Multi-phase postmortem CT angiography: recognizing technique-related artefacts and pitfalls

BACKGROUND AND PURPOSE Multi-phase postmortem CT angiography (MPMCTA) is increasingly being recognized as a valuable adjunct medicolegal tool to explore the vascular system. Adequate interpretation, however, requires knowledge about the most common technique-related artefacts. The purpose of this study was to identify and index the possible artefacts related to MPMCTA. MATERIAL AND METHODS An experienced radiologist blinded to all clinical and forensic data retrospectively reviewed 49 MPMCTAs. Each angiographic phase, i.e. arterial, venous and dynamic, was analysed separately to identify phase-specific artefacts based on location and aspect. RESULTS Incomplete contrast filling of the cerebral venous system was the most commonly encountered artefact, followed by contrast agent layering in the lumen of the thoracic aorta. Enhancement or so-called oedematization of the digestive system mucosa was also frequently observed. CONCLUSION All MPMCTA artefacts observed and described here are reproducible and easily identifiable. Knowledge about these artefacts is important to avoid misinterpreting them as pathological findings.

Digital multi-text editions from scratch to electronic performance. Transcription and collation routines transformed in a flexible database system

The poster demonstrates the preparatory steps of a digital multi-text edition that are abstracted from the experiences made in the Parzival Project, based at the University of Bern, the Berlin-Brandenburg Academy of Sciences and the University of Erlangen. This edition of Wolfram von Eschenbach’s German Grail novel, written shortly after 1200 and transmitted during several centuries in ca. hundred witnesses, has now been completed by more than a half of the textual corpus.

Novel emboli protection system during cardiac surgery: a multi-center, randomized, clinical trial.

BACKGROUND Stroke is a major cause of morbidity and mortality during open-heart surgery. Up to 60% of intraoperative cerebral events are emboli induced. This randomized, controlled, multicenter trial is the first human study evaluating the safety and efficacy of a novel aortic cannula producing simultaneous forward flow and backward suction for extracting solid and gaseous emboli from the ascending aorta and aortic arch upon their intraoperative release. METHODS Sixty-six patients (25 females; 68±10 years) undergoing elective aortic valve replacement surgery, with or without coronary artery bypass graft surgery, were randomized to the use of the CardioGard (CardioGard Medical, Or-Yehuda, Israel) Emboli Protection cannula ("treatment") or a standard ("control") aortic cannula. The primary endpoint was the volume of new brain lesions measured by diffusion-weighted magnetic resonance imaging (DW-MRI), performed preoperatively and postoperatively. Device safety was investigated by comparisons of complications rate, namely neurologic events, stroke, renal insufficiency and death. RESULTS Of 66 patients (34 in the treatment group), 51 completed the presurgery and postsurgery MRI (27 in the treatment group). The volume of new brain lesion for the treatment group was (mean±standard error of the mean) 44.00±64.00 versus 126.56±28.74 mm3 in the control group (p=0.004). Of the treatment group, 41% demonstrated new postoperative lesions versus 66% in the control group (p=0.03). The complication rate was comparable in both groups. CONCLUSIONS The CardioGard cannula is safe and efficient in use during open-heart surgery. Efficacy was demonstrated by the removal of a substantial amount of emboli, a significant reduction in the volume of new brain lesions, and the percentage of patients experiencing new brain lesions.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.