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Purpose: Tensor-valued diffusion encoding can probe more specific features of tissue microstructure than what is available by conventional diffusion weighting. In this work, we investigate the technical feasibility of tensor-valued diffusion encoding at high b-values with q-space trajectory imaging (QTI) analysis, in the human heart in vivo. Methods: Ten healthy volunteers were scanned on a 3T scanner. We designed time-optimal gradient waveforms for tensor-valued diffusion encoding (linear and planar) with second-order motion compensation. Data were analyzed with QTI. Normal values and repeatability were investigated for the mean diffusivity (MD), fractional anisotropy (FA), microscopic FA (μFA), isotropic, anisotropic and total mean kurtosis (MKi, MKa, and MKt), and orientation coherence (Cc). A phantom, consisting of two fiber blocks at adjustable angles, was used to evaluate sensitivity of parameters to orientation dispersion and diffusion time. Results: QTI data in the left ventricular myocardium were MD = 1.62 ± 0.07 μm2/ms, FA = 0.31 ± 0.03, μFA = 0.43 ± 0.07, MKa = 0.20 ± 0.07, MKi = 0.13 ± 0.03, MKt = 0.33 ± 0.09, and Cc = 0.56 ± 0.22 (mean ± SD across subjects). Phantom experiments showed that FA depends on orientation dispersion, whereas μFA was insensitive to this effect. Conclusion: We demonstrated the first tensor-valued diffusion encoding and QTI analysis in the heart in vivo, along with first measurements of myocardial μFA, MKi, MKa, and Cc. The methodology is technically feasible and provides promising novel biomarkers for myocardial tissue characterization.

Purpose: To evaluate potential modeling paradigms and the impact of relaxation time effects on human blood-brain barrier (BBB) water exchange measurements using FEXI (BBB-FEXI), and to quantify the accuracy, precision, and repeatability of BBB-FEXI exchange rate estimates at 3 (Formula presented.). Methods: Three modeling paradigms were evaluated: (i) the apparent exchange rate (AXR) model; (ii) a two-compartment model ((Formula presented.)) explicitly representing intra- and extravascular signal components, and (iii) a two-compartment model additionally accounting for finite compartmental (Formula presented.) and (Formula presented.) relaxation times ((Formula presented.)). Each model had three free parameters. Simulations quantified biases introduced by the assumption of infinite relaxation times in the AXR and (Formula presented.) models, as well as the accuracy and precision of all three models. The scan–rescan repeatability of all paradigms was quantified for the first time in vivo in 10 healthy volunteers (age range 23–52 years; five female). Results: The assumption of infinite relaxation times yielded exchange rate errors in simulations up to 42%/14% in the AXR/ (Formula presented.) models, respectively. Accuracy was highest in the compartmental models; precision was best in the AXR model. Scan–rescan repeatability in vivo was good for all models, with negligible bias and repeatability coefficients in grey matter of (Formula presented.) (Formula presented.), (Formula presented.) (Formula presented.), and (Formula presented.) (Formula presented.). Conclusion: Compartmental modelling of BBB-FEXI signals can provide accurate and repeatable measurements of BBB water exchange; however, relaxation time and partial volume effects may cause model-dependent biases.

A technique for quantifying regional blood-brain barrier (BBB) water exchange rates using contrast-enhanced arterial spin labelling (CE-ASL) is presented and evaluated in simulations and in vivo. The two-compartment ASL model describes the water exchange rate from blood to tissue,kb, but to estimatekbin practice it is necessary to separate the intra- and extravascular signals. This is challenging in standard ASL data owing to the small difference inT1values. Here, a gadolinium-based contrast agent is used to increase thisT1difference and enable the signal components to be disentangled. The optimal post-contrast bloodT1at 3T was determined in a sensitivity analysis, and the accuracy and precision of the method quantified using Monte Carlo simulations. Proof-of-concept data were acquired in six healthy volunteers (five female, age range 24 – 46 years). The sensitivity analysis identified the optimalat 3T as 0.8 s. Simulations showedkbcould be estimated in individual cortical regions with a relative errorϵ< 1% and coefficient of variation CoV = 30 %; however, a high dependence on bloodT1was also observed. In volunteer data, mean parameter values in grey matter were: arterial transit timetA= 1.15±0.49 s, cerebral blood flowf= 58.0±14.3 ml blood / min / 100 ml tissue, water exchange ratekb= 2.32 ± 2.49 s−1. CE-ASL can provide regional BBB water exchange rate estimates; however, the clinical utility of the technique is dependent on the achievable accuracy of measuredT1values.

Background and ObjectivesCognitive impairment in multiple sclerosis (MS) is associated with functional connectivity abnormalities. While there have been calls to use functional connectivity measures as biomarkers, there remains to be a full understanding of why they are affected in MS. In this cross-sectional study, we tested the hypothesis that functional network regions may be susceptible to disease-related “wear and tear” and that this can be observable on co-occurring abnormalities on other magnetic resonance metrics. We tested whether functional connectivity abnormalities in cognitively impaired patients with MS co-occur with (1) overlapping, (2) local, or (3) distal changes in anatomic connectivity and cerebral blood flow abnormalities.MethodsMultimodal 3T MRI and assessment with the Brief Repeatable Battery of Neuropsychological tests were performed in 102 patients with relapsing-remitting MS and 27 healthy controls. Patients with MS were classified as cognitively impaired if they scored ≥1.5 SDs below the control mean on ≥2 tests (n = 55) or as cognitively preserved (n = 47). Functional connectivity was assessed with Independent Component Analysis and dual regression of resting-state fMRI images. Cerebral blood flow maps were estimated, and anatomic connectivity was assessed with anatomic connectivity mapping and fractional anisotropy of diffusion-weighted MRI. Changes in cerebral blood flow and anatomic connectivity were assessed within resting-state networks that showed functional connectivity abnormalities in cognitively impaired patients with MS.ResultsFunctional connectivity was significantly decreased in the anterior and posterior default mode networks and significantly increased in the right and left frontoparietal networks in cognitively impaired relative to cognitively preserved patients with MS (threshold-free cluster enhancement corrected at p ≤ 0.05, 2 sided). Networks showing functional abnormalities showed altered cerebral blood flow and anatomic connectivity locally and distally but not in overlapping locations.DiscussionWe provide the first evidence that functional connectivity abnormalities are accompanied by local cerebral blood flow and structural connectivity abnormalities but also demonstrate that these effects do not occur in exactly the same location. Our findings suggest a possibly shared pathologic mechanism for altered functional connectivity in brain networks in MS.

