Estimating axial diffusivity in the NODDI model.

To estimate microstructure-related parameters from diffusion MRI data, biophysical models make strong, simplifying assumptions about the underlying tissue. The extent to which many of these assumptions are valid remains an open research question. This study was inspired by the disparity between the estimated intra-axonal axial diffusivity from literature and that typically assumed by the Neurite Orientation Dispersion and Density Imaging (NODDI) model (d∥=1.7µm2/ms). We first demonstrate how changing the assumed axial diffusivity results in considerably different NODDI parameter estimates. Second, we illustrate the ability to estimate axial diffusivity as a free parameter of the model using high b-value data and an adapted NODDI framework. Using both simulated and in vivo data we investigate the impact of fitting to either real-valued or magnitude data, with Gaussian and Rician noise characteristics respectively, and what happens if we get the noise assumptions wrong in this high b-value and thus low SNR regime. Our results from real-valued human data estimate intra-axonal axial diffusivities of ∼2-2.5µm2/ms, in line with current literature. Crucially, our results demonstrate the importance of accounting for both a rectified noise floor and/or a signal offset to avoid biased parameter estimates when dealing with low SNR data.

Generalisation of continuous time random walk to anomalous diffusion MRI models with an age-related evaluation of human corpus callosum.

Diffusion MRI measures of the human brain provide key insight into microstructural variations across individuals and into the impact of central nervous system diseases and disorders. One approach to extract information from diffusion signals has been to use biologically relevant analytical models to link millimetre scale diffusion MRI measures with microscale influences. The other approach has been to represent diffusion as an anomalous transport process and infer microstructural information from the different anomalous diffusion equation parameters. In this study, we investigated how parameters of various anomalous diffusion models vary with age in the human brain white matter, particularly focusing on the corpus callosum. We first unified several established anomalous diffusion models (the super-diffusion, sub-diffusion, quasi-diffusion and fractional Bloch-Torrey models) under the continuous time random walk modelling framework. This unification allows a consistent parameter fitting strategy to be applied from which meaningful model parameter comparisons can be made. We then provided a novel way to derive the diffusional kurtosis imaging (DKI) model, which is shown to be a degree two approximation of the sub-diffusion model. This link between the DKI and sub-diffusion models led to a new robust technique for generating maps of kurtosis and diffusivity using the sub-diffusion parameters ßSUB and DSUB. Superior tissue contrast is achieved in kurtosis maps based on the sub-diffusion model. 7T diffusion weighted MRI data for 65 healthy participants in the age range 19-78 years was used in this study. Results revealed that anomalous diffusion model parameters α and ß have shown consistent positive correlation with age in the corpus callosum, indicating α and ß are sensitive to tissue microstructural changes in ageing.

Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact.

Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.

High fidelity fiber orientation density functions from fiber ball imaging.

The fiber orientation density function (fODF) in white matter is a primary physical quantity that can be estimated with diffusion MRI. It has often been employed for fiber tracking and microstructural modeling. Requirements for the construction of high fidelity fODFs, in the sense of having good angular resolution, adequate data to avoid sampling errors, and minimal noise artifacts, are described for fODFs calculated with fiber ball imaging. A criterion is formulated for the number of diffusion encoding directions needed to achieve a given angular resolution. The advantages of using large b-values (≥6000 s/mm2 ) are also discussed. For the direct comparison of different fODFs, a method is developed for defining a local frame of reference tied to each voxel's individual axonal structure. The Matusita anisotropy axonal is proposed as a scalar fODF measure for quantifying angular variability. Experimental results, obtained at 3 T from human volunteers, are used as illustrations.

Diagnostic benefit of high b-value computed diffusion-weighted imaging in acute brainstem infarction.

