Implementing verifiable oncological imaging by quality assurance and optimization (i‑Violin) : Protocol for a European multicenter study.

Background: Advanced imaging techniques play a pivotal role in oncology. A large variety of computed tomography (CT) scanners, scan protocols, and acquisition techniques have led to a wide range in image quality and radiation exposure. This study aims at implementing verifiable oncological imaging by quality assurance and optimization (i-Violin) through harmonizing image quality and radiation dose across Europe.

Is noninvasive hemoglobin measurement suitable for children undergoing preoperative anesthesia consultation?

Preoperative anemia in children is a significant clinical concern requiring precise diagnosis. Although traditional blood sample collection is effective, it poses challenges because of children's aversion and technical difficulties. Therefore, this study explores the suitability of noninvasive hemoglobin measurements in children during preoperative anesthesia consultation.

Estimated Annual Healthcare Costs After Acute Pulmonary Embolism: Results From a Prospective Multicentre Cohort Study.

Objective: Patients surviving acute pulmonary embolism (PE) necessitate long-term treatment and follow-up. However, the chronic economic impact of PE on European healthcare systems remains to be determined.

Methods And Results: We calculated the direct cost of illness during the first year after discharge for the index PE, analyzing data from a multicentre prospective cohort study in Germany.

Structured reporting for efficient epidemiological and in-hospital prevalence analysis of pulmonary embolisms.

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.

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.

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.

[Report template from the German Society of Urology and the German Radiological Society for standardized, structured reporting of native computed tomography scans in the diagnosis of urinary stones].

Standardized structured radiological reporting (SSRB) has been promoted in recent years. The aims of SSRB include that reports be complete, clear, understandable, and stringent. Repetitions or superfluous content should be avoided.

Natural language processing for automatic evaluation of free-text answers - a feasibility study based on the European Diploma in Radiology examination.

Background: Written medical examinations consist of multiple-choice questions and/or free-text answers. The latter require manual evaluation and rating, which is time-consuming and potentially error-prone. We tested whether natural language processing (NLP) can be used to automatically analyze free-text answers to support the review process.

Structured reporting in radiology enables epidemiological analysis through data mining: urolithiasis as a use case.

Purpose: To investigate the epidemiology and distribution of disease characteristics of urolithiasis by data mining structured radiology reports.

Methods: The content of structured radiology reports of 2028 urolithiasis CTs was extracted from the department's structured reporting (SR) platform. The investigated cohort represented the full spectrum of a tertiary care center, including mostly symptomatic outpatients as well as inpatients.

Pediatric computed tomography doses in Germany from 2016 to 2018 based on large-scale data collection.

Purpose: Accumulating evidence from epidemiological studies that pediatric computed tomography (CT) examinations can be associated with a small but non-zero excess risk for developing leukemia or brain tumor highlights the need to optimize doses of pediatric CT procedures. Mandatory dose reference levels (DRL) can support reduction of collective dose from CT imaging. Regular surveys of applied dose-related parameters are instrumental to decide when technological advances and optimized protocol design allow lower doses without sacrificing image quality.

Implementation of structured reporting in clinical routine: a review of 7 years of institutional experience.

Background: To evaluate the implementation process of structured reporting (SR) in a tertiary care institution over a period of 7 years.

Methods: We analysed the content of our image database from January 2016 to December 2022 and compared the numbers of structured reports and free-text reports. For the ten most common SR templates, usage proportions were calculated on a quarterly basis.

Efficient structured reporting in radiology using an intelligent dialogue system based on speech recognition and natural language processing.

Background: Structured reporting (SR) is recommended in radiology, due to its advantages over free-text reporting (FTR). However, SR use is hindered by insufficient integration of speech recognition, which is well accepted among radiologists and commonly used for unstructured FTR. SR templates must be laboriously completed using a mouse and keyboard, which may explain why SR use remains limited in clinical routine, despite its advantages.

Chronic Administration of Δ-Tetrahydrocannabinol Alters Brain Glucose Uptake and Improves Waiting Impulsivity in the Rat.

