Improved geometric accuracy of whole body diffusion-weighted imaging at 1.5T and 3T using reverse polarity gradients.
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ABSTRACT:
SUBMITTER: Sjoholm T
PROVIDER: S-EPMC9270424 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:INTRODUCTION:Diffusion Weighted Imaging (DWI), which is based on Echo Planar Imaging (EPI) protocols, is becoming increasingly important for neurosurgical applications. However, its use in this context is limited in part by significant spatial distortion inherent to EPI. METHOD:We evaluated an efficient algorithm for EPI distortion correction (EPIC) across 814 DWI scans from 250 brain tumor patients and quantified the magnitude of geometric distortion for whole brain and multiple brain regions. RESULTS:Evaluation of the algorithm's performance revealed significantly higher mutual information between T1-weighted pre-contrast images and corrected b = 0 images than the uncorrected b = 0 images (p < 0.001). The distortion magnitude across all voxels revealed a median EPI distortion effect of 2.1 mm, ranging from 1.2 mm to 5.9 mm, the 5th and 95th percentile, respectively. Regions adjacent to bone-air interfaces, such as the orbitofrontal cortex, temporal poles, and brain stem, were the regions most severely affected by DWI distortion. CONCLUSION:Using EPIC to estimate the degree of distortion in 814 DWI brain tumor images enabled the creation of a topographic atlas of DWI distortion across the brain. The degree of displacement of tumors boundaries in uncorrected images is severe but can be corrected for using EPIC. Our results support the use of distortion correction to ensure accurate and careful application of DWI to neurosurgical practice.
| S-EPMC4814112 | biostudies-literature
Project description:PurposeThe in vivo probing of restricted diffusion effects in large lipid droplets on a clinical MR scanner remains a major challenge due to the need for high b-values and long diffusion times. This work proposes a methodology to probe mean lipid droplet sizes using diffusion-weighted MRS (DW-MRS) at 3T.MethodsAn analytical expression for restricted diffusion was used. Simulations were performed to evaluate the noise performance and the influence of particle size distribution. To validate the method, oil-in-water emulsions were prepared and examined using DW-MRS, laser deflection and light microscopy. The tibia bone marrow was scanned in volunteers to test the method repeatability and characterize microstructural differences at different locations.ResultsThe simulations showed accurate and precise droplet size estimation when a sufficient SNR is reached with minor dependence on the size distribution. In phantoms, a good correlation between the measured droplet sizes by DW-MRS and by laser deflection (R2 = 0.98; P = 0.01) and microscopy (R2 = 0.99; P < 0.01) measurements was obtained. A mean coefficient of variation of 11.5 % was found for the lipid droplet diameter in vivo. The average diameter was smaller at a proximal (50.1 ± 7.3 µm) compared with a distal tibia location (61.1 ± 6.8 µm) (P < 0.01).ConclusionThe presented methods were able to probe restricted diffusion effects in lipid droplets using DW-MRS and to estimate lipid droplet size. The methodology was validated using phantoms and the in vivo feasibility in bone marrow was shown based on a good repeatability and findings in agreement with literature.
| S-EPMC6519235 | biostudies-literature
Project description:Single-shot diffusion-weighted (DW) echo planar imaging (EPI), which is commonly used for imaging the thyroid, is characterised by severe blurring and distortion. The objectives of this work were: 1, to show that a reduced-field of view (r-FOV) DW EPI technique can improve image quality; and 2, to investigate the effect of different reconstruction strategies on the resulting apparent diffusion coefficients (ADCs).We implemented a single-shot, r-FOV DW EPI technique with a two-dimensional radiofrequency excitation pulse for DW imaging of the thyroid at 3T. Images were reconstructed using root sum of squares (SOS) and an optimal-B1 reconstruction (OBR). Phantom and in vivo experiments were performed to compare r-FOV and conventional full-FOV DW EPI with root SOS and OBR.r-FOV with OBR substantially improved image quality at 3T. In phantoms, r-FOV gave more accurate ADCs than full-FOV. In vivo r-FOV always gave lower ADC values with respect to the full-FOV technique irrespective of the reconstruction used and whether only two or multiple b-values were used to compute the ADCs.r-FOV DW EPI can reduce image blurring and distortion at the expense of a low signal-to-noise ratio. OBR is a promising reconstruction technique for accurate ADC measurements in lower signal-to-noise ratio regimes, although further studies are needed to characterise its performance.DW imaging of the thyroid at 3T could potentially benefit from r-FOV acquisition strategies, such as the r-FOV DW EPI technique proposed in this paper.
