Dataset Information

Continuous prospectively navigated multi-echo GRE for improved BOLD imaging of the kidneys.

ABSTRACT: The objective of this study is to develop improved methods for renal blood oxygenation level dependent (BOLD) imaging. T2* mapping of the kidneys, or renal BOLD imaging, may depict renal oxygen levels and may be valuable as a noninvasive means of following the progression of renal disease. Current renal BOLD data is limited by imaging in a single breath hold, which results in low resolution and low signal-to-noise ratio (SNR). We compare a new free-breathing renal BOLD method with conventional breath-hold BOLD (BH-BOLD). A multi-echo GRE sequence with continuous prospective respiratory navigation and real-time feedback was developed that allows high resolution and high SNR renal BOLD imaging with constant sequence repetition time (TR) during free-breathing BOLD (FB-BOLD). The sequence was evaluated in 10 normal volunteers and compared with conventional BH-BOLD. Scan time for the FB-BOLD sequence was approximately three minutes, compared with 15 seconds for the BH-BOLD sequence. SNR of source images and residual error of T2* fitting were compared between the two methods. The FB-BOLD sequence produced motion-free T2* maps of the kidneys with SNR 1.9 times higher than BH-BOLD images. Residual error of T2* fitting was consistently lower in the right kidney with FB-BOLD (30% less than BH-BOLD) but higher in the left kidney (80% more than BH-BOLD), likely related to placement of the navigator on the right hemidiaphragm. A free-breathing prospectively navigated renal BOLD sequence allows flexible tradeoff between scan time, resolution, and SNR.

SUBMITTER: Morrell GR

PROVIDER: S-EPMC6476650 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Continuous prospectively navigated multi-echo GRE for improved BOLD imaging of the kidneys.

Morrell Glen Robert GR Jeong Eun-Kee EK Shi Xianfeng X Zhang Lei L Lee Vivian Shu-Ching VS

NMR in biomedicine 20190227 5

The objective of this study is to develop improved methods for renal blood oxygenation level dependent (BOLD) imaging. T2* mapping of the kidneys, or renal BOLD imaging, may depict renal oxygen levels and may be valuable as a noninvasive means of following the progression of renal disease. Current renal BOLD data is limited by imaging in a single breath hold, which results in low resolution and low signal-to-noise ratio (SNR). We compare a new free-breathing renal BOLD method with conventional b ...[more]

