Temporal Huber Regularization for DCE-MRI
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Temporal Huber Regularization for DCE-MRI Matti Hanhela1
· Mikko Kettunen2 · Olli Gröhn2 · Marko Vauhkonen1 · Ville Kolehmainen1
Received: 30 July 2019 / Accepted: 21 July 2020 / Published online: 18 September 2020 © The Author(s) 2020
Abstract Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to study microvascular structure and tissue perfusion. In DCE-MRI, a bolus of gadolinium-based contrast agent is injected into the blood stream and spatiotemporal changes induced by the contrast agent flow are estimated from a time series of MRI data. Sufficient time resolution can often only be obtained by using an imaging protocol which produces undersampled data for each image in the time series. This has lead to the popularity of compressed sensing-based image reconstruction approaches, where all the images in the time series are reconstructed simultaneously, and temporal coupling between the images is introduced into the problem by a sparsity promoting regularization functional. We propose the use of Huber penalty for temporal regularization in DCE-MRI, and compare it to total variation, total generalized variation and smoothness-based temporal regularization models. We also study the effect of spatial regularization to the reconstruction and compare the reconstruction accuracy with different temporal resolutions due to varying undersampling. The approaches are tested using simulated and experimental radial golden angle DCE-MRI data from a rat brain specimen. The results indicate that Huber regularization produces similar reconstruction accuracy with the total variation-based models, but the computation times are significantly faster. Keywords Dce-mri · Compressed sensing · Huber penalty · Total variation · Radial mri
1 Introduction Dynamic Contrast-Enhanced MRI (DCE-MRI) is an imaging method which is used to study microvascular structure and tissue perfusion. It is used widely, for example, in studies of antivascular drugs [28,49], multiple sclerosis [10,16], bloodbrain-barrier assessment after acute ischemic stroke [27,42] and treatment monitoring in breast cancer [26,30] and glioma [31]. The operation principle in DCE-MRI is to inject a bolus of gadolinium-based contrast agent into the blood stream and acquire a time series of MRI data with a suitable T1 -weighting to obtain a time series of 2D (or 3D) images which exhibit contrast changes induced by concentration changes of the contrast agent in the tissues. High spatial and temporal resolution of the DCE image series is required for accurate analysis of the contrast agent dynamics. In many cases, sufficient time resolution can
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Matti Hanhela [email protected]
1
Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland
2
A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, 70211 Kuopio, Finland
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only be obtained by utilizing an imaging protocol which produces undersampled data for each image in the time series. However, this has the complication that reconstructing undersampled datas
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