Automated adaptive preconditioner for quantitative susceptibility mapping.
Ontology highlight
ABSTRACT: Purpose
To develop an automated adaptive preconditioner for QSM reconstruction with improved susceptibility quantification accuracy and increased image quality.Theory and methods
The total field was used to rapidly produce an approximate susceptibility map, which was then averaged and trended over R2? binning to generate a spatially varying distribution of preconditioning values. This automated adaptive preconditioner was used to reconstruct QSM via total field inversion and was compared with its empirical counterparts in a numerical simulation, a brain experiment with 5 healthy subjects and 5 patients with intracerebral hemorrhage, and a cardiac experiment with 3 healthy subjects.Results
Among evaluated preconditioners, the automated adaptive preconditioner achieved the fastest convergence in reducing the RMSE of the QSM in the simulation, suppressed hemorrhage-associated artifacts while preserving surrounding brain tissue contrasts, and provided cardiac chamber oxygenation values consistent with those reported in the literature.Conclusion
An automated adaptive preconditioner allows high-quality QSM from the total field in imaging various anatomies with dynamic susceptibility ranges.
SUBMITTER: Liu Z
PROVIDER: S-EPMC6778703 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
Publications
Automated adaptive preconditioner for quantitative susceptibility mapping.
Liu Zhe Z Wen Yan Y Spincemaille Pascal P Zhang Shun S Yao Yihao Y Nguyen Thanh D TD Wang Yi Y
Magnetic resonance in medicine 20190811 1
<h4>Purpose</h4>To develop an automated adaptive preconditioner for QSM reconstruction with improved susceptibility quantification accuracy and increased image quality.<h4>Theory and methods</h4>The total field was used to rapidly produce an approximate susceptibility map, which was then averaged and trended over R2∗ binning to generate a spatially varying distribution of preconditioning values. This automated adaptive preconditioner was used to reconstruct QSM via total field inversion and was ...[more]
Similar Datasets
Project description:BACKGROUND:Accurate measurement of the liver iron concentration (LIC) is needed to guide iron-chelating therapy for patients with transfusional iron overload. In this work, we investigate the feasibility of automated quantitative susceptibility mapping (QSM) to measure the LIC. PURPOSE:To develop a rapid, robust, and automated liver QSM for clinical practice. STUDY TYPE:Prospective. POPULATION:13 healthy subjects and 22 patients. FIELD STRENGTH/SEQUENCES:1.5 T and 3 T/3D multiecho gradient-recalled echo (GRE) sequence. ASSESSMENT:Data were acquired using a 3D GRE sequence with an out-of-phase echo spacing with respect to each other. All odd echoes that were in-phase (IP) were used to initialize the fat-water separation and field estimation (T2 *-IDEAL) before performing QSM. Liver QSM was generated through an automated pipeline without manual intervention. This IP echo-based initialization method was compared with an existing graph cuts initialization method (simultaneous phase unwrapping and removal of chemical shift, SPURS) in healthy subjects (n = 5). Reproducibility was assessed over four scanners at two field strengths from two manufacturers using healthy subjects (n = 8). Clinical feasibility was evaluated in patients (n = 22). STATISTICAL TESTS:IP and SPURS initialization methods in both healthy subjects and patients were compared using paired t-test and linear regression analysis to assess processing time and region of interest (ROI) measurements. Reproducibility of QSM, R2 *, and proton density fat fraction (PDFF) among the four different scanners was assessed using linear regression, Bland-Altman analysis, and the intraclass correlation coefficient (ICC). RESULTS:Liver QSM using the IP method was found to be ~5.5 times faster than SPURS (P < 0.05) in initializing T2 *-IDEAL with similar outputs. Liver QSM using the IP method were reproducibly generated in all four scanners (average coefficient of determination 0.95, average slope 0.90, average bias 0.002 ppm, 95% limits of agreement between -0.06 to 0.07 ppm, ICC 0.97). DATA CONCLUSION:Use of IP echo-based initialization enables robust water/fat separation and field estimation for automated, rapid, and reproducible liver QSM for clinical applications. LEVEL OF EVIDENCE:1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:725-732.
