Diffusion‐weighted imaging of the prostate and rectal wall: comparison of biexponential and monoexponential modelled diffusion and associated perfusion coefficients

This study compares parameters from monoexponential and biexponential modelling of diffusion‐weighted imaging of normal and malignant prostate tissue and normal rectal wall tissues. Fifty men with Stage Ic prostate cancer were studied using endorectal T₂‐weighted imaging and diffusion‐weighted imaging with 11 diffusion‐sensitive values (b‐values = 0, 1, 2, 4, 10, 20, 50, 100, 200, 400, 800 s/mm²). Regions of interest were drawn within non‐malignant central gland and peripheral zone, malignant prostate tissue and normal rectal wall tissue. Both a monoexponential and biexponential model was fitted over various b‐value ranges, giving an apparent diffusion coefficient (ADC) from the monoexponential model and a diffusion coefficient, perfusion coefficient and perfusion fraction from the biexponential model. In all tissues, over the full range of b‐values, the ADC from the monoexponential model was significantly higher than the corresponding diffusion coefficient from the biexponential model. As the minimum b‐value increased, the ADC decreased and was equal to the diffusion coefficient for some b‐value ranges. The biexponential model best described the data when low b‐values were included, suggesting that there is a fast perfusion component. Neither model could distinguish between benign prostate tissues on the basis of diffusion coefficients, but the rectal wall tissue and malignant prostate tissue had significantly lower diffusion coefficients than normal prostate tissues. Perfusion coefficients and fractions were highly variable within the population, so their clinical utility may be limited, but removal of this variable perfusion component from reported diffusion coefficients is important when attributing clinical differences to diffusion within tissues. Copyright © 2008 John Wiley & Sons, Ltd.     

Probing metabolite diffusion at ultra‐short time scales in the mouse brain using optimized oscillating gradients and “short”‐echo‐time diffusion‐weighted MRS

Measuring diffusion at ultra‐short time scales may yield information about short‐range intracellular structure and cytosol viscosity. However, reaching such time scales usually requires oscillating gradients, which in turn imply long echo times T_E. Here we propose a new kind of stretched oscillating gradient that allows us to increase diffusion‐weighting b while preserving spectral and temporal properties of the gradient modulation. We used these optimized gradients to measure metabolite diffusion in the mouse brain down to effective diffusion times of 1 ms while keeping T_E relatively short (60 ms). At such T_E, a significant macromolecule signal could still be observed and used as an internal reference of approximately null diffusivity, which proved critical to discard datasets corrupted by some motion artifact. The methods introduced here may be useful to improve the accuracy and precision of metabolite apparent diffusion coefficient measurements with oscillating gradients.     

Time‐dependent diffusion MRI as a probe of microstructural changes in a mouse model of Duchenne muscular dystrophy

Dystrophic muscles show a high variability of fibre sizes and altered sarcolemmal integrity, which are typically assessed by histology. Time‐dependent diffusion MRI is sensitive to tissue microstructure and its investigation through age‐related changes in dystrophic and healthy muscles may help the understanding of the onset and progression of Duchenne muscular dystrophy (DMD). We investigated the capability of time‐dependent diffusion MRI to quantify age and disease‐related changes in hind‐limb muscle microstructure between dystrophic (mdx) and wild‐type (WT) mice of three age groups (7.5, 22 and 44 weeks). Diffusion time‐dependent apparent diffusion coefficients (ADCs) of the gastrocnemius and tibialis anterior muscles were determined versus age and diffusion‐gradient orientation at six diffusion times (Δ; range: 25–350 ms). Mean muscle ADCs were compared between groups and ages, and correlated with T₂, using Student's t test, one‐way analysis of variance and Pearson correlation, respectively. Muscle fibre sizes and sarcolemmal integrity were evaluated by histology and compared with diffusion measurements. Hind‐limb muscle ADC showed characteristic restricted diffusion behaviour in both mdx and WT animals with decreasing ADC values at longer Δ. Significant differences in ADC were observed at long Δ values (≥ 250 ms; p < 0.05, comparison between groups; p < 0.01, comparison between ages) with ADC increased by 5–15% in dystrophic muscles, indicative of reduced diffusion restriction. No significant correlation was found between T₂ and ADC. Additionally, muscle fibre size distributions showed higher variability and lower mean fibre size in mdx than WT animals (p < 0.001). The extensive Evans Blue Dye uptake shown in dystrophic muscles revealed substantial sarcolemmal damage, suggesting diffusion measurements as more consistent with altered permeability rather than changes in muscle fibre sizes. This study shows the potential of diffusion MRI to non‐invasively discriminate between dystrophic and healthy muscles with enhanced sensitivity when using long Δ.     

