{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T12:06:00Z","timestamp":1789992360139,"version":"4.0.1"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,8,2]],"date-time":"2017-08-02T00:00:00Z","timestamp":1501632000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000866","name":"Cardiff University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100000866","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"published-print":{"date-parts":[[2018,1]]},"DOI":"10.1007\/s00330-017-4973-y","type":"journal-article","created":{"date-parts":[[2017,8,2]],"date-time":"2017-08-02T11:02:19Z","timestamp":1501671739000},"page":"428-436","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":62,"title":["Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer"],"prefix":"10.1007","volume":"28","author":[{"given":"Kieran G","family":"Foley","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert K.","family":"Hills","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beatrice","family":"Berthon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Marshall","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Craig","family":"Parkinson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wyn G.","family":"Lewis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tom D. L.","family":"Crosby","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emiliano","family":"Spezi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stuart Ashley","family":"Roberts","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2017,8,2]]},"reference":[{"key":"4973_CR1","doi-asserted-by":"crossref","first-page":"4006","DOI":"10.1038\/ncomms5006","volume":"5","author":"HJ Aerts","year":"2014","unstructured":"Aerts HJ, Velazquez ER, Leijenaar RT et al (2014) Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 5:4006","journal-title":"Nat Commun"},{"key":"4973_CR2","doi-asserted-by":"crossref","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 et al (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48:441\u2013446","journal-title":"Eur J Cancer"},{"key":"4973_CR3","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1148\/radiol.2015151169","volume":"278","author":"RJ Gillies","year":"2016","unstructured":"Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563\u2013577","journal-title":"Radiology"},{"key":"4973_CR4","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1056\/NEJMoa1113205","volume":"366","author":"M Gerlinger","year":"2012","unstructured":"Gerlinger M, Rowan AJ, Horswell S et al (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366:883\u2013892","journal-title":"N Engl J Med"},{"key":"4973_CR5","doi-asserted-by":"crossref","first-page":"414","DOI":"10.2967\/jnumed.113.129858","volume":"55","author":"F Orlhac","year":"2014","unstructured":"Orlhac F, Soussan M, Maisonobe JA, Garcia CA, Vanderlinden B, Buvat I (2014) Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis. J Nucl Med 55:414\u2013422","journal-title":"J Nucl Med"},{"key":"4973_CR6","doi-asserted-by":"crossref","first-page":"38","DOI":"10.2967\/jnumed.114.144055","volume":"56","author":"M Hatt","year":"2015","unstructured":"Hatt M, Majdoub M, Vallieres M et al (2015) 18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort. J Nucl Med 56:38\u201344","journal-title":"J Nucl Med"},{"key":"4973_CR7","doi-asserted-by":"crossref","first-page":"691","DOI":"10.2967\/jnumed.115.163766","volume":"57","author":"PS Rossum van","year":"2016","unstructured":"van Rossum PS, Fried DV, Zhang L et al (2016) The incremental value of subjective and quantitative assessment of 18F-FDG PET for the prediction of pathologic complete response to preoperative chemoradiotherapy in esophageal cancer. J Nucl Med 57:691\u2013700","journal-title":"J Nucl Med"},{"key":"4973_CR8","volume-title":"UICC TNM Classification of Malignant Tumours","author":"LH Sobin","year":"2009","unstructured":"Sobin LH, Gospodarowicz MK, Wittekind CH (2009) UICC TNM Classification of Malignant Tumours, 7th edn. Wiley, New York","edition":"7"},{"key":"4973_CR9","doi-asserted-by":"crossref","first-page":"4855","DOI":"10.1088\/0031-9155\/61\/13\/4855","volume":"61","author":"B Berthon","year":"2016","unstructured":"Berthon B, Marshall C, Evans M, Spezi E (2016) ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography. Phys