PurposeWe sought to determine the degree to which oxygen extraction fraction (OEF) estimated using quantitative susceptibility mapping (QSM) depends on two critical acquisition parameters that have a significant impact on acquisition time: voxel size and final echo time.MethodsFour healthy volunteers were imaged using a range of isotropic voxel sizes and final echo times. The 0.7 mm data were downsampled at different stages of QSM processing by a factor of 2 (to 1.4 mm), 3 (2.1 mm), or 4 (2.8 mm) to determine the impact of voxel size on each analysis step. OEF was estimated from 11 veins of varying diameter. Inter- and intra-session repeatability were estimated for the optimal protocol by repeat scanning in 10 participants.ResultsFinal echo time was found to have no significant effect on OEF. The effect of voxel size was significant, with larger voxel sizes underestimating OEF, depending on the proximity of the vein to the superficial surface of the brain and on vein diameter. The last analysis step of estimating vein OEF values from susceptibility images had the largest dependency on voxel size. Inter-session coefficients of variation on OEF estimates of between 5.2% and 8.7% are reported, depending on the vein.ConclusionQSM acquisition times can be minimized by reducing the final echo time but an isotropic voxel size no larger than 1 mm is needed to accurately estimate OEF in most medium/large veins in the brain. Such acquisitions can be achieved in under 4 min.

Electrospinning is a simple route to generate polymer-based fibres with diameters on the nano- to micron-scale. It has been very widely explored in biomedical science for applications including drug delivery systems, diagnostic imaging, theranostics, and tissue engineering. This extensive literature reveals that a diverse range of functional components including small molecule drugs, biologics, and nanoparticles can be incorporated into electrospun fibres, and it is possible to prepare materials with complex compartmentalised architectures. This perspective article briefly introduces the electrospinning technique before considering its potential applications in biomedicine. Particular attention is paid to the translation of electrospinning to the clinic, including the need to produce materials at large scale and the requirement to do so under Good Manufacturing Practice conditions. We finish with a summary of the key current challenges and future perspectives.

To compare imaging biomarkers from hyperpolarisedProspective longitudinal.Forty-one ILD (fourteen idiopathic pulmonary fibrosis (IPF), eleven hypersensitivity pneumonitis (HP), eleven drug-induced ILD (DI-ILD), five connective tissue disease related-ILD (CTD-ILD)) patients and ten healthy volunteers imaged at visit 1. Thirty-four ILD patients completed visit 2 (eleven IPF, eight HP, ten DIILD, five CTD-ILD) after 6 or 26 weeks.MRI was performed at 1.5 T, including inversion recovery TFiveTo evaluate differences at visit 1 among subgroups: ANOVA or Kruskal-Wallis rank tests with correction for multiple comparisons. To assess the relationships between imaging biomarkers, PFT, age and gender, at visit 1 and for the change between visit 1 and 2: Pearson correlations and multilinear regression models.The global PFT tests could not distinguish ILD subtypes. Percentage ventilated volumes were lower in ILD patients than in HVs when measured withNeither

Multi-diffusion-time diffusion-weighted MRI can probe tissue microstructure, but the method has not been widely applied to the microvasculature. At long diffusion-times, blood flow in capillaries is in the diffusive regime, and signal attenuation is dependent on blood velocity ([Formula: see text]) and capillary segment length ([Formula: see text]). It is described by the pseudo-diffusion coefficient ([Formula: see text]) of intravoxel incoherent motion (IVIM). At shorter diffusion-times, blood flow is in the ballistic regime, and signal attenuation depends on [Formula: see text], and not [Formula: see text]. In theory, [Formula: see text] could be estimated using [Formula: see text] and [Formula: see text]. In this study, we compare the accuracy and repeatability of three approaches to estimating [Formula: see text], and therefore [Formula: see text]: the IVIM ballistic model, the velocity autocorrelation model, and the ballistic approximation to the velocity autocorrelation model. Twenty-nine rat datasets from two strains were acquired at 7 T, with [Formula: see text]-values between 0 and 1000 smm−2 and diffusion times between 11.6 and 50 ms. Five rats were scanned twice to assess scan-rescan repeatability. Measurements of [Formula: see text] were validated using corrosion casting and micro-CT imaging. The ballistic approximation of the velocity autocorrelation model had lowest bias relative to corrosion cast estimates of [Formula: see text], and had highest repeatability.

Introduction: Cognitive impairment in multiple sclerosis (MS) is increasingly being investigated with resting-state functional MRI (rs-fMRI) functional connectivity (FC). However, results remain difficult to interpret, showing both high and low FC associated with cognitive impairment. We conducted a systematic review of rs-fMRI studies in MS to understand whether the direction of FC change relates to cognitive dysfunction, and how this may be influenced by the choice of methodology. Methods: Embase, Medline, and PsycINFO were searched for studies assessing cognitive function and rs-fMRI FC in adults with MS. Results: Fifty-seven studies were included in a narrative synthesis. Of these, 50 found an association between cognitive impairment and FC abnormalities. Worse cognition was linked to high FC in 18 studies, and to low FC in 17 studies. Nine studies found patterns of both high and low FC related to poor cognitive performance, in different regions or for different magnetic resonance (MR) metrics. There was no clear link to increased FC during the early stages of MS and reduced FC in later stages, as predicted by common models of MS pathology. Throughout, we found substantial heterogeneity in study methodology, and carefully consider how this may impact on the observed findings. Discussion: These results indicate an urgent need for greater standardization in the field - in terms of the choice of MRI analysis and the definition of cognitive impairment. This will allow us to use rs-fMRI FC as a biomarker in future clinical studies, and as a tool to understand mechanisms underpinning cognitive symptoms in MS.

Multifrequency bioimpedance spectroscopy (BIS) is an established method for assessing fluid status in chronic kidney disease (CKD). However, the technique is lacking in predictive value and accuracy. BIS algorithms assume constant tissue resistivity, which may vary with changing tissue ionic sodium concentration (Na+). This may introduce significant inaccuracies to BIS outputs. To investigate this, we used 23Na magnetic resonance imaging (MRI) to measure Na+ in muscle and subcutaneous tissues of 10 healthy controls (HC) and 20 patients with CKD 5 (not on dialysis). The extracellular (Re) and intracellular (Ri) resistance, tissue capacitance, extracellular (ECW) and total body water (TBW) were measured using BIS. Tissue water content was assessed using proton density-weighted MRI with fat suppression. BIS-derived volume indices were comparable in the two groups (OH: HC − 0.4 ± 0.9 L vs. CKD 0.5 ± 1.9 L, p = 0.13). However, CKD patients had higher Na+ (HC 21.2 ± 3.0, CKD 25.3 ± 7.4 mmol/L; p = 0.04) and significantly lower Re (HC 693 ± 93.6, CKD 609 ± 74.3 Ohms; p = 0.01); Ri and capacitance did not vary. Na+ showed a significant inverse linear relationship to Re (rs = − 0.598, p

Blood-brain barrier (BBB) breakdown has been hypothesized to play a key role in the onset and progression of Alzheimer's disease (AD). However, the question of whether AD itself contributes to loss of BBB integrity is still uncertain, as many in-vivo studies have failed to detect signs of AD-related BBB breakdown. We hypothesize AD-related BBB damage is subtle, and that these negative results arise from a lack of measurement sensitivity. With the aim of developing a more sensitive measure of BBB breakdown, we have designed a novel MRI scanning protocol to quantify the trans-BBB exchange of endogenous water. Using this method, we detect increased BBB water permeability in a rat model of AD that is associated with reduced expression of the tight junction protein occludin. BBB permeability to MRI contrast agent, assessed using dynamic contrast-enhanced (DCE)-MRI, did not differ between transgenic and wild-type animals and was uncorrelated with occludin expression. Our data supports the occurrence of AD-related BBB breakdown, and indicates that such BBB pathology is subtle and may be undetectable using existing ‘tracer leakage’ methods. Our validated water-exchange MRI method provides a new powerful tool with which to study BBB damage in-vivo.

