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Simulated field maps for susceptibility artefact correction in interventional MRI
Martin Kochan1, Pankaj Daga, Ninon Burgos
1Centre for Medical Image Computing, University College London, London, UK, m.kochan.12@ucl.ac.uk.
Purpose:
Intraoperative MRI (iMRI) is a powerful modality for acquiring images of the brain to facilitate precise image-guided neurosurgery. Diffusion-weighted MRI (DW-MRI) provides critical information about location, orientation and structure of nerve fibre tracts, but suffers from the "susceptibility artefact" stemming from magnetic field perturbations due to the step change in magnetic susceptibility at air-tissue boundaries in the head. An existing approach to correcting the artefact is to acquire a field map by means of an additional MRI scan. However, to recover true field maps from the acquired field maps near air-tissue boundaries is challenging, and acquired field maps are unavailable in historical MRI data sets. This paper reports a detailed account of our method to simulate field maps from structural MRI scans that was first presented at IPCAI 2014 and provides a thorough experimental and analysis section to quantitatively validate our technique.
Methods:
We perform automatic air-tissue segmentation of intraoperative MRI scans, feed the segmentation into a field map simulation step and apply the acquired and the simulated field maps to correct DW-MRI data sets.
Results:
We report results for 12 patient data sets acquired during anterior temporal lobe resection surgery for the surgical management of focal epilepsy. We find a close agreement between acquired and simulated field maps and observe a statistically significant reduction in the susceptibility artefact in DW-MRI data sets corrected using simulated field maps in the vicinity of the resection. The artefact reduction obtained using acquired field maps remains better than that using the simulated field maps in all evaluated regions of the brain.
Conclusions:
The proposed simulated field maps facilitate susceptibility artefact reduction near the resection. Accurate air-tissue segmentation is key to achieving accurate simulation. The proposed simulation approach is adaptable to different iMRI and neurosurgical applications.
Insights
Simulated field maps reduce susceptibility artifacts in diffusion-weighted MRI during neurosurgery. This method, using structural MRI, aids in precise image-guided surgery by improving image quality near the resection area.
Area of Science:
- Medical Imaging
- Neurosurgery
- Image Processing
Background:
- Intraoperative MRI (iMRI) aids precise image-guided neurosurgery.
- Diffusion-weighted MRI (DW-MRI) is crucial for nerve tract visualization but suffers from susceptibility artifacts near air-tissue boundaries.
- Existing artifact correction methods using field maps are challenging, especially with historical data.
Purpose of the Study:
- To present and validate a method for simulating magnetic field maps from structural MRI scans.
- To assess the effectiveness of simulated field maps in correcting DW-MRI susceptibility artifacts.
- To improve image quality for neurosurgical applications.
Main Methods:
- Automatic air-tissue segmentation of iMRI scans.
- Simulation of magnetic field maps using segmented structural MRI data.
- Application of both acquired and simulated field maps for DW-MRI artifact correction.
Main Results:
- Close agreement observed between acquired and simulated field maps.
- Statistically significant reduction in susceptibility artifacts in DW-MRI data corrected with simulated field maps near the resection.
- Acquired field maps provided superior artifact reduction across all brain regions evaluated.
Conclusions:
- Simulated field maps effectively reduce susceptibility artifacts, particularly near surgical resection sites.
- Accurate air-tissue segmentation is critical for successful field map simulation.
- The simulation technique is adaptable for various iMRI and neurosurgical procedures.
