{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T23:56:43Z","timestamp":1780617403532,"version":"3.54.1"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"1130","license":[{"start":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T00:00:00Z","timestamp":1638489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,2,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>To develop an MRI-based radiomics model to predict postlaminar optic nerve invasion (PLONI) in retinoblastoma (RB) and compare its predictive performance with subjective radiologists\u2019 assessment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We retrospectively enrolled 124 patients with pathologically proven RB (90 in training set and 34 in validation set) who had MRI scans before surgery. A radiomics model for predicting PLONI was developed by extracting quantitative imaging features from axial T2W images and contrast-enhanced T1W images in the training set. The Kruskal\u2013Wallis test, least absolute shrinkage and selection operator regression, and recursive feature elimination were used for feature selection, where upon a radiomics model was built with a logistic regression (LR) classifier. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and the accuracy were assessed to evaluate the predictive performance in the training and validation set. The performance of the radiomics model was compared to radiologists\u2019 assessment by DeLong test.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The AUC of the radiomics model for the prediction of PLONI was 0.928 in the training set and 0.841 in the validation set. Radiomics model produced better sensitivity than radiologists\u2019 assessment (81.1% vs \u200943.2% in training set, 82.4vs\u200952.9% in validation set). In all 124 patients, the AUC of the radiomics model was 0.897, while that of radiologists\u2019 assessment was 0.674 (p &amp;lt; 0.001, DeLong test).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>MRI-based radiomics model to predict PLONI in RB patients was shown to be superior to visual assessment with improved sensitivity and AUC, and may serve as a potential tool to guide personalized treatment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1259\/bjr.20211027","type":"journal-article","created":{"date-parts":[[2021,11,26]],"date-time":"2021-11-26T14:48:12Z","timestamp":1637938092000},"source":"Crossref","is-referenced-by-count":12,"title":["MRI-based radiomics model can improve the predictive performance of postlaminar optic nerve invasion in retinoblastoma"],"prefix":"10.1093","volume":"95","author":[{"given":"Zhenzhen","family":"Li","sequence":"first","affiliation":[{"name":"Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1 of Dongjiaominxiang, Dongcheng District , Beijing , China"},{"name":"Clinical Center for Eye Tumors, Capital Medical University , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1 of Dongjiaominxiang, Dongcheng District , Beijing , China"},{"name":"Clinical Center for Eye Tumors, Capital Medical University , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolin","family":"Xu","sequence":"additional","affiliation":[{"name":"Clinical Center for Eye Tumors, Capital Medical University , Beijing , China"},{"name":"Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbin","family":"Wei","sequence":"additional","affiliation":[{"name":"Clinical Center for Eye Tumors, Capital Medical University , Beijing , China"},{"name":"Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junfang","family":"Xian","sequence":"additional","affiliation":[{"name":"Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1 of Dongjiaominxiang, Dongcheng District , Beijing , China"},{"name":"Clinical Center for Eye Tumors, Capital Medical University , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,12,3]]},"reference":[{"key":"2024050216184796100_b1","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1136\/bjo.2008.150292","article-title":"The epidemiological challenge of the most frequent eye cancer: retinoblastoma, an issue of birth and death","volume":"93","author":"Kivel\u00e4","year":"2009","journal-title":"Br J Ophthalmol"},{"key":"2024050216184796100_b2","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1136\/bjo.2008.143842","article-title":"Survival with