Purpose: Dynamic contrast-enhanced (DCE) -MRI with Patlak model analysis is increasingly used to quantify low-level blood-brain barrier (BBB) leakage in studies of pathophysiology. We aimed to investigate systematic errors due to physiological, experimental, and modeling factors influencing quantification of the permeability-surface area product PS and blood plasma volume v p, and to propose modifications to reduce the errors so that subtle differences in BBB permeability can be accurately measured. Methods: Simulations were performed to predict the effects of potential sources of systematic error on conventional PS and v p quantification: restricted BBB water exchange, reduced cerebral blood flow, arterial input function (AIF) delay and (Formula presented.) error. The impact of targeted modifications to the acquisition and processing were evaluated, including: assumption of fast versus no BBB water exchange, bolus versus slow injection of contrast agent, exclusion of early data from model fitting and (Formula presented.) correction. The optimal protocol was applied in a cohort of recent mild ischaemic stroke patients. Results: Simulation results demonstrated substantial systematic errors due to the factors investigated (absolute PS error ≤ 4.48 × 10 −4 min −1). However, these were reduced (≤0.56 × 10 −4 min −1) by applying modifications to the acquisition and processing pipeline. Processing modifications also had substantial effects on in-vivo normal-appearing white matter PS estimation (absolute change ≤ 0.45 × 10 −4 min −1). Conclusion: Measuring subtle BBB leakage with DCE-MRI presents unique challenges and is affected by several confounds that should be considered when acquiring or interpreting such data. The evaluated modifications should improve accuracy in studies of neurodegenerative diseases involving subtle BBB breakdown.

PurposeRecent advances in diffusion-weighted MRI provide ‘restricted diffusion signal fraction’ and restricting pore size estimates. Materials based on co-electrospun oriented hollow cylinders have been introduced to provide validation for such methods. This study extends this work, exploring accuracy and repeatability using an extended acquisition on a 300 mT/m gradient human MRI scanner, in substrates closely mimicking tissue, i.e., non-circular cross-sections, intra-voxel fibre crossing, intra-voxel distributions of pore-sizes and smaller pore-sizes overall.MethodsIn a single-blind experiment, diffusion-weighted data were collected from a biomimetic phantom on a 3T Connectom system using multiple gradient directions/diffusion times. Repeated scans established short-term and long-term repeatability. The total scan time (54 minutes) matched similar protocols used in human studies. The number of distinct fibre populations was estimated using spherical deconvolution, and median pore size estimated through the combination of CHARMED and AxCaliber3D framework. Diffusion-based estimates were compared with measurements derived from scanning electron microscopy.ResultsThe phantom contained substrates with different orientations, fibre configurations and pore size distributions. Irrespective of one or two populations within the voxel, the pore-size estimates (~5μm) and orientation-estimates showed excellent agreement with the median values of pore-size derived from scanning electron microscope and phantom configuration. Measurement repeatability depended on substrate complexity, with lower values seen in samples containing crossing-fibres. Sample-level repeatability was found to be good.ConclusionWhile no phantom mimics tissue completely, this study takes a step closer to validating diffusion microstructure measurements for use in vivo by demonstrating the ability to quantify microgeometry in relatively complex configurations.

Cognitive impairment is common in multiple sclerosis (MS) and resting state functional MRI (rs-fMRI) functional connectivity (FC) is increasingly used to study its pathophysiology. However, results remain difficult to interpret, showing both high and low FC associated with cognitive impairment. We conducted a systematic review of rs-fMRI studies in MS to understand whether the direction of FC change relates to cognitive dysfunction, and how this may be influenced by the choice of methodology. Embase, Medline and PsycINFO were searched for studies assessing cognitive function and rs-fMRI FC in adults with MS. Fifty-seven studies were included in a narrative synthesis. Of these, 50 found an association between cognitive impairment and FC abnormalities. Worse cognition was linked to high FC in 18 studies, and to low FC in 17 studies. Nine studies found patterns of both high and low FC related to poor cognitive performance, in different regions or for different MR metrics. There was no clear link to increased FC during early stages of MS and reduced FC in later stages, as predicted by common models of MS pathology. Throughout, we found substantial heterogeneity in study methodology, and carefully consider how this may impact on the observed findings. These results indicate an urgent need for greater standardisation in the field – in the choice of MRI analysis and the definition of cognitive impairment. Through this we will be closer to using rs-fMRI FC as a biomarker in clinical studies, and as a tool to understand mechanisms underpinning cognitive symptoms in MS.Key pointsCognitive impairment in multiple sclerosis (MS) is increasingly being researched with advanced magnetic resonance imaging (MRI) measures, including resting state functional MRI (rs-fMRI)The rs-fMRI functional connectivity (FC) metric is associated with cognitive impairment, and has the potential to be a biomarker of cognitive decline.A main challenge to developing a FC biomarker is the lack of consistency in the direction of FC changes associated with cognitive impairment, with cognitive deficits associated with both lower and higher FC.FC changes don’t appear to be linked to clinical and methodological factors such as disease phenotype, disease duration and brain region or network studied.Overall, there is substantial heterogeneity in study methodology, suggesting an acute need to standardise the study of cognitive impairment in MS and its investigation by rs-fMRI methods.

