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Study of standardizing nomenclatures for organs at risk of nasopharyngeal carcinoma via the contouring content-based image retrieval method / 中华放射肿瘤学杂志
Article in Zh | WPRIM | ID: wpr-910472
Responsible library: WPRO
ABSTRACT
Objective:Based on the AAPM TG-263, a Content-Based Standardizing Nomenclatures (CBSN) was proposed to explore the feasibility of its standardization verification for organs at risk (OAR) of nasopharyngeal carcinoma (NPC).Methods:The radiotherapy structure files of 855 patients with nasopharyngeal carcinoma (NPC) receiving intensity-modulated radiotherapy (IMRT) from 2017 to 2019(15 of whom showed clinical anomalous structures) were retrospectively collected and processed. The Matlab self-developed software was used to obtain the image position, geometric features, first-order gray histogram, and the Gray-level Co-occurrence Matrix′s texture features of the OAR contour outlined by the doctor to establish the CBSN Location Verification model and CBSN Knowledge Library. Fisher discriminant analysis was employed to establish a CBSN OAR classification model, which was evaluated using self-validation, cross-validation, and external validation, respectively.Results:99%(69/70) of the simulated anomalous structures were outside the 90% reference range of the CBSN Knowledge Library and the characteristic parameters significantly differed among different OARs (all P<0.001). The accuracy rates of self-validation, cross-validation and external verification of the CBSN OAR classification model were 92.1%, 92.0% and 91.8%, respectively. Fourteen cases of clinical abnormal structures were successfully detected by CBSN with an accuracy rate of 93%(14/15). In the simulation test, the accuracy of the left and right location verification reached 100%, such as detecting the right eye lens named Len_L. Conclusion:CBSN can be used for OAR verification of NPC, providing reference for multi-center cooperation and standardized radiotherapy of NPC patients.
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Full text: 1 Index: WPRIM Type of study: Etiology_studies / Prognostic_studies Language: Zh Journal: Chinese Journal of Radiation Oncology Year: 2021 Type: Article
Full text: 1 Index: WPRIM Type of study: Etiology_studies / Prognostic_studies Language: Zh Journal: Chinese Journal of Radiation Oncology Year: 2021 Type: Article