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Adams LC, Bressem KK, Ziegeler K, Vahldiek JL, Poddubnyy D. Artificial intelligence to analyze magnetic resonance imaging in rheumatology. Joint Bone Spine 2024; 91:105651. [PMID: 37797827 DOI: 10.1016/j.jbspin.2023.105651] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 08/29/2023] [Accepted: 09/26/2023] [Indexed: 10/07/2023]
Abstract
Rheumatic disorders present a global health challenge, marked by inflammation and damage to joints, bones, and connective tissues. Accurate, timely diagnosis and appropriate management are crucial for favorable patient outcomes. Magnetic resonance imaging (MRI) has become indispensable in rheumatology, but interpretation remains laborious and variable. Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), offers a means to improve and advance MRI analysis. This review examines current AI applications in rheumatology MRI analysis, addressing diagnostic support, disease classification, activity assessment, and progression monitoring. AI demonstrates promise, with high sensitivity, specificity, and accuracy, achieving or surpassing expert performance. The review also discusses clinical implementation challenges and future research directions to enhance rheumatic disease diagnosis and management.
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Affiliation(s)
- Lisa C Adams
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany.
| | - Keno K Bressem
- Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Katharina Ziegeler
- Department of Hematology, Oncology , and Cancer Immunology, Campus Charité Mitte, Charité Universitätsmedizin Berlin, Germany; Evidia Radiologie am Rheumazentrum Ruhrgebiet, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Denis Poddubnyy
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany
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Busch F, Xu L, Sushko D, Weidlich M, Truhn D, Müller-Franzes G, Heimer MM, Niehues SM, Makowski MR, Hinsche M, Vahldiek JL, Aerts HJ, Adams LC, Bressem KK. Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs. Comput Methods Programs Biomed 2023; 234:107505. [PMID: 37003043 DOI: 10.1016/j.cmpb.2023.107505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 02/17/2023] [Accepted: 03/21/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND AND OBJECTIVES Bedside chest radiographs (CXRs) are challenging to interpret but important for monitoring cardiothoracic disease and invasive therapy devices in critical care and emergency medicine. Taking surrounding anatomy into account is likely to improve the diagnostic accuracy of artificial intelligence and bring its performance closer to that of a radiologist. Therefore, we aimed to develop a deep convolutional neural network for efficient automatic anatomy segmentation of bedside CXRs. METHODS To improve the efficiency of the segmentation process, we introduced a "human-in-the-loop" segmentation workflow with an active learning approach, looking at five major anatomical structures in the chest (heart, lungs, mediastinum, trachea, and clavicles). This allowed us to decrease the time needed for segmentation by 32% and select the most complex cases to utilize human expert annotators efficiently. After annotation of 2,000 CXRs from different Level 1 medical centers at Charité - University Hospital Berlin, there was no relevant improvement in model performance, and the annotation process was stopped. A 5-layer U-ResNet was trained for 150 epochs using a combined soft Dice similarity coefficient (DSC) and cross-entropy as a loss function. DSC, Jaccard index (JI), Hausdorff distance (HD) in mm, and average symmetric surface distance (ASSD) in mm were used to assess model performance. External validation was performed using an independent external test dataset from Aachen University Hospital (n = 20). RESULTS The final training, validation, and testing dataset consisted of 1900/50/50 segmentation masks for each anatomical structure. Our model achieved a mean DSC/JI/HD/ASSD of 0.93/0.88/32.1/5.8 for the lung, 0.92/0.86/21.65/4.85 for the mediastinum, 0.91/0.84/11.83/1.35 for the clavicles, 0.9/0.85/9.6/2.19 for the trachea, and 0.88/0.8/31.74/8.73 for the heart. Validation using the external dataset showed an overall robust performance of our algorithm. CONCLUSIONS Using an efficient computer-aided segmentation method with active learning, our anatomy-based model achieves comparable performance to state-of-the-art approaches. Instead of only segmenting the non-overlapping portions of the organs, as previous studies did, a closer approximation to actual anatomy is achieved by segmenting along the natural anatomical borders. This novel anatomy approach could be useful for developing pathology models for accurate and quantifiable diagnosis.
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Affiliation(s)
- Felix Busch
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany; Department of Anesthesiology, Division of Operative Intensive Care Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
| | - Lina Xu
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Dmitry Sushko
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Matthias Weidlich
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Daniel Truhn
- Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany
| | - Gustav Müller-Franzes
- Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany
| | - Maurice M Heimer
- Department of Radiology, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Stefan M Niehues
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Marcus R Makowski
- Department of Radiology, Technical University of Munich, Munich, Germany
| | - Markus Hinsche
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Hugo Jwl Aerts
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Departments of Radiation Oncology and Radiology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA, USA; Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands
| | - Lisa C Adams
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Keno K Bressem
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA
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Bressem KK, Adams LC, Proft F, Hermann KGA, Diekhoff T, Spiller L, Niehues SM, Makowski MR, Hamm B, Protopopov M, Rios Rodriguez V, Haibel H, Rademacher J, Torgutalp M, Lambert RG, Baraliakos X, Maksymowych WP, Vahldiek JL, Poddubny D. Deep Learning Detects Changes Indicative of Axial Spondyloarthritis at MRI of Sacroiliac Joints. Radiology 2023; 307:e239007. [PMID: 37093751 DOI: 10.1148/radiol.239007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
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Haibel H, Poddubnyy D, Angermair S, Allers K, Vahldiek JL, Schumann M, Schneider T. Successful treatment of severe COVID-19 pneumonia, a case series with simultaneous interleukin-1 and interleukin-6 blockade with 1-month follow-up. Ther Adv Musculoskelet Dis 2022; 14:1759720X221116405. [PMID: 36071720 PMCID: PMC9444821 DOI: 10.1177/1759720x221116405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 07/12/2022] [Indexed: 11/17/2022] Open
Abstract
Interleukin (IL)-6 and IL-1 blockade showed beneficial results in patients with severe COVID-19 pneumonia and evidence of cytokine release at the early disease stage. Here, we report outcomes of open-label therapy with a combination of blocking IL-6 with tocilizumab 8 mg/kg up to 800 mg and IL-1 receptor antagonist anakinra 100–300 mg over 3–5 days. Thirty-one adult patients with severe COVID-19 pneumonia and signs of cytokine release, mean age 54 (30–79) years, 5 female, 26 male, and mean symptom duration 6 (3–10) days were treated. Patients with more than 10 days of symptoms, evidence of bacterial infection/elevated procalcitonin and other severe lung diseases were excluded. Computed tomography (CT) scans of the lung were performed initially and after 1 month; inflammatory activity was assessed on a scale 0–25. Twenty-five patients survived without intubation and mechanical lung ventilation, two patients died. C-reactive protein decreased in 19/31 patients to normal ranges. The mean activity CT score decreased from 14 (8–20) to 6 (0–16, n = 16). In conclusion, most of our patients recovered fast and sustained, indicating that early interruption of cytokine release might be very effective in preventing patients from mechanical ventilation, death, and long-term damage.