Purpose\ud Recent advances in diffusion-weighted MRI provide “restricted diffusion signal fraction” and restricting pore size estimates. Materials based on co-electrospun oriented hollow cylinders have been introduced to provide validation for such methods. This study extends this work, exploring accuracy and repeatability using an extended acquisition on a 300 mT/m gradient human MRI scanner, in substrates closely mimicking tissue, that is, non-circular cross-sections, intra-voxel fiber crossing, intra-voxel distributions of pore-sizes, and smaller pore-sizes overall.\ud \ud Methods\ud In a single-blind experiment, diffusion-weighted data were collected from a biomimetic phantom on a 3T Connectom system using multiple gradient directions/diffusion times. Repeated scans established short-term and long-term repeatability. The total scan time (54 min) matched similar protocols used in human studies. The number of distinct fiber populations was estimated using spherical deconvolution, and median pore size estimated through the combination of CHARMED and AxCaliber3D framework. Diffusion-based estimates were compared with measurements derived from scanning electron microscopy.\ud \ud Results\ud The phantom contained substrates with different orientations, fiber configurations, and pore size distributions. Irrespective of one or two populations within the voxel, the pore-size estimates (~5 μm) and orientation-estimates showed excellent agreement with the median values of pore-size derived from scanning electron microscope and phantom configuration. Measurement repeatability depended on substrate complexity, with lower values seen in samples containing crossing-fibers. Sample-level repeatability was found to be good.\ud \ud Conclusion\ud While no phantom mimics tissue completely, this study takes a step closer to validating diffusion microstructure measurements for use in vivo by demonstrating the ability to quantify microgeometry in relatively complex configurations.

The effects of Alzheimer's disease (AD) and ageing on blood-brain barrier (BBB) breakdown are investigated in TgF344-AD and wild-type rats aged 13, 18 and 21 months. Permeability surface area products of the BBB to water (PSw ) and gadolinium-based contrast agent (PSg ) were measured in grey matter using multiflip angle multiecho dynamic contrast-enhanced MRI. At 13 months of age, there was no significant difference in PSw between TgF344-AD and wild-types (p = 0.82). Between 13 and 18 months, PSw increased in TgF344-AD rats (p = 0.027), but not in wild-types (p = 0.99), leading to significantly higher PSw in TgF344-AD rats at 18 months, as previously reported (p = 0.012). Between 18 and 21 months, PSw values increased in wild-types (p = 0.050), but not in TgF344-AD rats (p = 0.50). These results indicate that BBB water permeability is affected by both AD pathology and ageing, but that changes occur earlier in the presence of AD pathology. There were no significant genotype or ageing effects on PSg (p > 0.05). In conclusion, we detected increases in BBB water permeability with age in TgF344-AD and wild-type rats, and found that changes occurred at an earlier age in rats with AD pathology.

Purpose: We introduce a novel, generalized tracer kinetic model selection framework to quantify microvascular characteristics of liver and tumor tissue in gadoxetate-enhanced dynamic contrast-enhanced MRI (DCE-MRI). Methods: Our framework includes a hierarchy of nested models, from which physiological parameters are derived in 2 regimes, corresponding to the active transport and free diffusion of gadoxetate. We use simulations to show the sensitivity of model selection and parameter estimation to temporal resolution, time-series duration, and noise. We apply the framework in 8 healthy volunteers (time-series duration up to 24 minutes) and 10 patients with hepatocellular carcinoma (6 minutes). Results: The active transport regime is preferred in 98.6% of voxels in volunteers, 82.1% of patients’ non-tumorous liver, and 32.2% of tumor voxels. Interpatient variations correspond to known co-morbidities. Simulations suggest both datasets have sufficient temporal resolution and signal-to-noise ratio, while patient data would be improved by using a time-series duration of at least 12 minutes. Conclusions: In patient data, gadoxetate exhibits different kinetics: (a) between liver and tumor regions and (b) within regions due to liver disease and/or tumor heterogeneity. Our generalized framework selects a physiological interpretation at each voxel, without preselecting a model for each region or duplicating time-consuming optimizations for models with identical functional forms.

Objectives Evaluate test-retest repeatability, ability to discriminate between osteoarthritic and healthy participants, and sensitivity to change over 6 months, of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) biomarkers in knee OA. Methods Fourteen individuals aged 40–60 with mild-moderate knee OA and 6 age-matched healthy volunteers (HV) underwent DCE-MRI at 3 T at baseline, 1 month and 6 months. Voxelwise pharmacokinetic modelling of dynamic data was used to calculate DCE-MRI biomarkers including Ktrans and IAUC60. Median DCE-MRI biomarker values were extracted for each participant at each study visit. Synovial segmentation was performed using both manual and semiautomatic methods with calculation of an additional biomarker, the volume of enhancing pannus (VEP). Test-retest repeatability was assessed using intraclass correlation coefficients (ICC). Smallest detectable differences (SDDs) were calculated from test-retest data. Discrimination between OA and HV was assessed via calculation of between-group standardised mean differences (SMD). Responsiveness was assessed via the number of OA participants with changes greater than the SDD at 6 months. Results Ktrans demonstrated the best test-retest repeatability (Ktrans/IAUC60/VEP ICCs 0.90/0.84/0.40, SDDs as % of OA mean 33/71/76%), discrimination between OA and HV (SMDs 0.94/0.54/0.50) and responsiveness (5/1/1 out of 12 OA participants with 6-month change > SDD) when compared to IAUC60 and VEP. Biomarkers derived from semiautomatic segmentation outperformed those derived from manual segmentation across all domains. Conclusions Ktrans demonstrated the best repeatability, discrimination and sensitivity to change suggesting that it is the optimal DCE-MRI biomarker for use in experimental medicine studies. Key Points • Dynamic contrast-enhanced MRI (DCE-MRI) provides quantitative measures of synovitis in knee osteoarthritis which may permit early assessment of efficacy in experimental medicine studies. • This prospective observational study compared DCE-MRI biomarkers across domains relevant to experimental medicine: test-retest repeatability, discriminative validity and sensitivity to change. • The DCE-MRI biomarker Ktransdemonstrated the best performance across all three domains, suggesting that it is the optimal biomarker for use in future interventional studies.

Microscopic diffusion anisotropy imaging using diffusion-weighted MRI and multidimensional diffusion encoding is a promising method for quantifying clinically and scientifically relevant microstructural properties of neural tissue. Several methods for estimating microscopic fractional anisotropy (µFA), a normalized measure of microscopic diffusion anisotropy, have been introduced but the differences between the methods have received little attention thus far. In this study, the accuracy and precision of µFA estimation using q-space trajectory encoding and different signal models were assessed using imaging experiments and simulations. Three healthy volunteers and a microfibre phantom were imaged with five non-zero b-values and gradient waveforms encoding linear and spherical b-tensors. Since the ground-truth µFA was unknown in the imaging experiments, Monte Carlo random walk simulations were performed using axon-mimicking fibres for which the ground truth was known. Furthermore, parameter bias due to time-dependent diffusion was quantified by repeating the simulations with tuned waveforms, which have similar power spectra, and with triple diffusion encoding, which, unlike q-space trajectory encoding, is not based on the assumption of time-independent diffusion. The truncated cumulant expansion of the powder-averaged signal, gamma-distributed diffusivities assumption, and q-space trajectory imaging, a generalization of the truncated cumulant expansion to individual signals, were used to estimate µFA. The gamma-distributed diffusivities assumption consistently resulted in greater µFA values than the second order cumulant expansion, 0.1 greater when averaged over the whole brain. In the simulations, the generalized cumulant expansion provided the most accurate estimates. Importantly, although time-dependent diffusion caused significant overestimation of µFA using all the studied methods, the simulations suggest that the resulting bias in µFA is less than 0.1 in human white matter.

