Physics, Techniques and Review of Neuroradiological Applications of Diffusion Kurtosis Imaging (DKI)

Calculation of intravoxel incoherent motion parameter maps using a kernelized total difference-based method

Quantitative analysis of diffusion-weighted magnetic resonance imaging (DW-MRI) has been explored for many clinical applications since its development. In particular, the intravoxel incoherent motion (IVIM) model for DW-MRI has been commonly utilized in various organs. However, because of the presence of excessive noise, the IVIM parameter maps obtained from pixel-wise fitting are often unreliable. In this study, we propose a kernelized total difference-based curve-fitting method to estimate the IVIM parameters. Simulated DW-MRI data at five signal-to-noise ratios (i.e., 10, 20, 30, 50, and 100) and real abdominal DW-MRI data acquired on a 1.5-T MRI scanner with nine b-values (i.e., 0, 10, 25, 50, 100, 200, 300, 400, and 500 s/mm2) and six diffusion-encoding gradient directions were used to evaluate the performance of the proposed method. The results were compared with those obtained by three existing methods: trust-region reflective (TRR) algorithm, Bayesian probability (BP), and deep neural network (DNN). Our simulation results showed that the proposed method outperformed the other three comparing methods in terms of root-mean-square error. Moreover, the proposed method could preserve small details in the estimated IVIM parameter maps. The experimental results showed that, compared with the TRR method, the proposed method as well as the BP (and DNN) method could reduce the overestimation of the pseudodiffusion coefficient and improve the quality of IVIM parameter maps. For all studied abdominal organs except the pancreas, both the proposed method and the BP method could provide IVIM parameter estimates close to the reference values; the former had higher precision. The kernelized total difference-based curve-fitting method has the potential to improve the reliability of IVIM parametric imaging.

Diffusion Correction in Fricke Hydrogel Dosimeters: A Deep Learning Approach with 2D and 3D Physics-Informed Neural Network Models

In this work an innovative approach was developed to address a significant challenge in the field of radiation dosimetry: the accurate measurement of spatial dose distributions using Fricke gel dosimeters. Hydrogels are widely used in radiation dosimetry due to their ability to simulate the tissue-equivalent properties of human tissue, making them ideal for measuring and mapping radiation dose distributions. Among the various gel dosimeters, Fricke gels exploit the radiation-induced oxidation of ferrous ions to ferric ions and are particularly notable due to their sensitivity. The concentration of ferric ions can be measured using various techniques, including magnetic resonance imaging (MRI) or spectrophotometry. While Fricke gels offer several advantages, a significant hurdle to their widespread application is the diffusion of ferric ions within the gel matrix. This phenomenon leads to a blurring of the dose distribution over time, compromising the accuracy of dose measurements. To mitigate the issue of ferric ion diffusion, researchers have explored various strategies such as the incorporation of additives or modification of the gel composition to either reduce the mobility of ferric ions or stabilize the gel matrix. The computational method proposed leverages the power of artificial intelligence, particularly deep learning, to mitigate the effects of ferric ion diffusion that can compromise measurement precision. By employing Physics Informed Neural Networks (PINNs), the method introduces a novel way to apply physical laws directly within the learning process, optimizing the network to adhere to the principles governing ion diffusion. This is particularly advantageous for solving the partial differential equations that describe the diffusion process in 2D and 3D. By inputting the spatial distribution of ferric ions at a given time, along with boundary conditions and the diffusion coefficient, the model can backtrack to accurately reconstruct the original ion distribution. This capability is crucial for enhancing the fidelity of 3D spatial dose measurements, ensuring that the data reflect the true dose distribution without the artifacts introduced by ion migration. Here, multidimensional models able to handle 2D and 3D data were developed and tested against dose distributions numerically evolved in time from 20 to 100 h. The results in terms of various metrics show a significant agreement in both 2D and 3D dose distributions. In particular, the mean square error of the prediction spans the range 1×10-6-1×10-4, while the gamma analysis results in a 90-100% passing rate with 3%/2 mm, depending on the elapsed time, the type of distribution modeled and the dimensionality. This method could expand the applicability of Fricke gel dosimeters to a wider range of measurement tasks, from simple planar dose assessments to intricate volumetric analyses. The proposed technique holds great promise for overcoming the limitations imposed by ion diffusion in Fricke gel dosimeters.

Microstructural changes of peripheral nerves in early multiple sclerosis: A prospective magnetic resonance neurography study

BACKGROUND AND PURPOSE

Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system (CNS). However, there is increasing evidence of peripheral nerve involvement. This study aims to characterize the pattern of peripheral nerve changes in patients with newly diagnosed MS using quantitative magnetic resonance (MR) neurography.

METHODS

In this prospective study, 25 patients first diagnosed with MS according to the revised McDonald criteria (16 female, mean age = 32.8 ± 10.6 years) and 14 healthy controls were examined with high-resolution 3-T MR neurography of the sciatic nerve using diffusion kurtosis imaging (DKI; 20 diffusional directions, b = 0, 700, 1200 s/mm2 ) and magnetization transfer imaging (MTI). In total, 15 quantitative MR biomarkers were analyzed and correlated with clinical symptoms, intrathecal immunoglobulin synthesis, electrophysiology, and lesion load on brain and spine MR imaging.

RESULTS

Patients showed decreased fractional anisotropy (mean = 0.51 ± 0.04 vs. 0.56 ± 0.03, p < 0.001), extra-axonal tortuosity (mean = 2.32 ± 0.17 vs. 2.49 ± 0.17, p = 0.008), and radial kurtosis (mean = 1.40 ± 0.23 vs. 1.62 ± 0.23, p = 0.014) and higher radial diffusivity (mean = 1.09 ∙ 10-3  mm2 /s ± 0.16 vs. 0.98 ± 0.11 ∙ 10-3  mm2 /s, p = 0.036) than controls. Groups did not differ in MTI. No significant association was found between MR neurography markers and clinical/laboratory parameters or CNS lesion load.

CONCLUSIONS

This study provides further evidence of peripheral nerve involvement in MS already at initial diagnosis. The characteristic pattern of DKI parameters indicates predominant demyelination and suggests a primary coaffection of the peripheral nervous system in MS. This first human study using DKI for peripheral nerves shows its potential and clinical feasibility in providing novel biomarkers.

