Objectives:Clinical examination alone cannot reliably rule out significant traumatic abdominal injury. Computed tomography (CT) has become the primary method for evaluating blunt abdominal trauma and clinicians rely heavily on it to rule out abdominal injury. Ultrasound examination may miss significant abdominal injury particularly in stable patients. The use of a contrast agent improves ultrasound sensitivity to visceral abdominal injuries. The objective of this diagnostic study is to compare bedside contrast enhanced ultrasound (CEUS) performed by emergency physicians to CT in hemodynamically stable adults for the assessment of blunt abdominal trauma and evaluate CEUS accuracy outcomes.Methods:Hemodynamically stable patients with blunt trauma were prospectively enrolled in the trauma bay. After initial evaluation, we included patients at risk of abdominal injury and for whom an abdominal CT was planned by the trauma leader. Ultrasonography was performed prospectively and at the bedside by the emergency physician followed by abdominal CT used as a reference standard.Results:Thirty-three patients were enrolled in the study; among them, 52% showed positive traumatic findings in abdominal CT scans, and 42% were diagnosed with solid organ lesions. Compared to CT, a focused abdominal sonography (FOCUS) examination, looking for free fluid or perirenal hematoma, showed limited performance for traumatic findings with a sensitivity of 65% (95% confidence interval [CI]: 38%-86%), a specificity of 75% (95% CI: 48%-93%), a negative likelihood ratio (NLR) of 0.47 (95% CI: 0.23-0.95), and a positive likelihood ratio (PLR) of 2.59 (95% CI: 1.03-6.48). When combining FOCUS with CEUS, the sensitivity of the sonography increased to 94% (95% CI: 71%-100%) with a specificity of 75% (95% CI: 48%-93%). The PLR was 3.76 (95% CI: 1.6-8.87) and the NLR was 0.08 (95% CI: 0.01-0.54). In our population, abdominal sonography with contrast failed to identify a single positive abdominal CT with a grade 1 kidney injury.Conclusions:A FOCUS examination shows limited sensitivity and specificity to detect positive abdominal CT in stable adults with abdominal trauma. With the addition of contrast and careful inspection of solid organs, abdominal sonography with contrast performed by the emergency physician improves the ability to rule out traumatic findings on abdominal CT. CEUS performed by emergency physicians may miss injuries, especially in the absence of free fluid, in cases of low-grade injuries, simultaneous injuries, or poor-quality examinations.

Introduction: In a non-endemic setting, disseminated histoplasmosis is a rare travel-related health problem of immunosuppressed returnees from endemic regions. Methods: We describe the case of a 68-year-old man with rheumatoid arthritis and tumor necrosis factor alpha (TNF-α) inhibitor treatment-related immunodeficiency, who suffered from disseminated histoplasmosis after traveling to Brazil. Based on this case, we discuss challenges and pitfalls associated with the diagnosis of disseminated histoplasmosis in a non-endemic setting. Results: The disease mimicked a hemophagocytic lymphohistiocytosis (HLH) like syndrome. Histoplasma capsulatum was microscopically detected in bronchoalveolar fluid and bone marrow aspirate smears, but was initially misclassified as Leishmania spp., another class of pathogens, which may cause HLH like syndromes in immunocompromised individuals. Discussion: Since the clinical symptoms of histoplasmosis are nonspecific and physicians in non-endemic regions might not be familiar with this disease pattern, there is a risk of delayed diagnosis of travel related cases. Taking a thorough travel history is key in unclear cases of illness in immunocompromised patients.