| S-EPMC3745056 | biostudies-other
Project description:PurposeInhomogeneities in the static magnetic field (B0 ) deteriorate MRSI data quality by lowering the spectral resolution and SNR. MRSI with low spatial resolution is also prone to lipid bleeding. These problems are increasingly problematic at ultra-high fields. An approach to tackling these challenges independent of B0 -shim hardware is to increase the spatial resolution. Therefore, we investigated the effect of improved spatial resolution on spectral quality and quantification at 4 field strengths.MethodsWhole-brain MRSI data was simulated for 3 spatial resolutions and 4 B0 s based on experimentally acquired MRI data and simulated free induction decay signals of metabolites and lipids. To compare the spectral quality and quantification, we derived SNR normalized to the voxel size (nSNR), linewidth and metabolite concentration ratios, their Cramer-Rao-lower-bounds (CRLBs), and the absolute percentage error (APE) of estimated concentrations compared to the gold standard for the whole-brain and 8 brain regions.ResultsAt 7T, we found up to a 3.4-fold improved nSNR (in the frontal lobe) and a 2.8-fold reduced linewidth (in the temporal lobe) for 1 cm3 versus 0.25 cm3 resolution. This effect was much more pronounced at higher and less homogenous B0 (1.6-fold improved nSNR and 1.8-fold improved linewidth in the parietal lobe at 3T). This had direct implications for quantification: the volume of reliably quantified spectra increased with resolution by 1.2-fold and 1.5-fold (when thresholded by CRLBs or APE, respectively).ConclusionMRSI data quality benefits from increased spatial resolution particularly at higher B0 , and leads to more reliable metabolite quantification. In conjunction with the development of better B0 shimming hardware, this will enable robust whole-brain MRSI at ultra-high field.
| S-EPMC6563461 | biostudies-literature
Project description:PurposeVolumetric liver fat fraction (VLFF) measurements were made using the HepaFat-Scan® technique at 1.5T and 3T to determine the agreement between the measurements obtained at the two fields.MethodsSixty patients with type 2 diabetes (67% male, mean age 50.92 ± 6.56yrs) and thirty healthy volunteers (50% male, mean age 48.63 ± 6.32yrs) were scanned on 1.5T Aera and 3T Skyra (Siemens, Erlangen, Germany) MRI scanners on the same day using the HepaFat-Scan® gradient echo protocol with modification of echo times for 3T (TEs 2.38, 4.76, 7.14 ms at 1.5T and 1.2, 2.4, 3.6 ms at 3T). The 3T analyses were performed independently of the 1.5T analyses by a different analyst, blinded from the 1.5T results. Data were analysed for agreement and bias using Bland-Altman methods and intraclass correlation coefficients (ICC). A second cohort of 17 participants underwent interstudy repeatability assessment of VLFF measured by HepaFat-Scan® at 3T.ResultsA small, but statistically significant mean bias of 0.48% was observed between 3T and 1.5T with 95% limits of agreement -2.2% to 3.2% VLFF. The ICC for agreement between field strengths was 0.983 (95% CI 0.972-0.989). In the repeatability cohort studied at 3T the repeatability coefficient was 4.2%. The ICC for agreement was 0.971 (95% CI 0.921-0.989).ConclusionThere is minimal bias and excellent agreement between the measures of VLFF using the HepaFat-Scan® at 1.5 and 3T. The test retest repeatability coefficient at 3T is comparable to the 95% limits of agreement between 1.5T and 3T suggesting that measurements can be made interchangeably between field strengths.