Interstitial fluid pressure correlates with intravoxel incoherent motion imaging metrics in a mouse mammary carcinoma model

The effective delivery of a therapeutic drug to the core of a tumor is often impeded by physiological barriers, such as the interstitial fluid pressure (IFP). There are a number of therapies that can decrease IFP and induce tumor vascular normalization. However, a lack of a noninvasive means to measure IFP hinders the utilization of such a window of opportunity for the maximization of the treatment response. Thus, the purpose of this study was to investigate the feasibility of using intravoxel incoherent motion (IVIM) diffusion parameters as noninvasive imaging biomarkers for IFP. Mice bearing the 4T1 mammary carcinoma model were studied using diffusion‐weighted imaging (DWI), immediately followed by wick‐in‐needle IFP measurement. Voxelwise analysis was conducted with a conventional monoexponential diffusion model, as well as a biexponential model taking IVIM into account. There was no significant correlation of IFP with either the median apparent diffusion coefficient from the monoexponential model (r = 0.11, p = 0.78) or the median tissue diffusivity from the biexponential model (r = 0.30, p = 0.44). However, IFP was correlated with the median pseudo‐diffusivity (D_p) of apparent vascular voxels (r = 0.76, p = 0.02) and with the median product of the perfusion fraction and pseudo‐diffusivity (f_pD_p) of apparent vascular voxels (r = 0.77, p = 0.02). Although the effect of IVIM in tumors has been reported previously, to our knowledge, this study represents the first direct comparison of IVIM metrics with IFP, with the results supporting the feasibility of the use of IVIM DWI metrics as noninvasive biomarkers for tumor IFP. Copyright © 2011 John Wiley & Sons, Ltd.     

Biexponential T1ρ relaxation mapping of human knee cartilage in vivo at 3 T

The purpose of this study was to demonstrate the feasibility of biexponential T_1ρ relaxation mapping of human knee cartilage in vivo. A three‐dimensional, customized, turbo‐flash sequence was used to acquire T_1ρ‐weighted images from healthy volunteers employing a standard 3‐T MRI clinical scanner. A series of T_1ρ‐weighted images was fitted using monoexponential and biexponential models with two‐ and four‐parametric non‐linear approaches, respectively. Non‐parametric Kruskal–Wallis and Mann–Whitney U‐statistical tests were used to evaluate the regional relaxation and gender differences, respectively, with a level of significance of P = 0.05. Biexponential relaxations were detected in the cartilage of all volunteers. The short and long relaxation components of T_1ρ were estimated to be 6.9 and 51.0 ms, respectively. Similarly, the fractions of short and long T_1ρ were 37.6% and 62.4%, respectively. The monoexponential relaxation of T_1ρ was 32.6 ms. The experiments showed good repeatability with a coefficient of variation (CV) of less than 20%. A biexponential relaxation model showed a better fit than a monoexponential model to the T_1ρ relaxation decay in knee cartilage. Biexponential T_1ρ components could potentially be used to increase the specificity to detect early osteoarthritis by the measurement of different water compartments and their fractions.     

In vivo chlorine‐35, sodium‐23 and proton magnetic resonance imaging of the rat brain

In this study we demonstrate the feasibility of combined chlorine‐35, sodium‐23 and proton magnetic resonance imaging (MRI) at 9.4 Tesla, and present the first in vivo chlorine‐35 images obtained by means of MRI. With the experimental setup used in this study all measurements could be done in one session without changing the setup or moving the subject. The multinuclear measurement requires a total measurement time of 2 h and provides morphological (protons) and physiological (sodium‐23, chlorine‐35) information in one scanning session. Chlorine‐35, sodium‐23 and high resolution proton images were acquired from a phantom, a healthy rat and from a rat displaying a focal cerebral infarction. Compared to the healthy tissue a signal enhancement of a factor of 2.2 ± 0.2 in the chlorine‐35 and a factor of 2.9 ± 0.6 in the sodium‐23 images is observed in the areas of infarction. Exemplary unlocalized measurement of the in vivo longitudinal and transversal relaxation time of chlorine‐35 in a healthy rat showed multi‐exponential behaviour. A biexponential fit revealed a fast and a slow relaxing component with T_1,a = (1.7 ± 0.4) ms, T_1,b = (25.1 ± 1.4) ms, amplitudes of A = 0.26 ± 0.02, (1–A) = 0.74 ± 0.02 and T_2,a = (1.3 ± 0.1) ms, T_2,b = (11.8 ± 1.1) ms, A = 0.64 ± 0.02, (1–A) = 0.36 ± 0.02. Combined proton, sodium‐23 and chlorine‐35 MRI may provide a new approach for non‐invasive studies of ionic regulatory processes under physiological and pathological conditions in vivo. Copyright © 2010 John Wiley & Sons, Ltd.     