Cognitive impairment in multiple sclerosis is associated with functional connectivity abnormalities, but the pathological substrates of these abnormalities are not well understood. It has been proposed that resting-state network nodes that integrate information from disparate regions are susceptible to metabolic stress, which may impact functional connectivity. In multiple sclerosis, pathology could increase metabolic stress within axons, damaging the anatomical connections of network regions, and leading to functional connectivity changes. We tested this hypothesis by assessing whether resting state network regions that show functional connectivity abnormalities in people with cognitive impairment also show anatomical connectivity abnormalities.Multimodal MRI and neuropsychological assessments were performed in 102 relapsing remitting multiple sclerosis patients and 27 healthy controls. Patients were considered cognitively impaired if they obtained a z-score of ≤1.5 on ≥2 tests of the Brief Repeatable Battery of Neuropsychological Tests (n=55). Functional connectivity was assessed with Independent Component Analysis of resting state fMRI images, and anatomical connectivity with Anatomical Connectivity Mapping of diffusion-weighted MRI. Exploratory analyses of fractional anisotropy and cerebral blood flow changes were conducted to assess local tissue characteristics.We found significantly decreased functional connectivity in the anterior and posterior default mode networks and significant increases in the right and left frontoparietal networks in cognitively impaired relative to cognitively preserved patients. Networks showing functional abnormalities also showed reduced anatomical connectivity and white matter microstructure integrity as well as reduced local tissue cerebral blood flow.Our results identify key pathological correlates of functional connectivity abnormalities associated with impaired cognitive function in multiple sclerosis, consistent with metabolic dysfunction in functional network regions.

Imaging biomarkers require technical, biological, and clinical validation to be translated into robust tools in research or clinical settings. This study contributes to the technical validation of radiomic features from magnetic resonance imaging (MRI) by evaluating the repeatability of features from four MR sequences: pre-contrast T1- and T2-weighted images, pre-contrast quantitative T1 maps (qT1), and contrast-enhanced T1-weighted images. Fifty-one patients with colorectal cancer liver metastases were scanned twice, up to 7 days apart. Repeatability was quantified using the intraclass correlation coefficient (ICC) and repeatability coefficient (RC), and the impact of non-Gaussian feature distributions and image normalisation was evaluated. Most radiomic features had non-Gaussian distributions, but Box&ndash, Cox transformations enabled ICCs and RCs to be calculated appropriately for an average of 97% of features across sequences. ICCs ranged from 0.30 to 0.99, with volume and other shape features tending to be most repeatable, volume ICC &gt, 0.98 for all sequences. 19% of features from non-normalised images exhibited significantly different ICCs in pair-wise sequence comparisons. Normalisation tended to increase ICCs for pre-contrast T1- and T2-weighted images, and decrease ICCs for qT1 maps. RCs tended to vary more between sequences than ICCs, showing that evaluations of feature performance depend on the chosen metric. This work suggests that feature-specific repeatability, from specific combinations of MR sequence and pre-processing steps, should be evaluated to select robust radiomic features as biomarkers in specific studies. In addition, as different repeatability metrics can provide different insights into a specific feature, consideration of the appropriate metric should be taken in a study-specific context.

BackgroundBlood–brain barrier (BBB) disruption has been noted in animal models of Parkinson’s disease (PD) and forms the basis of the vascular hypothesis of neurodegeneration, yet clinical studies are lacking.ObjectiveTo determine alterations in BBB integrity in PD, with comparison to cerebrovascular disease.MethodsDynamic contrast enhanced magnetic resonance images were collected from 49 PD patients, 15 control subjects with cerebrovascular disease [control positive (CP)] and 31 healthy control subjects [control negative (CN)], with all groups matched for age. Quantitative maps of the contrast agent transfer coefficient across the BBB (Ktrans) and plasma volume (vp) were produced using Patlak analysis. Differences in Ktrans and vp were assessed with voxel-based analysis as well as in regions associated with PD pathophysiology. In addition, the volume of white matter lesions (WMLs) was obtained from T2-weighted fluid attenuation inversion recovery (FLAIR) images.ResultsHigher Ktrans, reflecting higher BBB leakage, was found in the PD group than in the CN group using voxel-based analysis; differences were most prominent in the posterior white matter regions. Region of interest analysis confirmed Ktrans to be significantly higher in PD than in CN, predominantly driven by differences in the substantia nigra, normal-appearing white matter, WML and the posterior cortex. WML volume was significantly higher in PD compared to CN. Ktrans values and WML volume were similar in PD and CP, suggesting a similar burden of cerebrovascular disease despite lower cardiovascular risk factors.ConclusionThese results show BBB disruption in PD.

Simple Summary Medical images are data. They contain more information than is routinely identified by radiologists reading scans. Many scientists are investigating if extracting shape and grey-scale features from images can predict which oncology patients will respond to therapy. This approach, termed ‘radiomics’, must be validated before being ready for clinical use. One step is to determine measurement repeatability to ensure that radiomic features are robust, and that changes in features reflect genuine changes in tumours. In this study patients had two repeated sets of magnetic resonance imaging scans. We found that radiomic feature repeatability varied depending on scan acquisition parameters and the use of an administered contrast agent. We also compared how different repeatability assessment methods can best reveal these findings. We conclude that measuring radiomic feature repeatability is essential, but is also complex and prone to pitfalls. Overall, our study provides several insights into how radiomic feature repeatability is best assessed. Abstract Imaging biomarkers require technical, biological, and clinical validation to be translated into robust tools in research or clinical settings. This study contributes to the technical validation of radiomic features from magnetic resonance imaging (MRI) by evaluating the repeatability of features from four MR sequences: pre-contrast T1- and T2-weighted images, pre-contrast quantitative T1 maps (qT1), and contrast-enhanced T1-weighted images. Fifty-one patients with colorectal cancer liver metastases were scanned twice, up to 7 days apart. Repeatability was quantified using the intraclass correlation coefficient (ICC) and repeatability coefficient (RC), and the impact of non-Gaussian feature distributions and image normalisation was evaluated. Most radiomic features had non-Gaussian distributions, but Box–Cox transformations enabled ICCs and RCs to be calculated appropriately for an average of 97% of features across sequences. ICCs ranged from 0.30 to 0.99, with volume and other shape features tending to be most repeatable; volume ICC > 0.98 for all sequences. 19% of features from non-normalised images exhibited significantly different ICCs in pair-wise sequence comparisons. Normalisation tended to increase ICCs for pre-contrast T1- and T2-weighted images, and decrease ICCs for qT1 maps. RCs tended to vary more between sequences than ICCs, showing that evaluations of feature performance depend on the chosen metric. This work suggests that feature-specific repeatability, from specific combinations of MR sequence and pre-processing steps, should be evaluated to select robust radiomic features as biomarkers in specific studies. In addition, as different repeatability metrics can provide different insights into a specific feature, consideration of the appropriate metric should be taken in a study-specific context.

