Prognostic predictive value of urothelial carcinoma of the bladder after TURBT based on multiphase CT radiomics.
Objective: To investigate multiphase computed tomography (CT) radiomics-based combined with clinical factors to predict overall survival (OS) in patients with bladder urothelial carcinoma (BLCA) who underwent transurethral resection of bladder tumor (TURBT). Methods: Data were retrospectively collec...
| Published in: | Abdominal Radiology Vol. 49; no. 6; pp. 1975 - 1987 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Published: |
Springer Nature
Jun2024
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=178150409&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 178150409 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Jun2024 vid: 49 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 178150409 176605958 10.1007/s00261-024-04265-0 178150409 ppf: 1975 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prognostic predictive value of urothelial carcinoma of the bladder after TURBT based on multiphase CT radiomics. aug: au: Xue, Jing Zhuang, Zijian Peng, Lin Chen, Xingchi Zhu, Haitao Wang, Dongqing Zhang, Lirong affil: https://ror.org/028pgd321 Department of Medical Imaging, The Affiliated Hospital of Jiangsu University, 212001, Zhenjiang, Jiangsu, China sug: ab: Objective: To investigate multiphase computed tomography (CT) radiomics-based combined with clinical factors to predict overall survival (OS) in patients with bladder urothelial carcinoma (BLCA) who underwent transurethral resection of bladder tumor (TURBT). Methods: Data were retrospectively collected from 114 patients with primary BLCA from February 2016 to February 2018. The regions of interest (ROIs) of the plain, arterial, and venous phase images were manually segmented. The Cox regression algorithm was used to establish 3 basic models for the plain phase (PP), arterial phase (AP), and venous phase (VP) and 2 combination models (AP + VP and PP + AP + VP). The highest-performing radiomics model was selected to calculate the radiomics score (Rad-score), and independent risk factors affecting patients' OS were analyzed using Cox regression. The Rad-score and clinical risk factors were combined to construct a joint model and draw a visualized nomogram. Results: The combined model of PP + AP + VP showed the best performance with the Akaike Information Criterion (AIC) and Consistency Index (C-index) in the test group of 130.48 and 0.779, respectively. A combined model constructed with two independent risk factors (age and Ki-67 expression status) in combination with the Rad-score outperformed the radiomics model alone; AIC and C-index in the test group were 115.74 and 0.840, respectively. The calibration curves showed good agreement between the predicted probabilities of the joint model and the actual (p < 0.05). The decision curve showed that the joint model had good clinical application value within a large range of threshold probabilities. Conclusion: This new model can be used to predict the OS of patients with BLCA who underwent TURBT. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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