Diffusion MRI (dMRI) has become one of the most important imaging modalities for noninvasively probing tissue microstructure. Diffusional Kurtosis MRI (DKI) quantifies the degree of non-Gaussian ...diffusion, which in turn has been shown to increase sensitivity towards, e.g., disease and orientation mapping in neural tissue. However, the specificity of DKI is limited as different sources can contribute to the total intravoxel diffusional kurtosis, including: variance in diffusion tensor magnitudes (Kiso), variance due to diffusion anisotropy (Kaniso), and microscopic kurtosis (μK) related to restricted diffusion, microstructural disorder, and/or exchange. Interestingly, μK is typically ignored in diffusion MRI signal modelling as it is assumed to be negligible in neural tissues. However, recently, Correlation Tensor MRI (CTI) based on Double-Diffusion-Encoding (DDE) was introduced for kurtosis source separation, revealing non negligible μK in preclinical imaging. Here, we implemented CTI for the first time on a clinical 3T scanner and investigated the sources of total kurtosis in healthy subjects. A robust framework for kurtosis source separation in humans is introduced, followed by estimation of μK (and the other kurtosis sources) in the healthy brain. Using this clinical CTI approach, we find that μK significantly contributes to total diffusional kurtosis both in grey and white matter tissue but, as expected, not in the ventricles. The first μK maps of the human brain are presented, revealing that the spatial distribution of μK provides a unique source of contrast, appearing different from isotropic and anisotropic kurtosis counterparts. Moreover, group average templates of these kurtosis sources have been generated for the first time, which corroborated our findings at the underlying individual-level maps. We further show that the common practice of ignoring μK and assuming the multiple Gaussian component approximation for kurtosis source estimation introduces significant bias in the estimation of other kurtosis sources and, perhaps even worse, compromises their interpretation. Finally, a twofold acceleration of CTI is discussed in the context of potential future clinical applications. We conclude that CTI has much potential for future in vivo microstructural characterizations in healthy and pathological tissue.
Background
There is growing interest in the effect of diffusion time on apparent diffusion coefficient (ADC) values in cancers; however, little evidence exists regarding its utility to differentiate ...malignant from benign head and neck tumors.
Purpose
To investigate the utility of ADC value changes in distinguishing between malignant and benign head and neck tumors using the different diffusion times obtained from oscillating gradient spin‐echo (OGSE) and pulsed gradient spin‐echo (PGSE) MRI sequences.
Study Type
Prospective.
Subjects
Thirty‐one consecutive patients with suspected head and neck tumors and a phantom.
Field Strength/Sequence
3T MRI with diffusion‐weighted imaging (DWI) using OGSE (effective diffusion time: 4.3 msec) and PGSE (effective diffusion time: 82.6 msec) sequences and b‐values of 0 and 700 s/mm2.
Assessment
ADC values using OGSE (ADCOGSE) and PGSE (ADCPGSE) and relative ADC value changes between ADCOGSE and ADCPGSE.
Statistical Tests
Wilcoxon test, Mann–Whitney test, and McNemar test.
Results
Relative ADC changes for each polyvinylpyrrolidone (PVP) and water in the phantom between OGSE and PGSE sequences were small (relative ADC change within 0.6%). Malignant tumors had significantly smaller ADCOGSE and ADCPGSE values than benign tumors (P < 0.001 and < 0.0001, respectively). Significantly larger relative ADC changes were observed in malignant compared with benign head and neck tumors (P < 0.0001). ADCPGSE values were significantly lower than ADCOGSE values in both malignant and benign head and neck tumors (0.97 vs. 1.28 × 10−3mm2/s: P < 0.0001 and 1.93 vs. 1.99 × 10−3mm2/s: P = 0.0056, respectively). Relative ADC change and ADCPGSE tended to have higher diagnostic performance than ADCOGSE, with area under the curve (AUC) values of 0.97, 0.96, and 0.89, respectively.
Data Conclusion
ADC values obtained using the PGSE sequence were lower than those obtained with OGSE. This difference was larger for malignant than benign tumors, suggesting differences in tissue structure (diffusion hindrance) or cell permeability, revealed by changes in diffusion time. The results underline the potential importance of reporting diffusion time for interpretation of head and neck diffusion MRI.
Level of Evidence: 1
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2019;50:88–95.
