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2. Key summary of German national guideline for adult patients with nosocomial pneumonia- Update 2024 Funding number at the Federal Joint Committee (G-BA): 01VSF22007

Author

Rademacher, Jessica, Ewig, Santiago, Grabein, Béatrice, Nachtigall, Irit, Abele-Horn, Marianne, Deja, Maria, Gaßner, Martina, Gatermann, Sören, Geffers, Christine, Gerlach, Herwig, Hagel, Stefan, Heußel, Claus Peter, Kluge, Stefan, Kolditz, Martin, Kramme, Evelyn, Kühl, Hilmar, Panning, Marcus, Rath, Peter-Michael, Rohde, Gernot, Schaaf, Bernhard, Salzer, Helmut J. F., Schreiter, Dierk, Schweisfurth, Hans, Unverzagt, Susanne, Weigand, Markus A., Welte, Tobias, and Pletz, Mathias W.

Published
2024
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5. cOOpD: Reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations

Author

Almeida, Silvia D., Lüth, Carsten T., Norajitra, Tobias, Wald, Tassilo, Nolden, Marco, Jaeger, Paul F., Heussel, Claus P., Biederer, Jürgen, Weinheimer, Oliver, and Maier-Hein, Klaus

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Classification of heterogeneous diseases is challenging due to their complexity, variability of symptoms and imaging findings. Chronic Obstructive Pulmonary Disease (COPD) is a prime example, being underdiagnosed despite being the third leading cause of death. Its sparse, diffuse and heterogeneous appearance on computed tomography challenges supervised binary classification. We reformulate COPD binary classification as an anomaly detection task, proposing cOOpD: heterogeneous pathological regions are detected as Out-of-Distribution (OOD) from normal homogeneous lung regions. To this end, we learn representations of unlabeled lung regions employing a self-supervised contrastive pretext model, potentially capturing specific characteristics of diseased and healthy unlabeled regions. A generative model then learns the distribution of healthy representations and identifies abnormalities (stemming from COPD) as deviations. Patient-level scores are obtained by aggregating region OOD scores. We show that cOOpD achieves the best performance on two public datasets, with an increase of 8.2% and 7.7% in terms of AUROC compared to the previous supervised state-of-the-art. Additionally, cOOpD yields well-interpretable spatial anomaly maps and patient-level scores which we show to be of additional value in identifying individuals in the early stage of progression. Experiments in artificially designed real-world prevalence settings further support that anomaly detection is a powerful way of tackling COPD classification.

Published
2023

8. Midregional Proatrial Natriuretic Peptide (MRproANP) is associated with vertebral fractures and low bone density in patients with chronic obstructive pulmonary disease (COPD)

Author

Trudzinski, Franziska C., Jörres, Rudolf A., Alter, Peter, Watz, Henrik, Vogelmeier, Claus F., Kauczor, Hans-Ulrich, Thangamani, Subasini, Debic, Manuel, Welte, Tobias, Behr, Jürgen, Kahnert, Kathrin, Bals, Robert, Herr, Christian, Heußel, Claus Peter, Biederer, Jürgen, von Stackelberg, Oyunbileg, Fähndrich, Sebastian, Wouters, Emiel F. M., Waschki, Benjamin, Rabe, Klaus F., Herth, Felix J. F., and Palm, Viktoria

Published
2024
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10. Abstract: Radiomics Processing Toolkit

Author

Bohn, Jonas R., primary, Heidt, Christian M., additional, Almeida, Silvia D., additional, Kausch, Lisa, additional, Götz, Michael, additional, Nolden, Marco, additional, Christopoulos, Petros, additional, Rheinheimer, Stephan, additional, Peters, Alan A., additional, von Stackelberg, Oyunbileg, additional, Kauczor, Hans-Ulrich, additional, Maier-Hein, Klaus H., additional, Heußel, Claus P., additional, and Norajitra, Tobias, additional

Published
2024
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16. RPTK: The Role of Feature Computation on Prediction Performance

