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2,244 results on '"Adam, Gerhard"'

12. Differentiation of acute non-ST elevation myocardial infarction and acute infarct-like myocarditis by visual pattern analysis: a head-to-head comparison of different cardiac MR techniques

Author

Jahnke, Charlotte, Sinn, Martin, Hot, Amra, Cavus, Ersin, Erley, Jennifer, Schneider, Jan, Chevalier, Celeste, Bohnen, Sebastian, Radunski, Ulf, Meyer, Mathias, Lund, Gunnar, Adam, Gerhard, Kirchhof, Paulus, Blankenberg, Stefan, Muellerleile, Kai, and Tahir, Enver

Published
2023
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14. Work expectations, their fulfillment, and exhaustion among radiologists of all career levels: what can be learned from the example of Germany

Author

Molwitz, Isabel, Kemper, Christoph, Stahlmann, Katharina, Oechtering, Thekla Helene, Sieren, Malte Maria, Afat, Saif, Gerwing, Mirjam, Bucher, Andreas Michael, Storz, Corinna, Langenbach, Marcel C., Reim, Martin, Lotz, Joachim, Zagrosek-Regitz, Vera, Can, Elif, Köhler, Daniel, Yamamura, Jin, Adam, Gerhard, Hamm, Bernd, and Keller, Sarah

Published
2023
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18. Unrecognized myocardial scar by late-gadolinium-enhancement cardiovascular magnetic resonance: Insights from the population-based Hamburg City Health Study

Author

Cavus, Ersin, Schneider, Jan N., di Carluccio, Eleonora, Ziegler, Andreas, Haack, Alena, Ojeda, Francisco, Chevalier, Celeste, Jahnke, Charlotte, Riedl, Katharina A., Radunski, Ulf K., Twerenbold, Raphael, Kirchhof, Paulus, Blankenberg, Stefan, Adam, Gerhard, Tahir, Enver, Lund, Gunnar K., and Muellerleile, Kai

Published
2024
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19. Smart Chest X-ray Worklist Prioritization using Artificial Intelligence: A Clinical Workflow Simulation

Author

Baltruschat, Ivo M., Steinmeister, Leonhard, Nickisch, Hannes, Saalbach, Axel, Grass, Michael, Adam, Gerhard, Knopp, Tobias, and Ittrich, Harald

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTAT) for critical findings in chest radiographs (CXRs). Furthermore, we investigate a method to counteract the effect of false negative predictions by AI -- resulting in an extremely and dangerously long RTAT, as CXRs are sorted to the end of the worklist. We developed a simulation framework that models the current workflow at a university hospital by incorporating hospital specific CXR generation rates, reporting rates and pathology distribution. Using this, we simulated the standard worklist processing "first-in, first-out" (FIFO) and compared it with a worklist prioritization based on urgency. Examination prioritization was performed by the AI, classifying eight different pathological findings ranked in descending order of urgency: pneumothorax, pleural effusion, infiltrate, congestion, atelectasis, cardiomegaly, mass and foreign object. Furthermore, we introduced an upper limit for the maximum waiting time, after which the highest urgency is assigned to the examination. The average RTAT for all critical findings was significantly reduced in all Prioritization-simulations compared to the FIFO-simulation (e.g. pneumothorax: 35.6 min vs. 80.1 min; p $<0.0001$), while the maximum RTAT for most findings increased at the same time (e.g. pneumothorax: 1293 min vs 890 min; p $<0.0001$). Our "upper limit" substantially reduced the maximum RTAT all classes (e.g. pneumothorax: 979 min vs. 1293 min / 1178 min; p $<0.0001$). Our simulations demonstrate that smart worklist prioritization by AI can reduce the average RTAT for critical findings in CXRs while maintaining a small maximum RTAT as FIFO.

Published
2020

26. When does Bone Suppression and Lung Field Segmentation Improve Chest X-Ray Disease Classification?

Author

Baltruschat, Ivo M., Steinmeister, Leonhard, Ittrich, Harald, Adam, Gerhard, Nickisch, Hannes, Saalbach, Axel, von Berg, Jens, Grass, Michael, and Knopp, Tobias

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Chest radiography is the most common clinical examination type. To improve the quality of patient care and to reduce workload, methods for automatic pathology classification have been developed. In this contribution we investigate the usefulness of two advanced image pre-processing techniques, initially developed for image reading by radiologists, for the performance of Deep Learning methods. First, we use bone suppression, an algorithm to artificially remove the rib cage. Secondly, we employ an automatic lung field detection to crop the image to the lung area. Furthermore, we consider the combination of both in the context of an ensemble approach. In a five-times re-sampling scheme, we use Receiver Operating Characteristic (ROC) statistics to evaluate the effect of the pre-processing approaches. Using a Convolutional Neural Network (CNN), optimized for X-ray analysis, we achieve a good performance with respect to all pathologies on average. Superior results are obtained for selected pathologies when using pre-processing, i.e. for mass the area under the ROC curve increased by 9.95%. The ensemble with pre-processed trained models yields the best overall results.

