Quantitative Biomedical Imaging Laboratory

Title: Comparison of the Performance of Tracer Kinetic Model-Driven Registration for Dynamic Contrast Enhanced MRI Using Different Models of Contrast Enhancement
Authors: Giovanni A. Buonaccorsi, Caleb Roberts, Sue Cheung, Yvonne Watson, James P.B. O’Connor, Karen Davies, Alan Jackson, Gordon C. Jayson, Geoff J.M. Parker
Journal: Acad. Radiology
Link: http://www.academicradiology.org/article/S1076-6332(06)00312-6/abstract
Year: 2006
Volume: 13
Number: 9
Pages: 1112–1123
Month: September
Abstract: RATIONALE 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.