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.

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.

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 (v_e) and vascular permeability (K^trans).

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 v_e and K^trans (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: K^trans and v_e at baseline (HV vs. HF), change in K^trans and v_e following exercise, and following lung congestion resolution (ADHF). K^trans and v_e were fitted separately using ANOVA. Secondary endpoint: repeatability, that is, within‐participant variability in v_e and K^trans between sessions (coefficient of variation estimated via mixed effects model).

Results

There was no significant difference in mean K^trans 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. v_e 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 K^trans or v_e between scans for participants with ADHF (small population precluded significance testing). Scanning was well tolerated.

Data Conclusion

While no differences were detected in K^trans, v_e 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

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

Quantitative Magnetic Resonance Imaging in Perianal Crohn's Disease at 1.5 and 3.0 T: A Feasibility Study

Perianal Crohn's Disease (pCD) is a common manifestation of Crohn's Disease. Absence of reliable disease measures makes disease monitoring unreliable. Qualitative MRI has been increasingly used for diagnosing and monitoring pCD and has shown potential for assessing response to treatment. Quantitative MRI sequences, such as diffusion-weighted imaging (DWI), dynamic contrast enhancement (DCE) and magnetisation transfer (MT), along with T2 relaxometry, offer opportunities to improve diagnostic capability. Quantitative MRI sequences (DWI, DCE, MT and T2) were used in a cohort of 25 pCD patients before and 12 weeks after biological therapy at two different field strengths (1.5 and 3 T). Disease activity was measured with the Perianal Crohn's Disease Activity index (PDAI) and serum C-reactive protein (CRP). Diseased tissue areas on MRI were defined by a radiologist. A baseline model to predict outcome at 12 weeks was developed. No differences were seen in the quantitative MR measured in the diseased tissue regions from baseline to 12 weeks; however, PDAI and CRP decreased. Baseline PDAI, CRP, T2 relaxometry and surgical history were found to have a moderate ability to predict response after 12 weeks of biological treatment. Validation in larger cohorts with MRI and clinical measures are needed in order to further develop the model.

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.

Salt and Water Retention Is Associated with Microinflammation and Endothelial Injury in Chronic Kidney Disease

BACKGROUND

Progressive chronic kidney disease (CKD) inevitably leads to salt and water retention and disturbances in the macro-and microcirculation.

OBJECTIVES

We hypothesize that salt and water dysregulation in advanced CKD may be linked to inflammation and microvascular injury pathways.

METHODS

We studied 23 CKD stage 5 patients and 11 healthy controls (HC). Tissue sodium concentration was assessed using 23Sodium magnetic resonance (MR) imaging. Hydration status was evaluated using bioimpedance spectroscopy. A panel of inflammatory and endothelial biomarkers was also measured.

RESULTS

CKD patients had fluid overload (FO) when compared to HC (overhydration index: CKD = 0.5 ± 1.9 L vs. HC = -0.5 ± 1.0 L; p = 0.03). MR-derived tissue sodium concentrations were predominantly higher in the subcutaneous (SC) compartment (median [interquartile range] CKD = 22.4 mmol/L [19.4-31.3] vs. HC = 18.4 mmol/L [16.6-21.3]; p = 0.03), but not the muscle (CKD = 24.9 ± 5.5 mmol/L vs. HC = 22.8 ± 2.5 mmol/L; p = 0.26). Tissue sodium in both compartments correlated to FO (muscle: r = 0.63, p < 0.01; SC: rs = 0.63, p < 0.01). CKD subjects had elevated levels of vascular cell adhesion molecule (p < 0.05), tumor necrosis factor-alpha (p < 0.01), and interleukin (IL)-6 (p = 0.01) and lower levels of vascular endothelial growth factor-C (p = 0.04). FO in CKD was linked to higher IL-8 (r = 0.51, p < 0.05) and inversely associated to E-selectin (r = -0.52, p = 0.01). Higher SC sodium was linked to higher intracellular adhesion molecule (ICAM; rs = 0.54, p = 0.02).

CONCLUSION

Salt and water accumulation in CKD appears to be linked with inflammation and endothelial activation pathways. Specifically IL-8, E-Selectin (in FO), and ICAM (in salt accumulation) may be implicated in the pathophysiology of FO and merit further investigation.

Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail

Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.

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.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.