Diffusion kurtosis imaging tractography reveals disrupted white matter structural networks in children with obstructive sleep apnea syndrome

To assess the disruptions of brain white matter (WM) structural network in children with obstructive sleep apnea (OSA) using diffusion kurtosis imaging (DKI). We use DKI tractography to construct individual whole-brain, region-level WM networks in 40 OSA and 28 healthy children. Then, we apply graph theory approaches to analyze whether OSA children would show altered global and regional network topological properties and whether these alterations would significantly correlate with the clinical characteristics of OSA. We found that both OSA and healthy children showed an efficient small-world organization and highly similar hub distributions in WM networks. However, characterized by kurtosis fractional anisotropy (KFA) weighted networks, OSA children exhibited decreased global and local efficiency, increased shortest path length compared with healthy children. For regional topology, OSA children exhibited significant decreased nodal betweenness centrality (BC) in the bilateral medial orbital superior frontal gyrus (ORBsupmed), right orbital part superior frontal gyrus (ORBsup), insula, postcentral gyrus, left middle temporal gyrus (MTG), and increased nodal BC in the superior parietal gyrus, pallidum. Intriguingly, the altered nodal BC of multiple regions (right ORBsupmed, ORBsup and left MTG) within default mode network showed significant correlations with sleep parameters for OSA patients. Our results suggest that children with OSA showed decreased global integration and local specialization in WM networks, typically characterized by DKI tractography and KFA metric. This study may advance our current understanding of the pathophysiological mechanisms of impaired cognition underlying OSA.

Long period changes of hippocampal diffusion kurtosis imaging and its correlation with cognitive dysfunction after incomplete cerebral ischemia-reperfusion in rats

This study aims to summarize the changes of functional diffusion kurtosis imaging (DKI) parameters in the bilateral hippocampal CA1 region of the hemorrhagic shock reperfusion (HSR) model of rats and their correlation with cognitive dysfunction. Adult male Sprague-Dawley rats (9-10 weeks of age, weighing 350-400 g) were randomized into the HSR group (n = 30) and the sham-operated group (Sham) (n = 30). Rats in the HSR group and the Sham group were subdivided into five time points (1, 2, 4, 8, and 12 weeks) for examination. Diffusion kurtosis imaging (DKI) was performed. Cognitive dysfunction was analyzed by the Morris Water Maze. The correlation between the DKI parameters and cognitive dysfunction was analyzed by the Spearman correlation. In the HSR group, the values of axial kurtosis (Ka), radial kurtosis (Kr), and mean kurtosis (MK) in the bilateral hippocampal CA1 of rats at 1, 2, 4, 8 and 12 weeks after the surgery were significantly higher. The rats in the HSR group had significantly longer escape latency than in the Sham group. The rats in the HSR group had significantly shorter time and shorter distance in target quadrant than those in the Sham group. The escape latency had positive correlation with MK, Ka, and Kr. The distance and the time in target quadrant had negative correlation with MK, Ka, and Kr. The parameters get from the DKI could accurately evaluate the abnormal blood perfusion and microstructure changes in hippocampal CA1 area of the incomplete cerebral ischemia reperfusion rats induced by HSR. MK, Ka, and Kr values could reflect the decreased learning and memory ability in HSR rat model.

Characterizing the penumbras of white matter hyperintensities in patients with cerebral small vessel disease

PURPOSE

The white matter hyperintensity penumbra (WMH-P) is the subtly changed normal-appearing white matter (NAWM) that surrounds white matter hyperintensities (WMHs). The goal of this study was to define WMH-P in cerebral small vessel disease (CSVD) by arterial spin labeling (ASL) and diffusion tensor imaging (DTI)/diffusion kurtosis imaging (DKI).

MATERIALS AND METHODS

We prospectively analyzed 42 patients with CSVD. To determine the range of cerebral blood flow (CBF) and DTI/DKI penumbras around white matter hyperintensities, we generated NAWM layer masks from periventricular WMHs (PVWMHs) and deep WMHs (DWMHs). Mean values of CBF, fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis, and radial kurtosis within the WMHs and their corresponding NAWM layer masks were analyzed. Paired sample t tests were used for analysis, and differences were considered statistically significant if the associated p value was ≤ 0.05.

RESULTS

For DWMHs, the CBF penumbras were 13 mm, and the DTI/DKI penumbras were 8 mm. For PVWMHs, the CBF penumbras were 14 mm, and the DTI/DKI penumbras were 14 mm.

CONCLUSIONS

Our findings revealed that DTI/DKI and ASL can show structural and blood flow changes in brain tissue surrounding WMHs. In DWMHs, the blood flow penumbra was larger than the structural penumbra, while in PVWMHs, the blood flow penumbra was almost the same as the structural penumbra.

Glutaric Aciduria Type 1: Comparison between Diffusional Kurtosis Imaging and Conventional MR Imaging

BACKGROUND AND PURPOSE

Routine MR imaging has limited use in evaluating the severity of glutaric aciduria type 1. To better understand the mechanisms of brain injury in glutaric aciduria type 1, we explored the value of diffusional kurtosis imaging in detecting microstructural injury of the gray and white matter.

MATERIALS AND METHODS

This study included 17 patients with glutaric aciduria type 1 and 17 healthy controls who underwent conventional MR imaging and diffusional kurtosis imaging. The diffusional kurtosis imaging metrics of the gray and white matter were measured. Then, the MR imaging scores and diffusional kurtosis imaging metrics of all ROIs were further correlated with the morbidity scores and Barry-Albright dystonia scores.

