Towards a Whole Sample Imaging Approach Using Diffusion Tensor Imaging to Examine the Foreign Body Response to Explanted Medical Devices.

Analysing the composition and organisation of the fibrous capsule formed as a result of the Foreign Body Response (FBR) to medical devices, is imperative for medical device improvement and biocompatibility. Typically, analysis is performed using histological techniques which often involve random sampling strategies. This method is excellent for acquiring representative values but can miss the unique spatial distribution of features in 3D, especially when analysing devices used in large animal studies. To overcome this limitation, we demonstrate a non-destructive method for high-resolution large sample imaging of the fibrous capsule surrounding human-sized implanted devices using diffusion tensor imaging (DTI). In this study we analyse the fibrous capsule surrounding two unique macroencapsulation devices that have been implanted in a porcine model for 21 days. DTI is used for 3D visualisation of the microstructural organisation and validated using the standard means of fibrous capsule investigation; histological analysis and qualitative micro computed tomography (microCT) and scanning electron microscopy (SEM) imaging. DTI demonstrated the ability to distinguish microstructural differences in the fibrous capsules surrounding two macroencapsulation devices made from different materials and with different surface topographies. DTI-derived metrics yielded insight into the microstructural organisation of both capsules which was corroborated by microCT, SEM and histology. The non-invasive characterisation of the integration of implants in the body has the potential to positively influence analysis methods in pre-clinical studies and accelerate the clinical translation of novel implantable devices.

Ex Vivo Study Using Diffusion Tensor Imaging to Identify Biomarkers of Atherosclerotic Disease in Human Cadaveric Carotid Arteries.

BACKGROUND: This study aims to address the potential of ex vivo diffusion tensor imaging to provide insight into the microstructural composition and morphological arrangement of aged human atherosclerotic carotid arteries. METHODS: In this study, whole human carotid arteries were investigated both anatomically and by comparing healthy and diseased regions. Nonrigid image registration was used with unsupervised segmentation to investigate the influence of elastin, collagen, cell density, glycosaminoglycans, and calcium on diffusion tensor imaging derived metrics (fractional anisotropy and mean diffusivity). Early stage atherosclerotic features were also investigated in terms of microstructural components and diffusion tensor imaging metrics. RESULTS: All vessels displayed a dramatic decrease in fractional anisotropy compared with healthy animal arterial tissue, while the mean diffusivity was sensitive to regions of advanced disease. Elastin content strongly correlated with both fractional anisotropy (r>0.7, P<0.001) and mean diffusivity (r>-0.79, P<0.0002), and the thickened intima was also distinguishable from arterial media by these metrics. CONCLUSIONS: These different investigations point to the potential of diffusion tensor imaging to identify characteristics of arterial disease progression, at early and late-stage lesion development.

Exploring arterial tissue microstructural organization using non-Gaussian diffusion magnetic resonance schemes.

The purpose of this study was to characterize the alterations in microstructural organization of arterial tissue using higher-order diffusion magnetic resonance schemes. Three porcine carotid artery models namely; native, collagenase treated and decellularized, were used to estimate the contribution of collagen and smooth muscle cells (SMC) on diffusion signal attenuation using gaussian and non-gaussian schemes. The samples were imaged in a 7 T preclinical scanner. High spatial and angular resolution diffusion weighted images (DWIs) were acquired using two multi-shell (max b-value = 3000 s/mm2) acquisition protocols. The processed DWIs were fitted using monoexponential, stretched-exponential, kurtosis and bi-exponential schemes. Directionally variant and invariant microstructural parametric maps of the three artery models were obtained from the diffusion schemes. The parametric maps were used to assess the sensitivity of each diffusion scheme to collagen and SMC composition in arterial microstructural environment. The inter-model comparison showed significant differences across the considered models. The bi-exponential scheme based slow diffusion compartment (Ds) was highest in the absence of collagen, compared to native and decellularized microenvironments. In intra-model comparison, kurtosis along the radial direction was the highest. Overall, the results of this study demonstrate the efficacy of higher order dMRI schemes in mapping constituent specific alterations in arterial microstructure.

Quantitative susceptibility mapping of carotid arterial tissue ex vivo: Assessing sensitivity to vessel microstructural composition.

