Ignite Creation Date:
2025-12-24 @ 4:42 PM
Ignite Modification Date:
2025-12-28 @ 11:56 AM
Study NCT ID:
NCT07037966
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-09-23
First Post:
2025-05-20
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Advancing Portable Brain Imaging: The NextMRI Project's Role in Revolutionizing Diagnostic MRI
Sponsor:
Instituto de Investigacion Sanitaria La Fe
Organization:
Study Overview
Official Title:
Truly Portable MRI for Extremity and Brain Imaging Anywhere & Everywhere
Status:
NOT_YET_RECRUITING
Status Verified Date:
2025-06
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Mobile imaging diagnostic devices are extremely valuable for clinical diagnosis both inside and outside healthcare facilities. However, Magnetic Resonance Imaging (MRI)-the gold standard for diagnosing many neurological and musculoskeletal conditions-is not easily portable. Moreover, due to its high cost (in the million-euro range) and limited availability, the average wait time in Europe for an MRI scan is from several weeks to months.
The NextMRI project aims to take the technical, industrial, and commercial steps required to deploy portable low-field MRI systems in remote and developing regions, rural areas, sporting events, military or medical camps, and home healthcare settings, improving diagnostic capabilities. The specific goals of the NextMRI project are:
1. Expand current low-field MRI technology to brain imaging.
2. Enhance diagnostic accuracy using machine learning.
3. Improve portability and usability for end users.
4. Reduce production costs for broader affordability.
5. Collect clinical evidence through trials to validate medical performance.
6. Develop a sustainable business model for market commercialization.
The NextMRI project aims to take the technical, industrial, and commercial steps required to deploy portable low-field MRI systems in remote and developing regions, rural areas, sporting events, military or medical camps, and home healthcare settings, improving diagnostic capabilities. The specific goals of the NextMRI project are:
1. Expand current low-field MRI technology to brain imaging.
2. Enhance diagnostic accuracy using machine learning.
3. Improve portability and usability for end users.
4. Reduce production costs for broader affordability.
5. Collect clinical evidence through trials to validate medical performance.
6. Develop a sustainable business model for market commercialization.
Detailed Description:
Based on this context, the NextMRI project will carry out a clinical evaluation study involving a multidisciplinary team of radiologists, rheumatologists, physiotherapists, data managers, and physicists. The study will focus on patients with suspected multiple sclerosis (MS). Its main goals are to:
1. Assess the diagnostic value of the low-field MRI prototype.
2. Evaluate usability for end users.
3. Train AI algorithms using deep learning to differentiate between healthy and damaged tissues, thereby aiding radiologists, reducing diagnostic time, and lightening their workload.
Radiologists will first generate structured reports based on standard high-resolution MRI scans. They will then evaluate the low-field MRI images from the NextMRI prototype. The initial high-field MRI reports will serve as the reference standard for assessing performance and training the AI system.
Each patient will undergo two MRI scans on the same day (after providing informed consent): one at the standard 3T MR scan and other at the low-field MRI scan (NextMRI). To prevent bias, both scans will be interpreted by a professional radiologist with an 8-week interval between readings.
A total of 50 patients aged between 18 and 65 years with suspected multiple sclerosis will be included. Patients with any contraindications for high-field MRI will be excluded from the study.
1. Assess the diagnostic value of the low-field MRI prototype.
2. Evaluate usability for end users.
3. Train AI algorithms using deep learning to differentiate between healthy and damaged tissues, thereby aiding radiologists, reducing diagnostic time, and lightening their workload.
Radiologists will first generate structured reports based on standard high-resolution MRI scans. They will then evaluate the low-field MRI images from the NextMRI prototype. The initial high-field MRI reports will serve as the reference standard for assessing performance and training the AI system.
Each patient will undergo two MRI scans on the same day (after providing informed consent): one at the standard 3T MR scan and other at the low-field MRI scan (NextMRI). To prevent bias, both scans will be interpreted by a professional radiologist with an 8-week interval between readings.
A total of 50 patients aged between 18 and 65 years with suspected multiple sclerosis will be included. Patients with any contraindications for high-field MRI will be excluded from the study.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: