S. Alfieri, R. RomanĂ², M. Bologna, G. Calareso, A. Mirabile, A. Ferri, A. Marcantoni, E. Grosso, A. Tarsitano, S. Valerini, S. Vecchio, L. Deantonio, F. Blengio, T. Ibrahim, M. Mancinelli, F. Ascoli, P. Bossi, L. D. Locati, L. Mainardi, L. F. Licitra

Prognostic role of pre-treatment magnetic resonance imaging (MRI) radiomic analysis in patients with squamous cell carcinoma of the head and neck (SCCHN)

Medical Imaging Analysis and Diagnostics

Emerging data suggest that radiomics can be used to predict outcomes in SCCHN. At present, only few data are available for pre-treatment MRI.

Study population was retrieved from an ongoing multicenter, randomized, prospective trial (NCT02262221, HETeCo) evaluating health and economic outcomes of two different follow-up (FUP) strategies (intensive vs non-intensive) in effectively cured stage III-IV (VIII TNM ed.) SCCHN. We selected only patients with both pre- and post-contrast enhancement T1 and T2-weighted baseline MRI (b-MRI) and at least 2 years (2y) of FUP. A radiomic model was developed to identify high risk (HR) and low risk (LR) of disease recurrence. Radiomic features (RF) were extracted from the primary tumor in the b-MRI. The best RF combination was selected by Least Absolute Shrinkage and Selection Operator (LASSO). Ten-fold cross-validation was used to compute sensitivity, specificity and area under the curve (AUC) of the classifier. Kaplan-Meier (KM) curves were estimated for HR and LR, for both overall survival (OS) and disease-free survival (DFS) and log rank test was performed. Three years (3y)-DFS and OS were also estimated for the two groups. The radiomic risk class was used as a new variable in a multivariate Cox model including well established prognostic factors in SCCHN (TNM stage, subsite and HPV).

Out of 155 enrolled HETeCO patients, 98 baseline imaging were retrieved of which 57 b-MRI. Of these, 51 met the eligibility criteria (25 in intensive and 26 in non-intensive arm). Baseline patients’ characteristics were: median age 66 yr (38-86); sex (M 42; F 9); median smoking history: 30 packs/y (1-100); 25 oral cavity (49%), 18 oropharynx (35%, 14 HPV+), 6 larynx (12%), 2 hypopharynx (4%). At a median FUP of 42 months (25-64), 45 (88%) patients are still alive. The recurrence rate was 20% (10/51, of which 2 distant). In total, 1608 RF were extracted. The sensitivity, specificity and AUC of the classifier were 90%, 76%, and 80%, respectively. The radiomic risk class was found to be an independent prognostic factor for both DFS and OS (p=0.01 and p=0.046, respectively). KM curves for DFS and OS were significantly different between HR and LR groups (p=0.002 and p=0.04, respectively). In HR vs LR, 3-y DFS and OS were: 78% [61-100%] vs 97% [90-100%], and 88% [75-100%] vs 96% [88-100%], respectively.

Radiomics of pre-treatment MRI can predict outcomes in SCCHN. External validation of this preliminary radiomics-based model is currently ongoing.

This article is authored also by Synbrain data scientists and collaborators. READ THE FULL ARTICLE