BACKGROUND AND PURPOSE: Diffusion-weighted imaging (DWI) is a cornerstone in diagnostic of ischemic stroke. The aim of this study was to investigate the usefulness of high-b-value computed DWI (c-DWI) in comparison to standard DWI in patients with acute brainstem infarction. MATERIALS AND METHODS: 56 patients with acute brainstem infarction were retrospectively analysed by two readers. DWI was obtained with the b-values 0, 500 and 1000 s/mm² on either a 1.5 or 3 T magnetic resonance imaging (MRI) scanner. c-DWI was calculated with a monoexponential model with high b-values 2000, 3000, 4000 and 5000 s/mm². All c-DWI series with high-b-values were compared to the standard DWI sequence at b-value of 1000 s/mm² in terms of image artifacts, lesion extent and contrast. RESULTS: There was no statistically significant difference between 1.5 and 3 T MRI regarding the measured ischemic lesion size. There were no statistically significant differences between the ischemic lesion sizes on DWI at b-values of 1000 s/mm² and on c-DWI at higher b-values. Overall, the contrast between the lesion and the surrounding normal areas improved with increasing b-value on the isotropic DWIs: maximum at b = 5000, followed by that at b 2000 and b 1000 s/mm², in order. The best relation between artifacts and lesion contrast was identified for b 2000 s/mm². CONCLUSION: High b-value DWI derived from c-DWI has a higher visibility for ischemic brainstem lesions compared to standard DWI without additional time cost. The b-2000 image is recommended to use in clinical routine, higher b-value images lead to more imaging artifacts, which might result in misdiagnosis.

Scan-rescan repeatability of axonal imaging metrics using high-gradient diffusion MRI and statistical implications for study design.

Axon diameter mapping using diffusion MRI in the living human brain has attracted growing interests with the increasing availability of high gradient strength MRI systems. A systematic assessment of the consistency of axon diameter estimates within and between individuals is needed to gain a comprehensive understanding of how such methods extend to quantifying differences in axon diameter index between groups and facilitate the design of neurobiological studies using such measures. We examined the scan-rescan repeatability of axon diameter index estimation based on the spherical mean technique (SMT) approach using diffusion MRI data acquired with gradient strengths up to 300 mT/m on a 3T Connectom system in 7 healthy volunteers. We performed statistical power analyses using data acquired with the same protocol in a larger cohort consisting of 15 healthy adults to investigate the implications for study design. Results revealed a high degree of repeatability in voxel-wise restricted volume fraction estimates and tract-wise estimates of axon diameter index derived from high-gradient diffusion MRI data. On the region of interest (ROI) level, across white matter tracts in the whole brain, the Pearson's correlation coefficient of the axon diameter index estimated between scan and rescan experiments was r = 0.72 with an absolute deviation of 0.18 µm. For an anticipated 10% effect size in studies of axon diameter index, most white matter regions required a sample size of less than 15 people to observe a measurable difference between groups using an ROI-based approach. To facilitate the use of high-gradient strength diffusion MRI data for neuroscientific studies of axonal microstructure, the comprehensive multi-gradient strength, multi-diffusion time data used in this work will be made publicly available, in support of open science and increasing the accessibility of such data to the greater scientific community.

Quartile histogram assessment of glioma malignancy using high b-value diffusion MRI with a continuous-time random-walk model.