Zusammenfassung. Die Schweiz ist von der COVID-19-Pandemie stark betroffen. Das klinische Spektrum dieser Erkrankung hinsichtlich klinischer Präsentation und Verlauf ist breit. Eine korrekte initiale Beurteilung in der Praxis oder auf der Notfallstation ist wichtig und umfasst neben Anamnese und klinischer Untersuchung auch bildgebende Verfahren und Laboruntersuchungen. Die meisten Personen mit COVID-19 können ambulant behandelt werden. Eine Hospitalisation kann notwendig werden bei Kranken mit ausgeprägter COVID-19-Pneumonie oder weiteren Komplikationen, die vor allem in der 2. und 3. Phase der Erkrankung auftreten. Auch muss die Dynamik der Erkrankung in die Überlegungen mit einbezogen werden. Bei ambulanten Patientinnen und Patienten erfolgt in der Regel eine symptomatische Therapie, Antibiotika oder Kortikosteroide sind nicht indiziert.

Background The functional residual capacity (FRC) determines the oxygenating capacity of the lung and is heavily affected in the clinical context of the acute respiratory distress syndrome. Nitrogen-wash-in/wash-out methods have been used to measure FRC. These methods have rarely been validated against exactly known volumes. The aim of the study was to assess the accuracy and precision of the N 2 washout/washin method in measuring FRC, by comparing it with set volumes in a lung simulator. Methods We conducted a diagnostic bench study in the Intensive Care Unit and Radiology Department of a tertiary hospital in Switzerland. Using a fully controllable high fidelity lung simulator (TestChest®), we set the functional residual capacity at 1500 ml, 2000 ml and 2500 ml and connected to the GE Carestation respirator, which includes the nitrogen washout/washin technique (INview™ tool). FRC was then set to vary by different levels of PEEP (5, 8, 12 and 15 cmH 2 O). The main outcome measures were bias and precision of the TestChest® when compared to the results from the washout/washin technique, according to the results of a Bland Altman Analysis. We verified our findings with volumetric computed tomography. Results One hundred and thirty-five nitrogen-wash-in/wash-out measurements were taken at three levels of F I O 2 (0.4, 0.5, 0.6). The CT volumetry reproduced the set end-expiratory volumes at the Simulator with a bias of 4 ml. The nitrogen-wash-in/wash-out method had a bias of 603 ml with acceptable limits of agreement (95% CI 252 to − 953 ml). Changes were detected with a concordance rate of 97%. Conclusions We conclude that the TestChest® simulator is an accurate simulation tool, concerning the simulation of lung volumes. The nitrogen wash-in/wash out method correlated positively with FRC changes, despite a relatively large bias in absolute measurements. The reference volumes in the lung simulator verified with CT volumetry were very close to their expected values. The reason for the bias could not be determined.

Posttraumatic pulmonary artery pseudoaneurysm is a very rare, yet potentially lethal complication after thoracic trauma. Pulmonary artery pseudoaneurysm is associated with high mortality. Still literature highlights that untreated, lesions can enlarge, rupture, and lead to exsanguination and death. We present a case of a posttraumatic peripheral pulmonary artery pseudoaneurysm with complete disappearance after one year. This case confirms that conservative treatment can be an effective option in asymptomatic and stable patients.

Background A number of episodes of nosocomial Agrobacterium spp . bacteremia (two cases per year) were observed at Bern University Hospital, Switzerland, from 2015 to 2017. This triggered an outbreak investigation. Methods Cases of Agrobacterium spp . bacteremias that occurred between August 2011 and February 2017 were investigated employing line lists, environmental sampling, rapid protein- (MALDI-TOF MS), and genome-based typing (pulsed field gel electrophoresis and whole genome sequencing) of the clinical isolates. Results We describe a total of eight bacteremia episodes due to A. radiobacter ( n = 2), Agrobacterium genomovar G3 ( n = 5) and A. pusense ( n = 1). Two tight clusters were observed by WGS typing, representing the two A. radiobacter isolates (cluster I, isolated in 2015) and four of the Agrobacterium genomovar G3 isolates (cluster II, isolated in 2016 and 2017), suggesting two different point sources. The epidemiological investigations revealed two computer tomography (CT) rooms as common patient locations, which correlated with the two outbreak clusters. MALDI-TOF MS permitted faster evaluation of strain relatedness than DNA-based methods. High resolution WGS-based typing confirmed the MALDI-TOF MS clustering. Conclusions We report clinical and epidemiological characteristics of two outbreak clusters with Agrobacterium. spp. bacteremia likely acquired during CT contrast medium injection and highlight the use of MALDI-TOF MS as a rapid tool to assess relatedness of rare gram-negative pathogens in an outbreak investigation.

