This project focuses on researching chronic rhinosinusitis in patients, employing image processing techniques and molecular biology methods to jointly determine the research objectives:

1. Investigating heterogeneity.
2. Developing an intelligent assessment model.
3. Creating a visual tool for diagnosis and prognosis.

1. Investigating the heterogeneity of chronic rhinosinusitis: the project will utilize high-throughput information from various sources such as radiology, pathology, and proteomics to gain insights into the multi-dimensional and big data aspects of chronic rhinosinusitis. By analyzing this data, the study aims to identify and understand the different subtypes with more precise and personalized treatment approaches.
2. Developing an intelligent assessment model: using artificial intelligence algorithms, the project will analyze multi-omics data gathered from the research. The goal is to establish an intelligent assessment model that can accurately interpret the data and provide valuable insights into chronic rhinosinusitis.
3. Creating a visual tool for diagnosis and prognosis: the project seeks to integrate multi-omics information to establish an AI model for typing and prognostic prediction. By achieving these research objectives, this project aspires to enhance the understanding of chronic rhinosinusitis and contribute to the development of more precise, personalized, and effective treatment strategies for patients suffering from this condition.

Inclusion Criteria:

1. oral glucocorticoid, and intranasal steroid spray and steroid irrigation treatment were discontinued at least 3 months and 1 month before surgery, respectively;
2. without acute asthma episode or acute upper airway infection within 1 month before surgery;
3. not under allergen immunotherapy or biologic treatment.

Exclusion Criteria:

1. fungal sinusitis;
2. antrochoanal polyps;
3. cystic fibrosis, vasculitis, primary ciliary dyskinesia, or immunodeficiency;
4. odontogenic maxillary sinusitis;
5. patients with history of craniocerebral trauma or sinonasal tumours.
6. insufficient CT quality (e.g., metal artifacts, motion artifacts, and lack of intact CT scan of sinuses);
7. slice thickness more than 2.5 mm.
8. women must not be pregnant, or breast-feeding;
9. patients with serious metabolic, cardiovascular, autoimmune, neurology, blood, digestive, cerebrovascular, or respiratory system disease, or any disease interfering with the evaluation of results or affecting subjects safety are excluded, such as glaucoma and tuberculosis;
10. patients with emotional or mental problems are excluded;
11. patients unsuitable for inclusion based on judgement of researchers are excluded;

Chronic rhinosinusitis (CRS) was diagnosed according to the international guideline European position paper on rhinosinusitis and nasal polyps (EPOS) 2020. All the patients had ongoing symptoms after initial attempts on medical treatments and underwent endoscopic sinus surgery.