Delivering Functional Imaging on the MRI-Linac: Current Challenges and Potential Solutions

Magnetic resonance imaging (MRI) is a highly versatile imaging modality that can be used to measure features of the tumour microenvironment including cell death, proliferation, metabolism, angiogenesis, and hypoxia. Mapping and quantifying these pathophysiological features has the potential to alter the use of adaptive radiotherapy planning. Although these methods are available for use on diagnostic machines, several challenges exist for implementing these functional MRI methods on the MRI-linear accelerators (linacs). This review considers these challenges and potential solutions.

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.

Volumetric dynamic oxygen-enhanced MRI (OE-MRI): comparison with CT Brody score and lung function in cystic fibrosis patients

OBJECTIVES

To demonstrate, in patients with cystic fibrosis (CF), the correlation between three-dimensional dynamic oxygen-enhanced magnetic resonance imaging (OE-MRI) measurements and computed tomography Brody score (CF-CT) and lung function testing (LFT).

METHODS

Twenty-one patients (median age, 25 years; female, n = 8) with a range of CF lung disease and five healthy volunteers (median age, 31 years; female, n = 2) underwent OE-MRI performed on a 1.5-T MRI scanner. Coronal volumes were acquired while patients alternately breathed room air and 100% oxygen. Pre-oxygen T₁ was measured. Dynamic series of T₁-weighted volumes were then obtained while breathing oxygen. T₁-parameter maps were generated and the following OE-MRI parameters were measured: oxygen uptake (ΔPO_2max), wash-in time and wash-out time. High-resolution CT and LFT were performed. The relationship between CF-CT, LFT and OE-MRI parameters were evaluated using Pearson correlation for the whole lung and regionally.

RESULTS

Mean CF-CT was 24.1±17.1. Mean ΔPO_2max and mean wash-in as well as skewness of wash-out showed significant correlation with CF-CT (ΔPO_2max: r = -0.741, p < 0.001; mean wash-in: r = 0.501, p = 0.017; skewness of wash-out: r = 0.597, p = 0.001). There was significant correlation for the whole lung and regionally between LFT parameters and OE-MR (ΔPO_2max: r = 0.718, p < 0.001; wash-in: r = -0.576, p = 0.003; wash-out skewness: r = -0.552, p = 0.004).

CONCLUSIONS

Functional lung imaging using OE-MRI has the capability to assess the severity of CF lung disease and shows a significant correlation with LFT and CF-CT.

KEY POINTS

• Oxygen-enhanced MRI might play a future role in evaluation and follow-up of cystic fibrosis. • Heterogeneity of parameter maps reflects localised functional impairment in cystic fibrosis. • Avoidance of cumulative radiation burden in CF is feasible using OE-MRI.

Evaluation of dynamic contrast-enhanced MRI biomarkers for stratified cancer medicine: How do permeability and perfusion vary between human tumours?

BACKGROUND

Solid tumours exhibit enhanced vessel permeability and fenestrated endothelium to varying degree, but it is unknown how this varies in patients between and within tumour types. Dynamic contrast-enhanced (DCE) MRI provides a measure of perfusion and permeability, the transfer constant Ktrans, which could be employed for such comparisons in patients.

AIM

To test the hypothesis that different tumour types exhibit systematically different Ktrans.

MATERIALS AND METHODS

DCE-MRI data were retrieved from 342 solid tumours in 230 patients. These data were from 18 previous studies, each of which had had a different analysis protocol. All data were reanalysed using a standardised workflow using an extended Tofts model. A model of the posterior density of median Ktrans was built assuming a log-normal distribution and fitting a simple Bayesian hierarchical model.

RESULTS

12 histological tumour types were included. In glioma, median Ktrans was 0.016min-1 and for non-glioma tumours, median Ktrans ranged from 0.10 (cervical) to 0.21min-1 (prostate metastatic to bone). The geometric mean (95% CI) across all the non-glioma tumours was 0.15 (0.05, 0.45)min-1. There was insufficient separation between the posterior densities to be able to predict the Ktrans value of a tumour given the tumour type, except that the median Ktrans for gliomas was below 0.05min-1 with 80% probability, and median Ktrans measurements for the remaining tumour types were between 0.05 and 0.4min-1 with 80% probability.

CONCLUSION

With the exception of glioma, our hypothesis that different tumour types exhibit different Ktrans was not supported. Studies in which tumour permeability is believed to affect outcome should not simply seek tumour types thought to exhibit high permeability. Instead, Ktrans is an idiopathic parameter, and, where permeability is important, Ktrans should be measured in each tumour to personalise that treatment.