RESULTS

The MR imaging scores showed no significant relation to the morbidity and Barry-Albright dystonia scores. Compared with healthy controls, patients with glutaric aciduria type 1 showed higher kurtosis values in the basal ganglia, corona radiata, centrum semiovale, and temporal lobe (P < .05). The DTI metrics of the basal ganglia were higher than those of healthy controls (P < .05). The fractional anisotropy value of the temporal lobe and the mean diffusivity values of basal ganglia in glutaric aciduria type 1 were lower than those in the control group (P < .05). The diffusional kurtosis imaging metrics of the temporal lobe and basal ganglia were significantly correlated with the Barry-Albright dystonia scores. The mean kurtosis values of the anterior and posterior putamen and Barry-Albright dystonia scores were most relevant (r = 0.721, 0.730, respectively). The mean kurtosis values of the basal ganglia had the best diagnostic efficiency with area under the curve values of 0.837 for the temporal lobe, and the mean diffusivity values of the basal ganglia in glutaric aciduria type 1 were lower than those in the control group (P < .05). The diffusional kurtosis imaging metrics of the temporal lobe and basal ganglia were significantly correlated with the Barry-Albright dystonia scores. The mean kurtosis values of the anterior and posterior putamen and Barry-Albright dystonia scores were most relevant (r = 0.721, 0.730, respectively). The mean kurtosis values of the basal ganglia had the best diagnostic efficiency with area under the curve values of 0.837.

CONCLUSIONS

Diffusional kurtosis imaging provides more comprehensive quantitative information regarding the gray and white matter micropathologic damage in glutaric aciduria type 1 than routine MR imaging scores.

Role of Imaging Modalities and N-Acetylcysteine Treatment in Sepsis-Associated Encephalopathy

Sepsis-associated encephalopathy is a severe systemic infection complication. Although early stages involve pathophysiological changes, detection using conventional imaging is challenging. Glutamate chemical exchange saturation transfer and diffusion kurtosis imaging can noninvasively investigate cellular and molecular events in early disease stages using magnetic resonance imaging (MRI). N-Acetylcysteine, an antioxidant and precursor of glutathione, regulates neurotransmitter glutamate metabolism and participates in neuroinflammation. We investigated the protective role of n-acetylcysteine in sepsis-associated encephalopathy using a rat model and monitored changes in brain using magnetic resonance (MR) molecular imaging. Bacterial lipopolysaccharide was injected intraperitoneally to induce a sepsis-associated encephalopathy model. Behavioral performance was assessed using the open-field test. Tumor necrosis factor α and glutathione levels were detected biochemically. Imaging was performed using a 7.0-T MRI scanner. Protein expression, cellular damage, and changes in blood-brain barrier permeability were assessed using western blotting, pathological staining, and Evans blue staining, respectively. Lipopolysaccharide-induced rats showed reduced anxiety and depression after treatment with n-acetylcysteine. MR molecular imaging can identify pathological processes at different disease stages. Furthermore, rats treated with n-acetylcysteine showed increased glutathione levels and decreased tumor necrosis factor α, suggesting enhanced antioxidant capacity and inhibition of inflammatory processes, respectively. Western blot analysis showed reduced expression of nuclear factor kappa B (p50) protein after treatment, suggesting that n-acetylcysteine inhibits inflammation via this signaling pathway. Finally, n-acetylcysteine-treated rats showed reduced cellular damage by pathology and reduced extravasation of their blood-brain barrier by Evans Blue staining. Thus, n-acetylcysteine might be a therapeutic option for sepsis-associated encephalopathy and other neuroinflammatory diseases. Furthermore, noninvasive "dynamic visual monitoring" of physiological and pathological changes related to sepsis-associated encephalopathy was achieved using MR molecular imaging for the first time, providing a more sensitive imaging basis for early diagnosis, identification, and prognosis.

Mapping early tumor response to radiotherapy using diffusion kurtosis imaging*

PURPOSE

In this pilot study, DKI measures of diffusivity and kurtosis were compared in active tumor regions and correlated to radiologic response to radiotherapy after completion of 2 weeks of treatment to derive potential early measures of tumor response.

METHODS

MRI and Magnetic Resonance Spectroscopic Imaging (MRSI) data were acquired before the beginning of RT (pre-RT) and 2 weeks after the initiation of treatment (during-RT) in 14 glioblastoma patients. The active tumor region was outlined as the union of the residual contrast-enhancing region and metabolically active tumor region. Average and standard deviation of mean, axial, and radial diffusivity (MD, AD, RD) and mean, axial, and radial kurtosis (MK, AK, RK) values were calculated for the active tumor VOI from images acquired pre-RT and during-RT and paired t-tests were executed to estimate pairwise differences. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the predictive capabilities of changes in diffusion metrics for progression-free survival (PFS).

RESULTS

Analysis showed significant pairwise differences for AD (p = 0.035; Cohen's d of 0.659) and AK (p = 0.019; Cohen's d of 0.753) in diffusion measures after 2 weeks of RT. ROC curve analysis showed that percentage change differences in AD and AK between pre-RT and during-RT scans provided an Area Under the Curve (AUC) of 0.524 and 0.762, respectively, in discriminating responders (PFS>180 days) and non-responders (PFS<180 days).

CONCLUSION

This pilot study, although preliminary in nature, showed significant changes in AD and AK maps, with kurtosis derived AK maps showing an increased sensitivity in mapping early changes in the active tumor regions.

Role of imaging modalities and N-acetylcysteine treatment in sepsis-associated encephalopathy.. [DOI: 10.21203/rs.3.rs-2459747/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background Sepsis-associated encephalopathy is a severe complication due to systemic infection. Although early stages involve pathophysiological changes, detection using conventional imaging is challenging. Glutamate chemical exchange saturation transfer and diffusion kurtosis imaging can noninvasively investigate cellular and molecular events in the early stage of the disease by MRI. N-acetylcysteine, an antioxidant and precursor of glutathione, regulates the metabolism of the neurotransmitter glutamate and participates in neuroinflammation. We aimed to investigate the protective role of n-acetylcysteine in sepsis-associated encephalopathy using a rat model and monitor changes in the brain using magnetic resonance molecular imaging. Methods Bacterial lipopolysaccharide was injected intraperitoneally into the rats to induce a sepsis-associated encephalopathy model. The behavioural performance was assessed using the open field test. Tumour necrosis factor alpha and glutathione levels were detected biochemically. Imaging was performed using a 7.0-T MRI scanner. Protein expressions and cellular damage were assessed by western blotting and pathological staining, respectively. We also evaluated changes in the blood-brain barrier permeability by the Evans blue staining. Results The lipopolysaccharide-induced rats showed reduced anxiety and depression after treatment with n-acetylcysteine. Magnetic resonance molecular imaging can identify pathological processes at different stages of the disease. Furthermore, rats treated with n-acetylcysteine showed increased glutathione levels and decreased tumour necrosis factor alpha, suggesting enhanced antioxidant capacity and inhibition of inflammatory processes, respectively. Western blot analysis showed a reduced expression of nuclear factor kappa B (p50) protein after treatment, suggesting that n-acetylcysteine inhibits inflammation via this signalling pathway. Finally, n-acetylcysteine treated rats also showed reduced cellular damage by pathology and reduced extravasation of their blood-brain barrier by Evan Blue staining. Conclusion This study showed that n-acetylcysteine might be a therapeutic option for sepsis-associated encephalopathy and other neuroinflammatory diseases. Furthermore, non-invasive ‘dynamic visual monitoring’ of the physiological and pathological changes related to sepsis-associated encephalopathy was achieved for the first time using magnetic resonance molecular imaging, which provides a more sensitive imaging basis for early clinical diagnosis, identification, and prognosis.