Med Biol 61:4855\u20134869","journal-title":"Phys Med Biol"},{"key":"4973_CR10","doi-asserted-by":"crossref","first-page":"979","DOI":"10.1118\/1.1568978","volume":"30","author":"JO Deasy","year":"2003","unstructured":"Deasy JO, Blanco AI, Clark VH (2003) CERR: a computational environment for radiotherapy research. Med Phys 30:979\u2013985","journal-title":"Med Phys"},{"key":"4973_CR11","doi-asserted-by":"crossref","first-page":"11075","DOI":"10.1038\/srep11075","volume":"5","author":"RT Leijenaar","year":"2015","unstructured":"Leijenaar RT, Nalbantov G, Carvalho S et al (2015) The effect of SUV discretization in quantitative FDG-PET radiomics: the need for standardized methodology in tumor texture analysis. Sci Rep 5:11075","journal-title":"Sci Rep"},{"key":"4973_CR12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2967\/jnumed.108.057174","volume":"50","author":"RL Wahl","year":"2009","unstructured":"Wahl RL, Jacene H, Kasamon Y, Lodge MA (2009) From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumours. J Nucl Med 50:1\u201350","journal-title":"J Nucl Med"},{"key":"4973_CR13","doi-asserted-by":"crossref","unstructured":"Haralick RM, Shanmugam K, Dinstein I (1973) Textural features for image classification. IEEE Trans Syst, Man Cybern 3:610\u2013621","DOI":"10.1109\/TSMC.1973.4309314"},{"key":"4973_CR14","doi-asserted-by":"crossref","first-page":"1264","DOI":"10.1109\/21.44046","volume":"19","author":"M Amadasun","year":"1989","unstructured":"Amadasun M, King R (1989) Textural features corresponding to textural properties. IEEE Trans Syst, Man Cybern 19:1264\u20131273","journal-title":"IEEE Trans Syst, Man Cybern"},{"key":"4973_CR15","unstructured":"Thibault G, Fertil B, Navarro C et al. (2009) Texture indexes and gray level size zone matrix application to cell nuclei classification. Pattern Recognit Inf Process:140\u2013145"},{"key":"4973_CR16","doi-asserted-by":"crossref","first-page":"369","DOI":"10.2967\/jnumed.110.082404","volume":"52","author":"F Tixier","year":"2011","unstructured":"Tixier F, Le Rest CC, Hatt M et al (2011) Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med 52:369\u2013378","journal-title":"J Nucl Med"},{"key":"4973_CR17","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1148\/radiol.13122869","volume":"270","author":"C Yip","year":"2014","unstructured":"Yip C, Landau D, Kozarski R et al (2014) Primary esophageal cancer: heterogeneity as potential prognostic biomarker in patients treated with definitive chemotherapy and radiation therapy. Radiology 270:141\u2013148","journal-title":"Radiology"},{"key":"4973_CR18","doi-asserted-by":"crossref","first-page":"1662","DOI":"10.1007\/s00259-013-2486-8","volume":"40","author":"M Hatt","year":"2013","unstructured":"Hatt M, Tixier F, Cheze Le Rest C, Pradier O, Visvikis D (2013) Robustness of intratumour 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma. Eur J Nucl Med Mol Imaging 40:1662\u20131671","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"4973_CR19","first-page":"71","volume":"6","author":"W Wu","year":"2016","unstructured":"Wu W, Parmar C, Grossmann P et al (2016) Exploratory study to identify radiomics classifiers for lung cancer histology. Front Oncol 6:71","journal-title":"Front Oncol"},{"key":"4973_CR20","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1016\/S0895-4356(96)00236-3","volume":"49","author":"P Peduzzi","year":"1996","unstructured":"Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR (1996) A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 49:1373\u20131379","journal-title":"J Clin Epidemiol"},{"key":"4973_CR21","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","volume":"19","author":"H Akaike","year":"1974","unstructured":"Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716\u2013723","journal-title":"IEEE Trans Autom Control"},{"key":"4973_CR22","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1136\/heartjnl-2011-301246","volume":"98","author":"KG Moons","year":"2012","unstructured":"Moons KG, Kengne AP, Woodward M et al (2012) Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart 98:683\u2013690","journal-title":"Heart"},{"key":"4973_CR23","doi-asserted-by":"crossref","first-page":"b375","DOI":"10.1136\/bmj.b375","volume":"338","author":"KG