Trial Title:
Development of Intelligent Model for Radioactive Brain Damage of Nasopharyngeal Carcinoma Based on Radio-metabolomics
NCT ID:
NCT05547971
Condition:
Nasopharyngeal Carcinoma
Conditions: Official terms:
Carcinoma
Nasopharyngeal Carcinoma
Brain Injuries
Conditions: Keywords:
radioactive brain damage
radio-metabolomics
machine learning
Artificial Neural Network
Study type:
Observational
Overall status:
Unknown status
Study design:
Time perspective:
Prospective
Intervention:
Intervention type:
Radiation
Intervention name:
intensity-modulated radiation therapy
Description:
The patients got intensity-modulated radiation therapy during observation
Arm group label:
No Radiation Encephalopathy Group
Arm group label:
Radiation Encephalopathy Group
Summary:
This project focuses on the early prediction and diagnosis of radiation-induced brain
injury in nasopharyngeal carcinoma patients. Based on the big data of imaging and serum
metabonomics samples, combined with the machine learning analysis method， dynamic
evolution mode of radio-metabolomics characteristics was analyzed . The potential
internal relationship between brain structure and serum metabolic changes was explored,
and the individualized prediction model was constructed to screen out the high-risk
patients with brain injury after tumor radiotherapy, so as to provide reference for the
diagnosis of radiation-induced brain injury caused by tumor. radiotherapy Intelligent
diagnosis provides a new theoretical and practical basis.
Detailed description:
Research Process
1. The MRI based cohort data set of nasopharyngeal carcinoma was established, and the
data of multiple follow-up time points before and after radiotherapy (including
initial diagnosis, 6 months, 12 months and 24 months after radiotherapy) were
standardized to obtain the longitudinal data set;
2. Region of interest (ROI): it mainly delineates the bilateral temporal lobe, brain
stem and other brain regions, and extracts the corresponding image features in ROI;
3. Feature selection: using the strategy of radiomics combined with Artificial Neural
Network to reduce the dimension of high-dimensional image features, the key features
are selected and used for the subsequent construction of classification and
prediction model;
4. Extracting key features: using vertical axis data analysis method and logistic
regression to establish dynamic prediction model.
Criteria for eligibility:
Study pop:
Nasopharyngeal cancer patients in South University Xiangya Hospital, the First Affiliated
Hospital of Nanhua University and the Affiliated Cancer Hospital of Central South
University.
Sampling method:
Non-Probability Sample
Criteria:
Inclusion Criteria:
1. Age 20-65; right handedness; Karnofsky physical condition score (KPS) ≥ 80;
2. Histologically or cytologically confirmed non keratinizing squamous cell carcinoma
of the nasopharynx with stage T3-4NxM0（AJCC 7th）;
3. Plan to receive intensity-modulated radiation therapy, the primary dose is more than
or equal to 66Gy, fractional dose is less than 2.3Gy;
4. Concurrent chemotherapy with cisplatin during radiotherapy, the total dose of
chemotherapy is more than or equal to 200mg / m^2; 7. Primary school education or
above, be able and willing to participate in the clinical trial, be able and willing
to sign the agreement and consent, and be able and willing to record the symptoms
and treatment details as often as necessary;
5. White blood cell count ≥ 3 × 10^9 / L, neutrophil count ≥ 1.5 × 10^9 / L, hemoglobin
≥ 90g / L and platelet count ≥ 100 × 10^9 / L; ALT / AST ≤ 1.5 times of upper limit
of normal (ULN), alkaline phosphatase (ALP) < 2.5 × ULN, bilirubin < ULN; ALB ≥ 28g
/ L;
6. Patients can receive magnetic resonance imaging (MRI).
Exclusion Criteria:
1. Unable or unwilling to give written and informed consent for MRI imaging, patients
with claustrophobia, aneurysm clip, implantable nerve stimulator, implantable
cardiac pacemaker or defibrillator, cochlear implant, eye foreign body or implant
(such as metal chips, retinal clip) or pancreatic islet pump, and other
contraindications for MRI scanning;
2. He has a history of radiotherapy for the parts requiring radiotherapy in the past;
3. There were no organic lesions in the brain, such as white matter lesions and brain
atrophy, cerebrovascular diseases, brain tumors and brain trauma;
4. Active, known or suspected autoimmune diseases, including but not limited to
systemic lupus erythematosus, rheumatoid arthritis, Sjogren's syndrome, ulcerative
colitis, Crohn's disease, myasthenia gravis, Hashimoto's thyroiditis, Graves'
disease and asthma requiring bronchodilators. Subjects with type I diabetes,
hypothyroidism requiring hormone replacement therapy only, and skin diseases (such
as vitiligo, psoriasis, or alopecia) not requiring systemic therapy were included.
5. Uncontrolled heart diseases, such as: (1) New York Heart Association classification
grade 2 or above heart failure (2) unstable angina pectoris (3) myocardial
infarction within one year (4) supraventricular or ventricular arrhythmias with
clinical significance and requiring treatment or intervention.
6. Pregnant or lactating women (for women with sexual life and fertility, pregnancy
test should be considered);
7. Previous or concurrent malignant tumors, except for non melanoma skin cancer,
cervical carcinoma in situ and papillary thyroid cancer, which have recovered well
after adequate treatment;
8. Active infection requiring systemic treatment, positive for human immunodeficiency
virus (HIV, HIV 1 / 2 antibody).
9. A history of psychotropic drug abuse, alcoholism or drug abuse;
10. Anti-vascular targeted drugs were used during induction chemotherapy before
treatment;
11. Other factors that may affect the safety of the subjects or the compliance of the
test according to the judgment of the researcher. For example, serious diseases
(including mental illness), serious laboratory abnormalities, or other family or
social factors that need to be treated together. Currently or in the past, there are
no major physical diseases, such as acute infection or untreated infection (viral,
bacterial or fungal infection), heart disease, severe hypertension, diabetes,
chronic kidney disease, genetic diseases, etc.
Gender:
All
Minimum age:
20 Years
Maximum age:
65 Years
Locations:
Facility:
Name:
Xiangya Hospital of Central South University
Address:
City:
Changsha
Zip:
410008
Country:
China
Status:
Recruiting
Contact:
Last name:
Weihua Liao
Phone:
+8613973126486
Email:
ouwenliao@163.com
Contact backup:
Last name:
Youming Zhang
Phone:
+8615974266761
Email:
fsknpcxm@163.com
Start date:
September 2022
Completion date:
June 2023
Lead sponsor:
Agency:
Xiangya Hospital of Central South University
Agency class:
Other
Source:
Xiangya Hospital of Central South University
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05547971