Application of TBSS-based machine learning models in the diagnosis of pediatric autism

Objective

To explore the microstructural changes of white matter in children with pediatric autism by using diffusion kurtosis imaging (DKI), and evaluate whether the combination of tract-based spatial statistics (TBSS) and back-propagation neural network (BPNN)/support vector machine (SVM)/logistic regression (LR) was feasible for the classification of pediatric autism.

Methods

DKI data were retrospectively collected from 32 children with autism and 27 healthy controls (HCs). Kurtosis fractional anisotropy (FAK), mean kurtosis (MK), axial kurtosis (KA), radial kurtosis (RK), fractional anisotropy (FA), axial diffusivity (DA), mean diffusivity (MD) and Radial diffusivity (DR) were generated by iQuant workstation. TBSS was used to detect the regions of parameters values abnormalities and for the comparison between these two groups. In addition, we also introduced the lateralization indices (LI) to study brain lateralization in children with pediatric autism, using TBSS for additional analysis. The parameters values of the differentiated regions from TBSS were then calculated for each participant and used as the features in SVM/BPNN/LR. All models were trained and tested with leave-one-out cross validation (LOOCV).

Results

Compared to the HCs group, the FAK, DA, and KA values of multi-fibers [such as the bilateral superior longitudinal fasciculus (SLF), corticospinal tract (CST) and anterior thalamic radiation (ATR)] were lower in pediatric autism group (p < 0.05, TFCE corrected). And we also found DA lateralization abnormality in Superior longitudinal fasciculus (SLF) (the LI in HCs group was higher than that in pediatric autism group). However, there were no significant differences in FA, MD, MK, DR, and KR values between HCs and pediatric autism group (P > 0.05, TFCE corrected). After performing LOOCV to train and test three model (SVM/BPNN/LR), we found the accuracy of BPNN (accuracy = 86.44%) was higher than that of LR (accuracy = 76.27%), but no different from SVM (RBF, accuracy = 81.36%; linear, accuracy = 84.75%).

Conclusion

Our proposed method combining TBSS findings with machine learning (LR/SVM/BPNN), was applicable in the classification of pediatric autism with high accuracy. Furthermore, the FAK, DA, and KA values and Lateralization index (LI) value could be used as neuroimaging biomarkers to discriminate the children with pediatric autism or not.

Evaluation of diffuse glioma grade and proliferation activity by different diffusion-weighted-imaging models including diffusion kurtosis imaging (DKI) and mean apparent propagator (MAP) MRI

PURPOSE

To evaluate two advanced diffusion models, diffusion kurtosis imaging and the newly proposed mean apparent propagation factor-magnetic resonance imaging, in the grading of gliomas and the assessing of their proliferative activity.

METHODS

Fifty-nine patients with clinically diagnosed and pathologically proven gliomas were enrolled in this retrospective study. All patients underwent DKI and MAP-MRI scans. Manually outline the ROI of the tumour parenchyma. After delineation, the imaging parameters were extracted using only the data from within the ROI including mean diffusion kurtosis (MK), return-to-origin probability (RTOP), Q-space inverse variance (QIV) and non-Gaussian index (NG), and the differences in each parameter in the classification of glioma were compared. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of these parameters.

RESULTS

MK, NG, RTOP and QIV were significantly different amongst the different grades of glioma. MK, NG and RTOP had excellent diagnostic value in differentiating high-grade from low-grade glioma, with largest areas under the curve (AUCs; 0.929, 0.933 and 0.819, respectively; P < 0.01). MK and NG had the largest AUCs (0.912 and 0.904) when differentiating grade II tumours from III tumours (P < 0.01) and large AUCs (0.791 and 0.786) when differentiating grade III from grade IV tumours. Correlation analysis of tumour proliferation activity showed that MK, NG and QIV were strongly correlated with the Ki-67 LI (P < 0.001).

CONCLUSION

MK, RTOP and NG can effectively represent the microstructure of these altered tumours. Multimodal diffusion-weighted imaging is valuable for the preoperative evaluation of glioma grade and tumour proliferative activity.

The microstructural abnormalities of cingulum was related to patients with mild cognitive impairment: a diffusion kurtosis imaging study

OBJECTIVE

Our study aimed to investigate the correlations between microstructural changes of cingulum and patients with mild cognitive impairment (MCI) by diffusion kurtosis imaging (DKI) technique.

METHOD

A total of 104 patients with cerebral small vessel diseases (cSVD) were retrospectively enrolled in this study. According to Montreal Cognitive Assessment Scale (MoCA) scores, these patients were divided into MCI group (n = 59) and non-MCI group (n = 45). The general clinical data was collected and analyzed. The regions of interests (ROIs) were selected for investigation in cingulum. The values of DKI parameters were measured in each ROI and compared between the two groups, the correlations between DKI parameters and MoCA scores were examined.

RESULTS

Compared to non-MCI group, MCI patients had more severe white matter hyperintensities (WMHs) (P = 0.038) and lower MoCA scores (P < 0.01). MCI patients showed significantly decreased fractional anisotropy (FA), axial kurtosis (AK), mean kurtosis (MK), radial kurtosis (RK), and kurtosis fractional anisotropy (KFA) in the left cingulum in the cingulated cortex (CgC) region (all P < 0.0125). In the left CgC region, FA, AK, MK, RK, and KFA were positively correlated with MoCA scores (r = 0.348, 0.409, 0.310, 0.441, 0.422, all P < 0.001). Meanwhile, FA, AK, MK, RK, and KFA were also positively correlated with MoCA scores (r = 0.338, 0.352, 0.289, 0.380, 0.370, all P < 0.001) in the right CgC region.

