Prediction of CT-Based Radiomics in T1 Peripheral Non-Small Cell Lung Cancer via Spread Though Air Spaces
10.3969/j.issn.1005-5185.2024.07.007
- VernacularTitle:CT影像组学预测T1期周围型非小细胞肺癌气腔播散
- Author:
Huijie GE
1
;
Yujuan CAO
;
Lin WANG
;
Juan GUO
;
Shuai QUAN
;
Linning E
Author Information
1. 山西医科大学医学影像学院,山西 太原 030001
- Keywords:
Carcinoma,non-small-cell lung;
Tomography,X-ray computed;
Radiomics;
Spread though air spaces
- From:
Chinese Journal of Medical Imaging
2024;32(7):674-681
- CountryChina
- Language:Chinese
-
Abstract:
Purpose To investigate the predictive value of chest CT-based radiomics for spread through air spaces in stage T1 peripheral type lung cancer.Materials and Methods A total of 173 patients with surgically pathologically confirmed stage T1 non-small cell lung cancer were retrospectively collected and divided into positive group(49 cases)and negative group(124 cases)according to the presence or absence of spread through air spaces.All lesions were randomly divided into training set(122 cases)and validation set(51 cases)according to the ratio of 7∶3.The primary area of lung cancer(the main body of the lesion),the peripheral infiltrative area(a 5-mm annular area expanding outward along the edge of the lesion)and the tumor margin area(a 5-mm annular area retracting inward along the edge of the lesion)were used as areas of interest to extract imaging histological features.Three imaging histological models were established for the primary area of lung cancer,the peripheral infiltrative area and the tumor margin area,and combined with the morphological features of CT to establish three combined models.The efficacy of each model was evaluated and the optimal model was selected.Results The lobulation signs of positive group was significantly more than that of negative group(χ2=9.946,P=0.002).The area under the curve(AUC)of the imaging histological model based on the three regions of interest were 0.899,0.825,0.840 for the training group and 0.876,0.811 and 0.832 for the validation group,respectively.The model with the highest AUC was the primary tumor imaging model(P=0.043,P<0.001,P=0.017),the AUC of the combined model established by adding the lobar sign were 0.917,0.835 and 0.851,respectively.The AUC of the three regions of interest in the validation group were 0.912,0.832,and 0.845 and the highest AUC was found in the primary tumor area(P<0.001,P=0.017,P=0.049).Conclusion It is feasible to study lung cancer with airway metastasis via CT-based radiomics,taken lobulation signs as the risk predictive factor.
