中国医学科学院学报2024，Vol.46Issue(2)：169-175,7.DOI:10.3881/j.issn.1000-503X.15618
基于临床可视化参数建立肺磨玻璃结节生长预测模型
A Growth Prediction Model of Pulmonary Ground-Glass Nodules Based on Clinical Visualization Parameters
周莹莹 1陈志军1
作者信息
- 1. 浙江省舟山医院胸心外科, 浙江舟山 316021
- 折叠
摘要
Abstract
Objective To establish a model for predicting the growth of pulmonary ground-glass nodules(GGN)based on the clinical visualization parameters extracted by the 3D reconstruction technique and to verify the prediction performance of the model.Methods A retrospective analysis was carried out for 354 cases of pul-monary GGN followed up regularly in the outpatient of pulmonary nodules in Zhoushan Hospital of Zhejiang Prov-ince from March 2015 to December 2022.The semi-automatic segmentation method of 3D Slicer was employed to extract the quantitative imaging features of nodules.According to the follow-up results,the nodules were classi-fied into a resting group and a growing group.Furthermore,the nodules were classified into a training set and a test set by the simple random method at a ratio of 7∶3.Clinical and imaging parameters were used to establish a prediction model,and the prediction performance of the model was tested on the validation set.Results A total of 119 males and 235 females were included,with a median age of 55.0(47.0,63.0)years and the mean fol-low-up of(48.4±16.3)months.There were247 cases in the training set and107 cases in the test set.The bina-ry Logistic regression analysis showed that age(95%CI =1.010-1.092,P =0.015)and mass(95%CI = 1.002-1.067,P =0.035)were independent predictors of nodular growth.The mass(M)of nodules was calcu-lated according to the formula M =V×(CTmean +1000)×0.001(where V is the volume,V =3/4πR3,R:ra-dius).Therefore,the logit prediction model was established as ln[P/(1-P)]=-1.300 +0.043×age + 0.257×two-dimensional diameter +0.007×CTmean.The Hosmer-Lemeshow goodness of fit test was performed to test the fitting degree of the model for the measured data in the validation set(χ2 =4.515,P =0.808).The check plot was established for the prediction model,which showed the area under receiver-operating characteris-tic curve being 0.702.Conclusions The results of this study indicate that patient age and nodule mass are inde-pendent risk factors for promoting the growth of pulmonary GGN.A model for predicting the growth possibility of GGN is established and evaluated,which provides a basis for the formulation of GGN management strategies.关键词
肺癌/肺磨玻璃结节/三维重建/建模/预测Key words
lung cancer/pulmonary ground-glass nodule/3D reconstruction/modeling/prediction分类
医药卫生引用本文复制引用
周莹莹,陈志军..基于临床可视化参数建立肺磨玻璃结节生长预测模型[J].中国医学科学院学报,2024,46(2):169-175,7.
