17 research outputs found
Bias, Repeatability and Reproducibility of Liver T1 Mapping With Variable Flip Angles.
Funder: National Institute for Health Research; Id: http://dx.doi.org/10.13039/501100000272BACKGROUND: Three-dimensional variable flip angle (VFA) methods are commonly used for T1 mapping of the liver, but there is no data on the accuracy, repeatability, and reproducibility of this technique in this organ in a multivendor setting. PURPOSE: To measure bias, repeatability, and reproducibility of VFA T1 mapping in the liver. STUDY TYPE: Prospective observational. POPULATION: Eight healthy volunteers, four women, with no known liver disease. FIELD STRENGTH/SEQUENCE: 1.5-T and 3.0-T; three-dimensional steady-state spoiled gradient echo with VFAs; Look-Locker. ASSESSMENT: Traveling volunteers were scanned twice each (30 minutes to 3 months apart) on six MRI scanners from three vendors (GE Healthcare, Philips Medical Systems, and Siemens Healthineers) at two field strengths. The maximum period between the first and last scans among all volunteers was 9 months. Volunteers were instructed to abstain from alcohol intake for at least 72 hours prior to each scan and avoid high cholesterol foods on the day of the scan. STATISTICAL TESTS: Repeated measures ANOVA, Student t-test, Levene's test of variances, and 95% significance level. The percent error relative to literature liver T1 in healthy volunteers was used to assess bias. The relative error (RE) due to intrascanner and interscanner variation in T1 measurements was used to assess repeatability and reproducibility. RESULTS: The 95% confidence interval (CI) on the mean bias and mean repeatability RE of VFA T1 in the healthy liver was 34 ± 6% and 10 ± 3%, respectively. The 95% CI on the mean reproducibility RE at 1.5 T and 3.0 T was 29 ± 7% and 25 ± 4%, respectively. DATA CONCLUSION: Bias, repeatability, and reproducibility of VFA T1 mapping in the liver in a multivendor setting are similar to those reported for breast, prostate, and brain. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1
Contrast-agent-based perfusion MRI code repository and testing framework: ISMRM Open Science Initiative for Perfusion Imaging (OSIPI)
Purpose
Software has a substantial impact on quantitative perfusion MRI values. The lack of generally accepted implementations, code sharing and transparent testing reduces reproducibility, hindering the use of perfusion MRI in clinical trials. To address these issues, the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI) aimed to establish a community-led, centralized repository for sharing open-source code for processing contrast-based perfusion imaging, incorporating an open-source testing framework.
Methods
A repository was established on the OSIPI GitHub website. Python was chosen as the target software language. Calls for code contributions were made to OSIPI members, the ISMRM Perfusion Study Group, and publicly via OSIPI websites. An automated unit-testing framework was implemented to evaluate the output of code contributions, including visual representation of the results.
Results
The repository hosts 86 implementations of perfusion processing steps contributed by 12 individuals or teams. These cover all core aspects of DCE- and DSC-MRI processing, including multiple implementations of the same functionality. Tests were developed for 52 implementations, covering five analysis steps. For T1 mapping, signal-to-concentration conversion and population AIF functions, different implementations resulted in near-identical output values. For the five pharmacokinetic models tested (Tofts, extended Tofts-Kety, Patlak, two-compartment exchange, and two-compartment uptake), differences in output parameters were observed between contributions.