PURPOSE: To characterize microstructural contributions to the magnetic susceptibility of carotid arteries. METHOD: Arterial vessels were scanned using high-resolution quantitative susceptibility mapping (QSM) at 7 Tesla. Models of vessel degradation were generated using ex vivo porcine carotid arteries that were subjected to several different enzymatic digestion treatments that selectively removed microstructural components (smooth muscle cells, collagen, and elastin). Magnetic susceptibilities measured in these tissue models were compared to those in untreated (native) porcine arteries. Magnetic susceptibility measured in native porcine carotid arteries was further compared to the susceptibility of cadaveric human carotid arteries to investigate their similarity. RESULTS: The magnetic susceptibility of native porcine vessels was diamagnetic (χnative = -0.1820 ppm), with higher susceptibilities in all models of vessel degradation (χelastin-degraded = -0.0163 ppm; χcollagen-degraded = -0.1158 ppm; χdecellularized = -0.1379 ppm; χfixed native = -0.2199 ppm). Magnetic susceptibility was significantly higher in collagen-degraded compared to native porcine vessels (Tukey-Kramer, P < .01) and between elastin-degraded and all other models (including native, Tukey-Kramer, P < .001). The susceptibility of fixed healthy human arterial tissue was diamagnetic, and no significant difference was found between fixed human and fixed porcine arterial tissue susceptibilities (analysis of variance, P > .05). CONCLUSIONS: Magnetic susceptibility measured using QSM is sensitive to the microstructural composition of arterial vessels-most notably to collagen. The similarity of human and porcine arterial tissue susceptibility values provides a solid basis for translational studies. Because vessel microstructure becomes disrupted during the onset and progression of carotid atherosclerosis, QSM has the potential to provide a sensitive and specific marker of vessel disease.

Model-based Bayesian inference of brain oxygenation using quantitative BOLD.

Streamlined Quantitative BOLD (sqBOLD) is an MR technique that can non-invasively measure physiological parameters including Oxygen Extraction Fraction (OEF) and deoxygenated blood volume (DBV) in the brain. Current sqBOLD methodology rely on fitting a linear model to log-transformed data acquired using an Asymmetric Spin Echo (ASE) pulse sequence. In this paper, a non-linear model implemented in a Bayesian framework was used to fit physiological parameters to ASE data. This model makes use of the full range of available ASE data, and incorporates the signal contribution from venous blood, which was ignored in previous analyses. Simulated data are used to demonstrate the intrinsic difficulty in estimating OEF and DBV simultaneously, and the benefits of the proposed non-linear model are shown. In vivo data are used to show that this model improves parameter estimation when compared with literature values. The model and analysis framework can be extended in a number of ways, and can incorporate prior information from external sources, so it has the potential to further improve OEF estimation using sqBOLD.

Simulations of the effect of diffusion on asymmetric spin echo based quantitative BOLD: An investigation of the origin of deoxygenated blood volume overestimation.

Quantitative BOLD (qBOLD) is a technique for mapping oxygen extraction fraction (OEF) and deoxygenated blood volume (DBV) in the human brain. Recent measurements using an asymmetric spin echo (ASE) based qBOLD approach produced estimates of DBV which were systematically higher than measurements from other techniques. In this study, we investigate two hypotheses for the origin of this DBV overestimation using simulations and consider the implications for experimental measurements. Investigations were performed by combining Monte Carlo simulations of extravascular signal with an analytical model of the intravascular signal. HYPOTHESIS 1: DBV overestimation is due to the presence of intravascular signal which is not accounted for in the analysis model. Intravascular signal was found to have a weak effect on qBOLD parameter estimates. HYPOTHESIS 2: DBV overestimation is due to the effects of diffusion which are not accounted for in the analysis model. The effect of diffusion on the extravascular signal was found to result in a vessel radius dependent variation in qBOLD parameter estimates. In particular, DBV overestimation peaks for vessels with radii from 20 to 30 µm and is OEF dependent. This results in the systematic underestimation of OEF. IMPLICATIONS: The impact on experimental qBOLD measurements was investigated by simulating a more physiologically realistic distribution of vessel sizes with a small number of discrete radii. Overestimation of DBV consistent with previous experiments was observed, which was also found to be OEF dependent. This results in the progressive underestimation of the measured OEF. Furthermore, the relationship between the measured OEF and the true OEF was found to be dependent on echo time and spin echo displacement time. The results of this study demonstrate the limitations of current ASE based qBOLD measurements and provide a foundation for the optimisation of future acquisition approaches.

Prospects for investigating brain oxygenation in acute stroke: Experience with a non-contrast quantitative BOLD based approach.