Mitotic Activity in Glioblastoma Correlates with Estimated Extravascular Extracellular Space Derived from Dynamic Contrast-Enhanced MR Imaging

BACKGROUND AND PURPOSE

A number of parameters derived from dynamic contrast-enhanced MR imaging and separate histologic features have been identified as potential prognosticators in high-grade glioma. This study evaluated the relationships between dynamic contrast-enhanced MRI-derived parameters and histologic features in glioblastoma multiforme.

MATERIALS AND METHODS

Twenty-eight patients with newly presenting glioblastoma multiforme underwent preoperative imaging (conventional imaging and T1 dynamic contrast-enhanced MRI). Parametric maps of the initial area under the contrast agent concentration curve, contrast transfer coefficient, estimate of volume of the extravascular extracellular space, and estimate of blood plasma volume were generated, and the enhancing fraction was calculated. Surgical specimens were used to assess subtype and were graded (World Health Organization classification system) and were assessed for necrosis, cell density, cellular atypia, mitotic activity, and overall vascularity scores. Quantitative assessment of endothelial surface area, vascular surface area, and a vascular profile count were made by using CD34 immunostaining. The relationships between MR imaging parameters and histopathologic features were examined.

RESULTS

High values of contrast transfer coefficient were associated with the presence of frank necrosis (P = .005). High values of the estimate of volume of the extravascular extracellular space were associated with a fibrillary histologic pattern (P < .01) and with increased mitotic activity (P < .05). No relationship was found between mitotic activity and histologic pattern, suggesting that the correlation between the estimate of volume of the extravascular extracellular space and mitotic activity was independent of the histologic pattern.

CONCLUSIONS

A correlation between the estimate of volume of the extravascular extracellular space and mitotic activity is reported. Further work is warranted to establish how dynamic contrast-enhanced MRI parameters relate to more quantitative histologic measurements, including markers of proliferation and measures of vascular endothelial growth factor expression.

T1 Relaxation Time in Lungs of Asymptomatic Smokers

Purpose

Interest in using T₁ as a potential MRI biomarker of chronic obstructive pulmonary disease (COPD) has recently increased. Since tobacco smoking is the major risk factor for development of COPD, the aim for this study was to examine whether tobacco smoking, pack-years (PY), influenced T₁ of the lung parenchyma in asymptomatic current smokers.

Materials and Methods

Lung T₁ measurements from 35 subjects, 23 never smokers and 12 current smokers were retrospectively analyzed from an institutional review board approved study. All 35 subjects underwent pulmonary function test (PFT) measurements and lung T_1, with similar T₁ measurement protocols. A backward linear model of T₁ as a function of FEV₁, FVC, weight, height, age and PY was tested.

Results

A significant correlation between lung T₁ and PY was found with a negative slope of -3.2 ms/year (95% confidence interval [CI] [-5.8, -0.6], p = 0.02), when adjusted for age and height. Lung T₁ shortens with ageing among all subjects, -4.0 ms/year (95%CI [-6.3, -1.7], p = 0.001), and among the never smokers, -3.7 ms/year (95%CI [-6.0, -1.3], p = 0.003).

Conclusions

A correlation between lung T₁ and PY when adjusted for both age and height was found, and T₁ of the lung shortens with ageing. Accordingly, PY and age can be significant confounding factors when T₁ is used as a biomarker in lung MRI studies that must be taken into account to detect underlying patterns of disease.

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.

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.

Respiratory tract exacerbations revisited: ventilation, inflammation, perfusion, and structure (VIPS) monitoring to redefine treatment

For cystic fibrosis (CF) patients older than 6 years there are convincing data that suggest respiratory tract exacerbations (RTE) play an important role in the progressive loss of functional lung tissue. There is a poor understanding of the pathobiology of RTE and whether specific treatment of RTE reduces lung damage in the long term. In addition, there are limited tools available to measure the various components of CF lung disease and responses to therapy. Therefore, in order to better understand the impact of RTE on CF lung disease we need to develop sensitive measures to characterize RTE and responses to treatment; and improve our understanding of structure-function changes during treatment of RTE. In this paper we review our current knowledge of the impact of RTE on the progression of lung disease and identify strategies to improve our understanding of the pathobiology of RTE. By improving our knowledge regarding RTE in CF we will be better positioned to develop approaches to treatment that are individualized and that can prevent permanent structural damage. We suggest the development of a ventilation, perfusion, inflammation and structure (VIPS)-MRI suite that supplies the clinician with data on ventilation, inflammation, perfusion, and structure in one MRI session. VIPS-MRI could be an important step to better understand the factors that contribute to and limit treatment efficacy of RTE.

