{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:09:40Z","timestamp":1740107380342,"version":"3.37.3"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T00:00:00Z","timestamp":1597968000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T00:00:00Z","timestamp":1597968000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Charit\u00e9"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"published-print":{"date-parts":[[2021,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Objectives<\/jats:title>\n                <jats:p>To evaluate texture analysis in nonenhanced 3-T MRI for differentiating pulmonary fungal infiltrates and lymphoma manifestations in hematological patients and to compare the diagnostic performance with that of signal intensity quotients (\u201cnonenhanced imaging characterization quotients,\u201d NICQs).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>MR scans were performed using a speed-optimized imaging protocol without an intravenous contrast medium including axial T2-weighted (T2w) single-shot fast spin-echo and T1-weighted (T1w) gradient-echo sequences. ROIs were drawn within the lesions to extract first-order statistics from original images using HeterogeneityCAD and PyRadiomics. NICQs were calculated using signal intensities of the lesions, muscle, and fat. The standard of reference was histology or clinical diagnosis in follow-up. Statistical testing included ROC analysis, clustered ROC analysis, and DeLong test. Intra- and interrater reliability was tested using intraclass correlation coefficients (ICC).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Thirty-three fungal infiltrates in 16 patients and 38 pulmonary lymphoma manifestations in 19 patients were included. Considering the leading lesion in each patient, diagnostic performance was excellent for T1w entropy (AUC 80.2%; <jats:italic>p<\/jats:italic>\u2009&lt; 0.005) and slightly inferior for T2w energy (79.9%; <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.005), T1w uniformity (79.6%; <jats:italic>p<\/jats:italic>\u2009&lt; 0.005), and T1w energy (77.0%; <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.01); the best AUC for NICQs was 72.0% for T2NICQmean (<jats:italic>p<\/jats:italic>\u2009&lt; 0.05). Intra- and interrater reliability was good to excellent (ICC\u2009&gt;\u20090.81) for these parameters except for moderate intrarater reliability of T1w energy (ICC\u2009=\u20090.64).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>T1w entropy, uniformity, and energy and T2w energy showed the best performances for differentiating pulmonary lymphoma and fungal pneumonia and outperformed NICQs. Results of the texture analysis should be checked for their intrinsic consistency to identify possible incongruities of single parameters.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Key Points<\/jats:title>\n                <jats:p><jats:italic>\u2022 Texture analysis in nonenhanced pulmonary MRI improves the differentiation of pulmonary lymphoma and fungal pneumonia compared with signal intensity quotients.<\/jats:italic><\/jats:p>\n                <jats:p><jats:italic>\u2022 T1w entropy, uniformity, and energy along with T2w energy show the best performances for differentiating pulmonary lymphoma from fungal pneumonia.<\/jats:italic><\/jats:p>\n                <jats:p><jats:italic>\u2022 The results of the texture analysis should be checked for their intrinsic consistency to identify possible incongruities of single parameters.