23 research outputs found

    Multimodality imaging for repaired tetralogy of Fallot

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    Despite complete repair at an optimal time in the current era, almost all patients with tetralogy of Fallot will have residual anatomic and hemodynamic sequelae, which make ongoing surveillance of paramount importance. Echocardiography suffices surveillance matrix in most pre-operative cases unless there is a specific question about coronary artery anomaly or branch pulmonary arteries when cardiac catheterization or computed tomography scan can be extremely helpful. For long-term follow-up of repaired tetralogy of Fallot patients, several diagnostic/imaging monitoring modalities are available; however, no single modality is perfect in terms of obtaining all the necessary information. A multimodality approach is suggested for long-term surveillance where a diagnostic test is selected based on the clinical circumstances/questions raised and institutional preference/expertise

    Enhanced co-registration methods to improve intracranial electrode contact localization

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    Background: Electrode contact locations are important when planning tailored brain surgeries to identify pathological tissue targeted for resection and conversely avoid eloquent tissue. Current methods employ trained experts to use neuroimaging scans that are manually co-registered and localize contacts within ~2 mm. Yet, the state of the art is limited by either the expertise needed for each type of intracranial electrode or the inter-modality co-registration which increases error, reducing accuracy. Patients often have a variety of strips, grids and depths implanted; therefore, it is cumbersome and time-consuming to apply separate localization methods for each type of electrode, requiring expertise across different approaches. New method: To overcome these limitations, a computational method was developed by separately registering an implant magnetic resonance image (MRI) and implant computed tomography image (CT) to the pre-implant MRI, then calculating an iterative closest point transformation using the contact locations extracted from the signal voids as ground truth. Results: The implant MRI is robustly co-registered to the pre-implant MRI with a boundary-based registration algorithm. By extracting and utilizing ‘signal voids’ (the metal induced artifacts from the implant MRI) as electrode fiducials, the novel method is an all-in-one approach for all types of intracranial electrodes while eliminating inter-modality co-registration errors. Comparison with existing methods: The distance between each electrode centroid and the brain's surface was measured, for the proposed method as well as the state of the art method using two available software packages, SPM 12 and FSL 4.1. The method presented here achieves the smallest distances to the brain's surface for all strip and grid type electrodes, i.e. contacts designed to rest directly on the brain surface. Conclusion: We use one of the largest reported sample sizes in localization studies to validate this novel method for localizing different kinds of intracranial electrodes including grids, strips and depth electrodes. Keywords: MRI, ECoG, Epilepsy, Localization, Grid, Strip, Dept
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