retinoblastoma in the USA: 1975-2004","volume":"93","author":"Broaddus","year":"2009","journal-title":"Br J Ophthalmol"},{"key":"2024050216184796100_b3","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1002\/pbc.21080","article-title":"Outcome of retinoblastoma in East Africa","volume":"50","author":"Bowman","year":"2008","journal-title":"Pediatr Blood Cancer"},{"key":"2024050216184796100_b4","doi-asserted-by":"crossref","first-page":"1436","DOI":"10.1016\/S0140-6736(11)61137-9","article-title":"Retinoblastoma","volume":"379","author":"Dimaras","year":"2012","journal-title":"Lancet"},{"key":"2024050216184796100_b5","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1016\/j.ophtha.2012.10.044","article-title":"High-Risk retinoblastoma based on international classification of retinoblastoma: analysis of 519 enucleated eyes","volume":"120","author":"Kaliki","year":"2013","journal-title":"Ophthalmology"},{"key":"2024050216184796100_b6","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.1002\/(SICI)1097-0142(19960315)77:6<1206::AID-CNCR30>3.0.CO;2-3","article-title":"Histopathologic risk factors in retinoblastoma: a retrospective study of 172 patients treated in a single institution","volume":"77","author":"Khelfaoui","year":"1996","journal-title":"Cancer"},{"key":"2024050216184796100_b7","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/S0161-6420(91)32325-X","article-title":"Risk factors for metastases in patients with retinoblastoma","volume":"98","author":"Messmer","year":"1991","journal-title":"Ophthalmology"},{"key":"2024050216184796100_b8","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1002\/1097-0142(19940201)73:3<692::AID-CNCR2820730331>3.0.CO;2-8","article-title":"Optic nerve invasion of retinoblastoma. metastatic potential and clinical risk factors","volume":"73","author":"Shields","year":"1994","journal-title":"Cancer"},{"key":"2024050216184796100_b9","doi-asserted-by":"crossref","first-page":"1551","DOI":"10.1038\/s41388-017-0050-x","article-title":"The management of retinoblastoma","volume":"37","author":"Fabian","year":"2018","journal-title":"Oncogene"},{"key":"2024050216184796100_b10","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.1016\/j.ophtha.2012.01.029","article-title":"Outcome, pathologic findings, and compliance in orbital retinoblastoma (International retinoblastoma staging system stage III) treated with neoadjuvant chemotherapy: a prospective study","volume":"119","author":"Radhakrishnan","year":"2012","journal-title":"Ophthalmology"},{"key":"2024050216184796100_b11","doi-asserted-by":"crossref","first-page":"1109","DOI":"10.1016\/j.ophtha.2013.11.021","article-title":"Diagnostic performance of magnetic resonance imaging and computed tomography for advanced retinoblastoma: a systematic review and meta-analysis","volume":"121","author":"de Jong","year":"2014","journal-title":"Ophthalmology"},{"key":"2024050216184796100_b12","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1007\/s00330-014-3514-1","article-title":"Assessment of early-stage optic nerve invasion in retinoblastoma using high-resolution 1.5 Tesla MRI with surface coils: a multicentre, prospective accuracy study with histopathological correlation","volume":"25","author":"Brisse","year":"2015","journal-title":"Eur Radiol"},{"key":"2024050216184796100_b13","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1148\/radiol.2015151213","article-title":"Diagnostic accuracy of intraocular tumor size measured with MR imaging in the prediction of Postlaminar optic nerve invasion and massive choroidal invasion of retinoblastoma","volume":"279","author":"De Jong","year":"2016","journal-title":"Radiology"},{"key":"2024050216184796100_b14","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1007\/s00247-011-2201-5","article-title":"Guidelines for imaging retinoblastoma: imaging principles and MRI standardization","volume":"42","author":"de Graaf","year":"2012","journal-title":"Pediatr Radiol"},{"key":"2024050216184796100_b15","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1007\/s00247-012-2576-y","article-title":"Diagnostic image quality of gadolinium-enhanced T1-weighted MRI with and without fat saturation in children with retinoblastoma","volume":"43","author":"Sirin","year":"2013","journal-title":"Pediatr