Abstract
To monitor tumor response to neoadjuvant chemotherapy, investigators have begun to employ quantitative physiological parameters available from dynamic contrast enhanced MRI (DCE-MRI). However, most studies track the changes in these parameters obtained from the tumor region of interest (ROI) or histograms, thereby discarding all spatial information on tumor heterogeneity. In this study, we applied a nonrigid registration to longitudinal DCE-MRI data and performed a voxel-by-voxel analysis to examine the ability of early changes in parameters at the voxel level to separate pathologic complete responders (pCR) from non-responders (NR). Twenty-two patients were examined using DCE-MRI pre-, post one cycle, and at the conclusion of all neoadjuvant chemotherapy. The fast exchange regime model (FXR) was applied to both the original and registered DCE-MRI data to estimate tumor-related parameters. The results indicate that compared with the ROI analysis, the voxel-based analysis after longitudinal registration may improve the ability of DCE-MRI to separate complete responders from non-responders after one cycle of therapy when using the FXR model (p = 0.02).
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Li, X. et al. (2012). Early DCE-MRI Changes after Longitudinal Registration May Predict Breast Cancer Response to Neoadjuvant Chemotherapy. In: Dawant, B.M., Christensen, G.E., Fitzpatrick, J.M., Rueckert, D. (eds) Biomedical Image Registration. WBIR 2012. Lecture Notes in Computer Science, vol 7359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31340-0_24
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DOI: https://doi.org/10.1007/978-3-642-31340-0_24
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