Diffusion abnormalities in temporal lobes of children with temporal lobe epilepsy: a preliminary diffusional kurtosis imaging study and comparison with diffusion tensor imaging

In this preliminary study, we aimed to investigate the abnormalities of water diffusion in children with temporal lobe epilepsy (TLE). Eight children with unilateral TLE (according to electroencephalography, EEG) and eight age‐ and sex‐matched controls were recruited. Diffusion tensor imaging (DTI)/diffusional kurtosis imaging (DKI) acquisitions were performed. Radial diffusivity (λ_⊥), axial diffusivity (λ_∥), mean diffusivity (MD) and fractional anisotropy (FA) maps were calculated for both DTI and DKI, and radial kurtosis (K_⊥), axial kurtosis (K_∥) and mean kurtosis (MK) maps were calculated for DKI only. Mann–Whitney test showed that, for white matter in the temporal lobe, DKI‐derived λ_∥, MD and K_∥ were significantly different in bilateral temporal lobes and EEG‐abnormal and EEG‐normal sides of the temporal lobe between patients and controls, whereas DTI showed no abnormalities. For gray matter, DKI detected significantly higher MD and MK in the same three comparisons, whereas DTI detected abnormalities only in the comparison between bilateral temporal lobes and between EEG‐normal sides in cases and left–right matched sides in controls. No significant difference was observed between EEG‐abnormal and EEG‐normal sides in cases. These preliminary results indicate that DKI is more sensitive than DTI for the detection of diffusion abnormalities in the temporal lobes of children with TLE, even when EEG signals are normal. These findings pave the way for the application of DKI for in‐depth studies on TLE in children. Copyright © 2012 John Wiley & Sons, Ltd.     

Fast diffusion kurtosis imaging (DKI) with Inherent COrrelation‐based Normalization (ICON) enhances automatic segmentation of heterogeneous diffusion MRI lesion in acute stroke

Diffusion kurtosis imaging (DKI) has been shown to augment diffusion‐weighted imaging (DWI) for the definition of irreversible ischemic injury. However, the complexity of cerebral structure/composition makes the kurtosis map heterogeneous, limiting the specificity of kurtosis hyperintensity to acute ischemia. We propose an Inherent COrrelation‐based Normalization (ICON) analysis to suppress the intrinsic kurtosis heterogeneity for improved characterization of heterogeneous ischemic tissue injury. Fast DKI and relaxation measurements were performed on normal (n = 10) and stroke rats following middle cerebral artery occlusion (MCAO) (n = 20). We evaluated the correlations between mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) derived from the fast DKI sequence and relaxation rates R₁ and R₂, and found a highly significant correlation between MK and R₁ (p < 0.001). We showed that ICON analysis suppressed the intrinsic kurtosis heterogeneity in normal cerebral tissue, enabling automated tissue segmentation in an animal stroke model. We found significantly different kurtosis and diffusivity lesion volumes: 147 ± 59 and 180 ± 66 mm³, respectively (p = 0.003, paired t‐test). The ratio of kurtosis to diffusivity lesion volume was 84% ± 19% (p < 0.001, one‐sample t‐test). We found that relaxation‐normalized MK (RNMK), but not MD, values were significantly different between kurtosis and diffusivity lesions (p < 0.001, analysis of variance). Our study showed that fast DKI with ICON analysis provides a promising means of demarcation of heterogeneous DWI stroke lesions.     

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

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

Reproducibility of tract‐specific magnetization transfer and diffusion tensor imaging in the cervical spinal cord at 3 tesla