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.

Ground Truth for Diffusion MRI in Cancer: A Model-Based Investigation of a Novel Tissue-Mimetic Material

This work presents preliminary results on the development, characterisation, and use of a novel physical phantom designed as a simple mimic of tumour cellular structure, for diffusion-weighted magnetic resonance imaging (DW-MRI) applications. The phantom consists of a collection of roughly spherical, micron-sized core-shell polymer 'cells', providing a system whose ground truth microstructural properties can be determined and compared with those obtained from modelling the DW-MRI signal. A two-compartment analytic model combining restricted diffusion inside a sphere with hindered extracellular diffusion was initially investigated through Monte Carlo diffusion simulations, allowing a comparison between analytic and simulated signals. The model was then fitted to DW-MRI data acquired from the phantom over a range of gradient strengths and diffusion times, yielding estimates of 'cell' size, intracellular volume fraction and the free diffusion coefficient. An initial assessment of the accuracy and precision of these estimates is provided, using independent scanning electron microscope measurements and bootstrap-style simulations. Such phantoms may be useful for testing microstructural models relevant to the characterisation of tumour tissue.

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.

Dynamic oxygen-enhanced magnetic resonance imaging of the lung in asthma -- initial experience

OBJECTIVES

To prospectively estimate the feasibility and reproducibility of dynamic oxygen-enhanced magnetic resonance imaging (OE-MRI) in the assessment of regional oxygen delivery, uptake and washout in asthmatic lungs.

MATERIALS AND METHODS

The study was approved by the National Research Ethics Committee and written informed consent was obtained. Dynamic OE-MRI was performed twice at one month apart on four mild asthmatic patients (23±5 years old, FEV1=96±3% of predicted value) and six severe asthmatic patients (41±12 years old, FEV1=60±14% of predicted value) on a 1.5T MR scanner using a two-dimensional T1-weighted inversion-recovery turbo spin echo sequence. The enhancing fraction (EF), the maximal change in the partial pressure of oxygen in lung tissue (ΔPO2max_l) and arterial blood of the aorta (ΔPO2max_a), and the oxygen wash-in (τup_l, τup_a) and wash-out (τdown_l, τdown_a) time constants were extracted and compared between groups using the independent-samples t-test (two-tailed). Correlations between imaging readouts and clinical measurements were assessed by Pearson's correlation analysis. Bland-Altman analysis was used to estimate the levels of agreement between the repeat scans and the intra-observer agreement in the MR imaging readouts.

RESULTS

The severe asthmatic group had significantly smaller EF (70±16%) and median ΔPO2max_l (156±52mmHg) and significantly larger interquartile range of τup_l (0.84±0.26min) than the mild asthmatic group (95±3%, P=0.014; 281±40mmHg, P=0.004; 0.20±0.07min, P=0.001, respectively). EF, median ΔPO2max_l and τdown_l and the interquartile range of τup_l and τdown_l were significantly correlated with age and pulmonary function test parameters (r=-0.734 to -0.927, 0.676-0.905; P=0.001-0.045). Median ΔPO2max_l was significantly correlated with ΔPO2max_a (r=0.745, P=0.013). Imaging readouts showed good one-month reproducibility and good intra-observer agreement (mean bias between repeated scans and between two observations did not significantly deviate from zero).

CONCLUSIONS

Dynamic OE-MRI is feasible in asthma and sensitive to the severity of disease. The technique provides indices related to regional oxygen delivery, uptake and washout that show good one month reproducibility and intra-observer agreement.

Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction.

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.

Multiparametric cardiovascular magnetic resonance assessment of cardiac allograft vasculopathy

OBJECTIVES

This study sought to evaluate the diagnostic performance of multiparametric cardiovascular magnetic resonance (CMR) for detecting cardiac allograft vasculopathy (CAV) using contemporary invasive epicardial artery and microvascular assessment techniques as reference standards, and to compare the performance of CMR with that of angiography.

BACKGROUND

CAV continues to limit the long-term survival of heart transplant recipients. Coronary angiography has a Class I recommendation for CAV surveillance and annual or biannual surveillance angiography is performed routinely in most centers.

