Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI.

PURPOSE: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique. THEORY AND METHODS: A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images. RESULTS: Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, although some discrepancies were observed. The spherical mean power-law method overestimated fiber radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material-specific relaxation changes. CONCLUSION: The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.

Bias, Repeatability and Reproducibility of Liver T1 Mapping With Variable Flip Angles.

BACKGROUND: 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.

Evaluation of Dynamic Contrast-Enhanced MRI Measures of Lung Congestion and Endothelial Permeability in Heart Failure: A Prospective Method Validation Study.

BACKGROUND: Methods for accurate quantification of lung fluid in heart failure (HF) are needed. Dynamic contrast-enhanced (DCE)-MRI may be an appropriate modality. PURPOSE: DCE-MRI evaluation of fraction of fluid volume in the interstitial lung space (ve ) and vascular permeability (Ktrans ). STUDY TYPE: Prospective, single-center method validation. POPULATION: Seventeen evaluable healthy volunteers (HVs), 12 participants with HF, and 3 with acute decompensated HF (ADHF). FIELD STRENGTH/SEQUENCE: T1 mapping (spoiled gradient echo variable flip angle acquisition) followed by dynamic series (three-dimensional spoiled gradient-recalled echo acquisitions [constant echo time, repetition time, and flip angle at 1.5 T]). ASSESSMENT: Three whole-chest scans were acquired: baseline (Session 1), 1-week later (Session 2), following exercise (Session 3). Extended Tofts model quantified ve and Ktrans (voxel-wise basis); total lung median measures were extracted and fitted via repeat measure analysis of variance (ANOVA) model. Patient tolerability of the scanning protocol was assessed. STATISTICAL TESTS: This was constructed as an experimental medicine study. PRIMARY ENDPOINTS: Ktrans and ve at baseline (HV vs. HF), change in Ktrans and ve following exercise, and following lung congestion resolution (ADHF). Ktrans and ve were fitted separately using ANOVA. Secondary endpoint: repeatability, that is, within-participant variability in ve and Ktrans between sessions (coefficient of variation estimated via mixed effects model). RESULTS: There was no significant difference in mean Ktrans between HF and HV (P ≤ 0.17): 0.2216 minutes-1 and 0.2353 minutes-1 (Session 1), 0.2044 minutes-1 and 0.2567 minutes-1 (Session 2), 0.1841 minutes-1 and 0.2108 minutes-1 (Session 3), respectively. ve was greater in the HF group (all scans, P ≤ 0.02). Results were repeatable between Sessions 1 and 2; mean values for HF and HV were 0.4946 and 0.3346 (Session 1), 0.4353 and 0.3205 (Session 2), respectively. There was minimal difference in Ktrans or ve between scans for participants with ADHF (small population precluded significance testing). Scanning was well tolerated. DATA CONCLUSION: While no differences were detected in Ktrans , ve was greater in chronic HF patients vs. HV, augmented beyond plasma and intracellular volume. DCE-MRI is a valuable diagnostic and physiologic tool to evaluate changes in fluid volume in the interstitial lung space associated with symptomatic HF. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Diffusion model comparison identifies distinct tumor sub-regions and tracks treatment response.

PURPOSE: MRI biomarkers of tumor response to treatment are typically obtained from parameters derived from a model applied to pre-treatment and post-treatment data. However, as tumors are spatially and temporally heterogeneous, different models may be necessary in different tumor regions, and model suitability may change over time. This work evaluates how the suitability of two diffusion-weighted (DW) MRI models varies spatially within tumors at the voxel level and in response to radiotherapy, potentially allowing inference of qualitatively different tumor microenvironments. METHODS: DW-MRI data were acquired in CT26 subcutaneous allografts before and after radiotherapy. Restricted and time-independent diffusion models were compared, with regions well-described by the former hypothesized to reflect cellular tissue, and those well-described by the latter expected to reflect necrosis or oedema. Technical and biological validation of the percentage of tissue described by the restricted diffusion microstructural model (termed %MM) was performed through simulations and histological comparison. RESULTS: Spatial and radiotherapy-related variation in model suitability was observed. %MM decreased from a mean of 64% at baseline to 44% 6 days post-radiotherapy in the treated group. %MM correlated negatively with the percentage of necrosis from histology, but overestimated it due to noise. Within MM regions, microstructural parameters were sensitive to radiotherapy-induced changes. CONCLUSIONS: There is spatial and radiotherapy-related variation in different models' suitability for describing diffusion in tumor tissue, suggesting the presence of different and changing tumor sub-regions. The biological and technical validation of the proposed %MM cancer imaging biomarker suggests it correlates with, but overestimates, the percentage of necrosis.

