The effects of random directional distributed flow in nuclear magnetic resonance imaging

Velocity-compensated intravoxel incoherent motion of the human calf muscle

PURPOSE

To determine whether intravoxel incoherent motion (IVIM) describes the blood perfusion in muscles better, assuming pseudo diffusion (Bihan Model 1) or ballistic motion (Bihan Model 2).

METHODS

IVIM parameters were measured in 18 healthy subjects with three different diffusion gradient time profiles (bipolar with two diffusion times and one with velocity compensation) and 17 b-values (0-600 s/mm2) at rest and after muscle activation. The diffusion coefficient, perfusion fraction, and pseudo-diffusion coefficient were estimated with a segmented fit in the gastrocnemius medialis (GM) and tibialis anterior (TA) muscles.

RESULTS

Velocity-compensated gradients resulted in a decreased perfusion fraction (6.9% ± 1.4% vs. 4.4% ± 1.3% in the GM after activation) and pseudo-diffusion coefficient (0.069 ± 0.046 mm2/s vs. 0.014 ± 0.006 in the GM after activation) compared to the bipolar gradients with the longer diffusion encoding time. Increased diffusion coefficients, perfusion fractions, and pseudo-diffusion coefficients were observed in the GM after activation for all gradient profiles. However, the increase was significantly smaller for the velocity-compensated gradients. A diffusion time dependence was found for the pseudo-diffusion coefficient in the activated muscle.

CONCLUSION

Velocity-compensated diffusion gradients significantly suppress the IVIM effect in the calf muscle, indicating that the ballistic limit is mostly reached, which is supported by the time dependence of the pseudo-diffusion coefficient.

Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs

PURPOSE

The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M1) and acceleration-weighting (M2) levels and to evaluate their efficacy in correcting signal dropouts and preserving the black-blood state in liver diffusion-weighted imaging. Additionally, we seek to determine an optimal degree of compensation that minimizes signal dropouts while maintaining blood signal suppression.

METHODS

Numerically optimized gradient waveforms were adapted using a novel method that allows for the simultaneous tuning of M1- and M2-weighting by changing only one timing variable. Seven healthy volunteers underwent diffusion-weighted magnetic resonance imaging (DWI) with five diffusion encoding schemes (monopolar, velocity-compensated (M1 = 0), acceleration-compensated (M1 = M2 = 0), 84%-M1-M2-compensated, 67%-M1-M2-compensated) at b-values of 50 and 800 s/mm2 at a constant echo time of 70 ms. Signal dropout correction and apparent diffusion coefficients (ADCs) were quantified using regions of interest in the left and right liver lobe. The blood appearance was evaluated using two five-point Likert scales.

RESULTS

Signal dropout was more pronounced in the left lobe (19%-42% less signal than in the right lobe with monopolar scheme) and best corrected by acceleration-compensation (8%-10% less signal than in the right lobe). The black-blood state was best with monopolar encodings and decreased significantly (p < 0.001) with velocity- and/or acceleration-compensation. The partially M1-M2-compensated encoding schemes could restore the black-blood state again. Strongest ADC bias occurred for monopolar encodings (difference between left/right lobe of 0.41 μm2/ms for monopolar vs. < 0.12 μm2/ms for the other encodings).

CONCLUSION

All of the diffusion encodings used in this study demonstrated suitability for routine DWI application. The results indicate that a perfect value for the level of M1-M2-compensation does not exist. However, among the examined encodings, the 84%-M1-M2-compensated encodings provided a suitable tradeoff.

Gradient waveform design for tensor-valued encoding in diffusion MRI

Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of tensor-valued diffusion encoding is that it unlocks the 'shape of the b-tensor' as a new encoding dimension. By modulating the b-tensor shape, we can control the sensitivity to microscopic diffusion anisotropy which can be used as a contrast mechanism; a feature that is inaccessible by conventional diffusion encoding. Since imaging methods based on tensor-valued diffusion encoding are finding an increasing number of applications we are prompted to highlight the challenge of designing the optimal gradient waveforms for any given application. In this review, we first establish the basic design objectives in creating field gradient waveforms for tensor-valued diffusion MRI. We also survey additional design considerations related to limitations imposed by hardware and physiology, potential confounding effects that cannot be captured by the b-tensor, and artifacts related to the diffusion encoding waveform. Throughout, we discuss the expected compromises and tradeoffs with an aim to establish a more complete understanding of gradient waveform design and its impact on accurate measurements and interpretations of data.

Motion-compensated gradient waveforms for tensor-valued diffusion encoding by constrained numerical optimization

PURPOSE

Diffusion-weighted MRI is sensitive to incoherent tissue motion, which may confound the measured signal and subsequent analysis. We propose a "motion-compensated" gradient waveform design for tensor-valued diffusion encoding that negates the effects bulk motion and incoherent motion in the ballistic regime.

METHODS

Motion compensation was achieved by constraining the magnitude of gradient waveform moment vectors. The constraint was incorporated into a numerical optimization framework, along with existing constraints that account for b-tensor shape, hardware restrictions, and concomitant field gradients. We evaluated the efficacy of encoding and motion compensation in simulations, and we demonstrated the approach by linear and planar b-tensor encoding in a healthy heart in vivo.

RESULTS

The optimization framework produced asymmetric motion-compensated waveforms that yielded b-tensors of arbitrary shape with improved efficiency compared with previous designs for tensor-valued encoding, and equivalent efficiency to previous designs for linear (conventional) encoding. Technical feasibility was demonstrated in the heart in vivo, showing vastly improved data quality when using motion compensation. The optimization framework is available online in open source.

CONCLUSION

Our gradient waveform design is both more flexible and efficient than previous methods, facilitating tensor-valued diffusion encoding in tissues in which motion would otherwise confound the signal. The proposed design exploits asymmetric encoding times, a single refocusing pulse or multiple refocusing pulses, and integrates compensation for concomitant gradient effects throughout the imaging volume.