In vivo measurement of apparent diffusion coefficients of hyperpolarized 13C‐labeled metabolites

The combination of hyperpolarized MRS with diffusion weighting (dw) allows for determination of the apparent diffusion coefficient (ADC), which is indicative of the intra‐ or extracellular localization of the metabolite. Here, a slice‐selective pulsed‐gradient spin echo sequence was implemented to acquire a series of dw spectra from rat muscle in vivo to determine the ADCs of multiple metabolites after a single injection of hyperpolarized [1‐¹³C]pyruvate. An optimal control optimized universal‐rotation pulse was used for refocusing to minimize signal loss caused by B₁ imperfections. Non‐dw spectra were acquired interleaved with the dw spectra and these were used to correct for signal decay during the acquisition as a result of T₁ decay, pulse imperfections, flow etc. The data showed that the ADC values for [1‐¹³C]lactate (0.4–0.7 µm²/ms) and [1‐¹³C]alanine (0.4–0.9 µm²/ms) were about a factor of two lower than the ADC of [1‐¹³C]pyruvate (1.1–1.5 µm²/ms). This indicates a more restricted diffusion space for the former two metabolites consistent with lactate and alanine being intracellular. The higher ADC for pyruvate (similar to the proton ADC) reflected that the injected substance was not confined inside the muscle cells but also present extracellular. Copyright © 2014 John Wiley & Sons, Ltd.     

MRI quantification of non‐Gaussian water diffusion in normal human kidney: a diffusional kurtosis imaging study

Our aim was to prospectively evaluate the feasibility of diffusional kurtosis imaging (DKI) in normal human kidney and to report preliminary DKI measurements. Institutional review board approval and informed consent were obtained. Forty‐two healthy volunteers underwent diffusion‐weighted imaging (DWI) scans with a 3‐T MR scanner. b values of 0, 500 and 1000 s/mm² were adopted. Maps of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (D_⊥), axial diffusivity (D_||), mean kurtosis (MK), radial kurtosis (K_⊥) and axial kurtosis (K_||) were produced. Three representative axial slices in the upper pole, mid‐zone and lower pole were selected in the left and right kidney. On each selected slice, three regions of interest were drawn on the renal cortex and another three on the medulla. Statistical comparison was performed with t‐test and analysis of variance. Thirty‐seven volunteers successfully completed the scans. No statistically significant differences were observed between the left and right kidney for all metrics (p values in the cortex: FA, 0.114; MD, 0.531; D_⊥, 0.576; D_||, 0.691; MK, 0.934; K_⊥, 0.722; K_||, 0.891; p values in the medulla: FA, 0.348; MD, 0.732; D_⊥, 0.470; D_||, 0.289; MK, 0.959; K_⊥, 0.780; K_||, 0.287). Kurtosis metrics (MK, K_||, K_⊥) obtained in the renal medulla were significantly (p <0.001) higher than those in the cortex (0.552 ± 0.04, 0.637 ± 0.07 and 0.530 ± 0.08 in the medulla and 0.373 ± 0.04, 0.492 ± 0.06 and 0.295 ± 0.06 in the cortex, respectively). For the diffusivity measures, FA of the medulla (0.356 ± 0.03) was higher than that of the cortex (0.179 ± 0.03), whereas MD, D_⊥ and D_|| (mm²/ms) were lower in the medulla than in the cortex (3.88 ± 0.09, 3.50 ± 0.23 and 4.65 ± 0.29 in the cortex and 2.88 ± 0.11, 2.32 ± 0.20 and 3.47 ± 0.31 in the medulla, respectively). Our results indicate that DKI is feasible in the human kidney. We have reported the preliminary DKI measurements of normal human kidney that demonstrate well the non‐Gaussian behavior of water diffusion, especially in the renal medulla. Copyright © 2014 John Wiley & Sons, Ltd.     