Author

Bohn, Jonas R., Heidt, Christian M., Almeida, Silvia D., Kausch, Lisa, Götz, Michael, Nolden, Marco, Christopoulos, Petros, Rheinheimer, Stephan, Peters, Alan A., Stackelberg, Oyunbileg von, Kauczor, Hans-Ulrich, Maier-Hein, Klaus H., Heußel, Claus P., Norajitra, Tobias, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woo, Jonghye, editor, Hering, Alessa, editor, Silva, Wilson, editor, Li, Xiang, editor, Fu, Huazhu, editor, Liu, Xiaofeng, editor, Xing, Fangxu, editor, Purushotham, Sanjay, editor, Mathai, Tejas S., editor, Mukherjee, Pritam, editor, De Grauw, Max, editor, Beets Tan, Regina, editor, Corbetta, Valentina, editor, Kotter, Elmar, editor, Reyes, Mauricio, editor, Baumgartner, Christian F., editor, Li, Quanzheng, editor, Leahy, Richard, editor, Dong, Bin, editor, Chen, Hao, editor, Huo, Yuankai, editor, Lv, Jinglei, editor, Xu, Xinxing, editor, Li, Xiaomeng, editor, Mahapatra, Dwarikanath, editor, Cheng, Li, editor, Petitjean, Caroline, editor, and Presles, Benoît, editor

Published
2023
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17. Deep Learning-Based Air Trapping Quantification Using Paired Inspiratory-Expiratory Ultra-low Dose CT

Author

Muller, Sarah M., Ram, Sundaresh, Bayfield, Katie J., Reuter, Julia H., Gestewitz, Sonja, Yu, Lifeng, Wielpütz, Mark O., Kauczor, Hans-Ulrich, Heussel, Claus P., Robinson, Terry E., Bartholmai, Brian J., Hatt, Charles R., Robinson, Paul D., Galban, Craig J., Weinheimer, Oliver, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Greenspan, Hayit, editor, Madabhushi, Anant, editor, Mousavi, Parvin, editor, Salcudean, Septimiu, editor, Duncan, James, editor, Syeda-Mahmood, Tanveer, editor, and Taylor, Russell, editor

Published
2023
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18. Abstract: Radiomics Processing Toolkit : Role of Feature Computation on Prediction Performance

Author

Bohn, Jonas R., Heidt, Christian M., Almeida, Silvia D., Kausch, Lisa, Götz, Michael, Nolden, Marco, Christopoulos, Petros, Rheinheimer, Stephan, Peters, Alan A., von Stackelberg, Oyunbileg, Kauczor, Hans-Ulrich, Maier-Hein, Klaus H., Heußel, Claus P., Norajitra, Tobias, Gesellschaft für Informatik e.V. (GI), Maier, Andreas, editor, Deserno, Thomas M., editor, Handels, Heinz, editor, Maier-Hein, Klaus, editor, Palm, Christoph, editor, and Tolxdorff, Thomas, editor

Published
2024
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19. Abstract: Reformulating COPD Classification on Chest CT Scans as Anomaly Detection using Contrastive Representations : cOOpD

Author

Almeida, Silvia D., Lüth, Carsten T., Norajitra, Tobias, Wald, Tassilo, Nolden, Marco, Jäger, Paul F., Heussel, Claus P., Biederer, Jürgen, Weinheimer, Oliver, Maier-Hein, Klaus H., Gesellschaft für Informatik e.V. (GI), Maier, Andreas, editor, Deserno, Thomas M., editor, Handels, Heinz, editor, Maier-Hein, Klaus, editor, Palm, Christoph, editor, and Tolxdorff, Thomas, editor

Published
2024
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20. Revision and Update of the Consensus Definitions of Invasive Fungal Disease From the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium

Author

Donnelly, J Peter, Chen, Sharon C, Kauffman, Carol A, Steinbach, William J, Baddley, John W, Verweij, Paul E, Clancy, Cornelius J, Wingard, John R, Lockhart, Shawn R, Groll, Andreas H, Sorrell, Tania C, Bassetti, Matteo, Akan, Hamdi, Alexander, Barbara D, Andes, David, Azoulay, Elie, Bialek, Ralf, Bradsher, Robert W, Bretagne, Stephane, Calandra, Thierry, Caliendo, Angela M, Castagnola, Elio, Cruciani, Mario, Cuenca-Estrella, Manuel, Decker, Catherine F, Desai, Sujal R, Fisher, Brian, Harrison, Thomas, Heussel, Claus Peter, Jensen, Henrik E, Kibbler, Christopher C, Kontoyiannis, Dimitrios P, Kullberg, Bart-Jan, Lagrou, Katrien, Lamoth, Frédéric, Lehrnbecher, Thomas, Loeffler, Jurgen, Lortholary, Olivier, Maertens, Johan, Marchetti, Oscar, Marr, Kieren A, Masur, Henry, Meis, Jacques F, Morrisey, C Orla, Nucci, Marcio, Ostrosky-Zeichner, Luis, Pagano, Livio, Patterson, Thomas F, Perfect, John R, Racil, Zdenek, Roilides, Emmanuel, Ruhnke, Marcus, Prokop, Cornelia Schaefer, Shoham, Shmuel, Slavin, Monica A, Stevens, David A, Thompson, George R, Vazquez, Jose A, Viscoli, Claudio, Walsh, Thomas J, Warris, Adilia, Wheat, L Joseph, White, P Lewis, Zaoutis, Theoklis E, and Pappas, Peter G

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Cancer, Prevention, Clinical Research, Good Health and Well Being, Antifungal Agents, Consensus, Humans, Immunocompromised Host, Invasive Fungal Infections, Mycoses, Neoplasms, consensus, definitions, invasive fungal diseases, diagnosis, research, Biological Sciences, Medical and Health Sciences, Microbiology, Clinical sciences
Abstract

BackgroundInvasive fungal diseases (IFDs) remain important causes of morbidity and mortality. The consensus definitions of the Infectious Diseases Group of the European Organization for Research and Treatment of Cancer and the Mycoses Study Group have been of immense value to researchers who conduct clinical trials of antifungals, assess diagnostic tests, and undertake epidemiologic studies. However, their utility has not extended beyond patients with cancer or recipients of stem cell or solid organ transplants. With newer diagnostic techniques available, it was clear that an update of these definitions was essential.MethodsTo achieve this, 10 working groups looked closely at imaging, laboratory diagnosis, and special populations at risk of IFD. A final version of the manuscript was agreed upon after the groups' findings were presented at a scientific symposium and after a 3-month period for public comment. There were several rounds of discussion before a final version of the manuscript was approved.ResultsThere is no change in the classifications of "proven," "probable," and "possible" IFD, although the definition of "probable" has been expanded and the scope of the category "possible" has been diminished. The category of proven IFD can apply to any patient, regardless of whether the patient is immunocompromised. The probable and possible categories are proposed for immunocompromised patients only, except for endemic mycoses.ConclusionsThese updated definitions of IFDs should prove applicable in clinical, diagnostic, and epidemiologic research of a broader range of patients at high-risk.

Published
2020

21. Global guideline for the diagnosis and management of mucormycosis: an initiative of the European Confederation of Medical Mycology in cooperation with the Mycoses Study Group Education and Research Consortium

