These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Automated ischemic lesion detection in a neonatal model of hypoxic ischemic injury.
    Author: Ghosh N, Recker R, Shah A, Bhanu B, Ashwal S, Obenaus A.
    Journal: J Magn Reson Imaging; 2011 Apr; 33(4):772-81. PubMed ID: 21448940.
    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.
    [Abstract] [Full Text] [Related] [New Search]