Investigation of field and diffusion time dependence of the diffusion‐weighted signal at ultrahigh magnetic fields

Over the last decade, there has been a significant increase in the number of high‐magnetic‐field MRI magnets. However, the exact effect of a high magnetic field strength (B₀) on diffusion‐weighted MR signals is not yet fully understood. The goal of this study was to investigate the influence of different high magnetic field strengths (9.4 T and 14.1 T) and diffusion times (9, 11, 13, 15, 17 and 24 ms) on the diffusion‐weighted signal in rat brain white matter. At a short diffusion time (9 ms), fractional anisotropy values were found to be lower at 14.1 T than at 9.4 T, but this difference disappeared at longer diffusion times. A simple two‐pool model was used to explain these findings. The model describes the white matter as a first hindered compartment (often associated with the extra‐axonal space), characterized by a faster orthogonal diffusion and a lower fractional anisotropy, and a second restricted compartment (often associated with the intra‐axonal space), characterized by a slower orthogonal diffusion (i.e. orthogonal to the axon direction) and a higher fractional anisotropy. Apparent T₂ relaxation time measurements of the hindered and restricted pools were performed. The shortening of the pseudo‐T₂ value from the restricted compartment with B₀ is likely to be more pronounced than the apparent T₂ changes in the hindered compartment. This study suggests that the observed differences in diffusion tensor imaging parameters between the two magnetic field strengths at short diffusion time may be related to differences in the apparent T₂ values between the pools. Copyright © 2013 John Wiley & Sons, Ltd.     

Diffusion MRI detects early brain microstructure abnormalities in 2‐month‐old 3×Tg‐AD mice

The 3×Tg‐AD mouse is one of the most studied animal models of Alzheimer's disease (AD), and develops both amyloid beta deposits and neurofibrillary tangles in a temporal and spatial pattern that is similar to human AD pathology. Additionally, abnormal myelination patterns with changes in oligodendrocyte and myelin marker expression are reported to be an early pathological feature in this model. Only few diffusion MRI (dMRI) studies have investigated white matter abnormalities in 3×Tg‐AD mice, with inconsistent results. Thus, the goal of this study was to investigate the sensitivity of dMRI to capture brain microstructural alterations in 2‐month‐old 3×Tg‐AD mice. In the fimbria, the fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), and radial kurtosis (K_┴) were found to be significantly lower in 3×Tg‐AD mice than in controls, while the mean diffusivity (MD) and radial diffusivity (D_┴) were found to be elevated. In the fornix, K_┴ was lower for 3×Tg‐AD mice; in the dorsal hippocampus MD and D_┴ were elevated, as were FA, MD, and D_┴ in the ventral hippocampus. These results indicate, for the first time, dMRI changes associated with myelin abnormalities in young 3×Tg‐AD mice, before they develop AD pathology. Morphological quantification of myelin basic protein immunoreactivity in the fimbria was significantly lower in the 3×Tg‐AD mice compared with the age‐matched controls. Our results demonstrate that dMRI is able to detect widespread, significant early brain morphological abnormalities in 2‐month‐old 3×Tg‐AD mice.     

An intravoxel oriented flow model for diffusion‐weighted imaging of the kidney

By combining intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) we introduce a new diffusion model called intravoxel oriented flow (IVOF) that accounts for anisotropy of diffusion and the flow‐related signal. An IVOF model using a simplified apparent flow fraction tensor (IVOF_f) is applied to diffusion‐weighted imaging of human kidneys. The kidneys of 13 healthy volunteers were examined on a 3 T scanner. Diffusion‐weighted images were acquired with six b values between 0 and 800 s/mm² and 30 diffusion directions. Diffusivity and flow fraction were calculated for different diffusion models. The Akaike information criterion was used to compare the model fit of the proposed IVOF_f model to IVIM and DTI. In the majority of voxels the proposed IVOF_f model with a simplified apparent flow fraction tensor performs better than IVIM and DTI. Mean diffusivity is significantly higher in DTI compared with models that account for the flow‐related signal. The fractional anisotropy of diffusion is significantly reduced when flow fraction is considered to be anisotropic. Anisotropy of the apparent flow fraction tensor is significantly higher in the renal medulla than in the cortex region. The IVOF_f model describes diffusion‐weighted data in the human kidney more accurately than IVIM or DTI. The apparent flow fraction in the kidney proved to be anisotropic.     

