Advancing Portable Brain Imaging: The NextMRI Project's Role in Revolutionizing Diagnostic MRI

NCT ID: NCT07037966

Last Updated: 2025-09-23

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

50 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-10-31

Study Completion Date

2026-09-30

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Multiple Sclerosis

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

All participants receive the same intervention. There's no randomization.-the aim is to evaluate the performance of the device within the same group of patients.
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

The radiologist is assessing the diagnostic outcome without knowledge of the reference scan.

Study Groups

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Patients with Suspected Multiple Sclerosis

A total of 50 patients aged between 18 and 65 years with suspected multiple sclerosis will be scanned using both the 3T MRI and the NextMRI prototype.

Group Type EXPERIMENTAL

MRI

Intervention Type DEVICE

Standard 3T MRI Scan

MRI

Intervention Type DEVICE

Low-field MRI scan using the NextMRI prototype

Interventions

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MRI

Standard 3T MRI Scan

Intervention Type DEVICE

MRI

Low-field MRI scan using the NextMRI prototype

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Patients with suspected multiple sclerosis

Exclusion Criteria

* Any contradictions for high-field MRI
Minimum Eligible Age

18 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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National Research Council, Spain

OTHER_GOV

Sponsor Role collaborator

Instituto de Investigacion Sanitaria La Fe

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Hospital Universitario y Politécnico la Fe

Valencia, Valencia, Spain

Site Status

Countries

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Spain

Central Contacts

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Paula Doria Borrell, PhD

Role: CONTACT

+34629301756

References

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Guallart-Naval T, Algarin JM, Pellicer-Guridi R, Galve F, Vives-Gilabert Y, Bosch R, Pallas E, Gonzalez JM, Rigla JP, Martinez P, Lloris FJ, Borreguero J, Marcos-Perucho A, Negnevitsky V, Marti-Bonmati L, Rios A, Benlloch JM, Alonso J. Portable magnetic resonance imaging of patients indoors, outdoors and at home. Sci Rep. 2022 Jul 30;12(1):13147. doi: 10.1038/s41598-022-17472-w.

Reference Type BACKGROUND
PMID: 35907975 (View on PubMed)

O'Reilly T, Teeuwisse WM, de Gans D, Koolstra K, Webb AG. In vivo 3D brain and extremity MRI at 50 mT using a permanent magnet Halbach array. Magn Reson Med. 2021 Jan;85(1):495-505. doi: 10.1002/mrm.28396. Epub 2020 Jul 5.

Reference Type BACKGROUND
PMID: 32627235 (View on PubMed)

Related Links

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https://nextmri.eu/

Truly portable MRI for extremity and brain imaging anywhere \& everywhere

Other Identifiers

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NextMRI Brain Validation

Identifier Type: -

Identifier Source: org_study_id

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