Moons","year":"2009","unstructured":"Moons KG, Royston P, Vergouwe Y, Grobbee DE, Altman DG (2009) Prognosis and prognostic research: what, why, and how? BMJ 338:b375","journal-title":"BMJ"},{"key":"4973_CR24","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1002\/(SICI)1097-0142(20000415)88:8<1781::AID-CNCR4>3.0.CO;2-G","volume":"88","author":"JM Blazeby","year":"2000","unstructured":"Blazeby JM, Farndon JR, Donovan J, Alderson D (2000) A prospective longitudinal study examining the quality of life of patients with esophageal carcinoma. Cancer 88:1781\u20131787","journal-title":"Cancer"},{"key":"4973_CR25","doi-asserted-by":"crossref","first-page":"1823","DOI":"10.2967\/jnumed.116.173708","volume":"57","author":"F Orlhac","year":"2016","unstructured":"Orlhac F, Theze B, Soussan M, Boisgard R, Buvat I (2016) Multiscale texture analysis: from 18F-FDG PET images to histologic images. J Nucl Med 57:1823\u20131828","journal-title":"J Nucl Med"},{"key":"4973_CR26","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1111\/dote.12170","volume":"28","author":"C Yip","year":"2015","unstructured":"Yip C, Davnall F, Kozarski R et al (2015) Assessment of changes in tumor heterogeneity following neoadjuvant chemotherapy in primary esophageal cancer. Dis Esophagus 28:172\u2013179","journal-title":"Dis Esophagus"},{"key":"4973_CR27","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.crad.2011.08.012","volume":"67","author":"B Ganeshan","year":"2012","unstructured":"Ganeshan B, Skogen K, Pressney I, Coutroubis D, Miles K (2012) Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival. Clin Radiol 67:157\u2013164","journal-title":"Clin Radiol"},{"key":"4973_CR28","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.3109\/0284186X.2010.498437","volume":"49","author":"PE Galavis","year":"2010","unstructured":"Galavis PE, Hollensen C, Jallow N, Paliwal B, Jeraj R (2010) Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters. Acta Oncol 49:1012\u20131016","journal-title":"Acta Oncol"},{"key":"4973_CR29","doi-asserted-by":"crossref","first-page":"2805","DOI":"10.1007\/s00330-015-3681-8","volume":"25","author":"G Doumou","year":"2015","unstructured":"Doumou G, Siddique M, Tsoumpas C, Goh V, Cook GJ (2015) The precision of textural analysis in (18)F-FDG-PET scans of oesophageal cancer. Eur Radiol 25:2805\u20132812","journal-title":"Eur Radiol"},{"key":"4973_CR30","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/s40336-014-0064-0","volume":"2","author":"GJR Cook","year":"2014","unstructured":"Cook GJR, Siddique M, Taylor BP, Yip C, Chicklore S, Goh V (2014) Radiomics in PET: principles and applications. Clin Transl Imaging 2:269\u2013276","journal-title":"Clin Transl Imaging"},{"key":"4973_CR31","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.3109\/0284186X.2015.1062136","volume":"54","author":"P Lambin","year":"2015","unstructured":"Lambin P, Zindler J, Vanneste B et al (2015) Modern clinical research: How rapid learning health care and cohort multiple randomised clinical trials complement traditional evidence based medicine. Acta Oncol 54:1289\u20131300","journal-title":"Acta Oncol"},{"key":"4973_CR32","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1002\/bjs.9437","volume":"101","author":"A Karran","year":"2014","unstructured":"Karran A, Blake P, Chan D et al (2014) Propensity score analysis of oesophageal cancer treatment with surgery or definitive chemoradiotherapy. Br J Surg 101:502\u2013510","journal-title":"Br J Surg"}],"container-title":["European Radiology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00330-017-4973-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-017-4973-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-017-4973-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T19:44:42Z","timestamp":1569959082000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00330-017-4973-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,2]]},"references-count":32,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,1]]}},"alternative-id":["4973"],"URL":"https:\/\/doi.org\/10.1007\/s00330-017-4973-y","relation":{},"ISSN":["0938-7994","1432-1084"],"issn-type":[{"value":"0938-7994","type":"print"},{"value":"1432-1084","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,8,2]]}}}