DTI at 7 and 3 T: systematic comparison of SNR and its influence on quantitative metrics

ComBating inter-site differences in field strength: harmonizing preclinical traumatic brain injury MRI data

Integrating datasets from multiple sites and scanners can increase statistical power for neuroimaging studies but can also introduce significant inter-site confounds. We evaluated the effectiveness of ComBat, an empirical Bayes approach, to combine longitudinal preclinical MRI data acquired at 4.7 or 9.4 T at two different sites in Australia. Male Sprague Dawley rats underwent MRI on Days 2, 9, 28, and 150 following moderate/severe traumatic brain injury (TBI) or sham injury as part of Project 1 of the NIH/NINDS-funded Centre Without Walls EpiBioS4Rx project. Diffusion-weighted and multiple-gradient-echo images were acquired, and outcomes included QSM, FA, and ADC. Acute injury measures including apnea and self-righting reflex were consistent between sites. Mixed-effect analysis of ipsilateral and contralateral corpus callosum (CC) summary values revealed a significant effect of site on FA and ADC values, which was removed following ComBat harmonization. Bland-Altman plots for each metric showed reduced variability across sites following ComBat harmonization, including for QSM, despite appearing to be largely unaffected by inter-site differences and no effect of site observed. Following harmonization, the combined inter-site data revealed significant differences in the imaging metrics consistent with previously reported outcomes. TBI resulted in significantly reduced FA and increased susceptibility in the ipsilateral CC, and significantly reduced FA in the contralateral CC compared with sham-injured rats. Additionally, TBI rats also exhibited a reversal in ipsilateral CC ADC values over time with significantly reduced ADC at Day 9, followed by increased ADC 150 days after injury. Our findings demonstrate the need for harmonizing multi-site preclinical MRI data and show that this can be successfully achieved using ComBat while preserving phenotypical changes due to TBI.

The effect of elimination of gibbs ringing, noise and systematic errors on the DTI metrics and tractography in a rat brain

Diffusion tensor imaging (DTI) metrics and tractography can be biased due to low signal-to-noise ratio (SNR) and systematic errors resulting from image artifacts and imperfections in magnetic field gradients. The imperfections include non-uniformity and nonlinearity, effects caused by eddy currents, and the influence of background and imaging gradients. We investigated the impact of systematic errors on DTI metrics of an isotropic phantom and DTI metrics and tractography of a rat brain measured at high resolution. We tested denoising and Gibbs ringing removal methods combined with the B matrix spatial distribution (BSD) method for magnetic field gradient calibration. The results showed that the performance of the BSD method depends on whether Gibbs ringing is removed and the effectiveness of stochastic error removal. Region of interest (ROI)-based analysis of the DTI metrics showed that, depending on the size of the ROI and its location in space, correction methods can remove systematic bias to varying degrees. The preprocessing pipeline proposed and dedicated to this type of data together with the BSD method resulted in an even - 90% decrease in fractional anisotropy (FA) (globally and locally) in the isotropic phantom and - 45% in the rat brain. The largest global changes in the rat brain tractogram compared to the standard method without preprocessing (sDTI) were noticed after denoising. The direction of the first eigenvector obtained from DTI after denoising, Gibbs ringing removal and BSD differed by an average of 56 and 10 degrees in the ROI from sDTI and from sDTI after denoising and Gibbs ringing removal, respectively. The latter can be identified with the amount of improvement in tractography due to the elimination of systematic errors related to imperfect magnetic field gradients. Based on the results, the systematic bias for high resolution data mainly depended on SNR, but the influence of non-uniform gradients could also be seen. After denoising, the BSD method was able to further correct both the metrics and tractography of the diffusion tensor in the rat brain by taking into account the actual distribution of magnetic field gradients independent of the examined object and uniquely dependent on the scanner and sequence. This means that in vivo studies are also subject to this type of errors, which should be taken into account when processing such data.

Widespread White Matter Abnormalities in Concussed Athletes Detected by 7T Diffusion Magnetic Resonance Imaging

Sports-related concussions may cause white matter injuries and persistent post-concussive symptoms (PPCS). We hypothesized that athletes with PPCS would have neurocognitive impairments and white matter abnormalities that could be revealed by advanced neuroimaging using ultra-high field strength diffusion tensor (DTI) and diffusion kurtosis (DKI) imaging metrics and cerebrospinal fluid (CSF) biomarkers. A cohort of athletes with PPCS severity limiting the ability to work/study and participate in sport school and/or social activities for ≥6 months completed 7T magnetic resonance imaging (MRI) (morphological T1-weighed volumetry, DTI and DKI), extensive neuropsychological testing, symptom rating, and CSF biomarker sampling. Twenty-two athletes with PPCS and 22 controls were included. Concussed athletes performed below norms and significantly lower than controls on all but one of the psychometric neuropsychology tests. Supratentorial white and gray matter, as well as hippocampal volumes did not differ between concussed athletes and controls. However, of the 72 examined white matter tracts, 16% of DTI and 35% of DKI metrics (in total 28%) were significantly different between concussed athletes and controls. DKI fractional anisotropy and axial kurtosis were increased, and DKI radial diffusivity and radial kurtosis decreased in concussed athletes when compared with controls. CSF neurofilament light (NfL; an axonal injury marker), although not glial fibrillary acidic protein, correlated with several diffusion metrics. In this first 7T DTI and DKI study investigating PPCS, widespread microstructural alterations were observed in the white matter, correlating with CSF markers of axonal injury. More white matter changes were observed using DKI than using DTI. These white matter alterations may indicate persistent pathophysiological processes following concussion in sport.

Current perspectives on tractography-guided deep brain stimulation for the treatment of mood disorders

INTRODUCTION

Deep brain stimulation (DBS) is an emerging therapy for mood disorders, particularly treatment-resistant depression (TRD). Different brain areas implicated in depression-related brain networks have been investigated as DBS targets and variable clinical outcomes highlight the importance of target identification. Tractography has provided insight into how DBS modulates disorder-related brain networks and is being increasingly used to guide DBS for psychiatric disorders.

AREAS COVERED

In this perspective, an overview of the current state of DBS for TRD and the principles of tractography is provided. Next, a comprehensive review of DBS targets is presented with a focus on tractography. Finally, the challenges and future directions of tractography-guided DBS are discussed.

