[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100624402":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":12,"locations":10,"responsibleParty":18,"collaborators":10,"id":22,"slug":23,"hasResults":24,"nctId":25,"briefTitle":26,"officialTitle":27,"acronym":10,"eligibilityCriteria":28,"healthyVolunteers":24,"sex":29,"minAge":30,"maxAge":10,"enrollmentInfo":31,"targetDuration":10,"studyType":34,"phases":10,"briefSummary":35,"conditions":36,"keywords":10,"overallStatus":38,"whyStopped":10,"lastUpdateSubmitDate":39,"lastUpdatePostDateStruct":40,"startDateStruct":43,"completionDateStruct":45,"leadSponsor":47,"locationsCount":10},{"fullName":5,"class":6},"Sun Yat-sen University","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"First-line Asparaginase-based Treatment Cohort",null,"Participants in this cohort are patients with extranodal natural killer\u002FT-cell lymphoma (NKTCL) who are planned to receive standard first-line asparaginase-based chemotherapy according to institutional practice. Pretreatment clinical data, contrast-enhanced magnetic resonance imaging (MRI) of the nasopharynx and neck, and digital pathology images from hematoxylin and eosin (H\\&E)-stained tumor sections will be collected. Patients will be followed for progression-free survival and overall survival according to routine follow-up schedule.",[13],{"name":14,"role":15,"phone":16,"phoneExt":10,"email":17},"Qingqing Cai, MD. PhD.","CONTACT","0208734282","caiqq@sysucc.org.cn",{"type":19,"investigatorFullName":20,"investigatorTitle":21,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Qingqing Cai","chief phycisian","100624402","multi-modal-fusion-model-and-deep-learning-for-predicting-treatment-response-in-nktcl-100624402",false,"NCT07409168","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\u002FT-Cell Lymphoma","Inclusion Criteria:\n\n* 1\\. Age ≥ 18 years.\n* 2\\. Pathologically confirmed extranodal natural killer\u002FT-cell lymphoma (NKTCL) according to the World Health Organization (WHO) classification.\n* 3\\. Patients who are planned to receive first-line asparaginase-based chemotherapy or chemoradiotherapy.\n* 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.\n* 5\\. Ability to understand the study and provide written informed consent (ICF).\n\nExclusion Criteria:\n\n* 1\\. History of other malignant tumors.\n* 2\\. Patients with psychiatric disorders or those unable to provide informed consent.","ALL","18 Years",{"count":32,"type":33},100,"ESTIMATED","OBSERVATIONAL","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\u002FT-cell lymphoma (NKTCL) receiving first-line asparaginase-based therapy.",[37],"Natural Killer\u002FT-cell Lymphoma","NOT_YET_RECRUITING","2026-04-26",{"date":41,"type":42},"2026-04-28","ACTUAL",{"date":44,"type":33},"2026-08-15",{"date":46,"type":33},"2027-12-31",{"name":5,"class":6}]