Optimal acquisition scheme for flow-compensated intravoxel incoherent motion diffusion-weighted imaging in the abdomen: An accurate and precise clinically feasible protocol

PURPOSE

Flow-compensated (FC) diffusion-weighted MRI (DWI) for intravoxel-incoherent motion (IVIM) modeling allows for a more detailed description of tissue microvasculature than conventional IVIM. The long acquisition time of current FC-IVIM protocols, however, has prohibited clinical application. Therefore, we developed an optimized abdominal FC-IVIM acquisition with a clinically feasible scan time.

METHODS

Precision and accuracy of the FC-IVIM parameters were assessed by fitting the FC-IVIM model to signal decay curves, simulated for different acquisition schemes. Diffusion-weighted acquisitions were added subsequently to the protocol, where we chose the combination of b-value, diffusion time and gradient profile (FC or bipolar) that resulted in the largest improvement to its accuracy and precision. The resulting two optimized FC-IVIM protocols with 25 and 50 acquisitions (FC-IVIMopt25 and FC-IVIMopt50 ), together with a complementary acquisition consisting of 50 diffusion-weighting (FC-IVIMcomp ), were acquired in repeated abdominal free-breathing FC-IVIM imaging of seven healthy volunteers. Intersession and intrasession within-subject coefficient of variation of the FC-IVIM parameters were compared for the liver, spleen, and kidneys.

RESULTS

Simulations showed that the performance of FC-IVIM improved in tissue with larger perfusion fraction and signal-to-noise ratio. The scan time of the FC-IVIMopt25 and FC-IVIMopt50 protocols were 8 and 16 min. The best in vivo performance was seen in FC-IVIMopt50 . The intersession within-subject coefficients of variation of FC-IVIMopt50 were 11.6%, 16.3%, 65.5%, and 36.0% for FC-IVIM model parameters diffusivity, perfusion fraction, characteristic time and blood flow velocity, respectively.

CONCLUSIONS

We have optimized the FC-IVIM protocol, allowing for clinically feasible scan times (8-16 min).

Multiple dimensions for random walks

Current trends in diffusion NMR and MRI methods development are reviewed. While great efforts are still directed towards further improving the spectral, spatial, and relaxation rate resolution of basic diffusion measurements, recent improvements in magnetic field gradient technology on whole-body scanners have enabled an exciting line of research involving MRI implementations of advanced diffusion NMR methods with motion-encoding gradient waveforms designed for multidimensional separation and correlation of properties like short-time diffusivity, restriction, anisotropy, flow, and exchange, thereby opening up for highly specific characterization of microstructure and heterogeneity in healthy and diseased tissues in a clinical setting.

Assessment of intravoxel incoherent motion MRI with an artificial capillary network: analysis of biexponential and phase-distribution models

Purpose

To systematically analyze intravoxel incoherent motion (IVIM) MRI in a perfusable capillary phantom closely matching the geometry of capillary beds in vivo and to compare the validity of the biexponential pseudo‐diffusion and the recently introduced phase‐distribution IVIM model.

Methods

IVIM‐MRI was performed at 12 different flow rates (0.2⋯2.4mL/min) in a capillary phantom using 4 different DW‐MRI sequences (2 with monopolar and 2 with flow‐compensated diffusion‐gradient schemes, with up to 16b values between 0 and 800s/mm2). Resulting parameters from the assessed IVIM models were compared to results from optical microscopy.

Results

The acquired data were best described by a static and a flowing compartment modeled by the phase‐distribution approach. The estimated signal fraction f of the flowing compartment stayed approximately constant over the applied flow rates, with an average of f=0.451±0.023 in excellent agreement with optical microscopy (f=0.454±0.002). The estimated average particle flow speeds v=0.25⋯2.7mm/s showed a highly significant linear correlation to the applied flow. The estimated capillary segment length of approximately 189um agreed well with optical microscopy measurements. Using the biexponential model, the signal fraction f was substantially underestimated and displayed a strong dependence on the applied flow rate.

Conclusion

The constructed phantom facilitated the detailed investigation of IVIM‐MRI methods. The results demonstrate that the phase‐distribution method is capable of accurately characterizing fluid flow inside a capillary network. Parameters estimated using the biexponential model, specifically the perfusion fraction f, showed a substantial bias because the model assumptions were not met by the underlying flow pattern.

Characterization of the diffusion coefficient of blood

PURPOSE

To characterize the diffusion coefficient of human blood for accurate results in intravoxel incoherent motion imaging.

METHODS

Diffusion-weighted MRI of blood samples from 10 healthy volunteers was acquired with a single-shot echo-planar-imaging sequence at body temperature. Effects of gradient profile (monopolar or flow-compensated), diffusion time (40-100 ms), and echo time (60-200 ms) were investigated.

RESULTS

Although measured apparent diffusion coefficients of blood were larger for flow-compensated than for monopolar gradients, no dependence of the apparent diffusion coefficient on the diffusion time was found. Large differences between individual samples were observed, with results ranging from 1.26 to 1.66 µm2 /ms for flow-compensated and 0.94 to 1.52 µm2 /ms for monopolar gradients. Statistical analysis indicates correlations of the flow-compensated apparent diffusion coefficient with hematocrit (P = 0.007) and hemoglobin (P = 0.017), but not with mean corpuscular volume (P = 0.64). Results of Monte-Carlo simulations support the experimental observations.

CONCLUSIONS

Measured blood apparent diffusion coefficient values depend on hematocrit/hemoglobin concentration and applied gradient profile due to non-Gaussian diffusion. Because in vivo measurement is delicate, an estimation based on blood count results could be an alternative. For intravoxel incoherent motion modeling, the use of a blood self-diffusion constant Db  = 1.54 ± 0.12 µm2 /ms for flow-compensated and Db  = 1.30 ± 0.18 µm2 /ms for monopolar encoding is suggested. Magn Reson Med 79:2752-2758, 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.

