| A fast and efficient method to compensate for brain shift for tumor resection therapies measured between preoperative and postoperative tomograms. | |
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MedLine Citation:
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PMID: 20172796 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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In this paper, an efficient paradigm is presented to correct for brain shift during tumor resection therapies. For this study, high resolution preoperative (pre-op) and postoperative (post-op) MR images were acquired for eight in vivo patients, and surface/subsurface shift was identified by manual identification of homologous points between the pre-op and immediate post-op tomograms. Cortical surface deformation data were then used to drive an inverse problem framework. The manually identified subsurface deformations served as a comparison toward validation. The proposed framework recaptured 85% of the mean subsurface shift. This translated to a subsurface shift error of 0.4 +/- 0.4 mm for a measured shift of 3.1 +/- 0.6 mm. The patient's pre-op tomograms were also deformed volumetrically using displacements predicted by the model. Results presented allow a preliminary evaluation of correction both quantitatively and visually. While intraoperative (intra-op) MR imaging data would be optimal, the extent of shift measured from pre- to post-op MR was comparable to clinical conditions. This study demonstrates the accuracy of the proposed framework in predicting full-volume displacements from sparse shift measurements. It also shows that the proposed framework can be extended and used to update pre-op images on a time scale that is compatible with surgery. |
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Authors:
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Prashanth Dumpuri; Reid C Thompson; Aize Cao; Siyi Ding; Ishita Garg; Benoit M Dawant; Michael I Miga |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural Date: 2010-02-17 |
Journal Detail:
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Title: IEEE transactions on bio-medical engineering Volume: 57 ISSN: 1558-2531 ISO Abbreviation: IEEE Trans Biomed Eng Publication Date: 2010 Jun |
Date Detail:
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Created Date: 2010-07-27 Completed Date: 2010-12-15 Revised Date: 2011-11-18 |
Medline Journal Info:
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Nlm Unique ID: 0012737 Medline TA: IEEE Trans Biomed Eng Country: United States |
Other Details:
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Languages: eng Pagination: 1285-96 Citation Subset: IM |
Affiliation:
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Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA. prashanth.dumpuri@vanderbilt.edu |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Artifacts* Brain Neoplasms / pathology*, surgery* Female Humans Image Enhancement / methods Image Interpretation, Computer-Assisted / methods* Magnetic Resonance Imaging / methods* Male Middle Aged Neurosurgical Procedures / methods Pattern Recognition, Automated / methods Postoperative Care / methods Preoperative Care / methods Reproducibility of Results Sensitivity and Specificity Subtraction Technique* Surgery, Computer-Assisted / methods* |
| Grant Support | |
ID/Acronym/Agency:
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R01 NS049251-01A1/NS/NINDS NIH HHS; R01 NS049251-04A1/NS/NINDS NIH HHS; R01 NS049251-07/NS/NINDS NIH HHS |
| Comments/Corrections | |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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