{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T07:44:40Z","timestamp":1777362280564,"version":"3.51.4"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,2,9]],"date-time":"2023-02-09T00:00:00Z","timestamp":1675900800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,2,9]],"date-time":"2023-02-09T00:00:00Z","timestamp":1675900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["8187354"],"award-info":[{"award-number":["8187354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["8187354"],"award-info":[{"award-number":["8187354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["8187354"],"award-info":[{"award-number":["8187354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["8187354"],"award-info":[{"award-number":["8187354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["8187354"],"award-info":[{"award-number":["8187354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["8187354"],"award-info":[{"award-number":["8187354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["8187354"],"award-info":[{"award-number":["8187354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["8187354"],"award-info":[{"award-number":["8187354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Academic promotion programme of Shandong First Medical University","award":["2019QL023"],"award-info":[{"award-number":["2019QL023"]}]},{"name":"Academic promotion programme of Shandong First Medical University","award":["2019QL023"],"award-info":[{"award-number":["2019QL023"]}]},{"name":"Academic promotion programme of Shandong First Medical University","award":["2019QL023"],"award-info":[{"award-number":["2019QL023"]}]},{"name":"Academic promotion programme of Shandong First Medical University","award":["2019QL023"],"award-info":[{"award-number":["2019QL023"]}]},{"name":"Academic promotion programme of Shandong First Medical University","award":["2019QL023"],"award-info":[{"award-number":["2019QL023"]}]},{"name":"Academic promotion programme of Shandong First Medical University","award":["2019QL023"],"award-info":[{"award-number":["2019QL023"]}]},{"name":"Academic promotion programme of Shandong First Medical University","award":["2019QL023"],"award-info":[{"award-number":["2019QL023"]}]},{"name":"Academic promotion programme of Shandong First Medical University","award":["2019QL023"],"award-info":[{"award-number":["2019QL023"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Imaging"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Differentiating between solitary spinal metastasis (SSM) and solitary primary spinal tumor (SPST) is essential for treatment decisions and prognosis. The aim of this study was to develop and validate an MRI-based radiomics nomogram for discriminating SSM from SPST.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>One hundred and thirty-five patients with solitary spinal tumors were retrospectively studied and the data set was\u00a0divided\u00a0into\u00a0two\u00a0groups: a training set (n\u2009=\u200998) and a validation set (n\u2009=\u200937). Demographics and MRI characteristic features were evaluated to build a clinical factors model. Radiomics features were extracted from sagittal T1-weighted and fat-saturated T2-weighted images, and a radiomics signature model was constructed. A radiomics nomogram was established by combining radiomics features and significant clinical factors. The diagnostic performance of the three models was evaluated using receiver operator characteristic (ROC) curves on the training and validation sets. The Hosmer\u2013Lemeshow test was performed to assess the calibration capability of radiomics nomogram, and we used decision curve analysis (DCA) to estimate the clinical usefulness.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The age, signal, and boundaries were used to construct the clinical factors model. Twenty-six features from MR images were used to build the radiomics signature. The radiomics nomogram achieved good performance for differentiating SSM from SPST with an area under the curve (AUC) of 0.980 in the training set and an AUC of 0.924 in the validation set. The Hosmer\u2013Lemeshow test and decision curve analysis demonstrated the radiomics nomogram outperformed the clinical factors model.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>A radiomics nomogram as a noninvasive diagnostic method, which combines radiomics features and clinical factors, is helpful in distinguishing between SSM and SPST.