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Volume Reconstruction Techniques Improve the Correlation Between
Histological and in vivo Tumor Volume Measurements in Mouse Models of
Human Gliomas
Karl F. Schmidt,
Mateo Ziu, Nils Ole Schmidt, Pramil Vaghasia, Theresa
G. Cargioli, Sameer Doshi, Mitchell S. Albert, Peter McL. Black, Rona S. Carroll,
Yanping Sun
Department
of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA;
Present address: Center for Comparative NeuroImaging (CCNI), University of
Massachusetts Medical School, Worcester, USA (K.F.S.); Department of
Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA,
USA (M.Z.,
N.O.S., Th.G.C, P.McL.B., R.S.C.); Department of Radiology, Brigham and Women's Hospital,
Harvard Medical School Boston, USA (P.V., S.D., M.S.A., Y.S.)
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.
Keywords: 3D reconstruction, brain tumor, glioma, MRI, tumor volume measurement
Copyright
©
2004 Kluwer Academic Publishers.
All rights reserved
Source: http://ipsapp009.kluweronline.com/IPS/content/ext/x/J/5042/I/119/A/3/abstract.htm
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