Introduction: Novel biomarkers are needed to improve assessment of ILD. Oxygen enhanced MRI (OE-MRI) monitors regional O2 delivery from changes in the MRI relaxation time T1 in response to hyperoxia. We present OE-MRI biomarkers in different ILD phenotypes (IPF, DI-ILD, CTD-ILD, HSP) acquired in a prospective observational study and compare them with lung function tests under standard clinical care. Methods: Patients recruited and scans analysed to date are summarised in fig 1. The OE MR parameters considered were: baseline T1, change in delta pO2 (ΔpO2), O2 wash-in time and ventilated volume fraction. Biomarker values at each visit and the change between visits were compared with lung function tests (FVC%, FEV1%, Tlco%, KCO%) using Pearson correlation (no correction for multiple comparisons). Results: In the IPF subgroup, T1 correlated with Tlco% and KCO% (r=-0.43, p=0.027 and r=-0.43, p=0.028). Changes between visits in ΔpO2 and in KCO%(r = 0.86, p=0.003) were also correlated. No significant correlations were found in other phenotypes. Conclusions: In IPF, change between visits in ΔpO2 correlates with the change in KCO%, but not in the other ILD subtypes.

Introduction: Patients with pulmonary hypertension (PH) require repeat investigation to allow risk stratification and guide optimal therapy. These tests include CT and catheter studies utilising ionising radiation and contrast. Oxygen-enhanced magnetic resonance imaging (OE-MRI) is an alternative technique that provides measures related to regional ventilation, diffusion and perfusion and may provide novel biomarkers of PH severity. Aims: Assess correlation of OE-MRI measures with standard clinical measures of PH severity. Methods: Newly diagnosed group 1 or 4 PH patients underwent OE-MRI, with resultant measures compared with standard of care clinical outputs via Spearman’s correlation. Results: 12 patients were scanned (mean age 54.9±16.6 years old, mean pulmonary artery pressure 41.3±13.9mmHg). Significant correlation was seen between right ventricular (RV) end diastolic volume and median OE-MRI oxygen wash in time (WIT) (rs= 0.571, p= 0.048) and WIT interquartile range – a marker of spatial disease heterogeneity (rs= 0.857, p= 0.003). The WIT interquartile range also showed a moderate, negative association with RV ejection fraction (rs= -0.618, p=0.034). Interquartile range of native lung T1 relaxation time negatively correlated with TLCO (rs= -0.786, p= 0.021). Conclusions: Significant correlations have been demonstrated between OE-MRI measures of gas delivery and established markers of PH severity.

Since the emergence of the novel coronavirus SARS-CoV-2 in Wuhan, China in 2019 [1], the resulting COVID-19 disease has rapidly transitioned into a global pandemic with over 31 000 deaths and 215 000 infections in the UK as of 10th May 2020 [2]. Confirmation of SARS-CoV-2 infection requires reverse-transcriptase polymerase chain reaction (RT-PCR) testing [3]. Chest radiographic and/or computed tomography imaging is also central to diagnosis and management [4]., The National COVID-19 Chest Imaging Database (NCCID) is a repository of chest X-Ray, CT and MRI images and clinical data from COVID-19 patients across the UK, to support research and development of AI technology that may proffer insights into the disease.

There has been an increasing interest in examining organisational principles of the cerebral cortex (and subcortical regions) using different MRI features such as structural or functional connectivity. Despite the widespread interest, introductory tutorials on the underlying technique targeted for the novice neuroimager are sparse in the literature. Articles that investigate various “neural gradients” (for example based on region studied “cortical gradients,” “cerebellar gradients,” “hippocampal gradients” etc … or feature of interest “functional gradients,” “cytoarchitectural gradients,” “myeloarchitectural gradients” etc …) have increased in popularity. Thus, we believe that it is opportune to discuss what is generally meant by “gradient analysis”. We introduce basics concepts in graph theory, such as graphs themselves, the degree matrix, and the adjacency matrix. We discuss how one can think about gradients of feature similarity (the similarity between timeseries in fMRI, or streamline in tractography) using graph theory and we extend this to explore such gradients across the whole MRI scale; from the voxel level to the whole brain level. We proceed to introduce a measure for quantifying the level of similarity in regions of interest. We propose the term “the Vogt-Bailey index” for such quantification to pay homage to our history as a brain mapping community. We run through the techniques on sample datasets including a brain MRI as an example of the application of the techniques on real data and we provide several appendices that expand upon details. To maximise intuition, the appendices contain a didactic example describing how one could use these techniques to solve a particularly pernicious problem that one may encounter at a wedding. Accompanying the article is a tool, available in both MATLAB and Python, that enables readers to perform the analysis described in this article on their own data. We refer readers to the graphical abstract as an overview of the analysis pipeline presented in this work., Graphical abstract The two basic algorithms to compute the VB Index and the principal gradient. The algorithm on the left depicts a searchlight algorithm that identifies local borders. The algorithm on the right (yellow route) depicts the creation of a gradient map and single VB Index for the whole brain or (inclusion of orange route) multiple clusters.Image 1, Highlights • This article provides a beginner friendly review of the main steps for creating gradient maps. • We introduce a new index for quantifying mesoscopic gradients (the “VB Index”). • We use historical background to highlight the need for such quantification. • Software for computing gradient maps and the VB Index is made available.

BACKGROUND AND PURPOSE Studies in animal models suggest that inflammation is a major contributor to secondary injury after intracerebral hemorrhage (ICH). Direct, noninvasive monitoring of inflammation in the human brain after ICH will facilitate early-phase development of anti-inflammatory treatments. We sought to investigate the feasibility of multimodality brain imaging in subacute ICH. METHODS Acute ICH patients were recruited to undergo multiparametric MRI (including dynamic contrast-enhanced measurement of blood-brain barrier transfer constant (Ktrans) and PET with [11C]-(R)-PK11195). [11C]-(R)-PK11195 binds to the translocator protein 18 kDa (TSPO), which is rapidly upregulated in activated microglia. Circulating inflammatory markers were measured at the time of PET. RESULTS Five patients were recruited to this feasibility study with imaging between 5 and 16 days after onset. Etiologies included hypertension-related small vessel disease, cerebral amyloid angiopathy (CAA), cavernoma, and arteriovenous malformation (AVM). [11C]-(R)-PK11195 binding was low in all hematomas and 2 (patient 2 [probable CAA] and 4 [AVM]) cases showed widespread increase in binding in the perihematomal region versus contralateral. All had increased Ktrans in the perihematomal region (mean difference = 2.2 × 10−3 minute−1; SD = 1.6 × 10−3 minute−1) versus contralateral. Two cases (patients 1 [cavernoma] and 4 [AVM]) had delayed surgery (3 and 12 months post-onset, respectively) with biopsies showing intense microglial activation in perilesional tissue. CONCLUSIONS Our study demonstrates for the first time the feasibility of performing complex multimodality brain imaging for noninvasive monitoring of neuroinflammation for this severe stroke subtype.