| S-EPMC6929208 | biostudies-literature
Project description:BackgroundQuantitative susceptibility mapping (QSM) uses prior information to reconstruct maps, but prior information may not show pathology and introduce inconsistencies with susceptibility maps, degrade image quality and inadvertently smoothing image features.PurposeTo develop a local field data-driven QSM reconstruction that does not depend on spatial edge prior information.Study typeRetrospective.Subjects, animal modelsA dataset from 2016 ISMRM QSM Challenge, 11 patients with glioblastoma, a patient with microbleeds and porcine heart.Sequence/field strength3D gradient echo sequence on 3T and 7T scanners.AssessmentAccuracy was compared to Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS), and several published techniques using region of interest (ROI) measurements, root-mean-squared error (RMSE), structural similarity index metric (SSIM), and high-frequency error norm (HFEN). Numerical ranking and semiquantitative image grading was performed by three expert observers to assess overall image quality (IQ) and image sharpness (IS).Statistical testsBland-Altman, Friedman test, and Conover multiple comparisons.ResultsLoss adaptive dipole inversion (LADI) (β = 0.82, R2 = 0.96), morphology-enabled dipole inversion (MEDI) (β = 0.91, R2 = 0.97), and fast nonlinear susceptibility inversion (FANSI) (β = 0.81, R2 = 0.98) had excellent correlation with COSMOS and no bias was detected (bias = 0.006 ± 0.014, P < 0.05). In glioblastoma patients, LADI showed consistently better performance (IQGrade = 2.6 ± 0.4, ISGrade = 2.6 ± 0.3, IQRank = 3.5 ± 0.4, ISRank = 3.9 ± 0.2) compared with MEDI (IQGrade = 2.1 ± 0.3, ISGrade = 2 ± 0.5, IQRank = 2.4 ± 0.5, ISRank = 2.8 ± 0.2) and FANSI (IQGrade = 2.2 ± 0.5, ISGrade = 2 ± 0.4, IQRank = 2.8 ± 0.3, ISRank = 2.1 ± 0.2). Dark artifact visible near the infarcted region in MEDI (InfMEDI = -0.27 ± 0.06 ppm) was better mitigated by FANSI (InfFANSI-TGV = -0.17 ± 0.05 ppm) and LADI (InfLADI = -0.18 ± 0.05 ppm).ConclusionFor neuroimaging applications, LADI preserved image sharpness and fine features in glioblastoma and microbleed patients. LADI performed better at mitigating artifacts in cardiac QSM.Evidence level4 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:823-835.
| S-EPMC8034229 | biostudies-literature
Project description:Adaptive Total Field Inversion is described for quantitative susceptibility mapping (QSM) reconstruction from total field data through a spatially adaptive suppression of shadow artifacts through spatially adaptive regularization. The regularization for shadow suppression consists of penalizing low-frequency components of susceptibility in regions of small susceptibility contrasts as estimated by R2∗ derived signal intensity. Compared with a conventional local field method and two previously proposed regularized total field inversion methods, improvements were demonstrated in phantoms and subjects without and with hemorrhages. This algorithm, named TFIR, demonstrates the lowest error in numerical and gadolinium phantom datasets. In COSMOS data, TFIR performs well in matching ground truth in high-susceptibility regions. For patient data, TFIR comes close to meeting the quality of the reference local field method and outperforms other total field techniques in both clinical scores and shadow reduction.
| S-EPMC7522736 | biostudies-literature
Project description:To apply quantitative susceptibility mapping (QSM) in the basal ganglia of patients with multiple sclerosis (MS) and relate the findings to R2* mapping with regard to the sensitivity for clinical and morphologic measures of disease severity.The local ethics committee approved this study, and all subjects gave written informed consent. Sixty-eight patients (26 with clinically isolated syndrome, 42 with relapsing-remitting MS) and 23 control subjects underwent 3-T magnetic resonance (MR) imaging. Susceptibility and R2* maps were reconstructed from the same three-dimensional multiecho spoiled gradient-echo sequence. Mean susceptibilities and R2* rates were measured in the basal ganglia and were compared between different phenotypes of the disease (clinically isolated syndrome, MS) and the control subjects by using analysis of variance, and regressing analysis was used to identify independent predictors.Compared with control subjects, patients with MS and clinically isolated syndrome had increased (more paramagnetic) magnetic susceptibilities in the basal ganglia. R2* mapping proved less sensitive than QSM regarding group differences. The strongest predictor of magnetic susceptibility was age. Susceptibilities were higher with increasing neurologic deficits (r = 0.34, P < .01) and lower with normalized volumes of gray matter (r = -0.35, P < .005) and the cortex (r = -0.35, P < .005).QSM provides superior sensitivity over R2* mapping in the detection of MS-related tissue changes in the basal ganglia. With QSM but not with R2* mapping, changes were already observed in patients with clinically isolated syndrome, which suggests that QSM can serve as a sensitive measure at the earliest stage of the disease.