METHODS

All transplant recipients referred for surveillance angiography at a single UK center over a 2-year period were prospectively screened for study eligibility. Patients prospectively underwent coronary angiography followed by coronary intravascular ultrasound, fractional flow reserve, and index of microcirculatory resistance. Within 1 month, patients underwent multiparametric CMR, including assessment of regional and global ventricular function, absolute myocardial blood flow quantification, and myocardial tissue characterization. In addition, 10 healthy volunteers underwent CMR.

RESULTS

Forty-eight patients were recruited, median 7.1 years (interquartile range: 4.6 to 10.3 years) since transplantation. The CMR myocardial perfusion reserve was the only independent predictor of both epicardial (β = -0.57, p < 0.001) and microvascular disease (β = -0.60, p < 0.001) on stepwise multivariable regression. The CMR myocardial perfusion reserve significantly outperformed angiography for detecting moderate CAV (area under the curve, 0.89 [95% confidence interval (CI): 0.79 to 1.00] vs. 0.59 [95% CI: 0.42 to 0.77], p = 0.01) and severe CAV (area under the curve, 0.88 [95% CI: 0.78 to 0.98] vs. 0.67 [95% CI: 0.52 to 0.82], p = 0.05).

CONCLUSIONS

CAV, including epicardial and microvascular components, can be detected more accurately using noninvasive CMR-based absolute myocardial blood flow assessment than with invasive coronary angiography, the current clinical surveillance technique.

Using in vivo probabilistic tractography to reveal two segregated dorsal 'language-cognitive' pathways in the human brain

Primate studies have recently identified the dorsal stream as constituting multiple dissociable pathways associated with a range of specialized cognitive functions. To elucidate the nature and number of dorsal pathways in the human brain, the current study utilized in vivo probabilistic tractography to map the structural connectivity associated with subdivisions of the left supramarginal gyrus (SMG). The left SMG is a prominent region within the dorsal stream, which has recently been parcellated into five structurally-distinct regions which possess a dorsal-ventral (and rostral-caudal) organisation, postulated to reflect areas of functional specialisation. The connectivity patterns reveal a dissociation of the arcuate fasciculus into at least two segregated pathways connecting frontal-parietal-temporal regions. Specifically, the connectivity of the inferior SMG, implicated as an acoustic-motor speech interface, is carried by an inner/ventro-dorsal arc of fibres, whilst the pathways of the posterior superior SMG, implicated in object use and cognitive control, forms a parallel outer/dorso-dorsal crescent.

Comprehensive validation of cardiovascular magnetic resonance techniques for the assessment of myocardial extracellular volume

BACKGROUND

Extracellular matrix expansion is a key element of ventricular remodeling and a potential therapeutic target. Cardiovascular magnetic resonance (CMR) T1-mapping techniques are increasingly used to evaluate myocardial extracellular volume (ECV); however, the most widely applied methods are without histological validation. Our aim was to perform comprehensive validation of (1) dynamic-equilibrium CMR (DynEq-CMR), where ECV is quantified using hematocrit-adjusted myocardial and blood T1 values measured before and after gadolinium bolus; and (2) isolated measurement of myocardial T1, used as an ECV surrogate.

METHODS AND RESULTS

Whole-heart histological validation was performed using 96 tissue samples, analyzed for picrosirius red collagen volume fraction, obtained from each of 16 segments of the explanted hearts of 6 patients undergoing heart transplantation who had prospectively undergone CMR before transplantation (median interval between CMR and transplantation, 29 days). DynEq-CMR-derived ECV was calculated from T1 measurements made using a modified Look-Locker inversion recovery sequence before and 10 and 15 minutes post contrast. In addition, ECV was measured 2 to 20 minutes post contrast in 30 healthy volunteers. There was a strong linear relationship between DynEq-CMR-derived ECV and histological collagen volume fraction (P<0.001; within-subject: r=0.745; P<0.001; r(2)=0.555 and between-subject: r=0.945; P<0.01; r(2)=0.893; for ECV calculated using 15-minute postcontrast T1). Correlation was maintained throughout the entire heart. Isolated postcontrast T1 measurement showed significant within-subject correlation with histological collagen volume fraction (r=-0.741; P<0.001; r(2)=0.550 for 15-minute postcontrast T1), but between-subject correlations were not significant. DynEq-CMR-derived ECV varied significantly according to contrast dose, myocardial region, and sex.

