| CTRI Number |
CTRI/2024/02/062536 [Registered on: 12/02/2024] Trial Registered Prospectively |
| Last Modified On: |
05/02/2024 |
| Post Graduate Thesis |
No |
| Type of Trial |
Observational |
|
Type of Study
|
Observational |
| Study Design |
Other |
|
Public Title of Study
|
Voxelbox based structural and functional brain mapping in patients with space occupying lesions |
|
Scientific Title of Study
|
Voxelbox based structural and functional brain mapping in patients with space occupying lesions |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Ullas V Acharya |
| Designation |
Neuroradiologist |
| Affiliation |
Manipal Hospital |
| Address |
Dr Ullas V Acharya
MBBS, MD, DM (Neuroimaging and Interventional Radiology)
Neuroradiologist
Department of Radiology
Minus Two Floor
Manipal hospital
Old Airport Road
Bengaluru - 560017
Bangalore
KARNATAKA
560017
India |
| Phone |
9845889825 |
| Fax |
|
| Email |
ullasva77@gmail.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Ullas V Acharya |
| Designation |
Neuroradiologist |
| Affiliation |
Manipal Hospital |
| Address |
Dr Ullas V Acharya
MBBS, MD, DM (Neuroimaging and Interventional Radiology)
Neuroradiologist
Department of Radiology
Minus Two Floor
Manipal hospital
Old Airport Road
Bengaluru - 560017
Bangalore
KARNATAKA
560017
India |
| Phone |
9845889825 |
| Fax |
|
| Email |
ullasva77@gmail.com |
|
Details of Contact Person
Public Query
|
| Name |
Ullas V Acharya |
| Designation |
Neuroradiologist |
| Affiliation |
Manipal Hospital |
| Address |
Dr Ullas V Acharya
MBBS, MD, DM (Neuroimaging and Interventional Radiology)
Neuroradiologist
Department of Radiology
Minus Two Floor
Manipal hospital
Old Airport Road
Bengaluru - 560017
Bangalore
KARNATAKA
560017
India |
| Phone |
9845889825 |
| Fax |
|
| Email |
ullasva77@gmail.com |
|
|
Source of Monetary or Material Support
|
| Grant |
| Manipal Hospitals (infrastructural support) |
|
|
Primary Sponsor
|
| Name |
BrainSightAI |
| Address |
No. 677, 1st Floor, 27th Main, 13th Cross, HSR Layout, Sector 1 Bangalore, Karnataka, 560102. |
| Type of Sponsor |
Other [For-profit company] |
|
|
Details of Secondary Sponsor
|
| Name |
Address |
| NIL |
Not applicable as we have no 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 Ullas V Acharya |
Manipal Hospital |
Dr Ullas V Acharya
MBBS, MD, DM (Neuroimaging and Interventional Radiology)
Neuroradiologist
Department of Radiology
Minus Two Floor
Manipal hospital
Old Airport Road
Bengaluru - 560017
Bangalore
KARNATAKA |
9845889825
ullasva77@gmail.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| Ethics Committee of Manipal Hospitals |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Patients |
(1) ICD-10 Condition: G94||Other disorders of brain in diseases classified elsewhere, |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Intervention |
Nil |
Not applicable as this is an observational trial |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
60.00 Year(s) |
| Gender |
Both |
| Details |
1. Brain SOLs
2. Eligible for surgical resection
|
|
| ExclusionCriteria |
| Details |
1. Anyone < 18 and > 60 years of age
2. History of primary neurological disorders including seizure disorders/pre-existing disorders of development and degenerative disorders involving structural changes
3. Primary/pre-existing development and degenerative disorder involving structural changes
4. Primary/pre-existing Movement, Vision and speech disorders
5. Surgery in adjunct with cranial radiotherapy
6. Follow-up cases
7. Patients with contraindications to magnetic resonance imaging scanning
8. Pregnant women
9. Cases of meningioma
10. Non- compliance with fMRI protocol
11. Clinical symptoms not matching with SOL
|
|
|
Method of Generating Random Sequence
|
Not Applicable |
|
Method of Concealment
|
Not Applicable |
|
Blinding/Masking
|
Not Applicable |
|
Primary Outcome
|
| Outcome |
TimePoints |
| This study will come to an end when at least 50 analyzable datasets are obtained for rs-fMRI and tb-fMRI (25 for language, 25 for motor). |
The study is expected to take 12 months. |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
| There are no secondary outcomes. |
N/A |
|
|
Target Sample Size
|
Total Sample Size="60"
Sample Size from India="60"
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)
|
15/02/2024 |
| 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="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 most commonly used imaging modalities in neuro-oncological surgery today are the structural magnetic resonance imaging and the task-based functional magnetic imaging, with the resting-state functional magnetic imaging being less commonly used. However, the latter is in many ways more efficient than the former.
We aim to utilize a resting-state connectomics approach augmented by machine learning, as mentioned below for space occupying lesions. This machine learning-augmented connectomics approach will minimize the risk of resecting functional networks during surgery and improve patient outcomes post-operation.
To supplement the use of task-based functional magnetic resonance imaging by using resting-state fMRI which utilises machine learning-generated brain masks.
Our machine learning has been trained, on 1200 datasets obtained from the Human Connectome Project, to not only build both task-positive and task-negative networks from preexisting HCP datasets, but also to use those datasets to derive these networks from the patients’ brains. These activations will be validated against those from a task-based functional magnetic imaging for language and motor networks.
To quantify the extent of network and midline shift in the brain due to mass effect of space occupying lesion.
|