Published
2018

30. Towards Picogram Detection of Superparamagnetic Iron-Oxide Particles Using a Gradiometric Receive Coil

Author

Gräser, Matthias, Knopp, Tobias, Szwargulski, Patryk, Friedrich, Thomas, von Gladiss, Anselm, Kaul, Michael, Krishnan, Kannan M, Ittrich, Harald, Adam, Gerhard, and Buzug, Thorsten M.

Subjects
Physics - Medical Physics
Abstract

Superparamagnetic iron-oxide nanoparticles can be used in a variety of medical applications like vascular or targeted imaging. Magnetic particle imaging (MPI) is a promising tomographic imaging technique that allows visualizing the 3D nanoparticle distribution concentration in a non-invasive manner. The two main strengths of MPI are high temporal resolution and high sensitivity. While the first has been proven in the assessment of dynamic processes like cardiac imaging, it is unknown how far the detection limit of MPI can be lowered. Within this work, we will present a highly sensitive gradiometric receive-coil unit combined with a noise-matching network tailored for the measurement of mice. The setup is capable of detecting 5 ng of iron in vitro at 2.14 sec acquisition time. In terms of iron concentration we are able to detect 156 {\mu}g/L marking the lowest value that has been reported for an MPI scanner so far. In vivo MPI mouse images of a 512 ng bolus at 21.5 ms acquisition time allow for capturing the flow of an intravenously injected tracer through the heart of a mouse. Since it has been rather difficult to compare detection limits across MPI publications we propose guidelines improving the comparability of future MPI studies., Comment: 15 Pages, 7 Figures, V2: Changed the initials of Author Kannan M Krishnan, added two citations, corrected typos

Published
2017

31. Introduction

Author

Dosch, Helmut, Adam, Gerhard, Grosu, Anca-Ligia, Purschke, Matthias, Jost, Jürgen, Series Editor, Stock, Armin, Series Editor, and Busch, Uwe, editor

Published
2021
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32. Liver Cancer Trait Detection and Classification Through Machine Learning on Smart Mobile Devices

Author

Giannou, Olympia, Giannou, Anastasios D., Zazara, Dimitra E., Kleinschmidt, Dörte, Mummert, Tobias, Stüben, Björn Ole, Kaul, Michael Gerhard, Adam, Gerhard, Huber, Samuel, Pavlidis, Georgios, Angelov, Plamen, Series Editor, Kozma, Robert, Series Editor, Iliadis, Lazaros, editor, Macintyre, John, editor, Jayne, Chrisina, editor, and Pimenidis, Elias, editor

Published
2021
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34. Myocardial injury detected by T1 and T2 mapping on CMR predicts subsequent cancer therapy–related cardiac dysfunction in patients with breast cancer treated by epirubicin-based chemotherapy or left-sided RT

Author

Tahir, Enver, Azar, Manuella, Shihada, Sahar, Seiffert, Katharina, Goy, Yvonne, Beitzen-Heineke, Antonia, Molwitz, Isabel, Muellerleile, Kai, Stehning, Christian, Schön, Gerhard, Adam, Gerhard, Petersen, Cordula, Müller, Volkmar, and Lund, Gunnar K.

Published
2022
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40. Fat quantification in dual-layer detector spectral CT: How to handle iron overload, varying tube voltage and radiation dose Indices

Author

Molwitz, Isabel, primary, Campbell, Graeme Michael, additional, Knopp, Tobias, additional, Schubert, Niklas, additional, Erley, Jennifer, additional, Löser, Anastassia, additional, Adam, Gerhard, additional, Yamamura, Jin, additional, Fischer, Roland, additional, Ozga, Ann-Kathrin, additional, and Szwargulski, Patryk, additional

Published
2024
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42. Einleitung

Author

Dosch, Helmut, Adam, Gerhard, Grosu, Anca-Ligia, Purschke, Matthias, Breidbach, Olaf, Founding Editor, Jost, Jürgen, Founding Editor, Stock, Armin, Series Editor, and Busch, Uwe, editor

Published
2020
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43. Rationale and Design of the Hamburg City Health Study