The purpose of this study is to investigate the feasibility of using a continuous-time random-walk (CTRW) diffusion model, together with a quartile histogram analysis, for assessing glioma malignancy by probing tissue heterogeneity as well as cellularity. In this prospective study, 91 patients (40 females, 51 males) with histopathologically proven gliomas underwent MRI at 3 T. The cohort included 42 grade II (GrII), 19 grade III (GrIII) and 29 grade IV (GrIV) gliomas. Echo-planar diffusion-weighted imaging was conducted using 17 b-values (0-4000 s/mm2 ). Three CTRW model parameters, including an anomalous diffusion coefficient Dm , and two parameters related to temporal and spatial diffusion heterogeneity α and ß, respectively, were obtained. The mean parameter values within the tumor regions of interest (ROIs) were computed by utilizing the first quartile of the histograms as well as the full ROI for comparison. A Bonferroni-Holm-corrected Mann-Whitney U-test was used for the group comparisons. Individual and combinations of the CTRW parameters were evaluated for the characterization of gliomas with a receiver operating characteristic analysis. All first-quartile mean CTRW parameters yielded significant differences (p-values < 0.05) between pair-wise comparisons of GrII (Dm : 1.14 ± 0.37 µm2 /ms; α: 0.904 ± 0.03, ß: 0.913 ± 0.06), GrIII (Dm : 0.88 ± 0.21 µm2 /ms; α: 0.888 ± 0.01, ß: 0.857 ± 0.06) and GrIV gliomas (Dm : 0.73 ± 0.22 µm2 /ms; α: 0.878 ± 0.01; ß: 0.791 ± 0.07). The highest sensitivity, specificity, accuracy and area-under-the-curve of using the combinations of the first-quartile parameters were 84.2%, 78.5%, 75.4% and 0.76 for GrII and GrIII classification; 86.2%, 89.4%, 75% and 0.76 for GrIII and GrIV classification; and 86.2%, 85.7%, 84.5% and 0.90 for GrII and GrIV classification, respectively. Quartile-based analysis produced higher accuracy and area-under-the-curve than the full ROI-based analysis in all classifications. The CTRW diffusion model, together with a quartile-based histogram analysis, offers a new way for probing tumor structural heterogeneity at a subvoxel level, and has potential for in vivo assessment of glioma malignancy to complement histopathology.

Axon diameter index estimation independent of fiber orientation distribution using high-gradient diffusion MRI.

Axon diameter mapping using high-gradient diffusion MRI has generated great interest as a noninvasive tool for studying trends in axonal size in the human brain. One of the main barriers to mapping axon diameter across the whole brain is accounting for complex white matter fiber configurations (e.g., crossings and fanning), which are prevalent throughout the brain. Here, we present a framework for generalizing axon diameter index estimation to the whole brain independent of the underlying fiber orientation distribution using the spherical mean technique (SMT). This approach is shown to significantly benefit from the use of real-valued diffusion data with Gaussian noise, which reduces the systematic bias in the estimated parameters resulting from the elevation of the noise floor when using magnitude data with Rician noise. We demonstrate the feasibility of obtaining whole-brain orientationally invariant estimates of axon diameter index and relative volume fractions in six healthy human volunteers using real-valued diffusion data acquired on a dedicated high-gradient 3-Tesla human MRI scanner with 300 mT/m maximum gradient strength. The trends in axon diameter index are consistent with known variations in axon diameter from histology and demonstrate the potential of this generalized framework for revealing coherent patterns in axonal structure throughout the living human brain. The use of real-valued diffusion data provides a viable solution for eliminating the Rician noise floor and should be considered for all spherical mean approaches to microstructural parameter estimation.

Quasi-diffusion magnetic resonance imaging (QDI): A fast, high b-value diffusion imaging technique.

To enable application of non-Gaussian diffusion magnetic resonance imaging (dMRI) techniques in large-scale clinical trials and facilitate translation to clinical practice there is a requirement for fast, high contrast, techniques that are sensitive to changes in tissue structure which provide diagnostic signatures at the early stages of disease. Here we describe a new way to compress the acquisition of multi-shell b-value diffusion data, Quasi-Diffusion MRI (QDI), which provides a probe of subvoxel tissue complexity using short acquisition times (1-4 â€‹min). We also describe a coherent framework for multi-directional diffusion gradient acquisition and data processing that allows computation of rotationally invariant quasi-diffusion tensor imaging (QDTI) maps. QDI is a quantitative technique that is based on a special case of the Continuous Time Random Walk model of diffusion dynamics and assumes the presence of non-Gaussian diffusion properties within tissue microstructure. QDI parameterises the diffusion signal attenuation according to the rate of decay (i.e. diffusion coefficient, D in mm2 s-1) and the shape of the power law tail (i.e. the fractional exponent, α). QDI provides analogous tissue contrast to Diffusional Kurtosis Imaging (DKI) by calculation of normalised entropy of the parameterised diffusion signal decay curve, Hn, but does so without the limitations of a maximum b-value. We show that QDI generates images with superior tissue contrast to conventional diffusion imaging within clinically acceptable acquisition times of between 84 and 228 â€‹s. We show that QDI provides clinically meaningful images in cerebral small vessel disease and brain tumour case studies. Our initial findings suggest that QDI may be added to routine conventional dMRI acquisitions allowing simple application in clinical trials and translation to the clinical arena.