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12880-023-00978-8","type":"journal-article","created":{"date-parts":[[2023,2,9]],"date-time":"2023-02-09T03:04:10Z","timestamp":1675911850000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["MRI-based radiomics nomogram for differentiation of solitary metastasis and solitary primary tumor in the spine"],"prefix":"10.1186","volume":"23","author":[{"given":"Sha","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinxin","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongchao","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baosen","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ran","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bing","family":"Kang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fangyuan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ximing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,2,9]]},"reference":[{"issue":"2","key":"978_CR1","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1177\/107327481402100205","volume":"21","author":"PE Kaloostian","year":"2014","unstructured":"Kaloostian PE, Zadnik PL, Etame AB, Vrionis FD, Gokaslan ZL, Sciubba DM. Surgical management of primary and metastatic spinal tumors. Cancer Control. 2014;21(2):133\u20139.","journal-title":"Cancer Control"},{"issue":"4","key":"978_CR2","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1016\/S1470-2045(11)70384-9","volume":"13","author":"XS Wang","year":"2012","unstructured":"Wang XS, Rhines LD, Shiu AS, Yang JN, Selek U, Gning I, Liu P, Allen PK, Azeem SS, Brown PD, et al. Stereotactic body radiation therapy for management of spinal metastases in patients without spinal cord compression: a phase 1\u20132 trial. Lancet Oncol. 2012;13(4):395\u2013402.","journal-title":"Lancet Oncol"},{"issue":"1","key":"978_CR3","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1055\/s-0038-1675551","volume":"23","author":"D Albano","year":"2019","unstructured":"Albano D, Messina C, Gitto S, Papakonstantinou O, Sconfienza LM. Differential diagnosis of spine tumors: my favorite mistake. Semin Musculoskelet Radiol. 2019;23(1):26\u201335.","journal-title":"Semin Musculoskelet Radiol"},{"issue":"4","key":"978_CR4","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1148\/rg.284075156","volume":"28","author":"MH Rodallec","year":"2008","unstructured":"Rodallec MH, Feydy A, Larousserie F, Anract P, Campagna R, Babinet A, Zins M, Drap\u00e9 J-L. Diagnostic imaging of solitary tumors of the spine: what to do and say. Radiographics. 2008;28(4):1019\u201341.","journal-title":"Radiographics"},{"key":"978_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbo.2018.100213","volume":"14","author":"L Zhang","year":"2019","unstructured":"Zhang L, Wang Y, Gu Y, Hou Y, Chen Z. The need for bone biopsies in the diagnosis of new bone lesions in patients with a known primary malignancy: a comparative review of 117 biopsy cases. J Bone Oncol. 2019;14: 100213.","journal-title":"J Bone Oncol"},{"issue":"6","key":"978_CR6","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.2214\/AJR.12.10261","volume":"201","author":"B Raphael","year":"2013","unstructured":"Raphael B, Hwang S, Lefkowitz RA, Landa J, Sohn M, Panicek DM. Biopsy of suspicious bone lesions in patients with a single known malignancy: prevalence of a second malignancy. AJR Am J Roentgenol. 2013;201(6):1309\u201314.","journal-title":"AJR Am J Roentgenol"},{"issue":"23","key":"978_CR7","doi-asserted-by":"publisher","first-page":"2438","DOI":"10.1001\/jama.2020.0716","volume":"323","author":"RG Chiu","year":"2020","unstructured":"Chiu RG, Mehta AI. Spinal metastases. JAMA. 2020;323(23):2438.","journal-title":"JAMA"},{"key":"978_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2021.109586","volume":"137","author":"V Chianca","year":"2021","unstructured":"Chianca V, Cuocolo R, Gitto S, Albano D, Merli I, Badalyan J, Cortese MC, Messina C, Luzzati A, Parafioriti A, et al. Radiomic machine learning classifiers in spine bone tumors: a multi-software, multi-scanner study. Eur J Radiol. 2021;137: 109586.","journal-title":"Eur J Radiol"},{"key":"978_CR9","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2020.605746","volume":"7","author":"X Fan","year":"2020","unstructured":"Fan X, Zhang H, Yin Y, Zhang J, Yang M, Qin S, Zhang X, Yu F. Texture analysis of F-FDG PET\/CT for differential diagnosis spinal metastases. Front Med (Lausanne). 