Simultaneous magnetic resonance diffusion and pseudo-diffusion tensor imaging

PURPOSE

An emerging topic in diffusion magnetic resonance is imaging blood microcirculation alongside water diffusion using the intravoxel incoherent motion (IVIM) model. Recently, a combined IVIM diffusion tensor imaging (IVIM-DTI) model was proposed, which accounts for both anisotropic pseudo-diffusion due to blood microcirculation and anisotropic diffusion due to tissue microstructures. In this article, we propose a robust IVIM-DTI approach for simultaneous diffusion and pseudo-diffusion tensor imaging.

METHODS

Conventional IVIM estimation methods can be broadly divided into two-step (diffusion and pseudo-diffusion estimated separately) and one-step (diffusion and pseudo-diffusion estimated simultaneously) methods. Here, both methods were applied on the IVIM-DTI model. An improved one-step method based on damped Gauss-Newton algorithm and a Gaussian prior for the model parameters was also introduced. The sensitivities of these methods to different parameter initializations were tested with realistic in silico simulations and experimental in vivo data.

RESULTS

The one-step damped Gauss-Newton method with a Gaussian prior was less sensitive to noise and the choice of initial parameters and delivered more accurate estimates of IVIM-DTI parameters compared to the other methods.

CONCLUSION

One-step estimation using damped Gauss-Newton and a Gaussian prior is a robust method for simultaneous diffusion and pseudo-diffusion tensor imaging using IVIM-DTI model. Magn Reson Med 79:2367-2378, 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.

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

The idea that in vivo intravoxel incoherent motion magnetic resonance signal is influenced by blood motion in the microvasculature is exciting, because it suggests that local and quantitative perfusion information can be obtained in a simple and elegant way from a few diffusion-weighted images, without contrast injection. When the method was proposed in the late 1980s some doubts appeared as to its feasibility, and, probably because the signal to noise and image quality at the time was not sufficient, no obvious experimental evidence could be produced to alleviate them. Helped by the tremendous improvements seen in the last three decades in MR hardware, pulse design, and post-processing capabilities, an increasing number of encouraging reports on the value of intravoxel incoherent motion perfusion imaging have emerged. The aim of this article is to review the current published evidence on the feasibility of in vivo perfusion imaging with intravoxel incoherent motion MRI.

Quantification of microcirculatory parameters by joint analysis of flow-compensated and non-flow-compensated intravoxel incoherent motion (IVIM) data

The aim of this study was to improve the accuracy and precision of perfusion fraction and blood velocity dispersion estimates in intravoxel incoherent motion (IVIM) imaging, using joint analysis of flow-compensated and non-flow-compensated motion-encoded MRI data. A double diffusion encoding sequence capable of switching between flow-compensated and non-flow-compensated encoding modes was implemented. In vivo brain data were collected in eight healthy volunteers and processed using the joint analysis. Simulations were used to compare the performance of the proposed analysis method with conventional IVIM analysis. With flow compensation, strong rephasing was observed for the in vivo data, approximately cancelling the IVIM effect. The joint analysis yielded physiologically reasonable perfusion fraction maps. Estimated perfusion fractions were 2.43 ± 0.81% in gray matter, 1.81 ± 0.90% in deep gray matter, and 1.64 ± 0.72% in white matter (mean ± SD, n = 8). Simulations showed improved accuracy and precision when using joint analysis of flow-compensated and non-flow-compensated data, compared with conventional IVIM analysis. Double diffusion encoding with flow compensation was feasible for in vivo imaging of the perfusion fraction in the brain. The strong rephasing implied that blood flowing through the cerebral microvascular system was closer to the ballistic limit than the diffusive limit.

Comparison of Intravoxel Incoherent Motion Parameters across MR Imagers and Field Strengths: Evaluation in Upper Abdominal Organs

Purpose To determine the reproducibility of intravoxel incoherent motion (IVIM) parameters measured in upper abdominal organs with magnetic resonance (MR) imagers from different vendors and with different field strengths. Materials and Methods This prospective study was approved by the independent ethics committees of Kanton Bern and Kanton Zurich, and signed informed consent was obtained from all participants. Abdominal diffusion-weighted images in 10 healthy men (mean age, 37 years ± 8 [standard deviation]) were acquired by using 1.5- and 3.0-T MR imagers from three different vendors. Two readers independently delineated regions of interest that were used to measure IVIM parameters (diffusion coefficient [Dt], perfusion fraction [Fp], and pseudodiffusion coefficient [Dp]) in the left and right lobes of the liver, and in the pancreas, spleen, renal cortex, and renal medulla. Measurement reproducibility between readers was assessed with intraclass correlation coefficients (ICCs). Variability across MR imagers was analyzed by using between- and within-subject coefficients of variation (CVs) and analysis of variance (ANOVA). Results Between-reader reproducibility was high for Dt (ICC, 94.6%), intermediate for Fp (ICC, 81.7%), and low for Dp (ICC, 69.5%). Between- and within-subject CVs of Dt were relatively high (>20%) in the left lobe of the liver and relatively low (<10%) in the renal cortex and renal medulla. CVs generally exceeded 15% for Fp values and 20% for Dp. ANOVA indicated significant differences (P < .05) between MR imagers. Conclusion IVIM parameters in the upper abdomen may differ substantially across MR imagers. (©) RSNA, 2015 Online supplemental material is available for this article.

Orientation dependence of microcirculation-induced diffusion signal in anisotropic tissues

PURPOSE

To seek a better understanding of the effect of organized capillary flow on the MR diffusion-weighted signal.

METHODS

A theoretical framework was proposed to describe the diffusion-weighted MR signal, which was then validated both numerically using a realistic model of capillary network and experimentally in an animal model of isolated perfused heart preparation with myocardial blood flow verified by means of direct arterial spin labeling measurements.

