MR radiomics unveils neoadjuvant chemo-responsiveness with insights into selective treatment de-intensification in HPV-positive oropharyngeal carcinoma

Background: Accurate prediction of neoadjuvant chemotherapy (NAC) response allows for NAC-guided personalized treatment de-intensification in HPV-positive oropharyngeal squamous cell carcinoma (OPSCC). In this study, we aimed to apply baseline MR radiomic features to predict NAC response to help select NAC-guided de-intensification candidates, and to explore biological underpinnings of response-oriented radiomics. Methods: Pre-treatment MR images and clinical data of 131 patients with HPV-positive OPSCC were retrieved from Fudan University Shanghai Cancer Center. Patients were divided into training cohort (n = 47), validation cohort 1 (n = 49) from NAC response-adapted de-intensification trial (IChoice-01, NCT04012502) and real-world validation cohort 2 (n = 35). NAC prediction model using linear support vector machine (SVM) was built and validated. Subsequent nomograms combined radiomics and clinical characteristics were established to predict survival outcomes. RNA-seq and proteomic data were compared to interpret the molecular features underlying radiomic signatures with differential NAC response. Findings: For NAC response prediction, the fusion model with both oropharyngeal and nodal signatures achieved encouraging performance to predict good responders in the training cohort (AUC 0<middle dot>89, 95% CI, 0<middle dot>79-0<middle dot>95) and validation cohort 1 (AUC 0<middle dot>71, 95% CI, 0<middle dot>59-0<middle dot>83). For prognosis prediction, radiomics-based nomograms exhibited satisfactory discriminative ability between low-risk and high-risk patients (PFS, C-index 0<middle dot>85, 0<middle dot>76 and 0<middle dot>83; OS, C-index 0<middle dot>79, 0<middle dot>76 and 0<middle dot>87, respectively) in three cohorts. Expression analysis unveiled NAC poor responders had predominantly enhanced keratinization while good responders were featured by upregulated immune response and oxidative stress. Interpretation: The MR-based radiomic models and prognostic models efficiently discriminate among patients with different NAC response and survival risk, which help candidate selection in HPV-positive OPSCC with regard to personalized treatment de-intensification.