Portable MRI Scanner Increases Access to Neuroimaging
|
By MedImaging International staff writers Posted on 23 Dec 2020 |

Image: A low-cost, low-power brain MRI device could scan brains at the POC (Photo courtesy of MGH)
A portable magnetic resonance imaging (MRI) scanner based on a compact, lightweight, permanent magnet could expand enable point-of-care (POC) diagnostics for neurological emergencies.
Developed at Massachusetts General Hospital (MGH; Boston, USA) and Harvard Medical School (HMS; Boston, MA, USA), the prototype brain MRI system uses an array of neodymium (NdFeB) rare-earth magnets that generate a low (80 mT) magnetic field with a built-in readout gradient. The configuration reduces reliance on high-power gradient drivers, lowers the overall requirements for power and cooling, and reduces acoustic noise. Imperfections in the encoding fields are mitigated with a generalized iterative image reconstruction technique.
A Halbach cylinder design creates a transverse field inside the magnet and zero field outside the magnet that results in a minimal stray field that requires neither cryogenics nor external power; the intrinsic self-shielding is thus ideal for portable applications where stray fields could pose safety hazards. The scanner can generate T1-weighted, T2-weighted, and proton density-weighted brain images with a spatial resolution of 2.2 × 1.3 × 6.8 mm3. The study was published on November 23, 2020, in Nature Biomedical Engineering.
“Although the scanner’s spatial resolution and sensitivity are both lower than that of a high-field MRI, its performance is sufficient to detect and characterize serious intracranial processes, such as hemorrhage, hydrocephalus, infarction, and mass lesions,” concluded lead author Clarissa Cooley, PhD, of the MGH department of radiology, and colleagues. “Our preliminary work also suggests that diffusion-weighted imaging, which is critical to applications such as acute stroke detection, should also be possible.”
A neodymium rare-earth magnet is made from an alloy of neodymium, iron, and boron formed into a tetragonal crystalline structure that has a magnetic energy value about 18 times greater than ferrite magnets (by volume) and 12 times (by mass). The strength and magnetic field homogeneity of such neodymium magnets has led to their introduction in MRI scanners as an alternative to superconducting magnets.
Related Links:
Massachusetts General Hospital
Harvard Medical School
Developed at Massachusetts General Hospital (MGH; Boston, USA) and Harvard Medical School (HMS; Boston, MA, USA), the prototype brain MRI system uses an array of neodymium (NdFeB) rare-earth magnets that generate a low (80 mT) magnetic field with a built-in readout gradient. The configuration reduces reliance on high-power gradient drivers, lowers the overall requirements for power and cooling, and reduces acoustic noise. Imperfections in the encoding fields are mitigated with a generalized iterative image reconstruction technique.
A Halbach cylinder design creates a transverse field inside the magnet and zero field outside the magnet that results in a minimal stray field that requires neither cryogenics nor external power; the intrinsic self-shielding is thus ideal for portable applications where stray fields could pose safety hazards. The scanner can generate T1-weighted, T2-weighted, and proton density-weighted brain images with a spatial resolution of 2.2 × 1.3 × 6.8 mm3. The study was published on November 23, 2020, in Nature Biomedical Engineering.
“Although the scanner’s spatial resolution and sensitivity are both lower than that of a high-field MRI, its performance is sufficient to detect and characterize serious intracranial processes, such as hemorrhage, hydrocephalus, infarction, and mass lesions,” concluded lead author Clarissa Cooley, PhD, of the MGH department of radiology, and colleagues. “Our preliminary work also suggests that diffusion-weighted imaging, which is critical to applications such as acute stroke detection, should also be possible.”
A neodymium rare-earth magnet is made from an alloy of neodymium, iron, and boron formed into a tetragonal crystalline structure that has a magnetic energy value about 18 times greater than ferrite magnets (by volume) and 12 times (by mass). The strength and magnetic field homogeneity of such neodymium magnets has led to their introduction in MRI scanners as an alternative to superconducting magnets.