Damage to specific white matter tracts within the spinal cord can often result in the particular neurological syndromes that characterize myelopathies such as traumatic spinal cord injury. Noninvasive visualization of these tracts with imaging techniques that are sensitive to microstructural integrity is an important clinical goal. Diffusion tensor imaging (DTI)‐ and magnetization transfer (MT)‐derived quantities have shown promise in assessing tissue health in the central nervous system. In this paper, we demonstrate that DTI of the cervical spinal cord can reliably discriminate sensory (dorsal) and motor (lateral) columns. From data derived from nine healthy volunteers, two raters quantified column‐specific parallel (λ_||) and perpendicular (λ_?) diffusivity, fractional anisotropy (FA), mean diffusivity (MD), and MT‐weighted signal intensity relative to cerebrospinal fluid (MTCSF) over two time‐points separated by more than 1 week. Cross‐sectional means and standard deviations of these measures in the lateral and dorsal columns were as follows: λ_||: 2.13 ± 0.14 and 2.14 ± 0.11 μm²/ms; λ_?: 0.67 ± 0.16 and 0.61 ± 0.09 μm²/ms; MD: 1.15 ± 0.15 and 1.12 ± 0.08 μm²/ms; FA: 0.68 ± 0.06 and 0.68 ± 0.05; MTCSF: 0.52 ± 0.05 and 0.50 ± 0.05. We examined the variability and interrater and test‐retest reliability for each metric. These column‐specific MR measurements are expected to enhance understanding of the intimate structure‐function relationship in the cervical spinal cord and may be useful for the assessment of disease progression. Copyright © 2009 John Wiley & Sons, Ltd.     

Comparison of image sensitivity between conventional tensor‐based and fast diffusion kurtosis imaging protocols in a rodent model of acute ischemic stroke

Diffusion kurtosis imaging (DKI) can offer a useful complementary tool to routine diffusion MRI for improved stratification of heterogeneous tissue damage in acute ischemic stroke. However, its relatively long imaging time has hampered its clinical application in the emergency setting. A recently proposed fast DKI approach substantially shortens the imaging time, which may help to overcome the scan time limitation. However, to date, the sensitivity of the fast DKI protocol for the imaging of acute stroke has not been fully described. In this study, we performed routine and fast DKI scans in a rodent model of acute stroke, and compared the sensitivity of diffusivity and kurtosis indices (i.e. axial, radial and mean) in depicting acute ischemic lesions. In addition, we analyzed the contrast‐to‐noise ratio (CNR) between the ipsilateral ischemic and contralateral normal regions using both conventional and fast DKI methods. We found that the mean kurtosis shows a relative change of 47.1 ± 7.3% between the ischemic and contralateral normal regions, being the most sensitive parameter in revealing acute ischemic injury. The two DKI methods yielded highly correlated diffusivity and kurtosis measures and lesion volumes (R² ? 0.90, p < 0.01). Importantly, the fast DKI method exhibited significantly higher CNR of mean kurtosis (1.6 ± 0.2) compared with the routine tensor protocol (1.3 ± 0.2, p < 0.05), with its CNR per unit time (CNR efficiency) approximately doubled when the scan time was taken into account. In conclusion, the fast DKI method provides excellent sensitivity and efficiency to image acute ischemic tissue damage, which is essential for image‐guided and individualized stroke treatment. Copyright © 2016 John Wiley & Sons, Ltd.     

Measuring healthy female nulliparous pubovisceral muscle from diffusion kurtosis imaging

This study explores the feasibility of using diffusion kurtosis imaging (DKI) in the pelvic floor region and assesses the water diffusivity of the pubovisceral muscle. Twenty-seven healthy young nulliparous females underwent DKI at 3.0 T that included 15 gradient directions and three b values (0, 750, and 1500 s/mm²). The diffusion tensor and diffusion kurtosis metrics values of the pubovisceral muscle were measured after image processing. Two independent sample t-tests, a paired-samples t-test, and a nonparametric hypothesis test were performed as appropriate to compare the differences among different metrics. Twenty-six subjects (mean ± standard deviation age, 25 ± 2 years) were successfully analyzed by measuring the diffusion tensor and diffusion kurtosis metrics of the bilateral pubovisceral muscles. The metrics included mean kurtosis, axial kurtosis, radial kurtosis, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. We found no statistically significant differences for these measurement values between the left and right pubovisceral muscles (p = 0.271–0.931). However, radial kurtosis was greater than axial kurtosis in both pubovisceral muscles (p < 0.001) and axial diffusivity was lower than radial diffusivity in both pubovisceral muscles (p < 0.001). We deem the application of DKI technology to the pelvic floor region to be feasible.     