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Affiliation(s)
- Hildrun Haibel
- Department of Gastroenterology, Infectiology and Rheumatology, Charité-University Medicine Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Denis Poddubnyy
- Department of Gastroenterology, Infectiology and Rheumatology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan Angermair
- Department of Anestesiology and Surgical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Kristina Allers
- Department of Gastroenterology, Infectiology and Rheumatology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Michael Schumann
- Department of Gastroenterology, Infectiology and Rheumatology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Thomas Schneider
- Department of Gastroenterology, Infectiology and Rheumatology, Charité-Universitätsmedizin Berlin, Berlin, Germany
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Bressem KK, Adams LC, Proft F, Hermann KGA, Diekhoff T, Spiller L, Niehues SM, Makowski MR, Hamm B, Protopopov M, Rios Rodriguez V, Haibel H, Rademacher J, Torgutalp M, Lambert RG, Baraliakos X, Maksymowych WP, Vahldiek JL, Poddubnyy D. Deep Learning Detects Changes Indicative of Axial Spondyloarthritis at MRI of Sacroiliac Joints. Radiology 2022; 305:655-665. [PMID: 35943339 DOI: 10.1148/radiol.212526] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background MRI is frequently used for early diagnosis of axial spondyloarthritis (axSpA). However, evaluation is time-consuming and requires profound expertise because noninflammatory degenerative changes can mimic axSpA, and early signs may therefore be missed. Deep neural networks could function as assistance for axSpA detection. Purpose To create a deep neural network to detect MRI changes in sacroiliac joints indicative of axSpA. Materials and Methods This retrospective multicenter study included MRI examinations of five cohorts of patients with clinical suspicion of axSpA collected at university and community hospitals between January 2006 and September 2020. Data from four cohorts were used as the training set, and data from one cohort as the external test set. Each MRI examination in the training and test sets was scored by six and seven raters, respectively, for inflammatory changes (bone marrow edema, enthesitis) and structural changes (erosions, sclerosis). A deep learning tool to detect changes indicative of axSpA was developed. First, a neural network to homogenize the images, then a classification network were trained. Performance was evaluated with use of area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. P < .05 was considered indicative of statistically significant difference. Results Overall, 593 patients (mean age, 37 years ± 11 [SD]; 302 women) were studied. Inflammatory and structural changes were found in 197 of 477 patients (41%) and 244 of 477 (51%), respectively, in the training set and 25 of 116 patients (22%) and 26 of 116 (22%) in the test set. The AUCs were 0.94 (95% CI: 0.84, 0.97) for all inflammatory changes, 0.88 (95% CI: 0.80, 0.95) for inflammatory changes fulfilling the Assessment of SpondyloArthritis international Society definition, and 0.89 (95% CI: 0.81, 0.96) for structural changes indicative of axSpA. Sensitivity and specificity on the external test set were 22 of 25 patients (88%) and 65 of 91 patients (71%), respectively, for inflammatory changes and 22 of 26 patients (85%) and 70 of 90 patients (78%) for structural changes. Conclusion Deep neural networks can detect inflammatory or structural changes to the sacroiliac joint indicative of axial spondyloarthritis at MRI. © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Keno K Bressem
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Lisa C Adams
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Fabian Proft
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Kay Geert A Hermann
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Torsten Diekhoff
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Laura Spiller
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Stefan M Niehues
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Marcus R Makowski
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Bernd Hamm
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Mikhail Protopopov
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Valeria Rios Rodriguez
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Hildurn Haibel
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Judith Rademacher
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Murat Torgutalp
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Robert G Lambert
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Xenofon Baraliakos
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Walter P Maksymowych
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Janis L Vahldiek
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
| | - Denis Poddubnyy
- From the Institute for Radiology (K.K.B., L.C.A., K.G.A.H., T.D., S.M.N., B.H., J.L.V.) and Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine) (F.P., L.S., M.P., V.R.R., H.H., J.R., M.T., D.P.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany (K.K.B., L.C.A., J.R.); Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Munich, Germany (M.R.M.); Department of Medicine, University of Alberta, Edmonton, Alberta, Canada (R.G.L., W.P.M.); Rheumazentrum Ruhrgebiet Herne, Ruhr University Bochum, Germany (X.B.); and Epidemiology Unit, German Rheumatism Research Centre, Berlin, Germany (D.P.)
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6
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Poch FGM, Eminger KJ, Neizert CA, Geyer B, Rieder C, Ballhausen H, Niehues SM, Vahldiek JL, Lehmann KS. Cooling Effects Occur in Hepatic Microwave Ablation At Low Vascular Flow Rates and in Close Proximity to Liver Vessels - Ex Vivo. Surg Innov 2022; 29:705-715. [PMID: 35227134 DOI: 10.1177/15533506221074619] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background. The impact of vascular cooling effects in hepatic microwave ablation (MWA) is controversially discussed. The objective of this study was a systematic assessment of vascular cooling effects in hepatic MWA ex vivo. Methods. Microwave ablations were performed in fresh porcine liver ex vivo with a temperature-controlled MWA generator (902-928 MHz) and a non-cooled 14-G-antenna. Energy input was set to 9.0 kJ. Hepatic vessels were simulated by glass tubes. Three different vessel diameters (3.0, 5.0, 8.0 mm) and vessel to antenna distances (5, 10, 20 mm) were examined. Vessels were perfused with saline solution at nine different flow rates (0-500 mL/min). Vascular cooling effects were assessed at the largest cross-sectional ablation area. A quantitative and semi-quantitative/morphologic analysis was carried out. Results. 228 ablations were performed. Vascular cooling effects were observed at close (5 mm) and medium (10 mm) antenna to vessel distances (P < .05). Vascular cooling effects occurred around vessels with flow rates ≥1.0 mL/min (P < .05) and a vessel diameter ≥3 mm (P < .05). Higher flow rates did not result in more distinct cooling effects (P > .05). No cooling effects were measured at large (20 mm) antenna to vessel distances (P > .05). Conclusion. Vascular cooling effects occur in hepatic MWA and should be considered in treatment planning. The vascular cooling effect was mainly affected by antenna to vessel distance. Vessel diameter and vascular flow rate played a minor role in vascular cooling effects.
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Affiliation(s)
- Franz G M Poch
- Department of General and Visceral Surgery-Campus Benjamin Franklin, 9373Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Katharina J Eminger
- Department of General and Visceral Surgery-Campus Benjamin Franklin, 9373Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Christina A Neizert
- Department of General and Visceral Surgery-Campus Benjamin Franklin, 9373Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Beatrice Geyer
- Department of General and Visceral Surgery-Campus Benjamin Franklin, 9373Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Christian Rieder
- Institute for Digital Medicine, Fraunhofer MEVIS, Bremen, Germany
| | - Hanne Ballhausen
- Institute for Digital Medicine, Fraunhofer MEVIS, Bremen, Germany
| | - Stefan M Niehues
- Department of Radiology-Campus Benjamin Franklin, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology-Campus Benjamin Franklin, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Kai S Lehmann
- Department of General and Visceral Surgery-Campus Benjamin Franklin, 9373Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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7
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Thieß HM, Bressem KK, Adams L, Böning G, Vahldiek JL, Niehues SM. Do submillisievert-chest CT protocols impact diagnostic quality in suspected COVID-19 patients? Acta Radiol Open 2022; 11:20584601211073864. [PMID: 35096416 PMCID: PMC8796096 DOI: 10.1177/20584601211073864] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 12/29/2021] [Indexed: 12/21/2022] Open
Abstract
Background During the ongoing global SARS-CoV-2 pandemic, there is a high demand for quick and reliable methods for early identification of infected patients. Due to its widespread availability, chest-CT is commonly used to detect early pulmonary manifestations and for follow-ups. Purpose This study aims to analyze image quality and reproducibility of readings of scans using low-dose chest CT protocols in patients suspected of SARS-CoV-2 infection. Materials and Methods Two radiologists retrospectively analyzed 100 low-dose chest CT scans of patients suspected of SARS-CoV-2 infection using two protocols on devices from two vendors regarding image quality based on a Likert scale. After 3 weeks, quality ratings were repeated to allow for analysis of intra-reader in addition to the inter-reader agreement. Furthermore, radiation dose and presence as well as distribution of radiological features were noted. Results The exams’ effective radiation doses were in median in the submillisievert range (median of 0.53 mSv, IQR: 0.35 mSv). While most scans were rated as being of optimal quality, 38% of scans were scored as suboptimal, yet only one scan was non-diagnostic. Inter-reader and intra-reader reliability showed almost perfect agreement with Cohen’s kappa of 0.82 and 0.87. Conclusion Overall, in this study, we present two protocols for submillisievert low-dose chest CT demonstrating appropriate or better image quality with almost perfect inter-reader and intra-reader agreement in patients suspected of SARS-CoV-2 infection.
