Semi-automated method for estimating lesion volumes

Hyun Joo Park, Andre G. Machado, Jessica Cooperrider, Havan Truong-Furmaga, Matthew Johnson, Vibhuti Krishna, Zhihong Chen, John T. Gale

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Accurately measuring the volume of tissue damage in experimental lesion models is crucial to adequately control for the extent and location of the lesion, variables that can dramatically bias the outcome of preclinical studies. Many of the current commonly used techniques for this assessment, such as measuring the lesion volume with primitive software macros and plotting the lesion location manually using atlases, are time-consuming and offer limited precision. Here we present an easy to use semi-automated computational method for determining lesion volume and location, designed to increase precision and reduce the manual labor required. We compared this novel method to currently used methods and demonstrate that this tool is comparable or superior to current techniques in terms of precision and has distinct advantages with respect to user interface, labor intensiveness and quality of data presentation.

Original languageEnglish (US)
Pages (from-to)76-83
Number of pages8
JournalJournal of Neuroscience Methods
Volume213
Issue number1
DOIs
StatePublished - Feb 5 2013

Bibliographical note

Funding Information:
The research was funded by an NIH grant : 5R01HD061363 .

Keywords

  • Cell death
  • Computational method
  • Lesion estimation
  • Lesion volume
  • Stroke
  • Traumatic brain injury

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