| S-EPMC3632806 | biostudies-other
Project description:Various regularization methods have been proposed for single-orientation quantitative susceptibility mapping (QSM), which is an ill-posed magnetic field to susceptibility source inverse problem. Noise amplification, a major issue in inverse problems, manifests as streaking artifacts and quantification errors in QSM and has not been comparatively evaluated in these algorithms. In this paper, various QSM methods were systematically categorized for noise analysis. Six representative QSM methods were selected from four categories: two non-Bayesian methods with alteration or approximation of the dipole kernel to overcome the ill conditioning; four Bayesian methods using a general mathematical prior or a specific physical structure prior to select a unique solution, and using a data fidelity term with or without noise weighting. The effects of noise in these QSM methods were evaluated by reconstruction errors in simulation and image quality in 50 consecutive human subjects. Bayesian QSM methods with noise weighting consistently reduced root mean squared errors in numerical simulations and increased image quality scores in the human brain images, when compared to non-Bayesian methods and to corresponding Bayesian methods without noise weighting (p ≤ 0.001). In summary, noise effects in QSM can be reduced using Bayesian methods with proper noise weighting.
| S-EPMC5553691 | biostudies-other
Project description:Quantitative Susceptibility Mapping (QSM) estimates tissue magnetic susceptibility distributions from Magnetic Resonance (MR) phase measurements by solving an ill-posed dipole inversion problem. Conventional single orientation QSM methods usually employ regularization strategies to stabilize such inversion, but may suffer from streaking artifacts or over-smoothing. Multiple orientation QSM such as calculation of susceptibility through multiple orientation sampling (COSMOS) can give well-conditioned inversion and an artifact free solution but has expensive acquisition costs. On the other hand, Convolutional Neural Networks (CNN) show great potential for medical image reconstruction, albeit often with limited interpretability. Here, we present a Learned Proximal Convolutional Neural Network (LP-CNN) for solving the ill-posed QSM dipole inversion problem in an iterative proximal gradient descent fashion. This approach combines the strengths of data-driven restoration priors and the clear interpretability of iterative solvers that can take into account the physical model of dipole convolution. During training, our LP-CNN learns an implicit regularizer via its proximal, enabling the decoupling between the forward operator and the data-driven parameters in the reconstruction algorithm. More importantly, this framework is believed to be the first deep learning QSM approach that can naturally handle an arbitrary number of phase input measurements without the need for any ad-hoc rotation or re-training. We demonstrate that the LP-CNN provides state-of-the-art reconstruction results compared to both traditional and deep learning methods while allowing for more flexibility in the reconstruction process.
| S-EPMC7647124 | biostudies-literature
Project description:Background and purposeQuantitative susceptibility mapping using MR imaging can assess changes in brain tissue structure and composition. This report presents preliminary results demonstrating changes in tissue magnetic susceptibility after sports-related concussion.Materials and methodsLongitudinal quantitative susceptibility mapping metrics were produced from imaging data acquired from cohorts of concussed and control football athletes. One hundred thirty-six quantitative susceptibility mapping datasets were analyzed across 3 separate visits (24 hours after injury, 8 days postinjury, and 6 months postinjury). Longitudinal quantitative susceptibility mapping group analyses were performed on stability-thresholded brain tissue compartments and selected subregions. Clinical concussion metrics were also measured longitudinally in both cohorts and compared with the measured quantitative susceptibility mapping.ResultsStatistically significant increases in white matter susceptibility were identified in the concussed athlete group during the acute (24 hour) and subacute (day 8) period. These effects were most prominent at the 8-day visit but recovered and showed no significant difference from controls at the 6-month visit. The subcortical gray matter showed no statistically significant group differences. Observed susceptibility changes after concussion appeared to outlast self-reported clinical recovery metrics at a group level. At an individual subject level, susceptibility increases within the white matter showed statistically significant correlations with return-to-play durations.ConclusionsThe results of this preliminary investigation suggest that sports-related concussion can induce physiologic changes to brain tissue that can be detected using MR imaging-based magnetic susceptibility estimates. In group analyses, the observed tissue changes appear to persist beyond those detected on clinical outcome assessments and were associated with return-to-play duration after sports-related concussion.