ObjectiveThe aim of this study was to investigate the performance of the arterial enhancement fraction (AEF) in multiphasic computed tomography (CT) acquisitions to detect hepatocellular carcinoma (HCC) in liver transplant recipients in correlation with the pathologic analysis of the corresponding liver explants. Materials and MethodsFifty-five transplant recipients were analyzed: 35 patients with 108 histologically proven HCC lesions and 20 patients with end-stage liver disease without HCC. Six radiologists looked at the triphasic CT acquisitions with the AEF maps in a first readout. For the second readout without the AEF maps, 3 radiologists analyzed triphasic CT acquisitions (group 1), whereas the other 3 readers had 4 contrast acquisitions available (group 2). A jackknife free-response reader receiver operating characteristic analysis was used to compare the readout performance of the readers. Receiver operating characteristic analysis was used to determine the optimal cutoff value of the AEF. ResultsThe figure of merit (&thgr; = 0.6935) for the conventional triphasic readout was significantly inferior compared with the triphasic readout with additional use of the AEF (&thgr; = 0.7478, P < 0.0001) in group 1. There was no significant difference between the fourphasic conventional readout (&thgr; = 0.7569) and the triphasic readout (&thgr; = 0.7615, P = 0.7541) with the AEF in group 2. Without the AEF, HCC lesions were detected with a sensitivity of 30.7% (95% confidence interval [CI], 25.5%–36.4%) and a specificity of 97.1% (96.0%–98.0%) by group 1 looking at 3 CT acquisition phases and with a sensitivity of 42.1% (36.2%–48.1%) and a specificity of 97.5% (96.4%–98.3%) in group 2 looking at 4 CT acquisition phases. Using the AEF maps, both groups looking at the same 3 acquisition phases, the sensitivity was 47.7% (95% CI, 41.9%–53.5%) with a specificity of 97.4% (96.4%–98.3%) in group 1 and 49.8% (95% CI, 43.9%–55.8%)/97.6% (96.6%–98.4%) in group 2. The optimal cutoff for the AEF was 50%. ConclusionThe AEF is a helpful tool to screen for HCC with CT. The use of the AEF maps may significantly improve HCC detection, which allows omitting the fourth CT acquisition phase and thus making a 25% reduction of radiation dose possible.

Introduction: Aspiration pneumonia in hospitalized surgical patients has been associated with a mortality of approximately 30%. The aim of this study was to assess pre-, intra-and postoperative risk factors for mortality in patients suffering aspiration pneumonia after abdominal surgery.Methods: Retrospective study from 01/2006-12/2012 of patients with clinically and radiologically confirmed aspiration pneumonia after abdominal surgery.Results: A total of 70 patients undergoing abdominal surgery and postoperative aspiration pneumonia were identified. There were 53 (76%) male patients, the mean age was 71 +/- 12 years and the mean ASA score was 3 +/- 1. The surgical procedures included 32 colorectal or small bowel resections, 10 partial liver resections, 9 gastric surgeries, 8 esophageal resections, 5 pancreatic surgeries, and 6 hernia repairs. Aspiration pneumonia occurred at mean postoperative day 7 +/- 10. Overall, 53% (n +/- 37) of patients required re-intubation, with 4 +/- 5 days of additional mechanical ventilation. Mean hospital and ICU length of stay was 32 +/- 25 days and 6 +/- 9 days, respectively. Overall mortality was 27% (n +/- 19). Forward logistic regression revealed older age [OR 7.41 (95% CI: 1.29-42.62)], bilateral aspiration pneumonia [OR 7.39 (95% CI: 1.86-29.29)] and intraoperative requirement of blood component transfusion [OR 5.09 (95% CI: 1.34-19.38)] as independent risk factors for mortality (overall R-2 +/- 0.336).Conclusion: Postoperative aspiration pneumonia remains a severe complication with significant mortality. Increasing age, the need for intraoperative blood component transfusion and bilateral pulmonary infiltrates are independent risk factors for fatal outcome after aspiration pneumonia. Therefore, these patients suffering aspiration pneumonia require special attention and increased monitoring. (C) 2016 IJS Publishing Group Limited. Published by Elsevier Ltd. All rights reserved.