Towards a 'resolution limit' for DW-MRI tumor microstructural models: A simulation study investigating the feasibility of distinguishing between microstructural changes.

PURPOSE: To determine the feasibility of extracting sufficiently precise estimates of cell radius, R, and intracellular volume fraction, fi , from DW-MRI data in order to distinguish between specific microstructural changes tissue may undergo, specifically focusing on cell death in tumors. METHODS: Simulations with optimized and non-optimized clinical acquisitions were performed for a range of microstructures, using a two-compartment model. The ability to distinguish between (i) cell shrinkage with cell density constant, mimicking apoptosis, and (ii) cell size constant with cell density decreasing, mimicking loss of cells, was evaluated based on the precision of simulated parameter estimates. Relationships between parameter precision, SNR, and the magnitude of specific parameter changes, were used to infer SNR requirements for detecting changes. RESULTS: Accuracy and precision depended on microstructural properties, SNR, and the acquisition protocol. The main benefit of optimized acquisitions tended to be improved accuracy and precision of R, particularly for small cells. In most cases considered, higher SNR was required for detecting changes in R than for changes in fi . CONCLUSIONS: Given the relative changes in R and fi due to apoptosis, simulations indicate that, for a range of microstructures, detecting changes in R require higher SNR than detecting changes in fi , and that such SNR is typically not achieved in clinical data. This suggests that if apoptotic cell size decreases are to be detected in clinical settings, improved SNR is required. Comparing measurement precision with the magnitude of expected biological changes should form part of the validation process for potential biomarkers.

A biomimetic tumor tissue phantom for validating diffusion-weighted MRI measurements.

PURPOSE: To develop a biomimetic tumor tissue phantom which more closely reflects water diffusion in biological tissue than previously used phantoms, and to evaluate the stability of the phantom and its potential as a tool for validating diffusion-weighted (DW) MRI measurements. METHODS: Coaxial-electrospraying was used to generate micron-sized hollow polymer spheres, which mimic cells. The bulk structure was immersed in water, providing a DW-MRI phantom whose apparent diffusion coefficient (ADC) and microstructural properties were evaluated over a period of 10 months. Independent characterization of the phantom's microstructure was performed using scanning electron microscopy (SEM). The repeatability of the construction process was investigated by generating a second phantom, which underwent high resolution synchrotron-CT as well as SEM and MR scans. RESULTS: ADC values were stable (coefficients of variation (CoVs) < 5%), and varied with diffusion time, with average values of 1.44 ± 0.03 µm2 /ms (Δ = 12 ms) and 1.20 ± 0.05 µm2 /ms (Δ = 45 ms). Microstructural parameters showed greater variability (CoVs up to 13%), with evidence of bias in sphere size estimates. Similar trends were observed in the second phantom. CONCLUSION: A novel biomimetic phantom has been developed and shown to be stable over 10 months. It is envisaged that such phantoms will be used for further investigation of microstructural models relevant to characterizing tumor tissue, and may also find application in evaluating acquisition protocols and comparing DW-MRI-derived biomarkers obtained from different scanners at different sites. Magn Reson Med 80:147-158, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Repeatability and response to therapy of dynamic contrast-enhanced magnetic resonance imaging biomarkers in rheumatoid arthritis in a large multicentre trial setting.

