Aperture NeuroNeurosciencePeer-reviewed journal article
Retrieving fMRI data in real-time: difficulties and pitfalls
Michael LührsiD, Benedikt Andreas PoseriD, Tibor AueriD, Rainer GoebeliD
Abstract
One of the significant challenges in real-time fMRI environments is to ensure that the functional images are exported in real-time. The prerequired ability to reconstruct these images immediately after the acquisition has already been resolved in 2004. Nowadays, more sophisticated sequences allow for higher resolution and faster repetition times and thereby challenging the ability to export this data in real-time. In this article, we tackle the potentially arising problem of sending the reconstructed data from the MRI to an external PC to perform the real-time fMRI analysis. We show that depending on the implementation of the data transfer, long delays can occur that can differ drastically in time and how often they occur. In addition, we propose a solution for SIEMENS MRI devices which was tested and applied already on multiple MRI devices including 3T and 7T machines on different vendor software versions. This new technique can be used as a blueprint that can be directly applied to other manufacturers. We also provide the source code of the described solution and show that the delay in the data transfer can be significantly reduced to a tolerable level using our proposed procedure. Finally, we integrate measurement options for the data transfer times to improve quality measures in real-time fMRI environments (e.g., clinical) that can implement the proposed solution. Efforts should be taken by the real-time community and MRI manufacturers to employ a standardized real-time export e.g., similar to the lab streaming layer which is used as a standard export method in EEG environments.
- assay: imaging
- research focus: benchmarking
- research focus: software / tool
- approach: experimental assay
- Citations
- 2
- FWCI
- 0.17
- Field percentile
- 39th percentile
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Improving the temporal accuracy of functional Magnetic Resonance Imaging
Niels Janssen, Juan A. Hernández-Cabrera, Laura Ezama Foronda·bioRxiv·Sep 5, 2016
- Adaptive and Wireless Recordings of Electrophysiological Signals during Concurrent Magnetic Resonance Imaging
R. Mandal, N. Babaria, … Z. Liu·bioRxiv·Sep 20, 2018
- rt-me-fMRI: A task and resting state dataset for real-time, multi-echo fMRI methods development and validation
Stephan Heunis, Marcel M. Breeuwer, … Albert Pierre Aldenkamp·F1000ResearchPeer-reviewed·Feb 4, 2021
- An optimized framework for simultaneous EEG-fMRI at 7T enabling safe, high-quality human brain imaging with millisecond temporal resolution and sub-millimeter spatial resolution
Cristina Sainz Martinez, Jonathan Wirsich, … João Jorge·bioRxiv·Aug 23, 2024
- A library for fMRI real-time processing systems in python (RTPSpy) with comprehensive online noise reduction, fast and accurate anatomical image processing, and online processing simulation
Masaya Misaki, Jerzy Bodurka, Martin P. Paulus·Frontiers in NeurosciencePeer-reviewed·Mar 11, 2022
- The effects of multi-echo fMRI combination and rapid T2*-mapping on offline and real-time BOLD sensitivity
Stephan Heunis, Marcel M. Breeuwer, … Albert Pierre Aldenkamp·NeuroImagePeer-reviewed·Jun 8, 2021