CONCLUSION

DKI technique could be used to explore the microstructural changes of cingulum in MCI patients and DKI-derived parameters might be feasible to evaluate MCI patients.

Cumulant expansion with localization: A new representation of the diffusion MRI signal

Diffusion MR is sensitive to the microstructural features of a sample. Fine-scale characteristics can be probed by employing strong diffusion gradients while the low b-value regime is determined by the cumulants of the distribution of particle displacements. A signal representation based on the cumulants, however, suffers from a finite convergence radius and cannot represent the 'localization regime' characterized by a stretched exponential decay that emerges at large gradient strengths. Here, we propose a new representation for the diffusion MR signal. Our method provides not only a robust estimate of the first three cumulants but also a meaningful extrapolation of the entire signal decay.

Brain microstructural alterations in the left precuneus mediate the association between KIBRA polymorphism and working memory in healthy adults: a diffusion kurtosis imaging study

Kidney and brain expressed protein (KIBRA) rs17070145 is associated with working memory function and cognitive processes. However, the neural mechanisms underlying these associations are not fully understood. This study aimed to explore the effect of KIBRA polymorphism on brain microstructure and blood oxygenation level dependent (BOLD) fluctuations using diffusion kurtosis imaging (DKI) and resting-state functional magnetic resonance imaging (fMRI) in 163 young adults. We also investigated that whether the imaging alterations mediated the association between KIBRA gene and working memory performance. Voxel-based analysis of DKI data showed that KIBRA C-allele carriers exhibited increased axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) as well as decreased fractional anisotropy (FA), mean kurtosis (MK) and radial kurtosis (RK) compared with KIBRA TT homozygotes, primarily involving the prefrontal lobe, left precuneus and the left superior parietal white matter. Meanwhile, KIBRA C-allele carriers exhibited decreased amplitude of low-frequency fluctuation (ALFF) in the left precuneus compared to KIBRA TT homozygotes. Mediation analysis revealed that the DKI metrics (MK and RK) of the left precuneus mediated the effect of the KIBRA polymorphism on working memory performance. Moreover, the MK and RK in the left precuneus were positively correlated with ALFF in the same brain region. These findings suggest that abnormal DKI parameters may provide a gene-brain-behavior pathway in which KIBRA rs17070145 affects working memory by modulating brain microstructure in the left precuneus. This illustrates that DKI may provide additional biological information and reveal new insights into the neural mechanisms of the KIBRA polymorphism.

Surgery of Motor Eloquent Glioblastoma Guided by TMS-Informed Tractography: Driving Resection Completeness Towards Prolonged Survival

Background

Surgical treatment of patients with glioblastoma affecting motor eloquent brain regions remains critically discussed given the risk–benefit dilemma of prolonging survival at the cost of motor-functional damage. Tractography informed by navigated transcranial magnetic stimulation (nTMS-informed tractography, TIT) provides a rather robust estimate of the individual location of the corticospinal tract (CST), a highly vulnerable structure with poor functional reorganisation potential. We hypothesised that by a more comprehensive, individualised surgical decision-making using TIT, tumours in close relationship to the CST can be resected with at least equal probability of gross total resection (GTR) than less eloquently located tumours without causing significantly more gross motor function harm. Moreover, we explored whether the completeness of TIT-aided resection translates to longer survival.

Methods

A total of 61 patients (median age 63 years, m = 34) with primary glioblastoma neighbouring or involving the CST were operated on between 2010 and 2015. TIT was performed to inform surgical planning in 35 of the patients (group T; vs. 26 control patients). To achieve largely unconfounded group comparisons for each co-primary outcome (i.e., gross-motor functional worsening, GTR, survival), (i) uni- and multivariate regression analyses were performed to identify features of optimal outcome prediction; (ii), optimal propensity score matching (PSM) was applied to balance those features pairwise across groups, followed by (iii) pairwise group comparison.

Results

Patients in group T featured a significantly higher lesion-CST overlap compared to controls (8.7 ± 10.7% vs. 3.8 ± 5.7%; p = 0.022). The frequency of gross motor worsening was higher in group T, albeit non-significant (n = 5/35 vs. n = 0/26; p = 0.108). PSM-based paired-sample comparison, controlling for the confounders of preoperative tumour volume and vicinity to the delicate vasculature of the insula, showed higher GTR rates in group T (77% vs. 69%; p = 0.025), particularly in patients with a priori intended GTR (87% vs. 78%; p = 0.003). This translates into a prolonged PFS in the same PSM subgroup (8.9 vs. 5.8 months; p = 0.03), with GTR representing the strongest predictor of PFS (p = 0.001) and OS (p = 0.0003) overall.

Conclusion

The benefit of TIT-aided GTR appears to overcome the drawbacks of potentially elevated motor functional risk in motor eloquent tumour localisation, leading to prolonged survival of patients with primary glioblastoma close to the CST.

A review on investigation of the basic contrast mechanism underlying multidimensional diffusion MRI in assessment of neurological disorders

INTRODUCTION

Multidimensional diffusion MRI (MDD MRI) is a novel diffusion technique that uses advanced gradient waveforms for microstructural tissue characterization to provide information about average rate, anisotropy and orientation of the diffusion and to disentangle the signal fraction from specific cell types i.e., elongated cells, isotropic cells and free water.

AIM

To review the diagnostic potential of MDD MRI in the clinical setting for microstructural tissue characterization in patients with neurological disorders to aid in patient care and treatment.

METHOD

A scoping review on the clinical applications of MDD MRI was conducted from original articles published in PubMed and Scopus from 2015 to 2021 using the keywords "Multidimensional diffusion MRI" OR "diffusion tensor distribution" OR "Tensor-Valued Diffusion" OR "b-tensor encoding" OR "microscopic diffusion anisotropy" OR "microscopic anisotropy" OR "microscopic fractional anisotropy" OR "double diffusion encoding" OR "triple diffusion encoding" OR "double pulsed field gradients" OR "double wave vector" OR "correlation tensor imaging" AND "brain" OR "axons".

