3D SASHA myocardial T1 mapping with high accuracy and improved precision

Nordio, Giovanna; Bustin, Aurélien; Henningsson, Markus; Rashid, Imran; Chiribiri, Amedeo; Ismail, Tevfik F; Odille, Freddy; Prieto, Claudia; Botnar, René M.

doi:10.1007/s10334-018-0703-y

Cited by 14 publications

(23 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…SENSE reconstruction was performed for both non‐motion‐corrected and motion‐corrected 3D SASHA data sets. A denoising method was applied to the T 1 ‐weighted images of both the 2D and 3D SASHA acquisitions before parametric fitting to reduce the noise and improve both image quality and T 1 precision of the T 1 maps . A 3‐parameter fitting model was then used to reconstruct the T 1 maps offline for the 2 data sets with a pixel‐wise fitting approach.…”

Section: Methodsmentioning

confidence: 99%

Whole‐heart T₁ mapping using a 2D fat image navigator for respiratory motion compensation

Nordio

Schneider

Cruz

et al. 2019

Magnetic Resonance in Med

Self Cite

View full text Add to dashboard Cite

Purpose To combine a 3D saturation-recovery-based myocardial T1 mapping (3D SASHA) sequence with a 2D image navigator with fat excitation (fat-iNAV) to allow 3D T1 maps with 100% respiratory scan efficiency and predictable scan time. Methods Data from T1 phantom and 10 subjects were acquired at 1.5T. For respiratory motion compensation, a 2D fat-iNAV was acquired before each 3D SASHA k-space segment to correct for 2D translational motion in a beat-to-beat fashion. The effect of the fat-iNAV on the 3D SASHA T1 estimation was evaluated on the T1 phantom. For 3 representative subjects, the proposed free-breathing 3D SASHA with fat-iNAV was compared to the original implementation with the diaphragmatic navigator. The 3D SASHA with fat-iNAV was compared to the breath-hold 2D SASHA sequence in terms of accuracy and precision. Results In the phantom study, the Bland-Altman plot shows that the 2D fat-iNAVs does not affect the T1 quantification of the 3D SASHA acquisition (0 ± 12.5 ms). For the in vivo study, the 2D fat-iNAV permits to estimate the respiratory motion of the heart, while allowing for 100% scan efficiency, improving the precision of the T1 measurement compared to non-motion-corrected 3D SASHA. However, the image quality achieved with the proposed 3D SASHA with fat-iNAV is lower compared to the original implementation, with reduced delineation of the myocardial borders and papillary muscles. Conclusions We demonstrate the feasibility to combine the 3D SASHA T1 mapping imaging sequence with a 2D fat-iNAV for respiratory motion compensation, allowing 100% respiratory scan efficiency and predictable scan time.

show abstract

Section: Methodsmentioning

confidence: 99%

Whole‐heart T₁ mapping using a 2D fat image navigator for respiratory motion compensation

Nordio

Schneider

Cruz

et al. 2019

Magnetic Resonance in Med

Self Cite

View full text Add to dashboard Cite

show abstract

“…In order to achieve high precision in spite of the reduced number of saturation recovery time points, we propose to apply a novel 3D Beltrami denoising technique to the T1-weighted images prior to the T1 fitting. The Beltrami framework for image denoising and enhancement was introduced for 2D natural images by Sochen, Kimmel and Malladi (16), proposed for 2D myocardial T1 mapping denoising by Bustin et al (16), and have been recently extended to 3D T1 mapping denoising (17). The Beltrami regularization allows to preserve the edges, while reducing the noise of the images without introducing staircasing artefacts (18) .…”

Section: D Denoisingmentioning

confidence: 99%

“…For both prospective and retrospective studies, the 3D SASHA T1 map with nine images along the recovery curve was considered as the reference standard. 3D SASHA with nine images along the recovery curve has been previously compared against 2D MOLLI showing excellent agreement in terms of accuracy(17).…”

mentioning

confidence: 99%

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising

Nordio

Bustin

Odille

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

AbstractPurposeTo accelerate the acquisition of free-breathing 3D saturation-recovery-based (SASHA) myocardial T1 mapping by acquiring fewer saturation points in combination with a novel post-processing 3D denoising technique to maintain high accuracy and precision.Methods3D SASHA T1 mapping acquires nine T1-weighted images along the saturation recovery curve, resulting in long acquisition times. In this work, we propose to accelerate conventional cardiac T1 mapping by reducing the number of saturation points. High T1 accuracy and precision is maintained by applying a 3D denoising technique to the T1-weighted images prior to pixel-wise T1 fitting. The proposed approach was evaluated on a T1 phantom and 20 healthy subjects, by varying the number of T1-weighted images acquired between three and nine, both prospectively and retrospectively. Three patients with suspected cardiovascular disease were acquired using five T1-weighted images. T1 accuracy and precision was determined for all the acquisitions before and after denoising.ResultsIn the T1 phantom, no statistical difference was found in terms of accuracy and precision for the different number of T1-weighted images before or after denoising (P=0.99 and P=0.99 for accuracy, P=0.64 and P=0.42 for precision, respectively). In vivo, both prospectively and retrospectively, the precision improved considerably with the number of T1-weighted images employed before denoising (P<0.05) but was independent on the number of T1-weighted images after denoising.ConclusionWe demonstrate the feasibility of accelerating 3D SASHA T1 mapping by reducing the number of acquired T1-weighted images in combination with an efficient 3D denoising, without affecting accuracy and precision of T1 values.

