Purpose: Imaging biomarkers (IBMs) are increasingly investigated as prognostic indicators. IBMs might be capable of assisting treatment selection by providing useful insights into tumor-specific factors in a non-invasive manner.
Methods: We investigated six three-dimensional shape-based IBMs: eccentricities between (I) intermediate-major axis (Eimaj), (II) intermediate-minor axis (Eimin), (III) major-minor axis (Emj-mn) and volumetric index of (I) sphericity (VioS), (II) flattening (VioF), (III) elongating (VioE). Additionally, we investigated previously established two-dimensional shape IBMs: eccentricity (E), index of sphericity (IoS), and minor-to-major axis length (Mn_Mj). IBMs were compared in terms of their predictive performance for 5-year overall survival in two independent cohorts of patients with lung cancer. Cohort 1 received surgical excision, while cohort 2 received radiation therapy alone or chemo-radiation therapy. Univariate and multivariate survival analyses were performed. Correlations with clinical parameters were evaluated using analysis of variance. IBM reproducibility was assessed using concordance correlation coefficients (CCCs).
Results: E was associated with reduced survival in cohort 1 (hazard ratio [HR]: 0.664). Eimin and VioF were associated with reduced survival in cohort 2 (HR 1.477 and 1.701). VioS was associated with reduced survival in cohorts 1 and 2 (HR 1.758 and 1.472). Spherical tumors correlated with shorter survival durations than did irregular tumors (median survival difference: 1.21 and 0.35 years in cohorts 1 and 2, respectively). VioS was a significant predictor of survival in multivariate analyses of both cohorts. All IBMs showed good reproducibility (CCC ranged between 0.86-0.98).
Conclusions: In both investigated cohorts, VioS successfully linked shape morphology to patient survival.
Keywords: Imaging biomarker; Non-small cell lung cancer; Overall survival; Prognosis; Tumor shape.