Literature DB >> 21448940

Automated ischemic lesion detection in a neonatal model of hypoxic ischemic injury.

Nirmalya Ghosh1, Rebecca Recker, Amul Shah, Bir Bhanu, Stephen Ashwal, Andre Obenaus.   

Abstract

PURPOSE: To develop and compare an automated detection system for ischemic lesions in a neonatal model of bilateral carotid artery occlusion with hypoxia (BCAO-H) from T2 weighted MRI (T2WI) to the currently used "gold standard" of manual segmentation.
MATERIALS AND METHODS: Forty-three P10 BCAO-H rat pups and 8 controls underwent T2WI at 1 day and 28 days. A computational imaging method, Hierarchical Region Splitting (HRS), was developed to automatically and rapidly detect and quantify 3D lesion and normal appearing brain matter (NABM) volumes.
RESULTS: HRS quantified lesion and NABM volumes within 15 s in comparison to 3 h for its manual counterpart, with a high correlation for injury (r(2) = 0. 95; P = 8.6 × 10(-7) ) and NABM (r(2) = 0. 92; P = 1.4 × 10(-22) ). Average lesion volumes for mild, moderate, and severe injuries were 3.85%, 28.85%, and 52.98% for HRS and 0.51%, 24.22%, and 48.74% for manual detection. Lesion volumes and locations were similar for both methods (sensitivity: 0.82, specificity: 0.86, and similarity: 1.47).
CONCLUSION: HRS is an accurate, objective, and rapid method to quantify injury evolution in neonatal hypoxic ischemic injury models.
Copyright © 2011 Wiley-Liss, Inc.

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Mesh:

Year:  2011        PMID: 21448940     DOI: 10.1002/jmri.22488

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  13 in total

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6.  Automated detection of brain abnormalities in neonatal hypoxia ischemic injury from MR images.

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10.  Reparative effects of neural stem cells in neonatal rats with hypoxic-ischemic injury are not influenced by host sex.

Authors:  Stephen Ashwal; Nirmalya Ghosh; Christine I Turenius; Melissa Dulcich; Christopher M Denham; Beatriz Tone; Richard Hartman; Evan Y Snyder; Andre Obenaus
Journal:  Pediatr Res       Date:  2014-01-24       Impact factor: 3.756

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