High‐resolution diffusion tensor imaging of the human kidneys using a free‐breathing,multi‐slice,targeted field of view approach

Fractional anisotropy (FA) obtained by diffusion tensor imaging (DTI) can be used to image the kidneys without any contrast media. FA of the medulla has been shown to correlate with kidney function. It is expected that higher spatial resolution would improve the depiction of small structures within the kidney. However, the achievement of high spatial resolution in renal DTI remains challenging as a result of respiratory motion and susceptibility to diffusion imaging artefacts. In this study, a targeted field of view (TFOV) method was used to obtain high‐resolution FA maps and colour‐coded diffusion tensor orientations, together with measures of the medullary and cortical FA, in 12 healthy subjects. Subjects were scanned with two implementations (dual and single kidney) of a TFOV DTI method. DTI scans were performed during free breathing with a navigator‐triggered sequence. Results showed high consistency in the greyscale FA, colour‐coded FA and diffusion tensors across subjects and between dual‐ and single‐kidney scans, which have in‐plane voxel sizes of 2 × 2 mm² and 1.2 × 1.2 mm², respectively. The ability to acquire multiple contiguous slices allowed the medulla and cortical FA to be quantified over the entire kidney volume. The mean medulla and cortical FA values were 0.38 ± 0.017 and 0.21 ± 0.019, respectively, for the dual‐kidney scan, and 0.35 ± 0.032 and 0.20 ± 0.014, respectively, for the single‐kidney scan. The mean FA between the medulla and cortex was significantly different (p < 0.001) for both dual‐ and single‐kidney implementations. High‐spatial‐resolution DTI shows promise for improving the characterization and non‐invasive assessment of kidney function. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.     

Characterization of clear cell renal cell carcinoma with diffusion kurtosis imaging: correlation between diffusion kurtosis parameters and tumor cellularity

The aim of this study was to evaluate the role of diffusion kurtosis imaging (DKI) in the characterization of clear cell renal cell carcinoma (ccRCC) and to correlate DKI parameters with tumor cellularity. Fifty‐nine patients with pathologically diagnosed ccRCCs were evaluated by DKI on a 3‐T scanner. Regions of interest were drawn on the maps of the mean diffusion coefficient (MD) and mean diffusion kurtosis (MK). All ccRCCs were histologically graded according to the Fuhrman classification system. Tumor cellularity was measured by the nuclear‐to‐cytoplasm (N/C) ratio and the number of tumor cell nuclei (NTCN). ccRCCs were classified as grade 1 (n = 23), grade 2 (n = 24), grade 3 (n = 10) and grade 4 (n = 3). Both MD and MK could readily discriminate between normal renal parenchyma and ccRCCs (p < 0.001), and receiver operating characteristic (ROC) curve analysis showed that MK exhibited a better performance with an area under the ROC curve of 0.874 and sensitivity/specificity of 68.33%/100% (p < 0.001). Further, MD and MK were significantly different between grade 1 and grades 3 and 4 (p = 0.01, p < 0.001) and between grade 2 and grades 3 and 4 (p = 0.015, p < 0.005), respectively. However, no significant difference was found between grade 1 and grade 2 (p > 0.05) for both MD and MK. With regard to NTCN, no significant difference was found between any two grades (p > 0.05), and the N/C ratio changed significantly with grade (p < 0.01, between any two grades). Negative correlations were found between MK and MD (r = –0.56, p < 0.001), and between MD and N/C ratio (r = –0.36, p < 0.005), whereas MK and the N/C ratio were positively correlated (r = 0.45, p = 0.003). DKI could quantitatively characterize ccRCC with different grades by probing non‐Gaussian diffusion properties related to changes in the tumor microenvironment or tissue complexities in the tumor. Copyright © 2016 John Wiley & Sons, Ltd.     

Diffusion tensor imaging of renal ischemia reperfusion injury in an experimental model