Sexuality is an essential aspect of quality of life. Nevertheless, sexual intercourse is physically challenging and leads to distinct changes in blood pressure, heart, and respiratory rate that may lead to vital complications. We present a case report of a 22-year-old female suffering from subarachnoid hemorrhage after sexual intercourse. The patient was immediately transported to hospital by emergency medical services and, after diagnosis, transferred to a tertiary hospital with neurosurgical expertise but died within 24 hours. After postcoital headaches, subarachnoid hemorrhage is the second most common cause of neurological complications of sexual intercourse and therefore patients admitted to an emergency department with headache after sexual intercourse should always be carefully evaluated by cerebral imaging.

OBJECTIVE:The purpose of this study was to investigate the feasibility of microdose CT using a comparable dose as for conventional chest radiographs in two planes including dual-energy subtraction for lung nodule assessment.MATERIALS AND METHODS:We investigated 65 chest phantoms with 141 lung nodules, using an anthropomorphic chest phantom with artificial lung nodules. Microdose CT parameters were 80 kV and 6 mAs, with pitch of 2.2. Iterative reconstruction algorithms and an integrated circuit detector system (Stellar, Siemens Healthcare) were applied for maximum dose reduction. Maximum intensity projections (MIPs) were reconstructed. Chest radiographs were acquired in two projections with bone suppression. Four blinded radiologists interpreted the images in random order.RESULTS:A soft-tissue CT kernel (I30f) delivered better sensitivities in a pilot study than a hard kernel (I70f), with respective mean (SD) sensitivities of 91.1%±2.2% versus 85.6%±5.6% (p=0.041). Nodule size was measured accurately for all kernels. Mean clustered nodule sensitivity with chest radiography was 45.7%±8.1% (with bone suppression, 46.1%±8%; p=0.94); for microdose CT, nodule sensitivity was 83.6%±9% without MIP (with additional MIP, 92.5%±6%; p<10(-3)). Individual sensitivities of microdose CT for readers 1, 2, 3, and 4 were 84.3%, 90.7%, 68.6%, and 45.0%, respectively. Sensitivities with chest radiography for readers 1, 2, 3, and 4 were 42.9%, 58.6%, 36.4%, and 90.7%, respectively. In the per-phantom analysis, respective sensitivities of microdose CT versus chest radiography were 96.2% and 75% (p<10(-6)). The effective dose for chest radiography including dual-energy subtraction was 0.242 mSv; for microdose CT, the applied dose was 0.1323 mSv.CONCLUSION:Microdose CT is better than the combination of chest radiography and dual-energy subtraction for the detection of solid nodules between 5 and 12 mm at a lower dose level of 0.13 mSv. Soft-tissue kernels allow better sensitivities. These preliminary results indicate that microdose CT has the potential to replace conventional chest radiography for lung nodule detection.

Objective:The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT) by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP) and an iterative reconstruction (IR) algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany) was investigated.Materials and Methods:136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP), SOMATOM Definition Flash (IR), and SOMATOM Definition Edge (ICD and IR). Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product.Results:Dose-length product (DLP) with FBP for the average chest CT was 308 mGy*cm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGy*cm ± 68.8 (P= 0.0001). Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGy*cm ± 54.5 (P= 0.033). The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR) was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (thePvalues ranged from 0.003 to 0.048). Overall contrast-to-noise ratio (CNR) improved with declining DLP.Conclusion:The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.