EXPERT OPINION

Tractography-guided DBS is a promising tool for improving DBS outcomes for mood disorders. Tractography is particularly useful for targeting patient-specific white matter tracts that are not visible using conventional structural MRI. Developments in tractography methods will help refine DBS targeting for TRD and may facilitate symptom-specific precision neuromodulation. Ultimately, the standardization of tractography methods will be essential to transforming DBS into an established therapy for mood disorders.

Influence of adaptive denoising on Diffusion Kurtosis Imaging at 3T and 7T

BACKGROUND AND OBJECTIVE

Choosing the most appropriate denoising method to improve the quality of diagnostic images maximally is key in pre-processing of diffusion MRI images. Recent advancements in acquisition and reconstruction techniques have questioned traditional noise estimation methods favoring adaptive denoising frameworks, circumventing the need to know a priori information that is hardly available in a clinical setting. In this observational study, we compared two innovative adaptive techniques sharing some features, Patch2Self and Nlsam, through application on reference adult data at 3T and 7T. The primary aim was identifying the most effective method in case of Diffusion Kurtosis Imaging (DKI) data - particularly susceptible to noise and signal fluctuations - at 3T and 7T fields. A side goal consisted of investigating the dependence of kurtosis metrics' variability with respect to the magnetic field on the adopted denoising methodology.

METHODS

For comparison purposes, we focused on qualitative and quantitative analysis of DKI data and related microstructural maps before and after applying the two denoising approaches. Specifically, we assessed computational efficiency, preservation of anatomical details via perceptual metrics, consistency of microstructure model fitting, alleviation of degeneracies in model estimation, and joint variability with varying field strength and denoising method.

RESULTS

Accounting for all these factors, Patch2Self framework has turned out to be specifically suitable for DKI data, with improving performance at 7T. Nlsam method is more robust in alleviating degenerate black voxels while introducing some blurring, which in turn is reflected in an overall loss of image sharpness. Regarding the impact of denoising on field-dependent variability, both methods have been shown to make variations from standard to Ultra-High Field more concordant with theoretical evidence, claiming that kurtosis metrics are sensitive to susceptibility-induced background gradients, directly proportional to the magnetic field strength and sensitive to the microscopic distribution of iron and myelin.

CONCLUSIONS

This study serves as a proof-of-concept stressing the need for an accurate choice of a denoising methodology, specifically tailored for the data under analysis and allowing higher spatial resolution acquisition within clinically compatible timings, with all the potential benefits that improving suboptimal quality of diagnostic images entails.

Dependence of apparent diffusion coefficient on slice position in magnetic resonance diffusion imaging

PURPOSE

The position dependence of the apparent diffusion coefficient (ADC) in magnetic resonance imaging (MRI) by echo-planar imaging (EPI)- and turbo spin echo (TSE)-diffusion-weighted imaging (DWI) was assessed using phantoms.

METHODS

Six pure water-filled containers were placed parallel to the direction of the static magnetic field from the center of the magnetic field to the foot direction (five containers) and the head direction (one container). Six slice positions were set, and a cross-section image was scanned at the center of each container using a 1.5-T MRI scanner. Diffusion times for both EPI- and TSE-DWI were matched as much as possible. The slice thickness was adjusted to match the signal-to-noise ratio (SNR) at the center of the magnetic field for both sequences. A B₁ map was analyzed. The ADC and SNR at each position of both sequences were tested using the Wilcoxon signed-rank test (P = 0.05) and compared using Friedman and Steel-Dwass multiple comparison tests (P = 0.05). Pearson correlation coefficients between ADC and SNR and between ADC and flip angle (FA) were calculated.

RESULTS

ADC decreased significantly with distance from the center of the magnetic field for both EPI-DWI and TSE-DWI (P < 0.05). TSE-ADC was significantly higher than EPI-ADC for all combinations (P < 0.01). Based on the Friedman test, the SNR of EPI- and TSE-DWI was significantly different and depended on the slice position (P < 0.01). The Pearson correlation coefficient between ADC and SNR was 0.78 in EPI-DWI and 0.60 in TSE-DWI, whereas that between ADC and FA was 0.97 in EPI-DWI and 0.94 in TSE-DWI. The FA decreased by 0.048 and 0.047° per mm from the center of the magnetic field to head and foot directions, respectively.

CONCLUSION

ADC depends on the slice position and decreases with an increase in distance from the magnetic field center. Caution should be taken when comparing and quantitatively evaluating the ADC at sites shifted in the long-axis direction.

High-resolution diffusion-weighted imaging at 7 Tesla: single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy

Diffusion MRI (dMRI) is a valuable imaging technique to study the connectivity and microstructure of the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various multi-shot acquisition strategies have been developed to achieve sub-millimeter resolution, but they require long scan times which can be restricting for patient scans. Alternatively, the SNR of single-shot acquisitions can be increased by using a spiral readout trajectory to minimize the sequence echo time. Imaging at ultra-high fields (UHF) could further increase the SNR of single-shot dMRI; however, the shorter T2* of brain tissue and the greater field non-uniformities at UHFs will degrade image quality, causing image blurring, distortions, and signal loss. In this study, we investigated the trade-off between the SNR and resolution of different k-space trajectories, including echo planar imaging (EPI), partial Fourier EPI, and spiral trajectories, over a range of dMRI resolutions at 7T. The effective resolution, spatial specificity and sharpening effect were measured from the point spread function (PSF) of the simulated diffusion sequences for a nominal resolution range of 0.6-1.8 mm. In-vivo partial brain scans at a nominal resolution of 1.5 mm isotropic were acquired using the three readout trajectories to validate the simulation results. Field probes were used to measure dynamic magnetic fields offline up to the 3^rd order of spherical harmonics. Image reconstruction was performed using static ΔB₀ field maps and the measured trajectories to correct image distortions and artifacts, leaving T2* effects as the primary source of blurring. The effective resolution was examined in fractional anisotropy (FA) maps calculated from a multi-shell dataset with b-values of 300, 1000, and 2000 s/mm² in 5, 16, and 48 directions, respectively. In-vivo scans at nominal resolutions of 1, 1.2, and 1.5 mm were acquired and the SNR of the different trajectories calculated using the multiple replica method to investigate the SNR. Finally, in-vivo whole brain scans with an effective resolution of 1.5 mm isotropic were acquired to explore the SNR and efficiency of different trajectories at a matching effective resolution. FA and intra-cellular volume fraction (ICVF) maps calculated using neurite orientation dispersion and density imaging (NODDI) were used for the comparison. The simulations and in vivo imaging results showed that for matching nominal resolutions, EPI trajectories had the highest specificity and effective resolution with maximum image sharpening effect. However, spirals have a significantly higher SNR, in particular at higher resolutions and even when the effective image resolutions are matched. Overall, this work shows that the higher SNR of single-shot spiral trajectories at 7T allows us to achieve higher effective resolutions compared to EPI and PF-EPI to map the microstructure and connectivity of small brain structures.