OBJECTIVES: To determine the repeatability and response to therapy of dynamic contrast-enhanced (DCE) MRI biomarkers of synovitis in the hand and wrist of rheumatoid arthritis (RA) patients, and in particular the performance of the transfer constant K trans , in a multicentre trial setting. METHODS: DCE-MRI and RA MRI scoring (RAMRIS) were performed with meticulous standardisation at baseline and 6 and 24 weeks in a substudy of fostamatinib monotherapy in reducing synovitis compared with placebo or adalimumab. Analysis employed statistical shape modelling to avoid biased regions-of-interest, kinetic modelling and heuristic analyses. Repeatability was also evaluated. RESULTS: At early study termination, DCE-MRI data had been acquired from 58 patients in 19 imaging centres. K trans intra-subject coefficient of variation (N = 14) was 30%. K trans change demonstrated inferiority of fostamatinib (N = 11) relative to adalimumab (N = 10) after 6 weeks (treatment ratio = 1.92, p = 0.003), and failed to distinguish fostamatinib from placebo (N = 10, p = 0.79). RAMRIS showed superiority of fostamatinib relative to placebo at 6 weeks (p = 0.023), and did not distinguish fostamatinib from adalimumab at either 6 (p = 0.175) or 24 (p = 0.230) weeks. CONCLUSION: This demonstrated repeatability of K trans and its ability to distinguish treatment groups show that DCE-MRI biomarkers are suitable for use in multicentre RA trials. KEY POINTS: • DCE-MRI biomarkers are feasible in large multicentre studies of joint inflammation. • DCE-MRI K trans showed fostamatinib inferior to adalimumab after 6 weeks. • K trans repeatability coefficient of variation was 30% multicentre.

T1-weighted Dynamic Contrast-enhanced MR Imaging of the Lung in Asthma: Semiquantitative Analysis for the Assessment of Contrast Agent Kinetic Characteristics.

PURPOSE: To evaluate the contrast agent kinetics of dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging in healthy lungs and asthmatic lungs by using non-model-based semiquantitative parameters and to explore the relationships with pulmonary function testing and eosinophil level. MATERIALS AND METHODS: The study was approved by the National Research Ethical Committee (reference no. 11/NW/0387), and written informed consent was obtained from all individuals. Ten healthy subjects and 30 patients with asthma underwent pulmonary function tests, blood and sputum eosinophil counts, and 1.5-T DCE MR imaging within 7 days. Semiquantitative parameters of contrast agent kinetics were calculated from the relative signal intensity-time course curves on a pixel-by-pixel basis and were summarized by using whole-lung median values. The distribution heterogeneity was assessed by using the regional coefficient of variation. DCE MR imaging readouts were compared between groups by using one-way analysis of variance, and the relationships with pulmonary function testing and eosinophil counts were assessed by using Pearson correlation analysis. RESULTS: Asthmatic patients showed significantly lower peak enhancement (P < .001) and initial areas under the relative signal intensity curve in the first 60 seconds (P = .002) and significantly reduced late-phase washout slope (P = .002) when compared with healthy control subjects. The distribution heterogeneity of bolus arrival time (P = .029), time to peak (P = .008), upslope of the first-pass peak (P = .011), and late-phase washout slope (P = .032), estimated by using the median coefficient of variation, were significantly higher in asthmatic patients than in healthy control subjects. These imaging readouts also showed significant linear correlations with measurements of pulmonary function testing but not with eosinophil level in patients with asthma. CONCLUSION: The contrast agent kinetic characteristics of T1-weighted DCE MR images of asthmatic lungs are different from those of healthy lungs and are related to measurements of pulmonary function testing but not to eosinophil level.

Biomimetic phantom for cardiac diffusion MRI.

PURPOSE: Diffusion magnetic resonance imaging (MRI) is increasingly used to characterize cardiac tissue microstructure, necessitating the use of physiologically relevant phantoms for methods development. Existing phantoms are generally simplistic and mostly simulate diffusion in the brain. Thus, there is a need for phantoms mimicking diffusion in cardiac tissue. MATERIALS AND METHODS: A biomimetic phantom composed of hollow microfibers generated using co-electrospinning was developed to mimic myocardial diffusion properties and fiber and sheet orientations. Diffusion tensor imaging was carried out at monthly intervals over 4 months at 9.4T. 3D fiber tracking was performed using the phantom and compared with fiber tracking in an ex vivo rat heart. RESULTS: The mean apparent diffusion coefficient and fractional anisotropy of the phantom remained stable over the 4-month period, with mean values of 7.53 ± 0.16 × 10(-4) mm(2) /s and 0.388 ± 0.007, respectively. Fiber tracking of the 1st and 3rd eigenvectors generated analogous results to the fiber and sheet-normal direction respectively, found in the left ventricular myocardium. CONCLUSION: A biomimetic phantom simulating diffusion in the heart was designed and built. This could aid development and validation of novel diffusion MRI methods for investigating cardiac microstructure, decrease the number of animals and patients needed for methods development, and improve quality control in longitudinal and multicenter cardiac diffusion MRI studies.