| S-EPMC8277031 | biostudies-literature
Project description:Background and purposeThe differentiation between Parkinson disease and atypical parkinsonian syndromes can be challenging in clinical practice, especially in early disease stages. Brain MR imaging can help to increase certainty about the diagnosis. Our goal was to evaluate the added value of SWI in relation to conventional 3T brain MR imaging for the diagnostic work-up of early-stage parkinsonism.Materials and methodsThis was a prospective observational cohort study of 65 patients presenting with parkinsonism but with an uncertain initial clinical diagnosis. At baseline, 3T brain MR imaging with conventional and SWI sequences was performed. After clinical follow-up, probable diagnoses could be made in 56 patients, 38 patients diagnosed with Parkinson disease and 18 patients diagnosed with atypical parkinsonian syndromes, including 12 patients diagnosed with multiple system atrophy-parkinsonian form. In addition, 13 healthy controls were evaluated with SWI. Abnormal findings on conventional brain MR imaging were grouped into disease-specific scores. SWI was analyzed by a region-of-interest method of different brain structures. One-way ANOVA was performed to analyze group differences. Receiver operating characteristic analyses were performed to evaluate the diagnostic accuracy of conventional brain MR imaging separately and combined with SWI.ResultsDisease-specific scores of conventional brain MR imaging had a high specificity for atypical parkinsonian syndromes (80%-90%), but sensitivity was limited (50%-80%). The mean SWI signal intensity of the putamen was significantly lower for multiple system atrophy-parkinsonian form than for Parkinson disease and controls (P < .001). The presence of severe dorsal putaminal hypointensity improved the accuracy of brain MR imaging: The area under the curve was increased from 0.75 to 0.83 for identifying multiple system atrophy-parkinsonian form, and it was increased from 0.76 to 0.82 for identifying atypical parkinsonian syndromes as a group.ConclusionsSWI improves the diagnostic accuracy of 3T brain MR imaging in the work-up of parkinsonism by identifying severe putaminal hypointensity as a sign indicative of multiple system atrophy-parkinsonian form.
| S-EPMC8013057 | biostudies-literature
Project description:PurposeMUSSELS is a one-step iterative reconstruction method for multishot diffusion weighted (msDW) imaging. The current work presents an efficient implementation, termed IRLS MUSSELS, that enables faster reconstruction to enhance its utility for high-resolution diffusion MRI studies.MethodsThe recently proposed MUSSELS reconstruction belongs to a new class of parallel imaging-based methods that recover artifact-free DWIs from msDW data without needing phase compensation. The reconstruction is achieved via structured low-rank matrix completion algorithms, which are computationally demanding due to the large size of the Hankel matrices and their associated computations involving singular value decompositions. Because of this, computational demands of the MUSSELS reconstruction scales as the matrix size and the number of shots increases, which hinders its practical utility for high-resolution applications. In this work, we derive a computationally efficient MUSSELS formulation by modifying the iterative reweighted least squares (IRLS) method that were proposed earlier to solve such problems. Using whole-brain in vivo data, we show the utility of the IRLS MUSSELS for routine high-resolution studies with reduced computational burden.ResultsIRLS MUSSELS provides about five times faster reconstruction for matrix sizes 192 × 192 and 256 × 256 compared to the earlier MUSSELS implementation. The widely employed conjugate symmetry priors can also be incorporated into IRLS MUSSELS to reduce blurring of the partial Fourier acquisitions, without incurring much computational burden.ConclusionsThe proposed method is observed to be computationally efficient to enable routine high-resolution studies. The computational complexity matches the traditional msDWI reconstruction methods and provides improved reconstruction results with the additional constraints.
| S-EPMC8045517 | biostudies-literature
Project description:Diffusion magnetic resonance images may suffer from geometric distortions due to susceptibility induced off resonance fields, which cause geometric mismatch with anatomical images and ultimately affect subsequent quantification of microstructural or connectivity indices. State-of-the art diffusion distortion correction methods typically require data acquired with reverse phase encoding directions, resulting in varying magnitudes and orientations of distortion, which allow estimation of an undistorted volume. Alternatively, additional field maps acquisitions can be used along with sequence information to determine warping fields. However, not all imaging protocols include these additional scans and cannot take advantage of state-of-the art distortion correction. To avoid additional acquisitions, structural MRI (undistorted scans) can be used as registration targets for intensity driven correction. In this study, we aim to (1) enable susceptibility distortion correction with historical and/or limited diffusion datasets that do not include specific sequences for distortion correction and (2) avoid the computationally intensive registration procedure typically required for distortion correction using structural scans. To achieve these aims, we use deep learning (3D U-nets) to synthesize an undistorted b0 image that matches geometry of structural T1w images and intensity contrasts from diffusion images. Importantly, the training dataset is heterogenous, consisting of varying acquisitions of both structural and diffusion. We apply our approach to a withheld test set and show that distortions are successfully corrected after processing. We quantitatively evaluate the proposed distortion correction and intensity-based registration against state-of-the-art distortion correction (FSL topup). The results illustrate that the proposed pipeline results in b0 images that are geometrically similar to non-distorted structural images, and more closely match state-of-the-art correction with additional acquisitions. In addition, we show generalizability of the proposed approach to datasets that were not in the original training / validation / testing datasets. These datasets included varying populations, contrasts, resolutions, and magnitudes and orientations of distortion and show efficacious distortion correction. The method is available as a Singularity container, source code, and an executable trained model to facilitate evaluation.
