Assessment of therapy efficacy using animal models of tumorigenic cancer requires the ability to accurately measure changes in tumor volume over the duration of disease course. In order to be meaningful, in vivo tumor volume measurements by non-invasive techniques must correlate with tumor volume measurements from endpoint histological analysis. Tumor volume is frequently assessed by endpoint histological analyses approximating the tumor volume with geometric primitives such as spheroids and ellipsoids. In this study we investigated alternative techniques for quantifying histological volume measurements of tumors in a xenograft orthotopic mouse model of human glioblastoma multiforme, and compared these to in vivo tumor volume measurements based on magnetic resonance imaging (MRI) data. Two techniques leveraging three-dimensional (3D) image analysis methods were investigated. The first technique involves the reconstruction of a smoothed polygonal model representing the tumor volume from histological section images and is intended for accuracy and qualitative assessment of tumor burden by visualization, while a second technique which approximates the tumor volume as a series of slabs is presented as an abbreviated process intended to produce quantitatively similar volume measurements with a minimum of effort required on behalf of the investigator. New software (QuickVol) designed for use in the first technique, is also discussed. In cases where tumor growth is asymmetric and invasive, we found that 3D analysis techniques using histological section images produced volume measurements more consistent with in vivo volume measurements based on MRI data, than approximation of tumor volume using geometric primitives. Visualizations of the volumes represented by each of these techniques qualitatively support this finding, and suggest that future research using mouse models of glioblastoma multiforme (genetically engineered or xenograft) will benefit from the use of these or similar alternative tumor volume measurement techniques.

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http://dx.doi.org/10.1023/b:neon.0000033364.43142.bfDOI Listing

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