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.

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.

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.

Demands and stress before and during the COVID-19 pandemic of parents to children with autism spectrum disorder.

Introduction: Parents to children with Autism Spectrum Disorder (ASD) face diverse daily demands that can lead to stress. The aim of this study was to examine to which extent stress in parents to children with ASD can be explained by daily demands before and during the COVID-19 pandemic (after lockdowns; first half of 2022), and whether there are differences between the two time periods in this regard. Methods: Data from parents to children with ASD living in Germany from two independent questionnaire studies (before the pandemic: N = 168, during the pandemic: N = 105) were matched for comparability. Simple and multiple linear regression analyses were used to answer the research question. Results: Parental stress as well as all demands examined showed higher levels during the COVID-19 pandemic than before. Significant predictors of parental stress before and during the COVID-19 pandemic were (1) the daily demands to deal with the child's problem behavior, (2) the restriction of one's personal way of life, and (3) the challenge to cooperate with the partner. During the COVID-19 pandemic, the child's problem behavior was particularly relevant. It was also found that the demand to deal with stigmatizing reactions did not explain parental stress during the COVID-19 pandemic whereas before the pandemic it had been a significant predictor. Discussion: Although parental stress and the demands of daily life increased during the pandemic, most of the stress can be explained by the same demands. It is suggested that the increased levels may be due to an increase in the child's ASD symptomatology, which is why it is advisable to install therapeutic and care structures that prepare children with ASD for future crises.

Coping resources and stress due to demands in parents to children with autism spectrum disorder.

Introduction: Parents to children with autism spectrum disorder (ASD) are exposed to numerous demands in their daily lives and exhibit high levels of stress. The present study aims to find out which coping resources are mediators that help parents cope with these demands and which of those coping resources amplify or reduce stress arising from the demands. Studies often only focus on the connection between coping resources and stress without taking the demands into account at the same time. Methods: For this reason, a mediation model was set up to answer the research question. Data from a German questionnaire survey with N = 266 parents who have children with ASD (two to 23 years old) were used. Subjectively perceived demands in everyday life (scale "Parental demands in everyday life"), parental stress ("Parental Stress Inventory", based on Abidin's parenting stress model) and the following coping resources were collected: parental self-efficacy beliefs ("Parents' sense of competence questionnaire"), available social support of parents (scale "Availability of social support") and parental coping strategies (German version of the Brief COPE). Results: An exploratory factor analysis revealed four mediators: dysfunctional coping, functional coping, social support, and self-efficacy. The use of dysfunctional behavior and parental self-efficacy were found to be significant mediators that mediated between daily demands and parental stress. A direct effect of demands on parental stress was also found, implying partial mediation. The two factors of functional coping and support were not found to be significant mediators. Discussion: Key findings indicate that parental stress resulting from the daily demands of parenting children with ASD can be reduced by high parental self-efficacy and increased by dysfunctional coping. For practice, it can be deduced that dysfunctional coping strategies of parents to children with ASD should be reduced and parental self-efficacy should be strengthened in order to reduce stress which arises from the multiple demands in everyday life.

Change in Splenic Volume as a Surrogate Marker for Immunotherapy Response in Patients with Advanced Urothelial and Renal Cell Carcinoma-Evaluation of a Novel Approach of Fully Automated Artificial Intelligence Based Splenic Segmentation.

BACKGROUND: In the treatment of advanced urothelial (aUC) and renal cell carcinoma (aRCC), biomarkers such as PD-1 and PD-L1 are not robust prognostic markers for immunotherapy (IO) response. Previously, a significant association between IO and a change in splenic volume (SV) was described for several tumour entities. To the best of our knowledge, this study presents the first correlation of SV to IO in aUC and aRCC. METHODS: All patients with aUC (05/2017-10/2021) and aRCC (01/2012-05/2022) treated with IO at our academic centre were included. SV was measured at baseline, 3 and 9 months after initiation of IO using an in-house developed convolutional neural network-based spleen segmentation method. Uni- and multivariate Cox regression models for overall survival (OS) and progression-free survival (PFS) were used. RESULTS: In total, 35 patients with aUC and 30 patients with aRCC were included in the analysis. Lower SV at the three-month follow-up was significantly associated with improved OS in the aRCC group. CONCLUSIONS: We describe a new, innovative artificial intelligence-based approach of a radiological surrogate marker for IO response in aUC and aRCC which presents a promising new predictive imaging marker. The data presented implicate improved OS with lower follow-up SV in patients with aRCC.