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Affiliation(s)
- Hans-Martin Thieß
- Department of Radiology, Charité Universitätsmedizin Berlin Campus Benjamin Franklin, Berlin, Germany
| | - Keno K Bressem
- Department of Radiology, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Lisa Adams
- Department of Radiology, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Böning
- Department of Radiology, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan M Niehues
- Klinik für Radiologie, Charité-Universitätsmedizin Berlin, Berlin, Germany
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8
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Bressem KK, Adams LC, Gaudin RA, Tröltzsch D, Hamm B, Makowski MR, Schüle CY, Vahldiek JL, Niehues SM. Highly accurate classification of chest radiographic reports using a deep learning natural language model pre-trained on 3.8 million text reports. Bioinformatics 2021; 36:5255-5261. [PMID: 32702106 DOI: 10.1093/bioinformatics/btaa668] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/25/2020] [Accepted: 07/17/2020] [Indexed: 01/19/2023] Open
Abstract
MOTIVATION The development of deep, bidirectional transformers such as Bidirectional Encoder Representations from Transformers (BERT) led to an outperformance of several Natural Language Processing (NLP) benchmarks. Especially in radiology, large amounts of free-text data are generated in daily clinical workflow. These report texts could be of particular use for the generation of labels in machine learning, especially for image classification. However, as report texts are mostly unstructured, advanced NLP methods are needed to enable accurate text classification. While neural networks can be used for this purpose, they must first be trained on large amounts of manually labelled data to achieve good results. In contrast, BERT models can be pre-trained on unlabelled data and then only require fine tuning on a small amount of manually labelled data to achieve even better results. RESULTS Using BERT to identify the most important findings in intensive care chest radiograph reports, we achieve areas under the receiver operation characteristics curve of 0.98 for congestion, 0.97 for effusion, 0.97 for consolidation and 0.99 for pneumothorax, surpassing the accuracy of previous approaches with comparatively little annotation effort. Our approach could therefore help to improve information extraction from free-text medical reports. Availability and implementationWe make the source code for fine-tuning the BERT-models freely available at https://github.com/fast-raidiology/bert-for-radiology. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Keno K Bressem
- Department of Radiology, Charité, Berlin 12203, Germany.,Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10117, Germany
| | - Lisa C Adams
- Department of Radiology, Charité, Berlin 12203, Germany.,Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10117, Germany
| | - Robert A Gaudin
- Department of Oral- and Maxillofacial Surgery, Charité, Berlin 12203, Germany
| | - Daniel Tröltzsch
- Department of Oral- and Maxillofacial Surgery, Charité, Berlin 12203, Germany
| | - Bernd Hamm
- Department of Radiology, Charité, Berlin 12203, Germany
| | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich 81675, Germany
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9
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Poddubnyy D, Proft F, Hermann KGA, Spiller L, Niehues SM, Adams LC, Protopopov M, Rios Rodriguez V, Muche B, Rademacher J, Torgutalp M, Bressem KK, Vahldiek JL. Detection of radiographic sacroiliitis with an artificial neural network in patients with suspicion of axial spondyloarthritis. Rheumatology (Oxford) 2021; 60:5868-5869. [PMID: 34363456 DOI: 10.1093/rheumatology/keab636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/28/2021] [Accepted: 08/02/2021] [Indexed: 11/12/2022] Open
Affiliation(s)
- Denis Poddubnyy
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,Epidemiology unit, German Rheumatism Research Centre, Berlin, Germany
| | - Fabian Proft
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Kay-Geert A Hermann
- Department of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Laura Spiller
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Stefan M Niehues
- Department of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Lisa C Adams
- Department of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Mikhail Protopopov
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Valeria Rios Rodriguez
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Burkhard Muche
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Judith Rademacher
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Murat Torgutalp
- Department of Gastroenterology, Infectious Diseases and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Keno K Bressem
- Department of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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10
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Niehues SM, Adams LC, Gaudin RA, Erxleben C, Keller S, Makowski MR, Vahldiek JL, Bressem KK. Deep-Learning-Based Diagnosis of Bedside Chest X-ray in Intensive Care and Emergency Medicine. Invest Radiol 2021; 56:525-534. [PMID: 33826549 DOI: 10.1097/rli.0000000000000771] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Validation of deep learning models should separately consider bedside chest radiographs (CXRs) as they are the most challenging to interpret, while at the same time the resulting diagnoses are important for managing critically ill patients. Therefore, we aimed to develop and evaluate deep learning models for the identification of clinically relevant abnormalities in bedside CXRs, using reference standards established by computed tomography (CT) and multiple radiologists. MATERIALS AND METHODS In this retrospective study, a dataset consisting of 18,361 bedside CXRs of patients treated at a level 1 medical center between January 2009 and March 2019 was used. All included CXRs occurred within 24 hours before or after a chest CT. A deep learning algorithm was developed to identify 8 findings on bedside CXRs (cardiac congestion, pleural effusion, air-space opacification, pneumothorax, central venous catheter, thoracic drain, gastric tube, and tracheal tube/cannula). For the training dataset, 17,275 combined labels were extracted from the CXR and CT reports by a deep learning natural language processing (NLP) tool. In case of a disagreement between CXR and CT, human-in-the-loop annotations were used. The test dataset consisted of 583 images, evaluated by 4 radiologists. Performance was assessed by area under the receiver operating characteristic curve analysis, sensitivity, specificity, and positive predictive value. RESULTS Areas under the receiver operating characteristic curve for cardiac congestion, pleural effusion, air-space opacification, pneumothorax, central venous catheter, thoracic drain, gastric tube, and tracheal tube/cannula were 0.90 (95% confidence interval [CI], 0.87-0.93; 3 radiologists on the receiver operating characteristic [ROC] curve), 0.95 (95% CI, 0.93-0.96; 3 radiologists on the ROC curve), 0.85 (95% CI, 0.82-0.89; 1 radiologist on the ROC curve), 0.92 (95% CI, 0.89-0.95; 1 radiologist on the ROC curve), 0.99 (95% CI, 0.98-0.99), 0.99 (95% CI, 0.98-0.99), 0.98 (95% CI, 0.97-0.99), and 0.99 (95% CI, 0.98-1.00), respectively. CONCLUSIONS A deep learning model used specifically for bedside CXRs showed similar performance to expert radiologists. It could therefore be used to detect clinically relevant findings during after-hours and help emergency and intensive care physicians to focus on patient care.
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Affiliation(s)
| | - Lisa C Adams
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH), Department of Radiology, Berlin, Germany
| | - Robert A Gaudin
- Institute of Oral and Maxillofacial Surgery, Charité, Berlin, Germany
| | | | - Sarah Keller
- From the Department of Radiology, Charité, Berlin, Germany
| | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, Technical Universtity of Munich, School of Medicine, Munich, Germany
| | | | - Keno K Bressem
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH), Department of Radiology, Berlin, Germany
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11
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Poch FGM, Neizert CA, Geyer B, Gemeinhardt O, Niehues SM, Vahldiek JL, Bressem KK, Lehmann KS. Perivascular vital cells in the ablation center after multibipolar radiofrequency ablation in an in vivo porcine model. Sci Rep 2021; 11:13886. [PMID: 34230573 PMCID: PMC8260723 DOI: 10.1038/s41598-021-93406-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 06/24/2021] [Indexed: 11/25/2022] Open
Abstract
Multibipolar radiofrequency ablation (RFA) is an advanced ablation technique for early stage hepatocellular carcinoma and liver metastases. Vessel cooling in multibipolar RFA has not been systematically investigated. The objective of this study was to evaluate the presence of perivascular vital cells within the ablation zone after multibipolar RFA. Multibipolar RFA were performed in domestic pigs in vivo. Three internally cooled bipolar RFA applicators were used simultaneously. Three experimental settings were planned: (1) inter-applicator-distance: 15 mm; (2) inter-applicator-distance: 20 mm; (3) inter-applicator-distance: 20 mm with hepatic inflow occlusion (Pringle maneuver). A vitality staining was used to analyze liver cell vitality around all vessels in the ablation center with a diameter > 0.5 mm histologically. 771 vessels were identified. No vital tissue was seen around 423 out of 429 vessels (98.6%) situated within the central white zone. Vital cells could be observed around major hepatic vessels situated adjacent to the ablation center. Vessel diameter (> 3.0 mm; p < 0.05) and low vessel-to-ablation-center distance (< 0.2 mm; p < 0.05) were identified as risk factors for incomplete ablation adjacent to hepatic vessels. The vast majority of vessels, which were localized in the clinically relevant white zone, showed no vital perivascular cells, regardless of vessel diameter and vessel type. However, there was a risk of incomplete ablation around major hepatic vessels situated directly within the ablation center. A Pringle maneuver could avoid incomplete ablations.
