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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. Methods Four commercial AI solutions were evaluated on a dual-center clinical dataset consisting of 500 CT studies; COVID-19 pneumonia was microbiologically proven in 50 of these. Sensitivity, specificity, positive and negative predictive values, and AUC were calculated. In a subgroup analysis, the performance of the AI solutions in differentiating COVID-19 pneumonia from other conditions was evaluated in CT studies with ground-glass opacities (GGOs). Results Sensitivity and specificity ranges were 62–96% and 31–80%, respectively. Negative and positive predictive values ranged between 82–99% and 19–25%, respectively. AUC was in the range 0.54–0.79. In CT studies with GGO, sensitivity remained unchanged. However, specificity was lower, and ranged between 15 and 53%. AUC for studies with GGO was in the range 0.54–0.69. Conclusions This study highlights the variable specificity and low positive predictive value of AI solutions in diagnosing COVID-19 pneumonia in chest CT. However, one solution yielded acceptable values for sensitivity. Thus, with further improvement, commercial AI solutions currently under development have the potential to be integrated as alert tools in clinical routine workflow. Randomized trials are needed to assess the true benefits and also potential harms of the use of AI in image analysis. Key Points • Commercial AI solutions achieved a sensitivity and specificity ranging from 62 to 96% and from 31 to 80%, respectively, in identifying patients suspicious for COVID-19 in a clinical dataset. • Sensitivity remained within the same range, while specificity was even lower in subgroup analysis of CT studies with ground-glass opacities, and interrater agreement between the commercial AI solutions was minimal to nonexistent. • Thus, commercial AI solutions have the potential to be integrated as alert tools for the detection of patients with lung changes suspicious for COVID-19 pneumonia in a clinical routine workflow, if further improvement is made.

Objective With the initiative of the ACR International Economics Committee, a multinational survey was conducted to evaluate radiology residency programs around the world. Methods A 31-question survey was developed. It included: economic issues, program size and length, resident's activities during daytime and call, academic aspects including syllabus and examinations. Data was tabulated using the forementioned thematic framework and was qualitatively analyzed. Results Responses were received from all 17 countries that were invited to participate (France, Netherlands, Israel, UK, Russia, USA, Japan, India, Germany, Canada, Turkey, Croatia, Serbia, Italy, Ireland, Hungary, and Greece). Residency length varied between 2 and 5 years. The certificate of residency completion is provided by a local hospital [4/17 (23%)], University [6/17 (36%)], National Board [6/17 (36%)], and Ministry of Health [1/17 (6%)]. There was variability among the number of residency programs and residents per program ranging from 15 to 300 programs per nation with a 1–700 residents in each one respectively. Salaries varied significantly and ranged from 8000 to 75,000 USD equivalent. Exams are an integral part of training in all surveyed countries. Length of call varied between 5 and 26 h and the number of monthly calls ranged from 3 to 6. The future of radiology was judged as growing in [12/17 (70%)] countries and stagnant in [5/17 (30%)] countries. Discussion Radiology residency programs worldwide have many similarities. The differences are in the structure of the residency programs. Stagnation and uncertainties need to be addressed to ensure the continued development of the next generation of radiologists. Summary statement There are many similarities in the academic aims and approach to education and training of radiology residency programs worldwide. The differences are in the structure of the residency programs and payments to individual residents.

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).A total of 32 consecutive patients with available PCD-CT and EID-CT HRCT scans were included in the final analysis. The CT dose index (CTDI vol ) was extracted from patient dose reports. Qualitative image analysis comprised the lung parenchyma and mediastinal structures and was assessed by 3 readers using a 5-point Likert scale. Quantitative image analysis included assessment of noise and signal-to-noise ratio in the lung parenchyma, trachea, aorta, muscle, and background.The mean CTDI vol was 2.0 times higher in the conventional EID-CT scans (1.8±0.5 mGy) compared with PCD-CT (0.9±0.5 mGy, P0.001). The overall image quality was rated significantly better by all 3 raters ( P0.001) in the PCD-CT relative to the EID-CT. Quantitative analysis showed no significant differences in noise and signal-to-noise ratio in the lung parenchyma between PCD-CT and EID-CT.Compared with conventional EID-CT scans, PCD-CT demonstrated similar or better objective and subjective image quality at significantly reduced dose levels in an intrapatient comparison. These results and their effect on clinical decision-making should be further investigated in prospective studies.

Abstract The European Directive 2013/59/Euratom requires member states of the European Union to ensure justification and optimisation of radiological procedures and store information on patient exposure for analysis and quality assurance. The EuroSafe Imaging campaign of the European Society of Radiology created a working group (WG) on “Dose Management” with the aim to provide European recommendations on the implementation of dose management systems (DMS) in clinical practice. The WG follows Action 4: “Promote dose management systems to establish local, national, and European diagnostic reference levels (DRL)” of the EuroSafe Imaging Call for Action 2018. DMS are designed for medical practitioners, radiographers, medical physics experts (MPE) and other health professionals involved in imaging to support their tasks and duties of radiation protection in accordance with local and national requirements. The WG analysed requirements and critical points when installing a DMS and classified the individual functions at different performance levels. Key Points • DMS are very helpful software tools for monitoring patient exposure, optimisation, compliance with DRLs and quality assurance. • DMS can help to fulfil dosimetric aspects of the European Directive 2013/59/Euratom. • The EuroSafe WG analyses DMS requirements and gives recommendations for users.

