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Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI (DCE-MRI) using different models of contrast enhancement

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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 timevaryingfeatures that occur as a result of contrast enhancement can confound motion correction techniques based on conventionalregistration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic modeldrivenregistration procedure, in which the model accounts for contrast enhancement, and applied it to the registration ofabdominal DCE-MRI data at high temporal resolution.Materials and Methods. Using severely motion-corrupted data sets that had been excluded from analysis in a clinicaltrial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic modeldrivenregistration 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 ofsquared errors but the improvement was only realized when using a model that adequately described the features of thetime series data. The registration against the time series mean significantly distorted the time series data, as did tracerkinetic 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 modelfit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positiveimplications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.Key Words. MRI; Gd-DTPA; image processing; computer-assisted; angiogenesis inhibitors; image registration.

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