Skip to content

Advertisement

  • Oral presentation
  • Open Access

High-resolution multi-breath-held 3D volumetric T1 mapping acquisition: analysis of T1 measurement reproducibility compared to 2D T1 mapping with a respiratory motion phantom

  • 1,
  • 3,
  • 2,
  • 4,
  • 1 and
  • 1
Journal of Cardiovascular Magnetic Resonance201517 (Suppl 1) :O2

https://doi.org/10.1186/1532-429X-17-S1-O2

  • Published:

Keywords

  • Respiratory Motion
  • Cartesian Projection
  • Single Readout
  • Respiratory Shift
  • Respiratory Drift

Background

Myocardial T1 mapping, which is used to detect diffuse fibrosis and quantify extracellular volumes, often employs 8-10 mm 2D slice acquisitions. However, this may be unsuited for accurate quantification of small tissues samples. We propose a new methodology that improves through-plane resolution using a novel 3D acquisition technique over multiple breath-holds. In this study, we compared this new approach to the reference multi-slice 2D approach using a respiratory motion phantom.

Methods

The proposed 3D sequence employs a Cartesian projection of radial sectors, where each opposite sector pair is acquired in a single readout crossing through the center of k-space at the acquisition window midpoint (Fig 1a). Spatial resolution is gained in 3D via partial kz (~62%) and circular shutter Field-of-View (FOV) (~27% reduction), yielding ~3x improvement in through-plane resolution.
Figure 1
Figure 1

a) Profile ordering of the proposed 3D method. b) Motion phantom and T1 maps from the reference IR-SE and from the 3D sequence, respectively

Imaging was performed using 1.5T MRI (Philips Achieva) with a 4-channel array on a respiratory motion phantom with 12 conical vials with varying Gd concentrations (fig 1b). The proposed 3D sequence employed a 5-(3s)-3 Modified Look-Locker Inversion Recovery (MOLLI) over ~11 heart beats per breath-hold. 2D MOLLI was also acquired across the same FOV. The following breathing patterns were examined: 1) no respiratory motion, 2) 8mm respiratory drift, and 3) 4-8 mm respiratory shifts between alternating breath-holds. 1 and 2 were repeated 5x for reproducibility, and 3 was implemented 4x to introduce motion blurring in the 3D approach. The following parameters were used for both 2D and 3D MOLLI: FOV (185x185x80mm), # of breath-holds (n=8), resolution (1.7x2.1 mm) with 2D vs 3D slice thickness/resolution = 10 vs 3.1 mm (8 and 26 slices, respectively). SENSE with R=2 acceleration was also used. A reference IR-SE scan was used to determine the reference T1 values for each vial. Relative T1 error of the 2D and 3D MOLLI measurements was calculated as ∆T1 = 100*|T1meas-T1Ref|/T1Ref. All measurements were performed using custom software. Student's t-test was used to compare inter-technique T1 measurements (p<0.05 significant).

Results

Both static 2D and 3D MOLLI yielded comparable (p=0.4) relative error with respect to the reference IR-SE T1 measurements. Under an 8mm mid-breath-hold drift, 2D MOLLI was unable to yield T1 values in 5 out of the 12 vials (42%), while 3D MOLLI allowed T1 measurement of all vials. The variation in the average T1 measurements across the 5 repeated scans was less with the 3D approach (2D vs 3D: 18.5±7 vs 8.4±6 ms; p<0.05). T1 mapping was feasible even under motion blurred 3D volumes, and both measured T1 values and T1 error were comparable to those from static 3D volumes (p=0.5, p=0.3, respectively).

Conclusions

Respiratory motion can result in failure of conventional 2D T1 mapping. The proposed novel 3D T1 mapping scheme performs robustly in the presence of respiratory motion at a significantly higher spatial resolution.

Funding

N/A.
Table 1

Relative T1 Error: 100*|T1meas - T1IR-SE |/T1IR-SE

T1meas

% Error vs Ref IR-SE

P-value

2D Static

9.8 ± 4.8

P = NS

2D with Respiratory Drift

10.0 ± 5.1

P = NS

2D with Respiratory Shift

11.7 ± 7.7

P = NS

3D Static

7.6 ± 6.1

P = NS

3D with Respiratory Drift

9.6 ± 9.3

P = NS

3D with Respiratory Shift

9.1 ± 9.2

P = NS

All pairwise comparisons yielded non-significant (NS) p-values (P > 0.05).

Authors’ Affiliations

(1)
Medicine, Section of Cardiology, The University of Chicago, Chicago, IL, USA
(2)
Medicine, Section of Surgery, The University of Chicago, Chicago, IL, USA
(3)
Biomedical Engineering, Northwestern University, Chicago, IL, USA
(4)
Philips Healthcare, Cleveland, OH, USA

Copyright

© Kawaji 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.

Advertisement