Author

Cornely, Oliver A, Alastruey-Izquierdo, Ana, Arenz, Dorothee, Chen, Sharon CA, Dannaoui, Eric, Hochhegger, Bruno, Hoenigl, Martin, Jensen, Henrik E, Lagrou, Katrien, Lewis, Russell E, Mellinghoff, Sibylle C, Mer, Mervyn, Pana, Zoi D, Seidel, Danila, Sheppard, Donald C, Wahba, Roger, Akova, Murat, Alanio, Alexandre, Al-Hatmi, Abdullah MS, Arikan-Akdagli, Sevtap, Badali, Hamid, Ben-Ami, Ronen, Bonifaz, Alexandro, Bretagne, Stéphane, Castagnola, Elio, Chayakulkeeree, Methee, Colombo, Arnaldo L, Corzo-León, Dora E, Drgona, Lubos, Groll, Andreas H, Guinea, Jesus, Heussel, Claus-Peter, Ibrahim, Ashraf S, Kanj, Souha S, Klimko, Nikolay, Lackner, Michaela, Lamoth, Frederic, Lanternier, Fanny, Lass-Floerl, Cornelia, Lee, Dong-Gun, Lehrnbecher, Thomas, Lmimouni, Badre E, Mares, Mihai, Maschmeyer, Georg, Meis, Jacques F, Meletiadis, Joseph, Morrissey, C Orla, Nucci, Marcio, Oladele, Rita, Pagano, Livio, Pasqualotto, Alessandro, Patel, Atul, Racil, Zdenek, Richardson, Malcolm, Roilides, Emmanuel, Ruhnke, Markus, Seyedmousavi, Seyedmojtaba, Sidharthan, Neeraj, Singh, Nina, Sinko, János, Skiada, Anna, Slavin, Monica, Soman, Rajeev, Spellberg, Brad, Steinbach, William, Tan, Ban Hock, Ullmann, Andrew J, Vehreschild, Jörg J, Vehreschild, Maria JGT, Walsh, Thomas J, White, P Lewis, Wiederhold, Nathan P, Zaoutis, Theoklis, Chakrabarti, Arunaloke, and Group, Mucormycosis ECMM MSG Global Guideline Writing

Subjects
Clinical Research, Good Health and Well Being, Disease Management, Humans, Mucormycosis, Mucormycosis ECMM MSG Global Guideline Writing Group, Clinical Sciences, Medical Microbiology, Public Health and Health Services, Microbiology
Abstract

Mucormycosis is a difficult to diagnose rare disease with high morbidity and mortality. Diagnosis is often delayed, and disease tends to progress rapidly. Urgent surgical and medical intervention is lifesaving. Guidance on the complex multidisciplinary management has potential to improve prognosis, but approaches differ between health-care settings. From January, 2018, authors from 33 countries in all United Nations regions analysed the published evidence on mucormycosis management and provided consensus recommendations addressing differences between the regions of the world as part of the "One World One Guideline" initiative of the European Confederation of Medical Mycology (ECMM). Diagnostic management does not differ greatly between world regions. Upon suspicion of mucormycosis appropriate imaging is strongly recommended to document extent of disease and is followed by strongly recommended surgical intervention. First-line treatment with high-dose liposomal amphotericin B is strongly recommended, while intravenous isavuconazole and intravenous or delayed release tablet posaconazole are recommended with moderate strength. Both triazoles are strongly recommended salvage treatments. Amphotericin B deoxycholate is recommended against, because of substantial toxicity, but may be the only option in resource limited settings. Management of mucormycosis depends on recognising disease patterns and on early diagnosis. Limited availability of contemporary treatments burdens patients in low and middle income settings. Areas of uncertainty were identified and future research directions specified.

Published
2019

26. Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR).

Author

deSouza, Nandita, Achten, Eric, Alberich-Bayarri, Angel, Bamberg, Fabian, Boellaard, Ronald, Clément, Olivier, Fournier, Laure, Gallagher, Ferdia, Golay, Xavier, Heussel, Claus, Jackson, Edward, Manniesing, Rashindra, Mayerhofer, Marius, Neri, Emanuele, OConnor, James, Oguz, Kader, Persson, Anders, Smits, Marion, van Beek, Edwin, and Zech, Christoph

Subjects
Clinical decision making, Imaging biomarkers, Quantitation, Standardisation
Abstract

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.