Reduction of vibration-induced signal loss by matching mechanical vibrational states: Application in high b-value diffusion-weighted MRS.

PURPOSE: Diffusion encoding gradients are known to yield vibrations of the typical clinical MR scanner hardware with a frequency of 20 to 30 Hz, which may lead to signal loss in diffusion-weighted MR measurements. This work proposes to mitigate vibration-induced signal loss by introducing a vibration-matching gradient (VMG) to match vibrational states during the 2 diffusion gradient pulses. THEORY AND METHODS: A theoretical description of displacements induced by gradient switching was introduced and modeled by a 2-mass-spring-damper system. An additional preceding VMG mimicking timing and properties of the diffusion encoding gradients was added to a high b-value diffusion-weighted MR spectroscopy sequence. Laser interferometry was employed to measure 3D displacements of a phantom surface. Lipid ADC was assessed in water-fat phantoms and in vivo in the tibial bone marrow of 3 volunteers. RESULTS: The modeling and the laser interferometer measurements revealed that the displacement curves are more similar during the 2 diffusion gradients with the VMG compared to the standard sequence, resulting in less signal loss of the diffusion-weighted signal. Phantom results showed lipid ADC overestimation up to 119% with the standard sequence and an error of 5.5% with the VMG. An 18% to 35% lower coefficient of variation was obtained for in vivo lipid ADC measurement when employing the VMG. CONCLUSION: The application of the VMG reduces the signal loss introduced by hardware vibrations in a high b-value diffusion-weighted MRS sequence in phantoms and in vivo. Reference measurements based on laser interferometry and mechanical modelling confirmed the findings.

Direction-averaged diffusion-weighted MRI signal using different axisymmetric B-tensor encoding schemes.

PURPOSE: It has been shown, theoretically and in vivo, that using the Stejskal-Tanner pulsed-gradient, or linear tensor encoding (LTE), and in tissue exhibiting a "stick-like" diffusion geometry, the direction-averaged diffusion-weighted MRI signal at high b-values ( 7000

Texture Analysis of High b-Value Diffusion-Weighted Imaging for Evaluating Consistency of Pituitary Macroadenomas.

BACKGROUND: Preoperative evaluation of the consistency of pituitary macroadenomas is important for neurosurgeons to prepare the surgical plan. PURPOSE: To evaluate the diagnostic performance of texture analysis (TA) of diffusion-weighted imaging (DWI) at a standard b-value (b = 1000 s/mm2 ) and a high b-value (b = 2000 s/mm2 ) for their ability to assess the tumor consistency of pituitary macroadenomas. STUDY TYPE: Retrospective. POPULATION/SUBJECTS: Fifty patients with histologically confirmed pituitary macroadenomas were classified as soft (n = 37) or hard (n = 13) types. FIELD STRENGTH/SEQUENCE: Coronal T2 -weighted imaging (T2 WI), Readout Segmentation of Long Variable Echo-trains (RESOLVE) DWI at b = 1000 s/mm2 and b = 2000 s/mm2 were acquired with 3.0T MRI. ASSESSMENT: The corresponding apparent diffusion coefficient (ADC) maps (ADC1000 and ADC2000 ) were registered to T2 WI. Regions of interest (ROIs) were manually drawn along the solid part of the tumor from the coregistered T2 WI-ADC images. The texture parameters from T2 WI, ADC1000 , and ADC2000 were acquired. STATISTICAL TESTS: The texture parameters were compared between the two types by using unpaired Student's t-test. Receiver operating characteristic (ROC) curves and logistic regression analyses were used to assess their diagnostic performance. RESULTS: Significant differences in TA parameters of ADC1000 and ADC2000 were observed between soft and hard types (P < 0.05 for all), whereas the TA of T2 WI resulted in no significant difference (P > 0.05 for all). TA of ADC2000 provided a superior diagnostic performance compared with that of ADC1000 (P = 0.038). A combination of mean value and entropy of ADC2000 yielded an AUC, a sensitivity, and a specificity of 0.911, 78.4% and 92.3%, respectively. DATA CONCLUSION: TA of ADC values were useful for assessing the tumor consistency of pituitary macroadenomas. ADC2000 may facilitate better type discrimination. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1507-1513.

