| CTRI Number |
CTRI/2026/01/101817 [Registered on: 22/01/2026] Trial Registered Prospectively |
| Last Modified On: |
22/01/2026 |
| Post Graduate Thesis |
No |
| Type of Trial |
Observational |
|
Type of Study
|
Cross Sectional Study |
| Study Design |
Other |
|
Public Title of Study
|
Use of Artificial intelligence and MRI for predicting brain tumor recurrence |
|
Scientific Title of Study
|
Development and validation of Artificial Intelligence (AI) models for prediction of glioma and meningioma recurrence using preoperative MRI – A Multicenter study |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Dr Rajagopal Kadavigere Venkatachalaiah |
| Designation |
Professor and Head of the Deaprtment |
| Affiliation |
Manipal Academy of Higher Education |
| Address |
Department of Radiodiagnosis and Imaging, Kasturba Medical College, Manipal Academy of Higher Education
Udupi
KARNATAKA
576104
India |
| Phone |
9448158901 |
| Fax |
|
| Email |
rajarad@gmail.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Dr Rajagopal Kadavigere Venkatachalaiah |
| Designation |
Professor and Head of the Deaprtment |
| Affiliation |
Manipal Academy of Higher Education |
| Address |
Department of Radiodiagnosis and Imaging, Kasturba Medical College, Manipal Academy of Higher Education
KARNATAKA
576104
India |
| Phone |
9448158901 |
| Fax |
|
| Email |
rajarad@gmail.com |
|
Details of Contact Person
Public Query
|
| Name |
Dr Rajagopal Kadavigere Venkatachalaiah |
| Designation |
Professor and Head of the Deaprtment |
| Affiliation |
Manipal Academy of Higher Education |
| Address |
Department of Radiodiagnosis and Imaging, Kasturba Medical College, Manipal Academy of Higher Education
KARNATAKA
576104
India |
| Phone |
9448158901 |
| Fax |
|
| Email |
rajarad@gmail.com |
|
|
Source of Monetary or Material Support
|
| Indian Council of Medical Research (ICMR), V. Ramalingaswami Bhawan, P.O. Box No. 4911, Ansari Nagar, New Delhi - 110029, India |
| Kasturba Medical College, Manipal Academy of Higher Education, Tiger Circle Road, Madhav Nagar, Eshwar Nagar, Manipal, Karnataka 576104, India |
| Sri Ramachandra Institute of Higher Education and Research, Ramachandra Nagar, Porur, Chennai - 600116, Tamil Nadu, India |
|
|
Primary Sponsor
|
| Name |
Indian Council of Medical Research |
| Address |
V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi - 110029 |
| Type of Sponsor |
Government funding agency |
|
|
Details of Secondary Sponsor
|
|
|
Countries of Recruitment
|
India |
|
Sites of Study
|
| No of Sites = 2 |
| Name of Principal
Investigator |
Name of Site |
Site Address |
Phone/Fax/Email |
| Dr Rajagopal Kadavigere Venkatachalaiah |
Kasturba Medical College and Kasturba Hospital |
Department of Radiodiagnosis and Imaging, Kasturba Medical college, Manipal Academy of Higher Education, Manipal
Udupi
KARNATAKA |
9448158901
rajarad@gmail.com |
| Dr Anupama Chandrasekharan |
Sri Ramachandra Medical Centre |
Department of Radiodiagnosis and Imaging, Sri Ramachandra Institute of Higher Education and Research, Chennai
Chennai
TAMIL NADU |
9940025243
anupamachandrasekharan@sriramachandra.edu.in |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 2 |
| Name of Committee |
Approval Status |
| Kasturba Medical College and Kasturba Hospital Institutional Ethics Committee |
Approved |
| Sri Ramachandra Institute of Higher Education and Research |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Patients |
(1) ICD-10 Condition: C719||Malignant neoplasm of brain, unspecified, (2) ICD-10 Condition: C700||Malignant neoplasm of cerebral meninges, |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Intervention |
Nil |
Nil |
| Comparator Agent |
Nil |
Nil |
| Intervention |
Nil |
Nil |
| Intervention |
Nil |
Nil |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
80.00 Year(s) |
| Gender |
Both |
| Details |
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
|
|
| ExclusionCriteria |
| Details |
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 |
|
|
Method of Generating Random Sequence
|
Not Applicable |
|
Method of Concealment
|
Not Applicable |
|
Blinding/Masking
|
Not Applicable |
|
Primary Outcome
|
| Outcome |
TimePoints |
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 models |
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 Outcome
|
| Outcome |
TimePoints |
| Radiomic characterization of tumors |
1. Preoperative MRI Scan |
|
|
Target Sample Size
|
Total Sample Size="380"
Sample Size from India="380"
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" |
|
Phase of Trial
|
N/A |
|
Date of First Enrollment (India)
|
19/02/2026 |
| Date of Study Completion (India) |
Applicable only for Completed/Terminated trials |
| Date of First Enrollment (Global) |
Date Missing |
| Date of Study Completion (Global) |
Applicable only for Completed/Terminated trials |
|
Estimated Duration of Trial
|
Years="3"
Months="0"
Days="0" |
|
Recruitment Status of Trial (Global)
|
Not Yet Recruiting |
| Recruitment Status of Trial (India) |
Not Yet Recruiting |
|
Publication Details
|
N/A |
|
Individual Participant Data (IPD) Sharing Statement
|
Will individual participant data (IPD) be shared publicly (including data dictionaries)?
Response - NO
|
|
Brief Summary
|
The study aims to develop and validate machine learning (ML) and deep learning (DL) models for predicting the recurrence of glioma and meningioma using preoperative magnetic resonance imaging (MRI).
In the initial phase, retrospective MRI data from 300 patients (150 with glioma and 150 with meningioma) will be used to train ML and DL models based on documented recurrence outcomes. Subsequently, the developed AI models will undergo prospective validation using preoperative MRI scans, with reference to postoperative MRI findings to confirm recurrence status. |