Polymers Diffusivity Encoded by Stimuli‐Induced Phase Transition: Theory and Application to Poly(N‐Isopropylacrylamide) with Hydrophilic and Hydrophobic End Groups

The self‐diffusion of various nano‐objects investigated by high‐resolution nuclear magnetic resonance diffusometry proves to be an efficient method for the characterization of dynamics, aggregation kinetic, and matrix morphology. This study investigates how the two‐state model and Boltzmann function approach can be used for the evaluation of the thermodynamic parameters of temperature‐induced phase transition encoded in polymer diffusivity. The characteristics of the phase transition given by the transition temperature, change of entropy, and width of transition are obtained for poly(N‐isopropylacrylamide) (PNIPAm) linear polymers with hydrophilic and hydrophobic end‐group functionalization. The effect of end groups upon the polymer diffusivity is investigated as a function of molecular weight (M _n), from which fractal dimensions and hydrodynamic drag coefficients are obtained. The PNIPAm diffusivity is affected strongly by the end groups, and it is reflected in the hydrodynamic radius dependence upon molecular weight that obeys different power‐law relations. In this study, the synthesis of α‐ω‐heterotelechelic PNIPAm of different molecular weights with a thiol end group and a hydrophilic NIPAm‐like as well as a hydrophobic benzyl end group are described by reversible addition–fragmentation chain‐transfer polymerization.     

Reliable estimation of brain intravoxel incoherent motion parameters using denoised diffusion‐weighted MRI

In this study, we evaluate whether diffusion‐weighted magnetic resonance imaging (DW‐MRI) data after denoising can provide a reliable estimation of brain intravoxel incoherent motion (IVIM) perfusion parameters. Brain DW‐MRI was performed in five healthy volunteers on a 3 T clinical scanner with 12 different b‐values ranging from 0 to 1000 s/mm². DW‐MRI data denoised using the proposed method were fitted with a biexponential model to extract perfusion fraction (PF), diffusion coefficient (D) and pseudo‐diffusion coefficient (D*). To further evaluate the accuracy and precision of parameter estimation, IVIM parametric images obtained from one volunteer were used to resimulate the DW‐MRI data using the biexponential model with the same b‐values. Rician noise was added to generate DW‐MRI data with various signal‐to‐noise ratio (SNR) levels. The experimental results showed that the denoised DW‐MRI data yielded precise estimates for all IVIM parameters. We also found that IVIM parameters were significantly different between gray matter and white matter (P < 0.05), except for D* (P = 0.6). Our simulation results show that the proposed image denoising method displays good performance in estimating IVIM parameters (both bias and coefficient of variation were <12% for PF, D and D*) in the presence of different levels of simulated Rician noise (SNR_b=0 = 20‐40). Simulations and experiments show that brain DW‐MRI data after denoising can provide a reliable estimation of IVIM parameters.     

Evaluation of short‐TE 1H MRSI for quantification of metabolites in the prostate

Back‐to‐back ¹H MRSI scans, using an endorectal and phased‐array coil combination, were performed on 18 low‐risk patients with prostate cancer at 3 T, employing TEs of 32 and 100 ms in order to compare metabolite visualization at each TE. Outer‐volume suppression of lipid signals was performed using regional saturation (REST) slabs and the quantification of spectra at both TEs was achieved with the quantitation using quantum estimation (QUEST) routine. Metabolite nulling experiments in an additional five patients found that there were negligible macromolecule background signals in prostate spectra at TE = 32 ms. Metabolite visibility was judged using the criterion Cramér–Rao lower bound (CRLB)/amplitude < 20%, and metabolite concentrations were corrected for relaxation effects and referenced to the data acquired in corresponding water‐unsuppressed MRSI scans. For the first time, the prostate metabolites spermine and myo‐inositol were quantified individually in vivo, together with citrate, choline and creatine. All five metabolite visibilities were higher in TE = 32 ms MRSI than in TE = 100 ms MRSI. At TE = 32 ms, citrate was visible in 99.0% of lipid‐free spectra, whereas, at TE = 100 ms, no metabolite simulation of citrate matched the in vivo peaks. Spermine, choline and creatine were visualised separately in 30.4% more spectra at TE = 32 ms than at TE = 100 ms, and myo‐inositol in 72.5% more spectra. T₂ values were calculated for spermine (53 ± 16 ms), choline (62 ± 17 ms) and myo‐inositol (90 ± 48 ms). Data from the TE = 32 ms spectra showed that the concentrations of citrate and spermine secretions were positively correlated in both the peripheral zone and central gland (R² = 0.73 and R² = 0.43, respectively), and that the citrate content was significantly higher in the former at 64 ± 22 mm than in the latter at 32 ± 16 mm (p = 0.01). However, lipid contamination at TE = 32 ms was substantial; therefore, to make clinical use of the greater visualisation of prostate metabolites at TE = 32 ms rather than at TE = 100 ms, three‐dimensional MRSI at TE = 32 ms with effective lipid suppression must be implemented. ©2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.     

