# Quantitative Imaging Advances in HPV-Positive Oropharyngeal Carcinoma

## TL;DR

This paper reviews how quantitative imaging techniques like MRI, CT, and PET, combined with AI, can improve care for patients with HPV-positive oropharyngeal cancer by enabling personalized treatment decisions.

## Contribution

The paper uniquely maps imaging findings to specific decision points in radiotherapy workflows and highlights requirements for clinical translation.

## Key findings

- Quantitative imaging supports risk stratification, treatment adaptation, and surveillance in HPV-positive OPSCC.
- Standardized reporting and validation are essential for integrating imaging biomarkers into clinical workflows.
- AI and radiomics show promise but face barriers like limited validation and heterogeneous methods.

## Abstract

This is a review article of published research on the area of quantitative imaging for HPV-positive oropharyngeal carcinomas. This review looks at advances in multiple modalities, including MRI, CT, PET, and the use of deep learning tools in this field. Progress in this field will potentially change diagnostic workflows for relevant patients. Unlike prior narrative reviews that have primarily catalogued modality-specific performance, this review focuses on both decision and implementation by mapping results from imaging investigations to decision points found in the radiotherapy pathway (diagnosis, treatment adaptation, and post-treatment surveillance). Further, we have highlighted where evidence is now informing de-escalation vs. where evidence still remains exploratory. We have summarised technical and validation requirements for embedding these biomarkers into radiotherapy workflows and de-escalation trials.

HPV-positive OPSCC shows a favourable prognosis, prompting evaluation of de-escalated and adaptive strategies. Quantitative imaging may provide scalable biomarkers to individualise care. Quantitative imaging can support baseline risk stratification, early on-treatment decision-making, and posttreatment surveillance in HPV-positive OPSCC. Real-world translation requires standardised reporting, calibration/harmonisation across centres, rigorous model validation, and workflow integration with radiotherapy planning. Quantitative MRI, CT, and PET, augmented by radiomics and AI, show convergent promise as non-invasive biomarkers to enable safe individualisation of therapy in HPV-positive OPSCC, contingent on methodological rigour and prospective, externally validated studies. Despite this promise, clinical translation faces substantial barriers, including limited external validation, heterogeneous methodologies, and the need for standardised, prospectively validated pipelines.