Age-related alterations in axonal microstructure in the corpus callosum measured by high-gradient diffusion MRI.

Cerebral white matter exhibits age-related degenerative changes during the course of normal aging, including decreases in axon density and alterations in axonal structure. Noninvasive approaches to measure these microstructural alterations throughout the lifespan would be invaluable for understanding the substrate and regional variability of age-related white matter degeneration. Recent advances in diffusion magnetic resonance imaging (MRI) have leveraged high gradient strengths to increase sensitivity toward axonal size and density in the living human brain. Here, we examined the relationship between age and indices of axon diameter and packing density using high-gradient strength diffusion MRI in 36 healthy adults (aged 22-72) in well-defined central white matter tracts in the brain. A recently validated method for inferring the effective axonal compartment size and packing density from diffusion MRI measurements acquired with 300 mT/m maximum gradient strength was applied to the in vivo human brain to obtain indices of axon diameter and density in the corpus callosum, its sub-regions, and adjacent anterior and posterior fibers in the forceps minor and forceps major. The relationships between the axonal metrics, corpus callosum area and regional gray matter volume were also explored. Results revealed a significant increase in axon diameter index with advancing age in the whole corpus callosum. Similar analyses in sub-regions of the corpus callosum showed that age-related alterations in axon diameter index and axon density were most pronounced in the genu of the corpus callosum and relatively absent in the splenium, in keeping with findings from previous histological studies. The significance of these correlations was mirrored in the forceps minor and forceps major, consistent with previously reported decreases in FA in the forceps minor but not in the forceps major with age. Alterations in the axonal imaging metrics paralleled decreases in corpus callosum area and regional gray matter volume with age. Among older adults, results from cognitive testing suggested an association between larger effective compartment size in the corpus callosum, particularly within the genu of the corpus callosum, and lower scores on the Montreal Cognitive Assessment, largely driven by deficits in short-term memory. The current study suggests that high-gradient diffusion MRI may be sensitive to the axonal substrate of age-related white matter degeneration reflected in traditional DTI metrics and provides further evidence for regionally selective alterations in white matter microstructure with advancing age.

Improved stimulated echo in diffusion magnetic resonance imaging: introducing a π pulse for SNR enhancement.

PURPOSE: Anomalous diffusion in biological tissues can be examined by diffusion MRI for various applications, including tumor diagnosis and measurement of brain fiber pathways. However, the measurement of anomalous diffusion requires high b-values for the diffusion gradient in MRI, and current MRI methods cannot provide a high SNR. This study aimed to improve on the standard stimulated echo (STE) to enhance the SNR in diffusion MRI with high b-values. METHODS: Because of hardware limitations and human safety considerations, prolonging the diffusion time (Δ) is 1 of the few methods available to realize high b-values. Here, we propose a new echo mechanism for diffusion MRI to enhance SNRs under long Δ. By introducing a π pulse at the midpoint between 2nd and 3rd π/2 pulses of STE, we refocus the magnetic moment vectors in the longitudinal plane before the third π/2 pulse is applied, which preserves the full echo signals. This sequence was compared with STE and spin echo (SE). Nine Δs were tested in a phantom. Multi b-values with 2 Δs were tested in a mouse liver, brain, and tumor. RESULTS: Compared with STE and SE, the proposed improved STE (ISTE) exhibited an improved SNR in the phantom experiment and improved performance in the in vivo experiments. CONCLUSION: By using the proposed echo mechanism in diffusion MRI, we enhanced the SNR of the images, which enables us to investigate diffusion behavior at higher b-values and further facilitates the development of quantitative diffusion MRI and radiomics.

A fractional motion diffusion model for a twice-refocused spin-echo pulse sequence.