Renal ischemia reperfusion injury (IRI) is a major cause of acute renal failure. It occurs in various clinical settings such as renal transplantation, shock and vascular surgery. Serum creatinine level has been used as an index for estimating the degree of renal functional loss in renal IRI. However, it only evaluates the global renal function. In this study, diffusion tensor imaging (DTI) was used to characterize renal IRI in an experimental rat model. Spin‐echo echo‐planar DTI with b‐value of 300 s/mm² and 6 diffusion gradient directions was performed at 7 T in 8 Sprague‐Dawley (SD) with 60‐min unilateral renal IRI and 8 normal SD rats. Apparent diffusion coefficient (ADC), directional diffusivities and fractional anisotropy (FA) were measured at the acute stage of IRI. The IR‐injured animals were also examined by diffusion‐weighted imaging with 7 b‐values up to 1000 s/mm² to estimate true diffusion coefficient (D_true) and perfusion fraction (P_fraction) using a bi‐compartmental model. ADC of injured renal cortex (1.69 ± 0.24 × 10^?3 mm²/s) was significantly lower (p < 0.01) than that of contralateral intact cortex (2.03 ± 0.35 × 10^?3 mm²/s). Meanwhile, both ADC and FA of IR‐injured medulla (1.37 ± 0.27 × 10^?3 mm²/s and 0.28 ± 0.04, respectively) were significantly less (p < 0.01) than those of contralateral intact medulla (2.01 ± 0.38 × 10^?3 mm²/s and 0.36 ± 0.04, respectively). The bi‐compartmental model analysis revealed the decrease in D_true and P_fraction in the IR‐injured kidneys. Kidney histology showed widespread cell swelling and erythrocyte congestion in both cortex and medulla, and cell necrosis/apoptosis and cast formation in medulla. These experimental findings demonstrated that DTI can probe both structural and functional information of kidneys following renal IRI. Copyright © 2010 John Wiley & Sons, Ltd.     

Diffusional kurtosis MRI of the lower leg: changes caused by passive muscle elongation and shortening

Diffusional kurtosis MRI (DKI) quantifies the deviation of water diffusion from a Gaussian distribution. We investigated the influence of passive elongation and shortening of the lower leg muscles on the DKI parameters D (diffusion coefficient) and K (kurtosis). After approval by the local ethics committee, eight healthy volunteers (age, 29.1 ± 2.9 years) underwent MRI of the lower leg at 3 T. Diffusion‐weighted images were acquired with 10 different b values at three ankle positions (passive dorsiflexion 10°, neutral position 0°, passive plantar flexion 40°). Parametrical maps of D and K were obtained by voxel‐wise fitting of the signal intensities using a non‐linear Levenberg–Marquardt algorithm. D and K were measured in the tibialis anterior, medial and lateral gastrocnemius, and soleus muscles. In the neutral position, D and K values were in the range between 1.66–1.79 × 10^–3 mm²/s and 0.21–0.39, respectively. D and K increased with passive shortening, and decreased with passive elongation, which could also be illustrated on the parametrical maps. In dorsiflexion, D (p < 0.01) and K (p = 0.036) were higher in the tibialis anterior than in the medial gastrocnemius. In plantar flexion, the opposite was found for K (p = 0.035). DKI parameters in the lower leg muscles are significantly influenced by the ankle joint position, indicating that the diffusion of water molecules in skeletal muscle deviates from a Gaussian distribution depending on muscle tonus. Copyright © 2016 John Wiley & Sons, Ltd.     

Validation of fast diffusion kurtosis MRI for imaging acute ischemia in a rodent model of stroke

Diffusion‐weighted imaging (DWI) captures ischemic tissue that is likely to infarct, and has become one of the most widely used acute stroke imaging techniques. Diffusion kurtosis imaging (DKI) has lately been postulated as a complementary MRI method to stratify the heterogeneously damaged DWI lesion. However, the conventional DKI acquisition time is relatively long, limiting its use in the acute stroke setting. Recently, a fast kurtosis mapping method has been demonstrated in fixed brains and control subjects. The fast DKI approach provides mean diffusion and kurtosis measurements under substantially reduced scan time, making it amenable to acute stroke imaging. Because it is not practical to obtain and compare different means of DKI to test whether the fast DKI method can reliably detect diffusion and kurtosis lesions in acute stroke patients, our study investigated its diagnostic value using an animal model of acute stroke, a critical step before fast DKI acquisition can be routinely applied in the acute stroke setting. We found significant correlation, per voxel, between the diffusion and kurtosis coefficients measured using the fast and conventional DKI protocols. In acute stroke rats, the two DKI methods yielded diffusion and kurtosis lesions that were in good agreement. Importantly, substantial kurtosis–diffusion lesion mismatch was observed using the conventional (26 ± 13%, P < 0.01) and fast DKI methods (23 ± 8%, P < 0.01). In addition, regression analysis showed that the kurtosis–diffusion lesion mismatches obtained using conventional and fast DKI methods were substantially correlated (R² = 0.57, P = 0.02). Our results confirmed that the recently proposed fast DKI method is capable of capturing heterogeneous diffusion and kurtosis lesions in acute ischemic stroke, and thus is suitable for translational applications in the acute stroke clinical setting. Copyright © 2014 John Wiley & Sons, Ltd.     

