2 July 2015 Assessing the accuracy and reproducibility of modality independent elastography in a murine model of breast cancer
Jared A. Weis, Katelyn M. Flint, Violeta Sanchez, Thomas E. Yankeelov, Michael I. Miga
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Abstract
Cancer progression has been linked to mechanics. Therefore, there has been recent interest in developing noninvasive imaging tools for cancer assessment that are sensitive to changes in tissue mechanical properties. We have developed one such method, modality independent elastography (MIE), that estimates the relative elastic properties of tissue by fitting anatomical image volumes acquired before and after the application of compression to biomechanical models. The aim of this study was to assess the accuracy and reproducibility of the method using phantoms and a murine breast cancer model. Magnetic resonance imaging data were acquired, and the MIE method was used to estimate relative volumetric stiffness. Accuracy was assessed using phantom data by comparing to gold-standard mechanical testing of elasticity ratios. Validation error was <12%. Reproducibility analysis was performed on animal data, and within-subject coefficients of variation ranged from 2 to 13% at the bulk level and 32% at the voxel level. To our knowledge, this is the first study to assess the reproducibility of an elasticity imaging metric in a preclinical cancer model. Our results suggest that the MIE method can reproducibly generate accurate estimates of the relative mechanical stiffness and provide guidance on the degree of change needed in order to declare biological changes rather than experimental error in future therapeutic studies.
© 2015 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2015/$25.00 © 2015 SPIE
Jared A. Weis, Katelyn M. Flint, Violeta Sanchez, Thomas E. Yankeelov, and Michael I. Miga "Assessing the accuracy and reproducibility of modality independent elastography in a murine model of breast cancer," Journal of Medical Imaging 2(3), 036001 (2 July 2015). https://doi.org/10.1117/1.JMI.2.3.036001
Published: 2 July 2015
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Cited by 10 scholarly publications.
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KEYWORDS
Tumors

Elastography

Magnetic resonance imaging

Tissues

Cancer

Tumor growth modeling

Breast cancer

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