Multicentre evaluation of MRI variability in the quantification of infarct size in experimental focal cerebral ischaemia

Ischaemic stroke is a leading cause of death and disability in the developed world. Despite that considerable advances in experimental research enabled understanding of the pathophysiology of the disease and identified hundreds of potential neuroprotective drugs for treatment, no such drug has shown efficacy in humans. The failure in the translation from bench to bedside has been partially attributed to the poor quality and rigour of animal studies. Recently, it has been suggested that multicentre animal studies imitating the design of randomised clinical trials could improve the translation of experimental research. Magnetic resonance imaging (MRI) could be pivotal in such studies due to its non-invasive nature and its high sensitivity to ischaemic lesions, but its accuracy and concordance across centres has not yet been evaluated. This thesis focussed on the use of MRI for the assessment of late infarct size, the primary outcome used in stroke models. Initially, a systematic review revealed that a plethora of imaging protocols and data analysis methods are used for this purpose. Using meta-analysis techniques, it was determined that T2-weighted imaging (T2WI) was best correlated with gold standard histology for the measurement of infarctbased treatment effects. Then, geometric accuracy in six different preclinical MRI scanners was assessed using structural phantoms and automated data analysis tools developed in-house. It was found that geometric accuracy varies between scanners, particularly when centre-specific T2WI protocols are used instead of a standardised protocol, though longitudinal stability over six months is high. Finally, a simulation study suggested that the measured geometric errors and the different protocols are sufficient to render infarct volumes and related group comparisons across centres incomparable. The variability increases when both factors are taken into account and when infarct volume is expressed as a relative estimate. Data in this study were analysed using a custom-made semi-automated tool that was faster and more reliable in repeated analyses than manual analysis. Findings of this thesis support the implementation of standardised methods for the assessment and optimisation of geometric accuracy in MRI scanners, as well as image acquisition and analysis of in vivo data for the measurement of infarct size in multicentre animal studies. Tools and techniques developed as part of the thesis show great promise in the analysis of phantom and in vivo data and could be a step towards this endeavour

Impact of Temporal Resolution and Methods for Correction on Cardiac Magnetic Resonance Perfusion Quantification

BACKGROUND: Acquisition of magnetic resonance first‐pass perfusion images is synchronized to the patient's heart rate (HR) and governs the temporal resolution. This is inherently linked to the process of myocardial blood flow (MBF) quantification and impacts MBF accuracy but to an unclear extent. PURPOSE: To assess the impact of temporal resolution on quantitative perfusion and compare approaches for accounting for its variability. STUDY TYPE: Prospective phantom and retrospective clinical study. POPULATION AND PHANTOM: Simulations, a cardiac perfusion phantom, and 30 patients with (16, 53%) or without (14, 47%) coronary artery disease. FIELD STRENGTH/SEQUENCE: 3.0 T/2D saturation recovery spoiled gradient echo sequence. ASSESSMENT: Dynamic perfusion data were simulated for a range of reference MBF (1 mL/g/min–5 mL/g/min) and HR (30 bpm–150 bpm). Perfusion imaging was performed in patients and a phantom for different temporal resolutions. MBF and myocardial perfusion reserve (MPR) were quantified without correction for temporal resolution or following correction by either MBF scaling based on the sampling interval or data interpolation prior to quantification. Simulated data were quantified using Fermi deconvolution, truncated singular value decomposition, and one‐compartment modeling, whereas phantom and clinical data were quantified using Fermi deconvolution alone. STATISTICAL TESTS: Shapiro–Wilk tests for normality, percentage error (PE) for measuring MBF accuracy in simulations, and one‐way repeated measures analysis of variance with Bonferroni correction to compare clinical MBF and MPR. Statistical significance set at P < 0.05. RESULTS: For Fermi deconvolution and an example simulated 1 mL/g/min, the MBF PE without correction for temporal resolution was between 55.4% and −62.7% across 30–150 bpm. PE was between −22.2% and −6.8% following MBF scaling and between −14.2% and −14.2% following data interpolation across the same HR. An interpolated HR of 240 bpm reduced PE to ≤10%. Clinical rest and stress MBF and MPR were significantly different between analyses. DATA CONCLUSION: Accurate perfusion quantification needs to account for the variability of temporal resolution, with data interpolation prior to quantification reducing MBF variability across different resolutions. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE:

