Nasopharyngeal Carcinoma, Oral Mucositis
Conditions
Keywords
Nasopharyngeal Carcinoma, Oral Mucositis, deep learning
Brief summary
The goal of this observational study is to apply the CNN-based DL method to extract the three-dimensional spatial information of IMRT dose distribution to predict the occurrence probability of serious radiotherapy and chemotherapy induced oral mucositis(SRCOM), and compare with a model based on dosimetry, NTCP or doseomics to improve the prediction accuracy of SRCOM, thus guiding the clinical planning design, reducing the occurrence probability of OM, and may have the potential value of preventing serious complications and improving the quality of life in patients with nasopharyngeal carcinoma.
Interventions
OTHERobservational group
patients initially diagnosed with nasopharyngeal carcinoma treated with IMRT
Sponsors
Sun Yat-sen University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Initial diagnosis, pathological histological diagnosis, the pathological type is non-keratotic carcinoma (according to the WHO pathological classification). * Initial intensity-modulated radiotherapy (Intensity modulated radiation therapy, IMRT). * No previous radiotherapy was received.
Exclusion criteria
* Patients with recurrent nasopharyngeal carcinoma. * Radiotherapy plan cannot be obtained. * Previous history of malignancy; previous radiotherapy. * The primary lesion and cervical metastatic lesions have received surgical treatment (except for diagnostic treatment).
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| RTOG/EROTC Acute Radiation Reaction Scoring Standard | through radiation therapy, an average of 7 weeks | Toxicity records of oral mucosal Reaction in patients are conducted by professionally trained oncologists |
Countries
China
Contacts
Primary ContactFang-Yun Xie, M.D.
Backup ContactPu-Yun OuYang, M.D.
Outcome results
None listed