The hub-and-spoke model of semantic cognition seeks to reconcile embodied views of a fully distributed semantic network with patient evidence, primarily from semantic dementia, who demonstrate modality-independent conceptual deficits associated with atrophy centred on the ventrolateral anterior temporal lobe. The proponents of this model have recently suggested that the temporal cortex is a graded representational space where concepts become less linked to a specific modality as they are processed farther away from primary and secondary sensory cortices and towards the ventral anterior temporal lobe. To explore whether there is evidence that the connectivity patterns of the temporal lobe converge in its ventral anterior end the current study uses three dimensional Laplacian eigenmapping, a technique that allows visualisation of similarity in a low dimensional space. In this space similarity is encoded in terms of distances between data points. We found that the ventral and anterior temporal lobe is in a unique position of being at the centre of mass of the data pointswithin the connective similarity space. This can be interpreted as the area where the connectivity profiles of all other temporal cortex voxels converge. This study is the first to explicitly investigate the pattern of connectivity and thus provides the missing link in the evidence that the ventral anterior temporal lobe can be considered a multi-modal graded hub., peer-reviewed

Introduction: Apparent diffusion coefficient (ADC) is a measure of gas diffusion in the airspaces, where restrictions by tissue boundaries provide information about lung microstructure down to the alveolar level. Diffusion-weighted (DW) MRI of the lung with hyperpolarised helium in idiopathic pulmonary fibrosis (IPF) has shown that ADC correlates with DLCO, KCO and CT fibrosis score (Chan, H-F. et al. Radiology 2019; doi:10.1148/radiol.2019181714) but to date no data are available on the utility of 129-xenon (129Xe) diffusion in interstitial lung disease (ILD). Aim: To evaluate the ability of 129Xe DW-MRI to distinguish between ILD subtypes. Methods: A prospective, multicentre study of patients with ILD including drug induced ILD (DI-ILD), hypersensitivity pneumonitis (HP), IPF and connective tissue disease ILD (CTD-ILD). Hyperpolarised 129Xe DW-MRI was performed on a 1.5 T scanner and mean ADC was calculated. Results: To date, 33 patients (6 DI-ILD, 7 HP, 15 IPF, 5 CTD-ILD) have undergone baseline 129Xe DW-MRI. There was a significant difference in mean ADC between the ILD subtypes (p=0.011), with the significant difference occuring between the HP (median: 0.038cm2/s) and IPF (median: 0.048cm2/s) groups (p Conclusions: We demonstrate a correlation between mean 129Xe ADC and DLCO but not FVC. Our findings suggest significant differences in mean ADC between IPF and HP. Therefore, 129Xe DW-MRI could potentially have a role in differentiating changes in the airway microstructure in ILD subtypes.

Introduction: Hyperpolarised 129-xenon (129Xe) MR spectroscopy (MRS) can be used as a quantitative marker of gas exchange in interstitial lung disease (ILD). The ratio of the uptake of 129Xe in the red blood cells to the tissue/plasma (RBC:TP) has been shown to be reduced by 70% in idiopathic pulmonary fibrosis (IPF) patients when compared with healthy volunteers (Kaushik, S.S. et al. J Appl Physiol 2014; 117:577-585). In IPF, a significant decline in 129Xe RBC:TP over 12 months has been demonstrated but no significant change in DLCO or KCO (Weatherley, N.D. et al. Thorax 2018 [Epub ahead of print]). Aim: To compare longitudinal changes in 129Xe RBC:TP with changes in FVC and DLCO between ILD subtypes. Methods: A prospective, multicentre study of ILD patients including drug induced ILD (DI-ILD), hypersensitivity pneumonitis (HP), IPF and connective tissue disease ILD (CTD-ILD). Hyperpolarised 129Xe MRS was performed on a 1.5 T scanner. Results: To date, 18 patients (5 DI-ILD, 5 HP, 6 IPF, 2 CTD-ILD) have undergone 129Xe MRS on two separate visits (6 weeks apart for DI-ILD/HP and 6 months apart for IPF/CTD-ILD). There was a significant difference in longitudinal change in RBC:TP between the HP and IPF groups (p=0.022). Median change in RBC:TP in the HP and IPF groups was 0.022 and -0.023 respectively. There was no significant difference in longitudinal change in FVC% predicted (p=0.79) or DLCO% predicted (p=0.39) between the ILD subtypes. Conclusions: Our findings demonstrate that 129Xe RBC:TP has sensitivity to longitudinal change with significant differences between IPF and HP patients, whilst FVC and DLCO showed no change, suggesting that RBC:TP is more sensitive to change than PFTs in ILD.

Diffusion magnetic resonance imaging (dMRI) is considered as a useful tool to study solid tumours. However, the interpretation of dMRI signal and validation of quantitative measurements of is challenging. One way to address these challenges is by using a standard reference material that can mimic tumour cell microstructure. There is a growing interest in using hollow polymeric microspheres, mainly prepared by multiple steps, as mimics of cells in healthy and diseased tissue. The present work reports on tumour cell-mimicking materials composed of hollow microspheres for application as a standard material in dMRI. These microspheres were prepared via one-step co-electrospraying process. The shell material was poly(D,L-lactic-co-glycolic acid) (PLGA) polymers with different molecule weights and/or ratios of glycolic acid-to-lactic, while the core was polyethylene glycol (PEG) or ethylene glycol. The resultant co-electrosprayed products were characterised by optical microscopy, scanning electron microscopy (SEM) and synchrotron X-ray micro-CT. These products were found to have variable structures and morphologies, e.g. from spherical particles with/without surface hole, through beaded fibres to smooth fibres, which mainly depend on PLGA composition and core materials. Only the shell material of PLGA polymer with ester terminated, Mw 50,000–75,000 g mol −1 , and lactide:glycolide 85:15 formed hollow microspheres via the co-electrospraying process using the core material of 8 wt% PEG/chloroform as the core. A water-filled test object (or phantom) was designed and constructed from samples of the material generated from co-electrosprayed PLGA microspheres and tested on a 7 T MRI scanner. The preliminary MRI results provide evidence that hollow PLGA microspheres can restrict/hinder water diffusion as cells do in tumour tissue, implying that the phantom may be suitable for use as a quantitative validation and calibration tool for dMRI.

