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On the b-value Derivation for diffusion-weighted Double-Echo Steady-State (dwDESS) Magnetic Resonance Imaging

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Computational Diffusion MRI (CDMRI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 13006))

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Abstract

To determine the degree of observed diffusion weighting and to calculate the diagnostically valuable “Apparent Diffusion Coefficient” (ADC) in MR-based “Diffusion-Weighted Imaging” (DWI), a standardized b-value is typically used. To overcome geometrical distortions in standard DWI, diffusion-weighted double-echo steady-state (dwDESS) sequences have been proposed. Balanced bipolar dwDESS, in particular, provides high SNR and is robust against motion. However, a proper definition of the b-value equivalent to standard DWI is not yet well addressed for this bipolar dwDESS. Therefore, this study investigated an estimation for effective b-values in bipolar dwDESS based on approximation of the underlying signal model in the framework of configuration theory. The obtained effective b-values have been validated in phantom as well as in vivo breast studies of a healthy human subject, yielding good agreement with the corresponding b-values of standard DWI. Thus, this study enables the quantitative comparison of dwDESS with diffusion-weighted images obtained from different sequences, different measurements, and different scanners, which helps a wide clinical adaption in studies of, for example, cartilage impairments or breast cancer lesions.

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Acknowledgements

The authors would like to thank Ch. Stehning and O. Bieri for their valuable support.

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Katscher, U., Meineke, J., Zhang, S., Steinhorst, B., Keupp, J. (2021). On the b-value Derivation for diffusion-weighted Double-Echo Steady-State (dwDESS) Magnetic Resonance Imaging. In: Cetin-Karayumak, S., et al. Computational Diffusion MRI. CDMRI 2021. Lecture Notes in Computer Science(), vol 13006. Springer, Cham. https://doi.org/10.1007/978-3-030-87615-9_1

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  • DOI: https://doi.org/10.1007/978-3-030-87615-9_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87614-2

  • Online ISBN: 978-3-030-87615-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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