Sensitivity of Diffusion MRI to White Matter Pathology: Influence of Diffusion Protocol, Magnetic Field Strength, and Processing Pipeline in Systemic Lupus Erythematosus

There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.

Post-Concussive Vestibular Dysfunction Is Related to Injury to the Inferior Vestibular Nerve

Symptoms of vestibular dysfunction such as dizziness and vertigo are common after sports-related concussions (SRC) and associated with a worse outcome and a prolonged recovery. Vestibular dysfunction after SRC can be because of an impairment of the peripheral or central neural parts of the vestibular system. The aim of the present study was to establish the cause of vestibular impairment in athletes with SRC who have persisting post-concussive symptoms (PPCS). We recruited 42 participants-21 athletes with previous SRCs and PPCS ≥6 months and 21 healthy athletic age- and sex-matched controls-who underwent symptom rating, a detailed test battery of vestibular function and 7T magnetic resonance imaging with diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) of cerebellar white matter tracts, and T1-weighted imaging for cerebellar volumetrics. Vestibular dysfunction was observed in 13 SRC athletes and three controls (p = 0.001). Athletes with vestibular dysfunction reported more pronounced symptoms on the Dizziness Handicap Inventory (DHI; p < 0.001) and the Hospital Anxiety and Depression Scale (HADS; p < 0.001). No significant differences in DTI metrics were found, while in DKI two metrics were observed in the superior and/or inferior cerebellar tracts. Cerebellar gray and white matter volumes were similar in athletes with SRC and controls. Compared with controls, pathological video head impulse test results (vHIT; p < 0.001) and cervical vestibular evoked myogenic potentials (cVEMP; p = 0.002) were observed in athletes with SRC, indicating peripheral vestibular dysfunction and specifically suggesting injury to the inferior vestibular nerve. In athletes with persisting symptoms after SRC, vestibular dysfunction is associated with injury to the inferior vestibular nerve.

A simulation study investigating potential diffusion-based MRI signatures of microstrokes

Recent studies suggested that cerebrovascular micro-occlusions, i.e. microstokes, could lead to ischemic tissue infarctions and cognitive deficits. Due to their small size, identifying measurable biomarkers of these microvascular lesions remains a major challenge. This work aims to simulate potential MRI signatures combining arterial spin labeling (ASL) and multi-directional diffusion-weighted imaging (DWI). Driving our hypothesis are recent observations demonstrating a radial reorientation of microvasculature around the micro-infarction locus during recovery in mice. Synthetic capillary beds, randomly- and radially-oriented, and optical coherence tomography (OCT) angiograms, acquired in the barrel cortex of mice (n = 5) before and after inducing targeted photothrombosis, were analyzed. Computational vascular graphs combined with a 3D Monte-Carlo simulator were used to characterize the magnetic resonance (MR) response, encompassing the effects of magnetic field perturbations caused by deoxyhemoglobin, and the advection and diffusion of the nuclear spins. We quantified the minimal intravoxel signal loss ratio when applying multiple gradient directions, at varying sequence parameters with and without ASL. With ASL, our results demonstrate a significant difference (p < 0.05) between the signal-ratios computed at baseline and 3 weeks after photothrombosis. The statistical power further increased (p < 0.005) using angiograms measured at week 4. Without ASL, no reliable signal change was found. We found that higher ratios, and accordingly improved significance, were achieved at lower magnetic field strengths (e.g., B0 = 3T) and shorter echo time TE (< 16 ms). Our simulations suggest that microstrokes might be characterized through ASL-DWI sequence, providing necessary insights for posterior experimental validations, and ultimately, future translational trials.

Apparent diffusion coefficient measurement using thin-slice diffusion-weighted magnetic resonance imaging: assessment of measurement errors and repeatability

We investigated the measurement error and repeatability of the apparent diffusion coefficient (ADC) obtained using thin-slice imaging. Diffusion-weighted images of an ice-water phantom were acquired using 1.5-T and 3.0-T scanners with 1-, 3-, and 5-mm thickness. ADC maps were generated at b = 0 and 1000 mm²/s using five consecutive scans. Measurement errors were assessed with accuracy and precision. Repeatability was assessed using the within-subject coefficient of variation. The ADC accuracy of both scanners agreed with the ADC of water at 0 °C. At 1-mm, precisions were 2.9% and 8.4% for the 3.0-T and 1.5-T scanners, respectively. The repeatabilities of 1-mm thickness were 1.3% and 3.4% in the 3.0-T and 1.5-T scanners, respectively. The 3.0-T scanner showed acceptable measurement errors and moderate repeatability compared with Quantitative Imaging Biomarkers Alliance recommendation. A 3.0-T scanner can be used for reliable ADC measurement, even with a 1-mm thickness at a reasonable scan time.

Longitudinal Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) Derived Metrics in the White Matter

Diffusion-weighted magnetic resonance imaging (DWI) is undergoing constant evolution with the ambitious goal of developing in-vivo histology of the brain. A recent methodological advancement is Neurite Orientation Dispersion and Density Imaging (NODDI), a histologically validated multi-compartment model to yield microstructural features of brain tissue such as geometric complexity and neurite packing density, which are especially useful in imaging the white matter. Since NODDI is increasingly popular in clinical research and fields such as developmental neuroscience and neuroplasticity, it is of vast importance to characterize its reproducibility (or reliability). We acquired multi-shell DWI data in 29 healthy young subjects twice over a rescan interval of 4 weeks to assess the within-subject coefficient of variation (CV_WS), between-subject coefficient of variation (CV_BS) and the intraclass correlation coefficient (ICC), respectively. Using these metrics, we compared regional and voxel-by-voxel reproducibility of the most common image analysis approaches (tract-based spatial statistics [TBSS], voxel-based analysis with different extents of smoothing ["VBM-style"], ROI-based analysis). We observed high test-retest reproducibility for the orientation dispersion index (ODI) and slightly worse results for the neurite density index (NDI). Our findings also suggest that the choice of analysis approach might have significant consequences for the results of a study. Collectively, the voxel-based approach with Gaussian smoothing kernels of ≥4 mm FWHM and ROI-averaging yielded the highest reproducibility across NDI and ODI maps (CV_WS mostly ≤3%, ICC mostly ≥0.8), respectively, whilst smaller kernels and TBSS performed consistently worse. Furthermore, we demonstrate that image quality (signal-to-noise ratio [SNR]) is an important determinant of NODDI metric reproducibility. We discuss the implications of these results for longitudinal and cross-sectional research designs commonly employed in the neuroimaging field.