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Affiliation(s)
- F G M Poch
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Benjamin Franklin, Berlin - Hindenburgdamm 30, 12203, Berlin, Germany.
| | - C A Neizert
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Benjamin Franklin, Berlin - Hindenburgdamm 30, 12203, Berlin, Germany
| | - B Geyer
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Benjamin Franklin, Berlin - Hindenburgdamm 30, 12203, Berlin, Germany
| | - O Gemeinhardt
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Benjamin Franklin, Berlin - Hindenburgdamm 30, 12203, Berlin, Germany
| | - S M Niehues
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Benjamin Franklin, Berlin - Hindenburgdamm 30, 12203, Berlin, Germany
| | - J L Vahldiek
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Benjamin Franklin, Berlin - Hindenburgdamm 30, 12203, Berlin, Germany
| | - K K Bressem
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Benjamin Franklin, Berlin - Hindenburgdamm 30, 12203, Berlin, Germany
| | - K S Lehmann
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Benjamin Franklin, Berlin - Hindenburgdamm 30, 12203, Berlin, Germany
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Graef J, Leidel BA, Bressem KK, Vahldiek JL, Hamm B, Niehues SM. Computed Tomography Imaging in Simulated Ongoing Cardiopulmonary Resuscitation: No Need to Switch Off the Chest Compression Device during Image Acquisition. Diagnostics (Basel) 2021; 11:diagnostics11061122. [PMID: 34205468 PMCID: PMC8235148 DOI: 10.3390/diagnostics11061122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 06/14/2021] [Accepted: 06/14/2021] [Indexed: 11/30/2022] Open
Abstract
Computed tomography (CT) represents the current standard for imaging of patients with acute life-threatening diseases. As some patients present with circulatory arrest, they require cardiopulmonary resuscitation. Automated chest compression devices are used to continue resuscitation during CT examinations, but tend to cause motion artifacts degrading diagnostic evaluation of the chest. The aim was to investigate and evaluate a CT protocol for motion-free imaging of thoracic structures during ongoing mechanical resuscitation. The standard CT trauma protocol and a CT protocol with ECG triggering using a simulated ECG were applied in an experimental setup to examine a compressible thorax phantom during resuscitation with two different compression devices. Twenty-eight phantom examinations were performed, 14 with AutoPulse® and 14 with corpuls cpr®. With each device, seven CT examinations were carried out with ECG triggering and seven without. Image quality improved significantly applying the ECG-triggered protocol (p < 0.001), which allowed almost artifact-free chest evaluation. With the investigated protocol, radiation exposure was 5.09% higher (15.51 mSv vs. 14.76 mSv), and average reconstruction time of CT scans increased from 45 to 76 s. Image acquisition using the proposed CT protocol prevents thoracic motion artifacts and facilitates diagnosis of acute life-threatening conditions during continuous automated chest compression.
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Affiliation(s)
- Jessica Graef
- Department of Radiology, Campus Benjamin Franklin, Charité–Universitätsmedizin Berlin, 12203 Berlin, Germany; (K.K.B.); (J.L.V.); (B.H.)
- Correspondence: (J.G.); (S.M.N.)
| | - Bernd A. Leidel
- Department of Emergency Medicine, Campus Benjamin Franklin, Charité–Universitätsmedizin Berlin, 12203 Berlin, Germany;
| | - Keno K. Bressem
- Department of Radiology, Campus Benjamin Franklin, Charité–Universitätsmedizin Berlin, 12203 Berlin, Germany; (K.K.B.); (J.L.V.); (B.H.)
- Berlin Institute of Health at Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Janis L. Vahldiek
- Department of Radiology, Campus Benjamin Franklin, Charité–Universitätsmedizin Berlin, 12203 Berlin, Germany; (K.K.B.); (J.L.V.); (B.H.)
| | - Bernd Hamm
- Department of Radiology, Campus Benjamin Franklin, Charité–Universitätsmedizin Berlin, 12203 Berlin, Germany; (K.K.B.); (J.L.V.); (B.H.)
| | - Stefan M. Niehues
- Department of Radiology, Campus Benjamin Franklin, Charité–Universitätsmedizin Berlin, 12203 Berlin, Germany; (K.K.B.); (J.L.V.); (B.H.)
- Correspondence: (J.G.); (S.M.N.)
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Bressem KK, Vahldiek JL, Adams L, Niehues SM, Haibel H, Rodriguez VR, Torgutalp M, Protopopov M, Proft F, Rademacher J, Sieper J, Rudwaleit M, Hamm B, Makowski MR, Hermann KG, Poddubnyy D. Deep learning for detection of radiographic sacroiliitis: achieving expert-level performance. Arthritis Res Ther 2021; 23:106. [PMID: 33832519 PMCID: PMC8028815 DOI: 10.1186/s13075-021-02484-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 03/22/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Radiographs of the sacroiliac joints are commonly used for the diagnosis and classification of axial spondyloarthritis. The aim of this study was to develop and validate an artificial neural network for the detection of definite radiographic sacroiliitis as a manifestation of axial spondyloarthritis (axSpA). METHODS Conventional radiographs of the sacroiliac joints obtained in two independent studies of patients with axSpA were used. The first cohort comprised 1553 radiographs and was split into training (n = 1324) and validation (n = 229) sets. The second cohort comprised 458 radiographs and was used as an independent test dataset. All radiographs were assessed in a central reading session, and the final decision on the presence or absence of definite radiographic sacroiliitis was used as a reference. The performance of the neural network was evaluated by calculating areas under the receiver operating characteristic curves (AUCs) as well as sensitivity and specificity. Cohen's kappa and the absolute agreement were used to assess the agreement between the neural network and the human readers. RESULTS The neural network achieved an excellent performance in the detection of definite radiographic sacroiliitis with an AUC of 0.97 and 0.94 for the validation and test datasets, respectively. Sensitivity and specificity for the cut-off weighting both measurements equally were 88% and 95% for the validation and 92% and 81% for the test set. The Cohen's kappa between the neural network and the reference judgements were 0.79 and 0.72 for the validation and test sets with an absolute agreement of 90% and 88%, respectively. CONCLUSION Deep artificial neural networks enable the accurate detection of definite radiographic sacroiliitis relevant for the diagnosis and classification of axSpA.
