MRI phase offset correction method impacts quantitative susceptibility mapping

Abdulla, Shaeez Usman; Reutens, David C.; Bollmann, Steffen; Vegh, Viktor

doi:10.1016/j.mri.2020.08.009

Cited by 4 publications

(10 citation statements)

References 40 publications

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“…The clinical translation of a QSM-based method for the examination of cortical regions would benefit from adaptations of the measurement techniques to the clinical setting. Our results suggest that the acquisition of single-echo data [40] rather than multiple echoes as well as the choice of a few representative ROIs instead of the whole brain may suffice to distinguish AD from HC based on the proposed QSM method. Such choices can significantly reduce the scanning times and may eventually be traded with an increased spatial resolution at lower field strengths of 7T and, possibly, at 3T.…”

Section: Discussionmentioning

confidence: 99%

“…Complex images were computed using an ASPIRE-like algorithm [39]. Single-echo phase data were used for QSM calculation to generate more accurate and homogeneous susceptibility maps [40]. Specifically, phase data from the third echo (17.92 ms) was chosen as it provided the highest grey/white matter contrast in the QSM images compared to combinations of the echoes and corresponds to the TE with the highest signal-to-noise ratio (SNR) based on our previously reported R 2 * values of 60-70s -1 in the AD patients’ cortex [24].…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Exploration of cortical ß-Amyloid load in Alzheimer’s disease using quantitative susceptibility mapping at 9.4T

Tuzzi

Loktyushin

Zeller

et al. 2022

Preprint

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Early detection of β-Amyloid (Aβ) deposits in Alzheimer’s disease (AD) patients may enable treatment in the early stages of the disease. To date, there are no validated, specific, and non-invasive routines for early Aβ detection which are suitable for clinical practice. Ultra-high resolution quantitative susceptibility mapping (QSM) at 14.1T has previously shown different contrasts in cortical areas of an AD sample that resembled distinct Aβ spatial patterns in histological sections of the same specimen. These contrasts appeared different in the QSM from a healthy control (HC) sample where, instead, no plaques were detected. In a few cases, this distinction in the cortical magnetic effects (para- and diamagnetic) between AD and HC was also observed in vivo using ultra- high resolution single-echo Acquisition Weighted (AW) gradient echo MRI at 9.4T. Based on this evidence, a method to quantify the paramagnetic and diamagnetic effects of Aβ to possibly distinguish between AD and HC was developed. In this study, we extended those results and explored the ability to use QSM to estimate β-Amyloid plaque load in the cortex of 7 elderly patients with early AD and 7 healthy age-matched HC. Besides ultra-high resolution AW images, we acquired lower resolution multi-echo (MTE) data and compared the previously used RESHARP- based method for background removal (“AW-filter”, with a high Tikhonov term and a small kernel size) with a method widely used in the literature (“mild-filter”, with a low-regularization term and a large kernel size) for the MTE processing. Paramagnetic and diamagnetic QSM changes were assessed in 16 cortical areas. All methods enabled the detection of regions with high QSM values (up to 45 ppb in AD and up to 25 ppb in HC) and known as early Aβ accumulation areas in AD progression. A distinct cortical pattern was observed at both spatial resolutions using the AW-filter. This was not the case with the mild-filter at the lower resolution. AW-QSM outperformed MTE maps with the AW-filter for the detection of areas with prominent cortical paramagnetic effects, including regions where Aβ accumulation happens in the earliest AD stages, such as the precuneus and posterior cingulate cortex. Diamagnetic changes were more prominent than the paramagnetic effects regardless of the spatial resolution used and this difference was further enhanced with the mild-filter. This explorative study points toward the development of more accessible clinical methods to non-invasively detect effects of Aβ accumulation in AD patients by exploring cortical features that can be detected by ultra-high field QSM at different spatial resolutions.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Exploration of cortical ß-Amyloid load in Alzheimer’s disease using quantitative susceptibility mapping at 9.4T

Tuzzi

Loktyushin

Zeller

et al. 2022

Preprint

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“…To better estimate 𝜙 0 , the two TEs chosen should be as short as possible but sufficiently far apart to allow phase evolution between echoes. 62 Including the initial phase component in the nonlinear signal modeling and fitting may be worth exploring in future studies.…”

Section: Discussionmentioning

confidence: 99%

“…However, because the microstructure‐induced nonlinear frequency evolution is largest at short TEs, the estimated

{\phi}_0

by MCPC‐3D may contain significant errors, which in turn affects the estimated effective frequency evolution and the fitted

\Delta f

values. To better estimate

{\phi}_0

, the two TEs chosen should be as short as possible but sufficiently far apart to allow phase evolution between echoes 62 . Including the initial phase component in the nonlinear signal modeling and fitting may be worth exploring in future studies.…”

Section: Discussionmentioning

confidence: 99%

Exploiting gradient‐echo frequency evolution: Probing white matter microstructure and extracting bulk susceptibility‐induced frequency for quantitative susceptibility mapping

Chen,

Shin,

van Zijl

et al. 2023

Magnetic Resonance in Med

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PurposeThis work is to investigate the microstructure‐induced frequency shift in white matter (WM) with crossing fibers and to separate the microstructure‐related frequency shift from the bulk susceptibility‐induced frequency shift by model fitting the gradient‐echo (GRE) frequency evolution for potentially more accurate quantitative susceptibility mapping (QSM).MethodsA hollow‐cylinder fiber model (HCFM) with two fiber populations was developed to investigate GRE frequency evolutions in WM voxels with microstructural orientation dispersion. The simulated and experimentally measured TE‐dependent local frequency shift was then fitted to a simplified frequency evolution model to obtain a microstructure‐related frequency difference parameter () and a TE‐independent bulk susceptibility‐induced frequency shift (). The obtained was then used for QSM reconstruction. Reconstruction performances were evaluated using a numerical head phantom and in vivo data and then compared to other multi‐echo combination methods.ResultsGRE frequency evolutions and ‐based tissue parameters in both parallel and crossing fibers determined from our simulations were comparable to those observed in vivo. The TE‐dependent frequency fitting method outperformed other multi‐echo combination methods in estimating in simulations. The fitted , , and QSM could be improved further by navigator‐based B0 fluctuation correction.ConclusionA HCFM with two fiber populations can be used to characterize microstructure‐induced frequency shifts in WM regions with crossing fibers. HCFM‐based TE‐dependent frequency fitting provides tissue contrast related to microstructure () and in addition may help improve the quantification accuracy of and the corresponding QSM.

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“…However, no further QSM analysis was made in order to better evaluate the impact each method had on susceptibility maps, specifically when looking on specific brain regions. [ 1 ] compared the impact different offset correction methods had on phase maps, focusing on QSM application. Their results showed differences between methods, which implies that the choice of phase reconstruction method can alter the resulting QSM, but no region-specific analysis was made.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of multi-channel phase reconstruction methods for quantitative susceptibility mapping on postmortem human brain

Otsuka

Otaduy

Azevedo

et al. 2023

Journal of Magnetic Resonance Open

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MRI phase offset correction method impacts quantitative susceptibility mapping

Cited by 4 publications

References 40 publications

Exploration of cortical ß-Amyloid load in Alzheimer’s disease using quantitative susceptibility mapping at 9.4T

Exploration of cortical ß-Amyloid load in Alzheimer’s disease using quantitative susceptibility mapping at 9.4T

Exploiting gradient‐echo frequency evolution: Probing white matter microstructure and extracting bulk susceptibility‐induced frequency for quantitative susceptibility mapping

Evaluation of multi-channel phase reconstruction methods for quantitative susceptibility mapping on postmortem human brain

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