RESULTS

Microcirculation in organized tissues gave rise to an MR signal that could be described as a combination of the bi-exponential behavior of conventional intravoxel incoherent motion (IVIM) theory and diffusion tensor imaging (DTI) -like anisotropy of the vascular signal, with the flow-related pseudo diffusivity represented as the linear algebraic product between the encoding directional unit vector and an appropriate tensor entity. Very good agreement between theoretical predictions and both numerical and experimental observations were found.

CONCLUSION

These findings suggest that the DTI formalism of anisotropic spin motion can be incorporated into the classical IVIM theory to describe the MR signal arising from diffusion and microcirculation in organized tissues. Magn Reson Med 76:1252-1262, 2016. © 2015 Wiley Periodicals, Inc.

Impact of the calculation algorithm on biexponential fitting of diffusion-weighted MRI in upper abdominal organs

PURPOSE

To compare the variability, precision, and accuracy of six different algorithms (Levenberg-Marquardt, Trust-Region, Fixed-Dp , Segmented-Unconstrained, Segmented-Constrained, and Bayesian-Probability) for computing intravoxel-incoherent-motion-related parameters in upper abdominal organs.

METHODS

Following the acquisition of abdominal diffusion-weighted magnetic resonance images of 10 healthy men, six distinct algorithms were employed to compute intravoxel-incoherent-motion-related parameters in the left and right liver lobe, pancreas, spleen, renal cortex, and renal medulla. Algorithms were evaluated regarding inter-reader and intersubject variability. Comparability of results was assessed by analyses of variance. The algorithms' precision and accuracy were investigated on simulated data.

RESULTS

A Bayesian-Probability based approach was associated with very low inter-reader variability (average Intraclass Correlation Coefficients: 96.5-99.6%), the lowest inter-subject variability (Coefficients of Variation [CV] for the pure diffusion coefficient Dt : 3.8% in the renal medulla, 6.6% in the renal cortex, 10.4-12.1% in the left and right liver lobe, 15.3% in the spleen, 15.8% in the pancreas; for the perfusion fraction Fp : 15.5% on average; for the pseudodiffusion coefficient Dp : 25.8% on average), and the highest precision and accuracy. Results differed significantly (P < 0.05) across algorithms in all anatomical regions.

CONCLUSION

The Bayesian-Probability algorithm should be preferred when computing intravoxel-incoherent-motion-related parameters in upper abdominal organs.

Correlative assessment of tumor microcirculation using contrast-enhanced perfusion MRI and intravoxel incoherent motion diffusion-weighted MRI: is there a link between them?

The purpose of this study was to correlate intravoxel incoherent motion (IVIM) imaging with classical perfusion-weighted MRI metrics in human gliomas. Parametric images for slow diffusion coefficient (D), fast diffusion coefficient (D*), and fractional perfusion-related volume (f) in patients with high-grade gliomas were generated. Maps of Fp (plasma flow), vp (vascular plasma volume), PS (permeability surface-area product), ve (extravascular, extracellular volume), E (extraction ratio), ke (influx ratio into the interstitium), and tc (vascular transit time) from dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast-enhanced (DSC) MRI were also generated. A region-of-interest analysis on the contralateral healthy white matter and on the tumor areas was performed and the extracted parameter values were tested for any significant differences among tumor grades or any correlations. Only f could be significantly correlated to DSC-derived vp and tc in healthy brain tissue. Concerning the tumor regions, Fp was significantly positively correlated with D* and inversely correlated with f in DSC measurements. The D*, f, and f × D* values in the WHO grade III gliomas were non-significantly different from those in the grade IV gliomas. There was a trend to significant negative correlations between f and PS as well as between f × D* and ke in DCE experiments. Presumably due to different theoretical background, tracer properties and modeling of the tumor vasculature in the IVIM theory, there is no clearly evident link between D*, f and DSC- and DCE-derived metrics.

4D UTE flow: a phase-contrast MRI technique for assessment and visualization of stenotic flows

PURPOSE

Inaccuracy of conventional four-dimensional (4D) flow MR imaging in the presence of random unsteady and turbulent blood flow distal to a narrowing has been an important challenge. Previous investigations have revealed that shorter echo times (TE) decrease the errors, leading to more accurate flow assessments.

METHODS

In this study, as part of a 4D flow acquisition, an Ultra-Short TE (UTE) method was adopted. UTE works based on a center-out radial k-space trajectory that inherently has a short TE. By employing free induction decay sampling starting from read-out gradient ramp-up, and by combining the refocusing lobe of the slice select gradient with the bipolar flow encoding gradient, TEs of ≈1 msec may be achieved.

RESULTS

Both steady and pulsatile flow regimes, and in each case a range of Reynolds numbers, were studied in an in-vitro model. Flow assessment at low and medium flow rates demonstrated a good agreement between 4D UTE and conventional 4D flow techniques. However, 4D UTE flow significantly outperformed conventional 4D flow, at high flow rates for both steady and pulsatile flow regimes. Feasibility of the method in one patient with Aortic Stenosis was also demonstrated.

CONCLUSION

For both steady and pulsatile high flow rates, the measured flow distal to the stenotic narrowing using conventional 4D flow revealed more than 20% error compared to the ground-truth flow. This error was reduced to less than 5% using the 4D UTE flow technique.

Dependence of brain intravoxel incoherent motion perfusion parameters on the cardiac cycle

Measurement of microvascular perfusion with Intravoxel Incoherent Motion (IVIM) MRI is gaining interest. Yet, the physiological influences on the IVIM perfusion parameters ("pseudo-diffusion" coefficient D*, perfusion fraction f, and flow related parameter fD*) remain insufficiently characterized. In this article, we hypothesize that D* and fD*, which depend on blood speed, should vary during the cardiac cycle. We extended the IVIM model to include time dependence of D* = D*(t), and demonstrate in the healthy human brain that both parameters D* and fD* are significantly larger during systole than diastole, while the diffusion coefficient D and f do not vary significantly. The results non-invasively demonstrate the pulsatility of the brain's microvasculature.

