The impact of heterogeneity and uncertainty on prediction of response to therapy using dynamic MRI data
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 0302-9743, Vol: 8149 LNCS, Issue: PART 1, Page: 316-323
2013
- 4Citations
- 30Captures
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Conference Paper Description
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 K with the bolus arrival time as a biomarker. © 2013 Springer-Verlag.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84885744735&origin=inward; http://dx.doi.org/10.1007/978-3-642-40811-3_40; http://www.ncbi.nlm.nih.gov/pubmed/24505681; http://link.springer.com/10.1007/978-3-642-40811-3_40; https://dx.doi.org/10.1007/978-3-642-40811-3_40; https://link.springer.com/chapter/10.1007/978-3-642-40811-3_40
Springer Science and Business Media LLC
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