Automated analysis of small animal PET studies through deformable registration to an atlasReport as inadecuate

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European Journal of Nuclear Medicine and Molecular Imaging

, Volume 39, Issue 11, pp 1807–1820

First Online: 21 July 2012Received: 29 February 2012Accepted: 28 June 2012


PurposeThis work aims to develop a methodology for automated atlas-guided analysis of small animal positron emission tomography PET data through deformable registration to an anatomical mouse model.

MethodsA non-rigid registration technique is used to put into correspondence relevant anatomical regions of rodent CT images from combined PET-CT studies to corresponding CT images of the Digimouse anatomical mouse model. The latter provides a pre-segmented atlas consisting of 21 anatomical regions suitable for automated quantitative analysis. Image registration is performed using a package based on the Insight Toolkit allowing the implementation of various image registration algorithms. The optimal parameters obtained for deformable registration were applied to simulated and experimental mouse PET-CT studies. The accuracy of the image registration procedure was assessed by segmenting mouse CT images into seven regions: brain, lungs, heart, kidneys, bladder, skeleton and the rest of the body. This was accomplished prior to image registration using a semi-automated algorithm. Each mouse segmentation was transformed using the parameters obtained during CT to CT image registration. The resulting segmentation was compared with the original Digimouse atlas to quantify image registration accuracy using established metrics such as the Dice coefficient and Hausdorff distance. PET images were then transformed using the same technique and automated quantitative analysis of tracer uptake performed.

ResultsThe Dice coefficient and Hausdorff distance show fair to excellent agreement and a mean registration mismatch distance of about 6 mm. The results demonstrate good quantification accuracy in most of the regions, especially the brain, but not in the bladder, as expected. Normalized mean activity estimates were preserved between the reference and automated quantification techniques with relative errors below 10 % in most of the organs considered.

ConclusionThe proposed automated quantification technique is reliable, robust and suitable for fast quantification of preclinical PET data in large serial studies.

KeywordsPET-CT Small animals Quantification Deformable registration Atlas  Download fulltext PDF

Author: Daniel F. Gutierrez - Habib Zaidi



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