iclinfmri software for integrating functional mri techniques in presurgical mapping and clinical studies
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2018
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Abstract
Task-evoked and resting-state (rs) functional magnetic resonance imaging (fMRI) techniques have been applied to the clinical management of neurological diseases, exemplified by presurgical localization of eloquent cortex, to assist neurosurgeons in maximizing resection while preserving brain functions. In addition, recent studies have recommended incorporating cerebrovascular reactivity (CVR) imaging into clinical fMRI to evaluate the risk of lesion-induced neurovascular uncoupling (NVU). Although each of these imaging techniques possesses its own advantage for presurgical mapping, a specialized clinical software that integrates the three complementary techniques and promptly outputs the analyzed results to radiology and surgical navigation systems in a clinical format is still lacking. We developed the Integrated fMRI for Clinical Research (IClinfMRI) software to facilitate these needs. Beyond the independent processing of task-fMRI, rs-fMRI, and CVR mapping, IClinfMRI encompasses three unique functions: (1) supporting the interactive rs-fMRI mapping while visualizing task-fMRI results (or results from published meta-analysis) as a guidance map, (2) indicating/visualizing the NVU potential on analyzed fMRI maps, and (3) exporting these advanced mapping results in a Digital Imaging and Communications in Medicine (DICOM) format that are ready to export to a picture archiving and communication system (PACS) and a surgical navigation system. In summary, IClinfMRI has the merits of efficiently translating and integrating state-of-the-art imaging techniques for presurgical functional mapping and clinical fMRI studies.
| Reference Key |
hsu2018frontiersiclinfmri
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| Authors | ;Ai-Ling Hsu;Ai-Ling Hsu;Ping Hou;Jason M. Johnson;Changwei W. Wu;Kyle R. Noll;Sujit S. Prabhu;Sherise D. Ferguson;Vinodh A. Kumar;Donald F. Schomer;John D. Hazle;Jyh-Horng Chen;Ho-Ling Liu |
| Journal | Nucleic Acids Research |
| Year | 2018 |
| DOI |
10.3389/fninf.2018.00011
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| URL | |
| Keywords |
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