Validation of High-Resolution Tractography Against In Vivo Tracing in the Macaque Visual Cortex.

Diffusion magnetic resonance imaging (MRI) allows for the noninvasive in vivo examination of anatomical connections in the human brain, which has an important role in understanding brain function. Validation of this technique is vital, but has proved difficult due to the lack of an adequate gold standard. In this work, the macaque visual system was used as a model as an extensive body of literature of in vivo and postmortem tracer studies has established a detailed understanding of the underlying connections. We performed probabilistic tractography on high angular resolution diffusion imaging data of 2 ex vivo, in vitro macaque brains. Comparisons were made between identified connections at different thresholds of probabilistic connection "strength," and with various tracking optimization strategies previously proposed in the literature, and known connections from the detailed visual system wiring map described by Felleman and Van Essen (1991; FVE91). On average, 74% of connections that were identified by FVE91 were reproduced by performing the most successfully optimized probabilistic diffusion MRI tractography. Further comparison with the results of a more recent tracer study ( Markov et al. 2012) suggests that the fidelity of tractography in estimating the presence or absence of interareal connections may be greater than this.

COPD Patients Have Short Lung Magnetic Resonance T1 Relaxation Time.

Magnetic resonance imaging (MRI) may provide attractive biomarkers for assessment of pulmonary disease in clinical trials as it is free from ionizing radiation, minimally invasive and allows regional information. The aim of this study was to characterize lung MRI T1 relaxation time as a biomarker of chronic obstructive pulmonary disease (COPD); and specifically its relationship to smoking history, computed tomography (CT), and pulmonary function test (PFT) measurements in comparison to healthy age-matched controls. Lung T1 and inter-quartile range (IQR) of T1 maps from 24 COPD subjects and 12 healthy age-matched non-smokers were retrospectively analyzed from an institutional review board approved study. The subjects underwent PFTs and two separate MR imaging sessions at 1.5 tesla to test T1 repeatability. CT scans were performed on the COPD subjects. T1 repeatability (intraclass correlation coefficient) was 0.72 for repeated scans acquired on two visits. The lung T1 was significantly shorter (p < 0.0001) and T1 IQR was significantly larger (p = 0.0002) for the COPD subjects compared to healthy controls. Lung T1 significantly (p = 0.001) correlated with lung density assessed with CT. Strong significant correlations (p < 0.0001) between lung T1 and all PFT measurements were observed. Cigarette exposure did not correlate with lung T1 in COPD subjects. In conclusion, lung MRI T1 mapping shows potential as a repeatable, radiation free, non-invasive imaging technique in the evaluation of COPD.

MR Quantitative Equilibrium Signal Mapping: A Reliable Alternative to CT in the Assessment of Emphysema in Patients with Chronic Obstructive Pulmonary Disease.

PURPOSE: To compare magnetic resonance (MR) quantitative equilibrium signal (qS0) mapping with quantitative computed tomography (CT) in the estimation of emphysema in patients with chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: Written informed consent of the original study permitted future reanalysis of data. This study was a retrospective analysis of data from an institutional review board-approved study. Twenty-four patients with COPD and 12 healthy patients who did not smoke underwent spirometry and two separate 1.5-T MR imaging examinations. All patients with COPD underwent additional chest CT. Lung MR qS0 maps were generated from MR images obtained with multiple inversion times by fitting the inversion recovery signal equation. Mean, 15th percentile, and standard deviation of whole-lung qS0 and relative lung area with a qS0 value below 0.20 (RA0.20) were measured and compared between groups with an unpaired t test. Reproducibility between two examinations was tested with intraclass correlation coefficients (ICCs), and their associations with spirometry and CT measurements of 15th percentile attenuation (PA15) and relative lung area with attenuation below -950 HU (RA-950) were assessed with the Pearson correlation coefficient. RESULTS: Whole-lung mean qS0 and 15th percentile of qS0 were significantly lower, whereas RA0.20 and standard deviation of qS0 were significantly higher in patients with COPD than in healthy control subjects (P = .014, P = .002, P = .005, and P < .001, respectively). Whole-lung mean qS0, the 15th percentile of qS0, and RA0.20 strongly correlated with RA-950 (r = -0.78, r = -0.81, and r = 0.86, respectively; P < .001) and PA15 (r = 0.78, r = 0.79, and r = -0.71, respectively; P < .001) and moderately correlated with the ratio of forced expiratory volume in 1 second (FEV1) to forced vital capacity (r = 0.63, r = 0.67, and r = -0.60, respectively; P < .001) and percentage predicted FEV1 (r = 0.54, r = 0.62, and r = -0.56, respectively; P ≤ .001). Good reproducibility of qS0 readouts was found in both groups (ICC range, 0.89-0.98). CONCLUSION: Lung MR qS0 mapping may be a reliable noncontrast nonradiation alternative to CT in the assessment of emphysema in patients with COPD.