Current Requirement Engineering research must face the need to deal with the increasing scale of today's requirement specifications. One important and recent research direction is handling the consistency assurance between large scale specifications and many additional regulations (e.g. national and international norms and standards), which the specifications must consider or satisfy. For example, the specification volume for a single electronic control unit (ECU) in the automotive domain sums up to 3000 to 5000 pages distributed over 30 to 300 individual documents (specification and regulations). In this work, we present an approach to automatically classify the requirements in a set of specification documents and regulations to content topics in order to improve review activities in identifying cross-document inconsistencies. An essential success criteria for this approach from an industrial perspective is a sufficient classification quality with minimal manual effort. In this paper, we show the results of an evaluation in the domain of automotive specifications at Mercedes-Benz passenger cars. The results show that one manually classified specification is sufficient to derive automatic classifications for other documents within this domain with satisfactory recall and precision. So, the approach of using content topics is not only effective but also efficient in large scale industrial environments.

We present a rare case of pulmonary intimal sarcoma mimicking pulmonary embolism in a 40-year-old woman. Although extremely rare, these tumors must be considered in patients who present inappropriate imaging findings that suggest embolism. Chest computed tomography is the modality of choice to determine the extent of the tumor. We present a female patient with suspected embolism that was in fact found to be an endothelial sarcoma of the pulmonary arteries.

Context and motivation: Requirements of todays industry specifications need to be categorized for multiple reasons, including analysis of certain requirement types (like non-functional requirements) and identification of dependencies among requirements.This is a pre-requisite for effective communication and prioritization of requirements in industry-size specifications. Question/problem: Because of the size and complexity of these specifications, categorization tasks must be specifically supported in order to minimize manual efforts and to ensure a high classification accuracy. Approaches that make use of (supervised) automatic classification algorithms have to deal with the problem to provide enough training data with excellent quality. Principal ideas/results: In this paper, we discuss the requirements engineering team and their requirements management tool as a socio-technical system that allows consistent classification of requirements with a focus on organizational learning. We compare a manual, a semi-automatic, and a fully-automatic approach for the classification of requirements in this environment. We evaluate performance of these approaches by measuring effort and accuracy of automatic classification recommendations and combined performance of user and tool, and capturing the opinion of the expert-participants in a questionnaire. Our results show that a semiautomatic approach is most promising, as it offers the best ratio of quality and effort and the best learning performance. Contribution: Our contribution is the definition of a socio-technical system for requirements classification and its evaluation in an industrial setting at Mercedes-Benz with a team of ten practitioners.

Context and motivation: Today's industry specifications, in particular those of the automotive industry, are complex and voluminous. At Mercedes-Benz, a specification and its referenced documents often sums up to 3,000 pages. Question/problem: A common way to ensure the quality in such natural language specifications is technical review. Given such large specifications, reviewers have major problems in finding defects, especially consistency or completeness defects, between requirements with related information, spread over the various documents. Principal ideas/results: In this paper, we investigate two specifications from Mercedes-Benz, whether requirements with related information spread over many sections of many documents can be automatically classified and extracted using text classification algorithms to support reviewers with their work. We further research enhancements to improve these classifiers. The results of this work demonstrate that an automatic classification of requirements for multiple aspects is feasible with high accuracy. Contribution: In this paper, we show how an automatic classification of requirements can be used to improve the review process. We discuss the limitations and potentials of using this approach.

