Predicting Radiological Extranodal Extension in Oropharyngeal Carcinoma Patients Using AI

Running, not enrolling

Conditions studied: Head and Neck Carcinoma

In brief

Development and validation of a model that predicts rENE from radiological imaging using annotated / labeled scans by means of deep learning

Key facts

Study ID

NCT05565313

Run by

Maastricht Radiation Oncology

People needed

900

Starts

2022-03-22

Expected to finish

2026-08-01

Last updated by the study team

2025-08-14

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Non-metastatic (M0) node-positive HPV+ and HPV- oropharyngeal carcinoma
• Treated between 2008 to 2019
• Curative intent
• Radiation only or concurrent chemoradiation
• Modern treatment modality: IMRT / VMAT
• diagnostic/staging image scanning protocols available (contrast-enhanced CT with 2-3 mm slice thickness and/or MR with 3 mm slice thickness)

You may not qualify if…

• removal of lymph node (LN) (excisional biopsy or neck dissection [ND]) prior to staging CT/MR scan
• no available imaging within 2 months prior to radiotherapy (RT)"

Where it is running

• Harvard Medical School and clinical faculty at Dana-Farber Cancer Institute/Brigham and Women's Hospital — Boston, Massachusetts, United States
• Princess Margaret Cancer Centre — Toronto, Ontario, Canada
• Maastro — Maastricht, Limburg, Netherlands

Full record on ClinicalTrials.gov

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