CONCLUSIONS

DynEq-CMR-derived ECV shows a good correlation with histological collagen volume fraction throughout the whole heart. Isolated postcontrast T1 measurement is insufficient for ECV assessment.

Anatomical brain connectivity can assess cognitive dysfunction in multiple sclerosis

BACKGROUND

Brain disconnection plays a major role in determining cognitive disabilities in multiple sclerosis (MS). We recently developed a novel diffusion-weighted magnetic resonance imaging (DW-MRI) tractography approach, namely anatomical connectivitity mapping (ACM), that quantifies structural brain connectivity.

OBJECTIVE

Use of ACM to assess structural connectivity modifications in MS brains and ascertain their relationship with the patients' Paced-Auditory-Serial-Addition-Test (PASAT) scores.

METHODS

Relapsing-remitting MS (RRMS) patients (n = 25) and controls (n = 25) underwent MRI at 3T, including conventional images, T1-weighted volumes and DW-MRI. Volumetric scans were coregistered to fractional anisotropy (FA) images, to obtain parenchymal FA maps for both white and grey matter. We initiated probabilistic tractography from all parenchymal voxels, obtaining ACM maps by counting the number of streamlines passing through each voxel, then normalizing by the total number of streamlines initiated. The ACM maps were transformed into standard space, for statistical use.

RESULTS

RRMS patients had reduced grey matter volume and FA, consistent with previous literature. Also, we showed reduced ACM in the thalamus and in the head of the caudate nucleus, bilaterally. In our RRMS patients, ACM was associated with PASAT scores in the corpus callosum, right hippocampus and cerebellum.

CONCLUSIONS

ACM opens a new perspective, clarifying the contribution of anatomical brain disconnection to clinical disabilities in MS.

Coaxially electrospun axon-mimicking fibers for diffusion magnetic resonance imaging

The study of brain structure and connectivity using diffusion magnetic resonance imaging (dMRI) has recently gained substantial interest. However, the use of dMRI still faces major challenges because of the lack of standard materials for validation. The present work reports on brain tissue-mimetic materials composed of hollow microfibers for application as a standard material in dMRI. These hollow fibers were fabricated via a simple and one-step coaxial electrospining (co-ES) process. Poly(ε-caprolactone) (PCL) and polyethylene oxide (PEO) were employed as shell and core materials, respectively, to achieve the most stable co-ES process. These co-ES hollow PCL fibers have different inner diameters, which mainly depend on the flow rate of the core solution and have the potential to cover the size range of the brain tissue we aimed to mimic. Co-ES aligned hollow PCL fibers were characterized using optical and electron microscopy and tested as brain white matter mimics on a high-field magnetic resonance imaging (MRI) scanner. To the best of our knowledge, this is the first time that co-ES hollow fibers have been successfully used as a tissue mimic or phantom in diffusion MRI. The results of the present study provide evidence that this phantom can mimic the dMRI behavior of cellular barriers imposed by axonal cell membranes and myelin; the measured diffusivity is compatible with that of in vivo biological tissues. Together these results suggest the potential use of co-ES hollow microfibers as tissue-mimicking phantoms in the field of medical imaging.

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.

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.

DCE-MRI model selection for investigating disruption of microvascular function in livers with metastatic disease

PURPOSE

To evaluate the Akaike information criterion (AIC) model selection technique as a method for detecting differences in microvascular characteristics between tumorous and non-tumor liver tissue.

MATERIALS AND METHODS

The AIC was applied to six patient datasets with liver metastases to determine, on a per voxel basis, which of two physiologically plausible candidate models gave a more appropriate description of the data. The dual-input single-compartment Materne model, extended to incorporate a novel portal input function estimation method, was chosen to represent liver tissue and the single-input dual-compartment extended Kety model was used for tumor.

RESULTS

Median AIC probabilities when comparing tumor versus liver and tumor versus tumor-margins were significantly different (P ≤ 0.01) in five of the six patient datasets. Comparisons between tumor margins and liver regions were significantly different in four datasets. Median AIC probabilities selected for the extended Kety model in all tumor regions, with the Materne model being progressively more probable through tumor margins into liver.

CONCLUSION

We present a viable method for assessing the spatially varying microvascular characteristics of tumor-bearing livers, with possible applications in lesion detection, assessment of tumor invasion, and measurement of drug efficacy.

