Study on clinical effect of artificial intelligence technique in delineating target volume of radiotherapy for lung cancer
10.3969/j.issn.1672-8270.2024.11.002
- VernacularTitle:人工智能技术用于肺癌放射治疗靶区勾画中的临床效果研究
- Author:
Jianglin TANG
1
;
Mingwei CHEN
;
Lugen LIU
;
Zhiqiang ZHAN
;
Fengheng LUO
;
Hao QIAO
Author Information
1. 萍乡市人民医院肿瘤科 萍乡 337000
- Keywords:
Artificial intelligence(AI)technique;
Lung cancer;
Delineation of clinical target volume;
Planning target volume(PTV);
Target radiation dose
- From:
China Medical Equipment
2024;21(11):7-11
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the clinical effect of artificial intelligence(AI)technique in delineating target volume for patients with lung cancer during radiotherapy.Methods:A total of 60 patients with lung cancer who received radiotherapy in Pingxiang People's Hospital from September 2021 to March 2023 were selected,and they were divided into control group and observation group by random envelope method,with 30 cases in each group.The control group outlined target volume as conventional method.The observation group adopted deep learning technique to conduct train,and then,UNet network model was output and was used to complete automatic delineation for the target volume of radiotherapy for patients.The near-term efficacy,planning target region volume,radiation dose of target volume,volume and dose of organ at risk(OAR),survival time and incidence of adverse reactions were compared between two groups.Results:The objective relief rate(ORR)of observation group was 70.0％(21/30)after intervention,which was higher than that[46.67％(14/30)]of control group,and the difference was statistically significant(x2=5.691,P＜0.05).The radiation doses of internal target volume(ITV)and planning target volume in observation group were lower respectively than those in control group(t=4.591,4.934,P＜0.05),and the differences of them were significant,respectively.The volume percentages(V20,V5)of the exposed radiation dose that were higher than 20 Gy and 5 Gy in normal lung tissue,the exposed mean lung dose(MLD)of bilateral lungs and the exposed dose of 1cc volume(D1cc)of bilateral lungs in observation group were all lower than those in control group,the differences were statistically significant(t=5.249,4.571,6.092,5.339,P＜0.05),respectively.There was no statistical significance in the incidence of adverse reaction between two groups(P＞0.05).Conclusion:The application of AI technique in delineating target volume of radiotherapy for lung cancer can improve ORR,which is helpful to decrease the planning target volume,D95 and conformal index,and reduce the volume and dose of OAR.It does not increase the incidence of adverse reactions.