Magnetic resonance diffusion kurtosis imaging in differential diagnosis of benign and malignant renal tumors

Background

Benign and malignant renal tumors share similar some imaging findings.

Methods

Sixty-six patients with clear cell renal cell carcinoma (CCRCC), 13 patients with renal angiomyolipoma with minimal fat (RAMF) and 7 patients with renal oncocytoma (RO) were examined. For diffusion kurtosis imaging (DKI), respiratory triggered echo-planar imaging sequences were acquired in axial plane (3 b-values: 0, 500, 1000s/mm²). Mean Diffusivity (MD), fractional Anisotropy (FA), mean kurtosis (MK), kurtosis anisotropy (KA) and radial kurtosis (RK) were performed.

Results

For MD, a significant higher value was shown in CCRCC (3.08 ± 0.23) than the rest renal tumors (2.93 ± 0.30 for RO, 1.52 ± 0.24 for AML, P < 0.05). The MD values were higher for RO than for AML (2.93 ± 0.30 vs.1.52 ± 0.24, P < 0.05), while comparable MD values were found between CCRCC and RO (3.08 ± 0.23 vs. 2.93 ± 0.30, P > 0.05). For MK, KA and RK, a significant higher value was shown in AML (1.32 ± 0.16, 1.42 ± 0.23, 1.41 ± 0.29) than CCRCC (0.43 ± 0.08, 0.57 ± 0.16, 0.37 ± 0.11) and RO (0.81 ± 0.08, 0.86 ± 0.16, 0.69 ± 0.08) (P < 0.05). The MK, KA and RK values were higher for RO than for CCRCC (0.81 ± 0.08 vs. 0.43 ± 0.08, 0.86 ± 0.16 vs. 0.57 ± 0.16, 0.69 ± 0.08 vs. 0.37 ± 0.11, P < 0.05). Using MD values of 2.86 as the threshold value for differentiating CCRCC from RO and AML, the best result obtained had a sensitivity of 76.1%, specificity of 72.6%. Using MK, KA and RK values of 1.19,1.13 and 1.11 as the threshold value for differentiating AML from CCRCC and RO, the best result obtained had a sensitivity of 91.2, 86.7, 82.1%, and specificity of 86.7, 83.2, 72.8%.

Conclusion

DKI can be used as another noninvasive biomarker for benign and malignant renal tumors’ differential diagnosis.

Diffusion Imaging in the Post HCP Era

Diffusion imaging is a critical component in the pursuit of developing a better understanding of the human brain. Recent technical advances promise enabling the advancement in the quality of data that can be obtained. In this review the context for different approaches relative to the Human Connectome Project are compared. Significant new gains are anticipated from the use of high-performance head gradients. These gains can be particularly large when the high-performance gradients are employed together with ultrahigh magnetic fields. Transmit array designs are critical in realizing high accelerations in diffusion-weighted (d)MRI acquisitions, while maintaining large field of view (FOV) coverage, and several techniques for optimal signal-encoding are now available. Reconstruction and processing pipelines that precisely disentangle the acquired neuroanatomical information are established and provide the foundation for the application of deep learning in the advancement of dMRI for complex tissues. Level of Evidence: 3 Technical Efficacy Stage: Stage 3.

Magnetic Resonance Imaging of the Musculoskeletal System at 7T: Morphological Imaging and Beyond

In 2017, a whole-body 7T magnetic resonance imaging (MRI) device was given regulatory approval for clinical use in both the EU and United States for neuro and musculoskeletal applications. As 7 Tesla allows for higher signal-to-noise , which results in higher resolution images than those obtained on lower-field-strength scanners, it has attracted considerable attention from the musculoskeletal field, as evidenced by the increasing number of publications in the last decade. Besides morphological imaging, the quantitative MR methods, such as T₂, T₂∗, T_1ρ mapping, sodium imaging, chemical-exchange saturation transfer, and spectroscopy, substantially benefit from ultrahigh field scanning. In this review, we provide technical considerations for the individual techniques and an overview of (mostly) clinical applications for the assessment of cartilage, tendon, meniscus, and muscle. The first part of the review is dedicated to morphological applications at 7T, and the second part describes the most recent developments in quantitative MRI at 7T.

Atrophic Changes and Diffusion Abnormalities of Affected Trigeminal Nerves in Trigeminal Neuralgia Using 7-T MRI

BACKGROUND

Magnetic resonance imaging (MRI) has been widely used for visualizing trigeminal nerves in trigeminal neuralgia.

OBJECTIVE

To assess atrophy and diffusion abnormalities of affected trigeminal nerves in trigeminal neuralgia with 7-T MRI.

METHODS

In this prospective study, 14 patients (mean age 49 years; range 31-64 years) with trigeminal neuralgia underwent 7-T MRI. We measured trigeminal nerve volumes along their course through the pontocerebellar cistern. We also evaluated fractional anisotropy (FA) and quantitative anisotropy (QA) values within cisternal segment and pontine nuclei of the affected-side and unaffected-side trigeminal nerves, using diffusion tensor imaging (DTI). Associations between DTI metrics and Barrow Neurological Institute (BNI) pain scores were examined.

RESULTS

The volumes were significantly smaller for the affected trigeminal nerves (33.83 ± 23.12 mm3) than for the unaffected ones (47.76 ± 32.48 mm3; p = 0.008). Cisternal segment FA and QA values were significantly lower in affected trigeminal nerves than in unaffected ones. However, DTI measurements in the pontine nuclei revealed no significant differences between affected-side and unaffected-side trigeminal nerves. No DTI metrics significantly correlated with BNI pain scores.

CONCLUSION

Our results suggest that 7-T MRI allows identifications of atrophy and diffusion abnormalities of trigeminal nerves in trigeminal neuralgia.