2020;7: 605746.","journal-title":"Front Med (Lausanne)"},{"issue":"2","key":"978_CR10","doi-asserted-by":"publisher","first-page":"96","DOI":"10.4184\/asj.2013.7.2.96","volume":"7","author":"K Uchida","year":"2013","unstructured":"Uchida K, Nakajima H, Miyazaki T, Tsuchida T, Hirai T, Sugita D, Watanabe S, Takeura N, Yoshida A, Okazawa H, et al. (18)F-FDG PET\/CT for diagnosis of osteosclerotic and osteolytic vertebral metastatic lesions: comparison with bone scintigraphy. Asian Spine J. 2013;7(2):96.","journal-title":"Asian Spine J"},{"key":"978_CR11","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.mri.2019.02.013","volume":"64","author":"N Lang","year":"2019","unstructured":"Lang N, Zhang Y, Zhang E, Zhang J, Chow D, Chang P, Yu HJ, Yuan H, Su M-Y. Differentiation of spinal metastases originated from lung and other cancers using radiomics and deep learning based on DCE-MRI. Magn Reason Imaging. 2019;64:4\u201312.","journal-title":"Magn Reason Imaging"},{"issue":"6","key":"978_CR12","doi-asserted-by":"publisher","first-page":"1287","DOI":"10.1016\/j.rcl.2011.07.010","volume":"49","author":"AJ Huang","year":"2011","unstructured":"Huang AJ, Kattapuram SV. Musculoskeletal neoplasms: biopsy and intervention. Radiol Clin N Am. 2011;49(6):1287.","journal-title":"Radiol Clin N Am"},{"issue":"4","key":"978_CR13","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1016\/j.ejca.2011.11.036","volume":"48","author":"P Lambin","year":"2012","unstructured":"Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, Granton P, Zegers CM, Gillies R, Boellard R, Dekker A, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441\u20136.","journal-title":"Eur J Cancer"},{"issue":"1","key":"978_CR14","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.crad.2016.09.013","volume":"72","author":"E Sala","year":"2017","unstructured":"Sala E, Mema E, Himoto Y, Veeraraghavan H, Brenton JD, Snyder A, Weigelt B, Vargas HA. Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging. Clin Radiol. 2017;72(1):3\u201310.","journal-title":"Clin Radiol"},{"issue":"2","key":"978_CR15","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1148\/radiol.2015151169","volume":"278","author":"RJ Gillies","year":"2016","unstructured":"Gillies RJ, Kinahan PE, Hricak H. Radiomics. Images are more than pictures, they are data. Radiology. 2016;278(2):563\u201377.","journal-title":"Radiology"},{"issue":"1","key":"978_CR16","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/s40644-021-00387-6","volume":"21","author":"W Sun","year":"2021","unstructured":"Sun W, Liu S, Guo J, Liu S, Hao D, Hou F, Wang H, Xu W. A CT-based radiomics nomogram for distinguishing between benign and malignant bone tumours. Cancer Imaging. 2021;21(1):20.","journal-title":"Cancer Imaging"},{"issue":"3","key":"978_CR17","doi-asserted-by":"publisher","first-page":"752","DOI":"10.1002\/jmri.26238","volume":"49","author":"P Yin","year":"2019","unstructured":"Yin P, Mao N, Zhao C, Wu J, Chen L, Hong N. A triple-classification radiomics model for the differentiation of primary chordoma, giant cell tumor, and metastatic tumor of sacrum based on T2-weighted and contrast-enhanced T1-weighted MRI. J Magn Reson Imaging. 2019;49(3):752\u20139.","journal-title":"J Magn Reson Imaging"},{"issue":"3","key":"978_CR18","doi-asserted-by":"publisher","first-page":"1880","DOI":"10.3390\/ijerph19031880","volume":"19","author":"E Faiella","year":"2022","unstructured":"Faiella E, Santucci D, Calabrese A, Russo F, Vadala G, Zobel BB, Soda P, Iannello G, de Felice C, Denaro V. Artificial intelligence in bone metastases: an MRI and CT imaging review. Int J Environ Res Public Health. 2022;19(3):1880.","journal-title":"Int J Environ Res Public Health"},{"key":"978_CR19","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.601699","volume":"11","author":"X Xiong","year":"2021","unstructured":"Xiong X, Wang J, Hu S, Dai Y, Zhang Y, Hu C. Differentiating between multiple myeloma and metastasis subtypes of lumbar vertebra lesions using machine learning-based radiomics. Front Oncol. 