This dataset contains all MRI phantom data discussed in the related publication as well as the python scripts used to analyse them. The format is DICOM files, where institution names and adresses have been anonymized.

Abstract Introduction: As there is an increasing number of multicentre lung imaging studies with MRI in patients, dedicated reference phantoms are required to allow for the assessment and comparison of image quality in multi-vendor and multi-centre environments. However, appropriate phantoms for this purpose are so far not available commercially. It was therefore the purpose of this project to design and evaluate a cost-effective and simple to use reference phantom which addresses the specific requirements for imaging the lungs with MRI.

Methods: We designed and employed a cost-effective and simple to use reference phantom specifically for the demands of chest MRI, simulating 4 compartments (lung, blood, muscle and fat) which reflect the specific conditions in proton-MRI of the chest. Multiple phantom instances were produced and measured at 15 sites using a complete proton-MRI protocol designed for an in vivo COPD study at intervals over the course of the study. Measures of signal- and contrast-to-noise ratio, as well as structure and edge depiction were extracted from conventionally acquired images using software written for this purpose.

Results: For the signal to noise ratio, low (short-term) intra-scanner variability was found with, 4.5% in the lung compartment, 4.0% for blood, 3.3% for muscle and 3.7% for fat. The inter-scanner variability was substantially higher, with 41%, 32% 27% and 32% for the same order of compartments. In addition, measures of structure and edge depiction were found to both vary significantly among several scanner types and among scanners of the same model which were equipped with different gradient systems.

Conclusion: The described reference phantom detected substantial inter-scanner variability in a current multicentre proton MRI study of the lung. Accordingly, the use of an appropriate reference phantom is advised and the extent of variability in image quality should be considered when interpreting results of such imaging studies.

Siemens Syngo MR, VB17; VB19; VD13; VE11

Python, 2.7+

Each zip archive contains multiple phantom measurements for one site performed using one phantom instance. Site13 was the scanner used for reference measurements and thus contains measurements from multiple instances.

Naming schemes for DICOM files vary between sites but are largely irrelevant since analysis is based on DICOM headers only.

The archives also contain .npz archives and .txt summaries as generated by the python scripts, containing analysis results.