Conclusions
The OSIPI DCE-DSC code repository represents a novel community-led model for code sharing and testing. The repository facilitates the re-use of existing code and the benchmarking of new code, promoting enhanced reproducibility in quantitative perfusion imaging
Effect of partial H2O-D2O replacement on the anisotropy of transverse proton spin relaxation in bovine articular cartilage
Anisotropy of transverse proton spin relaxation in collagen-rich tissues like cartilage and tendon is a well-known phenomenon that manifests itself as the "magic-angle" effect in magnetic resonance images of these tissues. It is usually attributed to the non-zero averaging of intra-molecular dipolar interactions in water molecules bound to oriented collagen fibers. One way to manipulate the contributions of these interactions to spin relaxation is by partially replacing the water in the cartilage sample with deuterium oxide. It is known that dipolar interactions in deuterated solutions are weaker, resulting in a decrease in proton relaxation rates. In this work, we investigate the effects of deuteration on the longitudinal and the isotropic and anisotropic contributions to transverse relaxation of water protons in bovine articular cartilage. We demonstrate that the anisotropy of transverse proton spin relaxation in articular cartilage is independent of the degree of deuteration, bringing into question some of the assumptions currently held over the origins of relaxation anisotropy in oriented tissues
Role of Functional MRI in Liver SBRT: Current Use and Future Directions
Stereotactic body radiation therapy (SBRT) is an emerging treatment for liver cancers whereby large doses of radiation can be delivered precisely to target lesions in 3–5 fractions. The target dose is limited by the dose that can be safely delivered to the non-tumour liver, which depends on the baseline liver functional reserve. Current liver SBRT guidelines assume uniform liver function in the non-tumour liver. However, the assumption of uniform liver function is false in liver disease due to the presence of cirrhosis, damage due to previous chemo- or ablative therapies or irradiation, and fatty liver disease. Anatomical information from magnetic resonance imaging (MRI) is increasingly being used for SBRT planning. While its current use is limited to the identification of target location and size, functional MRI techniques also offer the ability to quantify and spatially map liver tissue microstructure and function. This review summarises and discusses the advantages offered by functional MRI methods for SBRT treatment planning and the potential for adaptive SBRT workflows
Role of Functional MRI in Liver SBRT: Current Use and Future Directions
Stereotactic body radiation therapy (SBRT) is an emerging treatment for liver cancers whereby large doses of radiation can be delivered precisely to target lesions in 3–5 fractions. The target dose is limited by the dose that can be safely delivered to the non-tumour liver, which depends on the baseline liver functional reserve. Current liver SBRT guidelines assume uniform liver function in the non-tumour liver. However, the assumption of uniform liver function is false in liver disease due to the presence of cirrhosis, damage due to previous chemo- or ablative therapies or irradiation, and fatty liver disease. Anatomical information from magnetic resonance imaging (MRI) is increasingly being used for SBRT planning. While its current use is limited to the identification of target location and size, functional MRI techniques also offer the ability to quantify and spatially map liver tissue microstructure and function. This review summarises and discusses the advantages offered by functional MRI methods for SBRT treatment planning and the potential for adaptive SBRT workflows
Proton R<sub>1</sub> and R<sub>2</sub> as a function of %molar concentration of D<sub>2</sub>O in the D<sub>2</sub>O-PBS and H<sub>2</sub>O-PBS solutions fitted using least-squares algorithm.
<p>Proton R<sub>1</sub> and R<sub>2</sub> as a function of %molar concentration of D<sub>2</sub>O in the D<sub>2</sub>O-PBS and H<sub>2</sub>O-PBS solutions fitted using least-squares algorithm.</p
Regions of interest ROI A and ROI B are shown on a R<sub>1</sub> relaxation map of a sample.
<p>P1 and P2 are the manually selected endpoints of the articular surface represented by the green line at the two sample orientations (a) θ<sub>AS</sub> = 0° and (b) θ<sub>AS</sub> = 55°. The rectangular voxel array within ROI A was created using this line as reference, while ROI B was manually selected.</p
Quantifying collagen fibre architecture in articular cartilage using small-angle X-ray scattering
Collagen fibre architecture in articular cartilage is commonly described in terms of the predominant direction of fibre alignment. X-ray scattering has been used to study the distribution of fibre orientations in cartilage. In this paper, a new methodology for the analysis of small-angle X-ray scattering (SAXS) patterns of articular cartilage in order to quantitatively determine the distribution of collagen fibre orientations in the tissue is presented. A simple three-component model was used to fit intensity data from SAXS patterns to separate diffraction maxima from general diffuse scatter. Deconvolution of angular distributions of intensities of diffraction maxima obtained from SAXS patterns of articular cartilage and ligament samples yielded fibre orientation distributions in the cartilage samples. The methodology developed in this study worked reliably on a large set of SAXS patterns collected from native, dehydrated and trypsin-treated articular cartilage samples. The methods can be extended to quantitative analysis of small or wide angle X-ray scattering patterns obtained from other collagenous materials
Effect of deuteration on proton relaxation rates in solution.
<p>Apparent (a) R<sub>1</sub> rates and (b) R<sub>2</sub> rates in pure solution (blue squares; solid blue line) and in solution surrounding cartilage samples (multiple green symbols; checkered region) obtained using imaging measurements. Spectroscopic measurements of (c) R<sub>1</sub> rates and (d) R<sub>2</sub> rates in pure solution obtained using inversion-recovery and CPMG experiments respectively in the present study (blue squares; solid blue line) and the corresponding values obtained by Zhong et al. (red circles; broken red line).</p