The blood-brain barrier (BBB) regulates the transfer of solutes and essential nutrients into the brain. Growing evidence supports BBB dysfunction in a range of acute and chronic brain diseases, justifying the need for novel research and clinical tools that can non-invasively detect, characterize, and quantify BBB dysfunction in-vivo. Many approaches already exist for measuring BBB dysfunction in man using positron emission tomography and magnetic resonance imaging (e.g. dynamic contrast-enhanced MRI measurements of gadolinium leakage). This review paper focusses on MRI measurements of water exchange across the BBB, which occurs through a wide range of pathways, and is likely to be a highly sensitive marker of BBB dysfunction. Key mathematical models and acquisition methods are discussed for the two main approaches: those that utilize contrast agents to enhance relaxation rate differences between the intravascular and extravascular compartments and so enhance the sensitivity of MRI signals to BBB water exchange, and those that utilize the dynamic properties of arterial spin labelling to first isolate signal from intravascular spins and then estimate the impact of water exchange on the evolving signal. Data from studies in healthy and pathological brain tissue are discussed, in addition to validation studies in rodents.

Objective. The use of diffusion magnetic resonance imaging (dMRI) opens the door to characterizing brain microstructure because water diffusion is anisotropic in axonal fibres in brain white matter and is sensitive to tissue microstructural changes. As dMRI becomes more sophisticated and microstructurally informative, it has become increasingly important to use a reference object (usually called an imaging phantom) for validation of dMRI. This study aims to develop axon-mimicking physical phantoms from biocopolymers and assess their feasibility for validating dMRI measurements. Approach. We employed a simple and one-step method—coaxial electrospinning—to prepare axon-mimicking hollow microfibres from polycaprolactone-b-polyethylene glycol (PCL-b-PEG) and poly(D, L-lactide-co-glycolic) acid (PLGA), and used them as building elements to create axon-mimicking phantoms. Electrospinning was firstly conducted using two types of PCL-b-PEG and two types of PLGA with different molecular weights in various solvents, with different polymer concentrations, for determining their spinnability. Polymer/solvent concentration combinations with good fibre spinnability were used as the shell material in the following co-electrospinning process in which the polyethylene oxide polymer was used as the core material. Following the microstructural characterization of both electrospun and co-electrospun fibres using optical and electron microscopy, two prototype phantoms were constructed from co-electrospun anisotropic hollow microfibres after inserting them into water-filled test tubes. Main results. Hollow microfibres that mimic the axon microstructure were successfully prepared from the appropriate core and shell material combinations. dMRI measurements of two phantoms on a 7 tesla (T) pre-clinical scanner revealed that diffusivity and anisotropy measurements are in the range of brain white matter. Significance. This feasibility study showed that co-electrospun PCL-b-PEG and PLGA microfibre-based axon-mimicking phantoms could be used in the validation of dMRI methods which seek to characterize white matter microstructure.

Purpose: Hypoxia is associated with poor prognosis and is predictive of poor response to cancer treatments, including radiotherapy. Developing noninvasive biomarkers that both detect hypoxia prior to treatment and track change in tumor hypoxia following treatment is required urgently. Experimental Design: We evaluated the ability of oxygen-enhanced MRI (OE-MRI) to map and quantify therapy-induced changes in tumor hypoxia by measuring oxygen-refractory signals in perfused tissue (perfused Oxy-R). Clinical first-in-human study in patients with non–small cell lung cancer (NSCLC) was performed alongside preclinical experiments in two xenograft tumors (Calu6 NSCLC model and U87 glioma model). Results: MRI perfused Oxy-R tumor fraction measurement of hypoxia was validated with ex vivo tissue pathology in both xenograft models. Calu6 and U87 experiments showed that MRI perfused Oxy-R tumor volume was reduced relative to control following single fraction 10-Gy radiation and fractionated chemoradiotherapy (P < 0.001) due to both improved perfusion and reduced oxygen consumption rate. Next, evaluation of 23 patients with NSCLC showed that OE-MRI was clinically feasible and that tumor perfused Oxy-R volume is repeatable [interclass correlation coefficient: 0.961 (95% CI, 0.858–0.990); coefficient of variation: 25.880%]. Group-wise perfused Oxy-R volume was reduced at 14 days following start of radiotherapy (P = 0.015). OE-MRI detected between-subject variation in hypoxia modification in both xenograft and patient tumors. Conclusions: These findings support applying OE-MRI biomarkers to monitor hypoxia modification, to stratify patients in clinical trials of hypoxia-modifying therapies, to identify patients with hypoxic tumors that may fail treatment with immunotherapy, and to guide adaptive radiotherapy by mapping regional hypoxia.

Oncological use of anti-angiogenic VEGF inhibitors has been limited by the lack of informative biomarkers. Previously we reported circulating Tie2 as a vascular response biomarker for bevacizumab-treated ovarian cancer patients. Using advanced MRI and circulating biomarkers we have extended these findings in metastatic colorectal cancer (n = 70). Bevacizumab (10 mg/kg) was administered to elicit a biomarker response, followed by FOLFOX6-bevacizumab until disease progression. Bevacizumab induced a correlation between Tie2 and the tumor vascular imaging biomarker, Ktrans (R:−0.21 to 0.47) implying that Tie2 originated from the tumor vasculature. Tie2 trajectories were independently associated with pre-treatment tumor vascular characteristics, tumor response, progression free survival (HR for progression = 3.01, p = 0.00014; median PFS 248 vs. 348 days p = 0.0008) and the modeling of progressive disease (p, Identification of response biomarkers is a key step towards the development of personalised care. Here, Jayson et al. identify plasma Tie2 as a biomarker for the response of the tumor vasculature to anti-angiogenics in patients with metastatic colorectal cancer, suggesting that monitoring Tie2 levels may help guide therapy in the clinics.

Ataxia-Telangiectasia (A-T) is characterised by progressive ataxia, immunodeficiency, malignancy and chronic lung infection. Respiratory disease and cancer are leading causes of death. Imaging the lungs is challenging due to sensitivity to ionising radiation. Dynamic oxygen enhanced MRI (OE-MRI) characterises the arrival of oxygen into lung tissue by monitoring changes in MR signal on hyperoxia. No breath-hold is required. OEMRI has not previously been used in A-T. Aims: We aimed to assess the feasibility of undertaking OE-MRI in A-T. We hypothesized that children with A-T would be able to successfully complete an OE-MRI protocol. Methods: We studied children and young people with A-T. Participants have been enrolled to a 3 year cohort study. OE-MRI was done in a 1.5T GE systems machine, with image analysis with the Pulmolux (Bioxydyn, Ltd) platform. Results: We present early results from the first 5 participants (aged 9 – 15). All children undertook the OE-MRI protocol without sedation. Patient experience feedback from the scans has been positive. The median signal enhancement due to O2 breathing was 15%. Heterogeneity of oxygen delivery was observed, suggestive of ventilation variability. Conclusions: OE-MRI is feasible in children with A-T without sedation. Work is ongoing to understand OE-MRI reproducibility and role in A-T. Fig: Overlay of O2 enhancement map [%] over anatomical images.