The purpose of this study was to develop an analytical expression for a fractional motion (FM) diffusion model to characterize diffusion-induced signal attenuation in a twice-refocused spin-echo (TRSE) sequence that is resilient to eddy currents, and to demonstrate its applicability to human brain imaging in vivo. Based on the FM theory, which provides a unified statistical description for Langevin motions, the diffusion-weighted (DW) MR signal was measured with a TRSE sequence that balances the concomitant gradients. The analytical expression was fitted to a set of DW images acquired with 14 b-values (0-4000 s/mm2 ) from a total of 10 healthy human subjects at 3 T, yielding three FM parameter maps based on anomalous diffusion coefficient Dφ, ψ , diffusion increment variance φ, and diffusion correlation ψ, respectively. These parameters were used to characterize different brain regions in gray matter (GM), white matter (WM), and cerebrospinal fluid. The analytical expression for the TRSE-based FM model accurately described diffusion signal attenuation in healthy brain tissues at high b-values. TRSE's robustness against eddy currents was illustrated by comparing results from an expression for a conventional Stejskal-Tanner sequence. The TRSE-based FM model also produced consistent GM-WM contrast (p < 0.01) across all brain regions studied, whereas the consistency was not observed with the Stejskal-Tanner-based FM model. This new analytical expression is expected to enable further investigations to probe tissue structures by exploiting anomalous diffusion properties without being hindered by eddy-current perturbations at high b-values.

Characterizing intra-axonal water diffusion with direction-averaged triple diffusion encoding MRI.

For large diffusion weightings, the direction-averaged diffusion MRI (dMRI) signal from white matter is typically dominated by the contribution of water confined to axons. This fact can be exploited to characterize intra-axonal diffusion properties, which may be valuable for interpreting the biophysical meaning of diffusion changes associated with pathology. However, using just the classic Stejskal-Tanner pulse sequence, it has proven challenging to obtain reliable estimates for both the intrinsic intra-axonal diffusivity and the intra-axonal water fraction. Here we propose to apply a modification of the Stejskal-Tanner sequence designed for achieving such estimates. The key feature of the sequence is the addition of a set of extra diffusion encoding gradients that are orthogonal to the direction of the primary gradients, which corresponds to a specific type of triple diffusion encoding (TDE) MRI sequence. Given direction-averaged dMRI data for this TDE sequence, it is shown how the intra-axonal diffusivity and the intra-axonal water fraction can be determined by applying simple, analytic formulae. The method is illustrated with numerical simulations, which suggest that it should be accurate for b-values of about 4000 s/mm2 or higher.

Head-To-Head Comparison Between High- and Standard-b-Value DWI for Detecting Prostate Cancer: A Systematic Review and Meta-Analysis.

OBJECTIVE: The purpose of this study was to perform a head-to-head comparison between high-b-value (> 1000 s/mm2) and standard-b-value (800-1000 s/mm2) DWI regarding diagnostic performance in the detection of prostate cancer. MATERIALS AND METHODS: The MEDLINE and EMBASE databases were searched up to April 1, 2017. The analysis included diagnostic accuracy studies in which high- and standard-b-value DWI were used for prostate cancer detection with histopathologic examination as the reference standard. Methodologic quality was assessed with the revised Quality Assessment of Diagnostic Accuracy Studies tool. Sensitivity and specificity of all studies were calculated and were pooled and plotted in a hierarchic summary ROC plot. Meta-regression and multiple-subgroup analyses were performed to compare the diagnostic performances of high- and standard-b-value DWI. RESULTS: Eleven studies (789 patients) were included. High-b-value DWI had greater pooled sensitivity (0.80 [95% CI, 0.70-0.87]) (p = 0.03) and specificity (0.92 [95% CI, 0.87-0.95]) (p = 0.01) than standard-b-value DWI (sensitivity, 0.78 [95% CI, 0.66-0.86]); specificity, 0.87 [95% CI, 0.77-0.93] (p < 0.01). Multiple-subgroup analyses showed that specificity was consistently higher for high- than for standard-b-value DWI (p ≤ 0.05). Sensitivity was significantly higher for high- than for standard-b-value DWI only in the following subgroups: peripheral zone only, transition zone only, multiparametric protocol (DWI and T2-weighted imaging), visual assessment of DW images, and per-lesion analysis (p ≤ 0.04). CONCLUSION: In a head-to-head comparison, high-b-value DWI had significantly better sensitivity and specificity for detection of prostate cancer than did standard-b-value DWI. Multiple-subgroup analyses showed that specificity was consistently superior for high-b-value DWI.