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. The prevalences of urolithiasis in general and of nephro- and ureterolithasis were calculated. The distributions of age, sex, calculus size, density and location, and the number of ureteral and renal calculi were calculated. For ureterolithiasis, the impact of calculus characteristics on the degree of possible obstructive uropathy was calculated. RESULTS: The prevalence of urolithiasis in the investigated cohort was 72%. Of those patients, 25% had nephrolithiasis, 40% ureterolithiasis, and 35% combined nephro- and ureterolithiasis. The sex distribution was 2.3:1 (M:F). The median patient age was 50 years (IQR 36-62). The median number of calculi per patient was 1. The median size of calculi was 4 mm, and the median density was 734 HU. Of the patients who suffered from ureterolithiasis, 81% showed obstructive uropathy, with 2nd-degree uropathy being the most common. Calculus characteristics showed no impact on the degree of obstructive uropathy. CONCLUSION: SR-based data mining is a simple method by which to obtain epidemiologic data and distributions of disease characteristics, for the investigated cohort of urolithiasis patients. The added information can be useful for multiple purposes, such as clinical quality assurance, radiation protection, and scientific or economic investigations. To benefit from these, the consistent use of SR is mandatory. However, in clinical routine SR usage can be elaborate and requires radiologists to adapt.

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. Annual modality-specific SR usage was calculated for ultrasound, CT, and MRI. During the implementation process, we surveyed radiologists and clinical referring physicians concerning their views on reporting in radiology. RESULTS: As of December 2022, our reporting platform contained more than 22,000 structured reports. Use of the ten most common SR templates increased markedly since their implementation, leading to a mean SR usage of 77% in Q4 2022. The highest percentages of SR usage were shown for trauma CT, focussed assessment with ultrasound for trauma (FAST), and prostate MRI: 97%, 95%, and 92%, respectively, in 2022. Overall modality-specific SR usage was 17% for ultrasound, 13% for CT, and 6% for MRI in 2022. Both radiologists and referring physicians were more satisfied with structured reports and rated SR better than free-text reporting (FTR) on various attributes. CONCLUSIONS: The increasing SR usage during the period under review and the positive attitude towards SR among both radiologists and clinical referrers show that SR can be successfully implemented. We therefore encourage others to take this step in order to benefit from the advantages of SR. KEY POINTS: 1. Structured reporting usage increased markedly since its implementation at our institution in 2016. 2. Mean usage for the ten most popular structured reporting templates was 77% in 2022. 3. Both radiologists and referring physicians preferred structured reports over free-text reports. 4. Our data shows that structured reporting can be successfully implemented. 5. We strongly encourage others to implement structured reporting at their institutions.

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. Artificial intelligence and related fields, like natural language processing (NLP), offer enormous possibilities to facilitate the imaging workflow. Here, we aimed to use the potential of NLP to combine the advantages of SR and speech recognition. RESULTS: We developed a reporting tool that uses NLP to automatically convert dictated free text into a structured report. The tool comprises a task-oriented dialogue system, which assists the radiologist by sending visual feedback if relevant findings are missed. The system was developed on top of several NLP components and speech recognition. It extracts structured content from dictated free text and uses it to complete an SR template in RadLex terms, which is displayed in its user interface. The tool was evaluated for reporting of urolithiasis CTs, as a use case. It was tested using fictitious text samples about urolithiasis, and 50 original reports of CTs from patients with urolithiasis. The NLP recognition worked well for both, with an F1 score of 0.98 (precision: 0.99; recall: 0.96) for the test with fictitious samples and an F1 score of 0.90 (precision: 0.96; recall: 0.83) for the test with original reports. CONCLUSION: Due to its unique ability to integrate speech into SR, this novel tool could represent a major contribution to the future of reporting.

[Interdisciplinary case discussions]. / Interdisziplinäre Besprechungen.

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. Furthermore, the general conditions and forms of implementation of tumor conferences will be highlighted. Information technology (IT) tools for process automation and systems for assessing the course of tumor diseases will be presented. RESULTS: Detailed preparation of tumor conferences and clear communication of findings is essential. The radiological expertise in tumor conferences often leads to changes or adjustments of initially planned therapies. In addition to traditional face-to-face meetings, hybrid solutions have become established for tumor conferences in which the core team is on site and other participants (external referring physicians, internal participants outside the core team) are connected via video conference. Various systems have been established for assessing the course of tumor diseases. Due to its broad applicability, RECIST 1.1. is the most widely used. IT tools enable previously marked lesions to be displayed over time in a matrix view (lesion tracking). Artificial intelligence (AI) can also be used to automatically detect lesions and assess their volumes. CONCLUSION: Preparing and conducting tumor conferences is time-consuming for radiologists. IT tools can automate and thus facilitate the processes. Hybrid solutions combining face-to-face meetings and video conferences make it easier for external referring physicians to present their patients in tumor conferences.

[Image interpretation and the radiological report]. / Befundkommunikation.