Published
2019

32. Asynchronous calibration of quantitative computed tomography bone mineral density assessment for opportunistic osteoporosis screening: phantom-based validation and parameter influence evaluation

Author

Skornitzke, Stephan, Vats, Neha, Kopytova, Taisiya, Tong, Elizabeth Wai Yee, Hofbauer, Tobias, Weber, Tim Frederik, Rehnitz, Christoph, von Stackelberg, Oyunbileg, Maier-Hein, Klaus, Stiller, Wolfram, Biederer, Jürgen, Kauczor, Hans-Ulrich, Heußel, Claus-Peter, Wielpütz, Mark, and Palm, Viktoria

Published
2022
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33. Deciphering the immunosuppressive tumor microenvironment in ALK- and EGFR-positive lung adenocarcinoma

Author

Budczies, Jan, Kirchner, Martina, Kluck, Klaus, Kazdal, Daniel, Glade, Julia, Allgäuer, Michael, Kriegsmann, Mark, Heußel, Claus-Peter, Herth, Felix J., Winter, Hauke, Meister, Michael, Muley, Thomas, Goldmann, Torsten, Fröhling, Stefan, Wermke, Martin, Waller, Cornelius F., Tufman, Amanda, Reck, Martin, Peters, Solange, Schirmacher, Peter, Thomas, Michael, Christopoulos, Petros, and Stenzinger, Albrecht

Published
2022
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34. Abstract: Automated Detection and Quantification of Brain Metastases on Clinical MRI Data using CNNs

Author

Pflüger, Irada, Wald, Tassilo, Isensee, Fabian, Schell, Marianne, Meredig, Hagen, Schlamp, Kai, Bernhardt, Denise, Brugnara, Gianluca, Heußel, Claus P., Debus, Juergen, Wick, Wolfgang, Bendszus, Martin, Maier-Hein, Klaus, Vollmuth, Philipp, Gesellschaft für Informatik e.V. (GI), Deserno, Thomas M., editor, Handels, Heinz, editor, Maier, Andreas, editor, Maier-Hein, Klaus, editor, Palm, Christoph, editor, and Tolxdorff, Thomas, editor

Published
2023
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35. A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data

Author

Salg, Gabriel Alexander, Ganten, Maria-Katharina, Bucher, Andreas Michael, Kenngott, Hannes Goetz, Fink, Matthias Alexander, Seibold, Constantin, Fischbach, Ricarda Elisabeth, Schlamp, Kai, Velandia, Carlos Alberto, Fervers, Philipp, Doellinger, Felix, Luger, Anna, Afat, Saif, Merle, Uta, Diener, Markus K., Pereira, Philippe L., Penzkofer, Tobias, Persigehl, Thorsten, Othman, Ahmed, Heußel, Claus Peter, Baumhauer, Matthias, Widmann, Gerlig, Stathopoulos, Konstantinos, Hamm, Bernd, Vogl, Thomas J., Nikolaou, Konstantin, Kauczor, Hans-Ulrich, and Kleesiek, Jens

Published
2021
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38. Elexacaftor/Tezacaftor/Ivacaftor Improves Bronchial Artery Dilatation Detected by Magnetic Resonance Imaging in Patients with Cystic Fibrosis

Author

Wucherpfennig, Lena, primary, Triphan, Simon M. F., additional, Wege, Sabine, additional, Kauczor, Hans-Ulrich, additional, Heussel, Claus P., additional, Sommerburg, Olaf, additional, Stahl, Mirjam, additional, Mall, Marcus A., additional, Eichinger, Monika, additional, and Wielpütz, Mark O., additional

Published
2023
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39. Influence of CT dose reduction on AI-driven malignancy estimation of incidental pulmonary nodules

Author

Peters, Alan A., primary, Solomon, Justin B., additional, von Stackelberg, Oyunbileg, additional, Samei, Ehsan, additional, Alsaihati, Njood, additional, Valenzuela, Waldo, additional, Debic, Manuel, additional, Heidt, Christian, additional, Huber, Adrian T., additional, Christe, Andreas, additional, Heverhagen, Johannes T., additional, Kauczor, Hans-Ulrich, additional, Heussel, Claus P., additional, Ebner, Lukas, additional, and Wielpütz, Mark O., additional

Published
2023
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44. High‐resolution transcriptomic and epigenetic profiling identifies novel regulators of COPD