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Affiliation(s)
- Keno K Bressem
- Department of Radiology, Charité - Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
- Berlin Institute of Health, BIH, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité - Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany.
| | - Lisa Adams
- Department of Radiology, Charité - Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
- Berlin Institute of Health, BIH, Berlin, Germany
| | - Stefan Markus Niehues
- Department of Radiology, Charité - Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Hildrun Haibel
- Department of Gastroenterology, Infectious Diseases and Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Valeria Rios Rodriguez
- Department of Gastroenterology, Infectious Diseases and Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Murat Torgutalp
- Department of Gastroenterology, Infectious Diseases and Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Mikhail Protopopov
- Department of Gastroenterology, Infectious Diseases and Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Fabian Proft
- Department of Gastroenterology, Infectious Diseases and Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Judith Rademacher
- Berlin Institute of Health, BIH, Berlin, Germany
- Department of Gastroenterology, Infectious Diseases and Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Joachim Sieper
- Department of Gastroenterology, Infectious Diseases and Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Martin Rudwaleit
- Department of Internal Medicine and Rheumatology, Klinikum Bielefeld Rosenhöhe, Bielefeld, Germany
| | - Bernd Hamm
- Department of Radiology, Charité - Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Marcus R Makowski
- Department of Radiology, Charité - Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Kay-Geert Hermann
- Department of Radiology, Charité - Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Denis Poddubnyy
- Department of Gastroenterology, Infectious Diseases and Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Epidemiology, German Rheumatism Research Centre, Berlin, Germany
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Poch FGM, Geyer B, Neizert CA, Gemeinhardt O, Niehues SM, Vahldiek JL, Frericks B, Lehmann KS. Periportal fields cause stronger cooling effects than veins in hepatic microwave ablation: an in vivo porcine study. Acta Radiol 2021; 62:322-328. [PMID: 32493033 DOI: 10.1177/0284185120928929] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Vascular cooling effects are a well-known source for tumor recurrence in thermal in situ ablation techniques for hepatic malignancies. Microwave ablation (MWA) is an ablation technique to be considered in the treatment of malignant liver tumors. The impact of vascular cooling in MWA is still controversial. PURPOSE To evaluate the influence of different intrahepatic vessel types, vessel sizes, and vessel-to-antenna-distances on MWA geometry in vivo. MATERIAL AND METHODS Five MWAs (902-928 MHz) were performed with an energy input of 24.0 kJ in three porcine livers in vivo. MWA lesions were cut into 2-mm slices. The minimum and maximum radius of the ablation area was measured for each slice. Distances were measured from ablation center toward all adjacent hepatic vessels with a diameter of ≥1 mm and within a perimeter of 20 mm around the antenna. The respective vascular cooling effect relative to the maximum ablation radius was calculated. RESULTS In total, 707 vessels (489 veins, 218 portal fields) were detected; 370 (76%) hepatic veins and 185 (85%) portal fields caused a cooling effect. Portal fields resulted in higher cooling effects (37%) than hepatic veins (26%, P < 0.01). No cooling effect could be observed in close proximity of vessels within the central ablation zone. CONCLUSION Hepatic vessels influenced MWA zones and caused a distinct cooling effect. Portal fields resulted in more pronounced cooling effect than hepatic veins. No cooling effect was observed around vessels situated within the central white zone.
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Affiliation(s)
- Franz GM Poch
- Department of General, Visceral and Vascular Surgery, Charité – Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Beatrice Geyer
- Department of General, Visceral and Vascular Surgery, Charité – Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Christina A Neizert
- Department of General, Visceral and Vascular Surgery, Charité – Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Ole Gemeinhardt
- Department of Radiology, Charité – Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Stefan M Niehues
- Department of Radiology, Charité – Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité – Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Bernd Frericks
- DRK Kliniken Berlin Westend, Institut for Diagnostic and Interventional Radiology, Berlin, Germany
| | - Kai S Lehmann
- Department of General, Visceral and Vascular Surgery, Charité – Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
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15
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Erxleben C, Adams LC, Albrecht J, Petersen A, Vahldiek JL, Thieß HM, Kremmin J, Makowski MR, Niehues A, Niehues SM, Bressem KK. Improving CT accuracy in the diagnosis of COVID-19 in a hospital setting. Clin Imaging 2021; 76:1-5. [PMID: 33545516 PMCID: PMC7846468 DOI: 10.1016/j.clinimag.2021.01.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 01/16/2021] [Accepted: 01/22/2021] [Indexed: 12/20/2022]
Abstract
Objective This study aimed to improve the accuracy of CT for detection of COVID-19-associated pneumonia and to identify patient subgroups who might benefit most from CT imaging. Methods A total of 269 patients who underwent CT for suspected COVID-19 were included in this retrospective analysis. COVID-19 was confirmed by reverse-transcription-polymerase-chain-reaction. Basic demographics (age and sex) and initial vital parameters (O2-saturation, respiratory rate, and body temperature) were recorded. Generalized mixed models were used to calculate the accuracy of vital parameters for detection of COVID-19 and to evaluate the diagnostic accuracy of CT. A clinical score based on vital parameters, age, and sex was established to estimate the pretest probability of COVID-19 and used to define low, intermediate, and high risk groups. A p-value of <0.05 was considered statistically significant. Results The sole use of vital parameters for the prediction of COVID-19 was inferior to CT. After correction for confounders, such as age and sex, CT showed a sensitivity of 0.86, specificity of 0.78, and positive predictive value of 0.36. In the subgroup analysis based on pretest probability, positive predictive value and sensitivity increased to 0.53 and 0.89 in the high-risk group, while specificity was reduced to 0.68. In the low-risk group, sensitivity and positive predictive value decreased to 0.76 and 0.33 with a specificity of 0.83. The negative predictive value remained high (0.94 and 0.97) in both groups. Conclusions The accuracy of CT for the detection of COVID-19 might be increased by selecting patients with a high-pretest probability of COVID-19.
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Affiliation(s)
- Christoph Erxleben
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Lisa C Adams
- Charité - Universitätsmedizin Berlin, Campus Charité Mitte - Klinik für Radiologie, Charitéplatz 1, 10117 Berlin, Germany.
| | - Jacob Albrecht
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Antonia Petersen
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Janis L Vahldiek
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Hans-Martin Thieß
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Julia Kremmin
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Marcus R Makowski
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Radiology, 81675 Munich, Germany
| | - Alexandra Niehues
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Stefan M Niehues
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Keno K Bressem
- Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin - Klinik für Radiologie, Hindenburgdamm 30, 12203 Berlin, Germany
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Erxleben C, Niehues SM, Geyer B, Poch F, Bressem KK, Lehmann KS, Vahldiek JL. CT-based quantification of short-term tissue shrinkage following hepatic microwave ablation in an in vivo porcine liver model. Acta Radiol 2021; 62:12-18. [PMID: 32264686 DOI: 10.1177/0284185120914452] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Microwave ablation (MWA) is a minimally invasive treatment option for solid tumors and belongs to the local ablative therapeutic techniques, based on thermal tissue coagulation. So far there are mainly ex vivo studies that describe tissue shrinkage during MWA. PURPOSE To characterize short-term volume changes of the ablated zone following hepatic MWA in an in vivo porcine liver model using contrast-enhanced computer tomography (CECT). MATERIAL AND METHODS We performed multiple hepatic MWA with constant energy parameters in healthy, narcotized and laparotomized domestic pigs. The volumes of the ablated areas were calculated from venous phase CT scans, immediately after the ablation and in short-term courses of up to 2 h after MWA. RESULTS In total, 19 thermally ablated areas in 10 porcine livers could be analyzed (n = 6 with two volume measurements during the measurement period and n = 13 with three measurements). Both groups showed a statistically significant but heterogeneous volume reduction of up to 12% (median 6%) of the ablated zones in CECT scans during the measurement period (P < 0.001 [n = 13] and P = 0.042 [n = 6]). However, the dimension and dynamics of volume changes were heterogenous both absolutely and relatively. CONCLUSION We observed a significant short-term volume reduction of ablated liver tissue in vivo. This volume shrinkage must be considered in clinical practice for technically successful tumor treatment by MWA and therefore it should be further investigated in in vivo studies.
