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A framework for validating open-source pulse sequences.

Gehua Tong1, Andreia S Gaspar2, Enlin Qian1

  • 1Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, USA; Columbia Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, USA.

Magnetic Resonance Imaging
|December 3, 2021
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Summary
This summary is machine-generated.

A new framework enhances open-source MRI pulse sequence usability and repeatability. Implemented Inversion Recovery Spin Echo (IRSE) and Turbo Spin Echo (TSE) sequences demonstrated reliable performance and passed key tests.

Keywords:
Pulse sequence programmingPulse sequence simulationRepeatabilityReproducible research

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Open-Source Software Development
  • Medical Imaging Physics

Background:

  • Open-source pulse sequences offer transparency but lack standardized testing and sharing frameworks.
  • Ensuring usability and repeatability of open-source MRI sequences is crucial for widespread adoption.

Purpose of the Study:

  • To propose and demonstrate a framework for testing, documenting, and sharing open-source MRI pulse sequences.
  • To implement and validate Inversion Recovery Spin Echo (IRSE) and Turbo Spin Echo (TSE) sequences using PyPulseq within this framework.

Main Methods:

  • Implemented IRSE and TSE sequences using PyPulseq on a 3T scanner.
  • Utilized ACR and ISMRM/NIST phantoms for qualitative imaging and quantitative T1/T2 mapping.
  • Assessed sequence performance against vendor counterparts and reference values, including ACR accreditation tests and scanner safety checks.

Main Results:

  • Qualitative imaging showed high agreement with vendor sequences (SSIM 0.810 for IRSE, 0.826 for TSE).
  • Sequences passed 5/7 ACR tests, comparable to vendor sequences; R² values were 0.9946 for IRSE T1 and 0.9331 for TSE T2 mapping.
  • All sequences passed safety checks and were successfully shared on GitHub with comprehensive documentation, including cross-site validation on a 1.5T scanner.

Conclusions:

  • The proposed framework effectively enhances the usability, repeatability, and shareability of open-source MRI pulse sequences.
  • Open-source sequences developed within this framework demonstrate robust performance suitable for clinical applications and research.
  • Standardized documentation and sharing facilitate broader accessibility and validation of open-source MRI technologies.