Metabolic markers of baseline brain oxygenation and tissue perfusion have an important role to play in the early identification of ischaemic tissue in acute stroke. Although well established MRI techniques exist for mapping brain perfusion, quantitative imaging of brain oxygenation is poorly served. Streamlined-qBOLD (sqBOLD) is a recently developed technique for mapping oxygenation that is well suited to the challenge of investigating acute stroke. In this study a noninvasive serial imaging protocol was implemented, incorporating sqBOLD and arterial spin labelling to map blood oxygenation and perfusion, respectively. The utility of these parameters was investigated using imaging based definitions of tissue outcome (ischaemic core, infarct growth and contralateral tissue). Voxel wise analysis revealed significant differences between all tissue outcomes using pairwise comparisons for the transverse reversible relaxation rate (R 2 '), deoxygenated blood volume (DBV) and deoxyghaemoglobin concentration ([dHb]; p < 0.01 in all cases). At the patient level (n = 9), a significant difference was observed for [dHb] between ischaemic core and contralateral tissue. Furthermore, serial analysis at the patient level (n = 6) revealed significant changes in R 2 ' between the presentation and 1 week scans for both ischaemic core (p < 0.01) and infarct growth (p < 0.05). In conclusion, this study presents evidence supporting the potential of sqBOLD for imaging oxygenation in stroke.

A streamlined acquisition for mapping baseline brain oxygenation using quantitative BOLD.

Quantitative BOLD (qBOLD) is a non-invasive MR technique capable of producing quantitative measurements of the haemodynamic and metabolic properties of the brain. Here we propose a refinement of the qBOLD methodology, dubbed streamlined-qBOLD, in order to provide a clinically feasible method for mapping baseline brain oxygenation. In streamlined-qBOLD confounding signal contributions are minimised during data acquisition through the application of (i) a Fluid Attenuated Inversion Recovery (FLAIR) preparation to remove cerebral spinal fluid (CSF) signal contamination, (ii) a Gradient Echo Slice Excitation Profile Imaging (GESEPI) acquisition to reduce the effect of macroscopic magnetic field gradients and (iii) an Asymmetric Spin Echo (ASE) pulse sequence to directly measure the reversible transverse relaxation rate, R2'. Together these features simplify the application of the qBOLD model, improving the robustness of the resultant parametric maps. A theoretical optimisation framework was used to optimise acquisition parameters in relation to signal to noise ratio. In a healthy subject group (n = 7) apparent elevations in R2' caused by partial volumes of CSF were shown to be reduced with the application of CSF nulling. Significant decreases in R2' (p < 0.001) and deoxygenated blood volume (p < 0.01) were seen in cortical grey matter, across the group, with the application of CSF suppression. Quantitative baseline brain oxygenation parameter maps were calculated using qBOLD modelling and compared with literature values.

Improving the specificity of R2' to the deoxyhaemoglobin content of brain tissue: Prospective correction of macroscopic magnetic field gradients.

The reversible transverse relaxation rate, R2', is sensitive to the deoxyhaemoglobin content of brain tissue, enabling information about the oxygen extraction fraction to be obtained. However, R2' is also sensitive to macroscopic magnetic field gradients, particularly at air-tissue interfaces where a large susceptibility difference is present. It is important that this latter effect is minimised in order to produce meaningful estimates of blood oxygenation. Therefore, the aim of this study was to implement a technique to prospectively correct for the effect of susceptibility induced magnetic field gradients on R2' weighted data. This was achieved by combining the Gradient-Echo Slice Excitation Profile Imaging (GESEPI) technique with an Asymmetric Spin Echo (ASE) pulse sequence. The main advantages of this approach are (i) shorter acquisition times, since a separately acquired magnetic field map is not required and (ii) simpler analysis, since retrospective correction for the effects of magnetic field gradients in postprocessing is not required. In these experiments we show that with this newly developed technique it is possible to correct the majority of grey matter voxels for the expected distribution of through-slice magnetic field gradients to produce maps of R2' in a short scan duration.

Measurement of oxygen extraction fraction (OEF): An optimized BOLD signal model for use with hypercapnic and hyperoxic calibration.

Several techniques have been proposed to estimate relative changes in cerebral metabolic rate of oxygen consumption (CMRO2) by exploiting combined BOLD fMRI and cerebral blood flow data in conjunction with hypercapnic or hyperoxic respiratory challenges. More recently, methods based on respiratory challenges that include both hypercapnia and hyperoxia have been developed to assess absolute CMRO2, an important parameter for understanding brain energetics. In this paper, we empirically optimize a previously presented "original calibration model" relating BOLD and blood flow signals specifically for the estimation of oxygen extraction fraction (OEF) and absolute CMRO2. To do so, we have created a set of synthetic BOLD signals using a detailed BOLD signal model to reproduce experiments incorporating hypercapnic and hyperoxic respiratory challenges at 3T. A wide range of physiological conditions was simulated by varying input parameter values (baseline cerebral blood volume (CBV0), baseline cerebral blood flow (CBF0), baseline oxygen extraction fraction (OEF0) and hematocrit (Hct)). From the optimization of the calibration model for estimation of OEF and practical considerations of hypercapnic and hyperoxic respiratory challenges, a new "simplified calibration model" is established which reduces the complexity of the original calibration model by substituting the standard parameters α and ß with a single parameter θ. The optimal value of θ is determined (θ=0.06) across a range of experimental respiratory challenges. The simplified calibration model gives estimates of OEF0 and absolute CMRO2 closer to the true values used to simulate the experimental data compared to those estimated using the original model incorporating literature values of α and ß. Finally, an error propagation analysis demonstrates the susceptibility of the original and simplified calibration models to measurement errors and potential violations in the underlying assumptions of isometabolism. We conclude that using the simplified calibration model results in a reduced bias in OEF0 estimates across a wide range of potential respiratory challenge experimental designs.