<\/jats:italic><\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00330-020-07137-5","type":"journal-article","created":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T10:20:45Z","timestamp":1598005245000},"page":"695-705","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Enhancing the differentiation of pulmonary lymphoma and fungal pneumonia in hematological patients using texture analysis in 3-T MRI"],"prefix":"10.1007","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3145-7559","authenticated-orcid":false,"given":"Damon","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Elgeti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tobias","family":"Penzkofer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ingo G.","family":"Steffen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura J.","family":"Jensen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Schwartz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bernd","family":"Hamm","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sebastian N.","family":"Nagel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,8,21]]},"reference":[{"key":"7137_CR1","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.rcl.2013.08.010","volume":"52","author":"J Ahuja","year":"2014","unstructured":"Ahuja J, Kanne JP (2014) Thoracic infections in immunocompromised patients. Radiol Clin North Am 52:121\u2013136","journal-title":"Radiol Clin North Am"},{"key":"7137_CR2","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1016\/j.amjms.2019.01.009","volume":"357","author":"XY Zhang","year":"2019","unstructured":"Zhang XY, Gu DM, Guo JJ, Su QQ, Chen YB (2019) Primary pulmonary lymphoma: a retrospective analysis of 27 cases in a single tertiary hospital. Am J Med Sci 357:316\u2013322","journal-title":"Am J Med Sci"},{"key":"7137_CR3","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1259\/bjr\/77712845","volume":"78","author":"YR Lee","year":"2005","unstructured":"Lee YR, Choi YW, Lee KJ, Jeon SC, Park CK, Heo JN (2005) CT halo sign: the spectrum of pulmonary diseases. Br J Radiol 78:862\u2013865","journal-title":"Br J Radiol"},{"key":"7137_CR4","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1097\/RTI.0000000000000342","volume":"33","author":"N Tanaka","year":"2018","unstructured":"Tanaka N, Kunihiro Y, Yanagawa N (2018) Infection in immunocompromised hosts: imaging. J Thorac Imaging 33:306\u2013321","journal-title":"J Thorac Imaging"},{"key":"7137_CR5","doi-asserted-by":"publisher","first-page":"1408","DOI":"10.1183\/09031936.00039309","volume":"34","author":"R Borie","year":"2009","unstructured":"Borie R, Wislez M, Thabut G et al (2009) Clinical characteristics and prognostic factors of pulmonary MALT lymphoma. Eur Respir J 34:1408\u20131416","journal-title":"Eur Respir J"},{"key":"7137_CR6","first-page":"2065","volume":"20","author":"A Nahorecki","year":"2016","unstructured":"Nahorecki A, Chabowski M, Straszak E et al (2016) Primary pulmonary MALT lymphoma - case report and literature overview. Eur Rev Med Pharmacol Sci 20:2065\u20132069","journal-title":"Eur Rev Med Pharmacol Sci"},{"key":"7137_CR7","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1186\/s12885-018-4184-1","volume":"18","author":"D Yao","year":"2018","unstructured":"Yao D, Zhang L, Wu PL et al (2018) Clinical and misdiagnosed analysis of primary pulmonary lymphoma: a retrospective study. BMC Cancer 18:281","journal-title":"BMC Cancer"},{"key":"7137_CR8","doi-asserted-by":"publisher","first-page":"920","DOI":"10.1136\/thorax.58.11.920","volume":"58","author":"A Manhire","year":"2003","unstructured":"Manhire A, Charig M, Clelland C et al (2003) Guidelines for radiologically guided lung biopsy. Thorax. 58:920\u2013936","journal-title":"Thorax."},{"key":"7137_CR9","doi-asserted-by":"publisher","first-page":"1119","DOI":"10.1097\/01.RVI.0000086536.86489.82","volume":"14","author":"ML Martin","year":"2003","unstructured":"Martin ML, Lennox PH (2003) Sedation and analgesia in the interventional radiology department. J Vasc Interv Radiol 14:1119\u20131128","journal-title":"J Vasc Interv Radiol"},{"key":"7137_CR10","doi-asserted-by":"publisher","first-page":"2915","DOI":"10.1007\/s00330-015-4125-1","volume":"26","author":"N Henz Concatto","year":"2016","unstructured":"Henz Concatto N, Watte G, Marchiori E et al (2016) Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease-endemic region. Eur Radiol 26:2915\u20132920","journal-title":"Eur