Phase‐Separation Dynamics of Aqueous Poly (N‐isopropylacrylamide) Solutions: Characteristic Behavior of the Molecular Weight and Concentration Dependences

The dynamics of thermoresponsive phase‐separation processes in aqueous poly(N‐isopropylacrylamide) (PNIPAM) was studied using a laser temperature‐jump technique combined with photometry. The time constant for phase separation (τ) was determined with high accuracy for various molecular weights (M _w) and concentrations (C) of PNIPAM in solution. For the C‐dependence, τ decreased with increasing concentration, and eventually converged to a constant value (≈ 50 ms) at high concentration. Such behavior can be interpreted in terms of inter‐polymer‐chain entanglement and diffusion prior to phase separation. On the other hand, there was an optimum value of M _w at which the phase separation was fastest. The origins of these experimental results are discussed within the framework of a diffusion‐controlled model.     

Diffusion tensor imaging and T2 relaxometry of bilateral lumbar nerve roots: feasibility of in‐plane imaging

Lower back pain is a common problem frequently encountered without specific biomarkers that correlate well with an individual patient's pain generators. MRI quantification of diffusion and T₂ relaxation properties may provide novel insight into the mechanical and inflammatory changes that occur in the lumbosacral nerve roots in patients with lower back pain. Accurate imaging of the spinal nerve roots is difficult because of their small caliber and oblique course in all three planes. Two‐dimensional in‐plane imaging of the lumbosacral nerve roots requires oblique coronal imaging with large field of view (FOV) in both dimensions, resulting in severe geometric distortions using single‐shot echo planar imaging (EPI) techniques. The present work describes initial success using a reduced‐FOV single‐shot spin‐echo EPI acquisition to obtain in‐plane diffusion tensor imaging (DTI) and T₂ mapping of the bilateral lumbar nerve roots at the L4 level of healthy subjects, minimizing partial volume effects, breathing artifacts and geometric distortions. A significant variation in DTI and T₂ mapping metrics is also reported along the course of the normal nerve root. The fractional anisotropy is statistically significantly lower in the dorsal root ganglia (0.287 ± 0.068) than in more distal regions in the spinal nerve (0.402 ± 0.040) (p < 10^–5). The T₂ relaxation value is statistically significantly higher in the dorsal root ganglia (78.0 ± 11.9 ms) than in more distal regions in the spinal nerve (59.5 ± 7.4 ms) (p < 10^–5). The quantification of nerve root DTI and T₂ properties using the proposed methodology may identify the specific site of any degenerative and inflammatory changes along the nerve roots of patients with lower back pain. Copyright © 2012 John Wiley & Sons, Ltd.     

A multi‐Gaussian model for apparent diffusion coefficient histogram analysis of Wilms’ tumour subtype and response to chemotherapy

