Abstract

ObjectivesThis study aimed to develop radiomic models based on low-dose CT (LDCT) and standard-dose CT to distinguish adenocarcinomas from benign lesions in patients with solid solitary pulmonary nodules and compare the performance among these radiomic models and Lung CT Screening Reporting and Data System (Lung-RADS). The reproducibility of radiomic features between LDCT and standard-dose CT were also evaluated.MethodsA total of 141 consecutive pathologically confirmed solid solitary pulmonary nodules were enrolled including 50 adenocarcinomas and 48 benign nodules in primary cohort and 22 adenocarcinomas and 21 benign nodules in validation cohort. LDCT and standard-dose CT scans were conducted using same acquisition parameters and reconstruction method except for radiation dose. All nodules were automatically segmented and 104 original radiomic features were extracted. The concordance correlation coefficient was used to quantify reproducibility of radiomic features between LDCT and standard-dose CT. Radiomic features were selected to build radiomic signature, and clinical characteristics and radiomic signature were combined to develop radiomic nomogram for LDCT and standard-dose CT, respectively. The performance of radiomic models and Lung-RADS was assessed by area under curve (AUC) of receiver operating characteristic curve, sensitivity, and specificity.ResultsShape and first order features, and neighboring gray tone difference matrix features were highly reproducible between LDCT and standard-dose CT. No significant differences of AUCs were found among radiomic signature and nomogram of LDCT and standard-dose CT in both primary and validation cohort (0.915 vs. 0.919 vs. 0.898 vs. 0.909 and 0.976 vs. 0.976 vs. 0.985 vs. 0.987, respectively). These radiomic models had higher specificity than Lung-RADS (all correct P < 0.05), while there were no significant differences of sensitivity between Lung-RADS and radiomic models.ConclusionsThe diagnostic performance of LDCT-based radiomic models to differentiate adenocarcinomas from benign lesions in solid pulmonary nodules were equivalent to that of standard-dose CT. The LDCT-based radiomic model with higher specificity and lower false-positive rate than Lung-RADS might help reduce overdiagnosis and overtreatment of solid pulmonary nodules in lung cancer screening.

Highlights

  • Lung cancer is the leading cause of cancer-related death worldwide [1,2,3]

  • A total of 141 solid solitary pulmonary nodules (72 adenocarcinomas and 69 benign nodules) were consecutively included in this study from April 2019 and May 2020, according to the following inclusion criteria: 1) detection of solid solitary pulmonary nodule without calcification for typical benign lesion; 2) Low-dose computed tomography (LDCT) obtained from lung cancer screening; 3) standard-dose CT obtained within 24 h after LDCT to evaluate hilar and mediastinal lymph nodes; 4) pathologically confirmed

  • The McNemar test results further showed the radiomic models had higher specificity than Lung-RADS in the combined cohort, while there were no significant differences of sensitivity between Lung-RADS and radiomic models (Table 5)

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Summary

Introduction

Lung cancer is the leading cause of cancer-related death worldwide [1,2,3]. Low-dose computed tomography (LDCT) has been widely recommended for lung cancer screening as it can reduce the mortality [4, 5], but concerns about the high falsepositive rate of diagnosis and the following overtreatment are emerging [4, 6,7,8]. To study the effect of radiation dose reduction on radiomic features in vivo, Lo et al applied the noise addition methods to simulate dose reduction conditions [22], while Solomon et al repeated scan with half standard dose [23]. Their results indicated some texture features were not reproducible when reducing radiation dose. The reproducibility of radiomic features of solitary pulmonary nodules between LDCT for lung cancer screening and standard-dose CT examinations remains unaddressed

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