Author

Jagodzinski, Annika, Johansen, Christoffer, Koch-Gromus, Uwe, Aarabi, Ghazal, Adam, Gerhard, Anders, Sven, Augustin, Matthias, der Kellen, Ramona B., Beikler, Thomas, Behrendt, Christian-Alexander, Betz, Christian S., Bokemeyer, Carsten, Borof, Katrin, Briken, Peer, Busch, Chia-Jung, Büchel, Christian, Brassen, Stefanie, Debus, Eike S., Eggers, Larissa, Fiehler, Jens, Gallinat, Jürgen, Gellißen, Simone, Gerloff, Christian, Girdauskas, Evaldas, Gosau, Martin, Graefen, Markus, Härter, Martin, Harth, Volker, Heidemann, Christoph, Heydecke, Guido, Huber, Tobias B., Hussein, Yassin, Kampf, Marvin O., von dem Knesebeck, Olaf, Konnopka, Alexander, König, Hans-Helmut, Kromer, Robert, Kubisch, Christian, Kühn, Simone, Loges, Sonja, Löwe, Bernd, Lund, Gunnar, Meyer, Christian, Nagel, Lina, Nienhaus, Albert, Pantel, Klaus, Petersen, Elina, Püschel, Klaus, Reichenspurner, Hermann, Sauter, Guido, Scherer, Martin, Scherschel, Katharina, Schiffner, Ulrich, Schnabel, Renate B., Schulz, Holger, Smeets, Ralf, Sokalskis, Vladislavs, Spitzer, Martin S., Terschüren, Claudia, Thederan, Imke, Thoma, Tom, Thomalla, Götz, Waschki, Benjamin, Wegscheider, Karl, Wenzel, Jan-Per, Wiese, Susanne, Zyriax, Birgit-Christiane, Zeller, Tanja, and Blankenberg, Stefan

Published
2020

46. Phenotyping spinal abnormalities in patients with Neurofibromatosis type 1 using whole-body MRI

Author

Well Lennart, Careddu Anna, Stark Maria, Farschtschi Said, Bannas Peter, Adam Gerhard, Mautner Victor-Felix, and Salamon Johannes

Subjects
Medicine, Science
Abstract

Abstract Neurofibromatosis Type 1 (NF1) has been reported to be associated with a variety of spinal abnormalities. The purpose of this study was to quantify the prevalence of spinal abnormalities in a collective of NF1 patients that is representative for the general NF1 population, to associate the co-appearance of spinal abnormalities with both NF1 and clinical symptoms and to investigate if different mutations of the NF1 gene affect the prevalence of these abnormalities. Retrospectively, 275 patients with NF1 and an age- and sex-matched collective of 262 patients were analyzed. The prevalence of spinal abnormalities was recorded. Mutational analysis of the NF1 gene was obtained in 235 NF1 patients. Associations between spinal abnormalities, clinical symptoms and genotype were investigated by binary logistic regression analysis. Prevalence of all spinal abnormalities was higher in NF1 patients than in the control group. Six characteristics of spinal abnormalities were significantly associated with NF1 (all p

Published
2021
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47. Fat quantification in dual-layer detector spectral CT: how to handle iron overload, varying tube voltage and radiation dose Indices

Author

Molwitz, Isabel, Campbell, Graeme Michael, Knopp, Tobias, Schubert, Niklas, Erley, Jennifer, Löser, Anastassia, Adam, Gerhard, Yamamura, Jin, Fischer, Roland F., Ozga, Ann-Kathrin, Szwargulski, Patryk, Molwitz, Isabel, Campbell, Graeme Michael, Knopp, Tobias, Schubert, Niklas, Erley, Jennifer, Löser, Anastassia, Adam, Gerhard, Yamamura, Jin, Fischer, Roland F., Ozga, Ann-Kathrin, and Szwargulski, Patryk