The engineering of a 3T human MRI scanner equipped with 300mT/m gradients – the strongest gradients ever built for an in vivo human MRI scanner – was a major component of the NIH Blueprint Human ...Connectome Project (HCP). This effort was motivated by the HCP's goal of mapping, as completely as possible, the macroscopic structural connections of the in vivo healthy, adult human brain using diffusion tractography. Yet, the 300mT/m gradient system is well suited to many additional types of diffusion measurements. Here, we present three initial applications of the 300mT/m gradients that fall outside the immediate scope of the HCP. These include: 1) diffusion tractography to study the anatomy of consciousness and the mechanisms of brain recovery following traumatic coma; 2) q-space measurements of axon diameter distributions in the in vivo human brain and 3) postmortem diffusion tractography as an adjunct to standard histopathological analysis. We show that the improved sensitivity and diffusion-resolution provided by the gradients are rapidly enabling human applications of techniques that were previously possible only for in vitro and animal models on small-bore scanners, thereby creating novel opportunities to map the microstructure of the human brain in health and disease.
•Diffusion spectrum imaging to study traumatic coma recovery•In vivo human axon diameter measurements using 300mT/m gradients•High-resolution (0.6mm isotropic) diffusion imaging in whole, fixed human brain
Introduction/Aims
Muscle diffusion tensor imaging has not yet been explored in facioscapulohumeral muscular dystrophy (FSHD). We assessed diffusivity parameters in FSHD subjects compared with healthy ...controls (HCs), with regard to their ability to precede any fat replacement or edema.
Methods
Fat fraction (FF), water T2 (wT2), mean, radial, axial diffusivity (MD, RD, AD), and fractional anisotropy (FA) of thigh muscles were calculated in 10 FSHD subjects and 15 HCs. All parameters were compared between FSHD and controls, also exploring their gradient along the main axis of the muscle. Diffusivity parameters were tested in a subgroup analysis as predictors of disease involvement in muscle compartments with different degrees of FF and wT2 and were also correlated with clinical severity scores.
Results
We found that MD, RD, and AD were significantly lower in FSHD subjects than in controls, whereas we failed to find a difference for FA. In contrast, we found a significant positive correlation between FF and FA and a negative correlation between MD, RD, and AD and FF. No correlation was found with wT2. In our subgroup analysis we found that muscle compartments with no significant fat replacement or edema (FF < 10% and wT2 < 41 ms) showed a reduced AD and FA compared with controls. Less involved compartments showed different diffusivity parameters than more involved compartments.
Discussion
Our exploratory study was able to demonstrate diffusivity parameter abnormalities even in muscles with no significant fat replacement or edema. Larger cohorts are needed to confirm these preliminary findings.
There is ongoing debate whether using a higher spatial resolution (sampling k-space) or a higher angular resolution (sampling q-space angles) is the better way to improve diffusion MRI (dMRI) based ...tractography results in living humans. In both cases, the limiting factor is the signal-to-noise ratio (SNR), due to the restricted acquisition time. One possible way to increase the spatial resolution without sacrificing either SNR or angular resolution is to move to a higher magnetic field strength. Nevertheless, dMRI has not been the preferred application for ultra-high field strength (7T). This is because single-shot echo-planar imaging (EPI) has been the method of choice for human in vivo dMRI. EPI faces several challenges related to the use of a high resolution at high field strength, for example, distortions and image blurring. These problems can easily compromise the expected SNR gain with field strength. In the current study, we introduce an adapted EPI sequence in conjunction with a combination of ZOOmed imaging and Partially Parallel Acquisition (ZOOPPA). We demonstrate that the method can produce high quality diffusion-weighted images with high spatial and angular resolution at 7T. We provide examples of in vivo human dMRI with isotropic resolutions of 1mm and 800μm. These data sets are particularly suitable for resolving complex and subtle fiber architectures, including fiber crossings in the white matter, anisotropy in the cortex and fibers entering the cortex.
Display omitted
► Diffusion MRI (dMRI) at ultra-high field strength. ► Using ZOOPPA to exploit the SNR benefit of the high field strength. ► Enables dMRI with sub-millimeter isotropic resolution. ► High spatial and angular resolution with sufficient SNR to resolve crossing fibers.
Purpose
To develop a noninvasive technique to map human spinal cord (SC) perfusion in vivo. More specifically, to implement an intravoxel incoherent motion (IVIM) protocol at ultrahigh field for the ...human SC and assess parameters estimation errors.
