Discriminate atypical pulmonary hamartoma from lung adenocarcinoma based on clinical and CT radiomics features
10.3969/j.issn.1002-1671.2024.08.005
- VernacularTitle:基于临床及CT放射组学特征鉴别非典型肺错构瘤与肺腺癌
- Author:
Chuanbin WANG
1
,
2
;
Cuiping LI
;
Feng CAO
;
Jiangning DONG
;
Xingwang WU
Author Information
1. 安徽医科大学第一附属医院放射科,安徽 合肥 230022
2. 中国科学技术大学附属第一医院(安徽省立医院)西区放射科,安徽 合肥 230031
- Keywords:
hamartoma;
lung adenocarcinoma;
radiomics;
nomogram;
computed tomography
- From:
Journal of Practical Radiology
2024;40(8):1238-1242
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of combined prediction model based on clinical and CT radiomics features in discriminating atypical pulmonary hamartoma(APH)from atypical lung adenocarcinoma(ALA).Methods A total of 290 patients with APH and ALA confirmed by pathology were retrospectively selected.250 patients from the First Affiliated Hospital of Anhui Medical University were randomly assigned into a training set(APH=91,ALA=84)and an internal validation set(APH=39,ALA=36)at a ratio of 7∶3,and other 40 patients from the First Affiliated Hospital of USTC were assigned as an external validation set(APH=21,ALA=19).The independent model and multivariate logistic regression combined model were constructed using the selected clinical-CT features and radiomics features,respectively,and a nomogram was drawn.Receiver operating characteristic(ROC)curve and DeLong test were used to evaluate and compare the performances of the models.Results The area under the curve(AUC)of the combined model established by 3 clinical-CT features and 4 radiomics features in the training set was 0.980,which was higher than that of clinical-CT model(AUC=0.885,P＜0.001)and radiomics model(AUC=0.975,P=0.042).The AUC of the combined model in the internal and external validation sets(0.963 vs 0.917)were also higher than those of clinical-CT model(0.858 vs 0.774)and radiomics model(0.953 vs 0.897),respectively.Conclusion The combined prediction model based on clinical and CT radiomics features can improve the differential diagnosis ability of APH and ALA.
