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Multiparameter diagnostic model based on (18)F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis

OBJECTIVE: To evaluate the diagnostic value of a multiparameter model based on (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) metabolic parameters and clinical variables in differentiating nonmetastatic gallbladder cancer (GBC) from cholecystitis. PATIENTS AND METHODS: In tota...

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Detalles Bibliográficos
Autores principales: Li, Can, Luan, Xiaohui, Bi, Xiao, Chen, Shengxin, Pan, Yue, Zhang, Jingfeng, Han, Yun, Xu, Xiaodan, Wang, Guanyun, Xu, Baixuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901059/
https://www.ncbi.nlm.nih.gov/pubmed/36747196
http://dx.doi.org/10.1186/s12885-023-10599-7
Descripción
Sumario:OBJECTIVE: To evaluate the diagnostic value of a multiparameter model based on (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) metabolic parameters and clinical variables in differentiating nonmetastatic gallbladder cancer (GBC) from cholecystitis. PATIENTS AND METHODS: In total, 122 patients (88 GBC nonmetastatic patients and 34 cholecystitis patients) with gallbladder space-occupying lesions who underwent (18)F-FDG PET/CT were included. All patients received surgery and pathology, and baseline characteristics and clinical data were also collected. The metabolic parameters of (18)F-FDG PET, including SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), SUVpeak (peak standard uptake value), MTV (metabolic tumour volume), TLG (total lesion glycolysis) and SUVR (tumour-to-normal liver standard uptake value ratio), were evaluated. The differential diagnostic efficacy of each independent parameter and multiparameter combination model was evaluated using the receiver operating characteristic (ROC) curve. The improvement in diagnostic efficacy using a combination of the above multiple parameters was evaluated by integrated discriminatory improvement (IDI), net reclassification improvement (NRI) and bootstrap test. Decision curve analysis (DCA) was used to evaluate clinical efficacy. RESULTS: The ROC curve showed that SUVR had the highest diagnostic ability among the (18)F-FDG PET metabolic parameters (area under the curve [AUC] = 0.698; sensitivity = 0.341; specificity = 0.971; positive predictive value [PPV] = 0.968; negative predictive value [NPV] = 0.363). The combined diagnostic model of cholecystolithiasis, fever, CEA > 5 ng/ml and SUVR showed an AUC of 0.899 (sensitivity = 0.909, specificity = 0.735, PPV = 0.899, NPV = 0.758). The diagnostic efficiency of the model was improved significantly compared with SUVR. The clinical efficacy of the model was confirmed by DCA. CONCLUSIONS: The multiparameter diagnostic model composed of (18)F-FDG PET metabolic parameters (SUVR) and clinical variables, including patient signs (fever), medical history (cholecystolithiasis) and laboratory examination (CEA > 5 ng/ml), has good diagnostic efficacy in the differential diagnosis of nonmetastatic GBC and cholecystitis.