PURPOSE: We aimed to evaluate the influence of irreversible image compression at varying levels on image post-processing algorithms (3D volume rendering of angiographs, computer-assisted detection of lung nodules, segmentation and volumetry of liver lesions, and automated evaluation of functional cardiac imaging) in computed tomography (CT). METHODS: Uncompressed CT image data (30 angiographs of the lower limbs, 38 lung exams, 20 liver exams and 30 cardiac exams) were anonymized and subsequently compressed using the JPEG2000 algorithm with compression ratios of 8:1, 10:1, and 15:1. Volume renderings of CT angiographies obtained from compressed and uncompressed data were compared using objective and subjective measures. Computer-assisted detection of lung nodules was performed on compressed and uncompressed image data and compared with respect to diagnostic performance. Segmentation and volumetry of liver lesions as well as measurement of ejection fraction on cardiac studies was performed on compressed and uncompressed datasets; differences in measurements were analyzed. RESULTS: No differences could be detected for the 3D volume renderings and no statistically significant differences in performance were found for the computer-assisted detection algorithm. Measurements in volumetry of liver lesions and functional cardiac imaging showed good to excellent reliability. CONCLUSION: Irreversible image compression within the limits proposed by the European Society of Radiology has no significant influence on commonly used image post-processing algorithms in CT.

Purpose: The aim of this study was to determine the status of radiology quality improvement programs in a variety of selected nations worldwide. Methods: A survey was developed by select members of the International Economics Committee of the American College of Radiology on quality programs and was distributed to committee members. Members responded on behalf of their country. The 51-question survey asked about 12 different quality initiatives which were grouped into 4 themes: departments, users, equipment, and outcomes. Respondents reported whether a designated type of quality initiative was used in their country and answered subsequent questions further characterizing it. Results: The response rate was 100% and represented Australia, Canada, China, England, France, Germany, India, Israel, Japan, the Netherlands, Russia, and the United States. The most frequently reported quality initiatives were imaging appropriateness (91.7%) and disease registries (91.7%), followed by key performance indicators (83.3%) and morbidity and mortality rounds (83.3%). Peer review, equipment accreditation, radiation dose monitoring, and structured reporting were reported by 75.0% of respondents, followed by 58.3% of respondents for quality audits and critical incident reporting. The least frequently reported initiatives included Lean/Kaizen exercises and physician performance assessments, implemented by 25.0% of respondents. Conclusion: There is considerable diversity in the quality programs used throughout the world, despite some influence by national and international organizations, from whom further guidance could increase uniformity and optimize patient care in radiology.

Health care is moving toward an environment in which the exchange of data and interoperability of different information systems is of utmost importance. To ensure the ability of data transfer standards and guidelines are vital. In medical imaging the most important standards are Health Level Seven (HL7) and Digital Imaging and Communication in Medicine (DICOM). These standards already make a valuable contribution to the interoperability; however, standards alone are not enough. Guidelines on how to implement interoperability are also required and given by IHE. In this chapter, all three HL7, DICOM, and HL7 will be introduced and the basics will be discussed.

This study aimed to determine whether structured reports (SRs) reduce reporting time and/or increase the level of detail for trauma CT scans compared to free-text reports (FTRs).Eight radiology residents used SRs and FTRs to describe 14 whole-body CT scans of patients with polytrauma in a simulated emergency room setting. Each resident created both a brief report and a detailed report for each case using one of the two formats. We measured the time to complete the detailed reports and established a scoring system to objectively measure report completeness and the level of detail. Scoring sheets divided the CT findings into main and secondary criteria. Finally, the radiological residents completed a questionnaire on their opinions of the SRs and FTRs.The detailed SRs were completed significantly faster than the detailed FTRs (mean 19 min vs. 25 min; p 0.001). The maximum allowance of 25 min was used for 25% of SRs and 59% of FTRs. For brief reports, the SRs contained more secondary criteria than the FTRs (p = 0.001), but no significant differences were detected in main criteria. Study participants rated their own SRs as significantly more time-efficient, concise, and clearly structured compared to the FTRs. However, SRs and FTRs were rated similarly for quality, accuracy, and completeness.We found that SRs for whole-body trauma CT add clinical value compared to FTRs because SRs reduce reporting time and increase the level of detail for trauma CT scans.

