

Pericardial Effusion Predicts Clinical Outcomes in Patients with COVID-19: A Nationwide Multicenter Study.

RATIONALE AND OBJECTIVES: The prognostic role of pericardial effusion (PE) in Covid 19 is unclear. The aim of the present study was to estimate the prognostic role of PE in patients with Covid 19 in a large multicentre setting. MATERIALS AND METHODS: This retrospective study is a part of the German multicenter project RACOON (Radiological Cooperative Network of the Covid 19 pandemic). The acquired sample comprises 1197 patients, 363 (30.3%) women and 834 (69.7%) men. In every case, chest computed tomography was analyzed for PE. Data about 30-day mortality, need for mechanical ventilation and need for intensive care unit (ICU) admission were collected. Data were evaluated by means of descriptive statistics. Group differences were calculated with Mann-Whitney test and Fisher exact test. Uni-and multivariable regression analyses were performed. RESULTS: Overall, 46.4% of the patients were admitted to ICU, mechanical lung ventilation was performed in 26.6% and 30-day mortality was 24%. PE was identified in 159 patients (13.3%). The presence of PE was associated with 30-day mortality: HR= 1.54, CI 95% (1.05; 2.23), p = 0.02 (univariable analysis), and HR= 1.60, CI 95% (1.03; 2.48), p = 0.03 (multivariable analysis). Furthermore, density of PE was associated with the need for intubation (OR=1.02, CI 95% (1.003; 1.05), p = 0.03) and the need for ICU admission (OR=1.03, CI 95% (1.005; 1.05), p = 0.01) in univariable regression analysis. The presence of PE was associated with 30-day mortality in male patients, HR= 1.56, CI 95%(1.01-2.43), p = 0.04 (multivariable analysis). In female patients, none of PE values predicted clinical outcomes. CONCLUSION: The prevalence of PE in Covid 19 is 13.3%. PE is an independent predictor of 30-day mortality in male patients with Covid 19. In female patients, PE plays no predictive role.

A blended learning approach for teaching thoracic radiology to medical students: a proof-of-concept study.

Introduction: The best way to impart knowledge to medical students is still unclear. Therefore, we designed a blended learning course in thoracic radiology including both "traditional" in-class time as well as online learning modules. The aims were (1) to investigate students' attitudes toward this blended learning approach; and (2) to test whether it improved their knowledge about thoracic radiology. Methods: A prospective study was conducted at the local medical center; 156 fourth-year medical students completed this study. Before and after the course, students had to complete (1) questionnaires to investigate their attitudes (7-point Likert scale); and (2) an objective test to assess their knowledge (multiple-choice/free text questions; results as % of correct answers). Results: Regarding (1), the course led to an improvement in all items compared to baseline, exemplary: interest in thoracic radiology (precourse 4.2 vs. 5.4 postcourse) and the fulfillment of students' expressed requirements regarding the teaching content (4.5 precourse vs. 6.2 postcourse). Furthermore, the great majority (88%) of our participants wished for more online learning offerings in the future. Regarding (2), the course led to improved knowledge on the objective test (precourse: 40% vs. postcourse: 63% correct answers). Conclusion: This feasibility study showed the successful design and implementation of a blended learning approach in thoracic radiology. Furthermore, it revealed medical students' positive attitudes toward this approach and showed an increased knowledge in thoracic radiology. Thus, such approaches might be used to enrich the teaching armamentarium in medical education and to further enhance interest and knowledge in thoracic diseases among medical students.

Optimization of the Reconstruction Settings for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lungs.

Photon-counting detector computed tomography (PCD-CT) yields improved spatial resolution. The combined use of PCD-CT and a modern iterative reconstruction method, known as quantum iterative reconstruction (QIR), has the potential to significantly improve the quality of lung CT images. In this study, we aimed to analyze the impacts of different slice thicknesses and QIR levels on low-dose ultra-high-resolution (UHR) PCD-CT imaging of the lungs. Our study included 51 patients with different lung diseases who underwent unenhanced UHR-PCD-CT scans. Images were reconstructed using three different slice thicknesses (0.2, 0.4, and 1.0 mm) and three QIR levels (2-4). Noise levels were determined in all reconstructions. Three raters evaluated the delineation of anatomical structures and conspicuity of various pulmonary pathologies in the images compared to the clinical reference reconstruction (1.0 mm, QIR-3). The highest QIR level (QIR-4) yielded the best image quality. Reducing the slice thickness to 0.4 mm improved the delineation and conspicuity of pathologies. The 0.2 mm reconstructions exhibited lower image quality due to high image noise. In conclusion, the optimal reconstruction protocol for low-dose UHR-PCD-CT of the lungs includes a slice thickness of 0.4 mm, with the highest QIR level. This optimized protocol might improve the diagnostic accuracy and confidence of lung imaging.

