@article{BrandTroyaKrenzeretal.2022, author = {Brand, Markus and Troya, Joel and Krenzer, Adrian and Saßmannshausen, Zita and Zoller, Wolfram G. and Meining, Alexander and Lux, Thomas J. and Hann, Alexander}, title = {Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions}, series = {United European Gastroenterology Journal}, volume = {10}, journal = {United European Gastroenterology Journal}, number = {5}, doi = {10.1002/ueg2.12235}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-312708}, pages = {477-484}, year = {2022}, abstract = {Background The efficiency of artificial intelligence as computer-aided detection (CADe) systems for colorectal polyps has been demonstrated in several randomized trials. However, CADe systems generate many distracting detections, especially during interventions such as polypectomies. Those distracting CADe detections are often induced by the introduction of snares or biopsy forceps as the systems have not been trained for such situations. In addition, there are a significant number of non-false but not relevant detections, since the polyp has already been previously detected. All these detections have the potential to disturb the examiner's work. Objectives Development and evaluation of a convolutional neuronal network that recognizes instruments in the endoscopic image, suppresses distracting CADe detections, and reliably detects endoscopic interventions. Methods A total of 580 different examination videos from 9 different centers using 4 different processor types were screened for instruments and represented the training dataset (519,856 images in total, 144,217 contained a visible instrument). The test dataset included 10 full-colonoscopy videos that were analyzed for the recognition of visible instruments and detections by a commercially available CADe system (GI Genius, Medtronic). Results The test dataset contained 153,623 images, 8.84\% of those presented visible instruments (12 interventions, 19 instruments used). The convolutional neuronal network reached an overall accuracy in the detection of visible instruments of 98.59\%. Sensitivity and specificity were 98.55\% and 98.92\%, respectively. A mean of 462.8 frames containing distracting CADe detections per colonoscopy were avoided using the convolutional neuronal network. This accounted for 95.6\% of all distracting CADe detections. Conclusions Detection of endoscopic instruments in colonoscopy using artificial intelligence technology is reliable and achieves high sensitivity and specificity. Accordingly, the new convolutional neuronal network could be used to reduce distracting CADe detections during endoscopic procedures. Thus, our study demonstrates the great potential of artificial intelligence technology beyond mucosal assessment.}, language = {en} } @article{SchleeNeffSimoesetal.2022, author = {Schlee, Winfried and Neff, Patrick and Simoes, Jorge and Langguth, Berthold and Schoisswohl, Stefan and Steinberger, Heidi and Norman, Marie and Spiliopoulou, Myra and Schobel, Johannes and Hannemann, Ronny and Pryss, R{\"u}diger}, title = {Smartphone-guided educational counseling and self-help for chronic tinnitus}, series = {Journal of Clinical Medicine}, volume = {11}, journal = {Journal of Clinical Medicine}, number = {7}, issn = {2077-0383}, doi = {10.3390/jcm11071825}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-267295}, year = {2022}, abstract = {Tinnitus is an auditory phantom perception in the ears or head in the absence of a corresponding external stimulus. There is currently no effective treatment available that reliably reduces tinnitus. Educational counseling is a treatment approach that aims to educate patients and inform them about possible coping strategies. For this feasibility study, we implemented educational material and self-help advice in a smartphone app. Participants used the educational smartphone app unsupervised during their daily routine over a period of four months. Comparing the tinnitus outcome measures before and after smartphone-guided treatment, we measured changes in tinnitus-related distress, but not in tinnitus loudness. Improvements on the Tinnitus Severity numeric rating scale reached an effect size of 0.408, while the improvements on the Tinnitus Handicap Inventory (THI) were much smaller with an effect size of 0.168. An analysis of user behavior showed that frequent and intensive use of the app is a crucial factor for treatment success: participants that used the app more often and interacted with the app intensively reported a stronger improvement in the tinnitus. Between study allocation and final assessment, 26 of 52 participants dropped out of the study. Reasons for the dropouts and lessons for future studies are discussed in this paper.