Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96457
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dc.contributorDepartment of Health Technology and Informatics-
dc.creatorLam, SKen_US
dc.creatorZhang, Jen_US
dc.creatorZhang, Yen_US
dc.creatorLi, Ben_US
dc.creatorNi, RYen_US
dc.creatorZhou, Ten_US
dc.creatorPeng, Ten_US
dc.creatorCheung, ALYen_US
dc.creatorChau, TCen_US
dc.creatorLee, FKHen_US
dc.creatorYip, CWYen_US
dc.creatorAu, KHen_US
dc.creatorLee, VHFen_US
dc.creatorChang, ATYen_US
dc.creatorChan, LWCen_US
dc.creatorCai, Jen_US
dc.date.accessioned2022-12-07T02:55:00Z-
dc.date.available2022-12-07T02:55:00Z-
dc.identifier.urihttp://hdl.handle.net/10397/96457-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Lam, S. K., Zhang, J., Zhang, Y. P., Li, B., Ni, R. Y., Zhou, T., ... & Cai, J. (2022). A Multi-Center Study of CT-Based Neck Nodal Radiomics for Predicting an Adaptive Radiotherapy Trigger of Ill-Fitted Thermoplastic Masks in Patients with Nasopharyngeal Carcinoma. Life, 12(2), 241 is available at https://doi.org/10.3390/life12020241.en_US
dc.subjectAdaptive radiotherapyen_US
dc.subjectNeck lymph node shrinkageen_US
dc.subjectRadiomicsen_US
dc.subjectThermoplastic mask unfiten_US
dc.titleA multi-center study of CT-based neck nodal radiomics for predicting an adaptive radiotherapy trigger of ill-fitted thermoplastic masks in patients with nasopharyngeal carcinomaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume12en_US
dc.identifier.issue2en_US
dc.identifier.doi10.3390/life12020241en_US
dcterms.abstractSignificant lymph node shrinkage is common in patients with nasopharyngeal carcinoma (NPC) throughout radiotherapy (RT) treatment, causing ill-fitted thermoplastic masks (IfTMs). To deal with this, an ad hoc adaptive radiotherapy (ART) may be required to ensure accurate and safe radiation delivery and to maintain treatment efficacy. Presently, the entire procedure for evaluating an eligible ART candidate is time-consuming, resource-demanding, and highly inefficient. In the artificial intelligence paradigm, the pre-treatment identification of NPC patients at risk for IfTMs has become greatly demanding for achieving efficient ART eligibility screening, while no relevant studies have been reported. Hence, we aimed to investigate the capability of computed tomography (CT)-based neck nodal radiomics for predicting IfTM-triggered ART events in NPC patients via a multi-center setting. Contrast-enhanced CT and the clinical data of 124 and 58 NPC patients from Queen Elizabeth Hospital (QEH) and Queen Mary Hospital (QMH), respectively, were retrospectively analyzed. Radiomic (R), clinical (C), and combined (RC) models were developed using the ridge algorithm in the QEH cohort and evaluated in the QMH cohort using the median area under the receiver operating characteristics curve (AUC). Delong’s test was employed for model comparison. Model performance was further assessed on 1000 replicates in both cohorts separately via bootstrapping. The R model yielded the highest “corrected” AUC of 0.784 (BCa 95%CI: 0.673–0.859) and 0.723 (BCa 95%CI: 0.534–0.859) in the QEH and QMH cohort following bootstrapping, respectively. Delong’s test indicated that the R model performed significantly better than the C model in the QMH cohort (p < 0.0001), while demonstrating no significant difference compared to the RC model (p = 0.5773). To conclude, CT-based neck nodal radiomics was capable of predicting IfTMtriggered ART events in NPC patients in this multi-center study, outperforming the traditional clinical model. The findings of this study provide valuable insights for future study into developing an effective screening strategy for ART eligibility in NPC patients in the long run, ultimately alleviating the workload of clinical practitioners, streamlining ART procedural efficiency in clinics, and achieving personalized RT for NPC patients in the future.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationLife, Feb. 2022, v. 12, no. 2, 241en_US
dcterms.isPartOfLifeen_US
dcterms.issued2022-02-
dc.identifier.scopus2-s2.0-85124403784-
dc.identifier.eissn2075-1729en_US
dc.identifier.artn241en_US
dc.description.validate202212 bckw-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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