Effects of signal averaging, gradient encoding scheme, and spatial resolution on diffusion kurtosis imaging: An empirical study using 7T MRI

BACKGROUND

Although diffusion gradient directions and b-values have been optimized for diffusion kurtosis imaging (DKI), little is known about the effect of signal averaging on DKI reliability.

PURPOSE

To evaluate how signal averaging influences the reliability of DKI indices using two gradient encoding schemes with three spatial resolutions.

STUDY TYPE

Prospective.

ANIMAL MODEL

Fifteen naïve Sprague-Dawley rats.

FIELD STRENGTH/SEQUENCE

DKI was performed at 7T using two schemes (30 directions with three b-values [30d-3b] and six directions with 15 b-values [6d-15b]), three resolutions, and eight repetitions.

ASSESSMENT

DKI reliability was assessed using voxelwise relative error (σ) and test-retest error of fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) within gray matter (GM) and white matter (WM). The number of excitations (NEX) was optimized by considering DKI reliability. The influence of the partial volume effect (PVE) was also assessed.

STATISTICAL TEST

One-way analysis of variance.

RESULTS

The 30d-3b scheme, compared with the 6d-15b scheme, exhibited apparently smaller σ_FA and σ_MK (eg, at NEX 1, in GM, for three resolutions, σ_FA : 19.9-38.2% vs. 34.2-61.4%, σ_MK : 6.9-11.4% vs. 14.1-15.4%) and similar σ_MD (all differences between two schemes <1.6%). The optimal NEX was determined as 2 for enabling a reliable measurement of DKI-derived indices. The PVE at the lowest resolution apparently increased σ_FA for both schemes (19.9% for 30d-3b and 34.2% for 6d-15b) and σ_MK for the 6d-15b scheme (14.7%) in GM, and exerted lower effects on MK values for the 30d-3b scheme (P > 0.05).

DATA CONCLUSION

A higher number of diffusion directions would benefit FA and MK estimation. A higher spatial resolution helps to reduce PVE. By using the 30d-3b scheme, MK is considered a robust index to reflect microstructural changes in GM and WM. We propose a systematic approach to determine the optimal DKI protocols for appropriate preclinical settings.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1593-1603.

Tensor-valued diffusion encoding for diffusional variance decomposition (DIVIDE): Technical feasibility in clinical MRI systems

Microstructure imaging techniques based on tensor-valued diffusion encoding have gained popularity within the MRI research community. Unlike conventional diffusion encoding-applied along a single direction in each shot-tensor-valued encoding employs diffusion encoding along multiple directions within a single preparation of the signal. The benefit is that such encoding may probe tissue features that are not accessible by conventional encoding. For example, diffusional variance decomposition (DIVIDE) takes advantage of tensor-valued encoding to probe microscopic diffusion anisotropy independent of orientation coherence. The drawback is that tensor-valued encoding generally requires gradient waveforms that are more demanding on hardware; it has therefore been used primarily in MRI systems with relatively high performance. The purpose of this work was to explore tensor-valued diffusion encoding on clinical MRI systems with varying performance to test its technical feasibility within the context of DIVIDE. We performed whole-brain imaging with linear and spherical b-tensor encoding at field strengths between 1.5 and 7 T, and at maximal gradient amplitudes between 45 and 80 mT/m. Asymmetric gradient waveforms were optimized numerically to yield b-values up to 2 ms/μm2. Technical feasibility was assessed in terms of the repeatability, SNR, and quality of DIVIDE parameter maps. Variable system performance resulted in echo times between 83 to 115 ms and total acquisition times of 6 to 9 minutes when using 80 signal samples and resolution 2×2×4 mm3. As expected, the repeatability, signal-to-noise ratio and parameter map quality depended on hardware performance. We conclude that tensor-valued encoding is feasible for a wide range of MRI systems-even at 1.5 T with maximal gradient waveform amplitudes of 33 mT/m-and baseline experimental design and quality parameters for all included configurations. This demonstrates that tissue features, beyond those accessible by conventional diffusion encoding, can be explored on a wide range of MRI systems.

Spin echo based cardiac diffusion imaging at 7T: An ex vivo study of the porcine heart at 7T and 3T

Purpose of this work was to assess feasibility of cardiac diffusion tensor imaging (cDTI) at 7 T in a set of healthy, unfixed, porcine hearts using various parallel imaging acceleration factors and to compare SNR and derived cDTI metrics to a reference measured at 3 T. Magnetic resonance imaging was performed on 7T and 3T whole body systems using a spin echo diffusion encoding sequence with echo planar imaging readout. Five reference (b = 0 s/mm2) images and 30 diffusion directions (b = 700 s/mm2) were acquired at both 7 T and 3 T using a GRAPPA acceleration factor R = 1. Scans at 7 T were repeated using R = 2, R = 3, and R = 4. SNR evaluation was based on 30 reference (b = 0 s/mm2) images of 30 slices of the left ventricle and cardiac DTI metrics were compared within AHA segmentation. The number of hearts scanned at 7 T and 3 T was n = 11. No statistically significant differences were found for evaluated helix angle, secondary eigenvector angle, fractional anisotropy and apparent diffusion coefficient at the different field strengths, given sufficiently high SNR and geometrically undistorted images. R≥3 was needed to reduce susceptibility induced geometric distortions to an acceptable amount. On average SNR in myocardium of the left ventricle was increased from 29±3 to 44±6 in the reference image (b = 0 s/mm2) when switching from 3 T to 7 T. Our study demonstrates that high resolution, ex vivo cDTI is feasible at 7 T using commercial hardware.

A novel voxel-wise lesion segmentation technique on 3.0-T diffusion MRI of hyperacute focal cerebral ischemia at 1 h after permanent MCAO in rats

To assess hyperacute focal cerebral ischemia in rats on 3.0-Tesla diffusion-weighted imaging (DWI), we developed a novel voxel-wise lesion segmentation technique that overcomes intra- and inter-subject variation in apparent diffusion coefficient (ADC) distribution. Our novel technique involves the following: (1) intensity normalization including determination of the optimal type of region of interest (ROI) and its intra- and inter-subject validation, (2) verification of focal cerebral ischemic lesions at 1 h with gross and high-magnification light microscopy of hematoxylin-eosin (H&E) pathology, (3) voxel-wise segmentation on ADC with various thresholds, and (4) calculation of dice indices (DIs) to compare focal cerebral ischemic lesions at 1 h defined by ADC and matching H&E pathology. The best coefficient of variation was the mode of the left hemisphere after normalization using whole left hemispheric ROI, which showed lower intra- (2.54 ± 0.72%) and inter-subject (2.67 ± 0.70%) values than the original. Focal ischemic lesion at 1 h after middle cerebral artery occlusion (MCAO) was confirmed on both gross and microscopic H&E pathology. The 83 relative threshold of normalized ADC showed the highest mean DI (DI = 0.820 ± 0.075). We could evaluate hyperacute ischemic lesions at 1 h more reliably on 3-Tesla DWI in rat brains.