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Affiliation(s)
- Christoph Erxleben
- Charité – Universitätsmedizin Berlin, Department of Radiology, Berlin, Germany
| | - Stefan M Niehues
- Charité – Universitätsmedizin Berlin, Department of Radiology, Berlin, Germany
| | - Beatrice Geyer
- Charité – Universitätsmedizin Berlin, Department of Surgery, Berlin, Germany
| | - Franz Poch
- Charité – Universitätsmedizin Berlin, Department of Surgery, Berlin, Germany
| | - Keno K Bressem
- Charité – Universitätsmedizin Berlin, Department of Surgery, Berlin, Germany
| | - Kai S Lehmann
- Charité – Universitätsmedizin Berlin, Department of Surgery, Berlin, Germany
| | - Janis L Vahldiek
- Charité – Universitätsmedizin Berlin, Department of Radiology, Berlin, Germany
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Poch FG, Geyer B, Gemeinhardt O, Klopfleisch R, Niehues SM, Vahldiek JL, Bressem K, Kreis ME, Lehmann KS. Immediate post-interventional contrast-enhanced computed tomography overestimates hepatic microwave ablation - an in vivo animal study. Int J Hyperthermia 2020; 37:463-469. [PMID: 32396401 DOI: 10.1080/02656736.2020.1762936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
Abstract
Objectives: Contrast-enhanced computed tomography (CECT) is used to monitor technical success immediately after hepatic microwave ablation (MWA). However, it remains unclear, if CECT shows the exact extend of the thermal destruction zone, or if tissue changes such as peri-lesionary edema are depicted as well. The objective of this study was to correlate immediate post-interventional CECT with histological and macroscopic findings in hepatic MWA in porcine liver in vivo.Methods: Eleven MWA were performed in porcine liver in vivo with a microwave generator (928 MHz; energy input 24 kJ). CECT was performed post-interventionally. Livers were explanted and ablations were bisected immediately after ablation. Samples were histologically analyzed after vital staining (NADH-diaphorase). Ablation zones were histologically and macroscopically outlined. We correlated histologic findings, macroscopic images and CECT.Results: Three ablation zones were identified in histological and macroscopic findings. Only one ablation zone could be depicted in CECT. Close conformity was observed between histological and macroscopic findings. The ablation zone depicted in CECT overestimated the histological avital central zone and inner red zone (p < = .01). No differences were found between CECT and the histological outer red zone (p > .05).Conclusions: Immediate post-interventional CECT overestimated the clinically relevant zone of complete cell ablation after MWA in porcine liver in vivo. This entails the risk of incomplete tumor ablation and could lead to tumor recurrence.
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Affiliation(s)
- Franz G Poch
- Department of General, Visceral and Vascular Surgery, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Beatrice Geyer
- Department of General, Visceral and Vascular Surgery, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ole Gemeinhardt
- Department of Radiology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Robert Klopfleisch
- Institute of Veterinary Pathology, Freie Universität Berlin, Berlin, Germany
| | - Stefan M Niehues
- Department of Radiology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Janis L Vahldiek
- Department of Radiology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Keno Bressem
- Department of Radiology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Martin E Kreis
- Department of General, Visceral and Vascular Surgery, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Kai S Lehmann
- Department of General, Visceral and Vascular Surgery, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany
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18
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Bressem KK, Adams LC, Albrecht J, Petersen A, Thieß HM, Niehues A, Niehues SM, Vahldiek JL. Is lung density associated with severity of COVID-19? Pol J Radiol 2020; 85:e600-e606. [PMID: 33204375 PMCID: PMC7654311 DOI: 10.5114/pjr.2020.100788] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 09/03/2020] [Indexed: 02/07/2023] Open
Abstract
PURPOSE Emphysema and chronic obstructive lung disease were previously identified as major risk factors for severe disease progression in COVID-19. Computed tomography (CT)-based lung-density analysis offers a fast, reliable, and quantitative assessment of lung density. Therefore, we aimed to assess the benefit of CT-based lung density measurements to predict possible severe disease progression in COVID-19. MATERIAL AND METHODS Thirty COVID-19-positive patients were included in this retrospective study. Lung density was quantified based on routinely acquired chest CTs. Presence of COVID-19 was confirmed by reverse transcription polymerase chain reaction (RT-PCR). Wilcoxon test was used to compare two groups of patients. A multivariate regression analysis, adjusted for age and sex, was employed to model the relative increase of risk for severe disease, depending on the measured densities. RESULTS Intensive care unit (ICU) patients or patients requiring mechanical ventilation showed a lower proportion of medium- and low-density lung volume compared to patients on the normal ward, but a significantly larger volume of high-density lung volume (12.26 dl IQR 4.65 dl vs. 7.51 dl vs. IQR 5.39 dl, p = 0.039). In multivariate regression analysis, high-density lung volume was identified as a significant predictor of severe disease. CONCLUSIONS The amount of high-density lung tissue showed a significant association with severe COVID-19, with odds ratios of 1.42 (95% CI: 1.09-2.00) and 1.37 (95% CI: 1.03-2.11) for requiring intensive care and mechanical ventilation, respectively. Acknowledging our small sample size as an important limitation; our study might thus suggest that high-density lung tissue could serve as a possible predictor of severe COVID-19.
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Affiliation(s)
- Keno K. Bressem
- Correspondence address: Dr. Keno K. Bressem, Charité Universitätsmedizin Berlin, Berlin, Germany, e-mail:
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Bressem KK, Adams LC, Erxleben C, Hamm B, Niehues SM, Vahldiek JL. Comparing different deep learning architectures for classification of chest radiographs. Sci Rep 2020; 10:13590. [PMID: 32788602 PMCID: PMC7423963 DOI: 10.1038/s41598-020-70479-z] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 06/26/2020] [Indexed: 11/16/2022] Open
Abstract
Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research. However, most of the models used to classify chest radiographs are derived from openly available deep neural networks, trained on large image datasets. These datasets differ from chest radiographs in that they are mostly color images and have substantially more labels. Therefore, very deep convolutional neural networks (CNN) designed for ImageNet and often representing more complex relationships, might not be required for the comparably simpler task of classifying medical image data. Sixteen different architectures of CNN were compared regarding the classification performance on two openly available datasets, the CheXpert and COVID-19 Image Data Collection. Areas under the receiver operating characteristics curves (AUROC) between 0.83 and 0.89 could be achieved on the CheXpert dataset. On the COVID-19 Image Data Collection, all models showed an excellent ability to detect COVID-19 and non-COVID pneumonia with AUROC values between 0.983 and 0.998. It could be observed, that more shallow networks may achieve results comparable to their deeper and more complex counterparts with shorter training times, enabling classification performances on medical image data close to the state-of-the-art methods even when using limited hardware.
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Affiliation(s)
- Keno K Bressem
- Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203, Berlin, Germany.
| | - Lisa C Adams
- Charité Universitätsmedizin Berlin, Campus Mitte, Charitéplatz 1, 10117, Berlin, Germany
| | - Christoph Erxleben
- Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Bernd Hamm
- Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203, Berlin, Germany
- Charité Universitätsmedizin Berlin, Campus Mitte, Charitéplatz 1, 10117, Berlin, Germany
| | - Stefan M Niehues
- Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Janis L Vahldiek
- Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203, Berlin, Germany
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Bressem KK, Vahldiek JL, Erxleben C, Poch F, Shnaiyen S, Geyer B, Lehmann KS, Hamm B, Niehues SM. Exploring Patterns of Dynamic Size Changes of Lesions after Hepatic Microwave Ablation in an In Vivo Porcine Model. Sci Rep 2020; 10:805. [PMID: 31965024 PMCID: PMC6972764 DOI: 10.1038/s41598-020-57859-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 01/08/2020] [Indexed: 11/09/2022] Open
Abstract
Microwave ablation (MWA) is a type of minimally invasive cancer therapy that uses heat to induce necrosis in solid tumours. Inter- and post-ablational size changes can influence the accuracy of control imaging, posing a risk of incomplete ablation. The present study aims to explore post-ablation 3D size dynamics in vivo using computed tomography (CT). Ten MWA datasets obtained in nine healthy pigs were used. Lesions were subdivided along the z-axis with an additional planar subdivision into eight subsections. The volume of the subsections was analysed over different time points, subsequently colour-coded and three-dimensionally visualized. A locally weighted polynomial regression model (LOESS) was applied to describe overall size changes, and Student's t-tests were used to assess statistical significance of size changes. The 3D analysis showed heterogeneous volume changes with multiple small changes at the lesion margins over all time points. The changes were pronounced at the upper and lower lesion edges and characterized by initially eccentric, opposite swelling, followed by shrinkage. In the middle parts of the lesion, we observed less dimensional variations over the different time points. LOESS revealed a hyperbolic pattern for the volumetric changes with an initially significant volume increase of 11.6% (111.6% of the original volume) over the first 32 minutes, followed by a continuous decrease to 96% of the original volume (p < 0.05).
