Abstract
Simple SummaryIn this study we explored the predictive ability of radiomics in non-small cell lung cancer patients, and reported the complementary role of radiomics in predicting the treatment response of the lymph nodes. Radiomics analysis is a cutting-edge technology for the noninvasive assessment of tumor biology, which converts medical images into mineable high-dimensional data. Our method is cost-effective with no need for additional studies, and moreover, we used an easily reproducible study method that can be applicable in further studies using radiomics in oncology.Although a substantial decrease in 2-[fluorine-18]fluoro-2-deoxy-d-glucose (FDG) uptake on positron emission tomography-computed tomography (PET-CT) indicates a promising metabolic response to treatment, predicting the pathologic status of lymph nodes (LN) remains challenging. We investigated the potential of a CT radiomics approach to predict the pathologic complete response of LNs showing residual uptake after neoadjuvant concurrent chemoradiotherapy (NeoCCRT) in patients with non-small cell lung cancer (NSCLC). Two hundred and thirty-seven patients who underwent NeoCCRT for stage IIIa NSCLC were included. Two hundred fifty-two CT radiomics features were extracted from LNs showing remaining positive FDG uptake upon restaging PET-CT. A multivariable logistic regression analysis of radiomics features and clinicopathologic characteristics was used to develop a prediction model. Of the 237 patients, 135 patients (185 nodes) met our inclusion criteria. Eighty-seven LNs were proven to be malignant (47.0%, 87/185). Upon multivariable analysis, metastatic LNs were significantly prevalent in females and patients with adenocarcinoma (odds ratio (OR) = 2.02, 95% confidence interval (CI) = 0.88–4.62 and OR = 0.39, 95% CI = 0.19–0.77 each). Metastatic LNs also had a larger maximal 3D diameter and higher cluster tendency (OR = 9.92, 95% CI = 3.15–31.17 and OR = 2.36, 95% CI = 1.22–4.55 each). The predictive model for metastasis showed a discrimination performance with an area under the receiver operating characteristic curve of 0.728 (95% CI = 0.654–0.801, p value < 0.001). The radiomics approach allows for the noninvasive detection of metastases in LNs with residual FDG uptake after the treatment of NSCLC patients.
Highlights
Lung cancer remains the leading cause of worldwide cancer mortality [1], the use of molecular targeted agents [2] and the expansion of the role of immunotherapy using checkpoint inhibitors have significantly advanced treatment [3]
As the radiomics approach allows the better characterization of tumors, more precise prognostic assessment [8], and an improved prediction of drug resistance [9,10], it may be used as a helpful tool for evaluating the treatment response of lymph nodes
The accurate staging of lymph nodes (LN) is essential, because it affects the selection of treatment plans and the survival rate of cancer patients
Summary
Lung cancer remains the leading cause of worldwide cancer mortality [1], the use of molecular targeted agents [2] and the expansion of the role of immunotherapy using checkpoint inhibitors have significantly advanced treatment [3]. A substantial decrease in 2-[fluorine-18] fluoro-2-deoxy-d-glucose (FDG) uptake is promising, false negative and false positive values of 25% and 33%, respectively, have been reported when predicting the pathologic complete response of LNs [6]. These high false negative and positive values indicate that PET-CT images alone are not suitable for making a final decision and additional invasive pathologic confirmation is recommended. As the radiomics approach allows the better characterization of tumors, more precise prognostic assessment [8], and an improved prediction of drug resistance [9,10], it may be used as a helpful tool for evaluating the treatment response of lymph nodes
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