White matter connectivity between occipital and temporal regions involved in face and voice processing in hearing and early deaf individuals

Neuroplasticity following sensory deprivation has long inspired neuroscience research in the quest of understanding how sensory experience and genetics interact in developing the brain functional and structural architecture. Many studies have shown that sensory deprivation can lead to cross-modal functional recruitment of sensory deprived cortices. Little is known however about how structural reorganization may support these functional changes. In this study, we examined early deaf, hearing signer and hearing non-signer individuals using diffusion MRI to evaluate the potential structural connectivity linked to the functional recruitment of the temporal voice area by face stimuli in deaf individuals. More specifically, we characterized the structural connectivity between occipital, fusiform and temporal regions typically supporting voice- and face-selective processing. Despite the extensive functional reorganization for face processing in the temporal cortex of the deaf, macroscopic properties of these connections did not differ across groups. However, both occipito- and fusiform-temporal connections showed significant microstructural changes between groups (fractional anisotropy reduction, radial diffusivity increase). We propose that the reorganization of temporal regions after early auditory deprivation builds on intrinsic and mainly preserved anatomical connectivity between functionally specific temporal and occipital regions.

Disrupted development and integrity of frontal white matter in patients treated for pediatric medulloblastoma

Background

Treatment of pediatric medulloblastoma is associated with known neurocognitive deficits that we hypothesize are caused by microstructural damage to frontal white matter (WM).

Methods

Longitudinal MRI examinations were collected from baseline (after surgery but before therapy) to 36 months in 146 patients and at 3 time points in 72 controls. Regional analyses of frontal WM volume and diffusion tensor imaging metrics were performed and verified with tract-based spatial statistics. Age-adjusted, linear mixed-effects models were used to compare patient and control images and to associate imaging changes with Woodcock-Johnson Tests of Cognitive Abilities.

Results

At baseline, WM volumes in patients were similar to those in controls; fractional anisotropy (FA) was lower bilaterally (P < 0.001) and was associated with decreased Processing Speed (P = 0.014) and Broad Attention (P = 0.025) performance at 36 months. During follow-up, WM volumes increased in controls but decreased in patients (P < 0.001) bilaterally. Smaller WM volumes in patients at 36 months were associated with concurrent decreased Working Memory (P = 0.026) performance.

Conclusions

Lower FA in patients with pediatric medulloblastoma compared with age-similar controls indicated that patients suffer substantial acute microstructural damage to supratentorial frontal WM following surgery but before radiation therapy or chemotherapy. Additionally, this damage to the frontal WM was associated with decreased cognitive performance in executive function 36 months later. This early damage also likely contributed to posttherapeutic failure of age-appropriate WM development and to the known association between decreased WM volumes and decreased cognitive performance.

Diffusion tensor imaging in the musculoskeletal and peripheral nerve systems: from experimental to clinical applications

Magnetic resonance imaging (MRI) is a well-established imaging modality which is used in all districts of the musculoskeletal and peripheral nerve systems. More recently, initial studies have applied multiparametric MRI to evaluate quantitatively different aspects of musculoskeletal and peripheral nerve diseases, thus providing not only images but also numbers and clinical data. Besides ¹H and ³¹P magnetic resonance spectroscopy, diffusion-weighted imaging (DWI) and blood oxygenation level-dependent imaging, diffusion tensor imaging (DTI) is a relatively new MRI-based technique relying on principles of DWI, which has traditionally been used mainly for evaluating the central nervous system to track fibre course. In the musculoskeletal and peripheral nerve systems, DTI has been mostly used in experimental settings, with still few indications in clinical practice. In this review, we describe the potential use of DTI to evaluate different musculoskeletal and peripheral nerve conditions, emphasising the translational aspects of this technique from the experimental to the clinical setting.

Diffusion MRI of the human brain at ultra-high field (UHF): A review

The continued drive towards MRI scanners operating at increasingly higher main magnetic fields is primarily motivated by the maxim that more teslas mean more signal and lead to better images. This promise of increased signal, which cannot easily be achieved in other ways, encourages efforts to overcome the inextricable technical challenges which accompany this endeavor. Unlike for many applications, however, diffusion imaging is not currently able to directly reap these potential signal gains - at the time of writing it seems fair to say that, for matched gradient and RF hardware, the majority of diffusion images acquired at 7T, while comparable in quality to those achievable at 3T, do not demonstrate a clear advantage over what can be obtained at lower field. This does not mean that diffusion imaging at UHF is not a worthwhile pursuit - but more a reflection of the fact that the associated challenges are manifold - and converting the potential of higher field strengths into 'better' diffusion imaging is by no means a straightforward task. This article attempts to summarize the specific reasons that make diffusion imaging at UHF more complicated than one might expect, and to highlight the range of developments that have already been made which have enabled diffusion images of excellent quality to be acquired at 7T.

Comparison of Diffusion Metrics Obtained at 1.5T and 3T in Human Brain With Diffusional Kurtosis Imaging

PURPOSE

To quantitatively compare diffusion metrics for human brain estimated with diffusional kurtosis imaging (DKI) at applied field strengths of 1.5 and 3T.

MATERIALS AND METHODS

DKI data for brain were acquired at both 1.5 and 3T from each of six healthy volunteers using a twice-refocused diffusion-weighted imaging sequence. From these data, parametric maps of mean diffusivity (MD), axial diffusivity (D_‖ ), radial diffusivity (D_⊥ ), fractional anisotropy (FA), mean diffusional kurtosis (MK), axial kurtosis (K_‖ ), radial kurtosis (K_⊥ ), and kurtosis fractional anisotropy (KFA) were estimated. Comparisons of the results from the two field strengths were made for each metric using both Bland-Altman plots and linear regression to calculate coefficients of determination (R² ) and best fit lines.