A novel phase-corrected 3D cine ultra-short te (UTE) phase-contrast MRI technique

Phase-contrast (PC) MRI is a non-invasive technique to assess cardiovascular blood flow. However, this technique is not accurate for instance at the carotid bifurcation due to turbulent and disturbed blood flow in atherosclerotic disease. Flow quantification using conventional PC MRI distal to stenotic vessels suffers from intravoxel dephasing and flow artifacts. Previous studies have shown that short echo time (TE) potentially decreases the phase errors. In this work, a novel 3D cine UTE-PC imaging method is designed to measure the blood velocity in the carotid bifurcation using a UTE center-out radial trajectory and short TE time compared to standard PC MRI sequences. With a new phase error correction technique based on autocorrelation method, the proposed 3D cine UTE-PC has the potential to achieve high accuracy for quantification and visualization of velocity jet distal to a stenosis. Herein, we test the feasibility of the method in determining accurate flow waveforms in normal volunteers.

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(p)D(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.

CBF measurements using multidelay pseudocontinuous and velocity-selective arterial spin labeling in patients with long arterial transit delays: comparison with xenon CT CBF

PURPOSE

To test the theory that velocity-selective arterial spin labeling (VSASL) is insensitive to transit delay.

MATERIALS AND METHODS

Cerebral blood flow (CBF) was measured in ten Moyamoya disease patients using xenon computed tomography (xeCT) and magnetic resonance imaging (MRI), which included multiple pseudo-continuous ASL (pcASL) with different postlabel delays, VSASL, and dynamic susceptibility contrast (DSC) imaging. Correlation coefficient, root-mean-square difference, mean CBF error between ASL, and gold-standard xeCT CBF measurements as well the dependence of this error on transit delay (TD) as estimated by DSC time-to-peak of the residue function (Tmax) were determined.

RESULTS

For pcASL with different postlabel delay time (PLD), CBF measurement with short PLD (1.5-2 sec) had the strongest correlations with xeCT; VSASL had a lower but still significant correlation with a mean coefficient of 0.55. We noted the theoretically predicted dependence of CBF error on Tmax and on PLD for pcASL; VSASL CBF measurements had the least dependence of the error on TD. We also noted effects suggesting that the location of the label decay (blood vs. tissue) impacted the measurement, which was worse for pcASL than for VSASL.

CONCLUSION

We conclude that VSASL is less sensitive to TD than conventional ASL techniques and holds promise for CBF measurements in cerebrovascular diseases with slow flow.

COMPUTER-BASED IDENTIFICATION OF CATARACT AND CATARACT SURGERY EFFICACY USING OPTICAL IMAGES

The eyes are complex sensory organs, they are designed to capture images under varying light conditions. Eye disorders, such as cataract, among the elderly are a major health problem. Cataract is a painless clouding of the eye lens which develops over a long period of time. During this time, the eyesight gradually worsens. It can eventually lead to blindness and, is common in older people. In fact, about a third of people over 65 have cataracts in one or both eyes.

In this paper, we made use of two types of classifiers for identification of normal, cataract (early and developed stage), and post-cataract eyes using features extracted from optical images. These classifiers are artificial neural network and support vector machine. A database of 174 subjects, using the cross-validation strategy, is used to test the effectiveness of both classifiers. We demonstrate a sensitivity of more than 90% for both of these classifiers. Furthermore, they have a specificity of 100% and, as such, the results obtained are very promising. The proposed feature extraction and classification systems are ready clinically to run on a large amount of data sets.

Aortic valve stenotic area calculation from phase contrast cardiovascular magnetic resonance: the importance of short echo time

BACKGROUND

Cardiovascular magnetic resonance (CMR) can potentially quantify aortic valve area (AVA) in aortic stenosis (AS) using a single-slice phase contrast (PC) acquisition at valve level: AVA = aortic flow/aortic velocity-time integral (VTI). However, CMR has been shown to underestimate aortic flow in turbulent high velocity jets, due to intra-voxel dephasing. This study investigated the effect of decreasing intra-voxel dephasing by reducing the echo time (TE) on AVA estimates in patients with AS.

METHOD

15 patients with moderate or severe AS, were studied with three different TEs (2.8 ms/2.0 ms/1.5 ms), in the main pulmonary artery (MPA), left ventricular outflow tract (LVOT) and 0 cm/1 cm/2.5 cm above the aortic valve (AoV). PC estimates of stroke volume (SV) were compared with CMR left ventricular SV measurements and PC peak velocity, VTI and AVA were compared with Doppler echocardiography. CMR estimates of AVA obtained by direct planimetry from cine acquisitions were also compared with the echoAVA.

RESULTS

With a TE of 2.8 ms, the mean PC SV was similar to the ventricular SV at the MPA, LVOT and AoV0 cm (by Bland-Altman analysis bias +/- 1.96 SD, 1.3 +/- 20.2 mL/-6.8 +/- 21.9 mL/6.5 +/- 50.7 mL respectively), but was significantly lower at AoV1 and AoV2.5 (-29.3 +/- 31.2 mL/-21.1 +/- 35.7 mL). PC peak velocity and VTI underestimated Doppler echo estimates by approximately 10% with only moderate agreement. Shortening the TE from 2.8 to 1.5 msec improved the agreement between ventricular SV and PC SV at AoV0 cm (6.5 +/- 50.7 mL vs 1.5 +/- 37.9 mL respectively) but did not satisfactorily improve the PC SV estimate at AoV1 cm and AoV2.5 cm. Agreement of CMR AVA with echoAVA was improved at TE 1.5 ms (0.00 +/- 0.39 cm2) versus TE 2.8 (0.11 +/- 0.81 cm2). The CMR method which agreed best with echoAVA was direct planimetry (-0.03 cm2 +/- 0.24 cm2).

CONCLUSION

Agreement of CMR AVA at the aortic valve level with echo AVA improves with a reduced TE of 1.5 ms. However, flow measurements in the aorta (AoV 1 and 2.5) are underestimated and 95% limits of agreement remain large. Further improvements or novel, more robust techniques are needed in the CMR PC technique in the assessment of AS severity in patients with moderate to severe aortic stenosis.