Biomimetic phantom for the validation of diffusion magnetic resonance imaging.

PURPOSE: A range of advanced diffusion MRI (dMRI) techniques are currently in development which characterize the orientation of white matter fibers using diffusion tensor imaging (DTI). There is a need for a physical phantom with microstructural features of the brain's white matter to help validate these methods. METHODS: Hollow, co-electrospun, aligned fibers with a tuneable size distribution have been produced in bulk and with an MR visible solvent infused into the pores. The morphology and size of the phantoms was assessed using scanning electron microscopy (SEM) and compared with DTI results obtained on both a clinical and preclinical scanner. RESULTS: By varying inner diameter of the phantom fibers (from SEM: 9.5 µm, 11.9 µm, 13.4 µm) the radial diffusivity and fractional anisotropy, calculated from DTI, vary between 0.38 ± 0.05 × 10(3) and 0.61 ± 0.06 × 10(3) cm s(-1) and between 0.45 ± 0.05 and 0.33 ± 0.04, respectively. CONCLUSION: We envisage that these materials will be used for the validation of novel and established methods within the field of diffusion MRI, as well as for routine quality assurance purposes and for establishing scanner performance in multicenter trials.

Mixed-effects modeling of clinical DCE-MRI data: application to colorectal liver metastases treated with bevacizumab.

PURPOSE: Most dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data are evaluated for individual patients with cohorts analyzed to detect significant changes from baseline values, repeating the process at each posttreatment timepoint. Our study aimed to develop a statistically valid model for the complete time course of DCE-MRI data in a patient cohort. MATERIALS AND METHODS: Data from 10 patients with colorectal cancer liver metastases were analyzed, including two baseline scans and four post-bevacizumab scans. Apparent changes in tumor median K(trans) were adjusted for changes in observed enhancing tumor fraction (EnF) by multiplying K(trans) by EnF (KEnF). A mixed-effects model (MEM) was defined to describe the KEnF time course for all patients simultaneously by assuming a three-parameter indirect response model with model parameters lognormally distributed across patients. RESULTS: The typical cohort time course showed a KEnF reduction to 59% of baseline at 24 hours, returning to 65% of baseline values by day 12. Interpatient variability of model parameters ranged from 11% to 307%. CONCLUSION: The MEM approach has potential for comparing responses at a group level in clinical trials with different doses, schedules, or combination regimens. Furthermore, the KEnF biomarker successfully resolved confounds in interpreting K(trans) arising from therapy induced changes in the volume of enhancing tumor.

Multiparametric cardiovascular magnetic resonance surveillance of acute cardiac allograft rejection and characterisation of transplantation-associated myocardial injury: a pilot study.

BACKGROUND: Serial surveillance endomyocardial biopsies are performed in patients who have recently undergone heart transplantation in order to detect acute cardiac allograft rejection (ACAR) before symptoms occur, however the biopsy process is associated with a number of limitations. This study aimed to prospectively and longitudinally evaluate the performance of multiparametric cardiovascular magnetic resonance (CMR) for detecting and monitoring ACAR in the early phase post-transplant, and characterize graft recovery following transplantation. METHODS: All patients receiving a heart transplant at a single UK centre over a period of 25 months were approached within one month of transplantation. Multiparametric CMR was prospectively performed on the same day as biopsy on four separate occasions (6 weeks, 10 weeks, 15 weeks and 20 weeks post-transplant). CMR included assessment of global and regional ventricular function, myocardial tissue characterization (T1 mapping, T2 mapping, extracellular volume, LGE) and pixel-wise absolute myocardial blood flow quantification. CMR parameters were compared with biopsy findings. As is standard, grade 2R or higher ACAR was considered significant. RESULTS: 88 CMR-matched biopsies were performed in 22 patients. Eight (9%) biopsies in 5 patients demonstrated significant ACAR. Significant ACAR was associated with a reduction in circumferential strain (-12.7±2.5% vs. -13.7±3.6%, p=0.047) but there was considerable overlap between groups. Whilst trends were observed between ACAR and proposed CMR markers of oedema, particularly after adjusting for primary graft dysfunction, differences were not significant. Significant improvements were seen in markers of graft structure and contractility, oedema and microvascular function over the period studied, although few parameters normalised. CONCLUSIONS: This study provides novel insight into the myocardial injury associated with transplantation, and its recovery, however multiparametric CMR was not able to accurately detect ACAR during the early phase post-transplantation.