Objectives We investigated the attitudes of radiologists, information technology (IT) specialists, and industry representatives on artificial intelligence (AI) and its future impact on radiological work. Materials and Methods During a national meeting for AI, eHealth, and IT infrastructure in 2019, we conducted a survey to obtain participants’ attitudes. A total of 123 participants completed 28 items exploring AI usage in medicine. The Kruskal-Wallis test was used to identify differences between radiologists, IT specialists, and industry representatives. Results The strongest agreement between all respondents occurred with the following: plausibility checks are important to understand the decisions of the AI (93% agreement), validation of AI algorithms is mandatory (91%), and medicine becomes more efficient in the age of AI (86%). In contrast, only 25% of the respondents had confidence in the AI results, and only 17% believed that medicine will become more human through the use of AI. The answers were significantly different between the three professions for four items: relevance for protocol selection in cross-sectional imaging (p = 0.034), medical societies should be involved in validation (p = 0.028), patients should be informed about the use of AI (p = 0.047), and AI should be part of medical education (p = 0.026). Conclusion Currently, a discrepancy exists between high expectations for the future role of AI and low confidence in the results. This attitude was similar across all three groups. The demand for plausibility checks and the need to prove the usefulness in randomized controlled studies indicate what is needed in future research.

Objective The majority of radiological reports are still written as free text and lack structure. Further evaluation of free-text reports is difficult to achieve without a great deal of manual effort, and is not possible in everyday clinical practice. This study aims to automatically capture clinical information and positive hit rates from narrative radiological reports of suspected urolithiasis using natural language processing (NLP). Methods Narrative reports of low dose computed tomography (CT) of the retroperitoneum from April 2016 to July 2018 (n = 1714) were analyzed using NLP. These free-text reports were automatically structured based on RadLex concepts. Manual feedback was used to test and train the NLP engine to further enhance the performance. The chi-squared test, phi coefficient, and logistic regression analysis were performed to determine the effect of clinical information on the positive hit rate of urolithiasis. Results Urolithiasis was affirmed in 72 % of the reports; in 38 % at least one stone was described in the kidneys, and in 45 % at least one stone was described in the ureter. Clinical information, such as previous stone history and obstructive uropathy, showed a strong correlation with confirmed urolithiasis (p = 0.001). Previous stone history and the combination of obstructive uropathy and loin pain had the highest association with positive urolithiasis (p Conclusion Applying this NLP approach to already existing free-text reports allows the conversion of such reports into a structured form. This may be valuable for epidemiological studies, to evaluate the appropriateness of CT examinations, or to answer a variety of research questions.

International audience; Purpose The MEDIRAD project is about the effects of low radiation dose in the context of medical procedures. The goal of the work is to develop an informatics service that will provide the researchers of the MEDIRAD project with a platform to share acquired images, along with the associated dosimetric data pertaining to the radiation resulting from the procedure. Methods The authors designed a system architecture to manage image data and dosimetric data in an integrated way. DICOM and non-DICOM data are stored in separated repositories, and the link between the two is provided through a semantic database, i.e., a database whose information schema in aligned with an ontology. Results The system currently supports CT, PET, SPECT, and NM images as well as dose reports. Currently, two workflows for non-DICOM data generated from dosimetric calculations have been taken into account, one concerning Monte Carlo-based calculation of organ doses in Chest CT, and the other estimation of doses in nontarget organs in I-131 targeted radionuclide therapy of the thyroid. Conclusion The system is currently deployed, thus providing access to image and related dosimetric data to all MEDIRAD users. The software was designed in such a way that it can be reused to support similar needs in other projects.

Structured reporting is a favorable and sustainable form of reporting in radiology. Among its advantages are better presentation, clearer nomenclature, and higher quality. By using MRRT-compliant templates, the content of the categorized items (e.g., select fields) can be automatically stored in a database, which allows further research and quality analytics based on established ontologies like RadLex® linked to the items. Additionally, it is relevant to provide free-text input for descriptions of findings and impressions in complex imaging studies or for the information included with the clinical referral. So far, however, this unstructured content cannot be categorized. We developed a solution to analyze and code these free-text parts of the templates in our MRRT-compliant reporting platform, using natural language processing (NLP) with RadLex® terms in addition to the already categorized items. The established hybrid reporting concept is working successfully. The NLP tool provides RadLex® codes with modifiers (affirmed, speculated, negated). Radiologists can confirm or reject codes provided by NLP before finalizing the structured report. Furthermore, users can suggest RadLex® codes from free text that is not correctly coded with NLP or can suggest to change the modifier. Analyzing free-text fields took 1.23 s on average. Hybrid reporting enables coding of free-text information in our MRRT-compliant templates and thus increases the amount of categorized data that can be stored in the database. This enhances the possibilities for further analyses, such as correlating clinical information with radiological findings or storing high-quality structured information for machine-learning approaches.