On high b diffusion imaging in the human brain: ruminations and experimental insights

Interest in the manner in which brain tissue signal decays with b factor in diffusion imaging schemes has grown in recent years following the observation that the decay curves depart from purely monoexponential decay behavior. Regardless of the model or fitting function proposed for characterizing sufficiently sampled decay curves (vide infra), the departure from monoexponentiality spells increased tissue characterization potential. The degree to which this potential can be harnessed to improve specificity, sensitivity and spatial localization of diseases in brain, and other tissues, largely remains to be explored. Furthermore, the degree to which currently popular diffusion tensor imaging methods, including visually impressive white matter fiber "tractography" results, have almost completely ignored the nonmonoexponential nature of the basic signal decay with b factor is worthy of communal introspection. Here we limit our attention to a review of the basic experimental features associated with brain water signal diffusion decay curves as measured over extended b-factor ranges, the simple few parameter fitting functions that have been proposed to characterize these decays and the more involved models, e.g.,"ruminations," which have been proposed to account for the nonmonoexponentiality to date.

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 T(2)-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/mm(2)). 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.

Perfusion tensor imaging

Arterial spin labeling (ASL) provides a method by which to noninvasively measure the spatial and temporal characteristics of local tissue perfusion. Standard methods employ spatial tagging schemes, but recently methods based on velocity dependent tags, called Velocity Selective ASL (VSASL), have been introduced wherein the tagging depends upon the vascular velocity profile. In this article, we point out an interesting feature of VSASL: the velocity can be encoded in any direction, thereby allowing for the measurement of perfusion with a specified angular resolution. This then facilitates the reconstruction of the local perfusion field, characterized by a perfusion tensor P, from which can be derived quantities related to the structure of the local perfusion field, such as the mean perfusion, the perfusion anisotropy, and the principal directions of flow feeding each voxel. We demonstrate this new method, Perfusion Tensor Imaging (PTI), in both the brain and skeletal muscle of normal human volunteers and discuss possible applications.

Complimentary aspects of diffusion imaging and fMRI: II. Elucidating contributions to the fMRI signal with diffusion sensitization

Tissue water molecules reside in different biophysical compartments. For example, water molecules in the vasculature reside for variable periods of time within arteries, arterioles, capillaries, venuoles and veins, and may be within blood cells or blood plasma. Water molecules outside of the vasculature, in the extravascular space, reside, for a time, either within cells or within the interstitial space between cells. Within these different compartments, different types of microscopic motion that water molecules may experience have been identified and discussed. These range from Brownian diffusion to more coherent flow over the time scales relevant to functional magnetic resonance imaging (fMRI) experiments, on the order of several 10s of milliseconds. How these different types of motion are reflected in magnetic resonance imaging (MRI) methods developed for "diffusion" imaging studies has been an ongoing and active area of research. Here we briefly review the ideas that have developed regarding these motions within the context of modern "diffusion" imaging techniques and, in particular, how they have been accessed in attempts to further our understanding of the various contributions to the fMRI signal changes sought in studies of human brain activation.

Quantifying venous flow dynamics by flow-dephased and flow-rephased functional magnetic resonance imaging

By combining flow-dephased and flow-rephased diffusion weighting with blood oxygenation level dependent functional magnetic resonance imaging, it is possible to study flow dynamics in the venous network of the human brain. Thereby, ballistic flow, which conserves direction and velocity during echo time, is separated from diffusive flow with many changes in direction and velocity. By using this technique with very low diffusion/flow weighting, the mean velocity of ballistic flow was quantified in this study. The result of 10.9+/-3.2 cm/s strongly indicates that large venous vessels are the source of ballistic flow.

Quantifying the intra- and extravascular contributions to spin-echo fMRI at 3 T

Functional MRI (fMRI) by means of spin-echo (SE) techniques provides an interesting alternative to gradient-echo methods because the contrast is based primarily on dynamic averaging associated with the blood oxygenation level-dependent (BOLD) effect. In this article the contributions from different brain compartments to BOLD signal changes in SE echo planar imaging (EPI) are investigated. To gain a better understanding of the underlying mechanisms that cause the fMRI contrast, two experiments are presented: First, the intravascular contribution is decomposed into two fractions with different regimes of flow by means of diffusion-weighting gradient schemes which are either flow-compensated, or will maximally dephase moving spins. Second, contributions from the intra- and extravascular space are selectively suppressed by combining flow-weighting with additional refocusing pulses. The results indicate two qualitatively different components of flowing blood which contribute to the BOLD contrast and a nearly equal share in functional signal from the intra- and extravascular compartments at TE approximately 80 ms and 3 T. Combining these results, there is evidence that at least one-half of the functional signal originates from the parenchyma in SE fMRI at 3 T. The authors suggest the use of flow-compensated diffusion weighting for SE fMRI to improve the sensitivity to the parenchyma.

Effect of vascular crushing on FAIR perfusion kinetics, using a BIR-4 pulse in a magnetization prepared FLASH sequence

Flow-sensitive alternating inversion recovery (FAIR) perfusion imaging suffers from high vascular signal, resulting in artifacts and overestimation of perfusion. With TurboFLASH acquisition, crushing of vascular signal by bipolar gradients after each excitation is difficult due to the requirement of an ultrashort repetition time. Therefore, insertion of a preparation phase in the FAIR sequence, after labeling and prior to TurboFLASH acquisition, is proposed. A segmented adiabatic BIR-4 pulse, interleaved with crusher gradients, was used for flow crushing. The effect of the crusher preparation is shown as a function of crusher strength for a flow phantom and in rat brain. Influence of crusher strength on the time-dependent FAIR signal from rat brain was also measured. Signal from flowing spins in a flow phantom and from arterial spins in rat brain was significantly suppressed. Image quality was improved and the overestimation of perfusion at short inflow times was eliminated.

