Health Condition 1: C719- Malignant neoplasm of brain, unspecified Health Condition 2: C700- Malignant neoplasm of cerebral meninges
Conditions
Interventions
Intervention1: Nil: Nil
Intervention2: Nil: Nil
Intervention3: Nil: Nil
Intervention4: Nil: Nil
Control Intervention1: Nil: Nil
Sponsors
Indian Council of Medical Research
Eligibility
Inclusion criteria
Inclusion criteria: Phase I (Retrospective) Inclusion criteria: 1. Pre- and post-operative MRI Brain Images of the patients diagnosed with meningioma / Gliomas Phase II (Prospective) Inclusion criteria: 1. Post operative cases referred for MRI Brain diagnosed with meningioma / Gliomas with available preoperative images
Exclusion criteria
Exclusion criteria: Phase I (Retrospective) Exclusion criteria: 1. Patients who had incomplete MRI Brain imaging data 2. Suboptimal MRI image quality Phase II (Prospective) Exclusion criteria: 1. Suboptimal MRI image quality
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Phase I: The accuracy of Machine Learning (ML) and Deep Learning (DL) models for predicting glioma and meningioma recurrence using preoperative MRI with combined clinical and radiomic features. Phase II: Validation of the developed models Development of explainable AI modelsTimepoint: Phase I: (Retrospective) 1. Preoperative MRI scan 2. Post Operative MRI scan to check for the recurrence status Phase II: 1. Preoperative MRI 2. Post Operative MRI scan to check for the recurrence status | — |
Secondary
| Measure | Time frame |
|---|---|
| Radiomic characterization of tumorsTimepoint: 1. Preoperative MRI Scan | — |
Countries
India
Contacts
Public ContactDr Rajagopal Kadavigere Venkatachalaiah
Manipal Academy of Higher Education
Outcome results
None listed