2021;11: 601699.","journal-title":"Front Oncol"},{"issue":"1","key":"978_CR20","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/42.668698","volume":"17","author":"JG Sled","year":"1998","unstructured":"Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging. 1998;17(1):87\u201397.","journal-title":"IEEE Trans Med Imaging"},{"issue":"1","key":"978_CR21","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.media.2013.10.005","volume":"18","author":"A Depeursinge","year":"2014","unstructured":"Depeursinge A, Foncubierta-Rodriguez A, Van De Ville D, M\u00fcller H. Three-dimensional solid texture analysis in biomedical imaging: review and opportunities. Med Image Anal. 2014;18(1):176\u201396.","journal-title":"Med Image Anal"},{"key":"978_CR22","doi-asserted-by":"crossref","unstructured":"Arag\u00f3n-Roy\u00f3n F, Jim\u00e9nez-V\u00edlchez A, Arauzo-Azofra A, Ben\u00edtez JM. FSinR: an exhaustive package for feature selection. arXiv:2002.10330, 2020.","DOI":"10.32614\/CRAN.package.FSinR"},{"issue":"1","key":"978_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v033.i01","volume":"33","author":"J Friedman","year":"2010","unstructured":"Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33(1):1\u201322.","journal-title":"J Stat Softw"},{"key":"978_CR24","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1186\/1471-2105-12-77","volume":"12","author":"X Robin","year":"2011","unstructured":"Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, M\u00fcller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinform. 2011;12:77.","journal-title":"BMC Bioinform"},{"issue":"12","key":"978_CR25","doi-asserted-by":"publisher","first-page":"2604","DOI":"10.1007\/s00330-011-2221-4","volume":"21","author":"HL Yang","year":"2011","unstructured":"Yang HL, Liu T, Wang XM, Xu Y, Deng SM. Diagnosis of bone metastases: a meta-analysis comparing 18FDG PET, CT, MRI and bone scintigraphy. Eur Radiol. 2011;21(12):2604\u201317.","journal-title":"Eur Radiol"},{"issue":"4","key":"978_CR26","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1038\/nrc2627","volume":"9","author":"CA Klein","year":"2009","unstructured":"Klein CA. Parallel progression of primary tumours and metastases. Nat Rev Cancer. 2009;9(4):302\u201312.","journal-title":"Nat Rev Cancer"},{"issue":"9","key":"978_CR27","doi-asserted-by":"publisher","first-page":"5142","DOI":"10.1002\/mp.15137","volume":"48","author":"M Ren","year":"2021","unstructured":"Ren M, Yang H, Lai Q, Shi D, Liu G, Shuang X, Su J, Xie L, Dong Y, Jiang X. MRI-based radiomics analysis for predicting the EGFR mutation based on thoracic spinal metastases in lung adenocarcinoma patients. Med Phys. 2021;48(9):5142\u201351.","journal-title":"Med Phys"},{"issue":"1","key":"978_CR28","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1007\/s11547-018-0935-y","volume":"124","author":"L Filograna","year":"2019","unstructured":"Filograna L, Lenkowicz J, Cellini F, Dinapoli N, Manfrida S, Magarelli N, Leone A, Colosimo C, Valentini V. Identification of the most significant magnetic resonance imaging (MRI) radiomic features in oncological patients with vertebral bone marrow metastatic disease: a feasibility study. Radiol Med. 2019;124(1):50\u20137.","journal-title":"Radiol Med"},{"issue":"2","key":"978_CR29","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1016\/j.ejrad.2012.10.023","volume":"82","author":"F Ng","year":"2013","unstructured":"Ng F, Kozarski R, Ganeshan B, Goh V. Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis? Eur J Radiol. 2013;82(2):342\u20138.","journal-title":"Eur J Radiol"}],"container-title":["BMC Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-023-00978-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12880-023-00978-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-023-00978-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T13:44:45Z","timestamp":1720791885000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedimaging.biomedcentral.com\/articles\/10.1186\/s12880-023-00978-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,9]]},"references-count":29,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["978"],"URL":"https:\/\/doi.org\/10.1186\/s12880-023-00978-8","relation":{},"ISSN":["1471-2342"],"issn-type":[{"value":"1471-2342","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,9]]},"assertion":[{"value":"16 August 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 February 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ethical approval was obtained from the Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University, China. In addition, patient informed consent was waived due to the retrospective nature of this study, which was under the permission of the Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University. All methods were carried out in accordance with the Declaration of Helsinki. We confirmed that all methods were performed in accordance with relevant guidelines and regulations.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"29"}}