Related Links:
Massachusetts General Hospital
Harvard Medical School
Latest MRI News
- Advanced MRI Reveals Structural Brain Changes Linked to Better Cognitive Health
- Cardiac MRI Detects Hidden Heart Dysfunction After Heart Attack
- AI Tool Reveals Cortical Lesions on Standard MRI in Multiple Sclerosis
- AI Reconstruction Tool Speeds Dynamic Breast MRI and Improves Cancer Detection
- International Study Assesses AI for Prostate Cancer MRI Interpretation
- AI Approach Could Shorten Advanced Brain MRI Scans by Up to 90%
- Cardiac MRI Measure Improves Risk Prediction in Tricuspid Regurgitation
- AI System Improves Accuracy of Cardiac MRI Interpretation
- Deep Learning Model Predicts Alzheimer’s Disease Outcomes from Baseline MRI
- Blood-Brain Barrier Imaging Adds Risk Insight to Standard Stroke MRI
- AI Body Composition MRI Analysis Predicts Cardiometabolic Disease Risk
- AI MRI Tool Quantifies Muscle Fat to Assess Cardiometabolic Risk
- Advanced MRI Visualizes CSF Motion Changes After Mild Traumatic Brain Injury
- MRI Tool Enables Long-Term Tracking of Transplanted Cardiac Cells
- MRI-Based AI Tool Supports Differentiation of Parkinsonian Syndromes
- MRI-Derived Biomarker Improves Risk Stratification in Glioblastoma
Channels
Radiography
view channel
Computational X-Ray Technique Enables High-Resolution, Low-Dose Radiography
Reducing radiation in medical X-ray imaging remains a persistent challenge because dose reductions often degrade spatial resolution and diagnostic confidence. This is especially critical in pediatrics,... Read more
AI Tool Predicts Five-Year Breast Cancer Risk from Mammograms
Breast cancer risk assessment during routine screening is difficult because many women who develop the disease have no known genetic mutations or family history. Static risk tools provide limited discrimination... Read moreUltrasound
view channel
Simple 2D Ultrasound Tool Accurately Estimates Placental Volume
Stillbirth remains a major cause of perinatal loss, with about 21,000 cases annually in the United States. Although placental abnormalities are linked to adverse pregnancy outcomes, routine monitoring... Read more
Portable 3D Ultrasound System Enables Reproducible Breast Cancer Monitoring
Breast cancer can develop between annual mammograms, and these interval cancers account for 20% to 30% of cases and tend to be more aggressive. The challenge is pronounced in people with dense breast tissue.... Read moreNuclear Medicine
view channel
Radiotherapy Professionals Embrace AI as a Clinical Support Tool
Radiotherapy planning requires precise identification of organs at risk near a tumor, but manual contouring is repetitive and time-consuming, often delaying plan completion and straining specialist capacity.... Read more
Second PSMA PET Identifies Disease in More Than Half of Negative Cases
Biochemical recurrence of prostate cancer after prostatectomy or radiation can be difficult to localize when imaging is negative. Uncertain disease sites may delay salvage therapy and expose patients to... Read moreGeneral/Advanced Imaging
view channel
New PE-RADS Framework Standardizes Pulmonary Embolism Imaging Reports
Pulmonary embolism is a sudden blockage of the lung’s blood vessels that reduces pulmonary blood flow, can strain the right hear,t and may be fatal if untreated. Patients often present with shortness of... Read more
Virtual Staining Technique Creates Histology Images from CT Data
Pulmonary hypertension, a disorder marked by pathological remodeling of the pulmonary vessels, often requires detailed histologic assessment. Yet routine pathology remains anchored in labor‑intensive,... Read more
CT-Derived Biomarker Predicts Outcomes in Gastric Cancer
Gastric cancer, also known as stomach cancer, is the fifth most common malignancy worldwide and often shows heterogeneous outcomes even within the same stage. Prognostic estimates typically rely on tumor-centric... Read more
AI Tool Enhances Response Assessment and Survival Prediction in Pleural Mesothelioma
Pleural mesothelioma, a cancer that grows as a thin, irregular layer along the lung wall, is difficult to measure on imaging. Clinicians rely on diameter-based Response Evaluation Criteria in Solid Tumors... Read moreImaging IT
view channel
Ambient AI Reporting Platform Streamlines Radiology Reporting
Radiology departments face growing imaging volumes and staffing shortages, creating reporting bottlenecks and pressure to maintain turnaround times. Conventional dictation tools document findings after... Read more
Interactive AI Tool Supports Explainable Lung Nodule Assessment
Lung cancer is a leading cause of cancer mortality, and timely characterization of pulmonary nodules on chest computed tomography (CT) is essential for directing care. Interpreting nodule morphology demands... Read more
Breast Imaging Software Enhances Visualization and Tissue Characterization in Challenging Cases
Breast imaging can be particularly challenging in cases involving small breasts or implants, where image reconstruction and tissue characterization may be limited. Clinicians also need reproducible analysis... Read moreIndustry News
view channel
GE HealthCare Showcases AI-Enabled Nuclear Medicine Portfolio at SNMMI 2026
Nuclear medicine is expanding rapidly as health systems adopt theranostics and broaden access to radiopharmaceuticals, increasing demand for scalable operations and consistent diagnostic confidence.... Read more
GE HealthCare Highlights AI-Supported Radiation Therapy Tools at ESTRO 2026
At the European Society for Radiotherapy and Oncology (ESTRO) 2026 Congress in Stockholm, GE HealthCare is highlighting Intelligent Radiation Therapy (iRT), MIM Software innovations, and BK Medical surgical... Read more







