Nasopharyngeal CarcinomaNCT05547971
Development of Intelligent Model for Radioactive Brain Damage of Nasopharyngeal Carcinoma Based on Radio-metabolomics
An observational study of Nasopharyngeal Carcinoma, run by Xiangya Hospital of Central South University at 1 site in China.
Trial 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… Read more about this study
- Who is it for?
- Ages 20 to 65 years
- Conditions the study is for
- Nasopharyngeal Carcinoma
- What is being tested?
- intensity-modulated radiation therapy
- Type of treatment
- Surgery or procedure
- How many people
- 800 participants
- Where
- 1 siteChina
- Study dates
- Sep 2022to Jun 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 65 years
- All sexes
- Adult, Older adult
Study population: Nasopharyngeal cancer patients in South University Xiangya Hospital, the First Affiliated Hospital of Nanhua University and the Affiliated Cancer Hospital of Central South University.
Who may be able to join
- Age 20-65; right handedness; Karnofsky physical condition score (KPS) ≥ 80;
- Histologically or cytologically confirmed non keratinizing squamous cell carcinoma of the nasopharynx with stage T3-4NxM0（AJCC 7th）;
- Plan to receive intensity-modulated radiation therapy, the primary dose is more than or equal to 66Gy, fractional dose is less than 2.3Gy;
- 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;
- 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;
- Patients can receive magnetic resonance imaging (MRI).
Who cannot join
- 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;
- He has a history of radiotherapy for the parts requiring radiotherapy in the past;
- There were no organic lesions in the brain, such as white matter lesions and brain atrophy, cerebrovascular diseases, brain tumors and brain trauma;
- 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.
- 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.
- Pregnant or lactating women (for women with sexual life and fertility, pregnancy test should be considered);
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- 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;
- Active infection requiring systemic treatment, positive for human immunodeficiency virus (HIV, HIV 1 / 2 antibody).
- A history of psychotropic drug abuse, alcoholism or drug abuse;
- Anti-vascular targeted drugs were used during induction chemotherapy before treatment;
- 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.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Xiangya Hospital of Central South University
Changsha, Hunan, 410008
Weihua Liao, +8613973126486, ouwenliao@163.com
Youming Zhang, +8615974266761, fsknpcxm@163.com
About this study
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.
Read the detailed description
Research Process
- 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;
- 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;
- 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;
- Extracting key features: using vertical axis data analysis method and logistic regression to establish dynamic prediction model.
- Conditions
- Nasopharyngeal Carcinoma
- Being tested
- intensity-modulated radiation therapy
- Keywords
- radioactive brain damage, radio-metabolomics, machine learning, Artificial Neural Network
- Medical subject headings
- Nasopharyngeal Carcinoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
intensity-modulated radiation therapyRadiation
The patients got intensity-modulated radiation therapy during observation
| Study group | Role | What they receive |
|---|---|---|
| Radiation Encephalopathy Group | Patients with radioactive encephalopathy during follow-up Receives: Radiation: intensity-modulated radiation therapy | |
| No Radiation Encephalopathy Group | Patients without radioactive encephalopathy during follow-up Receives: Radiation: intensity-modulated radiation therapy |
What is being measured
The primary outcome is the main question the study is designed to answer.
The variations in imaging features from initial diagnosis to 24 months after radiotherapy
Brain MRI image data of included patients with MRI sequence (T1 Wi, T2 Wi, T1 + C etc.) before and after radiotherapy (including initial diagnosis, 6 months, 12 months and 24 months after radiotherapy) were obtained for Artificial Neural Network analysis. The key features were found out by machine learning.The variations in imaging features from initial diagnosis to 24 months after radiotherapy were abtained to conduct an efficient prediction model for the probability of radiation encephalopathy.
Measured: Before and after radiotherapy (including initial diagnosis, 6 months, 12 months and 24 months after radiotherapy). All the data got from each time point were used to conduct an efficient prediction model.
Changes in metabolic feature from initial diagnosis to 24 months after radiotherapy
Since the changes in serum nucleotide metabolism, amino acid metabolism, fat metabolism were observed in the radiation encephalopathy patients. All Gas chromatography-mass spectrometer(GC-MS) data including retention features, peak intensity and integral mass spectrometry for each serum sample are used for analysis, to predict whether the separation between the radiation encephalopathy patients group and the control group is significant. The serum metabolism changes of patients during two years after radiotherapy are followed to obtain metabolic footprint. The serum sample got from different time points were applied in agglomerate hierarchical clustering for the screening and identification of various metabolites in the serum samples to get biomarkers, which can evaluate the changes of the metabolites in radiation encephalopathy.The PLS-DA model is used to represent changes in metabolic feature during metabolism.
Measured: Before and after radiotherapy (including initial diagnosis, 6 months, 12 months and 24 months after radiotherapy). The PLS-DA model is used to represent changes in metabolic feature during metabolism.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Sep 2022
- Study startSep 2022 (estimated)
- Primary completionJun 2023 (estimated)
- Study completionJun 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Nasopharyngeal CarcinomaStudies of the same condition, open and under way.
