AI model for imaging-based extranodal extension detection and outcome prediction in HPV−positive oropharyngeal cancer

JAMA Otolaryngology–Head & Neck Surgery

2025-09-30

(Press-News.org) About The Study: This single-center cohort study found that an artificial intelligence (AI)-driven pipeline can successfully automate lymph node segmentation and imaging-based extranodal extension (iENE) classification from pretreatment computed tomography scans in human papillomavirus (HPV)-associated oropharyngeal carcinoma. Predicted iENE was independently associated with worse oncologic outcomes. External validation is required to assess generalizability and the potential for implementation in institutions without specialized imaging expertise.

Corresponding Author: To contact the corresponding author, Laurent Letourneau-Guillon, MD, MSc, email laurent.letourneau-guillon.1@umontreal.ca.

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/

(doi:10.1001/jamaoto.2025.3225)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

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Media advisory: This study is being presented at the ASTRO (American Society for Radiation Oncology) 2025 Annual Meeting.

Embed this link to provide your readers free access to the full-text article This link will be live at the embargo time https://jamanetwork.com/journals/jamaotolaryngology/fullarticle/10.1001/jamaoto.2025.3225?guestAccessKey=33bc7ced-891e-4ce3-99ff-04c152f15920&utm_source=for_the_media&utm_medium=referral&utm_campaign=ftm_links&utm_content=tfl&utm_term=093025

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AI model for imaging-based extranodal extension detection and outcome prediction in HPV−positive oropharyngeal cancer

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