}, language = {en} } @article{SchwitterWackerWilkeetal.2012, author = {Schwitter, Juerg and Wacker, Christian M. and Wilke, Norbert and Al-Saadi, Nidal and Sauer, Ekkehart and Huettle, Kalman and Sch{\"o}nberg, Stefan O. and Debl, Kurt and Strohm, Oliver and Ahlstrom, Hakan and Dill, Thorsten and Hoebel, Nadja and Simor, Tamas}, title = {Superior diagnostic performance of perfusion-cardiovascular magnetic resonance versus SPECT to detect coronary artery disease: The secondary endpoints of the multicenter multivendor MR-IMPACT II (Magnetic Resonance Imaging for Myocardial Perfusion Assessment in Coronary Artery Disease Trial)}, series = {Journal of Cardiovascular Magnetic Resonance}, volume = {14}, journal = {Journal of Cardiovascular Magnetic Resonance}, number = {61}, organization = {MR-IMPACT investigators}, doi = {10.1186/1532-429X-14-61}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134256}, year = {2012}, abstract = {Background: Perfusion-cardiovascular magnetic resonance (CMR) is generally accepted as an alternative to SPECT to assess myocardial ischemia non-invasively. However its performance vs gated-SPECT and in sub-populations is not fully established. The goal was to compare in a multicenter setting the diagnostic performance of perfusion-CMR and gated-SPECT for the detection of CAD in various populations using conventional x-ray coronary angiography (CXA) as the standard of reference. Methods: In 33 centers (in US and Europe) 533 patients, eligible for CXA or SPECT, were enrolled in this multivendor trial. SPECT and CXA were performed within 4 weeks before or after CMR in all patients. Prevalence of CAD in the sample was 49\% and 515 patients received MR contrast medium. Drop-out rates for CMR and SPECT were 5.6\% and 3.7\%, respectively (ns). The study was powered for the primary endpoint of non-inferiority of CMR vs SPECT for both, sensitivity and specificity for the detection of CAD (using a single-threshold reading), the results for the primary endpoint were reported elsewhere. In this article secondary endpoints are presented, i.e. the diagnostic performance of CMR versus SPECT in subpopulations such as multi-vessel disease (MVD), in men, in women, and in patients without prior myocardial infarction (MI). For diagnostic performance assessment the area under the receiver-operator-characteristics-curve (AUC) was calculated. Readers were blinded versus clinical data, CXA, and imaging results. Results: The diagnostic performance (= area under ROC = AUC) of CMR was superior to SPECT (p = 0.0004, n = 425) and to gated-SPECT (p = 0.018, n = 253). CMR performed better than SPECT in MVD (p = 0.003 vs all SPECT, p = 0.04 vs gated-SPECT), in men (p = 0.004, n = 313) and in women (p = 0.03, n = 112) as well as in the non-infarct patients (p = 0.005, n = 186 in 1-3 vessel disease and p = 0.015, n = 140 in MVD). Conclusion: In this large multicenter, multivendor study the diagnostic performance of perfusion-CMR to detect CAD was superior to perfusion SPECT in the entire population and in sub-groups. Perfusion-CMR can be recommended as an alternative for SPECT imaging.}, language = {en} } @article{SperlichDeClerckZinneretal.2018, author = {Sperlich, Billy and De Clerck, Ine and Zinner, Christoph and Holmberg,, Hans-Christer and Wallmann-Sperlich, Birgit}, title = {Prolonged sitting interrupted by 6-min of high-intensity exercise: circulatory, metabolic, hormonal, thermal, cognitive, and perceptual responses}, series = {Frontiers in Physiology}, volume = {9}, journal = {Frontiers in Physiology}, number = {1279}, doi = {10.3389/fphys.2018.01279}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-177307}, year = {2018}, abstract = {The aim was to examine certain aspects of circulatory, metabolic, hormonal, thermoregulatory, cognitive, and perceptual responses while sitting following a brief session of high-intensity interval exercise. Twelve students (five men; age, 22 ± 2 years) performed two trials involving either simply sitting for 180 min (SIT) or sitting for this same period with a 6-min session of high-intensity exercise after 60 min (SIT+HIIT). At T\(_0\) (after 30 min of resting), T\(_1\) (after a 20-min breakfast), T\(_2\) (after sitting for 1 h), T\(_3\) (immediately after the HIIT), T\(_4\), T\(_5\), T\(_6\), and T\(_7\) (30, 60, 90, and 120 min after the HIIT), circulatory, metabolic, hormonal, thermoregulatory, cognitive, and perceptual responses were assessed. The blood lactate concentration (at T\(_3\)-T\(_5\)), heart rate (at T\(_3\)-T\(_6\)), oxygen uptake (at T\(_3\)-T\(_7\)), respiratory exchange ratio, and sensations of heat (T\(_3\)-T\(_5\)), sweating (T\(_3\), T\(_4\)) and odor (T\(_3\)), as well as perception of vigor (T\(_3\)-T\(_6\)), were higher and the respiratory exchange ratio (T\(_4\)-T\(_7\)) and mean body and skin temperatures (T\(_3\)) lower in the SIT+HIIT than the SIT trial. Levels of blood glucose and salivary cortisol, cerebral oxygenation, and feelings of anxiety/depression, fatigue or hostility, as well as the variables of cognitive function assessed by the Stroop test did not differ between SIT and SIT+HIIT. In conclusion, interruption of prolonged sitting with a 6-min session of HIIT induced more pronounced circulatory and metabolic responses and improved certain aspects of perception, without affecting selected hormonal, thermoregulatory or cognitive functions.}, language = {en} }