Investigating the Effect of Flow Compensation and Quantitative Susceptibility Mapping Method on the Accuracy of Venous Susceptibility Measurement

Berg, Ronja; Preibisch, Christine; Thomas, David L.; Shmueli, Karin; Biondetti, Emma

doi:10.1101/2021.04.14.439812

Cited by 4 publications

(7 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, the improved performance of the iLSQR algorithm seems to be mainly benefiting from minimizing streaking artifacts in the reconstructed susceptibility maps 46 . However, we observed that this algorithm produced lower susceptibility levels in GP (compared with other reconstruction methods), which coincides with a previous study that reported lower estimation of venous susceptibility using the iLSQR 70 . This may originate from the concept the iLSQR employs to suppress streaking artifacts that involves estimating and subtracting the artifacts from an initial susceptibility map, which may alter the contrast of strong susceptibility sources 46 .…”

Section: Discussionsupporting

confidence: 89%

“…46 However, we observed that this algorithm produced lower susceptibility levels in GP (compared with other reconstruction methods), which coincides with a previous study that reported lower estimation of venous susceptibility using the iLSQR. 70 This may originate from the concept the iLSQR employs to suppress streaking artifacts that involves estimating and subtracting the artifacts from an initial susceptibility map, which may alter the contrast of strong susceptibility sources. 46 Thus, the iLSQR might not be the best choice for applications that involve estimating strong susceptibility sources, and other methods could be considered.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads

et al. 2022

View full text Add to dashboard Cite

Iron concentration in the human brain plays a crucial role in several neurodegenerative diseases and can be monitored noninvasively using quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R2*) mapping from multiecho T2*‐weighted images. Large population studies enable better understanding of pathologies and can benefit from pooling multisite data. However, reproducibility may be compromised between sites and studies using different hardware and sequence protocols. This work investigates QSM and R2* reproducibility at 3 T using locally optimized sequences from three centers and two vendors, and investigates possible reduction of cross‐site variability through postprocessing approaches. Twenty‐four healthy subjects traveled between three sites and were scanned twice at each site. Scan‐rescan measurements from seven deep gray matter regions were used for assessing within‐site and cross‐site reproducibility using intraclass correlation coefficient (ICC) and within‐subject standard deviation (SDw) measures. In addition, multiple QSM and R2* postprocessing options were investigated with the aim to minimize cross‐site sequence‐related variations, including: mask generation approach, echo‐timing selection, harmonizing spatial resolution, field map estimation, susceptibility inversion method, and linear field correction for magnitude images. The same‐subject cross‐site region of interest measurements for QSM and R2* were highly correlated (R2 ≥ 0.94) and reproducible (mean ICC of 0.89 and 0.82 for QSM and R2*, respectively). The mean cross‐site SDw was 4.16 parts per billion (ppb) for QSM and 1.27 s−1 for R2*. For within‐site measurements of QSM and R2*, the mean ICC was 0.97 and 0.87 and mean SDw was 2.36 ppb and 0.97 s−1, respectively. The precision level is regionally dependent and is reduced in the frontal lobe, near brain edges, and in white matter regions. Cross‐site QSM variability (mean SDw) was reduced up to 46% through postprocessing approaches, such as masking out less reliable regions, matching available echo timings and spatial resolution, avoiding the use of the nonconsistent magnitude contrast between scans in field estimation, and minimizing streaking artifacts.

show abstract

Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 99%

Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Where 24 Five subjects were scanned twice within the same session without repositioning to enable image-based calculation of magnitude and phase SNRs.…”

Section: Methodsmentioning

confidence: 99%

“…All volunteers provided written informed consent, and the local research ethics committees approved the experimental sessions. Images were acquired using a transverse orientation, FOV = 240×240×144 mm 3 , voxel size = 1‐mm isotropic, flip angle = 20 0 , TR = 29 ms, 5 evenly spaced echoes (TE 1 /TE spacing = 3/5.4 ms), bandwidth = 270 Hz/pixel, SENSE 23 factors = 2/1.5, flyback gradients = on, no flow compensating gradients, total scan duration = 04:37 min:s 24 . Five subjects were scanned twice within the same session without repositioning to enable image‐based calculation of magnitude and phase SNRs.…”