RESULTS

Diffusion metrics measured at 1.5 and 3T were observed to be similar. Linear regression of the full datasets had coefficients of determination varying from a low of R² = 0.86 for KFA to a high of R² = 0.97 for FA. The slopes of the 3T vs. 1.5T best linear fits varied from 0.881 ± 0.009 for KFA to 1.038 ± 0.010 for D_‖ . From a Bland-Altman analysis of selected regions of interest, the mean differences of the metrics for the two field strengths were all found to be less than 6%, except for KFA, which showed the largest relative discrepancy of 10%.

CONCLUSION

Diffusion metrics measured with DKI at 1.5 and 3T are strongly correlated and typically differ by only a few percent. The somewhat higher discrepancy for the KFA is argued to mainly reflect the effects of signal noise. This supports the robustness DKI results with respect to field strength.

LEVEL OF EVIDENCE

3 J. Magn. Reson. Imaging 2017;45:673-680.

Frontoparietal white matter integrity predicts haptic performance in chronic stroke

Frontoparietal white matter supports information transfer between brain areas involved in complex haptic tasks such as somatosensory discrimination. The purpose of this study was to gain an understanding of the relationship between microstructural integrity of frontoparietal network white matter and haptic performance in persons with chronic stroke and to compare frontoparietal network integrity in participants with stroke and age matched control participants. Nineteen individuals with stroke and 16 controls participated. Haptic performance was quantified using the Hand Active Sensation Test (HASTe), an 18-item match-to-sample test of weight and texture discrimination. Three tesla MRI was used to obtain diffusion-weighted and high-resolution anatomical images of the whole brain. Probabilistic tractography was used to define 10 frontoparietal tracts total; Four intrahemispheric tracts measured bilaterally 1) thalamus to primary somatosensory cortex (T–S1), 2) thalamus to primary motor cortex (T–M1), 3) primary to secondary somatosensory cortex (S1 to SII) and 4) primary somatosensory cortex to middle frontal gyrus (S1 to MFG) and, 2 interhemispheric tracts; S1–S1 and precuneus interhemispheric. A control tract outside the network, the cuneus interhemispheric tract, was also examined. The diffusion metrics fractional anisotropy (FA), mean diffusivity (MD), axial (AD) and radial diffusivity (RD) were quantified for each tract. Diminished FA and elevated MD values are associated with poorer white matter integrity in chronic stroke. Nine of 10 tracts quantified in the frontoparietal network had diminished structural integrity poststroke compared to the controls. The precuneus interhemispheric tract was not significantly different between groups. Principle component analysis across all frontoparietal white matter tract MD values indicated a single factor explained 47% and 57% of the variance in tract mean diffusivity in stroke and control groups respectively. Age strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T–M1 MD and affected hand HASTe score (r = − 0.62, p = 0.006) and less affected hand HASTe score (r = − 0.53, p = 0.022). Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD) in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T–M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

•

Poststroke participants had a wide range of haptic performance, the majority were impaired.

•

A good relationship was found between ipsilesional Thal–M1 integrity and poststroke haptics.

•

Around 90% of haptic performance was predicted by frontoparietal white matter integrity.

•

Precuneus interhemispheric tract integrity was a strong predictor of haptic performance.

•

Diminished integrity across the frontoparietal network suggests a general stroke-related factor.

Optimized radiofrequency coil setup for MR examination of living isolated rat hearts in a horizontal 9.4T magnet

PURPOSE

(i) To optimize an MR-compatible organ perfusion setup for the nondestructive investigation of isolated rat hearts by placing the radiofrequency (RF) coil inside the perfusion chamber; (ii) to characterize the benefit of this system for diffusion tensor imaging and proton ((1) H-) MR spectroscopy.

METHODS

Coil quality assessment was conducted both on the bench, and in the magnet. The benefit of the new RF-coil was quantified by measuring signal-to-noise ratio (SNR), accuracy, and precision of diffusion tensor imaging/error in metabolite amplitude estimation, and compared to an RF-coil placed externally to the perfusion chamber.

RESULTS

The new design provided a 59% gain in signal-to-noise ratio on a fixed rat heart compared to using an external resonator, which found reflection in an improvement of living heart data quality, compared to previous external resonator studies. This resulted in 14-29% improvement in accuracy and precision of diffusion tensor imaging. The Cramer-Rao lower bounds for metabolite amplitude estimations were up to 5-fold smaller.

CONCLUSION

Optimization of MR-compatible perfusion equipment advances the study of rat hearts with improved signal-to-noise ratio performance, and thus improved accuracy/precision.

Regional vulnerability of hippocampal subfields to aging measured by structural and diffusion MRI

In the past few years, there has been an increasing awareness of the regional vulnerability of the hippocampus to age-related processes. However, to date, no studies have assessed the effects of age on different structural magnetic resonance parameters in the specific hippocampal subfields. In this study, we measured volume, mean diffusivity (MD) and fractional anisotropy (FA) in the presubiculum, subiculum, fimbria, cornu ammonis (CA) 1,2-3,4-DG and the whole hippocampus in fifty cognitively intact elder adults between 50 and 75 years of age (20 men, 30 women). Segmentation of hippocampal subfields was performed using FreeSurfer. Individual MD and FA images were coregistered to T1-weighted volumes using FLIRT of FSL. Linear regression analyses were performed to assess the effects of age on the anatomical measures of each subfield. In addition, multiple regression analyses were also carried out to assess which of the anatomical measures that showed a correlation with age in the previous analyses, were the best age predictors in the hippocampus. In agreement with previous studies, our results showed a significant association between age and volume (P < 0.001) as well as MD (P < 0.001) in the whole hippocampus. Regarding the specific hippocampal subfields, we found that age had a significant negative effect on volume in CA2-3 (P < 0.001) and CA4-DG (P < 0.001). Importantly, we found a positive effect of age on MD in CA2-3 (P < 0.001) and fimbria (P < 0.001) as well as a negative age effect on FA in the subiculum (P < 0.001). Multiple regression analyses revealed that the best overall predictors of age in the hippocampus were MD in the fimbria and volume of CA2-3, which explained 73.8% of the age variance. These results indicate that age has an effect both on volume and diffusion tensor imaging measures in different subfields, suggesting they provide complementary information on age-related processes in the hippocampus.