PMID: 30811061

Similar Datasets

Project description:BACKGROUND:Subject motion is known to produce spurious covariance among time-series in functional connectivity that has been reported to induce distance-dependent spurious correlations. PURPOSE:To present a feasibility study for applying the extended Kalman filter (EKF) framework for high temporal resolution motion correction of resting state functional MRI (rs-fMRI) series using each simultaneous multi-slice (SMS) echo planar imaging (EPI) shot as its own navigator. STUDY TYPE:Prospective feasibility study. POPULATION/SUBJECTS:Three human volunteers. FIELD STRENGTH/SEQUENCE:3T GE DISCOVERY MR750 scanner using a 32-channel head coil. Simultaneous multi-slice rs-fMRI sequence with repetition time (TR)/echo time (TE) = 800/30 ms, and SMS factor 6. ASSESSMENT:Motion estimates were computed using two techniques: a conventional rigid-body volume-wise registration; and a high-temporal resolution motion estimation rigid-body approach. The reference image was resampled using the estimates obtained from both approaches and the difference between these predicted volumes and the original moving series was summarized using the normalized mean squared error (NMSE). STATISTICAL TESTS:Direct comparison of NMSE values. RESULTS:High-temporal motion estimation was always superior to volume-wise motion estimation for the sample presented. For staged continuous rotations, the NMSE using high-temporal resolution motion estimates ranged between [0.130, 0.150] for the first volunteer (in-plane rotations), between [0.060, 0.068] for the second volunteer (in-plane rotations), and between [0.063, 0.080] for the third volunteer (through-plane rotations). These values went up to [0.384, 0.464]; [0.136, 0.179]; and [0.080, 0.096], respectively, when using volume-wise motion estimates. DATA CONCLUSION:Accurate high-temporal rigid-body motion estimates can be obtained for rs-fMRI taking advantage of simultaneous multi-slice EPI sub-TR shots. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Project description:PurposeTo develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging.MethodsThe proposed QSM reconstruction algorithm, referred to as "structurally constrained Susceptibility Weighted Imaging and Mapping" scSWIM, performs an ℓ 1 and ℓ 2 regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. The multi-echo multi-flip angle data were used for improving the contrast-to-noise ratio in QSM through a weighted averaging scheme. The measured susceptibility values from scSWIM for both simulated and in vivo data were compared to the: original susceptibility model (for simulated data only), the multi orientation COSMOS (for in vivo data only), truncated k-space division (TKD), iterative susceptibility weighted imaging and mapping (iSWIM), and morphology enabled dipole inversion (MEDI) algorithms. Goodness of fit was quantified by measuring the root mean squared error (RMSE) and structural similarity index (SSIM). Additionally, scSWIM was assessed in ten healthy subjects.ResultsThe unique contrast and tissue boundaries from T1WE and iSWIM enable the accurate definition of edges of high susceptibility regions. For the simulated brain model without the addition of microbleeds and calcium, the RMSE was best at 5.21ppb for scSWIM and 8.74ppb for MEDI thanks to the reduced streaking artifacts. However, by adding the microbleeds and calcium, MEDI's performance dropped to 47.53ppb while scSWIM performance remained the same. The SSIM was highest for scSWIM (0.90) and then MEDI (0.80). The deviation from the expected susceptibility in deep gray matter structures for simulated data relative to the model (and for the in vivo data relative to COSMOS) as measured by the slope was lowest for scSWIM + 1%(-1%); MEDI + 2%(-11%) and then iSWIM -5%(-10%). Finally, scSWIM measurements in the basal ganglia of healthy subjects were in agreement with literature.ConclusionThis study shows that using a data fidelity term and structural constraints results in reduced noise and streaking artifacts while preserving structural details. Furthermore, the use of STAGE imaging with multi-echo and multi-flip data helps to improve the signal-to-noise ratio in QSM data and yields less artifacts.

Project description:Performing a BOLD functional MRI (fMRI) acquisition during breath-hold (BH) tasks is a non-invasive, robust method to estimate cerebrovascular reactivity (CVR). However, movement and breathing-related artefacts caused by the BH can substantially hinder CVR estimates due to their high temporal collinearity with the effect of interest, and attention has to be paid when choosing which analysis model should be applied to the data. In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during ten sessions, to obtain subject-specific CVR and haemodynamic lag estimates. The evaluated approaches range from conventional regression models, i.e. including drifts and motion timecourses as nuisance regressors, applied on single-echo or optimally-combined data, to more complex models including regressors obtained from multi-echo independent component analysis with different grades of orthogonalization in order to preserve the effect of interest, i.e. the CVR. We compare these models in terms of their ability to make signal intensity changes independent from motion, as well as the reliability as measured by voxelwise intraclass correlation coefficients of both CVR and lag maps over time. Our results reveal that a conservative independent component analysis model applied on the optimally-combined multi-echo fMRI signal offers the largest reduction of motion-related effects in the signal, while yielding reliable CVR amplitude and lag estimates, although a conventional regression model applied on the optimally-combined data results in similar estimates. This work demonstrates the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering its potential as a clinically-viable neuroimaging tool for individual patients. It also proves that the way in which data-driven regressors should be incorporated in the analysis model is not straight-forward due to their complex interaction with the BH-induced BOLD response.

Dataset Information

Continuous prospectively navigated multi-echo GRE for improved BOLD imaging of the kidneys.

Publications

Continuous prospectively navigated multi-echo GRE for improved BOLD imaging of the kidneys.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure