Harmonizing functional MRI with open-source data acquisition and reconstruction

In principle, pooling functional MRI data across different sites and points in time should allow for increased statistical power, provided that the imaging experiment can be conducted in a known and reproducible way. While post-processing attempts to correct for ‘site’ variance have been somewhat successful, it would be better to control for potential differences (e.g., vendor, scanner model, scanner software) during the acquisition itself. Historically this has been a challenge, as the details of the vendor-provided fMRI acquisition and reconstruction software are generally not known.

The researcher can in principle implement the imaging protocol themselves using each vendor’s pulse sequence programming environment, but this is a technically difficult and time-consuming task. Existing multi-site studies have therefore invested significant resources into making the fMRI protocols on different systems as similar as possible and maintaining them across scanner software upgrades. However, even then the protocols can often only be ‘harmonized’ with respect to high-level sequence parameters such as FOV, matrix size, and net acceleration factor; subtle but potentially important differences in, e.g., details of sequence timing or RF and gradient waveform shapes, are often not known to the researchers or are beyond their control.

In this talk we will discuss open-source fMRI approaches, and describe a fully vendor-agnostic and portable fMRI protocol that ensures identical sequence execution and image reconstruction across different scanners, and across scanner software upgrades. The acquisition sequence is defined in simple human-readable text files, and sequence execution on real hardware is made possible by openly available sequence-agnostic interpreters. We believe this framework will enable reproducible, truly harmonized multi-site and longitudinal functional studies.