Coronary artery bypass grafting (CABG) is still an important therapeutic approach in the treatment especially of advanced coronary artery disease. In this study, we elucidate the current role of multidetector computed tomography angiography (MD-CTA) in imaging patients after CABG surgery.This study is based on recent reports in the literature (2007 - 2016) on imaging of CABG using 64-slice MD-CT scanners and beyond. We included 13 reports that compared ECG-gated MD-CTA with conventional invasive coronary angiography (ICA) as the reference standard for the assessment of graft patency and for the detection of 50 % stenoses. These studies had to provide absolute values for true-positive, true-negative, false-positive and false-negative results or at least allow calculation of these numbers. In total, 1002 patients with 2521 bypass grafts were the basis for this review.The sensitivity and specificity for the assessment of graft patency or the detection of 50 % graft stenosis were 97.2 % and 97.5 %, respectively. The negative and positive predictive values were 93.6 % and 99 %, respectively. By using prospective ECG-gating and an increasing pitch factor, the radiation dose exposure declined to 2.4 mSv in the latest reports. ECG-gated MD-CTA provides a fast and reliable, noninvasive method for assessing patients after CABG. The most substantial benefit of the newest CT scanner generations is a remarkable reduction of radiation dose exposure while maintaining a still excellent diagnostic accuracy during recent years.· MD-CTA using 64-slice MDCT scanners and beyond is a reliable, noninvasive method for evaluating CABGs.. · Technical advances such as prospective ECG-gating, iterative reconstruction algorithms and high-pitch scanning lead to a remarkable drop-down in radiation dose exposures as low as 2.4 mSv.. · Despite significant dose reductions, MD-CTA could maintain a high diagnostic accuracy in evaluating CABGs in recent years..· Jungmann F, Emrich T, Mildenberger P et al. Multidetector Computed Tomography Angiography (MD-CTA) of Coronary Artery Bypass Grafts - Update 2017. Fortschr Röntgenstr 2018; 190: 237 - 249.Die aortokoronare Bypassoperation stellt unverändert einen wichtigen Bestandteil in der Behandlung der koronaren Herzerkrankung insbesondere in fortgeschrittenen Krankheitsstadien dar. In der vorliegenden Arbeit soll der aktuelle Stellenwert der Multidetektor-CT-Angiografie (MD-CTA) bei Patienten nach stattgehabter aortokoronarer Bypassoperation (ACVB) dargelegt werden.Die vorliegende Übersichtsarbeit basiert auf Publikationen aus den Jahren 2007 – 2016 zur nicht-invasiven Bildgebung von Patienten nach ACVB-Operation, die an MD-CT-Geräten mit mindestens 64 Zeilen untersucht wurden. Voraussetzung für eine Berücksichtigung in der Analyse waren Angaben zu den absoluten Vorhersagewerten (richtig-positiv, richtig-negativ, falsch-positiv und falsch-negativ) bzw. ihre Berechnung musste möglich sein. Insgesamt konnten 13 Publikationen berücksichtigt werden, bei denen die EKG-getriggerte CT-Angiografie mit der konventionellen Koronarangiografie als Referenzstandard hinsichtlich Bypassoffenheit bzw. der Detektion von 50 % Bypassstenosen verglichen wurde. Insgesamt wurden 1002 Patienten mit 2521 Bypässen in die Arbeit eingeschlossen.Die gepoolte Sensitivität und Spezifität in der Evaluation der Bypassoffenheit bzw. der Detektion von 50 % Bypassstenosen betrugen 97,2 % und 97,5 %. Der gemittelte positiv prädiktive Wert und der gemittelte negativ prädiktive Wert erreichte 93,6 % bzw. 99 %. Durch prospektive EKG-Triggerung und einer Erhöhung des Pitch-Faktors konnte die Strahlenexposition in den neuesten Publikationen auf bis zu 2,4 mSv gesenkt werden. Die EKG-getriggerte MD-CTA ist eine schnelle und zuverlässige Methode zur Untersuchung von Patienten nach ACVB-Operation. Der größte Fortschritt der neueren CT-Scanner-Generationen ist eine signifikante Reduktion der Strahlenexposition bei einer unverändert hohen diagnostischen Genauigkeit in der Bypassbeurteilung in den vergangenen Jahren.· Die MD-CTA ist eine zuverlässige, nicht-invasive Methode zur Beurteilung aortokoronarer Bypässe.. · Technische Weiterentwicklungen wie prospektive EKG-Triggerung, iterative Rekonstruktionsalgorithmen und high-pitch Technik führen zu einer deutlichen Reduktion der Strahlenexposition auf bis zu 2,4 mSv.. · In den vergangenen Jahren konnte die diagnostische Genauigkeit der MD-CTA auf konstant hohem Niveau gehalten werden, mit weiterhin ausgezeichneten Sensitivitäten und negativ prädiktiven Werten in Bezug auf Bypassoffenheit bzw. der Detektion relevanter Bypassstenosen..

