A team led by investigators at Dana-Farber Cancer Institute and Mass General Brigham has developed and validated an artificial intelligence (AI)–based noninvasive tool that can predict the likelihood that a patient’s oropharyngeal cancer—a type of head and neck cancer that develops in the throat—will spread, thereby signaling which patients should receive aggressive treatment.
The outcome of their research is published in the December 2025 edition of the Journal of Clinical Oncology.[1]
Benjamin H. Kann, MD, a radiation oncologist at Dana-Farber Cancer Institute and Brigham and Women’s Hospital. Photo courtesy © 2026 Dana-Farber Cancer Institute. used with permission.“Our tool may help identify which patients should receive multiple interventions or would be ideal candidates for clinical trials of intensive strategies such as immunotherapy or additional chemotherapy,” noted senior author Benjamin H. Kann, MD, a radiation oncologist at Dana-Farber Cancer Institute and Brigham and Women’s Hospital and faculty member of the Artificial Intelligence in Medicine (AIM) Program at Mass General Brigham.
“Our tool can also help identify which patients should undergo de-intensification of treatment, such as surgery alone,” Kann added.
Treatments for oropharyngeal cancer, including combinations of surgery, radiation therapy, and chemotherapy, can be difficult to tolerate and may have lasting negative effects. Therefore, it’s important to identify subgroups of patients who may benefit from less or more intensive treatment approaches.
One way to accomplish this is to assess whether the patient has pathologic extranodal extension (ENE), which occurs when cancer cells invade beyond the lymph node into surrounding tissue. Currently, ENE can only be definitively diagnosed by surgically removing and examining lymph nodes.
To provide a method for assessing ENE before treatment decisions are made, Kann and colleagues developed an AI-based tool that can analyze computed tomography scans and predict the number of lymph nodes with ENE, an indicator of a patient’s prognosis and likelihood of benefiting from intensified therapy.
When the tool was applied to imaging scans from 1,733 patients with oropharyngeal carcinoma, the tool was able to predict uncontrolled cancer spread and worse patient survival. Integrating the AI’s assessment into established clinical risk predictors improved risk stratification, leading to more accurate predictions of survival and cancer spread in individual patients.
“The AI tool enables the prediction of number of lymph nodes with ENE, which could not be done before, and shows that it is a powerful, novel prognostic biomarker for oropharyngeal cancer that could be used to improve the current staging scheme and treatment planning,” said Kann.
Reference
[1] Ye Z, Mojahed-Yazdi R, Zapaishchykova A, Tak D, Mahootiha M, Pardo JCC, Zielke J, Zha Y, Guthier C, Tishler RB, Margalit DN, Schoenfeld JD, Haddad RI, Uppaluri R, Haibe-Kains B, Fuller CD, Naser M, Burtness BA, Aerts HJWL, Hoebers F, Kann BH. Automated Lymph Node and Extranodal Extension Assessment Improves Risk Stratification in Oropharyngeal Carcinoma. J Clin Oncol. 2025 Dec 23:JCO2402679. doi: 10.1200/JCO-24-02679. Epub ahead of print. PMID: 41435207; PMCID: PMC12826331.
Featured image licensed under the Unsplash+ License. Used with permission.
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