Abstract

Objectives Opposed to other spectral CT techniques, fat quantification in dual-layer detector CT (dlCT) has only recently been developed. The impact of concomitant iron overload and dlCT-specific protocol settings such as the dose right index (DRI), a measure of image noise and tube current, on dlCT fat quantification was unclear. Further, spectral information became newly available <120 kV. Therefore, this study's objective was to evaluate the impact of iron, changing tube voltage, and DRI on dlCT fat quantification. Material and methods Phantoms with 0 and 8mg/cm3 iron; 0 and 5mg/cm3 iodine; 0, 10, 20, 35, 50, and 100% fat and liver equivalent, respectively, were scanned with a dlCT (CT7500, Philips, the Netherlands) at 100kV/20DRI, 120kV/20DRI, 140kV/20DRI, and at 120kV/16DRI, 120kV/24DRI. Material decomposition was done for fat, liver, and iodine (A1); for fat, liver, and iron (A2); and for fat, liver, and combined reference values of iodine and iron (A3). All scans were analyzed with reference values from 120kV/20DRI. For statistics, the intraclass correlation coefficient (ICC) and Bland-Altman analyses were used. Results In phantoms with iron and iodine, results were best for A3 with a mean deviation to phantom fat of 1.3±2.6% (ICC 0.999 [95%-confidence interval 0.996-1]). The standard approach A1 yielded a deviation of -2.5±3.0% (0.998[0.994-0.999]), A2 of 6.1±4.8% (0.991[0.974-0.997]). With A3 and changing tube voltage, the maximal difference between quantified fat and the phantom ground truth occurred at 100kV with 4.6±2.1%. Differences between scans were largest between 100kV and 140kV (2.0%[-7.1-11.2]). The maximal difference of changing DRI occurred between 16 and 24 DRI with 0.4%[-2.2-3.0]. Conclusion For dlCT fat quantification in the presence of iron, material decomposition with combined reference values for iodine and iron delivers the most accurate results. Tube voltage-specific calibration of reference values is advisable while the impact of the DR

Published
2024

48. Real-time multi-contrast magnetic particle imaging for the detection of gastrointestinal bleeding

Author

Mohn, Fabian, Szwargulski, Patryk, Kaul, Michael, Graeser, Matthias, Mummert, Tobias, Krishnan, Kannan M., Knopp, Tobias, Adam, Gerhard, Salamon, Johannes, Riedel, Christoph, Mohn, Fabian, Szwargulski, Patryk, Kaul, Michael, Graeser, Matthias, Mummert, Tobias, Krishnan, Kannan M., Knopp, Tobias, Adam, Gerhard, Salamon, Johannes, and Riedel, Christoph

Abstract

Gastrointestinal bleeding, as a potentially life-threatening condition, is typically diagnosed by radiation-based imaging modalities like computed tomography or more invasively catheter-based angiography. Endoscopy enables examination of the upper gastrointestinal tract and the colon but not of the entire small bowel. Magnetic Particle Imaging (MPI) enables non-invasive, volumetric imaging without ionizing radiation. The aim of this study was to evaluate the feasibility of detecting gastrointestinal bleeding by single- and multi-contrast MPI using human-sized organs. A 3D-printed small bowel phantom and porcine small bowel specimens were prepared with a defect within the bowel wall as the source of a bleeding. For multi-contrast MPI, the bowel lumen was filled with an intestinal tracer representing an orally administered tracer. MPI was performed to evaluate the fluid exchange between the vascular compartment of the bowel wall and the lumen while a blood pool tracer was applied. Leakage of the blood pool tracer was observed to the bowel lumen. Multi-contrast MPI enabled co-registration of both tracers at the same location within the bowel lumen indicating gastrointestinal bleeding. Single- and multi-contrast MPI are feasible to visualize gastrointestinal bleeding. Therefore, MPI might emerge as a useful tool for radiation-free detection of bleeding within the entire gastrointestinal tract.

Published
2024

49. In vitro detection of gastrointestinal bleeding using single- and multi-contrast MPI

Author

Mohn, Fabian, Szwargulski, Patryk, Kaul, Michael Gerhard, Gräser, Matthias, Mummert, Tobias, Krishnan, Kannan M., Knopp, Tobias, Adam, Gerhard, Salamon, Johannes, Riedel, Christoph, Mohn, Fabian, Szwargulski, Patryk, Kaul, Michael Gerhard, Gräser, Matthias, Mummert, Tobias, Krishnan, Kannan M., Knopp, Tobias, Adam, Gerhard, Salamon, Johannes, and Riedel, Christoph

Abstract

Gastrointestinal (GI) bleeding is a potentially life-threatening condition that is typically diagnosed using radiation-based imaging modalities such as computed tomography (CT) or catheter-based angiography. Magnetic Particle Imaging (MPI) could provide non-invasive, real-time volumetric imaging without ionizing radiation in future human-sized scanners that covers the entire GI tract. We have developed a human-sized (3D printed) phantom that represents both the bowel lumen and the vascular compartment of the bowel wall. One version has a perforation between the two compartments and a control phantom does not. For single contrast MPI, we evaluate the fluid exchange between the two lumen by observing an administered blood pool tracer. For multi-contrast MPI, the intestinal lumen was filled with an intestinal tracer, which represents an orally administered tracer, to allow co-registration of both tracers at the same location. Both single-and multi-contrast MPI are feasible to visualize GI bleeding and MPI may prove to be a useful tool for radiation-free detection of bleeding throughout the GI tract.

Published
2024

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