The impact of heterogeneity and uncertainty on prediction of response to therapy using dynamic MRI data
Bhushan M, Schnabel JA, Chappell M, Gleeson F, Anderson M, Franklin J, Brady SM, Jenkinson M (2013)
Publication Type: Conference contribution
Publication year: 2013
Journal
Book Volume: 8149 LNCS
Pages Range: 316-323
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: JPN
ISBN: 9783642408106
DOI: 10.1007/978-3-642-40811-3_40
Abstract
A comprehensive framework for predicting response to therapy on the basis of heterogeneity in dceMRI parameter maps is presented. A motion-correction method for dceMRI sequences is extended to incorporate uncertainties in the pharmacokinetic parameter maps using a variational Bayes framework. Simple measures of heterogeneity (with and without uncertainty) in parameter maps for colorectal cancer tumours imaged before therapy are computed, and tested for their ability to distinguish between responders and non-responders to therapy. The statistical analysis demonstrates the importance of using the spatial distribution of parameters, and their uncertainties, when computing heterogeneity measures and using them to predict response on the basis of the pre-therapy scan. The results also demonstrate the benefits of using the ratio of Ktrans with the bolus arrival time as a biomarker. © 2013 Springer-Verlag.
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United Kingdom (GB)How to cite
APA:
Bhushan, M., Schnabel, J.A., Chappell, M., Gleeson, F., Anderson, M., Franklin, J.,... Jenkinson, M. (2013). The impact of heterogeneity and uncertainty on prediction of response to therapy using dynamic MRI data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 316-323). JPN.
MLA:
Bhushan, Manav, et al. "The impact of heterogeneity and uncertainty on prediction of response to therapy using dynamic MRI data." Proceedings of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, JPN 2013. 316-323.
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