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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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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
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author Li, Can
Luan, Xiaohui
Bi, Xiao
Chen, Shengxin
Pan, Yue
Zhang, Jingfeng
Han, Yun
Xu, Xiaodan
Wang, Guanyun
Xu, Baixuan
author_facet Li, Can
Luan, Xiaohui
Bi, Xiao
Chen, Shengxin
Pan, Yue
Zhang, Jingfeng
Han, Yun
Xu, Xiaodan
Wang, Guanyun
Xu, Baixuan
author_sort Li, Can
collection PubMed
description 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.
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spelling pubmed-99010592023-02-07 Multiparameter diagnostic model based on (18)F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis Li, Can Luan, Xiaohui Bi, Xiao Chen, Shengxin Pan, Yue Zhang, Jingfeng Han, Yun Xu, Xiaodan Wang, Guanyun Xu, Baixuan BMC Cancer Research 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. BioMed Central 2023-02-06 /pmc/articles/PMC9901059/ /pubmed/36747196 http://dx.doi.org/10.1186/s12885-023-10599-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Li, Can
Luan, Xiaohui
Bi, Xiao
Chen, Shengxin
Pan, Yue
Zhang, Jingfeng
Han, Yun
Xu, Xiaodan
Wang, Guanyun
Xu, Baixuan
Multiparameter diagnostic model based on (18)F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis
title Multiparameter diagnostic model based on (18)F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis
title_full Multiparameter diagnostic model based on (18)F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis
title_fullStr Multiparameter diagnostic model based on (18)F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis
title_full_unstemmed Multiparameter diagnostic model based on (18)F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis
title_short Multiparameter diagnostic model based on (18)F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis
title_sort multiparameter diagnostic model based on (18)f-fdg pet metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis
topic Research
url 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
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