Joint myocardial T1 and T2 mapping

  • Mehmet Akçakaya
  • Sebastian Weingärtner
  • Tamer A Basha
  • Sébastien Roujol
  • Reza Nezafat
Open Access
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Keywords

Sequence Diagram Simultaneous Estimation Joint Estimation Phantom Imaging Longitudinal Magnetization 

Background

Recent studies suggest that quantitative myocardial T1 mapping allows assessment of focal and diffuse fibrosis in the myocardium [1]. Quantitative T2 mapping has also been proposed to overcome challenges associated with T2 weighted imaging [2]. These maps are traditionally acquired with different sequences, necessitating image registration to evaluate them jointly. A sequence that can jointly estimate T1 and T2 maps has been proposed [3], but it requires multiple relaxation cycles, which necessitates a lengthy free-breathing acquisition. In [4], an alternative joint estimation sequence was proposed based on the inversion-recovery SSFP curve. In this study, we sought to develop a saturation-recovery based heart-rate independent sequence that can be acquired in a breath-hold and that allows for simultaneous estimation of quantitative T1 and T2 maps.

Methods

The sequence diagram is depicted in Figure 1. At every heartbeat, a saturation pulse is applied to eliminate the magnetization history. The longitudinal magnetization then recovers for Tsat based on the T1 value. Subsequently a T2-prep pulse [5] with echo length TEprep is applied to generate the additional T2 weighting, after which a single shot SSFP image is acquired. The process is repeated for 13 heartbeats with various (Tsatk, TEprepk) corresponding to heartbeat k, to sample different T1-T2 weighted images. The first heartbeat is acquired with no magnetization preparation.
Figure 1

a) The sequence diagram for the proposed technique. A saturation pulse is applied in every R-R interval to eliminate the magnetization history. The longitudinal magnetization then recovers for Tsat. Subsequently a T2-prep with echo length TEprep is applied to generate the additional T2 weighting, after which a single shot SSFP image is acquired. b) The mapping sequence acquires the first image with no magnetization preparation (corresponding to Tsat = ∞ and TEprep = 0), followed by 12 images (3 are shown) acquired with different Tsat and TEprep values. The major characteristics of the longitudinal magnetization signal curve are depicted under the pulse sequence diagram.

The T1 and T2 maps were estimated jointly by voxel-wise least squares fitting to a 4-parameter signal model, A (1- exp(-Tsatk/T1)) exp(-TEprepk/T2) + B. Phantom imaging of 14 vials with different T1/T2 values were performed and compared to inversion-recovery and CPMG spin-echo references, respectively. Breath-held in-vivo imaging was performed on 5 healthy adult subjects, and the maps were compared to SASHA T1 maps [6] and to T2 maps [7].

Results

Phantom imaging resulted in T1 and T2 values not significantly different than the references (P = 0.481 and 0.479 respectively). Example in-vivo T1 and T2 maps are depicted in Figure 2, comparing various techniques. The T1 and T2 values were in good agreement (1211 ± 82 ms vs. 1210 ± 92 ms for T1; 49.0 ± 5.8 ms and 47.3 ± 6.5 ms for T2).
Figure 2

T1 and T maps from a healthy subject, acquired using the proposed technique, as well as SASHA T1 mapping, and conventional T2 mapping using 4 T2prep echo times. Both the T1 and T2 maps generated jointly with the proposed method are similar to the individual maps with similar magnetization preparations. The myocardial T1 and T2 values in the septum were 1211 ± 82 ms (SASHA T1), 1210 ± 92 ms (Joint T1-T2), 49.0 ± 5.8 ms (conventional T2) and 47.3 ± 6.5 ms (Joint T1-T2) for each technique. The methods generated with the proposed method were acquired in the same time as each individual map, and are jointly registered by design.

Conclusions

The proposed sequence allows for the simultaneous estimation of accurate and jointly registered quantitative T1 and T2 maps with similar accuracy and precision to saturation-based T1 mapping and to T2 mapping of same duration.

Funding

NIH:K99HL111410-01; R01EB008743-01A2.

References

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    Chow : MRM. 2013Google Scholar
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Copyright information

© Akçakaya et al; licensee BioMed Central Ltd. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Mehmet Akçakaya
    • 1
  • Sebastian Weingärtner
    • 1
    • 2
  • Tamer A Basha
    • 1
  • Sébastien Roujol
    • 1
  • Reza Nezafat
    • 1
  1. 1.Medicine, Beth Israel Deaconess Medical CenterHarvard Medical SchoolBostonUSA
  2. 2.Computer Assisted Clinical Medicine, University Medical Center MannheimHeidelberg UniversityMannheimGermany

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