Motion Compensated fMRI for Pre-Surgical Planning in Epilepsy

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Project Summary Epilepsy affects about 1% of people, and one-third of cases do not respond effectively to drug treatment. Patients with drug-resistant epilepsy are candidates for surgical resection of the epileptogenic zone, a potentially curative treatment. Clinical functional MRI plays a critical role in planning for neurosurgery in epilepsy. FMRI provides data to localize eloquent cortex, to assess the risks and benefits of a planned surgical resection, and to allow a resection to be tailored to the individual patient. The primary challenge to acquiring high quality functional MRI is motion of the participant. Motion reduces the temporal signal-to-noise ratio (tSNR) by misaligning the BOLD signal, motion creates spin history artifact, and motion can move parts of the brain out of the imaging field of view. These artifacts in turn lead to both false positive and false negative detections of functional activity, which compromise the fidelity of functional localization. This is usually detected and corrected to the extent possible, by discarding motion corrupted data, and using only motion-free segments. Since sufficient data must be acquired for such an analysis, fMRI acquisitions are designed to acquire redundant data to allow for loss to motion. At our institution, and others, this additional imaging time alone has been estimated to more than double the cost of fMRI imaging studies. The loss of fidelity and increased cost due to motion compromises the utility of the fMRI in planning for surgery. This is especially critical in patients who have difficulty following instructions, such as elderly, ill, or pediatric subjects. There is an unmet need for improved motion monitoring, prospective and retrospective correction for motion for fMRI. To improve the utility and decrease the cost of fMRI, we propose to develop, apply and evaluate novel technology to enable real-time self-navigated motion monitoring and improved correction for fMRI, through the following four specific aims: Aim 1: Develop and evaluate reduction of motion enabled by real-time slice-by-slice motion monitoring during fMRI; Aim 2: Develop and evaluate the reduction of motion artifact from slice by slice retrospective motion correction; Aim 3: Develop and evaluate the reduction of motion artifact from real-time slice by slice prospective motion correction (PMC); Aim 4: Assess the utility of motion monitoring, retrospective motion correction and prospective motion correction for improving functional MRI for planning for epilepsy surgery.