| CTRI Number |
CTRI/2025/03/083745 [Registered on: 28/03/2025] Trial Registered Prospectively |
| Last Modified On: |
03/04/2025 |
| Post Graduate Thesis |
Yes |
| Type of Trial |
Observational |
|
Type of Study
|
Cross Sectional Study |
| Study Design |
Other |
|
Public Title of Study
|
AI-Driven MRI Tool For Identifying Benign And Malignant Brain Tumors |
|
Scientific Title of Study
|
Integrating artificial intelligence (AI) with MRI for distinguishing Benign and Malignant tumors of Brain. |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Pranathi Ravula |
| Designation |
Post graduate, Radio-diagnosis |
| Affiliation |
Saveetha Medical college and Hospital |
| Address |
Room no.50, Department of radiology, Saveetha medical college and
hospital, Saveetha institute of medical and technical sciences,
Saveetha nagar, Thandala, Chennai, India
Kancheepuram
TAMIL NADU
602105
India |
| Phone |
9701130929 |
| Fax |
|
| Email |
pranathi1357@gmail.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Yuvaraj Murali |
| Designation |
Professor |
| Affiliation |
Saveetha medical college and hospital |
| Address |
Room no.50, Department of radiology, Saveetha medical college and
hospital, Saveetha institute of medical and technical sciences,
Saveetha nagar, Thandala, Chennai, India
Kancheepuram
TAMIL NADU
602105
India |
| Phone |
9840224048 |
| Fax |
|
| Email |
dr.yuvraj1987@gmail.com |
|
Details of Contact Person
Public Query
|
| Name |
Pranathi Ravula |
| Designation |
Post graduate, Radio-diagnosis |
| Affiliation |
Saveetha medical college and hospital |
| Address |
Room no.50, Department of radiology, Saveetha medical college and
hospital, Saveetha institute of medical and technical sciences,
Saveetha nagar, Thandala, Chennai, India
Kancheepuram
TAMIL NADU
602105
India |
| Phone |
9701130929 |
| Fax |
|
| Email |
pranathi1357@gmail.com |
|
|
Source of Monetary or Material Support
|
| Saveetha Medical College Hospital, Saveetha Nagar, Thandalam, Chennai-602105 |
|
|
Primary Sponsor
|
| Name |
Dr. Pranathi Ravula |
| Address |
Saveetha medical college hopsital, Saveetha nagar, Thandalam, Chennai - 602105 |
| Type of Sponsor |
Other [SELF] |
|
|
Details of Secondary Sponsor
|
|
|
Countries of Recruitment
|
India |
|
Sites of Study
|
| No of Sites = 1 |
| Name of Principal
Investigator |
Name of Site |
Site Address |
Phone/Fax/Email |
| Dr Pranathi Ravula |
Saveetha Medical College Hospita |
Room no 50, Department of Radiology, Saveetha
Medical College Hospital, Saveetha
Nagar, Thandalam,Chennai.
Kancheepuram
TAMIL NADU |
9701130929
pranathi1357@gmail.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| Saveetha Medical College and Hospital Institutional Ethics Committee |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Patients |
(1) ICD-10 Condition: G988||Other disorders of nervous system, (2) ICD-10 Condition: G988||Other disorders of nervous system, |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Comparator Agent |
nil |
nil |
| Intervention |
nil |
nil |
|
|
Inclusion Criteria
|
| Age From |
10.00 Year(s) |
| Age To |
90.00 Year(s) |
| Gender |
Both |
| Details |
1. Population Criteria: Patients aged 10 years and above.
Individuals with histopathologically confirmed benign or malignant brain tumors.
2. Medical History: Documented clinical history relevant to brain tumor diagnosis and treatment.
Patients with no prior surgical, radiation, or chemotherapy intervention to ensure baseline imaging accuracy.
3. MRI Scan Data: High-quality MRI images, including T1-weighted, T2-weighted, and contrast-enhanced sequences.
Images free from significant artifacts that could compromise AI analysis. |
|
| ExclusionCriteria |
| Details |
1. Population Criteria: Patients below 10 years of age. Patients with non-brain tumors or non-tumor brain conditions (e.g., infections, vascular abnormalities).
2. Medical History: Patients with incomplete or unavailable clinical history.
Individuals who have undergone prior surgical, radiation, or chemotherapy interventions before MRI acquisition. Patients with significant comorbidities or contraindications to MRI (e.g., pacemakers, metallic implants).
3. MRI Scan Data: Low-quality MRI images with significant artifacts or incomplete imaging sequences. MRI scans missing critical sequences such as T1-weighted, T2-weighted, or contrast-enhanced images. Imaging data not obtained from standardized MRI protocols. |
|
|
Method of Generating Random Sequence
|
Computer generated randomization |
|
Method of Concealment
|
An Open list of random numbers |
|
Blinding/Masking
|
Participant and Investigator Blinded |
|
Primary Outcome
|
| Outcome |
TimePoints |
| The primary outcome of this study is to accurately identify brain tumors and differentiate between benign and malignant types using AI-enhanced MRI analysis. This involves leveraging AI algorithms trained on diverse MRI sequences to provide precise and reliable classifications that align with histopathological findings, the gold standard for diagnosis. |
24 hours |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
| The accuracy of AI-enhanced MRI in differentiating benign from malignant brain tumors, measured against histopathological findings as the gold standard. |
30 days |
|
|
Target Sample Size
|
Total Sample Size="100"
Sample Size from India="100"
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)
|
01/04/2025 |
| 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="1"
Months="6"
Days="0" |
|
Recruitment Status of Trial (Global)
|
Not Yet Recruiting |
| Recruitment Status of Trial (India) |
Not Yet Recruiting |
Publication Details
Modification(s)
|
N/A |
|
Individual Participant Data (IPD) Sharing Statement
|
Will individual participant data (IPD) be shared publicly (including data dictionaries)?
Response - NO
|
|
Brief Summary
|
The integration of artificial intelligence (AI) with magnetic resonance imaging (MRI) offers a groundbreaking approach to distinguishing benign and malignant brain tumors. This study focuses on developing and validating AI models using advanced machine learning and deep learning techniques to analyze MRI sequences like T1-weighted, T2-weighted, and contrast-enhanced images. A comprehensive dataset of tumor cases is utilized to ensure robust and accurate model training.Key outcomes include evaluating the diagnostic accuracy, sensitivity, and specificity of AI-enhanced MRI compared to conventional radiological methods. The study also emphasizes the interpretability of AI models to ensure clinical trust and explores their impact on improving diagnostic efficiency, reducing time, and aiding treatment planning. The research aims to advance radiological practices, offering precise, efficient, and reliable tools for brain tumor classification. |