Prognostic Role Of Computed Tomography Textural Features In Early-Stage Non-Small Cell Lung Cancer Patients Receiving Stereotactic Body Radiotherapy

Cancer Manag Res. 2019 Nov 25:11:9921-9930. doi: 10.2147/CMAR.S220587. eCollection 2019.

Abstract

Purpose: The imaging features of patients with early-stage non-small cell lung cancer (NSCLC) receiving stereotactic body radiotherapy (SBRT) are crucial for the decision-making process to establish a treatment plan. The purpose of this study was to predict the clinical outcomes of SBRT from the textural features of pretreatment computed tomography (CT) images.

Patients and methods: Forty-one early-stage NSCLC patients who received SBRT were included in this retrospective study. In total, 72 textural features were extracted from the pretreatment contrast-enhanced CT images. Survival analysis was used to identify high-risk groups for progression-free survival (PFS) and disease-specific survival (DSS). Receiver operating characteristic (ROC) curve analysis was utilized to estimate the diagnostic abilities of the textural parameters. Univariable and multivariable Cox regression analyses were performed to evaluate the predictors of PFS and DSS.

Results: Four parameters, including entropy (P=0.003), second angular moment (SAM) (P=0.04), high-intensity long-run emphasis (HILRE) (P=0.046) and long-run emphasis (LRE) (P=0.042), were significant prognostic features for PFS. In addition, contrast (P=0.008), coarseness (P=0.017), low-intensity zone emphasis (LIZE) (P=0.01) and large number emphasis (LNE) (P=0.046) were significant prognostic factors for DSS. In the ROC analysis, the area under the curve (AUC) of coarseness for local recurrence (LR) was 0.722 (0.528-0.916), and the AUC of entropy for lymph node metastasis (LNM) was 0.771 (0.556-0.987). The four highest AUCs for distant metastasis (DM) were 0.885 (0.784-0.985) for LNE, 0.846 (0.733-0.959) for SAM, 0.731 (0.500-0.961) for LRE and 0.731 (0.585-0.876) for contrast. In the multivariable analysis, smoking and entropy were independent prognostic factors for PFS.

Conclusion: This exploratory study reveals that textual features derived from pretreatment CT scans have prognostic value in early-stage NSCLC patients treated with SBRT.

Keywords: NSCLC; clinical outcomes; computed tomography imaging; non-small cell lung cancer; stereotactic body radiation therapy; textural analysis.