RESULTS

Initially 145 articles were screened and after applying inclusion and exclusion criteria, nine articles were included in the final analysis. In most of these studies, microscopic diffusion anisotropy within the lesion showed deviation from the normal-appearing tissue.

CONCLUSION

Multidimensional diffusion MRI can provide better quantification and visualization of tissue microstructure than conventional diffusion MRI and can be used in the clinical setting for diagnosis of neurological disorders.

DWI of the Breast - Possibilities and Limitations

BACKGROUND

 The MRI of the breast is of great importance in the diagnosis of disorders of the breast. This can be stated for the primary diagnosis as well as the follow up. Of special interest is diffusion weighted imaging (DWI), which has an increasingly important role. The present review provides results regarding the diagnostic and prognostic relevance of DWI for disorders of the breast.

METHODS

 Under consideration of the recently published literature, the clinical value of DWI of the breast is discussed. Several diagnostic applications are shown, especially for the primary diagnosis of unclear tumors of the breast, the prediction of the axillary lymph node status and the possibility of a native screening. Moreover, correlations between DWI and histopathology features and treatment prediction with DWI are provided.

RESULTS

 Many studies have shown the diagnostic value of DWI for the primary diagnosis of intramammary lesions. Benign lesions of the breast have significantly higher apparent diffusion coefficients (ADC values) compared to malignant tumors. This can be clinically used to reduce unnecessary biopsies in clinical routine. However, there are inconclusive results for the prediction of the histological subtype of the breast cancer. DWI can aid in the prediction of treatment to neoadjuvant chemotherapy.

CONCLUSION

 DWI is a very promising imaging modality, which should be included in the standard protocol of the MRI of the breast. DWI can provide clinically value in the diagnosis as well as for prognosis in breast cancer.

KEY POINTS

  · DWI can aid in the discrimination between benign and malignant tumors of the breast and therefore avoiding unnecessary biopsies.. · The ADC value cannot discriminate between immunhistochemical subtypes of the breast cancer. · The ADC value of breast cancer increases under neoadjuvant chemotherapy and can by this aid in treatment prediction.. · There is definite need of standardisation for clinical translation.

CITATION FORMAT

· Meyer HJ, Martin M, Denecke T. DWI of the Breast - Possibilities and Limitations. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1775-8572.

Detection of Chronic Blast-Related Mild Traumatic Brain Injury with Diffusion Tensor Imaging and Support Vector Machines

Blast-related mild traumatic brain injury (bmTBI) often leads to long-term sequalae, but diagnostic approaches are lacking due to insufficient knowledge about the predominant pathophysiology. This study aimed to build a diagnostic model for future verification by applying machine-learning based support vector machine (SVM) modeling to diffusion tensor imaging (DTI) datasets to elucidate white-matter features that distinguish bmTBI from healthy controls (HC). Twenty subacute/chronic bmTBI and 19 HC combat-deployed personnel underwent DTI. Clinically relevant features for modeling were selected using tract-based analyses that identified group differences throughout white-matter tracts in five DTI metrics to elucidate the pathogenesis of injury. These features were then analyzed using SVM modeling with cross validation. Tract-based analyses revealed abnormally decreased radial diffusivity (RD), increased fractional anisotropy (FA) and axial/radial diffusivity ratio (AD/RD) in the bmTBI group, mostly in anterior tracts (29 features). SVM models showed that FA of the anterior/superior corona radiata and AD/RD of the corpus callosum and anterior limbs of the internal capsule (5 features) best distinguished bmTBI from HCs with 89% accuracy. This is the first application of SVM to identify prominent features of bmTBI solely based on DTI metrics in well-defined tracts, which if successfully validated could promote targeted treatment interventions.

Altered Microstructural Changes Detected by Diffusion Kurtosis Imaging in Patients With Cognitive Impairment After Acute Cerebral Infarction

Objective

To detect the microstructural changes in patients with cognitive impairment after acute cerebral infarction using diffusion kurtosis imaging (DKI).

Materials and Methods

A total of 70 patients with acute cerebral infarction were divided into two groups: 35 patients with cognitive impairment (VCI group), and 35 patients without cognitive impairment (N-VCI group), according to mini-mental state examination (MMSE) score. Healthy individuals (n = 36) were selected as the normal control (NORM) group. DKI parameters from 28 different brain regions of interest (ROIs) were selected, measured, and compared.

Results

VCI group patients had significantly higher mean diffusion (MD) and significantly lower mean kurtosis (MK) values in most ROIs than those in the N-VCI and NORM groups. DKI parameters in some ROIs correlated significantly with MMSE score. The splenium of corpus callosum MD was most correlated with MMSE score, the correlation coefficient was −0.652, and this parameter had good ability to distinguish patients with VCI from healthy controls; at the optimal cut-off MD value (0.9915), sensitivity was 91.4%, specificity 100%, and the area under the curve value 0.964.

Conclusions

Pathological changes in some brain regions may underlie cognitive impairment after acute cerebral infarction, especially the splenium of corpus callosum. These preliminary results suggest that, in patients with VCI, DKI may be useful for assessing microstructural tissue damage.

Integration of quantitative diffusion kurtosis imaging and prostate specific antigen in differential diagnostic of prostate cancer

This study aimed to evaluate the diagnostic performance of diffusion kurtosis imaging (DKI) and prostate-specific antigen (PSA) biomarkers in differentiating prostate cancer (PCa) and benign prostatic hyperplasia (BPH).A total of 43 cases of prostate diseases verified by pathology were enrolled in the present study. These cases were assigned to the BPH group (n = 20, 68.85±10.81 years old) and PCa group (n = 23, 74.13 ± 7.37 years old). All patients underwent routine prostate magnetic resonance imaging and DKI examinations, and the mean diffusivity (MD), mean kurtosis (MK), and fractional anisotropy (FA) values were calculated. Three serum indicators (PSA, free PSA [fPSA], and f/t PSA) were collected. We used univariate logistic regression to analyze the above quantitative parameters between the 2 groups, and the independent factors were further incorporated into the multivariate logistic regression model. The area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnostic efficacy of the single indicator and combined model.The difference in PSA, f/t PSA, MK, and FA between PCa and BPH was statistically significant (P < .05). The AUC for the combined model (f/t PSA, MK, and FA) of 0.972 (95% confidence interval [CI]: 0.928, 1.000) was higher than the AUC of 0.902 (95% CI: 0.801, 1.000) for f/t PSA, 0.833 (95% CI: 0.707, 0.958) for MK, and 0.807 (95% CI: 0.679, 0.934) for FA.The MK and FA values for DKI and f/t PSA effectively identify PCa and BPH, compared to the PSA indicators. Combining DKI and PSA derivatives can further improve the diagnosis efficiency and might help in the clinical setting.

