Open-source magnetic resonance imaging acquisition: Data and documentation for two validated pulse sequences

Gehua Tong; Andreia S Gaspar; Enlin Qian; Keerthi Sravan Ravi; John Thomas Vaughan; Rita G Nunes; Sairam Geethanath

doi:10.1016/j.dib.2022.108105

Open-source magnetic resonance imaging acquisition: Data and documentation for two validated pulse sequences

Data Brief. 2022 Mar 28:42:108105. doi: 10.1016/j.dib.2022.108105. eCollection 2022 Jun.

Authors

Gehua Tong^{1

2}, Andreia S Gaspar³, Enlin Qian^{1

2}, Keerthi Sravan Ravi^{1

2}, John Thomas Vaughan^{1

2

4}, Rita G Nunes³, Sairam Geethanath²

Affiliations

¹ Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, USA.
² Columbia Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, USA.
³ Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
⁴ Department of Radiology, Columbia University Irving Medical Center, Columbia University in the City of New York, New York, NY, USA.

Abstract

Raw data, simulated and acquired phantom images, and quantitative longitudinal and transverse relaxation times (T₁/T₂) maps from two open-source Magnetic Resonance Imaging (MRI) pulse sequences are presented in this dataset along with corresponding ".seq" files, sequence implementation scripts, and reconstruction/analysis scripts [1]. Real MRI data were collected from a 3T Siemens Prisma Fit and a 1.5T Siemens Aera via the Pulseq open-source MR sequence platform, and corresponding in silico data were generated using the simulation module of Virtual Scanner [2]. This dataset and its associated code can be used to validate the pipeline for using the same pulse sequences at other research sites using Pulseq, to provide guidelines for documenting and sharing open-source pulse sequences in general, and to demonstrate practical, customizable acquisition scripts using the PyPulseq library.

Keywords: MRI simulation; Pulse sequence programming; Repeatability; Reproducible research; T1/T2 mapping.