Convolutional neural network-based kidney volume estimation from low-dose unenhanced computed tomography scans.

PURPOSE: Kidney volume is important in the management of renal diseases. Unfortunately, the currently available, semi-automated kidney volume determination is time-consuming and prone to errors. Recent advances in its automation are promising but mostly require contrast-enhanced computed tomography (CT) scans. This study aimed at establishing an automated estimation of kidney volume in non-contrast, low-dose CT scans of patients with suspected urolithiasis. METHODS: The kidney segmentation process was automated with 2D Convolutional Neural Network (CNN) models trained on manually segmented 2D transverse images extracted from low-dose, unenhanced CT scans of 210 patients. The models' segmentation accuracy was assessed using Dice Similarity Coefficient (DSC), for the overlap with manually-generated masks on a set of images not used in the training. Next, the models were applied to 22 previously unseen cases to segment kidney regions. The volume of each kidney was calculated from the product of voxel number and their volume in each segmented mask. Kidney volume results were then validated against results semi-automatically obtained by radiologists. RESULTS: The CNN-enabled kidney volume estimation took a mean of 32 s for both kidneys in a CT scan with an average of 1026 slices. The DSC was 0.91 and 0.86 and for left and right kidneys, respectively. Inter-rater variability had consistencies of ICC = 0.89 (right), 0.92 (left), and absolute agreements of ICC = 0.89 (right), 0.93 (left) between the CNN-enabled and semi-automated volume estimations. CONCLUSION: In our work, we demonstrated that CNN-enabled kidney volume estimation is feasible and highly reproducible in low-dose, non-enhanced CT scans. Automatic segmentation can thereby quantitatively enhance radiological reports.

Photon-counting detector CT-based virtual monoenergetic reconstructions: repeatability and reproducibility of radiomics features of an organic phantom and human myocardium.

BACKGROUND: Photon-counting detector computed tomography (PCD-CT) may influence imaging characteristics for various clinical conditions due to higher signal and contrast-to-noise ratio in virtual monoenergetic images (VMI). Radiomics analysis relies on quantification of image characteristics. We evaluated the impact of different VMI reconstructions on radiomic features in in vitro and in vivo PCD-CT datasets. METHODS: An organic phantom consisting of twelve samples (four oranges, four onions, and four apples) was scanned five times. Twenty-three patients who had undergone coronary computed tomography angiography on a first generation PCD-CT system with the same image acquisitions were analyzed. VMIs were reconstructed at 6 keV levels (40, 55, 70, 90, 120, and 190 keV). The phantoms and the patients' left ventricular myocardium (LVM) were segmented for all reconstructions. Ninety-three original radiomic features were extracted. Repeatability and reproducibility were evaluated through intraclass correlations coefficient (ICC) and post hoc paired samples ANOVA t test. RESULTS: There was excellent repeatability for radiomic features in phantom scans (all ICC = 1.00). Among all VMIs, 36/93 radiomic features (38.7%) in apples, 28/93 (30.1%) in oranges, and 33/93 (35.5%) in onions were not significantly different. For LVM, the percentage of stable features was high between VMIs ≥ 90 keV (90 versus 120 keV, 77.4%; 90 versus 190 keV, 83.9%; 120 versus 190 keV, 89.3%), while comparison to lower VMI levels led to fewer reproducible features (40 versus 55 keV, 8.6%). CONCLUSIONS: VMI levels influence the stability of radiomic features in an organic phantom and patients' LVM; stability decreases considerably below 90 keV. RELEVANCE STATEMENT: Spectral reconstructions significantly influence radiomic features in vitro and in vivo, necessitating standardization and careful attention to these reconstruction parameters before clinical implementation. KEY POINTS: • Radiomic features have an excellent repeatability within the same PCD-CT acquisition and reconstruction. • Differences in VMI lead to decreased reproducibility for radiomic features. • VMI ≥ 90 keV increased the reproducibility of the radiomic features.

Digital Transformation in Musculoskeletal Ultrasound: Acceptability of Blended Learning.

