OBJECT: The ability to manipulate image contrast and thus to obtain complementary information is one of the main advantages of MRI. Motion consistency within the whole data set is a key point in the context of multi contrast imaging. In cardiac and abdominal MRI, the acquisition strategy uses multiple breath-holds and often relies on acceleration methods that inherently suffer from a signal to-noise ratio loss. The aim of this work is to propose a free-breathing multi-contrast acquisition and reconstruction workflow to improve image quality and the subsequent data analysis. MATERIALS AND METHODS: We extended a previously proposed motion-compensated image reconstruction method for multi-contrast imaging. Shared information throughout the imaging protocol is now exploited by the image reconstruction in the form of an additional constraint based on image gradient sparsity. This constraint helps to minimize the amount of data needed for efficient non-rigid motion correction. T₁and T₂weighted images were reconstructed from free-breathing acquisitions in 4 healthy volunteers and in a phantom. The impact of multi-contrast motion correction was evaluated in a phantom in terms of precision and accuracy of T₁and T₂quantification. RESULTS: In the phantom, the proposed method achieved an accuracy of 97.5 % on the quantified parameters against 88.0 % before motion correction. In volunteers, motion inconsistency in T₁and T₂quantification were noticeably reduced within 5 min of free-breathing acquisition. CONCLUSION: An efficient, free-breathing, multi-contrast imaging method has been demonstrated that does not require prior assumptions about contrast and that is applicable to a wide range of examinations.
OBJECT: The ability to manipulate image contrast and thus to obtain complementary information is one of the main advantages of MRI. Motion consistency within the whole data set is a key point in the context of multi contrast imaging. In cardiac and abdominal MRI, the acquisition strategy uses multiple breath-holds and often relies on acceleration methods that inherently suffer from a signal to-noise ratio loss. The aim of this work is to propose a free-breathing multi-contrast acquisition and reconstruction workflow to improve image quality and the subsequent data analysis. MATERIALS AND METHODS: We extended a previously proposed motion-compensated image reconstruction method for multi-contrast imaging. Shared information throughout the imaging protocol is now exploited by the image reconstruction in the form of an additional constraint based on image gradient sparsity. This constraint helps to minimize the amount of data needed for efficient non-rigid motion correction. T₁and T₂weighted images were reconstructed from free-breathing acquisitions in 4 healthy volunteers and in a phantom. The impact of multi-contrast motion correction was evaluated in a phantom in terms of precision and accuracy of T₁and T₂quantification. RESULTS: In the phantom, the proposed method achieved an accuracy of 97.5 % on the quantified parameters against 88.0 % before motion correction. In volunteers, motion inconsistency in T₁and T₂quantification were noticeably reduced within 5 min of free-breathing acquisition. CONCLUSION: An efficient, free-breathing, multi-contrast imaging method has been demonstrated that does not require prior assumptions about contrast and that is applicable to a wide range of examinations.
Authors: P Y Marie; M Angioï; J P Carteaux; J M Escanye; S Mattei; K Tzvetanov; O Claudon; N Hassan; N Danchin; G Karcher; A Bertrand; P M Walker; J P Villemot Journal: J Am Coll Cardiol Date: 2001-03-01 Impact factor: 24.094
Authors: Peter Kellman; Yiu-Cho Chung; Orlando P Simonetti; Elliot R McVeigh; Andrew E Arai Journal: J Magn Reson Imaging Date: 2005-11 Impact factor: 4.813
Authors: Dan Ma; Vikas Gulani; Nicole Seiberlich; Kecheng Liu; Jeffrey L Sunshine; Jeffrey L Duerk; Mark A Griswold Journal: Nature Date: 2013-03-14 Impact factor: 49.962