| S-EPMC7394453 | biostudies-literature
Project description:PurposeTo evaluate the precision profile (repeatability and reproducibility) of quantitative STEAM-MRS and to determine the relationships between multiple MR biomarkers of chronic liver disease in subjects with iron overload at both 1.5 Tesla (T) and 3T.MethodsMRS data were acquired in patients with known or suspected liver iron overload. Two STEAM-MRS sequences (multi-TE and multi-TE-TR) were acquired at both 1.5T and 3T (same day), including test-retest acquisition. Each acquisition enabled estimation of R1, R2, and FWHM (each separately for water and fat); and proton density fat fraction. The test-retest repeatability and reproducibility across acquisition modes (multi-TE vs. multi-TE-TR) of the estimates were evaluated using intraclass correlation coefficients, linear regression, and Bland-Altman analyses. Multi-parametric relationships between parameters at each field strength, across field strengths, and with liver iron concentration were also evaluated using linear and nonlinear regression.ResultsFifty-six (n = 56) subjects (10 to 73 years, 37 males/19 females) were successfully recruited. Both STEAM-MRS sequences demonstrated good-to-excellent precision (intraclass correlation coefficient ≥ 0.81) for the quantification of R1water , R2water , FWHMwater , and proton density fat fraction at both 1.5T and 3T. Additionally, several moderate (R2 = 0.50 to 0.69) to high (R2 ≥ 0.70) correlations were observed between biomarkers, across field strengths, and with liver iron concentration.ConclusionsOver a broad range of liver iron concentration, STEAM-MRS enables rapid and precise measurement of multiple biomarkers of chronic liver disease. By evaluating the multi-parametric relationships between biomarkers, this work may advance the comprehensive MRS-based assessment of chronic liver disease and may help establish biomarkers of chronic liver disease.
| S-EPMC8858702 | biostudies-literature
Project description:To evaluate the incremental value of diffusion-weighted (DW) imaging and apparent diffusion coefficient (ADC) mapping in relation to conventional breast magnetic resonance (MR) imaging in the characterization of benign versus malignant breast lesions at 3.0 T.This retrospective HIPAA-compliant study was approved by the institutional review board, with the requirement for informed patient consent waived. Of 550 consecutive patients who underwent bilateral breast MR imaging over a 10-month period, 93 women with 101 lesions met the following study inclusion criteria: They had undergone three-dimensional (3D) high-spatial-resolution T1-weighted contrast material-enhanced MR imaging, dynamic contrast-enhanced MR imaging, and DW imaging examinations at 3.0 T and either had received a pathologic analysis-proven diagnosis (96 lesions) or had lesion stability confirmed at more than 2 years of follow-up (five lesions). DW images were acquired with b values of 0 and 600 sec/mm(2). Regions of interest were drawn on ADC maps of breast lesions and normal glandular tissue. Morphologic features (margin, enhancement pattern), dynamic contrast-enhanced MR results (semiquantitative kinetic curve data), absolute ADCs, and glandular tissue-normalized ADCs were included in multivariate models to predict a diagnosis of benign versus malignant lesion.Forty-one (44%) of the 93 patients were premenopausal, and 52 (56%) were postmenopausal. Thirty-three (32.7%) of the 101 lesions were benign, and 68 (67.3%) were malignant. Normalized ADCs were significantly different between the benign (mean ADC, 1.1 x 10(-3) mm(2)/sec +/- 0.4 [standard deviation]) and malignant (mean ADC, 0.55 x 10(-3) mm(2)/sec +/- 0.16) lesions (P < .001). Adding normalized ADCs to the 3D T1-weighted and dynamic contrast-enhanced MR data improved the diagnostic performance of MR imaging: The area under the receiver operating characteristic curve improved from 0.89 to 0.98, and the false-positive rate decreased from 36% (nine of 25 lesions) to 24% (six of 25 lesions).DW imaging with glandular tissue-normalized ADC assessment improves the characterization of breast lesions beyond the characterization achieved with conventional 3D T1-weighted and dynamic contrast-enhanced MR imaging at 3.0 T.
| S-EPMC2897691 | biostudies-other