Methods
Monte‐Carlo simulations were conducted to assess estimation errors of 2 standard IVIM fitting approaches (two‐step versus one‐step fit) over the range of IVIM values reported for the human brain and for typical SC diffusivities. Required signal‐to‐noise ratio (SNR) was inferred for estimation of the parameters product, fIVIMD* (microvascular fraction times pseudo‐diffusion coefficient), within 10% error margins. In‐vivo IVIM imaging of the SC was performed at 7T in 6 volunteers. An image processing pipeline is proposed to generate IVIM maps and register them for an atlas‐based region‐wise analysis.
Results
Required b = 0 SNRs for 10% error estimation on fIVIMD* with the one‐step fit were 159 and 185 for diffusion‐encoding perpendicular and parallel to the SC axis, respectively. Average in vivo b = 0 SNR within cord was 141 ± 79, corresponding to estimation errors of 12.7% and 14.7% according to numerical simulations. Slice‐ and group‐averaging reduced noise in IVIM maps, highlighting the difference in perfusion between gray and white matter. Mean ± standard deviation fIVIM and D* values across subjects within gray (respectively white) matter were 16.0 ± 1.7 (15.0 ± 1.6)% and 11.4 ± 2.9 (11.5 ± 2.4) × 10−3 mm2/s.
Conclusion
Single‐subject data SNR at 7T was insufficient for reliable perfusion estimation. However, atlas‐averaged IVIM maps highlighted the higher microvascular fraction of gray matter compared to white matter, providing first results of healthy human SC perfusion mapping with MRI.
The microstructural underpinnings of reduced diffusivity in transient splenial lesion remain unclear. Here, we report findings from oscillating gradient spin-echo (OGSE) diffusion imaging in a case ...of transient splenial lesion. Compared with normal-appearing white matter, the splenial lesion exhibited greater differences between diffusion time t = 6.5 and 35.2 ms, indicating microstructural changes occurring within the corresponding length scale. We also conducted 2D Monte-Carlo simulation. The results suggested that emergence of small and non-exchanging compartment, as often imagined in intramyelinic edema, does not fit well with the in vivo observation. Simulations with axonal swelling and microglial infiltration yielded results closer to the in vivo observations. The present report exemplifies the importance of controlling t for more specific radiological image interpretations.
Oscillating gradient spin-echo (OGSE) sequences enable acquisitions with shorter diffusion times. There is growing interest in the effect of diffusion time on apparent diffusion coefficient (ADC) ...values in patients with cancer. However, little evidence exists regarding its usefulness for differentiating between high-grade and low-grade brain tumors. The purpose of this study is to investigate the utility of changes in the ADC value between short and long diffusion times in distinguishing low-grade and high-grade brain tumors.
Eleven patients with high-grade brain tumors and ten patients with low-grade brain tumors were scanned using a 3 T magnetic resonance imaging with diffusion-weighted imaging (DWI) using OGSE and PGSE (effective diffusion time Δeff: 6.5 ms and 35.2 ms) and b-values of 0 and 1000 s/mm2. Using a region of interest (ROI) analysis of the brain tumors, we measured the ADC for two Δeff (ADCΔeff) values and computed the subtraction ADC (ΔADC = ADC6.5 ms − ADC35.2 ms) and the relative ADC (ΔADC = (ADC6.5 ms − ADC35.2 ms) / ADC35.2 ms × 100). The maximum values for the subtraction ADC (ΔADCmax) and the relative ADC (rADCmax) on the ROI were compared between low-grade and high-grade tumors using the Wilcoxon rank-sum test. A P-value <.05 was considered significant. The ROIs were also placed in the normal white matter of patients with high- and low-grade brain tumors, and ΔADCmax values were determined.
High-grade tumors had significantly higher ΔADCmax and rADCmax than low-grade tumors. The ΔADCmax values of the normal white matter were lower than the ΔADCmax of high- and low-grade brain tumors.
The dependence of ADC values on diffusion time between 6.5 ms and 35.2 ms was stronger in high-grade tumors than in low-grade tumors, suggesting differences in internal tissue structure. This finding highlights the importance of reporting diffusion times in ADC evaluations and might contribute to the grading of brain tumors using DWI.
PDF