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

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

Localized high-resolution DTI of the human midbrain using single-shot EPI, parallel imaging, and outer-volume suppression at 7T

Localized high-resolution diffusion tensor images (DTI) from the midbrain were obtained using reduced field-of-view (rFOV) methods combined with SENSE parallel imaging and single-shot echo planar (EPI) acquisitions at 7T. This combination aimed to diminish sensitivities of DTI to motion, susceptibility variations, and EPI artifacts at ultra-high field. Outer-volume suppression (OVS) was applied in DTI acquisitions at 2- and 1-mm(2) resolutions, b=1000s/mm(2), and six diffusion directions, resulting in scans of 7- and 14-min durations. Mean apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured in various fiber tract locations at the two resolutions and compared. Geometric distortion and signal-to-noise ratio (SNR) were additionally measured and compared for reduced-FOV and full-FOV DTI scans. Up to an eight-fold data reduction was achieved using DTI-OVS with SENSE at 1mm(2), and geometric distortion was halved. The localization of fiber tracts was improved, enabling targeted FA and ADC measurements. Significant differences in diffusion properties were observed between resolutions for a number of regions suggesting that FA values are impacted by partial volume effects even at a 2-mm(2) resolution. The combined SENSE DTI-OVS approach allows large reductions in DTI data acquisition and provides improved quality for high-resolution diffusion studies of the human brain.

A hitchhiker's guide to diffusion tensor imaging

Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.

Functional imaging of head and neck squamous cell carcinoma with diffusion-weighted MRI and FDG PET/CT: quantitative analysis of ADC and SUV

Purpose

Head and neck squamous cell carcinoma (HNSCC) may cause a decreased apparent diffusion coefficient (ADC) on diffusion-weighted magnetic resonance imaging (DW MRI) and an increased standardized uptake value (SUV) on fluorodeoxyglucose (FDG) positron emission tomography (PET/CT). We analysed the reproducibility of ADC and SUV measurements in HNSCC and evaluated whether these biomarkers are correlated or independent.

Methods

This retrospective analysis of DW MRI and FDG PET/CT data series included 34 HNSCC in 33 consecutive patients. Two experienced readers measured tumour ADC and SUV values independently. Statistical comparison and correlation with histopathology was done. Intra- and inter-observer agreement for ADC and SUV measurements was assessed.

Results

Intraclass correlation coefficient (ICC) analysis showed almost perfect reproducibility (>0.90) for ADC_mean, ADC_min, SUV_max and SUV_mean values for intra-observer and inter-observer agreement. Mean ADC_mean and ADC_min in HNSCC were 1.05 ± 0.34 × 10⁻³ mm²/s and 0.65 ± 0.29 × 10⁻³ mm²/s, respectively. Mean SUV_mean and mean SUV_max were 7.61 ± 3.87 and 12.8 ± 5.0, respectively. Although statistically not significant, a trend towards higher SUV and lower ADC was observed with increasing tumour dedifferentiation. Pearson’s correlation analysis showed no significant correlation between ADC and SUV measurements (r −0.103, −0.051; p 0.552, 0.777).

Conclusion

Our data suggest that ADC and SUV values are reproducible and independent biomarkers in HNSCC.

Functional imaging of head and neck squamous cell carcinoma with diffusion-weighted MRI and FDG PET/CT: quantitative analysis of ADC and SUV

PURPOSE

Head and neck squamous cell carcinoma (HNSCC) may cause a decreased apparent diffusion coefficient (ADC) on diffusion-weighted magnetic resonance imaging (DW MRI) and an increased standardized uptake value (SUV) on fluorodeoxyglucose (FDG) positron emission tomography (PET/CT). We analysed the reproducibility of ADC and SUV measurements in HNSCC and evaluated whether these biomarkers are correlated or independent.

METHODS

This retrospective analysis of DW MRI and FDG PET/CT data series included 34 HNSCC in 33 consecutive patients. Two experienced readers measured tumour ADC and SUV values independently. Statistical comparison and correlation with histopathology was done. Intra- and inter-observer agreement for ADC and SUV measurements was assessed.

RESULTS

Intraclass correlation coefficient (ICC) analysis showed almost perfect reproducibility (>0.90) for ADCmean, ADCmin, SUVmax and SUVmean values for intra-observer and inter-observer agreement. Mean ADCmean and ADCmin in HNSCC were 1.05 ± 0.34 × 10(-3) mm(2)/s and 0.65 ± 0.29 × 10(-3) mm(2)/s, respectively. Mean SUVmean and mean SUVmax were 7.61 ± 3.87 and 12.8 ± 5.0, respectively. Although statistically not significant, a trend towards higher SUV and lower ADC was observed with increasing tumour dedifferentiation. Pearson's correlation analysis showed no significant correlation between ADC and SUV measurements (r -0.103, -0.051; p 0.552, 0.777).

CONCLUSION

Our data suggest that ADC and SUV values are reproducible and independent biomarkers in HNSCC.

Magnetic resonance field strength effects on diffusion measures and brain connectivity networks

The quest to map brain connectivity is being pursued worldwide using diffusion imaging, among other techniques. Even so, we know little about how brain connectivity measures depend on the magnetic field strength of the scanner. To investigate this, we scanned 10 healthy subjects at 7 and 3 tesla-using 128-gradient high-angular resolution diffusion imaging. For each subject and scan, whole-brain tractography was used to estimate connectivity between 113 cortical and subcortical regions. We examined how scanner field strength affects (i) the signal-to-noise ratio (SNR) of the non-diffusion-sensitized reference images (b(0)); (ii) diffusion tensor imaging (DTI)-derived fractional anisotropy (FA), mean, radial, and axial diffusivity (MD/RD/AD), in atlas-defined regions; (iii) whole-brain tractography; (iv) the 113 × 113 brain connectivity maps; and (v) five commonly used network topology measures. We also assessed effects of the multi-channel reconstruction methods (sum-of-squares, SOS, at 7T; adaptive recombine, AC, at 3T). At 7T with SOS, the b0 images had 18.3% higher SNR than with 3T-AC. FA was similar for most regions of interest (ROIs) derived from an online DTI atlas (ICBM81), but higher at 7T in the cerebral peduncle and internal capsule. MD, AD, and RD were lower at 7T for most ROIs. The apparent fiber density between some subcortical regions was greater at 7T-SOS than 3T-AC, with a consistent connection pattern overall. Suggesting the need for caution, the recovered brain network was apparently more efficient at 7T, which cannot be biologically true as the same subjects were assessed. Care is needed when comparing network measures across studies, and when interpreting apparently discrepant findings.