All experimental models of traumatic brain injury (TBI) result in a progressive loss of brain tissue. The extent of tissue loss reflects the injury severity and can be measured to evaluate the potential neuroprotective effect of experimental treatments. Quantitation of tissue volumes is commonly performed using evenly spaced brain sections stained using routine histochemical methods and digitally captured. The brain tissue areas are then measured and the corresponding volumes are calculated using the distance between the sections. Measurements of areas are usually performed using a general purpose image analysis software and the results are then transferred to another program for volume calculations. To facilitate the measurement of brain tissue loss we developed novel algorithms which automatically separate the areas of brain tissue from the surrounding image background and identify the ventricles. We implemented these new algorithms by creating a new computer program (SectionToVolume) which also has functions for image organization, image adjustments and volume calculations. We analyzed brain sections from mice subjected to severe focal TBI using both SectionToVolume and ImageJ, a commonly used image analysis program. The volume measurements made by the two programs were highly correlated and analysis using SectionToVolume required considerably less time. The inter-rater reliability was high. Given the extensive use of brain tissue loss measurements in TBI research, SectionToVolume will likely be a useful tool for TBI research. We therefore provide both the source code and the program as attachments to this article.
Keywords: image analysis; tissue loss; traumatic brain injury.