DCE-MRI biomarkers of tumour heterogeneity predict CRC liver metastasis shrinkage following bevacizumab and FOLFOX-6

BACKGROUND

There is limited evidence that imaging biomarkers can predict subsequent response to therapy. Such prognostic and/or predictive biomarkers would facilitate development of personalised medicine. We hypothesised that pre-treatment measurement of the heterogeneity of tumour vascular enhancement could predict clinical outcome following combination anti-angiogenic and cytotoxic chemotherapy in colorectal cancer (CRC) liver metastases.

METHODS

Ten patients with 26 CRC liver metastases had two dynamic contrast-enhanced MRI (DCE-MRI) examinations before starting first-line bevacizumab and FOLFOX-6. Pre-treatment biomarkers of tumour microvasculature were computed and a regression analysis was performed against the post-treatment change in tumour volume after five cycles of therapy. The ability of the resulting linear model to predict tumour shrinkage was evaluated using leave-one-out validation. Robustness to inter-visit variation was investigated using data from a second baseline scan.

RESULTS

In all, 86% of the variance in post-treatment tumour shrinkage was explained by the median extravascular extracellular volume (v(e)), tumour enhancing fraction (E(F)), and microvascular uniformity (assessed with the fractal measure box dimension, d(0)) (R(2)=0.86, P<0.00005). Other variables, including baseline volume were not statistically significant. Median prediction error was 12%. Equivalent results were obtained from the second scan.

CONCLUSION

Traditional image analyses may over-simplify tumour biology. Measuring microvascular heterogeneity may yield important prognostic and/or predictive biomarkers.

Measurement of arterial plasma oxygenation in dynamic oxygen-enhanced MRI

Inhaled oxygen can be used as a contrast agent for magnetic resonance imaging, due to the T(1) shortening effect of the oxygen dissolved in blood and tissue water. In this study, blood T(1) was measured dynamically in 14 volunteers (seven smokers, seven never-smokers) as the inhaled gas was switched from medical air to 100% oxygen and back to medical air. These T(1) values were converted to changes in partial pressure of oxygen, which were found to be in agreement with literature values. There were differences in curve shape and curve height between the smoker and never-smoker groups, suggesting differences in lung function due to smoking-related damage. These curves could be used as an input function for modeling of oxygen uptake in tissues. The differences between groups highlight the importance of measuring such an input function for each individual rather than relying on an assumed measurement.

Comparison of dynamic contrast-enhanced MRI and dynamic contrast-enhanced CT biomarkers in bladder cancer

Dynamic contrast-enhanced MRI (DCE-MRI) is frequently used to provide response biomarkers in clinical trials of novel cancer therapeutics but assessment of their physiological accuracy is difficult. DCE-CT provides an independent probe of similar pharmacokinetic processes and may be modeled in the same way as DCE-MRI to provide purportedly equivalent physiological parameters. In this study, DCE-MRI and DCE-CT were directly compared in subjects with primary bladder cancer to assess the degree to which the model parameters report modeled physiology rather than artefacts of the measurement technique and to determine the interchangeability of the techniques in a clinical trial setting. The biomarker K(trans) obtained by fitting an extended version of the Kety model voxelwise to both DCE-MRI and DCE-CT data was in excellent agreement (mean across subjects was 0.085 ± 0.030 min(-1) for DCE-MRI and 0.087 ± 0.033 min(-1) for DCE-CT, intermodality coefficient of variation 9%). The parameter v(p) derived from DCE-CT was significantly greater than that derived from DCE-MRI (0.018 ± 0.006 compared to 0.009 ± 0.008, P = 0.0007) and v(e) was in reasonable agreement only for low values. The study provides evidence that the biomarker K(trans) is a robust parameter indicative of the underlying physiology and relatively independent of the method of measurement.

