Predicting Radiological Extranodal Extension in Oropharyngeal Carcinoma Patients Using AI

Sex: All

Ages: 18 Years – N/A

Healthy volunteers: No

Enrollment: 900

Sponsor: Maastricht Radiation Oncology

Location: Harvard Medical School and clinical faculty at Dana-Farber Cancer Institute/Brigham and Women's Hospital Boston Massachusetts

Summary

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

Eligibility Criteria

Inclusion criteria: * 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) Exclusion criteria: * 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)"

Interested in this study? View the official listing for contact and enrollment details.

View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT05565313). StuddyBuddy aggregates publicly available trial information.