{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["13(2)"],"submitter":["Li Q"],"pubmed_abstract":["Background
Nasopharyngeal carcinoma (NPC) is a common tumor in China. Accurate stages of NPC are crucial for treatment. We therefore aim to develop radiomics models for discriminating early-stage (I-II) and advanced-stage (III-IVa) NPC based on MR images.Methods
329 NPC patients were enrolled and randomly divided into a training cohort (n = 229) and a validation cohort (n = 100). Features were extracted based on axial contrast-enhanced T1-weighted images (CE-T1WI), T1WI, and T2-weighted images (T2WI). Least absolute shrinkage and selection operator (LASSO) was used to build radiomics signatures. Seven radiomics models were constructed with logistic regression. The AUC value was used to assess classification performance. The DeLong test was used to compare the AUCs of differ"],"journal":["Diagnostics (Basel, Switzerland)"],"pagination":["300"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9857437"],"repository":["biostudies-literature"],"pubmed_title":["The Effect of Magnetic Resonance Imaging Based Radiomics Models in Discriminating stage I-II and III-IVa Nasopharyngeal Carcinoma."],"pmcid":["PMC9857437"],"pubmed_authors":["Gong B","Lv F","Yu Q","Ning Y","Li Q","Gu J","Chen X","Peng J","Luo T"],"additional_accession":[]},"is_claimable":false,"name":"The Effect of Magnetic Resonance Imaging Based Radiomics Models in Discriminating stage I-II and III-IVa Nasopharyngeal Carcinoma.","description":"Background
Nasopharyngeal carcinoma (NPC) is a common tumor in China. Accurate stages of NPC are crucial for treatment. We therefore aim to develop radiomics models for discriminating early-stage (I-II) and advanced-stage (III-IVa) NPC based on MR images.Methods
329 NPC patients were enrolled and randomly divided into a training cohort (n = 229) and a validation cohort (n = 100). Features were extracted based on axial contrast-enhanced T1-weighted images (CE-T1WI), T1WI, and T2-weighted images (T2WI). Least absolute shrinkage and selection operator (LASSO) was used to build radiomics signatures. Seven radiomics models were constructed with logistic regression. The AUC value was used to assess classification performance. The DeLong test was used to compare the AUCs of differ","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Jan","modification":"2025-04-26T00:43:09.339Z","creation":"2025-04-06T09:47:49.537Z"},"accession":"S-EPMC9857437","cross_references":{"pubmed":["36673110"],"doi":["10.3390/diagnostics13020300"]}}