To compare the diagnostic accuracy of medical-grade and calibrated consumer-grade digital displays for the detection of subtle bone fissures. Three experienced radiologists assessed 96 digital radiographs, 40 without and 56 with subtle bone fissures, for the presence or absence of fissures in various bones using one consumer-grade and two medical-grade displays calibrated according to the DICOM-Grayscale Standard Display Function. The reference standard was consensus reading. Subjective image quality was also assessed by the three readers. Statistical analysis was performed using receiver operating characteristic analysis and by calculating the sensitivity, specificity, and Youden’s J for each combination of reader and display. Cohen’s unweighted kappa was calculated to assess inter-rater agreement. Subjective image quality was compared using the Wilcoxon signed-rank test. No significant differences were found for the assessment of subjective image quality. Diagnostic performance was similar across all readers and displays, with Youden’s J ranging from 0.443 to 0.661. The differences were influenced more by the reader than by the display used for the assessment. No significant differences were found between medical-grade and calibrated consumer-grade displays with regard to their diagnostic performance in assessing subtle bone fissures. Calibrated consumer-grade displays may be sufficient for most radiological examinations. • Diagnostic performance of calibrated consumer-grade displays is comparable to medical-grade displays. • There is no significant difference with regard to subjective image quality. • Use of calibrated consumer-grade displays could cut display costs by 60-80%.

Objectives To identify the number of CT scans repeated in acute trauma patients receiving imaging before being referred to a trauma center, to define indications, and to assess radiation doses and costs of repeated CT. Methods This retrospective study included all adult trauma patients transferred from other hospitals to a Level-I trauma center during 2014. Indications for repeated CT scans were categorized into: inadequate CT image data transfer, poor image quality, repetition of head CT after head injury together with completion to whole-body CT (WBCT), and follow-up of injury known from previous CT. Radiation doses from repeated CT were determined; costs were calculated using a nation-wide fee schedule. Results Within one year, 85/298 (28.5%) trauma patients were transferred from another hospital because of severe head injury (n = 45,53%) and major body trauma (n = 23;27%) not manageable in the referring hospital, repatriation from a foreign country (n = 14;16.5%), and no ICU-capacity (n = 3;3.5%). Of these 85 patients, 74 (87%) had repeated CT in our center because of inadequate CT data transfer (n = 29;39%), repetition of head CT with completion to WBCT (n = 24;32.5%), and follow-up of known injury (n = 21;28.5%). None occurred because of poor image quality. Cumulative dose length product (DLP) and annual costs of potential preventable, repeated CT (inadequate data transfer) was 631mSv (81′304mGy*cm) and 35′233€, respectively. Conclusion A considerable number of transferred trauma patients undergo potentially preventable, repeated CT, adding radiation dose to patients and costs to the health care system.

Computed tomography (CT) is an essential tool in modern medicine and is frequently used to diagnose a wide range of conditions, particularly in industrial countries, such as Japan and Germany. However, markedly higher doses of ionizing radiation are delivered during CT imaging than during conventional X-ray examinations. To assess pediatric CT practice patterns, data from three university hospital databases (two in Japan and one in Germany) were analyzed. Anonymized data for patients aged 0 to 14 years who had undergone CT examinations between 2008 and 2010 were extracted. To assess CT practice, an interdisciplinary classification scheme for CT indications, which incorporated the most common examination types and radiosensitive tissues, was developed. The frequency of CT examinations was determined according to sex, age at examination, and indications. A total of 5182 CT examinations were performed in 2955 children. Overall, the frequency of CT examinations at the Japanese university hospitals did not differ significantly from that at the German hospital. However, differences were detected in the age distribution of the patients who underwent CT examinations (the proportion of patients ?5 years of age was significantly higher in Japan than in Germany) and in the indications for CT. Substantial practice differences regarding the use of CT in pediatric health care were detected between the three hospitals. The results of this study point towards a need for approaches such as clinical guidelines to reduce unwarranted medical radiation exposures, particularly abdominal and head CT, in the Japanese health system., Journal of Radiation Research, 58(1), pp.135-141; 2017

Background Data used for training of deep learning networks usually needs large amounts of accurate labels. These labels are usually extracted from reports using natural language processing or by time-consuming manual review. The aim of this study was therefore to develop and evaluate a workflow for using data from structured reports as labels to be used in a deep learning application. Materials and methods We included all plain anteriorposterior radiographs of the ankle for which structured reports were available. A workflow was designed and implemented where a script was used to automatically retrieve, convert, and anonymize the respective radiographs of cases where fractures were either present or absent from the institution’s picture archiving and communication system (PACS). These images were then used to retrain a pretrained deep convolutional neural network. Finally, performance was evaluated on a set of previously unseen radiographs. Results Once implemented and configured, completion of the whole workflow took under 1 h. A total of 157 structured reports were retrieved from the reporting platform. For all structured reports, corresponding radiographs were successfully retrieved from the PACS and fed into the training process. On an unseen validation subset, the model showed a satisfactory performance with an area under the curve of 0.850 (95% CI 0.634–1.000) for detection of fractures. Conclusion We demonstrate that data obtained from structured reports written in clinical routine can be used to successfully train deep learning algorithms. This highlights the potential role of structured reporting for the future of radiology, especially in the context of deep learning.