Author

Schwartz, Uwe, primary, Llamazares Prada, Maria, additional, Pohl, Stephanie T, additional, Richter, Mandy, additional, Tamas, Raluca, additional, Schuler, Michael, additional, Keller, Corinna, additional, Mijosek, Vedrana, additional, Muley, Thomas, additional, Schneider, Marc A, additional, Quast, Karsten, additional, Hey, Joschka, additional, Heußel, Claus P, additional, Warth, Arne, additional, Winter, Hauke, additional, Serçin, Özdemirhan, additional, Karmouty‐Quintana, Harry, additional, Jyothula, Soma SK, additional, Patel, Manish K, additional, Herth, Felix, additional, Koch, Ina, additional, Petrosino, Giuseppe, additional, Titimeaua, Alexandru, additional, Mardin, Balca R, additional, Weichenhan, Dieter, additional, Jurkowski, Tomasz P, additional, Imbusch, Charles D, additional, Brors, Benedikt, additional, Benes, Vladimir, additional, Jung, Birgit, additional, Wyatt, David, additional, Stahl, Heiko F, additional, Plass, Christoph, additional, and Jurkowska, Renata Z, additional

Published
2023
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45. MRI Compared with Low-Dose CT for Incidental Lung Nodule Detection in COPD: A Multicenter Trial

Author

Li, Qian, Zhu, Lin, von Stackelberg, Oyunbileg, Triphan, Simon M. F., Biederer, Jürgen, Weinheimer, Oliver, Eichinger, Monika, Vogelmeier, Claus F., Jörres, Rudolf A., Kauczor, Hans-Ulrich, Heußel, Claus P., Jobst, Bertram J., and Wielpütz, Mark O.

Subjects
Original Research
Abstract

PURPOSE: To investigate morphofunctional chest MRI for the detection and management of incidental pulmonary nodules in participants with chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: In this prospective study, 567 participants (mean age, 66 years ± 9 [SD]; 340 men) underwent same-day contrast-enhanced MRI and nonenhanced low-dose CT (LDCT) in a nationwide multicenter trial (clinicaltrials.gov: NCT01245933). Nodule dimensions, morphologic features, and Lung Imaging Reporting and Data System (Lung-RADS) category were assessed at MRI by two blinded radiologists, and consensual LDCT results served as the reference standard. Comparisons were performed using the Student t test, and agreements were assessed using the Cohen weighted κ. RESULTS: A total of 525 nodules larger than 3 mm in diameter were detected at LDCT in 178 participants, with a mean diameter of 7.2 mm ± 6.1 (range, 3.1–63.1 mm). Nodules were not detected in the remaining 389 participants. Sensitivity and positive predictive values with MRI for readers 1 and 2, respectively, were 63.0% and 84.8% and 60.2% and 83.9% for solid nodules (n = 495), 17.6% and 75.0% and 17.6% and 60.0% for part-solid nodules (n = 17), and 7.7% and 100% and 7.7% and 50.0% for ground-glass nodules (n = 13). For nodules 6 mm or greater in diameter, sensitivity and positive predictive values were 73.3% and 92.2% for reader 1 and 71.4% and 93.2% for reader 2, respectively. Readers underestimated the long-axis diameter at MRI by 0.5 mm ± 1.7 (reader 1) and 0.5 mm ± 1.5 (reader 2) compared with LDCT (P < .001). For Lung-RADS categorization per nodule using MRI, there was substantial to perfect interreader agreement (κ = 0.75–1.00) and intermethod agreement compared with LDCT (κ = 0.70–1.00 and 0.69–1.00). CONCLUSION: In a multicenter setting, morphofunctional MRI showed moderate sensitivity for detection of incidental pulmonary nodules in participants with COPD but high agreement with LDCT for Lung-RADS classification of nodules. Clinical trial registration no. NCT01245933 and NCT02629432 Keywords: MRI, CT, Thorax, Lung, Chronic Obstructive Pulmonary Disease, Screening © RSNA, 2023 Supplemental material is available for this article.

Published
2023

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