Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

9.1K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
9.1K
Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

222
Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
222

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Effect of basis choice on quantitative parameter estimation in accelerated subspace reconstructions.

Magnetic resonance letters·2026
Same author

A retrospective cohort study of operated older patients undergoing lung resection after PFT-based versus CPET-based preoperative stratification.

Translational lung cancer research·2026
Same author

Multimodal ultrasound-based morphological differences between symptomatic and asymptomatic carotid web.

Frontiers in neurology·2026
Same author

Multiphysics Analysis and Optimization of a Thin-Film Lithium Niobate Phase Modulator for Fiber-Optic Gyroscopes.

Micromachines·2026
Same author

Hepatocellular Carcinoma Precursor Lesions: From Pathological Basis to Risk Stratification and Precision Intervention.

Journal of hepatocellular carcinoma·2026
Same author

Editorial for "Pre-Radiotherapy Synthetic MRI-Derived Quantitative Heterogeneity and Early Recurrence in Glioblastoma".

Journal of magnetic resonance imaging : JMRI·2026

Related Experiment Video

Updated: Jan 16, 2026

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
08:51

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

9.7K

Rapid whole-brain T2* and susceptibility mapping using 3D multiple overlapping-echo detachment acquisition and

Qinqin Yang1,2, Longkun Chen1, Nuowei Ge1

  • 1Department of Electronic Science, Xiamen University, Xiamen, China.

Magnetic Resonance in Medicine
|October 3, 2025
PubMed
Summary

A new 3D multiple overlapping-echo detachment (3D-MOLED) technique rapidly maps whole-brain T2* and quantitative susceptibility mapping (QSM) with improved motion robustness. This advanced imaging method offers superior performance over conventional 3D gradient-recalled echo (3D-GRE) techniques.

Keywords:
3D imagingMOLEDQSMT2* mappingmodality synthesis

More Related Videos

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
17:16

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

10.8K
High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

13.4K

Related Experiment Videos

Last Updated: Jan 16, 2026

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
08:51

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

9.7K
Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
17:16

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

10.8K
High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

13.4K

Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Physics
  • Neuroimaging

Background:

  • Quantitative susceptibility mapping (QSM) and T2* relaxometry provide valuable insights into brain tissue properties.
  • Conventional MRI techniques for whole-brain T2* and QSM mapping are often limited by long acquisition times and motion sensitivity.
  • Developing rapid and motion-robust imaging methods is crucial for clinical translation and broader application.

Purpose of the Study:

  • To develop and validate a novel 3D multiple overlapping-echo detachment (3D-MOLED) imaging technique.
  • To establish data generation and reconstruction strategies for rapid whole-brain T2* and QSM.
  • To evaluate the performance of 3D-MOLED against conventional 3D gradient-recalled echo (3D-GRE) methods.

Main Methods:

  • Extended MOLED encoding to a 3D multi-shot acquisition combined with dual-echo blip-reversed EPI trains.
  • Employed a deep learning-based missing modality synthesis for generating co-registered multi-parametric templates for Bloch simulations.
  • Utilized a pseudo-3D Bloch simulation to accelerate synthetic data generation for network training and evaluated in healthy and clinical cohorts.

Main Results:

  • 3D-MOLED demonstrated significant improvements in scan speed and motion robustness compared to 3D-GRE.
  • Over 70% of scans in both healthy and clinical cohorts achieved good image quality.
  • The developed deep learning and simulation framework enabled efficient generation of high-quality training data for accurate quantitative mapping.

Conclusions:

  • 3D-MOLED enables simultaneous whole-brain T2* and QSM mapping at 1mm isotropic resolution within 50 seconds.
  • The technique offers superior motion robustness compared to conventional 3D-GRE.
  • 3D-MOLED represents a significant advancement for rapid and reliable quantitative MRI of the brain.