BACKGROUND: In secondary data there are often unstructured free texts. The aim of this study was to validate a text mining system to extract unstructured medical data for research purposes. METHODS: From a radiological department, 1,000 out of 7,102 CT findings were randomly selected. These were manually divided into defined groups by 2 physicians. For automated tagging and reporting, the text analysis software Averbis Extraction Platform (AEP) was used. Special features of the system are a morphological analysis for the decomposition of compound words as well as the recognition of noun phrases, abbreviations and negated statements. Based on the extracted standardized keywords, findings reports were assigned to the given findings groups using machine learning methods. To assess the reliability and validity of the automated process, the automated and two independent manual mappings were compared for matches in multiple runs. RESULTS: Manual classification was too time-consuming. In the case of automated keywording, the classification according to ICD-10 turned out to be unsuitable for our data. It also showed that the keyword search does not deliver reliable results. Computer-aided text mining and machine learning resulted in reliable results. The inter-rater reliability of the two manual classifications, as well as the machine and manual classification was very high. Both manual classifications were consistent in 93% of all findings. The kappa coefficient is 0.89 [95% confidence interval (CI) 0.87–0.92]. The automatic classification agreed with the independent, second manual classification in 86% of all findings (Kappa coefficient 0.79 [95% CI 0.75–0.81]). DISCUSSION: The classification of the software AEP was very good. In our study, however, it followed a systematic pattern. Most misclassifications were found in findings that indicate an increased risk of cancer. The free-text structure of the findings raises concerns about the feasibility of a purely automated analysis. The combination of human intellect and intelligent, adaptive software appears most suitable for mining unstructured but important textual information for research. HINTERGRUND: In Sekundärdaten existieren oftmals unstrukturierte Freitexte. In dieser Arbeit wird ein Text-Mining-System validiert, um unstrukturierte medizinische Daten für Forschungszwecke zu extrahieren. METHODEN: Aus einer radiologischen Klinik wurden aus 7102 CT-Befunden 1000 zufällig ausgewählt. Diese wurden von 2 Medizinern manuell in definierte Befundgruppen eingeteilt. Zur automatisierten Verschlagwortung und Klassifizierung wurde die Textanalyse-Software Averbis Extraction Platform (AEP) eingesetzt. Besonderheiten des Systems sind u. a. eine morphologische Analyse zur Zerlegung zusammengesetzter Wörter sowie die Erkennung von Nominalphrasen, Abkürzungen und negierten Aussagen. Anhand der extrahierten standardisierten Schlüsselwörter werden Befundberichte mithilfe maschineller Lernverfahren den vorgegebenen Befundgruppen zugeordnet. Zur Bewertung von Reliabilität und Validität des automatisierten Verfahrens werden die automatisierten und 2 unabhängige manuelle Klassifizierungen in mehreren Durchläufen auf Übereinstimmungen hin verglichen. ERGEBNISSE: Die manuelle Klassifizierung war zu zeitaufwendig. Bei der automatisierten Verschlagwortung stellte sich in unseren Daten die Klassifizierung nach ICD-10 als ungeeignet heraus. Ebenfalls zeigte sich, dass die Stichwortsuche keine verlässlichen Ergebnisse liefert. Computerunterstütztes Textmining in Kombination mit maschinellem Lernen führte zu verlässlichen Klassifizierungen. Die Inter-Rater-Reliabilität der beiden manuellen Klassifizierungen, sowie der maschinellen und der manuellen Klassifizierung war sehr hoch. Beide manuelle Klassifizierungen stimmten in 93% aller Befunde überein. Der Kappa-Koeffizient beträgt 0,89 [95% Konfidenzintervall (KI) 0,87–0,92]. Die automatische Klassifizierung stimmte in 86% aller Befunde mit der unabhängigen, zweiten manuellen Klassifizierung überein (Kappa-Koeffizient 0,79 [95% KI 0,75–0,81]). DISKUSSION: Die Klassifizierung der Software AEP war sehr gut. In unserer Studie folgte sie allerdings einem systematischen Muster. Die meisten falschen Zuordnungen finden sich in Befunden, die auf ein erhöhtes Krebsrisiko hinweisen. Die Freitextstruktur der Befunde lässt Bedenken hinsichtlich der Machbarkeit einer rein automatisierten Analyse aufkommen. Die Kombination aus menschlichem Intellekt und einer intelligenten, lernfähigen Software erscheint als zukunftsweisend, um unstrukturierte aber wichtige Textinformationen der Forschung zugänglich machen zu können.

Aim To develop a robust open-source method for fully automated extraction of total lung capacity (TLC) from computed tomography (CT) images and to demonstrate its integration into the clinical workflow. Materials and methods Using only open-source software, an algorithm was developed based on a region-growing method that does not require manual interaction. Lung volumes calculated from reconstructions with different kernels (TLCCT) were assessed. To validate the algorithm calculations, the results were correlated to TLC measured by pulmonary function testing (TLCPFT) in a subgroup of patients for which this information was available within 3 days of the CT examination. Results A total of 288 patients were analysed retrospectively. Manual review revealed poor segmentation results in 13 (4.5%) patients. In the validation subgroup, the correlation between TLCCT and TLCPFT was r=0.87 (p Conclusions The algorithm developed allows fast and fully automated calculation of lung volume without any additional input from the radiologist. The algorithm delivers excellent segmentation in >95% of cases with significant positive correlations between lung volume on CT and TLC on PFT.

