Artificial intelligence models based on non-contrast chest CT for measuring bone mineral density
10.13929/j.issn.1003-3289.2024.08.026
- VernacularTitle:基于胸部平扫CT人工智能模型测量骨密度
- Author:
Wei DUAN
1
;
Guoqing YANG
;
Yang LI
;
Feng SHI
;
Lian YANG
;
Xin XIONG
;
Bei CHEN
;
Yong LI
;
Quanshui FU
Author Information
1. 川北医学院医学影像学院,四川南充 637000;遂宁市中心医院放射影像科,四川遂宁 629000
- Keywords:
osteoporosis;
bone density;
tomography,X-ray computed;
artificial intelligence
- From:
Chinese Journal of Medical Imaging Technology
2024;40(8):1231-1235
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1-L3 vertebrae were measured based on QCT.Spongy bones of T5-T10 vertebrae were segmented as RO1,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,MLBagging OP and RadBagging-OP had the best performances for classification of OP.In test set,AUC of MLBagging-OP,RadBagging-op and DLOP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P＞0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of(x)±1.96s),which were highly positively correlated(r=0.910-0.974,all P＜0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.