Evaluation of systematic quantification errors in velocity-selective arterial spin labeling of the brain

Velocity-selective (VS) sequences potentially permit arterial spin labeling (ASL) perfusion imaging with labeling applied very close to the tissue. In this study the effects of cerebrospinal fluid (CSF) motion, radiofrequency (RF) field imperfections, and sequence timing parameters on the appearance and quantitative perfusion values obtained with VS-ASL were evaluated. Large artifacts related to CSF motion were observed with moderate velocity weighting, which were removed by inversion recovery preparation at the cost of increased imaging time. Imperfect refocusing and excitation pulses resulting from nonuniform RF fields produced systematic errors in the ASL subtraction images. A phase cycling scheme was introduced to eliminate these errors. Quantitative perfusion images were obtained with CSF suppression and phase cycling. Gray matter blood flow of 27.7 ml 100 g(-1) min(-1), approximately half the value reported in studies using spatially-selective ASL, was measured. Potential sources for this underestimation are discussed.

Constrained modeling for spectroscopic measurement of bi-exponential spin-lattice relaxation of water in vivo

The (1)H NMR water signal from spectroscopic voxels localized in gray matter contains contributions from tissue and cerebral spinal fluid (CSF). A typically weak CSF signal at short echo times makes separating the tissue and CSF spin-lattice relaxation times (T(1)) difficult, often yielding poor precision in a bi-exponential relaxation model. Simulations show that reducing the variables in the T(1) model by using known signal intensity values significantly improves the precision of the T(1) measurement. The method was validated on studies on eight healthy subjects (four males and four females, mean age 21 +/- 2 years) through a total of twenty-four spectroscopic relaxation studies. Each study included both T(1) and spin-spin relaxation (T(2)) experiments. All volumes were localized along the Sylvian fissure using a stimulated echo localization technique with a mixing time of 10 ms. The T(2) experiment consisted of 16 stimulated echo acquisitions ranging from a minimum echo time (TE) of 20 ms to a maximum of 1000 ms, with a repetition time of 12 s. All T(1) experiments consisted of 16 stimulated echo acquisition, using a homospoil saturation recovery technique with a minimum recovery time of 50 ms and a maximum 12 s. The results of the T(2) measurements provided the signal intensity values used in the bi-exponential T(1) model. The mean T(1) values when the signal intensities were constrained by the T(2) results were 1055.4 ms +/- 7.4% for tissue and 5393.5 ms +/- 59% for CSF. When the signal intensities remained free variables in the model, the mean T(1) values were 1085 ms +/- 19.4% and 5038.8 ms +/- 113.0% for tissue and CSF, respectively. The resulting improvement in precision allows the water tissue T(1) value to be included in the spectroscopic characterization of brain tissue.

Relationship between apparent diffusion coefficient and signal intensity in endometrial and other pelvic cysts

We evaluated whether apparent diffusion coefficient (ADC) value is more useful than signal intensity for differentiating endometrial cysts from other pelvic cysts. In an in vitro study, signal intensity and diffusion coefficients were measured in whole blood phantoms in which blood oxidation was gradually increased and concentration subsequently diluted. Although both signal intensity and diffusion value were largely affected by blood concentration, diffusion value was almost independent of blood oxidation and red blood cell lysis-related diminution of magnetic nonhomogeneity, both factors greatly affecting signal intensity on T1- and T2-weighted images. In an in vivo study, differentiation between endometrial and other pelvic cysts was attempted by means of ADC values and signal ratios of cysts to muscles on T1- and T2-weighted images (T1- and T2-ratios). Endometrial cysts tended to show lower T2-ratios, higher T1-ratios, and lower ADC values than other pelvic cysts (p < 0.001). However, ADC values were not correlated with T1- and T2-ratios (p < /0.15/). The ability of ADC value to discriminate between these two groups (discriminant rate, 91.4%) was higher than that of T2-ratio (71.4%) or T1-ratio (88.6%). If combined, ADC and T1-ratio (or T2-ratio) showed higher discriminant rate (94.3%) than the combination of T1- and T2 ratios (88.6%). ADC value might be useful for evaluating the blood concentration of a cystic lesion, because diffusion value is more closely related to blood concentration and almost independent of blood oxidation and red blood cell lysis that largely affect signal intensity.

Effect of vasodilator hydralazine on tumor microvascular random flow and blood volume as measured by intravoxel incoherent motion (IVIM) weighted MRI in conjunction with Gd-DTPA-Albumin enhanced MRI

We studied the effect of hydralazine on tumor blood volume fraction and microvascular random flow velocity magnitude by IVIM weighted MRI in conjunction with dynamic Gd-DTPA-Albumin enhanced MRI. Blood volume fraction maps were obtained from the dynamic Gd-DTPA-Albumin enhanced MRI measurements. The average blood volume fraction of R3230 AC adenocarcinoma decreased from 0.125 +/- 0.022 (s.d.) ml/g to 0.105 +/- 0.018 (s.d.) ml/g (p < 0.001) after the administration of hydralazine at a dose of 5 mg/kg. The microvascular random flow velocity magnitude maps were obtained from the IVIM weighted MRI signals by utilizing the Gd-DTPA-Albumin measured blood volume fractions as an input in the compartmental modeling analysis of the IVIM weighted MRI signal. The random-directional microvascular flow induced MRI signal attenuation was separated from the molecular diffusion induced signal attenuation. Flow induced attenuation was more significant after the administration of hydralazine. The mean microvascular random flow velocity magnitude increased from 0.52 +/- 0.15 (s.d.) mm/sec to 0.73 +/- 0.23 (s.d.) mm/sec (p < 0.05) in the presence of the above blood volume fraction change.