The radiology report is the key component in the communication between radiologists and referring clinicians. Traditionally, reports are written as free text. Several studies have shown that structured reporting using dedicated report templates has a number of advantages compared to conventional reports. Therefore, many radiological societies have recommended the implementation of structured reporting in clinical routine. In the meantime, collections of freely available templates have been presented and software solutions for structured reporting have been made commercially available. These allow for quality improvements in the written radiology report as they ensure that all relevant clinical information is included. Most vendors mainly supply proprietary report templates or allow users to create templates for their own institution. The German Radiological Society (DRG) has the goal of developing consensus-based, quality-assured report templates and providing them under a free license. The DRG has developed its first consensus-based report templates and provides them at www.befundung.drg.de. Further report templates will be developed in close cooperation with the respective committees of the DRG and referring clinicians. Structured reporting allows for a significant improvement in the quality of written radiology reports. The use of report templates requires personal and technical changes to the reporting process itself. Radiology should face these challenges in its leading role in the application of modern IT-based solutions. Vendors are now encouraged to provide practical solutions. · Structured reports have numerous advantages over conventional narrative reports.. · The German Radiological Society is developing consensus-based and quality assured report templates.. · Report templates are provided at www.befundung.drg.de under a free license.. · Vendors are now encouraged to provide solutions for the implementation of structured reporting..· Pinto dos Santos D, Hempel J, Mildenberger P et al. Structured Reporting in Clinical Routine. Fortschr Röntgenstr 2019; 191: 33 - 39. Der radiologische Befundbericht ist das zentrale Mittel der Kommunikation zwischen Radiologen und Zuweisern. Traditionell wird dieser als Freitext verfasst. Aus zahlreichen Untersuchungen ist bekannt, dass eine strukturierte Befundung mit Nutzung entsprechender Befundvorlagen eine Vielzahl von Vorteilen gegenüber herkömmlichen Befundberichten aufweist. Zahlreiche radiologische Fachgesellschaften empfehlen daher die Implementierung einer strukturierten Befundung in der klinischen Routine. Inzwischen existieren bereits Sammlungen frei verfügbarer Befundvorlagen sowie kommerzielle Softwarelösungen zur strukturierten Befundung. Diese ermöglichen eine Verbesserung der Qualität radiologischer Befundberichte durch Nennung aller notwendigen klinischen Informationen. Die meisten Hersteller stellen vor allem proprietäre Befundvorlagen zur Verfügung oder erlauben dem Benutzer die Erstellung institutionsspezifischer Befundvorlagen. Die Deutsche Röntgengesellschaft (DRG) hat sich zum Ziel gesetzt, qualitätsgesicherte konsensbasierte Befundvorlagen zu entwickeln und unter freier Lizenz zur Verfügung zu stellen. Die DRG hat erste konsensbasierte Befundvorlagen entwickelt und unter www.befundung.drg.de zur freien Verfügung gestellt. Weitere Befundvorlagen werden in enger Zusammenarbeit mit den entsprechenden Arbeitsgemeinschaften der DRG und zuweisenden Kollegen erarbeitet. Strukturierte Befundung ermöglicht eine deutliche Verbesserung der Qualität radiologischer Befundberichte für eine Vielzahl von Fragestellungen. Die Nutzung strukturierter Befundvorlagen bedingt jedoch eine Umstellung im persönlichen und technischen Befundungsprozess. In ihrer führenden Rolle in der Anwendung moderner IT-gestützter Lösungen sollte sich die Radiologie diesen Herausforderungen bewusst stellen. Softwarehersteller sind nun gefordert, praktische Lösungen anzubieten. · Strukturierte Befundberichte weisen zahlreiche Vorteile gegenüber konventionellen, narrativen Befundberichten auf.. · Die Deutsche Röntgengesellschaft entwickelt konsensbasierte und qualitätsgesicherte Befundvorlagen.. · Befundvorlagen werden unter www.befundung.drg.de unter freier Lizenz zur Verfügung gestellt.. · Hersteller sind nun gefordert, Lösungen zur Implementierung strukturierter Befundung anzubieten..· Pinto dos Santos D, Hempel J, Mildenberger P et al. Structured Reporting in Clinical Routine. Fortschr Röntgenstr 2019; 191: 33 – 39.

