Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation model
Abstract Background The aim is to explore the value of pericoronary adipose tissue (PCAT) attenuation in predicting abnormal bone mass by establishing a prediction model. Materials and methods 361 patients with coronary computed tomography angiography (CCTA) and quantitative computed tomography (QCT...
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BMC
2025-04-01
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| Series: | BMC Geriatrics |
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| Online Access: | https://doi.org/10.1186/s12877-025-05928-3 |
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| author | Yanbo Liang Xiaoqing Yuan Qiang Shi Hui Yang Luping Zhao Minghao Che Yue Chen Changqin Li Qi Yang Jian Qin |
| author_facet | Yanbo Liang Xiaoqing Yuan Qiang Shi Hui Yang Luping Zhao Minghao Che Yue Chen Changqin Li Qi Yang Jian Qin |
| author_sort | Yanbo Liang |
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| description | Abstract Background The aim is to explore the value of pericoronary adipose tissue (PCAT) attenuation in predicting abnormal bone mass by establishing a prediction model. Materials and methods 361 patients with coronary computed tomography angiography (CCTA) and quantitative computed tomography (QCT) scans were retrospectively recruited. 311 patients from institution 1 from July 2021 to January 2023 were divided into a training cohort (n = 217) and an internal cohort (n = 94). The external cohort comprised 50 patients from institution 2 from January 2023 to August 2023. Clinical variables and PCAT attenuation of the major epicardial vessels were obtained. Univariate and multivariate logistic regression analyses were used to identify factors with statistical significance. Model 1 was constructed based on clinical variables. Model 2 was constructed by combining the clinical variables with the PCAT attenuation. The performances of the models were assessed using receiver operating characteristic curve analysis, calibration curves and decision curve analysis (DCA). Results Age, gender, coronary artery disease reporting and data system (CAD-RADS), statins and RCAPCAT were found to be significant predictors of abnormal bone mass. The area under the curve (AUC) of Model 2 was superior to that of Model 1 in the training cohort (AUC: 0.959 vs. 0.920), internal (AUC: 0.943 vs. 0.890) and external validation cohorts (AUC: 0.889 vs. 0.812). The calibration curves and DCA indicated that Model 2 had the higher clinical value. Conclusion The model incorporating clinical factors and RCAPCAT has good performance in predicting bone mass abnormalities. |
| format | Article |
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| institution | OA Journals |
| issn | 1471-2318 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
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| series | BMC Geriatrics |
| spelling | doaj-art-46a1ae03409446cdb571c74f934f49082025-08-20T02:30:27ZengBMCBMC Geriatrics1471-23182025-04-0125111110.1186/s12877-025-05928-3Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation modelYanbo Liang0Xiaoqing Yuan1Qiang Shi2Hui Yang3Luping Zhao4Minghao Che5Yue Chen6Changqin Li7Qi Yang8Jian Qin9Department of Radiology, The Second Affiliated Hospital of Shandong First Medical UniversityChinese Institute for Medical Research, Capital Medical UniversityDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical UniversityDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical UniversityDepartment of Radiology, Affiliated Hospital of Jining Medical UniversityDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical UniversityDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical UniversityDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical UniversityDepartment of Radiology, Beijing Chaoyang Hospital, Capital Medical UniversityDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical UniversityAbstract Background The aim is to explore the value of pericoronary adipose tissue (PCAT) attenuation in predicting abnormal bone mass by establishing a prediction model. Materials and methods 361 patients with coronary computed tomography angiography (CCTA) and quantitative computed tomography (QCT) scans were retrospectively recruited. 311 patients from institution 1 from July 2021 to January 2023 were divided into a training cohort (n = 217) and an internal cohort (n = 94). The external cohort comprised 50 patients from institution 2 from January 2023 to August 2023. Clinical variables and PCAT attenuation of the major epicardial vessels were obtained. Univariate and multivariate logistic regression analyses were used to identify factors with statistical significance. Model 1 was constructed based on clinical variables. Model 2 was constructed by combining the clinical variables with the PCAT attenuation. The performances of the models were assessed using receiver operating characteristic curve analysis, calibration curves and decision curve analysis (DCA). Results Age, gender, coronary artery disease reporting and data system (CAD-RADS), statins and RCAPCAT were found to be significant predictors of abnormal bone mass. The area under the curve (AUC) of Model 2 was superior to that of Model 1 in the training cohort (AUC: 0.959 vs. 0.920), internal (AUC: 0.943 vs. 0.890) and external validation cohorts (AUC: 0.889 vs. 0.812). The calibration curves and DCA indicated that Model 2 had the higher clinical value. Conclusion The model incorporating clinical factors and RCAPCAT has good performance in predicting bone mass abnormalities.https://doi.org/10.1186/s12877-025-05928-3OsteoporosisCoronary atherosclerosisCoronary computed tomography angiographyPericoronary adipose tissue |
| spellingShingle | Yanbo Liang Xiaoqing Yuan Qiang Shi Hui Yang Luping Zhao Minghao Che Yue Chen Changqin Li Qi Yang Jian Qin Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation model BMC Geriatrics Osteoporosis Coronary atherosclerosis Coronary computed tomography angiography Pericoronary adipose tissue |
| title | Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation model |
| title_full | Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation model |
| title_fullStr | Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation model |
| title_full_unstemmed | Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation model |
| title_short | Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation model |
| title_sort | prediction of abnormal bone mass with a pericoronary adipose tissue attenuation model |
| topic | Osteoporosis Coronary atherosclerosis Coronary computed tomography angiography Pericoronary adipose tissue |
| url | https://doi.org/10.1186/s12877-025-05928-3 |
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