Radiol"},{"key":"2024050216184796100_b16","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1002\/jmri.26961","article-title":"Diagnosis of postlaminar optic nerve invasion in retinoblastoma with MRI features","volume":"51","author":"Li","year":"2020","journal-title":"J Magn Reson Imaging"},{"key":"2024050216184796100_b17","doi-asserted-by":"crossref","first-page":"4041","DOI":"10.1016\/j.ejrad.2012.03.034","article-title":"Can preoperative MR imaging predict optic nerve invasion of retinoblastoma?","volume":"81","author":"Song","year":"2012","journal-title":"Eur J Radiol"},{"key":"2024050216184796100_b18","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1038\/nrclinonc.2017.141","article-title":"Radiomics: the bridge between medical imaging and personalized medicine","volume":"14","author":"Lambin","year":"2017","journal-title":"Nat Rev Clin Oncol"},{"key":"2024050216184796100_b19","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1148\/radiol.2015151169","article-title":"Radiomics: images are more than pictures, they are data","volume":"278","author":"Gillies","year":"2016","journal-title":"Radiology"},{"key":"2024050216184796100_b20","doi-asserted-by":"crossref","first-page":"R150","DOI":"10.1088\/0031-9155\/61\/13\/R150","article-title":"Applications and limitations of radiomics","volume":"61","author":"Yip","year":"2016","journal-title":"Phys Med Biol"},{"key":"2024050216184796100_b21","doi-asserted-by":"crossref","first-page":"5123","DOI":"10.1088\/0031-9155\/60\/13\/5123","article-title":"Staging of cervical cancer based on tumor heterogeneity characterized by texture features on (18)F-FDG PET images","volume":"60","author":"Mu","year":"2015","journal-title":"Phys Med Biol"},{"key":"2024050216184796100_b22","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1097\/MNM.0b013e32835ae50c","article-title":"Three-Dimensional positron emission tomography image texture analysis of esophageal squamous cell carcinoma: relationship between tumor 18F-fluorodeoxyglucose uptake heterogeneity, maximum standardized uptake value, and tumor stage","volume":"34","author":"Dong","year":"2013","journal-title":"Nucl Med Commun"},{"key":"2024050216184796100_b23","doi-asserted-by":"crossref","first-page":"2157","DOI":"10.1200\/JCO.2015.65.9128","article-title":"Development and validation of a Radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer","volume":"34","author":"Huang","year":"2016","journal-title":"J Clin Oncol"},{"key":"2024050216184796100_b24","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1007\/s00330-018-5698-2","article-title":"Clear cell renal cell carcinoma: machine Learning-Based quantitative computed tomography texture analysis for prediction of Fuhrman nuclear grade","volume":"29","author":"Bektas","year":"2019","journal-title":"Eur Radiol"},{"key":"2024050216184796100_b25","doi-asserted-by":"crossref","first-page":"1495","DOI":"10.1016\/j.acra.2018.12.019","article-title":"Machine Learning-based analysis of rectal cancer MRI Radiomics for prediction of metachronous liver metastasis","volume":"26","author":"Liang","year":"2019","journal-title":"Acad Radiol"},{"key":"2024050216184796100_b26","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.1016\/j.ophtha.2015.01.018","article-title":"Clinical features predictive of high-risk retinoblastoma in 403 Asian Indian patients: a case-control study","volume":"122","author":"Kaliki","year":"2015","journal-title":"Ophthalmology"},{"key":"2024050216184796100_b27","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1177\/1120672118781200","article-title":"The predictive value of magnetic resonance imaging of retinoblastoma for the likelihood of high-risk pathologic features","volume":"29","author":"Hiasat","year":"2019","journal-title":"Eur J Ophthalmol"},{"key":"2024050216184796100_b28","doi-asserted-by":"crossref","DOI":"10.4103\/ijo.IJO_1611_18","article-title":"Accuracy of preoperative imaging in predicting optic nerve invasion in retinoblastoma: a retrospective study","volume":"67","author":"Kim","year":"2019","journal-title":"Indian J Ophthalmol"},{"key":"2024050216184796100_b29","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1007\/s00234-020-02538-1","article-title":"Diagnostic performance of MRI of post-laminar optic nerve invasion detection in retinoblastoma: a systematic review and