Diffusional kurtosis imaging and white matter microstructure modeling in a clinical study of major depressive disorder

Major depressive disorder (MDD) is a globally prevalent psychiatric disorder that results from disruption of multiple neural circuits involved in emotional regulation. Although previous studies using diffusion tensor imaging (DTI) found smaller values of fractional anisotropy (FA) in the white matter, predominantly in the frontal lobe, of patients with MDD, studies using diffusion kurtosis imaging (DKI) are scarce. Here, we used DKI whole‐brain analysis with tract‐based spatial statistics (TBSS) to investigate the brain microstructural abnormalities in MDD. Twenty‐six patients with MDD and 42 age‐ and sex‐matched control subjects were enrolled. To investigate the microstructural pathology underlying the observations in DKI, a compartment model analysis was conducted focusing on the corpus callosum. In TBSS, the patients with MDD showed significantly smaller values of FA in the genu and frontal portion of the body of the corpus callosum. The patients also had smaller values of mean kurtosis (MK) and radial kurtosis (RK), but MK and RK abnormalities were distributed more widely compared with FA, predominantly in the frontal lobe but also in the parietal, occipital, and temporal lobes. Within the callosum, the regions with smaller MK and RK were located more posteriorly than the region with smaller FA. Model analysis suggested significantly smaller values of intra‐neurite signal fraction in the body of the callosum and greater fiber dispersion in the genu, which were compatible with the existing literature of white matter pathology in MDD. Our results show that DKI is capable of demonstrating microstructural alterations in the brains of patients with MDD that cannot be fully depicted by conventional DTI. Though the issues of model validation and parameter estimation still remain, it is suggested that diffusion MRI combined with a biophysical model is a promising approach for investigation of the pathophysiology of MDD.     

Hierarchical non‐negative matrix factorization to characterize brain tumor heterogeneity using multi‐parametric MRI

Tissue characterization in brain tumors and, in particular, in high‐grade gliomas is challenging as a result of the co‐existence of several intra‐tumoral tissue types within the same region and the high spatial heterogeneity. This study presents a method for the detection of the relevant tumor substructures (i.e. viable tumor, necrosis and edema), which could be of added value for the diagnosis, treatment planning and follow‐up of individual patients. Twenty‐four patients with glioma [10 low‐grade gliomas (LGGs), 14 high‐grade gliomas (HGGs)] underwent a multi‐parametric MRI (MP‐MRI) scheme, including conventional MRI (cMRI), perfusion‐weighted imaging (PWI), diffusion kurtosis imaging (DKI) and short‐TE ¹H MRSI. MP‐MRI parameters were derived: T₂, T₁ + contrast, fluid‐attenuated inversion recovery (FLAIR), relative cerebral blood volume (rCBV), mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and the principal metabolites lipids (Lip), lactate (Lac), N‐acetyl‐aspartate (NAA), total choline (Cho), etc. Hierarchical non‐negative matrix factorization (hNMF) was applied to the MP‐MRI parameters, providing tissue characterization on a patient‐by‐patient and voxel‐by‐voxel basis. Tissue‐specific patterns were obtained and the spatial distribution of each tissue type was visualized by means of abundance maps. Dice scores were calculated by comparing tissue segmentation derived from hNMF with the manual segmentation by a radiologist. Correlation coefficients were calculated between each pathologic tissue source and the average feature vector within the corresponding tissue region. For the patients with HGG, mean Dice scores of 78%, 85% and 83% were obtained for viable tumor, the tumor core and the complete tumor region. The mean correlation coefficients were 0.91 for tumor, 0.97 for necrosis and 0.96 for edema. For the patients with LGG, a mean Dice score of 85% and mean correlation coefficient of 0.95 were found for the tumor region. hNMF was also applied to reduced MRI datasets, showing the added value of individual MRI modalities. Copyright © 2015 John Wiley & Sons, Ltd.     