Tracer kinetic analysis of dynamic contrast-enhanced MRI and CT bladder cancer data: A preliminary comparison to assess the magnitude of water exchange effects

The purpose of this study was to determine the impact of water exchange on tracer kinetic parameter estimates derived from T(1)-weighted dynamic contrast-enhanced (DCE)-MRI data using a direct quantitative comparison with DCE-CT. Data were acquired from 12 patients with bladder cancer who underwent DCE-CT followed by DCE-MRI within a week. A two-compartment tracer kinetic model was fitted to the CT data, and two versions of the same model with modifications to account for the fast exchange and no exchange limits of water exchange were fitted to the MR data. The two-compartment tracer kinetic model provided estimates of the fractional plasma volume (v(p)), the extravascular extracellular space fraction (v(e)), plasma perfusion (F(p)), and the microvascular permeability surface area product. Our findings suggest that DCE-CT is an appropriate reference for DCE-MRI in bladder cancers as the only significant difference found between CT and MR parameter estimates were the no exchange limit estimates of v(p) (P = 0.002). These results suggest that although water exchange between the intracellular and extravascular-extracellular space has a negligible effect on DCE-MRI, vascular-extravascular-extracellular space water exchange may be more important.

Cross-visit tumor sub-segmentation and registration with outlier rejection for dynamic contrast-enhanced MRI time series data

Clinical trials of anti-angiogenic and vascular-disrupting agents often use biomarkers derived from DCE-MRI, typically reporting whole-tumor summary statistics and so overlooking spatial parameter variations caused by tissue heterogeneity. We present a data-driven segmentation method comprising tracer-kinetic model-driven registration for motion correction, conversion from MR signal intensity to contrast agent concentration for cross-visit normalization, iterative principal components analysis for imputation of missing data and dimensionality reduction, and statistical outlier detection using the minimum covariance determinant to obtain a robust Mahalanobis distance. After applying these techniques we cluster in the principal components space using k-means. We present results from a clinical trial of a VEGF inhibitor, using time-series data selected because of problems due to motion and outlier time series. We obtained spatially-contiguous clusters that map to regions with distinct microvascular characteristics. This methodology has the potential to uncover localized effects in trials using DCE-MRI-based biomarkers.

Anatomical connectivity mapping: a new tool to assess brain disconnection in Alzheimer's disease

Previous studies suggest that the clinical manifestations of Alzheimer's disease (AD) are not only associated with regional gray matter damage but also with abnormal functional integration of different brain regions by disconnection mechanisms. A measure of anatomical connectivity (anatomical connectivity mapping or ACM) can be obtained by initiating diffusion tractography streamlines from all parenchymal voxels and then counting the number of streamlines passing through each voxel of the brain. In order to assess the potential of this parameter for the study of disconnection in AD, we computed it in a group of patients with AD (N=9), in 16 patients with amnestic mild cognitive impairment (a-MCI, which is considered the prodromal stage of AD) and in 12 healthy volunteers. All subjects had an MRI scan at 3T, and diffusion MRI data were analyzed to obtain fractional anisotropy (FA) and ACM. Two types of ACM maps, absolute count (ac-ACM) and normalized by brain size count (nc-ACM), were obtained. No between group differences in FA surviving correction for multiple comparison were found, while areas of both decreased (in the supramarginal gyrus) and increased (in the putamen) ACM were found in patients with AD. Similar results were obtained with ac-ACM and nc-ACM. ACM of the supramarginal gyrus was strongly associated with measures of short-term memory in healthy subjects. This study shows that ACM provides information that is complementary to that offered by FA and appears to be more sensitive than FA to brain changes in patients with AD. The increased ACM in the putamen was unexpected. Given the nature of ACM, an increase of this parameter may reflect a change in any of the areas connected to it. One intriguing possibility is that this increase of ACM in AD patients might reflect processes of brain plasticity driven by cholinesterase inhibitors.

Brain hemispheric structural efficiency and interconnectivity rightward asymmetry in human and nonhuman primates

Evidence for interregional structural asymmetries has been previously reported for brain anatomic regions supporting well-described functional lateralization. Here, we aimed to investigate whether the two brain hemispheres demonstrate dissimilar general structural attributes implying different principles on information flow management. Common left hemisphere/right hemisphere structural network properties are estimated and compared for right-handed healthy human subjects and a nonhuman primate, by means of 3 different diffusion-weighted magnetic resonance imaging fiber tractography algorithms and a graph theory framework. In both the human and the nonhuman primate, the data support the conclusion that, in terms of the graph framework, the right hemisphere is significantly more efficient and interconnected than the left hemisphere, whereas the left hemisphere presents more central or indispensable regions for the whole-brain structural network than the right hemisphere. From our point of view, in terms of functional principles, this pattern could be related with the fact that the left hemisphere has a leading role for highly demanding specific process, such as language and motor actions, which may require dedicated specialized networks, whereas the right hemisphere has a leading role for more general process, such as integration tasks, which may require a more general level of interconnection.