Verschiedene Faktoren wie z.B. der TechnologieFortschritt und steigende Kundenerwartungen bedingen, dass heutige industrielle Anforderungsdokumente immer komplexer und umfangreicher werden. Aktuelle Anforderungsdokumente von Mercedes Benz besitzen beispielsweise zum Teil uber 50.000 Doors-Objekte [1], dies entspricht uber 2000 Seiten Text. Durch dieses Wachstum steigt auch die Fehlerwahrscheinlichkeit in diesen Dokumenten und gleichzeitig stosen heute verwendete Review-Techniken an ihre Grenzen. Dies liegt neben der Grose des Pruflings auch an der grosen Anzahl zusatzlicher Dokumente (z.B. Normen, Kfz-Vorschriften), die wahrend des Reviews in Betracht gezogen werden mussen. Bei Mercedes Benz sind das 30-300 zusatzliche referenzierte Dokumente pro Anforderungsdokument [1]. Nach einer aktuellen Studie bei Mercedes Benz [2] sind besonders Fehler, die inhaltliche Qualitatskriterien, wie Konsistenz, Vollstandigkeit und Korrektheit betreffen, nur noch sehr schwer in Anforderungsdokumenten zu finden. Ein Ansatz zur Verbesserung des Review-Prozesses ist die Themenkarte (Details in [3], [4]). Dabei soll durch die Aufteilung in kleinere Bereiche inhaltlich zusammengehorender Anforderungen ein menschlicher Inspektor diese Anforderungen einfacher nach inhaltlichen Qualitatskriterien kontrollieren konnen, ohne jeweils die ganzen Dokumente durchsuchen zu mussen. Zum Beispiel werden wahrend des Reviews alle Anforderungen des Anforderungsdokuments und seiner referenzierten Dokumente gesammelt und dargestellt, die das Thema ”Unfallerkennung“ betreffen. Im weiteren Verlauf dieser Arbeit werden die ersten Ergebnisse und daraus gewonnen Erfahrungen aus Untersuchungen mit der Themenkarte vorgestellt.

One of the most common ways to ensure the quality of industry specifications is technical review, as the documents are typically written in natural language. Unfortunately, review activities tends to be less effective because of the increasing size and complexity of the specifications. For example at Mercedes-Benz, a specification and its referenced documents often sums up to 3.000 pages. Given such large specifications, reviewers have major problems in finding defects, especially consistency or completeness defects, between requirements with related information that are spread over large or even different documents. The classification of each requirement according to related topics is one possibility to improve the review efficiency. The reviewers can filter the overall document set according to particular topics to check consistency and completeness between the requirements within one topic. In this paper, we investigate whether this approach really can help to improve the review situation by presenting an experiment with students reviewing specifications originating from Mercedes-Benz with and without such a classification. In addition, we research the experiment participants’ acceptance of an automatic classification derived from text classification algorithms compared to a manual classification and how much manual effort is needed to improve the automatic classification. The results of this experiment, combined with the results of previous research, lead us to the conclusion that an automatic pre-classification is an useful aid in review tasks for finding consistency and completeness defects. Keywords-experimental software engineering; review; topic; topic landscape; classified requirements; inspection

Natural language (NL) requirement specifications are widely used in industry, but ensuring high quality in these specifications is not easy. This work investigates in an empirical study the typical defect type distributions in current NL requirement specifications. For this study, more than 5,800 review-protocol-entries that originate from reviews of real automotive specifications according to a quality-model were categorized by us at MercedesBenz. As a result, we obtained (a) a typical defect type distribution in NL specifications in the automotive domain, (b) correlations of quality criteria to defect severity, (c) indicators on ease of handling quality criteria in the review-process and (d) information on time needed for defect correction with respect to quality criteria. To validate the findings from the data analysis, we additionally conducted 15 interviews with quality managers. The results confirm quantitatively that the most critical and important quality criteria in the investigated NL requirement specifications are consistency, completeness, and correctness.

Reviews are the most common way to ensure quality in natural language (NL) requirements specifications. But with increasing size (up to 3,000 pages in the automotive domain) and complexity of the specification documents, the review task tends to be less effective. To improve the review task for large documents, one possible solution is the `topic landscape'. The idea of this approach is to introduce a pre-classification and clustering of requirements according to topics. In a first empirical study with eight students, we analyzed the effectiveness of the topic landscape approach. During this study, we encountered a general limitation of experiments with large requirements specifications, especially in external environments like universities. Industries have a strong demand on new approaches and methods to deal with large specifications. However, there is a growing gap between the number of requirements that can be examined during an empirical study and the number of requirements required to ensure results that are valid for real requirements specifications. This paper describes the conducted empirical study in detail and shows recognized problems concerning the limits of educational environments.