Bilateral substantia nigra and pyramidal tract changes following experimental intracerebral hemorrhage: an MR diffusion tensor imaging study

The amelioration of secondary neurological damage is among the most important therapeutic goals for patients with intracerebral hemorrhage (ICH). Secondary injury of the ipsilateral substantia nigra (SN) and pyramidal tract (PY) is common after cerebral stroke. Such injury has been characterized previously by anatomical or diffusion MRI, but not in a comprehensive manner, and the knowledge regarding the contralateral changes is relatively poor. This study examined longitudinally both contralateral and ipsilateral SN and PY changes following experimental ICH with diffusion tensor imaging (DTI) and histology. ICH was induced in 14 Sprague‐Dawley rats by the infusion of collagenase into the right striatum. Four‐shot, spin‐echo, echo‐planar DTI was performed at 7 T with a b value of 1000 s/mm² and 30 diffusion gradient directions at 3.5 h and days 1, 3, 7, 14, 42 and 120 after ICH. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ_//) and radial diffusivity (λ_┴) were measured in SN and PY accordingly. Two to three rats were sacrificed at days 3, 7, 42 and 120 for histology. The contralateral SN showed an increase in λ_// with perivascular enlargement during the first 3 days after ICH. The ipsilateral SN showed increases in FA, λ_//, λ_┴ and MD at day 1, dramatic decreases at day 3 with neuronal degeneration and neuropil vacuolation, and subsequent gradual normalization. The contralateral PY showed diffusivity decreases at day 1. The ipsilateral PY showed early decreases and then late increases in MD and λ_┴, and continuously decreasing FA and λ_// with progressive axonal loss and demyelination. In summary, DTI revealed early bilateral changes in SN and PY following ICH. The evolution of the ipsilateral parameters correlated with the histological findings. In the ipsilateral PY, λ_// and λ_┴ changes indicated evolving and complex pathological processes underlying the monotonic FA decrease. These results support the use of quantitative multiparametric DTI for the evaluation of SN and PY injuries in clinical and preclinical investigations of ICH. Copyright © 2013 John Wiley & Sons, Ltd.     

Diffusion kurtosis imaging and log‐normal distribution function imaging enhance the visualisation of lesions in animal stroke models

In this work, we report a case study of a stroke model in animals using two methods of quantification of the deviations from Gaussian behaviour: diffusion kurtosis imaging (DKI) and log‐normal distribution function imaging (LNDFI). The affected regions were predominantly in grey rather than in white matter. The parameter maps were constructed for metrics quantifying the apparent diffusivity (evaluated from conventional diffusion tensor imaging, DKI and LNDFI) and for those quantifying the degree of deviations (mean kurtosis and a parameter σ characterising the width of the distribution). We showed that both DKI and LNDFI were able to dramatically enhance the visualisation of ischaemic lesions in comparison with conventional methods. The largest relative change in the affected versus healthy regions was observed in the mean kurtosis values. The average changes in the mean kurtosis and σ values in the lesions were a factor of two to three larger than the relative changes observed in the mean diffusivity. In conclusion, the applied methods promise valuable perspectives in the assessment of stroke. Copyright © 2012 John Wiley & Sons, Ltd.     

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

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

White matter organization in relation to upper limb motor control in healthy subjects: exploring the added value of diffusion kurtosis imaging

Diffusion tensor imaging (DTI) characterizes white matter (WM) microstructure. In many brain regions, however, the assumption that the diffusion probability distribution is Gaussian may be invalid, even at low b values. Recently, diffusion kurtosis imaging (DKI) was suggested to more accurately estimate this distribution. We explored the added value of DKI in studying the relation between WM microstructure and upper limb coordination in healthy controls (N = 24). Performance on a complex bimanual tracking task was studied with respect to the conventional DTI measures (DKI or DTI derived) and kurtosis metrics of WM tracts/regions carrying efferent (motor) output from the brain, corpus callosum (CC) substructures and whole brain WM. For both estimation models, motor performance was associated with fractional anisotropy (FA) of the CC-genu, CC-body, the anterior limb of the internal capsule, and whole brain WM (r _s range 0.42–0.63). Although DKI revealed higher mean, radial and axial diffusivity and lower FA than DTI (p < 0.001), the correlation coefficients were comparable. Finally, better motor performance was associated with increased mean and radial kurtosis and kurtosis anisotropy (r _s range 0.43–0.55). In conclusion, DKI provided additional information, but did not show increased sensitivity to detect relations between WM microstructure and bimanual performance in healthy controls.     