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. To this end, current guidelines are summarized and clinical examples are presented. RESULTS: The radiological report is typically a written piece of free text prose and highly individualized regarding its quality, precision, and structure. In order to improve the understanding of the written report, additional material (e.g., annotations, images, tables) can be supplemented (multimedia-enhanced reporting). In terms of standardization, national and international radiological associations promote structured reporting in radiology. However, this is not without issues. CONCLUSION: Effective communication should improve patient care and it should be clear and provided in a timely manner. As communication in clinical reality is often hampered by various factors, internal standard operating procedures (SOPs) should be developed to improve communication workflows. to improve communication procedures.

Delayed development of basic numerical skills in children with developmental dyscalculia.

Research suggests that children with developmental dyscalculia (DD) have deficits in basic numerical skills. However, there is conflicting evidence on whether basic numerical skills in children with DD are qualitatively different from those in typically developing children (TD) or whether basic numerical skills development in children with DD is simply delayed. In addition, there are also competing hypotheses about deficits in basic numerical skills, assuming (1) a general deficit in representing numerosities (Approximate Number System, ANS), (2) specific deficits in an object-based attentional system (Object Tracking System, OTS), or (3) deficits in accessing numerosities from symbols (Access Deficit, AD). Hence, the purpose of this study was to investigate whether deficits in basic numerical skills in children with DD are more indicative of a developmental delay or a dyscalculia-specific qualitative deviation and whether these deficits result from (selective) impairment of core cognitive systems involved in numerical processing. To address this, we tested 480 children (68 DD and 412 TD) in the 2nd, 3rd, and 4th grades with different paradigms for basic numerical skills (subitizing, counting, magnitude comparison tasks, number sets, and number line estimation tasks). The results revealed that DD children's impairments did not indicate qualitatively different basic numerical skills but instead pointed to a specific developmental delay, with the exception of dot enumeration. This result was corroborated when comparing mathematical profiles of DD children in 4th grade and TD children in 2nd grade, suggesting that DD children were developmentally delayed and not qualitatively different. In addition, specific deficits in core markers of numeracy in children with DD supported the ANS deficit rather than the AD and OTS deficit hypothesis.

Structured reporting of CT scans of patients with trauma leads to faster, more detailed diagnoses: An experimental study.

PURPOSE: 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). METHOD: 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. RESULTS: 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. CONCLUSION: 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.

Two Dyscalculia Subtypes With Similar, Low Comorbidity Profiles: A Mixture Model Analysis.

Several studies have aimed to identify subtypes of dyscalculia. In many of these studies, either pre-defined groups (e.g., children with reading and mathematical difficulties vs. children with isolated mathematical difficulties) were analyzed regarding their cognitive profiles (top-down approach), or clusters of children with dyscalculia (CwD) were identified based on a narrow range of cognitive and mathematical skills (data-driven or bottom-up approach). However, it has remained difficult to establish robust subtypes of dyscalculia across studies. Against this background, we conducted a mixture model analysis in order to explore and identify subtypes of dyscalculia based on a broad range of variables (intelligence, reading fluency, working memory, attention, and various mathematical skills). The total sample comprised 174 elementary school CwD (IQ > 70; mathematical abilities: percentile rank <10), which consisted of two subsamples. The first subsample was based on a diagnostic test focusing on calculation (HRT 1-4; n = 71; 46 girls, 25 boys; age: M = 9.28 years, SD = 0.94) whereas the second subsample was based on a diagnostic test with a strong focus on basic numerical capacities (ZAREKI-R; n = 103; 78 girls, 25 boys; age: M = 8.94 years, SD = 1.05). Results provided convincing evidence for the existence of two subtypes in CwD: A slightly impaired subtype and a strongly impaired subtype. Subtypes differed most strongly regarding mathematical abilities, but the analyses suggest that differences in attention could also be a key factor. Therefore, comorbid attention difficulties seem to be a relevant factor that needs to be considered when establishing subtypes. Substantial intelligence differences between dyscalculia subtypes could not be found. Differences in working memory and reading fluency were negligible. Overall, the results seemed to be robust regardless of the diagnostic test used for assessing dyscalculia. When planning interventions for CwD, the existence of a subtype with substantial attention problems should be kept in mind.

The co-occurrence of Attention-Deficit/Hyperactivity Disorder and mathematical difficulties: An investigation of the role of basic numerical skills.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) and dyscalculia, also called mathematics disorder, frequently co-occur, yet the etiology of this comorbidity is poorly understood. AIMS: This study investigated whether impairments in the understanding of numbers and magnitudes (basic numerical skills) are a unique risk factor for mathematical difficulties (MD) or a shared risk factor that could help to explain the association between ADHD and MD. METHODS AND PROCEDURES: Basic numerical skills were assessed with eight subtests in children (age 6-10 years, N = 86) with clinically significant ADHD symptoms and/or MD and typically developing children (control group). This double dissociation design allowed to test for main and interaction effects of ADHD and MD using both classical and Bayesian analysis of variance (ANOVA). OUTCOMES AND RESULTS: Children with MD were impaired in transcoding, complex number and magnitude comparison, and arithmetic fact retrieval. They were not impaired in tasks assessing core markers of numeracy, which might be explained by the sample including children with mathematical difficulties instead of a diagnosed dyscalculia. ADHD was not associated with deficits in any of the tasks. The evidence for an additive combination of cognitive profiles was weak. CONCLUSIONS AND IMPLICATIONS: Impairments in basic numerical skills are uniquely associated with MD and do not represent a shared risk factor for ADHD symptoms and MD.