- More trials run by Xiangya Hospital of Central South UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Xiangya Hospital of Central South University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- fsknpcxm@163.com Liao, PHD, Study director, Xiangya Hospital of Central South University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05547971
- Sponsor's protocol ID
- fskliaoweihua1
- Status last verified
- Sep 2022
- First submitted
- 16 Mar 2021
- Last updated
- 21 Sep 2022
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 21 Sep 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of Intelligent Model for Radioactive Brain Damage of Nasopharyngeal Carcinoma Based on Radio-metabolomics
- ClinicalTrials.gov ID
- NCT05547971
- Acronym / sponsor ID
- fskliaoweihua1
- Conditions
- Nasopharyngeal Carcinoma
- Keywords
- radioactive brain damage, radio-metabolomics, machine learning, Artificial Neural Network
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 800 participants (estimated)
- Lead sponsor
- Xiangya Hospital of Central South UniversityUniversity, hospital or other
- Study start
- Sep 2022 (estimated)
- Primary completion
- Jun 2023 (estimated)
- Study completion
- Jun 2023 (estimated)
- First posted
- 21 Sep 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
- 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;
- 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;
- 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;
- Extracting key features: using vertical axis data analysis method and logistic regression to establish dynamic prediction model.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Radiation Encephalopathy Group | – | Radiation: intensity-modulated radiation therapyPatients with radioactive encephalopathy during follow-up |
| No Radiation Encephalopathy Group | – | Radiation: intensity-modulated radiation therapyPatients without radioactive encephalopathy during follow-up |
Who may qualify
- Ages
- 20 to 65 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Nasopharyngeal cancer patients in South University Xiangya Hospital, the First Affiliated Hospital of Nanhua University and the Affiliated Cancer Hospital of Central South University.
Key inclusion criteria (6 listed)
- Age 20-65; right handedness; Karnofsky physical condition score (KPS) ≥ 80;
- Histologically or cytologically confirmed non keratinizing squamous cell carcinoma of the nasopharynx with stage T3-4NxM0（AJCC 7th）;
- Plan to receive intensity-modulated radiation therapy, the primary dose is more than or equal to 66Gy, fractional dose is less than 2.3Gy;
- 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;
- 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;
Key exclusion criteria (11 listed)
- 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;
- He has a history of radiotherapy for the parts requiring radiotherapy in the past;
- There were no organic lesions in the brain, such as white matter lesions and brain atrophy, cerebrovascular diseases, brain tumors and brain trauma;
- 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.
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| intensity-modulated radiation therapyThe patients got intensity-modulated radiation therapy during observation | Radiation | No Radiation Encephalopathy Group, Radiation Encephalopathy Group |
Primary outcome
The variations in imaging features from initial diagnosis to 24 months after radiotherapy
Time frame: Before and after radiotherapy (including initial diagnosis, 6 months, 12 months and 24 months after radiotherapy). All the data got from each time point were used to conduct an efficient prediction model.
Brain MRI image data of included patients with MRI sequence (T1 Wi, T2 Wi, T1 + C etc.) before and after radiotherapy (including initial diagnosis, 6 months, 12 months and 24 months after radiotherapy) were obtained for Artificial Neural Network analysis. The key features were found out by machine learning.The variations in imaging features from initial diagnosis to 24 months after radiotherapy were abtained to conduct an efficient prediction model for the probability of radiation encephalopathy.
Changes in metabolic feature from initial diagnosis to 24 months after radiotherapy
Time frame: Before and after radiotherapy (including initial diagnosis, 6 months, 12 months and 24 months after radiotherapy). The PLS-DA model is used to represent changes in metabolic feature during metabolism.
Since the changes in serum nucleotide metabolism, amino acid metabolism, fat metabolism were observed in the radiation encephalopathy patients. All Gas chromatography-mass spectrometer(GC-MS) data including retention features, peak intensity and integral mass spectrometry for each serum sample are used for analysis, to predict whether the separation between the radiation encephalopathy patients group and the control group is significant. The serum metabolism changes of patients during two years after radiotherapy are followed to obtain metabolic footprint. The serum sample got from different time points were applied in agglomerate hierarchical clustering for the screening and identification of various metabolites in the serum samples to get biomarkers, which can evaluate the changes of the metabolites in radiation encephalopathy.The PLS-DA model is used to represent changes in metabolic feature during metabolism.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Sep 2022.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
fsknpcxm@163.com Liao, PHD study director
Xiangya Hospital of Central South University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Nasopharyngeal Carcinoma, run by Xiangya Hospital of Central South University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 11 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 21 Sep 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Weihua Liao, PHD (86-13973126486, ouwenliao@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The variations in imaging features from initial diagnosis to 24 months after radiotherapy (time frame: Before and after radiotherapy (including initial diagnosis, 6 months, 12 months and 24 months after radiotherapy). All the data got from each time point were used to conduct an efficient prediction model.). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Sep 2022.