扩散峰度成像在预测直肠癌KRAS基因突变中的应用价值

目的 探讨扩散峰度成像(DKI)定量参数在预测直肠癌KRAS基因突变中的应用价值。方法 回顾性分析山西省肿瘤医院2016年11月-2018年6月经病理证实的152例直肠腺癌患者的资料,其中男92例,女60例;年龄33～86岁,平均61岁。患者均于术前行常规MRI和功能DKI序列检查,由2名放射科医师双盲勾画感兴趣区,应用MatLab软件计算两组患者DKI定量参数平均表观扩散系数(MD)、平均峰度(MK)以及表观扩散系数(ADC),并采用组内相关系数进行一致性分析。术后均进行KRAS基因检测,依据检测结果将患者分为野生组和突变组两组,采用独立样本t检验对比两组患者的MD、MK、ADC。绘制DKI定量参数诊断KRAS基因突变的受试者工作特征曲线(ROC) ,根据约登指数确定各定量参数的最佳诊断阈值,以及相应的灵敏度、特异度,并采用DeLong检验比较各定量参数的ROC的曲线下面积(AUC)。结果 152例直肠癌患者中,KRAS基因突变组74例,野生组78例,基因突变率为48.6%(74/152)。突变组患者的ADC、MD、MK值分别为(1.18±0.18)×10^-3 mm²/s、(1.28±0.18)×10^-3 mm²/s、0.97±0.11,野生组分别为(1.33±0.18)×10^-3 mm²/s、(1.42±0.17)×10^-3 mm²/s、0.82±0.09;突变组ADC、MD值均小于野生组患者,而MK值则大于野生组患者,差异均有统计学意义(t=5.424、4.882、-8.809, P值均＜0.01)。ROC曲线显示,ADC、MD、和MK值预测KRAS基因的AUC分别为0.758、0.740、0.845,灵敏度分别为75.7%、82.4%、77.0%,特异度分别为68.0%、57.8%、84.6%。DeLong检验结果显示,MK值的AUC明显高于ADC和MD值(P值均＜0.01),而ADC值和MD值间AUC差异无统计学意义(P＞0.05)。结论 DKI定量参数MD、MK和ADC值,在预测直肠癌的KRAS基因突变方面均有一定的价值,其中MK值有更高的AUC和特异度,有更高的诊断价值。     

Multi‐centre reproducibility of diffusion MRI parameters for clinical sequences in the brain

The purpose of this work was to assess the reproducibility of diffusion imaging, and in particular the apparent diffusion coefficient (ADC), intra‐voxel incoherent motion (IVIM) parameters and diffusion tensor imaging (DTI) parameters, across multiple centres using clinically available protocols with limited harmonization between sequences. An ice–water phantom and nine healthy volunteers were scanned across fives centres on eight scanners (four Siemens 1.5T, four Philips 3T). The mean ADC, IVIM parameters (diffusion coefficient D and perfusion fraction f) and DTI parameters (mean diffusivity MD and fractional anisotropy FA), were measured in grey matter, white matter and specific brain sub‐regions. A mixed effect model was used to measure the intra‐ and inter‐scanner coefficient of variation (CV) for each of the five parameters. ADC, D, MD and FA had a good intra‐ and inter‐scanner reproducibility in both grey and white matter, with a CV ranging between 1% and 7.4%; mean 2.6%. Other brain regions also showed high levels of reproducibility except for small structures such as the choroid plexus. The IVIM parameter f had a higher intra‐scanner CV of 8.4% and inter‐scanner CV of 24.8%. No major difference in the inter‐scanner CV for ADC, D, MD and FA was observed when analysing the 1.5T and 3T scanners separately. ADC, D, MD and FA all showed good intra‐scanner reproducibility, with the inter‐scanner reproducibility being comparable or faring slightly worse, suggesting that using data from multiple scanners does not have an adverse effect compared with using data from the same scanner. The IVIM parameter f had a poorer inter‐scanner CV when scanners of different field strengths were combined, and the parameter was also affected by the scan acquisition resolution. This study shows that the majority of diffusion MRI derived parameters are robust across 1.5T and 3T scanners and suitable for use in multi‐centre clinical studies and trials. © 2015 The Authors NMR in Biomedicine Published by John Wiley & Sons Ltd.