Pixel-wise assessment of cardiovascular magnetic resonance first-pass perfusion using a cardiac phantom mimicking transmural myocardial perfusion gradients

Purpose: Cardiovascular magnetic resonance first-pass perfusion for the pixel-wise detection of coronary artery disease is rapidly becoming the clinical standard, yet no widely available method exists for its assessment and validation. This study introduces a novel phantom capable of generating spatially dependent flow values to enable assessment of new perfusion imaging methods at the pixel level. Methods: A synthetic multicapillary myocardial phantom mimicking transmural myocardial perfusion gradients was designed and manufactured with high-precision 3D printing. The phantom was used in a stationary flow setup providing reference myocardial perfusion rates and was scanned on a 3T system. Repeated first-pass perfusion MRI for physiological perfusion rates between 1 and 4 mL/g/min was performed using a clinical dual-sequence technique. Fermi function-constrained deconvolution was used to estimate pixel-wise perfusion rate maps. Phase contrast (PC)-MRI was used to obtain velocity measurements that were converted to perfusion rates for validation of reference values and cross-method comparison. The accuracy of pixel-wise maps was assessed against simulated reference maps. Results: PC-MRI indicated excellent reproducibility in perfusion rate (coefficient of variation [CoV] 2.4-3.5%) and correlation with reference values (R2 = 0.985) across the full physiological range. Similar results were found for first-pass perfusion MRI (CoV 3.7-6.2%, R2 = 0.987). Pixel-wise maps indicated a transmural perfusion difference of 28.8-33.7% for PC-MRI and 23.8-37.7% for first-pass perfusion, matching the reference values (30.2-31.4%). Conclusion: The unique transmural perfusion pattern in the phantom allows effective pixel-wise assessment of first-pass perfusion acquisition protocols and quantification algorithms before their introduction into routine clinical use.Multi Phase System

Between-scanner variability.

<p>(a) Percentage linear scaling error across the three orthogonal directions in the MRI systems with median values shown by the black dashes and (b) the percent volumetric error with values predicted by the median scaling errors shown by the dashed lines. Scaling errors are based on the internal dimensions of the whole phantom measured on scans in all imaging planes, while volumetric errors are based on the central frustum-shaped compartment segmented on axial scans. Only the standard protocol was used to evaluate scanner “A” as no stroke protocols were utilized at this center prior to our study.</p

Imaging Parameters of Standard (“a”) and Stroke (“b”-“f”) Pulse Sequences.

<p>Imaging Parameters of Standard (“a”) and Stroke (“b”-“f”) Pulse Sequences.</p

Deformation needed to recover reference CT scans from MRI data.

<p>The maps show the in-plane absolute Euclidean displacement required to recover the true shape of the phantom in axial (<i>x-y</i>) and coronal (<i>x-z</i>) MRI data from the between-scanner variability assessment. Phase encoding is in the horizontal direction (<i>x</i>) in both planes. It is evident that scanning using an identical (standard) sequence ensures better correspondence between images from scanners “B”-“F” in terms of distortion effects. Correspondence declined when stroke sequences “b”-“f” were used, particularly in the coronal plane. Furthermore, overall distortion was characterized by two differing patterns; images from system “A” were uniformly stretched in both directions, whereas minor non-linearities were present in images from systems “B”-“F”. It should be emphasized that while these deformation maps successfully demonstrate the overall distortion of the MRI data compared to reference images, they do not represent the true geometric distortion in the MRI systems; a phantom with a large number of equidistant control points (grid structure) is often required for this purpose. Corresponding MRI images are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0162545#pone.0162545.s003" target="_blank">S2 Fig</a>.</p

Within-scanner variability.

<p>(a) Percent linear scaling error across the three orthogonal directions and (b) the percent volumetric error measured in system “A” using the standard sequence “a” after calibration of the gradient coils. The colored lines in (a) follow the median values at each time point. d indicates day; w, week; m, month. “d0” is the baseline time point immediately after calibration.</p