Paper
9 March 2011 Developing a tool for the validation of quantitative DCE-MRI
Karin Bol, Joost C. Haeck, Lejla Alic, Monique Bernsen, Marion de Jong, Wiro J. Niessen, Jifke F. Veenland
Author Affiliations +
Abstract
Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is becoming an indispensable tool to non-invasively study tumor characteristics. However, many different DCE-analysis methods are currently being used. To compare and validate different methods, histology is the gold standard. For this purpose, exact co-localization between histology and MRI images is a prerequisite. In this study a methodology is developed to validate DCE-data with histology with an emphasis on correct registration of DCE-MRI and histological data. A pancreatic tumor was grown in a rat model. The tumor was dissected after MR imaging, embedded in paraffin, and cut into thin slices. These slices were stained with haematoxylin and eosin, digitized and stacked in a 3D volume. Next, the 3D histology was registered to ex-vivo SWI-weighted MR images, which in turn were registered to in-vivo SWI and DCE images to achieve correct co-localization. Semi-quantitative and quantitative parameters were calculated. Preliminary results suggest that both pharmacokinetic and heuristic DCE-parameters can discriminate between vital and non-vital tumor regions. The developed method offers the basis for an accurate spatial correlation between DCE-MRI derived parametric maps and histology, and facilitates the evaluation of different DCE-MRI analysis methods.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Karin Bol, Joost C. Haeck, Lejla Alic, Monique Bernsen, Marion de Jong, Wiro J. Niessen, and Jifke F. Veenland "Developing a tool for the validation of quantitative DCE-MRI", Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 79651J (9 March 2011); https://doi.org/10.1117/12.877834
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Tumors

Magnetic resonance imaging

In vivo imaging

Image registration

3D image processing

Temporal resolution

Image segmentation

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