In vivo MR measurements of regional arterial and venous blood volume fractions in intact rat brain

In vivo measurement of cerebral arterial and venous volume fractions is important to the understanding of brain physiology and function. By using an intravascular perfluorocarbon and 19F NMR at 4.7 T, regional arterial and venous volume fractions from an intact rat brain were resolved based on the pseudodiffusion coefficients, which were (33 +/- 7) x 10(-3) and (0.45 +/- 0.13) x 10(-3) mm(2)/sec (mean +/- SD, n = 7) for the fast- and slow-moving component, respectively. By exploiting the linear dependence of the perfluorocarbon 19F 1/T1 on the dissolved paramagnetic oxygen concentration, combined inversion-recovery and diffusion measurements were made to correlate the short T1 (high-oxygenation) component with the fast-moving component and the long T1 (low-oxygenation) component with the slow-moving component. The arterial blood volume fraction was 29 +/- 7% of the total cerebral blood volume. Finally, experiments were performed in which different oxygen concentrations were inhaled to validate this technique.

Continuous saturation EPI with diffusion weighting at 3.0 T

This paper presents a steady-state method of arterial spin labelling using continuous saturation in conjunction with echo-planar imaging (EPI), which has been implemented at 3 T. The continuous saturation technique has the advantage of having high sensitivity compared to transient labelling techniques, when long repetition times are used. It is also easy to implement and requires minimal data to be acquired for quantitation. Like other arterial spin labelling techniques, continuous saturation is potentially prone to overestimation of perfusion rates due to the effect of tagged blood in vessels within the image slice. Using a simple model of the vasculature, the degree of diffusion weighting required to suppress the arterial signal has been determined, with the results indicating that a value of 2 s/mm2 is adequate. Histogram analysis of the experimental data has been used to evaluate the effect of diffusion weighting. Using a b-value of 2 s/mm2, the mean perfusion-related signal change in grey matter on continuous saturation was found to be 1.5 +/- 0.2%, yielding a mean perfusion rate of 87 +/- 9 ml/100 g/min. Brain activation studies using the diffusion weighted continuous saturation technique gave a mean increase in perfusion of 36 +/- 12% in activated motor cortex.

Measurement of tumor vascular volume and mean microvascular random flow velocity magnitude by dynamic Gd-DTPA-albumin enhanced and diffusion-weighted MRI

Tumor vascular volume fraction and the magnitude of the mean microvascular random flow velocity were measured in an animal tumor model by combining dynamic Gd-DTPA-albumin enhanced MRI and diffusion-weighted MRI in conjunction with a compartmental modeling analysis. The vascular volume fraction maps were obtained from the dynamic Gd-DTPA-albumin enhanced MRI measurement. It was found that the vascular volume fraction for Walker 256 tumor was higher within the outgrowing rim and decreased towards the central region. The average value obtained from five animals was 0.062 +/- 0.009 ml/g. By using the vascular volume fraction from the Gd-DTPA-albumin enhanced MRI measurement, maps of the magnitude of the mean microvascular random flow velocity were obtained from the diffusion-weighted MRI measurements with the compartmental modeling analysis. The relative extravascular and intravascular contributions to the diffusion-weighted MRI signal were determined for three tissue groups with different Gd-DTPA-albumin enhancement characteristics, and the flow and molecular diffusion-induced attenuation factors for the intravascular compartment were also compared. The mean microvascular random flow velocity magnitude maps were obtained with an average value of 0.67 +/- 0.06 mm/s.

Can the IVIM model be used for renal perfusion imaging?

OBJECTIVE

Renal perfusion imaging may provide information about the hemodynamic significance of a renal artery stenosis and could improve noninvasive characterization when combined with angiography. It was proposed previously that diffusion sequences could provide useful perfusion indices based on the intravoxel incoherent motion (IVIM) model. Owing to motion artifacts, diffusion imaging has been restricted to relatively immobile organs like the brain. With the availability of single-shot echo-planar imaging (EPI) our purpose was to evaluate the IVIM model in renal perfusion.

METHODS AND MATERIAL

Eight volunteers underwent diffusion-sensitive magnetic resonance (MR) imaging of the kidneys using a spin echo (SE) EPI sequence. The diffusion coefficients determined by a linear regression analysis and fits to the IVIM function were calculated.

RESULTS AND CONCLUSION

Our preliminary experience does not support the possibility of obtaining perfusion information using the IVIM model in the kidneys.

Diffusion MRI: precision, accuracy and flow effects

After a decade of evolution and application of diffusion imaging, a large body of literature has been accumulated. It is in this context that the accuracy and precision of diffusion-weighted and quantitative diffusion MRI are reviewed. The emphasis of the review is on practical methods for clinical human imaging, particularly in the brain. The requirements for accuracy and precision are reviewed for various clinical and basic science applications. The methods of measuring and calculating diffusion effects with MRI are reviewed. The pulse gradient spin echo (PGSE) methods are emphasized as these methods are used most commonly in the clinical setting. Processing of PGSE data is reviewed. Various PGSE encoding schemes are also reviewed in terms of the accuracy and precision of isotropic and anisotropic diffusion measurements. The broad range of factors impacting the accuracy of the PGSE methods and other encoding schemes is then considered. Firstly, system inaccuracies such as background imaging gradients, gradient linearity, refocusing RF pulses, eddy currents, image misregistration, noise and dynamic range are considered. A second class of inaccuracies is contributed by the bulk effects of the imaged object, and include sample background gradients, subject motion of cerebrospinal fluid and organs, and aperiodic organ motion. A final category of potential inaccuracies is classified as being contributed by microscopic, biophysical tissue properties and include partial volume effects, anisotropy, restriction, diffusion distance, compartmentation, exchange, multiexponential diffusion decay, T2 weighting and microvascular perfusion. Finally, the application of diffusion methods to studies of blood flow in the microvasculature (i.e. the arterioles, capillaries and venules) are reviewed in detail, particularly in terms of feasibility and the stringent accuracy and precision requirements. Recent provocative studies examining the use of PGSE approaches to suppress microvascular signals in brain functional MRI (fMRI) are also reviewed.