Wilms’ tumours (WTs) are large heterogeneous tumours, which typically consist of a mixture of histological cell types, together with regions of chemotherapy‐induced regressive change and necrosis. The predominant cell type in a WT is assessed histologically following nephrectomy, and used to assess the tumour subtype and potential risk. The purpose of this study was to develop a mathematical model to identify subregions within WTs with distinct cellular environments in vivo, determined using apparent diffusion coefficient (ADC) values from diffusion‐weighted imaging (DWI). We recorded the WT subtype from the histopathology of 32 tumours resected in patients who received DWI prior to surgery after pre‐operative chemotherapy had been administered. In 23 of these tumours, DWI data were also available prior to chemotherapy. Histograms of ADC values were analysed using a multi‐Gaussian model fitting procedure, which identified ‘subpopulations’ with distinct cellular environments within the tumour volume. The mean and lower quartile ADC values of the predominant viable tissue subpopulation (ADC_1MEAN, ADC_1LQ), together with the same parameters from the entire tumour volume (ADC_0MEAN, ADC_0LQ), were tested as predictors of WT subtype. ADC_1LQ from the multi‐Gaussian model was the most effective parameter for the stratification of WT subtype, with significantly lower values observed in high‐risk blastemal‐type WTs compared with intermediate‐risk stromal, regressive and mixed‐type WTs (p < 0.05). No significant difference in ADC_1LQ was found between blastemal‐type and intermediate‐risk epithelial‐type WTs. The predominant viable tissue subpopulation in every stromal‐type WT underwent a positive shift in ADC_1MEAN after chemotherapy. Our results suggest that our multi‐Gaussian model is a useful tool for differentiating distinct cellular regions within WTs, which helps to identify the predominant histological cell type in the tumour in vivo. This shows potential for improving the risk‐based stratification of patients at an early stage, and for guiding biopsies to target the most malignant part of the tumour. Copyright © 2015 John Wiley & Sons, Ltd.     

Diffusion behavior of cerebral metabolites of congenital portal systemic shunt mice assessed noninvasively by diffusion‐weighted 1H magnetic resonance spectroscopy

Diffusion‐weighted ¹H‐MRS (DW‐MRS) allows for noninvasive investigation of the cellular compartmentalization of cerebral metabolites. DW‐MRS applied to the congenital portal systemic shunt (PSS) mouse brain may provide specific insight into alterations of cellular restrictions associated with PSS in humans. At 14.1 T, adult male PSS and their age‐matched healthy (Ctrl) mice were studied using DW‐MRS covering b‐values ranging from 0 to 45 ms/μm² to determine the diffusion behavior of abundant metabolites. The remarkable sensitivity and spectral resolution, in combination with very high diffusion weighting, allowed for precise measurement of the diffusion properties of endogenous N‐acetyl‐aspartate, total creatine, myo‐inositol, total choline with extension to glutamine and glutamate in mouse brains, in vivo. Most metabolites had comparable diffusion properties in PSS and Ctrl mice, suggesting that intracellular distribution space for these metabolites was not affected in the model. The slightly different diffusivity of the slow decaying component of taurine (0.015 ± 0.003 μm²/ms in PSS vs 0.021 ± 0.002 μm²/ms in Ctrl, P < 0.05) might support a cellular redistribution of taurine in the PSS mouse brain.     

Precision and accuracy of diffusion kurtosis estimation and the influence of b‐value selection

Diffusion kurtosis imaging (DKI) is an extension of diffusion tensor imaging that accounts for leading non‐Gaussian diffusion effects. In DKI studies, a wide range of different gradient strengths (b‐values) is used, which is known to affect the estimated diffusivity and kurtosis parameters. Hence there is a need to assess the accuracy and precision of the estimated parameters as a function of b‐value. This work examines the error in the estimation of mean of the kurtosis tensor (MKT) with respect to the ground truth, using simulations based on a biophysical model for both gray (GM) and white (WM) matter. Model parameters are derived from densely sampled experimental data acquired in ex vivo rat brain and in vivo human brain. Additionally, the variability of MKT is studied using the experimental data. Prevalent fitting protocols are implemented and investigated. The results show strong dependence on the maximum b‐value of both net relative error and standard deviation of error for all of the employed fitting protocols. The choice of b‐values with minimum MKT estimation error and standard deviation of error was found to depend on the protocol type and the tissue. Protocols that utilize two terms of the cumulant expansion (DKI) were found to achieve minimum error in GM at b‐values less than 1 ms/μm², whereas maximal b‐values of about 2.5 ms/μm² were found to be optimal in WM. Protocols including additional higher order terms of the cumulant expansion were found to provide higher accuracy for the more commonly used b‐value regime in GM, but were associated with higher error in WM. Averaged over multiple voxels, a net average error of around 15% for both WM and GM was observed for the optimal b‐value choice. These results suggest caution when using DKI generated metrics for microstructural modeling and when comparing results obtained using different fitting techniques and b‐values.