BACKGROUND: ultrasound diagnostics have a broad spectrum of applications, including among diseases of the musculoskeletal system. Accordingly, it is important for the users to have a well-founded and up-to-date education in this dynamic examination method. The right balance between online and in-class teaching still needs to be explored in this context. Certifying institutions are currently testing digitally transformed teaching concepts to provide more evidence. METHODS: this study compared two musculoskeletal ultrasound blended learning models. Model A was more traditional, with a focus on in-person teaching, while Model B was more digitally oriented with compulsory webinar. Both used e-learning for preparation. Participants completed evaluations using a seven-point Likert scale, later converted to a 0-1 scale. Digital teaching media (e-learning) were used for preparation in both courses. RESULTS: the analysis included n = 41 evaluations for Model A and n = 30 for Model B. Model B received a better overall assessment (median: 0.73 vs. 0.69, p = 0.05). Model B also excelled in "course preparation" (p = 0.02), "webinar quality" (p = 0.04), and "course concept" (p = 0.04). The "gain of competence" (p = 0.82), "learning materials" (p = 0.30), and "tutor quality" (p = 0.28) showed no significant differences. CONCLUSION: participants favorably assessed blended learning in ultrasound teaching. Certifying institutions should consider accrediting models that combine digital methods (e.g., internet lectures/webinars) and materials (e.g., e-learning) with hands-on ultrasound training. Further research is needed to validate these subjective findings for a stronger evidential basis.

Development and evaluation of a point-of-care ocular ultrasound curriculum for medical students - a proof-of-concept study.

BACKGROUND: Point-of-care Ocular Ultrasound (POCOUS) has gained importance in emergency medicine and intensive care in recent years. This work aimed to establish and evaluate a dedicated ultrasound education program for learning POCOUS-specific skills during medical studies at a university hospital. METHODS: The blended learning-based program (6 teaching units) based on recent scientific publications and recommendations was developed for students in the clinical part of their medical studies. Experts and trainers consisted of physicians from the Ear-Nose-Throat, radiology, ophthalmology and neurology specialties as well as university educational specialists. Lecture notes containing digital video links for preparation was produced as teaching material. In total, 33 students participated in the study. The education program, including the teaching materials, motivation and subjective gain in competency, was evaluated with the aid of a questionnaire (7-point Likert response format). Objective learning success was assessed on the basis of pre- and post-tests. These covered the skill areas: "anatomical basics", "ultrasound basics", "understanding of cross-sectional images", "normal findings" and "pathology recognition". RESULTS: In the objective assessment of image interpretation, the participants improved significantly (p < 0.001) from pre- to post-test with a large effect size (Cohen's d = 1.78, effect size r = 0.66). The evaluations revealed a high level of satisfaction with the course concept, teaching materials and the tutors. In addition, a high level of motivation was recorded in relation to continuing to study "ultrasound diagnostics" and "ophthalmologic diseases". A significant (p < 0.01) positive gain was also achieved in terms of the subjective assessment of competency. This covers areas such as expertise, sonographic anatomy and performing a POCOUS examination as well as recognizing retinal detachment, globe perforation and increased optic nerve sheath diameter. CONCLUSION: The results of this feasibility study show that medical students accept and support a POCOUS-specific education program and are able to develop a higher objective and subjective level of competency. Future transfer to other sites and larger groups of participants seems feasible.

A Sustainable Method for Removal of the Full Range of Liquid and Solid Hydrocarbons from Water Including Up- and Recycling.

Beyond their CO2 emittance when burned as fuels, hydrocarbons (HCs) serve as omnipresent raw materials and commodities. No matter if as liquid oil spills or the endless amounts of plastic roaming the oceans, HCs behave as persistent pollutants with water as main carrier to distribute. Even if their general chemical structure [-(CH2 )n -] is quite simple, the endless range of n leads to contaminations of different appearances and properties. A water remediation method based on superparamagnetic iron oxide nanoparticles (SPIONs) modified with self-assembled monolayers of alkyl phosphonic acid derivatives is presented. These molecules enable the SPIONs to non-covalently bind HCs, independently from the molecular weight, size and morphology. The attractive interaction is mainly based on hydrophobic and Coulomb interaction, which allows recycling of the SPIONs. The superparamagnetic core allows a simple magnetic collection and separation from the water phase which makes it a promising addition to wastewater treatment. Agglomerates of collected plastic "waste" even exhibit superior adsorption properties for crude oil, another hydrocarbon waste which gives these collected wastes a second life. This upcycling approach combined with presented recycling methods enables a complete recycling loop.