Δ-Tetrahydrocannabinol (THC) acts as an agonist at cannabinoid receptors. Its chronic intake affects many behaviors, including cognitive processes. The aims of this study in rats are to assess the chronic effects of THC on impulsivity and on regional brain glucose uptake.

[Image interpretation and the radiological report].

Background: The radiological report is the cornerstone of communication between radiologists and referring physicians and patients, respectively. The report is comprised of image interpretation on the one hand and communication of this interpretation on the other hand.

Objectives And Methods: To outline different types of radiological reports (regarding content as well as structure) and their communication.

[Interdisciplinary case discussions].

Background: Interdisciplinary case discussions, especially tumor conferences, represent a large part of the clinical radiologist's daily work. Radiology plays a key role in tumor conferences, since imaging findings have a direct influence on therapy decisions.

Methods And Objectives: This article discusses the requirements for the radiologist in preparing and conducting tumor conferences.

[Validation and implementation of artificial intelligence in radiology : Quo vadis in 2022?].

Background: The hype around artificial intelligence (AI) in radiology continues and the number of approved AI tools is growing steadily. Despite the great potential, integration into clinical routine in radiology remains limited. In addition, the large number of individual applications poses a challenge for clinical routine, as individual applications have to be selected for different questions and organ systems, which increases the complexity and time required.

Interplay of pandemic and seasonal parameters in dental emergency service.

Background: To evaluate the relationship between pandemic events and dental emergency service frequentation. Utilization patterns in the scope of the COVID-19 pandemic were analyzed and considered in regard of seasonal parameters.

Methods: All outpatients seeking treatment in a university hospital's dental emergency service were analyzed in the years 2019, 2019 and 2020 according to demographic data and emergencies were subdivided into "absolute" and "relative".

Influence of cluster-period cells in stepped wedge cluster randomized trials.

Stepped wedge cluster randomized trials (SWCRT) are increasingly used for the evaluation of complex interventions in health services research. They randomly allocate treatments to clusters that switch to intervention under investigation at variable time points without returning to control condition. The resulting unbalanced allocation over time periods and the uncertainty about the underlying correlation structures at cluster-level renders designing and analyzing SWCRTs a challenge.

Dose Reduction and Image Quality in Photon-counting Detector High-resolution Computed Tomography of the Chest: Routine Clinical Data.

Purpose: Photon-counting detector computed tomography (PCD-CT) has the potential to significantly improve CT imaging in many ways including, but not limited to, low-dose high-resolution CT (HRCT) of the lung. The aim of this study was to perform an intrapatient comparison of the radiation dose and image quality of PCD-CT compared with conventional energy-integrating detector CT (EID-CT).

Methods: A total of 32 consecutive patients with available PCD-CT and EID-CT HRCT scans were included in the final analysis.

[Chances and challenges of increasing digitalization of teaching in the discipline anesthesiology from the perspective of students].

Background: The coronavirus pandemic caused a sudden change in medical education worldwide and induced a shift towards digital teaching. Previously, most courses were organized for students in physical presence on campus, while a few institutions already complemented these with blended learning methods, combining digital teaching with clinical presence; however, the use of digital teaching was heterogeneous, ranging from the use of PowerPoint slides to the application of virtual patients and telemedicine.

Objective: This study aimed to identify challenges and opportunities arising from the different tools used in digital teaching, such as recorded lectures or online seminars, and the role of hands-on clinical experience.

Commercial AI solutions in detecting COVID-19 pneumonia in chest CT: not yet ready for clinical implementation?

Objectives: In response to the COVID-19 pandemic, many researchers have developed artificial intelligence (AI) tools to differentiate COVID-19 pneumonia from other conditions in chest CT. However, in many cases, performance has not been clinically validated. The aim of this study was to evaluate the performance of commercial AI solutions in differentiating COVID-19 pneumonia from other lung conditions.

Multimodal Deep Learning for Prognosis Prediction in Renal Cancer.

Background: Clear-cell renal cell carcinoma (ccRCC) is common and associated with substantial mortality. TNM stage and histopathological grading have been the sole determinants of a patient's prognosis for decades and there are few prognostic biomarkers used in clinical routine. Management of ccRCC involves multiple disciplines such as urology, radiology, oncology, and pathology and each of these specialties generates highly complex medical data.