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Abstract #4158

Uncertainty assessment of iterative image reconstruction for dynamic contrast enhancement (DCE) MRI

Edengenet Mashilla Dejene1,2, Winfried Brenner2, Marcus R. Makowski3, Johannes Mayer1, and Christoph Kolbitsch1
1Physikalisch - Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany, 2Charité Universitätsmedizin Berlin, Berlin, Germany, 3Technical University of Munich, Munich, Germany

Synopsis

Keywords: Liver, Cancer

Motivation: The quality of the dynamic contrast enhanced images affects the quantification of physiological parameters.

Goal(s): We aim to quantitatively investigate the impact of reconstruction quality on the accurate estimation of physiological parameters.

Approach: Quantitative performance of two reconstruction methods was investigated using aleatoric (i.e., inherent ambiguity) and epistemic (i.e., mismatch between high quality training data and application data) uncertainties calculated with a DL approach.

Results: Quantitative parameter estimates for tumor sub-structures were affected by the reconstruction quality. Aleatoric and epistemic uncertainties for $$$k_{trans}$$$ and $$$v_{e}$$$ were sensitive to reconstruction quality. This metrics served as quantitative markers for assessing the quality of reconstruction methods.

Impact: The quality of the reconstructed images can impair diagnostic accuracy of quantitative parameters. The proposed approach allows to quantify the impact of image quality on the obtained quantitative DCE parameters without the need for a ground truth information.

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Keywords