This study focuses on tumor heterogeneity, a core challenge in the field of oncology, and innovatively utilizes patient imaging data to deeply mine and analyze intratumoral heterogeneity. By constructing an imaging analysis model for tumor heterogeneity and associating this model with clinical, pathological, transcriptomic, and metabolomic data of patients, a multi-omics decoding of tumor heterogeneity is achieved. The main questions it aims to address are:

Can the ITH model stratify patients' treatment efficacy and prognosis assessment? Can pathological and multi-omics sequencing map the mechanisms behind the ITH model?

Inclusion Criteria:

Pathologically confirmed head and neck squamous cell carcinoma (HNSCC). Complete clinical, imaging, and pathological data. Available complete follow-up information.

Exclusion Criteria:

Patients who received chemotherapy or radiotherapy before surgery. Poor image quality. Tumors too small to be easily identified. History of other concurrent malignant tumors.

Patients with pathologically confirmed HNSCC were collected from the Department of Otolaryngology, the First Affiliated Hospital of Chongqing Medical University.

Due to the high emphasis on patient privacy protection, there is currently no information about public availability of the dataset in this study. After the relevant articles of this study are officially published, peers can apply to obtain the research data from the corresponding author for legitimate scientific research purposes.