Accuracy of high b-value diffusion-weighted MRI for prostate cancer detection: a meta-analysis.

Background The diagnostic accuracy of diffusion-weighted imaging (DWI) to detect prostate cancer is well-established. DWI provides visual as well as quantitative means of detecting tumor, the apparent diffusion coefficient (ADC). Recently higher b-values have been used to improve DWI's diagnostic performance. Purpose To determine the diagnostic performance of high b-value DWI at detecting prostate cancer and whether quantifying ADC improves accuracy. Material and Methods A comprehensive literature search of published and unpublished databases was performed. Eligible studies had histopathologically proven prostate cancer, DWI sequences using b-values ≥ 1000 s/mm2, less than ten patients, and data for creating a 2 × 2 table. Study quality was assessed with QUADAS-2 (Quality Assessment of diagnostic Accuracy Studies). Sensitivity and specificity were calculated and tests for statistical heterogeneity and threshold effect performed. Results were plotted on a summary receiver operating characteristic curve (sROC) and the area under the curve (AUC) determined the diagnostic performance of high b-value DWI. Results Ten studies met eligibility criteria with 13 subsets of data available for analysis, including 522 patients. Pooled sensitivity and specificity were 0.59 (95% confidence interval [CI], 0.57-0.61) and 0.92 (95% CI, 0.91-0.92), respectively, and the sROC AUC was 0.92. Subgroup analysis showed a statistically significant ( P = 0.03) improvement in accuracy when using tumor visual assessment rather than ADC. Conclusion High b-value DWI gives good diagnostic performance for prostate cancer detection and visual assessment of tumor diffusion is significantly more accurate than ROI measurements of ADC.

Prospective motion correction in diffusion-weighted imaging using intermediate pseudo-trace-weighted images.

Subject head motion is a major challenge in diffusion-weighted imaging, which requires a precise alignment of images from different time points to allow a reliable quantification of diffusion parameters within each voxel. The technique requires long measurement times, making it highly sensitive to long-term subject motion, even when head restraint is used. Current methods of data analysis rely on retrospective motion correction, but there are potential benefits to using prospective motion correction, in which motion is tracked and compensated for during data acquisition. This technique is regularly used to enhance image quality in blood-oxygen-level dependent (BOLD) imaging, but its application to diffusion-weighted imaging has been limited by the contrast variation between images acquired with different diffusion-gradient directions. This paper describes a novel approach to this topic that exploits the rotational invariance of the trace of the diffusion tensor to reduce the effect of this contrast variation, making it possible to perform a fast image registration using a least-squares cost function. This results in an image-based motion detection algorithm that can be applied in real time during data acquisition to adapt the slice position and orientation in response to subject motion. The motion detection capabilities of the technique were evaluated in a study of ten subjects with b-values up to 3000s/mm². The resulting motion-parameter estimates were in close agreement with reference values provided by interleaved low-b-value images with a correlation coefficient of R=0.9634 for the voxel displacements measured across all subjects and b-values. The technique was also used to perform prospective motion correction on a standard clinical MRI system with b-values up to 2000s/mm². The correction was evaluated in 3 subjects using interleaved low-b-value images, retrospective image registration using the AFNI processing package and mean diffusivity histogram analysis. Compared to acquisitions without motion correction, prospective motion correction based on pseudo-trace-weighted images was found to provide a robust method for substantially reducing the level of misregistration between volumes. In most cases, misregistrations were reduced to less than 0.2mm of translation and 0.2° of rotation for an isotropic voxel size of 2mm, yielding high-quality diffusion parameter maps even in the absence of head restraint and post-acquisition image registration.