| S-EPMC6055518 | biostudies-literature
Project description:To assess quantitative susceptibility mapping (QSM) for reducing the inconsistency of standard magnetic resonance (MR) imaging sequences in measurements of cerebral microbleed burden.This retrospective study was HIPAA compliant and institutional review board approved. Ten patients (5.6%) were selected from among 178 consecutive patients suspected of having experienced a stroke who were imaged with a multiecho gradient-echo sequence at 3.0 T and who had cerebral microbleeds on T2*-weighted images. QSM was performed for various ranges of echo time by using both the magnitude and phase components in the morphology-enabled dipole inversion method. Cerebral microbleed size was measured by two neuroradiologists on QSM images, T2*-weighted images, susceptibility-weighted (SW) images, and R2* maps calculated by using different echo times. The sum of susceptibility over a region containing a cerebral microbleed was also estimated on QSM images as its total susceptibility. Measurement differences were assessed by using the Student t test and the F test; P < .05 was considered to indicate a statistically significant difference.When echo time was increased from approximately 20 to 40 msec, the measured cerebral microbleed volume increased by mean factors of 1.49 ± 0.86 (standard deviation), 1.64 ± 0.84, 2.30 ± 1.20, and 2.30 ± 1.19 for QSM, R2*, T2*-weighted, and SW images, respectively (P < .01). However, the measured total susceptibility with QSM did not show significant change over echo time (P = .31), and the variation was significantly smaller than any of the volume increases (P < .01 for each).The total susceptibility of a cerebral microbleed measured by using QSM is a physical property that is independent of echo time.
| S-EPMC3244668 | biostudies-other
Project description:This study explored whether autoregulatory shifts in cerebral blood volume induce susceptibility changes large enough to be depicted by quantitative susceptibility mapping. Eight healthy subjects underwent fast quantitative susceptibility mapping at 3T while lying down to slowly decrease mean arterial pressure. A linear relationship between mean arterial pressure and susceptibility was observed in cortical and subcortical structures, likely representing vessels involved in autoregulation. The slope of this relationship is assumed to indicate the extent of cerebral vascular compliance.
| S-EPMC6422309 | biostudies-literature
Project description:PurposeTo assess quantitative susceptibility mapping (QSM) in the depiction of the subthalamic nucleus (STN) by using 3-T magnetic resonance (MR) imaging.Materials and methodsThis study was HIPAA compliant and institutional review board approved. Ten healthy subjects (five men, five women; mean age, 24 years ± 3 [standard deviation]; age range, 21-33 years) and eight patients with Parkinson disease (five men, three women; mean age, 57 years ± 14; age range, 25-69 years) who were referred by neurologists for preoperative navigation MR imaging prior to deep brain stimulator placement were included in this study. T2-weighted (T2w), T2*-weighted (T2*w), R2* mapping (R2*), phase, susceptibility-weighted (SW), and QSM images were reconstructed for STN depiction. Qualitative visualization scores of STN and internal globus pallidus (GPi) were recorded by two neuroradiologists on all images. Contrast-to-noise ratios (CNRs) of the STN and GPi were also measured. Measurement differences were assessed by using the Wilcoxon rank sum test and the signed rank test.ResultsQualitative scores were significantly higher on QSM images than on T2w, T2*w, R2*, phase, or SW images (P < .05) for STN and GPi visualization. Median CNR was 6.4 and 10.7 times higher on QSM images than on T2w images for differentiation of STN from the zona incerta and substantia nigra, respectively, and was 22.7 and 9.1 times higher on QSM images than on T2w images for differentiation of GPi from the internal capsule and external globus pallidus, respectively. CNR differences between QSM images and all other images were significant (P < .01).ConclusionQSM at 3-T MR imaging performs significantly better than current standard-of-care sequences in the depiction of the STN.
| S-EPMC3781358 | biostudies-literature