Linyu Wu1,2, Chen Gao1,2, Jianfeng Ye1,2, Jingying Tao2, Neng Wang2, Peipei Pang3, Ping Xiang1,2, Maosheng Xu4,5. 1. Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China. 2. The First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, China. 3. Department of Pharmaceuticals Diagnosis, GE Healthcare, Hangzhou, China. 4. Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China. xums166@zcmu.edu.cn. 5. The First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, China. xums166@zcmu.edu.cn.
Abstract
OBJECTIVES: To evaluate the ability of CT radiomic features extracted from peritumoral parenchyma of 2 mm and 5 mm distinguishing invasive adenocarcinoma (IAC) from adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA). METHODS: For this retrospective study, 121 lung adenocarcinomas appearing as ground-glass nodules on thin-section CT were evaluated. Quantitative radiomic features were extracted from the peritumoral parenchymal region of 2 mm and 5 mm on CT imaging, and the radiomic models of External2 and External5 were constructed. The ROC curves were used to evaluate the performance of different models. Differences between the AUCs were evaluated using DeLong's method. RESULTS: The radiomic scores of IAC were statistically higher than those of MIA/AIS in both the External2 and External5 models. The AUCs of the External2 and External5 models were 0.882, 0.778 in the training cohort and 0.888, 0.804 in the validation cohort, respectively. The AUC of the External2 model was not statistically different from the External5 model both in the training cohort (p = 0.116) and validation cohort (p = 0.423). CONCLUSIONS: The radiomic features extracted from the peritumoral region of 2 mm and 5 mm at thin-section CT showed good predictive values to differentiate the IAC from AIS/MIA. The radiomic features from the peritumoral region of 5 mm provide no additional benefit in distinguishing IAC from MIA/AIS than that of the 2 mm region. KEY POINTS: • The radiomic models from various peritumoral lung parenchyma were developed and validated to predict invasiveness of adenocarcinoma. • The peritumoral parenchyma of lung adenocarcinoma may contain useful information. • Radiomics from peritumoral lung parenchyma of 5 mm provides no added efficiency of the prediction for invasiveness of lung adenocarcinoma.
OBJECTIVES: To evaluate the ability of CT radiomic features extracted from peritumoral parenchyma of 2 mm and 5 mm distinguishing invasive adenocarcinoma (IAC) from adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA). METHODS: For this retrospective study, 121 lung adenocarcinomas appearing as ground-glass nodules on thin-section CT were evaluated. Quantitative radiomic features were extracted from the peritumoral parenchymal region of 2 mm and 5 mm on CT imaging, and the radiomic models of External2 and External5 were constructed. The ROC curves were used to evaluate the performance of different models. Differences between the AUCs were evaluated using DeLong's method. RESULTS: The radiomic scores of IAC were statistically higher than those of MIA/AIS in both the External2 and External5 models. The AUCs of the External2 and External5 models were 0.882, 0.778 in the training cohort and 0.888, 0.804 in the validation cohort, respectively. The AUC of the External2 model was not statistically different from the External5 model both in the training cohort (p = 0.116) and validation cohort (p = 0.423). CONCLUSIONS: The radiomic features extracted from the peritumoral region of 2 mm and 5 mm at thin-section CT showed good predictive values to differentiate the IAC from AIS/MIA. The radiomic features from the peritumoral region of 5 mm provide no additional benefit in distinguishing IAC from MIA/AIS than that of the 2 mm region. KEY POINTS: • The radiomic models from various peritumoral lung parenchyma were developed and validated to predict invasiveness of adenocarcinoma. • The peritumoral parenchyma of lung adenocarcinoma may contain useful information. • Radiomics from peritumoral lung parenchyma of 5 mm provides no added efficiency of the prediction for invasiveness of lung adenocarcinoma.
Entities:
Keywords:
Adenocarcinoma of the lung; Area under the curve; Solitary pulmonary nodule; Tomography, X-ray computed
Authors: Pranjal Vaidya; Kaustav Bera; Philip A Linden; Amit Gupta; Prabhakar Shantha Rajiah; David R Jones; Matthew Bott; Harvey Pass; Robert Gilkeson; Frank Jacono; Kevin Li-Chun Hsieh; Gong-Yau Lan; Vamsidhar Velcheti; Anant Madabhushi Journal: Front Oncol Date: 2022-05-30 Impact factor: 5.738