Multi-modal Fusion Model and Deep Learning for Predicting Treatment Response in NKTCL

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Conditions studied: Natural Killer/T-cell Lymphoma

In brief

This is a multicenter prospective study to develop and validate a multimodal, deep learning-based model for predicting treatment response in patients with extranodal natural killer/T-cell lymphoma (NKTCL) receiving first-line asparaginase-based therapy.

Key facts

Study ID

NCT07409168

Run by

Sun Yat-sen University

People needed

100

Starts

2026-08-15

Expected to finish

2027-12-31

Last updated by the study team

2026-04-28

Who can join

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

You may qualify if…

• 1. Age ≥ 18 years.
• 2. Pathologically confirmed extranodal natural killer/T-cell lymphoma (NKTCL) according to the World Health Organization (WHO) classification.
• 3. Patients who are planned to receive first-line asparaginase-based chemotherapy or chemoradiotherapy.
• 4. Patients who have either contrast-enhanced MRI of the nasopharynx obtained as part of routine clinical care or pretreatment whole-slide images (WSI) of tumor tissue from hematoxylin and eosin (H\&E)-stained sections available for analysis.
• 5. Ability to understand the study and provide written informed consent (ICF).

You may not qualify if…

• 1. History of other malignant tumors.
• 2. Patients with psychiatric disorders or those unable to provide informed consent.

Full record on ClinicalTrials.gov

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