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Affiliation(s)
- Keno K Bressem
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany.
| | - Janis L Vahldiek
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
| | - Christoph Erxleben
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
| | - Franz Poch
- Department of Surgery, Charité - University Medicine Berlin, Berlin, Germany
| | - Seyd Shnaiyen
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
| | - Beatrice Geyer
- Department of Surgery, Charité - University Medicine Berlin, Berlin, Germany
| | - Kai S Lehmann
- Department of Surgery, Charité - University Medicine Berlin, Berlin, Germany
| | - Bernd Hamm
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
| | - Stefan M Niehues
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
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Geyer B, Poch FGM, Gemeinhardt O, Neizert CA, Niehues SM, Vahldiek JL, Klopfleisch R, Lehmann KS. Microwave ablation zones are larger than they macroscopically appear - Reevaluation based on NADH vitality staining ex vivo. Clin Hemorheol Microcirc 2019; 73:371-378. [DOI: 10.3233/ch-190583] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Beatrice Geyer
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of General, Visceral and Vascular Surgery – Campus Benjamin Franklin, Berlin, Germany
| | - Franz G. M. Poch
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of General, Visceral and Vascular Surgery – Campus Benjamin Franklin, Berlin, Germany
| | - Ole Gemeinhardt
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Radiology – Campus Mitte, Berlin, Germany
| | - Christina A. Neizert
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of General, Visceral and Vascular Surgery – Campus Benjamin Franklin, Berlin, Germany
| | - Stefan M. Niehues
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Radiology – Campus Benjamin Franklin, Berlin, Germany
| | - Janis L. Vahldiek
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Radiology – Campus Benjamin Franklin, Berlin, Germany
| | - Robert Klopfleisch
- Institute of Veterinary Pathology, Freie Universität Berlin, Berlin, Germany
| | - Kai S. Lehmann
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of General, Visceral and Vascular Surgery – Campus Benjamin Franklin, Berlin, Germany
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Bressem KK, Vahldiek JL, Erxleben C, Shnayien S, Poch F, Geyer B, Lehmann KS, Hamm B, Niehues SM. Improved Visualization of the Necrotic Zone after Microwave Ablation Using Computed Tomography Volume Perfusion in an In Vivo Porcine Model. Sci Rep 2019; 9:18506. [PMID: 31811190 PMCID: PMC6898643 DOI: 10.1038/s41598-019-55026-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 11/21/2019] [Indexed: 01/02/2023] Open
Abstract
After hepatic microwave ablation, the differentiation between fully necrotic and persistent vital tissue through contrast enhanced CT remains a clinical challenge. Therefore, there is a need to evaluate new imaging modalities, such as CT perfusion (CTP) to improve the visualization of coagulation necrosis. MWA and CTP were prospectively performed in five healthy pigs. After the procedure, the pigs were euthanized, and the livers explanted. Orthogonal histological slices of the ablations were stained with a vital stain, digitalized and the necrotic core was segmented. CTP maps were calculated using a dual-input deconvolution algorithm. The segmented necrotic zones were overlaid on the DICOM images to calculate the accuracy of depiction by CECT/CTP compared to the histological reference standard. A receiver operating characteristic analysis was performed to determine the agreement/true positive rate and disagreement/false discovery rate between CECT/CTP and histology. Standard CECT showed a true positive rate of 81% and a false discovery rate of 52% for display of the coagulation necrosis. Using CTP, delineation of the coagulation necrosis could be improved significantly through the display of hepatic blood volume and hepatic arterial blood flow (p < 0.001). The ratios of true positive rate/false discovery rate were 89%/25% and 90%/50% respectively. Other parameter maps showed an inferior performance compared to CECT.
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Affiliation(s)
- Keno K Bressem
- Department of Radiology, Charité, Hindenburgdamm 30, 12203, Berlin, Germany.
| | - Janis L Vahldiek
- Department of Radiology, Charité, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Christoph Erxleben
- Department of Radiology, Charité, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Seyd Shnayien
- Department of Radiology, Charité, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Franz Poch
- Department of Surgery, Charité, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Beatrice Geyer
- Department of Surgery, Charité, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Kai S Lehmann
- Department of Surgery, Charité, Hindenburgdamm 30, 12203, Berlin, Germany
| | - B Hamm
- Department of Radiology, Charité, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Stefan M Niehues
- Department of Radiology, Charité, Hindenburgdamm 30, 12203, Berlin, Germany
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Bressem KK, Vahldiek JL, Erxleben C, Geyer B, Poch F, Shnayien S, Lehmann KS, Hamm B, Niehues SM. Comparison of different 4D CT-Perfusion algorithms to visualize lesions after microwave ablation in an in vivo porcine model. Int J Hyperthermia 2019; 36:1098-1107. [DOI: 10.1080/02656736.2019.1679894] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Affiliation(s)
- Keno K. Bressem
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Janis L. Vahldiek
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Christoph Erxleben
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Beatrice Geyer
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - Franz Poch
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - Seyd Shnayien
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Kai S. Lehmann
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - B. Hamm
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Stefan M. Niehues
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
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Bressem KK, Erxleben C, Lauscher JC, Günther RW, de Bucourt M, Niehues SM, Vahldiek JL. Successful CT-Guided Obliteration of Isolated Bile Ducts with Ethylene Vinyl Alcohol Copolymer in a Patient with Chronic Bile Leakage after Hepatectomy. J Vasc Interv Radiol 2019; 30:1671-1673. [PMID: 31409565 DOI: 10.1016/j.jvir.2019.05.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 05/04/2019] [Accepted: 05/16/2019] [Indexed: 11/29/2022] Open
Affiliation(s)
- Keno K Bressem
- Department of Radiology, Charité Medical School, Humboldt University, Hindenburgdamm 30, Berlin D-12203, Germany
| | - Christoph Erxleben
- Department of Radiology, Charité Medical School, Humboldt University, Hindenburgdamm 30, Berlin D-12203, Germany
| | - Johannes C Lauscher
- Department of Surgery, Charité Medical School, Humboldt University, Hindenburgdamm 30, Berlin D-12203, Germany
| | - Rolf W Günther
- Department of Radiology, Charité Medical School, Humboldt University, Hindenburgdamm 30, Berlin D-12203, Germany
| | - Maximilian de Bucourt
- Department of Radiology, Charité Medical School, Humboldt University, Hindenburgdamm 30, Berlin D-12203, Germany
| | - Stefan M Niehues
- Department of Radiology, Charité Medical School, Humboldt University, Hindenburgdamm 30, Berlin D-12203, Germany
| | - Janis L Vahldiek
- Department of Radiology, Charité Medical School, Humboldt University, Hindenburgdamm 30, Berlin D-12203, Germany
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Vahldiek JL, Erxleben C, Bressem KK, Gemeinhardt O, Poch F, Hiebl B, Lehmann KS, Hamm B, Niehues SM. Multipolar RFA of the liver: Influence of intrahepatic vessels on ablation zones and appropriateness of CECT in detecting ablation dimensions - Results of an in-vivo porcine liver model. Clin Hemorheol Microcirc 2019; 70:467-476. [DOI: 10.3233/ch-189313] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Janis L. Vahldiek
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Christoph Erxleben
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Keno Kyrill Bressem
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Ole Gemeinhardt
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - Franz Poch
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - Bernhard Hiebl
- Institute for Animal Hygiene, Animal Welfare and Farm Animal Behaviour, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany
| | - Kai S. Lehmann
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - B. Hamm
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Stefan M. Niehues
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
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Vahldiek JL, Thieme S, Hamm B, Niehues SM. Incidence of combined cranial and cervical spine injuries in patients with blunt minor trauma: are combined CT examinations of the head and cervical spine justified? Acta Radiol 2017; 58:856-860. [PMID: 27754918 DOI: 10.1177/0284185116673120] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background The use of computed tomography (CT) scans of the head and cervical spine has markedly increased in patients with blunt minor trauma. The actual likelihood of a combined injury of head and cervical spine following a minor trauma is estimated to be low. Purpose To determine the incidence of such combined injuries in patients with a blunt minor trauma in order to estimate the need to derive improved diagnostic guidelines. Material and Methods A total of 1854 patients were retrospectively analyzed. All cases presented to the emergency department and in all patients combined CT scans of head and cervical spine were conducted. For the following analysis, only 1342 cases with assured blunt minor trauma were included. Data acquisition covered age, sex, and presence of a head injury as well as presence of a cervical spine injury or both. Results Of the 1342 cases, 46.9% were men. The mean age was 65.6 years. CT scans detected a head injury in 116 patients; of these, 70 cases showed an intracranial hemorrhage, 11 cases a skull fracture, and 35 cases an intracranial hemorrhage as well as a skull fracture. An injury of the cervical spine could be detected in 40 patients. A combined injury of the head and cervical spine could be found in one patient. Conclusion The paradigm of the coincidence of cranial and cervical spine injuries should be revised in patients with blunt minor trauma. Valid imaging decision algorithms are strongly needed to clinically detect high-risk patients in order to save limited resources.