Radiol"},{"key":"7137_CR11","doi-asserted-by":"publisher","first-page":"W210","DOI":"10.2214\/AJR.13.11618","volume":"202","author":"Y Kurihara","year":"2014","unstructured":"Kurihara Y, Matsuoka S, Yamashiro T et al (2014) MRI of pulmonary nodules. AJR Am J Roentgenol 202:W210\u2013W216","journal-title":"AJR Am J Roentgenol"},{"key":"7137_CR12","doi-asserted-by":"publisher","first-page":"11248","DOI":"10.1038\/s41598-018-29534-z","volume":"8","author":"F Zhang","year":"2018","unstructured":"Zhang F, Zhou Z, Tang D et al (2018) Diffusion-weighted MRI in solitary pulmonary lesions: associations between apparent diffusion coefficient and multiple histopathological parameters. Sci Rep 8:11248","journal-title":"Sci Rep"},{"key":"7137_CR13","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1016\/j.clinimag.2016.08.017","volume":"40","author":"B Jiang","year":"2016","unstructured":"Jiang B, Liu H, Zhou D (2016) Diagnostic and clinical utility of dynamic contrast-enhanced MR imaging in indeterminate pulmonary nodules: a metaanalysis. Clin Imaging 40:1219\u20131225","journal-title":"Clin Imaging"},{"key":"7137_CR14","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1002\/jmri.25977","volume":"48","author":"L Chen","year":"2018","unstructured":"Chen L, Liu D, Zhang J et al (2018) Free-breathing dynamic contrast-enhanced MRI for assessment of pulmonary lesions using golden-angle radial sparse parallel imaging. J Magn Reson Imaging 48:459\u2013468","journal-title":"J Magn Reson Imaging"},{"key":"7137_CR15","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.ejrad.2017.01.012","volume":"89","author":"SN Nagel","year":"2017","unstructured":"Nagel SN, Kim D, Penzkofer T et al (2017) Pulmonary MRI at 3T: non-enhanced pulmonary magnetic resonance imaging characterization quotients for differentiation of infectious and malignant lesions. Eur J Radiol 89:33\u201339","journal-title":"Eur J Radiol"},{"key":"7137_CR16","doi-asserted-by":"publisher","first-page":"e11172","DOI":"10.1097\/MD.0000000000011172","volume":"97","author":"SR Digumarthy","year":"2018","unstructured":"Digumarthy SR, Padole AM, Lo Gullo R, Singh R, Shepard JO, Kalra MK (2018) CT texture analysis of histologically proven benign and malignant lung lesions. Medicine (Baltimore) 97:e11172","journal-title":"Medicine (Baltimore)"},{"key":"7137_CR17","unstructured":"HeterogeneityCAD for Slicer 3D. Accessed at https:\/\/www.slicer.org\/wiki\/Documentation\/Nightly\/Modules\/HeterogeneityCAD. Accessed 30 Aug 2019"},{"key":"7137_CR18","doi-asserted-by":"publisher","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","volume":"77","author":"JJM van Griethuysen","year":"2017","unstructured":"van Griethuysen JJM, Fedorov A, Parmar C et al (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77:e104\u2013e1e7","journal-title":"Cancer Res"},{"key":"7137_CR19","doi-asserted-by":"publisher","unstructured":"Nagel SN, Kim D, Wylutzki T et al (2019) Diagnostic performance and reliability of non-enhanced imaging characterization quotients for the differentiation of infectious and malignant pulmonary nodules in hematological patients using 3T MRI. Rofo. https:\/\/doi.org\/10.1055\/a-1005-7424","DOI":"10.1055\/a-1005-7424"},{"key":"7137_CR20","doi-asserted-by":"publisher","first-page":"1813","DOI":"10.1086\/588660","volume":"46","author":"B De Pauw","year":"2008","unstructured":"De Pauw B, Walsh TJ, Donnelly JP et al (2008) Revised definitions of invasive fungal disease from the European Organization for Research and Treatment of Cancer\/Invasive Fungal Infections Cooperative Group and the National Institute of Allergy and Infectious Diseases Mycoses Study Group (EORTC\/MSG) Consensus Group. Clin Infect Dis 46:1813\u20131821","journal-title":"Clin Infect Dis"},{"key":"7137_CR21","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1007\/s13244-011-0146-8","volume":"3","author":"J Biederer","year":"2012","unstructured":"Biederer J, Beer M, Hirsch W et al (2012) MRI of the lung (2\/3). Why ... when ... how? Insights Imaging 3:355\u2013371","journal-title":"Insights