Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement.
AuthorsBuonaccorsi, Giovanni A
O'Connor, James P B
Jayson, Gordon C
Parker, Geoff J M
AffiliationDepartment of Imaging Science and Biomedical Engineering, Stopford Building, Oxford Road, University of Manchester, and Cancer Research UK Department of Medical Oncology, Christie Hospital NHS Trust, UK. email@example.com
MetadataShow full item record
AbstractRATIONALE AND OBJECTIVES: The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. MATERIALS AND METHODS: Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. RESULTS: Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. CONCLUSION: When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.
CitationComparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement. 2006, 13 (9):1112-23 Acad Radiol
- Tracer kinetic model-driven registration for dynamic contrast enhanced MRI time series.
- Authors: Buonaccorsi GA, Roberts C, Cheung S, Watson Y, Davies K, Jackson A, Jayson GC, Parker GJ
- Issue date: 2005
- Tracer kinetic model-driven registration for dynamic contrast-enhanced MRI time-series data.
- Authors: Buonaccorsi GA, O'Connor JP, Caunce A, Roberts C, Cheung S, Watson Y, Davies K, Hope L, Jackson A, Jayson GC, Parker GJ
- Issue date: 2007 Nov
- Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI.
- Authors: Chen W, Giger ML, Bick U, Newstead GM
- Issue date: 2006 Aug
- Improved accuracy and precision of tracer kinetic parameters by joint fitting to variable flip angle and dynamic contrast enhanced MRI data.
- Authors: Dickie BR, Banerji A, Kershaw LE, McPartlin A, Choudhury A, West CM, Rose CJ
- Issue date: 2016 Oct
- Multilevel analysis of spatiotemporal association features for differentiation of tumor enhancement patterns in breast DCE-MRI.
- Authors: Lee SH, Kim JH, Cho N, Park JS, Yang Z, Jung YS, Moon WK
- Issue date: 2010 Aug