Section: Methodsmentioning

confidence: 99%

Multi‐echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla

Biondetti

Karsa

Grussu

et al. 2022

Magnetic Resonance in Med

Self Cite

View full text Add to dashboard Cite

Purpose To compare different multi‐echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi‐echo gradient‐recalled echo signal phase information, either before or after applying Laplacian‐base methods (LBMs) for phase unwrapping or background field removal. Methods Multi‐echo gradient‐recalled echo data were simulated in a numerical head phantom, and multi‐echo gradient‐recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image‐based estimation of gradient‐recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE‐dependent phase and then combined multiple TEs via either TE‐weighted or SNR‐weighted averaging; and 2 calculated TE‐dependent susceptibility maps via either multi‐step or single‐step QSM and then combined multiple TEs via magnitude‐weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests). Results Nonlinearly fitting the multi‐echo phase over TEs before applying LBMs provided the highest regional accuracy of χ$$ \chi $$ and the lowest phase noise propagation compared to averaging the LBM‐processed TE‐dependent phase. This result was especially pertinent in high‐susceptibility venous regions. Conclusion For multi‐echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.

show abstract

“…All the volunteers provided written informed consent, and the local research ethics committees approved the experimental sessions. Images were acquired using a transverse orientation, field of view=240×240×144 mm 3 , voxel size=1-mm isotropic, flip angle=20□, repetition time=29 ms, five evenly spaced echoes (TE 1 TE spacing=3/5.4 ms), bandwidth=270 Hz/pixel, SENSE (23) factors=2/1.5, flyback gradients=on, no flow compensating gradients, total scan duration =04:37 min:s (24). Five subjects were scanned twice within the same session without repositioning to enable imagebased calculation of magnitude and phase SNRs.…”

Section: Methodsmentioning

confidence: 99%

Multi-echo Quantitative Susceptibility Mapping: How to Combine Echoes for Accuracy and Precision at 3 T

Biondetti

Karsa

Grussu

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Purpose: To compare different multi-echo combination methods for MRI quantitative susceptibility mapping (QSM), aiming to elucidate, given the current lack of consensus, how to optimally combine multi-echo gradient-recalled echo (GRE) signal phase information, either before or after applying Laplacian-base methods (LBMs) for phase unwrapping or background field removal. Methods: Multi-echo GRE data were simulated in a numerical head phantom, and multi-echo GRE images were acquired at 3 T in 10 healthy volunteers. To enable image-based estimation of GRE signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: one applied nonlinear phase fitting over echo times (TEs) before LBMs; two applied LBMs to the TE-dependent phase and then combined multiple TEs via either TE-weighted or signal-to-noise ratio (SNR)-weighted averaging; two calculated TE-dependent susceptibility maps via either multi-step or single-step QSM and then combined multiple TEs via magnitude-weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter and venous regions; phase noise propagation maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland-Altman) and regional differences between the means (non-parametric tests). Results: Nonlinearly fitting the multi-echo phase over TEs before applying LBMs provided the best compromise between regional accuracy/precision and mitigation of phase noise propagation compared to averaging the LBM-processed TE-dependent phase. This result was especially true in high-susceptibility venous regions. Conclusion: For multi-echo QSM, combining the signal phase by nonlinear fitting before applying LBMs is recommended.

show abstract

Investigating the Effect of Flow Compensation and Quantitative Susceptibility Mapping Method on the Accuracy of Venous Susceptibility Measurement

Cited by 4 publications

References 51 publications

Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads

Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads

Multi‐echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla

Multi-echo Quantitative Susceptibility Mapping: How to Combine Echoes for Accuracy and Precision at 3 T

Contact Info

Product

Resources

About