Imaging"},{"key":"7137_CR22","doi-asserted-by":"publisher","first-page":"e61","DOI":"10.1016\/j.ejrad.2013.09.002","volume":"83","author":"UI Attenberger","year":"2014","unstructured":"Attenberger UI, Morelli JN, Henzler T et al (2014) 3 Tesla proton MRI for the diagnosis of pneumonia\/lung infiltrates in neutropenic patients with acute myeloid leukemia: initial results in comparison to HRCT. Eur J Radiol 83:e61\u2013e66","journal-title":"Eur J Radiol"},{"key":"7137_CR23","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1016\/j.ejrad.2016.02.009","volume":"85","author":"SN Nagel","year":"2016","unstructured":"Nagel SN, Wyschkon S, Schwartz S, Hamm B, Elgeti T (2016) Can magnetic resonance imaging be an alternative to computed tomography in immunocompromised patients with suspected fungal infections? Feasibility of a speed optimized examination protocol at 3 Tesla. Eur J Radiol 85:857\u2013863","journal-title":"Eur J Radiol"},{"key":"7137_CR24","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1016\/j.mri.2012.05.001","volume":"30","author":"A Fedorov","year":"2012","unstructured":"Fedorov A, Beichel R, Kalpathy-Cramer J et al (2012) 3D Slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 30:1323\u20131341","journal-title":"Magn Reson Imaging"},{"key":"7137_CR25","doi-asserted-by":"publisher","first-page":"567","DOI":"10.2307\/2533958","volume":"53","author":"NA Obuchowski","year":"1997","unstructured":"Obuchowski NA (1997) Nonparametric analysis of clustered ROC curve data. Biometrics. 53:567\u2013578","journal-title":"Biometrics."},{"key":"7137_CR26","doi-asserted-by":"publisher","DOI":"10.1002\/0471722146","volume-title":"Applied logistic regression","author":"DW Hosmer","year":"2000","unstructured":"Hosmer DW, Lemeshow S (2000) Applied logistic regression, 2nd edn. Wiley, New York","edition":"2"},{"key":"7137_CR27","doi-asserted-by":"publisher","first-page":"837","DOI":"10.2307\/2531595","volume":"44","author":"ER DeLong","year":"1988","unstructured":"DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 44:837\u2013845","journal-title":"Biometrics."},{"key":"7137_CR28","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","volume":"15","author":"TK Koo","year":"2016","unstructured":"Koo TK, Li MY (2016) A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 15:155\u2013163","journal-title":"J Chiropr Med"},{"key":"7137_CR29","doi-asserted-by":"publisher","first-page":"750","DOI":"10.1183\/09031936.02.00404102","volume":"20","author":"J Cadranel","year":"2002","unstructured":"Cadranel J, Wislez M, Antoine M (2002) Primary pulmonary lymphoma. Eur Respir J 20:750\u2013762","journal-title":"Eur Respir J"},{"key":"7137_CR30","unstructured":"PyRadiomics documentation. Accessed at https:\/\/pyradiomics.readthedocs.io\/en\/latest\/features.html#module-radiomics.firstorder. Accessed 18 Nov 2019"},{"key":"7137_CR31","first-page":"w14281","volume":"146","author":"Y Schmiedel","year":"2016","unstructured":"Schmiedel Y, Zimmerli S (2016) Common invasive fungal diseases: an overview of invasive candidiasis, aspergillosis, cryptococcosis, and Pneumocystis pneumonia. Swiss Med Wkly 146:w14281","journal-title":"Swiss Med Wkly"},{"key":"7137_CR32","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1128\/CMR.00053-10","volume":"24","author":"J Guarner","year":"2011","unstructured":"Guarner J, Brandt ME (2011) Histopathologic diagnosis of fungal infections in the 21st century. Clin Microbiol Rev 24:247\u2013280","journal-title":"Clin Microbiol Rev"},{"key":"7137_CR33","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1053\/j.semdp.2017.06.002","volume":"34","author":"AC Roden","year":"2017","unstructured":"Roden AC, Schuetz AN (2017) Histopathology of fungal diseases of the lung. Semin Diagn Pathol 34:530\u2013549","journal-title":"Semin Diagn Pathol"},{"key":"7137_CR34","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1259\/bjr\/16420165","volume":"85","author":"SS Hare","year":"2012","unstructured":"Hare SS, Souza CA, Bain G et al (2012) The radiological spectrum of pulmonary lymphoproliferative disease. Br J Radiol 85:848\u2013864","journal-title":"Br J Radiol"},{"key":"7137_CR35","doi-asserted-by":"publisher","first-page":"382","DOI":"10.5858\/arpa.2012-0202-RA","volume":"137","author":"J William","year":"2013","unstructured":"William J, Variakojis D, Yeldandi A, Raparia K (2013) Lymphoproliferative neoplasms of the lung: a review. Arch Pathol Lab Med 137:382\u2013391","journal-title":"Arch Pathol Lab Med"},{"key":"7137_CR36","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.1016\/j.acra.2016.04.009","volume":"23","author":"S Suo","year":"2016","unstructured":"Suo S, Cheng J, Cao M et al (2016) Assessment of heterogeneity difference between edge and core by using texture analysis: differentiation of malignant from inflammatory pulmonary nodules and masses. Acad Radiol 23:1115\u20131122","journal-title":"Acad Radiol"},{"key":"7137_CR37","doi-asserted-by":"publisher","first-page":"1520","DOI":"10.1016\/j.acra.2007.06.028","volume":"14","author":"B Ganeshan","year":"2007","unstructured":"Ganeshan B, Miles KA, Young RC, Chatwin CR (2007) Hepatic enhancement in colorectal cancer: texture analysis correlates with hepatic hemodynamics and patient survival. Acad Radiol 14:1520\u20131530","journal-title":"Acad Radiol"}],"container-title":["European Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-020-07137-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00330-020-07137-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-020-07137-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,20]],"date-time":"2021-08-20T23:16:38Z","timestamp":1629501398000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00330-020-07137-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,21]]},"references-count":37,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["7137"],"URL":"https:\/\/doi.org\/10.1007\/s00330-020-07137-5","relation":{},"ISSN":["0938-7994","1432-1084"],"issn-type":[{"type":"print","value":"0938-7994"},{"type":"electronic","value":"1432-1084"}],"subject":[],"published":{"date-parts":[[2020,8,21]]},"assertion":[{"value":"27 March 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 June 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 August 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The scientific guarantor of this publication is Sebastian Nagel, MD, Charit\u00e9 - Universit\u00e4tsmedizin Berlin.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Guarantor"}},{"value":"Bernd Hamm is Grant Recipient for the Department of Radiology, Charit\u00e9, and has further received funding from Abbott, AbbVie, Ablative Solutions, Accovion, Achaogen lnc., Actelion Pharmaceuticals, ADIR, Aesculap, AGO, AIF Arbeitsgemeinschaft industrieller Forschungsvereinigungen, AIO Arbeitsgemeinschaft lnternistische Onkologie, Alexion Pharmaceuticals, Amgen, AO Foundation, Arena Pharmaceuticals, art photonics GmbH Berlin, ASR Advanced sleep research, Astellas, AstraZeneca, BARD, Bayer Healthcare, Bayer Schering Pharma, Bayer Vital, BBraun, Berlin-Brandenburger Centrum f\u00fcr Regenerative Therapien (BCRT), Berliner Krebsgesellschaft, Biotronik, Bioven, BMBF Bundesministerium f\u00fcr Bildung und Forschung, Boehring Ingelheimer, Boston Biomedical Inc., BRACCO Group, Brainsgate, Bristol-Myers Squibb, Cascadian Therapeutics, lnc., Celgene, CELLACT Pharma, Celldex Therapeutics, CeIoNova BioSciences, Charit\u00e9 research organisation GmbH, Chiltern, CCovance, CUBIST, Curis, Daiichi, DC Devices, lnc. USA, Delcath Systems, Dermira lnc., Deutsche Krebshilfe, Deutsche Rheuma Liga, DFG, DSM Nutritional Products AG, Dt. Stiftung f\u00fcr Herzforschung, Dynavax, Eisai Ltd.