Study on Radiogenomics Features Associated With Radiochemotherapy Sensitivity in Gliomas
NCT ID: NCT06454097
Last Updated: 2024-06-12
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
200 participants
INTERVENTIONAL
2024-01-23
2024-12-31
Brief Summary
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In this prospective cohort study, we will recruit patients with gliomas who have undergone craniotomy and received postoperative radiotherapy or radiochemotherapy (in cases of LGG and HGG, respectively). MRI images of the same sequences will be collected at corresponding time points, and transcriptomic sequencing will be performed on tumor tissue obtained during surgery. The established model will be applied to predict radiochemotherapy sensitivity and compared with the 'true' radiochemotherapy sensitivity labels, which are constructed based on the RANO criteria, to evaluate the predictive performance of the model.
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Detailed Description
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The collected MRI images before and after radiochemotherapy will be used to assess changes in tumor volume. The RANO criteria will be employed to determine the tumor's sensitivity to radiochemotherapy: a complete response and partial response will be classified as sensitive, while stable disease and disease progression will be considered insensitive.
Radiomics features will be extracted using the open-source 'PyRadiomics' python package after performing image preprocessing and segmentation. Transcriptomic data will be obtained by conducting RNA sequencing analysis on tumor samples collected during surgery. Selected radiogenomic features will be incorporated into a pre-constructed machine learning model to predict the sensitivity of gliomas to radiochemotherapy. The model's performance will be evaluated using metrics such as classification accuracy (ACC), area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and negative predictive value (NPV).
Conditions
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Study Design
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NA
SINGLE_GROUP
DIAGNOSTIC
NONE
Study Groups
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Evaluate the response of patients with glioma to radiochemotherapy
The response of patients with glioma to radiochemotherapy will be assessed by the RANO criteria and the established radiogenomics-based artificial intellegent model.
Assess the response glioma to radiochemotherapy using radiogenomics-based AI model
Predict the radiochemotherapy sensitivity of patients with glioma using an established radiogenomics-based artificial intellegent mode
Interventions
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Assess the response glioma to radiochemotherapy using radiogenomics-based AI model
Predict the radiochemotherapy sensitivity of patients with glioma using an established radiogenomics-based artificial intellegent mode
Eligibility Criteria
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Inclusion Criteria
* Histologically confirmed glioma
* No history of other brain tumors or previous cranial surgeries
* No history of preoperative radiotherapy or chemotherapy
* Available preoperative, pre-radiotherapy(postoperatively), and post-radiotherapy magnetic resonance imaging (MRI) data
18 Years
ALL
No
Sponsors
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Beijing Tiantan Hospital
OTHER
Responsible Party
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Principal Investigators
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Yinyan Wang, MD and PhD
Role: PRINCIPAL_INVESTIGATOR
Beijing Tiantan Hospital
Locations
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Beijing Tiantan Hospital
Beijing, Beijing Municipality, China
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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82072786
Identifier Type: -
Identifier Source: org_study_id
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