OBJECTIVE: This paper studies the possibilities of an integrated IT-based workflow for epidemiological research in pulmonary embolism (PE) using freely available tools and structured reporting (SR). METHODS: We included a total of 521 consecutive cases which had been referred to the radiology department for CT pulmonary angiography with suspected PE. Free-text reports were transformed into structured reports using a freely available IHE Management of Radiology Report Templates-compliant reporting platform. D-dimer values were retrieved from the hospitals laboratory results system. All information was stored in the platform’s database and visualized using freely available tools. For further analysis, we directly accessed the platform’s database with an advanced analytics tool (RapidMiner). RESULTS: Results: We were able to develop an integrated workflow for epidemiological statistics from reports obtained in clinical routine. The report data allowed for automated calculation of epidemiological parameters. Prevalence of PE was 27.6%. The mean age in patients with and without PE did not differ (62.8 years and 62.0 years, respectively, p = 0.987). As expected, there was a significant difference in mean D-dimer values (10.13 and 3.12 mg l−1 fibrinogen equivalent units, respectively, p < 0.001). Conclusion: SR can make data obtained from clinical routine more accessible. Designing practical workflows is feasible using freely available tools and allows for the calculation of epidemiological statistics on a near realtime basis. Therefore, radiologists should push for the implementation of SR in clinical routine. SUMMARY SENTENCE: Implementing practical workflows that allow for the calculation of epidemiological statistics using SR and freely available tools is easily feasible. ADVANCES IN KNOWLEDGE: Theoretical benefits of SR have long been discussed, but practical implementation demonstrating those benefits has been lacking. Here, we present a first experience providing proof that SR will make data from clinical routine more accessible.

Objectives To evaluate the incidence, management, and outcome of visceral artery aneurysms (VAA) over one decade. Methods 233 patients with 253 VAA were analyzed according to location, diameter, aneurysm type, aetiology, rupture, management, and outcome. Results VAA were localized at the splenic artery, coeliac trunk, renal artery, hepatic artery, superior mesenteric artery, and other locations. The aetiology was degenerative, iatrogenic after medical procedures, connective tissue disease, and others. The rate of rupture was much higher in pseudoaneurysms than true aneurysms (76.3 % vs.3.1 %). Fifty-nine VAA were treated by intervention (n = 45) or surgery (n = 14). Interventions included embolization with coils or glue, covered stents, or combinations of these. Thirty-five cases with ruptured VAA were treated on an emergency basis. There was no difference in size between ruptured and non-ruptured VAA. After interventional treatment, the 30-day mortality was 6.7 % in ruptured VAA compared to no mortality in non-ruptured cases. Follow-up included CT and/or MRI after a mean period of 18.0 ± 26.8 months. The current status of the patient was obtained by a structured telephone survey. Conclusions Pseudoaneurysms of visceral arteries have a high risk for rupture. Aneurysm size seems to be no reliable predictor for rupture. Interventional treatment is safe and effective for management of VAA. Key Points • Diagnosis of visceral artery aneurysms is increasing due to CT and MRI. • Diameter of visceral arterial aneurysms is no reliable predictor for rupture. • False aneurysms/pseudoaneurysms and symptomatic cases need emergency treatment. • Interventional treatment is safe and effective.

ZIEL: Übertragung des Befundungsbogens aus den Richtlinien zum Transplantationsgesetz (TPG) in ein standardkonformes Befundtemplate und Evaluation in der klinischen Routine. Das Template wurde mit der frei verfügbaren Software brackets.io erstellt. Die Implementierung des Templates in die klinische Routine erfolgte mithilfe einer in Eigenentwicklung programmierten Befundungsplattform. Schnittstellen zu RIS und PACS erlaubten eine Integration in den gewohnten Befundungsworkflow. Die Evaluationsperiode erstreckte sich über 70 Tage. Die Erstellung des Templates für die Umsetzung der Richtlinien war ohne Schwierigkeiten möglich. Der vorgegebene Befundungsbogen wurde hierbei inhaltlich eins zu eins abgebildet. Zusätzlich wurde ein Freitextfeld hinzugefügt, um ergänzende Anmerkungen zu ermöglichen. Im beobachteten Zeitraum wurden von sieben Radiologen 44 Auswertungen gemäß § 16 TPG erstellt. Sowohl die Nutzer des Templates als auch die beteiligten Zuweiser und Mitarbeiter des Transplantationsbüros berichteten insgesamt über eine hohe Zufriedenheit. Die elektronische Implementierung gesetzlich (etwa in den Richtlinien zu § 16 TPG) geforderter Befundungsbogen in die klinische Routine ist einfach umsetzbar und zeigt eine hohe Akzeptanz. Der von der Deutschen Röntgengesellschaft unterstützte Standard (IHE „Management of Radiology Report Templates“) erlaubt eine schnelle Antwort auf die zunehmenden Forderungen nach strukturierter und standardisierter Befundung. · Gesetzlich geforderte Befundungsbogen können in elektronischer Form einfach in die klinische Routine integriert werden.. · Strukturierte Befundungsvorlagen in der von der DRG unterstützten Form erlauben eine schnelle Antwort auf Forderungen nach standardisierter Befundung.. · Sowohl Radiologen als auch Zuweiser berichten über eine hohe Zufriedenheit mit der elektronischen Form des Befundungsbogens..· Pinto dos Santos D, Arnhold G, Mildenberger P et al. Guidelines Regarding §16 of the German Transplantation Act – Initial Experiences with Structured Reporting. Fortschr Röntgenstr 2017; 189: 1145 – 1151.