55 research outputs found

    The impact of signal-to-noise ratio, diffusion-weighted directions and image resolution in cardiac diffusion tensor imaging - insights from the ex-vivo rat heart

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    Background: Cardiac diffusion tensor imaging (DTI) is limited by scan time and signal-to-noise (SNR) restrictions. This invariably leads to a trade-off between the number of averages, diffusion-weighted directions (ND), and image resolution. Systematic evaluation of these parameters is therefore important for adoption of cardiac DTI in clinical routine where time is a key constraint. Methods: High quality reference DTI data were acquired in five ex-vivo rat hearts. We then retrospectively set 2 ≤ SNR ≤ 97, 7 ≤ ND ≤ 61, varied the voxel volume by up to 192-fold and investigated the impact on the accuracy and precision of commonly derived parameters. Results: For maximal scan efficiency, the accuracy and precision of the mean diffusivity is optimised when SNR is maximised at the expense of ND. With typical parameter settings used clinically, we estimate that fractional anisotropy may be overestimated by up to 13% with an uncertainty of ±30%, while the precision of the sheetlet angles may be as poor as ±31°. Although the helix angle has better precision of ±14°, the transmural range of helix angles may be under-estimated by up to 30° in apical and basal slices, due to partial volume and tapering myocardial geometry. Conclusions: These findings inform a baseline of understanding upon which further issues inherent to in-vivo cardiac DTI, such as motion, strain and perfusion, can be considered. Furthermore, the reported bias and reproducibility provides a context in which to assess cardiac DTI biomarkers

    Modulation of 11β-hydroxysteroid dehydrogenase as a strategy to reduce vascular inflammation

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    Atherosclerosis is a chronic inflammatory disease in which initial vascular damage leads to extensive macrophage and lymphocyte infiltration. Although acutely glucocorticoids suppress inflammation, chronic glucocorticoid excess worsens atherosclerosis, possibly by exacerbating systemic cardiovascular risk factors. However, glucocorticoid action within the lesion may reduce neointimal proliferation and inflammation. Glucocorticoid levels within cells do not necessarily reflect circulating levels due to pre-receptor metabolism by 11β-hydroxysteroid dehydrogenases (11β-HSDs). 11β-HSD2 converts active glucocorticoids into inert 11-keto forms. 11β-HSD1 catalyses the reverse reaction, regenerating active glucocorticoids. 11β-HSD2-deficiency/ inhibition causes hypertension, whereas deficiency/ inhibition of 11β-HSD1 generates a cardioprotective lipid profile and improves glycemic control. Importantly, 11β-HSD1-deficiency/ inhibition is atheroprotective, whereas 11β-HSD2-deficiency accelerates atherosclerosis. These effects are largely independent of systemic risk factors, reflecting modulation of glucocorticoid action and inflammation within the vasculature. Here, we consider whether evidence linking the 11β-HSDs to vascular inflammation suggests these isozymes are potential therapeutic targets in vascular injury and atherosclerosis

    Three dimensional first-pass myocardial perfusion imaging at 3T: feasibility study

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    <p>Abstract</p> <p>Background</p> <p>In patients with ischemic heart disease, accurate assessment of the extent of myocardial perfusion deficit may be important in predicting prognosis of clinical cardiac outcomes. The aim of this study was to compare the ability of three dimensional (3D) and of two dimensional (2D) multi-slice myocardial perfusion imaging (MPI) using cardiovascular magnetic resonance (CMR) in determining the size of defects, and to demonstrate the feasibility of 3D MPI in healthy volunteers at 3 Tesla.</p> <p>Methods</p> <p>A heart phantom was used to compare the accuracy of 3D and 2D multi-slice MPI in estimating the volume fraction of seven rubber insets which simulated transmural myocardial perfusion defects. Three sets of cross-sectional planes were acquired for 2D multi-slice imaging, where each set was shifted along the partition encoding direction by ± 10 mm. 3D first-pass contrast-enhanced (0.1 mmol/kg Gd-DTPA) MPI was performed in three volunteers with sensitivity encoding for six-fold acceleration. The upslope of the myocardial time-intensity-curve and peak SNR/CNR values were calculated.</p> <p>Results</p> <p>Mean/standard deviation of errors in estimating the volume fraction across the seven defects were -0.44/1.49%, 2.23/2.97%, and 2.59/3.18% in 3D, 2D 4-slice, and 2D 3-slice imaging, respectively. 3D MPI performed in healthy volunteers produced excellent quality images with whole left ventricular (LV) coverage. Peak SNR/CNR was 57.6 ± 22.0/37.5 ± 19.7 over all segments in the first eight slices.</p> <p>Conclusion</p> <p>3D performed better than 2D multi-slice MPI in estimating the size of perfusion defects in phantoms. Highly accelerated 3D MPI at 3T was feasible in volunteers, allowing whole LV coverage with excellent image quality and high SNR/CNR.</p

    Analysis protocols for MRI mapping of the blood oxygenation-sensitive parameters T(2)* and T(2) in the kidney

