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Related Concept Videos

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A pulse is a short burst of radio waves distributed over a range of frequencies that simultaneously excites all the nuclei in the sample. Upon passing a radio frequency pulse along the x-axis, the nuclei absorb energy corresponding to their Larmor frequencies and achieve resonance. This shifts the net magnetization vector from the z-axis toward the transverse plane. This angle of rotation of the magnetization vector, or the flip angle, is proportional to the duration and intensity of the pulse.
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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...
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Open-source magnetic resonance imaging acquisition: Data and documentation for two validated pulse sequences.

Gehua Tong1,2, Andreia S Gaspar3, Enlin Qian1,2

  • 1Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, USA.

Data in Brief
|April 18, 2022
PubMed
Summary
This summary is machine-generated.

This study presents open-source Magnetic Resonance Imaging (MRI) data and code for T1/T2 mapping. The dataset aids in validating and sharing MRI pulse sequences across research sites.

Keywords:
MRI simulationPulse sequence programmingRepeatabilityReproducible researchT1/T2 mapping

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Area of Science:

  • Medical Imaging
  • Biophysics

Background:

  • Open-source Magnetic Resonance Imaging (MRI) pulse sequences facilitate research reproducibility and data sharing.
  • Standardized documentation and sharing of pulse sequences are crucial for multi-site validation.

Purpose of the Study:

  • To present a dataset of raw and simulated MRI data, including T1/T2 relaxation maps.
  • To provide associated Pulseq sequence files, implementation, and analysis scripts.
  • To enable validation of MRI pulse sequences and demonstrate customizable acquisition scripts.

Main Methods:

  • Acquired real MRI data on 3T Siemens Prisma Fit and 1.5T Siemens Aera using the Pulseq platform.
  • Generated in silico data using the Virtual Scanner simulation module.
  • Included sequence implementation and reconstruction/analysis scripts using PyPulseq.

Main Results:

  • Provided quantitative longitudinal and transverse relaxation times (T1/T2) maps.
  • Dataset includes raw data, simulated images, and phantom images.
  • Associated code for sequence implementation and analysis is available.

Conclusions:

  • The dataset and code support validation of open-source MRI pulse sequences at different research sites.
  • Offers guidelines for documenting and sharing open-source pulse sequences.
  • Demonstrates practical, customizable acquisition scripts using PyPulseq.