\u201a European Knowledge Centre, Mosquito Way, Hatfield, Eli Lilly and Company Ltd., EORTC, Epizyme, Inc., Essex Pharma, EU Programmes, Euroscreen S.A., Fibrex Medical Inc., Focused Ultrasound Surgery Foundation, Fraunhofer Gesellschaft, Galena Biopharma, Galmed Research and Development Ltd., Ganymed, GE, Genentech. Inc., GETNE (Grupo Espa\u00f1ol de Tumores Neuroendocrinos), Gilead Sciences, Inc., Glaxo Smith Kline, Glycotope GmbH, Berlin, Goethe Uni Frankfurt, Guerbet, Guidant Europe NV, Halozyme, Holaira Inc., ICON (CRO), Immunomedics Inc., Immunocore, Incyte, INC Research, Innate Pharma, InSightec Ltd., Inspiremd, inVentiv Health Clinical UK Ltd., Inventivhealth, IOMEDICO, IONIS, IPSEN Pharma, ISA Therapeutics, lsis Pharmaceuticals Inc., ITM Solution GmbH, Jansen, Kantar Health GmbH (CRO), Karyopharm Therapeutics, Inc., Kendle\/MorphoSys AG, Kite Pharma, La Roche, Land Berlin, Lilly GmbH, Lion Biotechnology, Lombard Medical, Loxo Oncology, lnc, LSK BioPartners; USA, Lundbeck GmbH, LUX Biosciences, LYSARC, MacroGenics, MagForce, Medlmmune lnc., Medlmmune Limited, Medpace, Medpace Germany GmbH (CRO), MedPass (CRO), Medronic, Merck, Merrimack Pharmaceuticals lnc, MeVis Medical Solutions AG, Millennium Pharmaceuticals Inc., Mologen, MSD Sharp, NeoVacs SA, Nexus Oncology, Novartis, novocure, Nuvisan, Ockham oncology, Orion Corporation Orion Pharma, Parexel CRO Service, Perceptive, Pfizer GmbH, Pharma Mar, Pharmaceutical Research Associates GmbH (PRA), Pharmacyclics Inc., Philipps, PIQUR Therapeutics Ltd., Pluristem, Portola Pharmaceuticals, PPD (CRO), PRAint, Premier-research, Provectus Biopharmaceuticals, Inc., psi-cro, Pulmonx International S\u00e0rl, Quintiles Gmbh, Respicardia, Roche, Samsung, Sanofi, sanofis-aventis S.A, Schumacher GmbH, Seattle Genetics, Servier (CRO), SGS Life Science Services (CRO), Siemens, Silena Therapeutics, Spectranetics GmbH, Spectrum Pharmaceuticals, St. Jude Medical, Stiftung Wolfgang Schulze, Symphogen, Taiho Pharmaceutical Co., Taqu Therapeutics Ltd., Terumo Medical Corporation, Tesaro, TETEC AG, TEVA, Theorem, Theradex, Threshold Pharmaceuticals Inc., TNS Healthcare GmbH, Toshiba, UCB Pharma, Uni M\u00fcnchen, VDI\/VDE, Winicker Norimed, Wyeth Pharma, Xcovery Holding Company, Zukunftsfond Berlin (TSB).Stephan Schwartz reports personal fees and non-financial support from Basilea Pharmaceutica, personal fees and non-financial support from Gilead, personal fees and non-financial support from MSD Sharp & Dohme, personal fees and non-financial support from Pfizer, during the conduct of the study; personal fees and non-financial support from AMGEN, personal fees and non-financial support from BTG International Inc., other from GlaxoSmithKline, personal fees and non-financial support from Jazz Pharmaceuticals, outside the submitted work.Tobias Penzkofer receives grant support from the Berlin Institute of Health within the Clinician Scientist Programme and the Platform programme. TP declares no additional conflict of interest with respect to the relation to the work described. Outside of the current work, there are institutional relationships with the following entities (no personal payments to TP): research support from Siemens Healthcare and Philips Healthcare, clinical trials with AGO, Aprea AB, Astellas Pharma Global Inc., AstraZeneca, Celgene, Genmab A\/S, Incyte Coporation, Lion Biotechnologies, Inc., Millennium Pharmaceuticals, Inc., Morphotec Inc., MSD, Tesaro Inc., and Roche.The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"One of the authors (I.S.) has significant statistical expertise.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was obtained from all subjects (patients) in this study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was obtained.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"This is a subset of patients from a larger prospective study focusing on the use of signal intensity quotients for the differentiation of pulmonary lesions. The results are accepted for publication in another journal and are currently in press. For the texture analysis, the MRI scans were re-evaluated retrospectively.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"value":"\u2022 prospective\u2022 observational\u2022 performed at one institution","order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}