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    Renal hypoxia is generally accepted as a key pathophysiologic event in acute kidney injury of various origins and has also been suggested to play a role in the development of chronic kidney disease. Here we describe step-by-step data analysis protocols for MRI monitoring of renal oxygenation in rodents via the deoxyhemoglobin concentration sensitive MR parameters T(2)* and T(2)-a contrast mechanism known as the blood oxygenation level dependent (BOLD) effect.This chapter describes how to use the analysis tools provided by vendors of animal and clinical MR systems, as well as how to develop an analysis software. Aspects covered are: data quality checks, data exclusion, model fitting, fitting algorithm, starting values, effects of multiecho imaging, and result validation.This chapter is based upon work from the PARENCHIMA COST Action, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This experimental protocol chapter is complemented by two separate chapters describing the basic concept and data analysis

    Intramyocardial hemorrhage and microvascular obstruction after primary percutaneous coronary intervention

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    Reperfusion may cause intramyocardial hemorrhage (IMH) by extravasation of erythrocytes through severely damaged endothelial walls. The purpose of the study was to evaluate the clinical significance of IMH in relation to infarct size, microvascular obstruction (MVO) and function in patients after primary percutaneous intervention. Forty-five patients underwent cardiovascular MR imaging (CMR) 1 week and 4 months after primary stenting for a first acute myocardial infarction. T2-weighted spin-echo imaging (T2W) was used to assess infarct related edema and IMH, and delayed enhancement (DE) was used to assess infarct size and MVO. Cine CMR was used to assess left ventricular volumes and function at baseline and at 4 months follow-up. In 22 (49%) patients, IMH was detected as areas of attenuated signal in the core of the high signal intensity region on T2W images. Patients with IMH had larger infarcts, higher left ventricular volumes and lower ejection fraction. Contrast-to-noise ratio (CNR) between hyperintense periphery and the hypo-intense core of the T2W ischemic area correlated to peak CKMB, total infarct size and MVO size. Using univariable analysis, CNR predicted ejection fraction at baseline (β = −0.62, P = 0.003) and follow-up (β = −0.84, P < 0.001). However, after multivariable analysis, baseline ejection fraction and presence of MVO were the only parameters that predicted functional changes at follow-up. IMH was found in the majority of patients with MVO after reperfused myocardial infarction. It was closely related to markers of infarct size, MVO and function, but did not have prognostic significance beyond MVO

    3.0 T cardiovascular magnetic resonance in patients treated with coronary stenting for myocardial infarction: evaluation of short term safety and image quality

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    Purpose To evaluate safety and image quality of cardiovascular magnetic resonance (CMR) at 3.0 T in patients with coronary stents after myocardial infarction (MI), in comparison to the clinical standard at 1.5 T. Methods Twenty-five patients (21 men; 55 ± 9 years) with first MI treated with primary stenting, underwent 18 scans at 3.0 T and 18 scans at 1.5 T. Twenty-four scans were performed 4 ± 2 days and 12 scans 125 ± 23 days after MI. Cine (steady-state free precession) and late gadolinium-enhanced (LGE, segmented inversion-recovery gradient echo) images were acquired. Patient safety and image artifacts were evaluated, and in 16 patients stent position was assessed during repeat catheterization. Additionally, image quality was scored from 1 (poor quality) to 4 (excellent quality). Results There were no clinical events within 30 days of CMR at 3.0 T or 1.5 T, and no stent migration occurred. At 3.0 T, image quality of cine studies was clinically useful in all, but not sufficient for quantitative analysis in 44% of the scans, due to stent (6/18 scans), flow (7/18 scans) and/or dark band artifacts (8/18 scans). Image quality of LGE images at 3.0 T was not sufficient for quantitative analysis in 53%, and not clinically useful in 12%. At 1.5 T, all cine and LGE images were quantitatively analyzable. Conclusion 3.0 T is safe in the acute and chronic phase after MI treated with primary stenting. Although cine imaging at 3.0 T is suitable for clinical use, quantitative analysis and LGE imaging is less reliable than at 1.5 T. Further optimization of pulse sequences at 3.0 T is essential

    Data preparation protocol for low signal-to-noise ratio fluorine-19 MRI

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    Fluorine-19 MRI shows great promise for a wide range of applications including renal imaging, yet the typically low signal-to-noise ratios and sparse signal distribution necessitate a thorough data preparation.This chapter describes a general data preparation workflow for fluorine MRI experiments. The main processing steps are: (1) estimation of noise level, (2) correction of noise-induced bias and (3) background subtraction. The protocol is supplemented by an example script and toolbox available online.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concept and experimental procedure

    Denoising for improved parametric MRI of the kidney: protocol for nonlocal means filtering

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    In order to tackle the challenges caused by the variability in estimated MRI parameters (e.g., T(2)* and T(2)) due to low SNR a number of strategies can be followed. One approach is postprocessing of the acquired data with a filter. The basic idea is that MR images possess a local spatial structure that is characterized by equal, or at least similar, noise-free signal values in vicinities of a location. Then, local averaging of the signal reduces the noise component of the signal. In contrast, nonlocal means filtering defines the weights for averaging not only within the local vicinity, bur it compares the image intensities between all voxels to define "nonlocal" weights. Furthermore, it generally compares not only single-voxel intensities but small spatial patches of the data to better account for extended similar patterns. Here we describe how to use an open source NLM filter tool to denoise 2D MR image series of the kidney used for parametric mapping of the relaxation times T(2)* and T(2).This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers
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