Voxel-wise quantification of myocardial blood flow with cardiovascular magnetic resonance: effect of variations in methodology and validation with positron emission tomography.

BACKGROUND: Quantitative assessment of myocardial blood flow (MBF) from cardiovascular magnetic resonance (CMR) perfusion images appears to offer advantages over qualitative assessment. Currently however, clinical translation is lacking, at least in part due to considerable disparity in quantification methodology. The aim of this study was to evaluate the effect of common methodological differences in CMR voxel-wise measurement of MBF, using position emission tomography (PET) as external validation. METHODS: Eighteen subjects, including 9 with significant coronary artery disease (CAD) and 9 healthy volunteers prospectively underwent perfusion CMR. Comparison was made between MBF quantified using: 1. Calculated contrast agent concentration curves (to correct for signal saturation) versus raw signal intensity curves; 2. Mid-ventricular versus basal-ventricular short-axis arterial input function (AIF) extraction; 3. Three different deconvolution approaches; Fermi function parameterization, truncated singular value decomposition (TSVD) and first-order Tikhonov regularization with b-splines. CAD patients also prospectively underwent rubidium-82 PET (median interval 7 days). RESULTS: MBF was significantly higher when calculated using signal intensity compared to contrast agent concentration curves, and when the AIF was extracted from mid- compared to basal-ventricular images. MBF did not differ significantly between Fermi and Tikhonov, or between Fermi and TVSD deconvolution methods although there was a small difference between TSVD and Tikhonov (0.06 mL/min/g). Agreement between all deconvolution methods was high. MBF derived using each CMR deconvolution method showed a significant linear relationship (p<0.001) with PET-derived MBF however each method underestimated MBF compared to PET (by 0.19 to 0.35 mL/min/g). CONCLUSIONS: Variations in more complex methodological factors such as deconvolution method have no greater effect on estimated MBF than simple factors such as AIF location and observer variability. Standardization of the quantification process will aid comparison between studies and may help CMR MBF quantification enter clinical use.

An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training.

Large medical imaging data sets are becoming increasingly available. A common challenge in these data sets is to ensure that each sample meets minimum quality requirements devoid of significant artefacts. Despite a wide range of existing automatic methods having been developed to identify imperfections and artefacts in medical imaging, they mostly rely on data-hungry methods. In particular, the scarcity of artefact-containing scans available for training has been a major obstacle in the development and implementation of machine learning in clinical research. To tackle this problem, we propose a novel framework having four main components: (1) a set of artefact generators inspired by magnetic resonance physics to corrupt brain MRI scans and augment a training dataset, (2) a set of abstract and engineered features to represent images compactly, (3) a feature selection process that depends on the class of artefact to improve classification performance, and (4) a set of Support Vector Machine (SVM) classifiers trained to identify artefacts. Our novel contributions are threefold: first, we use the novel physics-based artefact generators to generate synthetic brain MRI scans with controlled artefacts as a data augmentation technique. This will avoid the labour-intensive collection and labelling process of scans with rare artefacts. Second, we propose a large pool of abstract and engineered image features developed to identify 9 different artefacts for structural MRI. Finally, we use an artefact-based feature selection block that, for each class of artefacts, finds the set of features that provide the best classification performance. We performed validation experiments on a large data set of scans with artificially-generated artefacts, and in a multiple sclerosis clinical trial where real artefacts were identified by experts, showing that the proposed pipeline outperforms traditional methods. In particular, our data augmentation increases performance by up to 12.5 percentage points on the accuracy, F1, F2, precision and recall. At the same time, the computation cost of our pipeline remains low - less than a second to process a single scan - with the potential for real-time deployment. Our artefact simulators obtained using adversarial learning enable the training of a quality control system for brain MRI that otherwise would have required a much larger number of scans in both supervised and unsupervised settings. We believe that systems for quality control will enable a wide range of high-throughput clinical applications based on the use of automatic image-processing pipelines.