meta-analysis","volume":"63","author":"Cho","year":"2021","journal-title":"Neuroradiology"},{"key":"2024050216184796100_b30","doi-asserted-by":"crossref","first-page":"4259","DOI":"10.1158\/1078-0432.CCR-16-2910","article-title":"Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma","volume":"23","author":"Zhang","year":"2017","journal-title":"Clin Cancer Res"},{"key":"2024050216184796100_b31","doi-asserted-by":"crossref","first-page":"3872","DOI":"10.1007\/s00330-018-5381-7","article-title":"MR-based radiomics signature in differentiating ocular adnexal lymphoma from idiopathic orbital inflammation","volume":"28","author":"Guo","year":"2018","journal-title":"Eur Radiol"},{"key":"2024050216184796100_b32","doi-asserted-by":"crossref","first-page":"4271","DOI":"10.1158\/1078-0432.CCR-18-3065","article-title":"Prognostic value of deep learning PET\/CT-Based Radiomics: potential role for future individual induction chemotherapy in advanced nasopharyngeal carcinoma","volume":"25","author":"Peng","year":"2019","journal-title":"Clin Cancer Res"},{"key":"2024050216184796100_b33","doi-asserted-by":"crossref","first-page":"5182","DOI":"10.1364\/BOE.7.005182","article-title":"Classification and analysis of human ovarian tissue using full field optical coherence tomography","volume":"7","author":"Nandy","year":"2016","journal-title":"Biomed Opt Express"},{"key":"2024050216184796100_b34","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0100244","article-title":"Noninvasive image texture analysis differentiates K-ras mutation from pan-wildtype NSCLC and is prognostic","volume":"9","author":"Weiss","year":"2014","journal-title":"PLoS One"},{"key":"2024050216184796100_b35","doi-asserted-by":"crossref","first-page":"4003","DOI":"10.1038\/s41598-018-22357-y","article-title":"Radiomics analysis at PET\/CT contributes to prognosis of recurrence and survival in lung cancer treated with stereotactic body radiotherapy","volume":"8","author":"Oikonomou","year":"2018","journal-title":"Sci Rep"},{"key":"2024050216184796100_b36","doi-asserted-by":"crossref","first-page":"1109","DOI":"10.1038\/nature09460","article-title":"The patterns and dynamics of genomic instability in metastatic pancreatic cancer","volume":"467","author":"Campbell","year":"2010","journal-title":"Nature"},{"key":"2024050216184796100_b37","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/s00259-016-3427-0","article-title":"Characterization of PET\/CT images using texture analysis: the past, the present\u2026 any future?","volume":"44","author":"Hatt","year":"2017","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"2024050216184796100_b38","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1001\/jamaophthalmol.2020.0427","article-title":"Genomic and transcriptomic tumor heterogeneity in bilateral retinoblastoma","volume":"138","author":"Winter","year":"2020","journal-title":"JAMA Ophthalmol"},{"key":"2024050216184796100_b39","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1158\/1055-9965.EPI-13-1069","article-title":"Diagnostic delay and sociodemographic predictors of stage at diagnosis and mortality in unilateral and bilateral retinoblastoma","volume":"23","author":"Ram\u00edrez-Ortiz","year":"2014","journal-title":"Cancer Epidemiol Biomarkers Prev"}],"container-title":["The British Journal of Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bjr\/article-pdf\/95\/1130\/20211027\/57373086\/bjr.20211027.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bjr\/article-pdf\/95\/1130\/20211027\/57373086\/bjr.20211027.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T14:48:08Z","timestamp":1714661288000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bjr\/article\/doi\/10.1259\/bjr.20211027\/7451410"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,3]]},"references-count":39,"journal-issue":{"issue":"1130","published-online":{"date-parts":[[2021,12,3]]},"published-print":{"date-parts":[[2022,2,1]]}},"URL":"https:\/\/doi.org\/10.1259\/bjr.20211027","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-328789\/v1","asserted-by":"object"}]},"ISSN":["0007-1285","1748-880X"],"issn-type":[{"value":"0007-1285","type":"print"},{"value":"1748-880X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,2,1]]},"published":{"date-parts":[[2021,12,3]]},"article-number":"20211027"}}