Attitudes Toward Artificial Intelligence Among Radiologists, IT Specialists, and Industry.

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.

Early results of a low-profile stent-graft for thoracic endovascular aortic repair.

PURPOSE: To assess outcomes of a low-profile thoracic stent-graft in the treatment of thoracic aortic pathologies. METHODS: A retrospective analysis of all consecutive patients with aortic thoracic pathologies treated with the RelayPro device in two university hospitals between October 2018 and July 2019. RESULTS: 23 patients (65% men; mean age 63.4 ± 15 years) were treated. Pathologies included aortic dissections (n = 10), 5 residual type A (22%) and 5 type B (22%), 6 degenerative aortic aneurysms (26%), 4 penetrating aortic ulcers (17%), and aortic erosion, intramural hematoma and aortic rupture (n = 1 and 4% in each case). Two cases (9%) were emergent and two urgent. Proximal landing was achieved in zones 0 (4%), 1 (4%), 2 (43%), and 3 (26%). Five grafts were frozen elephant trunk extensions. Technical success was 100% with accurate device deployment in the intended landing zone of the aortic arch in all 23 patients and with no Ia/III endoleaks and three (13%) type II endoleaks. Apposition was adequate in 96%. Two patients had post-implantation syndromes (one fever, one leukocytosis). Mean follow-up was 11.6 ± 3.7 months (range, 2-16) with no other complications, secondary interventions or conversions to open surgery. There was no 30-day mortality and no aortic-related mortality; all-cause mortality was 4% during follow-up. CONCLUSION: A 3-4 French reduced profile in the current generation of stent-grafts facilitates TEVAR particularly in patients with smaller vessels access. Early safety and effectiveness outcomes are favorable, even in endpoints such as deployment accuracy and apposition which may be surrogates for longer-term clinical success and durability.

Modeling Responses and Response Times in Tests With the Hierarchical Model and the Three-Parameter Lognormal Distribution.

The hierarchical model of van der Linden is the most popular model for responses and response times in tests. It is composed of two separate submodels-one for the responses and one for the response times-that are joined at a higher level. The submodel for the response times is based on the lognormal distribution. The lognormal distribution is a skew distribution with a support from zero to infinity. Such a support is unrealistic as the solution process demands a minimal processing time that sets a response time threshold. Ignoring this response time threshold misspecifies the model and threatens the validity of model-based inferences. In this article, the response time model of van der Linden is replaced by a model that is based on the three-parameter lognormal distribution. The three-parameter lognormal distribution extends the lognormal distribution by an additional location parameter that bounds the support away from zero. Two different approaches to model fitting are proposed and evaluated with regard to parameter recovery in a simulation study. The extended model is applied to two data sets. In both data sets, the extension improves the fit of the hierarchical model.

Computer tomographic analysis of anatomic characteristics of the ulna - essential parameters for preshaped implants.

PURPOSE: Anatomically preshaped implants are needed for exact restoration of the anatomy after fractures of the proximal ulna and ulnar shaft, which enables a good functional outcome. Aim of this computed tomographic analysis was to identify specific characteristics of the ulna. The data serve for the development of a new intramedullary implant for stabilisation of proximal and diaphyseal ulna fractures. METHODS: With a standardized research method 100 CT scans of the ulna were evaluated regarding anatomic parameters like width of the medullary canal, proximal ulna dorsal angulation and varus angulation. Also, correlations of these parameters were analyzed statistically. RESULTS: The mean proximal ulna dorsal angulation (PUDA) was 6.4° (SD 2.8°), while the mean varus angulation of the proximal ulna was 12.4° (SD 3.3°). The length of the ulna bone was 253.6 mm (SD 19.9 mm) on average. The average minimum diameter of the medullary canal was 4.2 mm (SD 1.1 mm) located at 141.3 mm (SD 19.7 mm) from the olecranon tip. There is a positive correlation between age and minimum diameter in our patient cohort (p< 0.001). CONCLUSION: Our study described the anatomy of the proximal ulna and the ulna shaft with a reproducible research method in a representative patient cohort. The knowledge of the evaluated anatomic parameters can lead to an improvement of any implant design for the fixation of proximal and diaphyseal ulna fractures.

Towards data-driven medical imaging using natural language processing in patients with suspected urolithiasis.

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 < 0.001). 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.