Deep learning model based on PET/CT and combination with Cox proportional hazard model for predicting progression of lung invasive adenocarcinoma after surgery
10.13929/j.issn.1003-3289.2024.08.018
- VernacularTitle:基于PET/CT深度学习及其联合模型预测肺浸润性腺癌术后进展
- Author:
Yingci LI
1
;
Dongbo WU
;
Feifei GONG
Author Information
1. 哈尔滨医科大学附属肿瘤医院PET/CT-MR中心,黑龙江哈尔滨 150081
- Keywords:
adenocarcinoma of lung;
positron-emission tomography and computed tomography;
deep learning;
disease progression
- From:
Chinese Journal of Medical Imaging Technology
2024;40(8):1194-1198
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the efficacy of deep learning(DL)model based on PET/CT and its combination with Cox proportional hazard model for predicting progressive disease(PD)of lung invasive adenocarcinoma within 5 years after surgery.Methods The clinical,PET/CT and 5-year follow-up data of 250 patients with lung invasive adenocarcinoma were retrospectively analyzed.According to PD or not,the patients were divided into the PD group(n=71)and non-PD group(n=179).The basic data and PET/CT findings were compared between groups,among which the quantitative variables being significant different between groups were transformed to categorical variables using receiver operating characteristic(ROC)curve and corresponding cut-off value.Multivariant Cox proportional hazard model was used to select independent predicting factors of PD of lung invasive adenocarcinoma within 5 years after surgery.The patients were divided into training,validation and test sets at the ratio of 6∶2∶2,and PET/CT data in training set and validation set were used to train model and tuning parameters to build the PET/CT DL model,and the combination model was built in serial connection of DL model and the predictive factors.In test set,the efficacy of each model for predicting PD of lung invasive adenocarcinoma within 5 years after surgery was assessed and compared using the area under the curve(AUC).Results Patients'gender and smoking status,as well as the long diameter,SUVmax and SUVmean of lesions measured on PET images,the long diameter,short diameter and type of lesions showed on CT were statistically different between groups(all P＜0.05).Smoking(HR=1.787[1.053,3.031],P=0.031)and lesion SUVmax＞4.15(HR=5.249[1.062,25.945],P=0.042)were both predictors of PD of lung invasive adenocarcinoma within 5 years after surgery.In test set,the AUC of PET/CT DL model for predicting PD was 0.847,of the combination model was 0.890,of the latter was higher than of the former(P=0.036).Conclusion DL model based on PET/CT had high efficacy for predicting PD of lung invasive adenocarcinoma within 5 years after surgery.Combining with Cox proportional hazard model could further improve its predicting efficacy.
