A Semiautomated Method for Measuring Brain Infarct Volume
Raymond A. Swanson, Matthew T. Morton, George Tsao-Wu, Robert A. Savalos, Charisse L. Davidson, Frank R. Sharp
Abstract
Raymond A. Swanson, Matthew T. Morton, George Tsao-Wu, Robert A. Savalos, Charisse L. Davidson, Frank R. Sharp
Abstract
An accurate, reproducible method for determining the infarct volumes of gray matter structures is presented for use with presently available image analysis systems. Areas of stained sections with optical densities above that of a threshold value are automatically recognized and measured. This eliminates the potential error and bias inherent in manually delineating infarcted regions. Moreover, the volume of surviving normal gray matter is determined rather than that of the infarct. This approach minimizes the error that is introduced by edema, which distorts and enlarges the infarcted tissue and surrounding white matter.
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An accurate, reproducible method for determining the infarct volumes of gray matter structures is presented for use with presently available image analysis systems. Areas of stained sections with optical densities above that of a threshold value are automatically recognized and measured. This eliminates the potential error and bias inherent in manually delineating infarcted regions. Moreover, the volume of surviving normal gray matter is determined rather than that of the infarct. This approach minimizes the error that is introduced by edema, which distorts and enlarges the infarcted tissue and surrounding white matter.
Key concepts: White matter, Gray (unit), Volume (thermodynamics), Brain tissue, Brain edema, Nuclear medicine, Biomedical engineering, Computer science