Convergent connectivity and graded specialization in the rostral human temporal lobe as revealed by diffusion-weighted imaging probabilistic tractography.

In recent years, multiple independent neuroscience investigations have implicated critical roles for the rostral temporal lobe in auditory and visual perception, language, and semantic memory. Although arising in the context of different cognitive functions, most of these suggest that there is a gradual convergence of sensory information in the temporal lobe that culminates in modality- and perceptually invariant representations at the most rostral aspect. Currently, however, too little is known regarding connectivity within the human temporal lobe to be sure of exactly how and where convergence occurs; existing hypotheses are primarily derived on the basis of cross-species generalizations from invasive nonhuman primate studies, the validity of which is unclear, especially where language function is concerned. In this study, we map the connectivity of the human rostral temporal lobe in vivo for the first time using diffusion-weighted imaging probabilistic tractography. The results indicate that convergence of sensory information in the temporal lobe is in fact a graded process that occurs along both its longitudinal and lateral axes and culminates in the most rostral limits. We highlight the consistency of our results with those of prior functional neuroimaging, computational modeling, and patient studies. By going beyond simple fasciculus reconstruction, we systematically explored the connectivity of specific temporal lobe areas to frontal and parietal language regions. In contrast to the graded within-temporal lobe connectivity, this intertemporal connectivity was found to dissociate across caudal, mid, and rostral subregions. Furthermore, we identified a basal rostral temporal region with very limited connectivity to areas outside the temporal lobe, which aligns with recent evidence that this subregion underpins the extraction of modality- and context-invariant semantic representations.

The variation of function across the human insula mirrors its patterns of structural connectivity: evidence from in vivo probabilistic tractography.

The human insula is a functionally complex yet poorly understood region of the cortex, implicated in a wide range of cognitive, motor, emotion and somatosensory activity. To elucidate the functional role of the insula, the current study used in vivo probabilistic tractography to map the structural connectivity of seven anatomically-defined insular subregions. The connectivity patterns identified reveal two complementary insular networks connected via a dual route architecture, and provide key insights about the neural basis of the numerous functions ascribed to this area. Specifically, anterior-most insular regions were associated with a ventrally-based network involving orbital/inferior frontal and anterior/polar temporal regions, forming part of a key emotional salience and cognitive control network associated with the implementation of goal-directed behavior. The posterior and dorsal-middle insular regions were associated with a network focused on posterior and (to a lesser extent) anterior temporal regions via both dorsal and ventral pathways. This is consistent with the involvement of the insula in sound-to-speech transformations, with an implicated role in the temporal resolution, sequencing, and feedback processes crucial for auditory and motor processing, and the monitoring and adjustment of expressive performance.

Group-averaged anatomical connectivity mapping for improved human white matter pathway visualisation.

Anatomical connectivity mapping (ACM) is a measure of anatomical connectivity obtained by initiating streamline diffusion tractography from all parenchymal voxels and then counting the number of streamlines passing through each voxel of the brain. ACM highlights WM structures that present multiple connections to the rest of the brain but not necessarily strong microstructural orientation coherence. In this study, ACM was used to develop an atlas of the human brain. The ACM template was constructed from 3 T diffusion-weighted data from 19 healthy adults. To account for multiple diffusion directions in a voxel, a high angular resolution diffusion imaging (HARDI) technique, namely Q-ball, was used to model diffusion. To bring data from different subjects into a common space, an algorithm for rotating and averaging the principal directions was implemented, which can be generalized to any application requiring algebraic operations on principal directions derived from any HARDI method. ACM from the average dataset was computed and several white matter connections of interest were identified and highlighted. Fractional anisotropy (FA) from standard diffusion tensor modelling was also derived and FA-modulated colour coded images obtained from the mean tensor were also shown for comparison, highlighting differences and similarities. The ACM template can serve for educational purposes and as future reference for studies based on the evaluation of ACM in subjects affected by neurological and psychiatric disorders.