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Affiliation(s)
| | - Stefan Thieme
- Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Bernd Hamm
- Charité – Universitätsmedizin Berlin, Berlin, Germany
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Vahldiek JL, Thieme SF, Gemeinhardt O, Poch F, Hiebl B, Lehmann KS, Hamm B, Niehues SM. Characterization of benign periablational enhancement following multipolar radiofrequency ablation using perfusion CT in an in-vivo porcine liver model. ACTA ACUST UNITED AC 2017. [DOI: 10.3233/jcb-15032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Janis L. Vahldiek
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
| | - Stefan F. Thieme
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
| | - Ole Gemeinhardt
- Department of Surgery, Charité - University Medicine Berlin, Berlin, Germany
| | - Franz Poch
- Department of Surgery, Charité - University Medicine Berlin, Berlin, Germany
| | - Bernhard Hiebl
- Center for Medical Basic Research, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Kai S. Lehmann
- Department of Surgery, Charité - University Medicine Berlin, Berlin, Germany
| | - B. Hamm
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
| | - Stefan M. Niehues
- Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany
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Gemeinhardt O, Poch FG, Hiebl B, Kunz-Zurbuchen U, Corte GM, Thieme SF, Vahldiek JL, Niehues SM, Kreis ME, Klopfleisch R, Lehmann KS. Comparison of bipolar radiofrequency ablation zones in an in vivo porcine model: Correlation of histology and gross pathological findings. Clin Hemorheol Microcirc 2017; 64:491-499. [DOI: 10.3233/ch-168123] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Ole Gemeinhardt
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Franz G.M. Poch
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Bernhard Hiebl
- Institute for Animal Hygiene, Animal Welfare and Farm Animal Behaviour, University of Veterinary Medicine Hannover, Hannover, Germany
| | - Urte Kunz-Zurbuchen
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Giuliano M. Corte
- Institute of Veterinary Anatomy, Freie Universität Berlin, Berlin, Germany
| | - Stefan F. Thieme
- Department of Radiology, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Janis L. Vahldiek
- Department of Radiology, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Stefan M. Niehues
- Department of Radiology, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Martin E. Kreis
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Robert Klopfleisch
- Institute of Veterinary Pathology, Freie Universität Berlin, Berlin, Germany
| | - Kai S. Lehmann
- Department of General, Visceral and Vascular Surgery, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
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Thieme SF, Vahldiek JL, Tummler K, Poch F, Gemeinhardt O, Hiebl B, Lehmann KS, Hamm B, Niehues SM. Value or waste: Perfusion imaging following radiofrequency ablation – early experience. Clin Hemorheol Microcirc 2015; 61:323-31. [DOI: 10.3233/ch-152000] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Stefan F. Thieme
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Janis L. Vahldiek
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Katja Tummler
- Theoretische Biophysik, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Franz Poch
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - Ole Gemeinhardt
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - Bernhard Hiebl
- Center for Medical Basic Research, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Kai S. Lehmann
- Department of Surgery, Charité-University Medicine Berlin, Berlin, Germany
| | - B. Hamm
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
| | - Stefan M. Niehues
- Department of Radiology, Charité-University Medicine Berlin, Berlin, Germany
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Vahldiek JL, Lehmann KS, Poch F, Zurbuchen U, Kreis ME, Gemeinhardt O, Hamm B, Niehues SM. Measuring and optimizing results in multipolar RFA: Techniques and early findings in an experimental setting. Clin Hemorheol Microcirc 2014; 58:77-87. [DOI: 10.3233/ch-141886] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Janis L. Vahldiek
- Department of Radiology, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Kai S. Lehmann
- Department of General, Vascular and Thoracic Surgery, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Franz Poch
- Department of General, Vascular and Thoracic Surgery, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Urte Zurbuchen
- Department of General, Vascular and Thoracic Surgery, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Martin E. Kreis
- Department of General, Vascular and Thoracic Surgery, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Ole Gemeinhardt
- Department of General, Vascular and Thoracic Surgery, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - B. Hamm
- Department of Radiology, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Stefan M. Niehues
- Department of Radiology, Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
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Vahldiek JL, Niehues SM, Hamm B. Primärversorgung von Patienten mit stumpfem Bagatelltrauma - sind kombinierte CT-Untersuchungen von Schädel und Halswirbelsäule gerechtfertigt? ROFO-FORTSCHR RONTG 2013. [DOI: 10.1055/s-0033-1346441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Brandt HC, Spiller I, Song IH, Vahldiek JL, Rudwaleit M, Sieper J. Performance of referral recommendations in patients with chronic back pain and suspected axial spondyloarthritis. Ann Rheum Dis 2007; 66:1479-84. [PMID: 17456526 PMCID: PMC2111623 DOI: 10.1136/ard.2006.068734] [Citation(s) in RCA: 127] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Ankylosing spondylitis (AS) and its early form account for up to 5% of all patients with chronic back pain. Interest has recently focused on shortening the delay of 5-10 years between the appearance of first symptoms and the diagnosis of AS, particularly because effective treatments have now become available. Referral parameters that are easy for doctors in primary care to apply to patients presenting with possible AS could contribute to earlier diagnosis. METHODS Orthopaedists and primary-care doctors were requested to refer patients with (1) chronic low back pain (duration >3 months) and (2) onset of back pain before <45 years of age to a specialist rheumatology outpatient clinic for further diagnostic investigation if at least one of the following screening parameters was present: (1) inflammatory back pain, (2) positive human leucocyte antigen B27, and (3) sacroiliitis detected by imaging. The final diagnosis was made according to expert opinion. RESULTS In total, 350 referred cases were analysed. A diagnosis of definite axial spondyloarthritis (axial SpA), comprising established AS and pre-radiographic axial SpA, could be made in 45.4% of all referred patients (of which 50.3% were classified as AS and 49.7% as preradiographic axial SpA), whereas 45.4% were classified as non-SpA and 9.1% as possible SpA. A diagnosis of definite axial SpA could be made in 34.2% if only one referral parameter was positive, and in 62.6% if there was >1 positive referral parameter. CONCLUSIONS The proposed referral parameters have proven useful when applied in primary care in identifying patients with AS/pre-radiographic axial SpA among young to middle-aged patients with chronic low back pain.
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