show abstract

“…Recently, we demonstrated the feasibility of a free-breathing 3D SASHA [10] imaging technique, which allows to provide wholeheart coverage with higher signal-to-noise ratio (SNR) and image resolution than with conventional 2D approaches. We have also demonstrated that the precision of 3D SASHA can be improved, without affecting the T1 accuracy, using a post-processing 3D denoising technique based on Beltrami regularization applied directly on the T1-weighted images [11]. The acquisition time of the 3D SASHA sequence is considerably longer than a breath-hold (in the order of 12 min), thus 1D diaphragmatic navigator gating (and tracking) was employed to enable 3D free-breathing T1 mapping [10].…”

Section: Introductionmentioning

confidence: 99%

“…In this study, we propose to accelerate the 3D SASHA acquisition by reducing the number of the T1-weighted images acquired along the saturation recovery curve. To overcome the expected loss in accuracy and precision due to the reduced number of T1-weighted images acquired, we use the 3D denoising technique based on Beltrami regularization applied directly to the T1-weighted images prior to T1 fitting (as is [11]), enabling accurate and precise 3D SASHA T1 mapping from fewer saturation points and thus shorter scan times. The proposed approach was tested on a standardized T1 phantom, 10 healthy subjects with retrospectively reduced number of T1-weighted images, 10 healthy subjects with prospectively varied number of T1-weighted images and three patients with suspected cardiovascular disease.…”

Section: Introductionmentioning

confidence: 99%

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising

et al. 2020

Self Cite

View full text Add to dashboard Cite

PurposeTo accelerate the acquisition of free-breathing 3D saturation-recovery-based (SASHA) myocardial T1 mapping by acquiring fewer saturation points in combination with a post-processing 3D denoising technique to maintain high accuracy and precision. Methods3D SASHA T1 mapping acquires nine T1-weighted images along the saturation recovery curve, resulting in long acquisition times. In this work, we propose to accelerate conventional cardiac T1 mapping by reducing the number of saturation points. High T1 accuracy and low standard deviation (as a surrogate for precision) is maintained by applying a 3D denoising technique to the T1-weighted images prior to pixel-wise T1 fitting. The proposed approach was evaluated on a T1 phantom and 20 healthy subjects, by varying the number of T1weighted images acquired between three and nine, both prospectively and retrospectively. Following the results from the healthy subjects, three patients with suspected cardiovascular disease were acquired using five T1-weighted images. T1 accuracy and precision was determined for all the acquisitions before and after denoising. ResultsIn the T1 phantom, no statistical difference was found in terms of accuracy and precision for the different number of T1-weighted images before or after denoising (P = 0.99 and P = 0.99 for accuracy, P = 0.64 and P = 0.42 for precision, respectively). In vivo, both prospectively and retrospectively, the precision improved considerably with the number of T1-weighted images employed before denoising (P<0.05) but was independent on the number of T1weighted images after denoising.

show abstract

3D SASHA myocardial T1 mapping with high accuracy and improved precision

Abstract: The precision of 3D SASHA myocardial T1 mapping was substantially improved using a 3D Beltrami regularization based denoising technique and was similar to that of 2D MOLLI T1 mapping, while preserving the higher accuracy and whole-heart coverage of 3D SASHA.

Cited by 14 publications

References 18 publications

Whole‐heart T₁ mapping using a 2D fat image navigator for respiratory motion compensation

Whole‐heart T₁ mapping using a 2D fat image navigator for respiratory motion compensation

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising

Contact Info

Product

Resources

About

3D SASHA myocardial T1 mapping with high accuracy and improved precision

Abstract: The precision of 3D SASHA myocardial T1 mapping was substantially improved using a 3D Beltrami regularization based denoising technique and was similar to that of 2D MOLLI T1 mapping, while preserving the higher accuracy and whole-heart coverage of 3D SASHA.

Cited by 14 publications

References 18 publications

Whole‐heart T1 mapping using a 2D fat image navigator for respiratory motion compensation

Whole‐heart T1 mapping using a 2D fat image navigator for respiratory motion compensation

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising

Contact Info

Product

Resources

About

Whole‐heart T₁ mapping using a 2D fat image navigator for respiratory motion compensation

Whole‐heart T₁ mapping using a 2D fat image navigator for respiratory motion compensation