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

Multi-modal Fusion Model and Deep Learning for Predicting Treatment Response in NK/T-Cell Lymphoma

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.

Inclusion Criteria:

• 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).

Exclusion Criteria:

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