Sources of systematic error in calibrated BOLD based mapping of baseline oxygen extraction fraction.

Recently a new class of calibrated blood oxygen level dependent (BOLD) functional magnetic resonance imaging (MRI) methods were introduced to quantitatively measure the baseline oxygen extraction fraction (OEF). These methods rely on two respiratory challenges and a mathematical model of the resultant changes in the BOLD functional MRI signal to estimate the OEF. However, this mathematical model does not include all of the effects that contribute to the BOLD signal, it relies on several physiological assumptions and it may be affected by intersubject physiological variability. The aim of this study was to investigate these sources of systematic error and their effect on estimating the OEF. This was achieved through simulation using a detailed model of the BOLD signal. Large ranges for intersubject variability in baseline physiological parameters such as haematocrit and cerebral blood volume were considered. Despite this the uncertainty in the relationship between the measured BOLD signals and the OEF was relatively low. Investigations of the physiological assumptions that underlie the mathematical model revealed that OEF measurements are likely to be overestimated if oxygen metabolism changes during hypercapnia or cerebral blood flow changes under hyperoxia. Hypoxic hypoxia was predicted to result in an underestimation of the OEF, whilst anaemic hypoxia was found to have only a minimal effect.

Measurement of OEF and absolute CMRO2: MRI-based methods using interleaved and combined hypercapnia and hyperoxia.

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is most commonly used in a semi-quantitative manner to infer changes in brain activity. Despite the basis of the image contrast lying in the cerebral venous blood oxygenation level, quantification of absolute cerebral metabolic rate of oxygen consumption (CMRO2) has only recently been demonstrated. Here we examine two approaches to the calibration of fMRI signal to measure absolute CMRO2 using hypercapnic and hyperoxic respiratory challenges. The first approach is to apply hypercapnia and hyperoxia separately but interleaved in time and the second is a combined approach in which we apply hyperoxic challenges simultaneously with different levels of hypercapnia. Eleven healthy volunteers were studied at 3T using a dual gradient-echo spiral readout pulsed arterial spin labelling (ASL) imaging sequence. Respiratory challenges were conducted using an automated system of dynamic end-tidal forcing. A generalised BOLD signal model was applied, within a Bayesian estimation framework, that aims to explain the effects of modulation of CBF and arterial oxygen content to estimate venous deoxyhaemoglobin concentration ([dHb]0). Using CBF measurements combined with the estimated oxygen extraction fraction (OEF), absolute CMRO2 was calculated. The interleaved approach to hypercapnia and hyperoxia, as well as yielding estimates of CMRO2 and OEF demonstrated a significant increase in regional CBF, venous oxygen saturation (SvO2) (a decrease in OEF) and absolute CMRO2 in visual cortex in response to a continuous (20 min) visual task, demonstrating the potential for the method in measuring long term changes in CMRO2. The combined approach to oxygen and carbon dioxide modulation, as well as taking less time to acquire data, yielded whole brain grey matter estimates of CMRO2 and OEF of 184±45 µmol/100 g/min and 0.42±0.12 respectively, along with additional estimates of the vascular parameters α=0.33±0.06, the exponent relating relative increases in CBF to CBV, and ß=1.35±0.13, the exponent relating deoxyhaemoglobin concentration to the relaxation rate R2*. Maps of cerebrovascular and cerebral metabolic parameters were also calculated. We show that combined modulation of oxygen and carbon dioxide can offer an experimentally more efficient approach to estimating OEF and absolute CMRO2 along with the additional vascular parameters that form an important part of the commonly used calibrated fMRI signal model.

Effect of motion on the ADC quantification accuracy of whole-body DWIBS.

BACKGROUND AND METHODS: Diffusion-weighted whole-body imaging with background body signal subtraction was introduced as a qualitative approach to detecting metastases in the body. A liver-mimicking phantom with embedded tumours that could be moved to replicate respiratory motion was developed to assess its ability to accurately quantify ADC values. RESULTS: Mean tumour ADC values were unaltered by the motion; however, a significant (p < 0.05) increase in the spread of ADC values was measured, even for relatively large tumours. CONCLUSIONS: These findings may be of significance in cancer therapy monitoring where subtle changes in ADC histograms may reveal changes in tumour heterogeneity.