Altered structural and functional connectivity in CSF1R-related leukoencephalopathy

CSF1R-related leukoencephalopathy is a rare white-matter encephalopathy characterized by motor and neuropsychiatric symptoms due to colony-stimulating factor 1 receptor (CSF1R) gene mutation. Few studies have investigated the intrinsic brain alternations of patients with CSF1R-related leukoencephalopathy. We aim to evaluate the structural and functional changes in those patients. Seven patients with CSF1R-related leukoencephalopathy and 15 age-matched healthy controls (HCs) underwent multimodal magnetic resonance imaging (MRI), including high-resolution T1-weighted imaging, T2-weighted fluid attenuated inversion recovery imaging, diffusion-weighted imaging, diffusion kurtosis imaging (DKI) and resting-state functional MRI. First, to detect structural alterations, the gray matter volumes were compared using voxel-based morphometry analyses. Second, DKI parametric maps were used to evaluate the white matter (WM) connectivity changes. Finally, we constructed a seed-based resting-state functional connectivity matrix based on 90 regions of interest and examined the functional network changes of CSF1R-related leukoencephalopathy. Unlike the HCs, patients with CSF1R-related leukoencephalopathy predominantly had morphological atrophy in the bilateral thalamus and left hippocampus. In addition, the abnormal diffusivity was mainly distributed in the splenium of the corpus callosum, periventricular regions, centrum semiovale, subcortical U-fibers and midline cortex structures. Moreover, the patients had significantly reduced functional connectivity between the bilateral caudate nucleus and their contralateral hippocampus. Therefore, in addition to hyperintensity on the T2-weighted images, CSF1R-related leukoencephalopathy also showed abnormal structural and functional alterations, including subcortical atrophy and reduced functional connectivity, as well as altered diffuse parameters in the WM and subcortical regions. These findings expand our understanding of the potential pathophysiologic mechanism behind this hereditary disease.

Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project

Diffusion-weighted magnetic resonance imaging (dMRI) measurements and models provide information about brain connectivity and are sensitive to the physical properties of tissue microstructure. Diffusional Kurtosis Imaging (DKI) quantifies the degree of non-Gaussian diffusion in biological tissue from dMRI. These estimates are of interest because they were shown to be more sensitive to microstructural alterations in health and diseases than measures based on the total anisotropy of diffusion which are highly confounded by tissue dispersion and fiber crossings. In this work, we implemented DKI in the Diffusion in Python (DIPY) project-a large collaborative open-source project which aims to provide well-tested, well-documented and comprehensive implementation of different dMRI techniques. We demonstrate the functionality of our methods in numerical simulations with known ground truth parameters and in openly available datasets. A particular strength of our DKI implementations is that it pursues several extensions of the model that connect it explicitly with microstructural models and the reconstruction of 3D white matter fiber bundles (tractography). For instance, our implementations include DKI-based microstructural models that allow the estimation of biophysical parameters, such as axonal water fraction. Moreover, we illustrate how DKI provides more general characterization of non-Gaussian diffusion compatible with complex white matter fiber architectures and gray matter, and we include a novel mean kurtosis index that is invariant to the confounding effects due to tissue dispersion. In summary, DKI in DIPY provides a well-tested, well-documented and comprehensive reference implementation for DKI. It provides a platform for wider use of DKI in research on brain disorders and in cognitive neuroscience.

Is Transcranial Magnetic Resonance Imaging-Guided Focused Ultrasound a Repeatable Treatment Option? Case Report of a Retreated Patient With Tremor Combined With Parkinsonism

INTRODUCTION

In recent years, transcranial Magnetic Resonance Imaging-guided Focused Ultrasound (tcMRgFUS) treatments for functional neurological disorders are giving a new thrust to the field of therapeutic brain lesioning.

OBJECTIVE

To present the case of a patient affected by tremor combined with Parkinsonism who underwent a second tcMRgFUS thalamotomy because of relapsing tremor after a few months from the first tcMRgFUS treatment.

METHODS

A 72-yr-old, right-handed man, came to our observation because of a disabling tremor affecting his upper limbs, refusing any invasive surgical procedure and already treated by tcMRgFUS left Vim thalamotomy. However, clinical benefit had brief duration, as a progressive recurrence of tremor on the right upper limb was observed after a few months from the first treatment. Thus, the patient underwent a new left-sided tcMRgFUS procedure 6 mo after the former treatment.

RESULTS

After the second procedure, an immediate and complete relief from tremor on the right upper limb was achieved with clinical benefit that persisted up to a 6-mo follow-up.

CONCLUSION

Since tcMRgFUS doesn't use ionizing radiations and it is incision-less, repeated and staged treatment procedures have always been hypothesized. Our report suggests that tcMRgFUS retreatment might actually be a feasible, safe, and effective option in selected patients in whom an optimal clinical outcome is not achieved after the first treatment session. However, future well-designed studies in large samples are needed to assess the possible risks of retreatment and the optimal timing of reintervention as well as eligibility and exclusion criteria.

An update in musculoskeletal tumors: from quantitative imaging to radiomics

In the last two decades, relevant progress has been made in the diagnosis of musculoskeletal tumors due to the development of new imaging tools, such as diffusion-weighted imaging, diffusion kurtosis imaging, magnetic resonance spectroscopy, and diffusion tensor imaging. Another important role has been played by the development of artificial intelligence software based on complex algorithms, which employ computing power in the detection of specific tumor types. The aim of this article is to report the most advanced imaging techniques focusing on their advantages in clinical practice.

Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease

Objective: The purpose of our study was to distinguish the changes in the microstructure of the cingulate cortex in patients with mild cognitive impairment (MCI) induced by cerebral small vessel disease (CSVD).Method: 80 patients were diagnosed with CSVD in this study, including 55 patients with MCI and 25 patients without MCI. Diffusion kurtosis imaging (DKI) and Montreal cognitive assessment (MoCA) were performed in all patients. The anterior cingulate gyrus, posterior cingulate gyrus and middle cingulate gyrus were selected as the regions of interest, and some parameters were recorded.Results: Compared with the non-MCI group, the MCI group mainly showed obviously higher mean diffusion (MD) and radial diffusion (RD) values (P = 0.022 and P = 0.029) but lower fractional anisotropy (FA), axial kurtosis (AK), mean kurtosis (MK) and radial kurtosis (RK) values (P = 0.047, P = 0.001, P < 0.01, and P = 0.001, respectively) in the right anterior cingulate gyrus. Meanwhile, in the right posterior cingulate gyrus, the MCI group also showed higher axial diffusion (AD) and MD (P = 0.027 and P = 0.030) and lower AK (P = 0.014). Additionally, negative correlations of AD, MD, and RD with MoCA scores and positive correlations of FA, AK, MK and RK with MoCA scores were observed in some regions of the cingulate gyrus.Conclusions: DKI is a good method to examine microstructural damage in the cingulate cortex, and some parameters of DKI may be used as imaging biomarkers to detect early MCI in patients with CSVD.

Diffusion Kurtosis Imaging Fiber Tractography of Major White Matter Tracts in Neurosurgery

Diffusion tensor imaging (DTI)-based fiber tractography is routinely used in clinical applications to visualize major white matter tracts, such as the corticospinal tract (CST), optic radiation (OR), and arcuate fascicle (AF). Nevertheless, DTI is limited due to its capability of resolving intra-voxel multi-fiber populations. Sophisticated models often require long acquisition times not applicable in clinical practice. Diffusion kurtosis imaging (DKI), as an extension of DTI, combines sophisticated modeling of the diffusion process with short acquisition times but has rarely been investigated in fiber tractography. In this study, DTI- and DKI-based fiber tractography of the CST, OR, and AF was investigated in healthy volunteers and glioma patients. For the CST, significantly larger tract volumes were seen in DKI-based fiber tractography. Similar results were obtained for the OR, except for the right OR in patients. In the case of the AF, results of both models were comparable with DTI-based fiber tractography showing even significantly larger tract volumes in patients. In the case of the CST and OR, DKI-based fiber tractography contributes to advanced visualization under clinical time constraints, whereas for the AF, other models should be considered.

Combined 18F-FET PET and diffusion kurtosis MRI in posttreatment glioblastoma: differentiation of true progression from treatment-related changes

Background

Radiological differentiation of tumor progression (TPR) from treatment-related changes (TRC) in pretreated glioblastoma is crucial. This study aimed to explore the diagnostic value of diffusion kurtosis MRI combined with information derived from O-(2-[¹⁸F]-fluoroethyl)-l-tyrosine (¹⁸F-FET) PET for the differentiation of TPR from TRC in patients with pretreated glioblastoma.

Methods

Thirty-two patients with histomolecularly defined and pretreated glioblastoma suspected of having TPR were included in this retrospective study. Twenty-one patients were included in the TPR group, and 11 patients in the TRC group, as assessed by neuropathology or clinicoradiological follow-up. Three-dimensional (3D) regions of interest were generated based on increased ¹⁸F-FET uptake using a tumor-to-brain ratio of 1.6. Furthermore, diffusion MRI kurtosis maps were obtained from the same regions of interest using co-registered ¹⁸F-FET PET images, and advanced histogram analysis of diffusion kurtosis map parameters was applied to generated 3D regions of interest. Diagnostic accuracy was analyzed by receiver operating characteristic curve analysis and combinations of PET and MRI parameters using multivariate logistic regression.

Results

Parameters derived from diffusion MRI kurtosis maps show high diagnostic accuracy, up to 88%, for differentiating between TPR and TRC. Logistic regression revealed that the highest diagnostic accuracy of 94% (area under the curve, 0.97; sensitivity, 94%; specificity, 91%) was achieved by combining the maximum tumor-to-brain ratio of ¹⁸F-FET uptake and diffusion MRI kurtosis metrics.

Conclusions

The combined use of ¹⁸F-FET PET and MRI diffusion kurtosis maps appears to be a promising approach to improve the differentiation of TPR from TRC in pretreated glioblastoma and warrants further investigation.

The association between White matter microstructure alterations detected by Diffusional kurtosis imaging in Neural circuit and post-stroke depression

AIM

In order to study the mechanism of post-stroke depression (PSD), we used diffusion kurtosis imaging (DKI) to describe the changes in white matter (WM) microstructure in PSD patients, to investigate the association between WM damage in limbic-cortical-striatal-pallidal-thalamic (LCSPT) circuit and PSD, and the utility of DKI in the diagnosis of PSD.

METHODS

Fifty-eight participants were divided into different groups: control group (n=20), stroke patients without depression (Non-PSD, n=21) and PSD group (n=17). All were taken DKI scans. The WM of bilateral superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, temporal lobe, parietal lobe, occipital lobe, the anterior and posterior limb of internal capsule, the genu and splenium of corpus callosum were selected as the regions of interest (ROI) and selected mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK) as the DKI parameters.

RESULTS

Compared with control and Non-PSD, MK of PSD group in bilateral superior frontal gyrus, middle frontal gyrus, temporal lobe and the genu of corpus callosum were decreased significantly, as well as the RK in left superior frontal gyrus, bilateral middle frontal gyrus and temporal lobe. But there was no significant difference in AK. Besides, the decrease in MK and RK in frontal and temporal lobe was negatively associated with the severity of PSD.

CONCLUSION

Our research indicated that the damage to WM microstructure in the frontal lobe, temporal lobe and the genu of corpus callosum may be related toPSD. DKI explores the microstructural changes of WM in PSD patients and may be an auxiliary diagnostic method for PSD.

Diffusion kurtosis imaging and pathological comparison of early hypoxic-ischemic brain damage in newborn piglets

To investigate the application value of magnetic resonance diffusion kurtosis imaging (DKI) in hypoxic–ischemic brain damage (HIBD) in newborn piglets and to compare imaging and pathological results. Of 36 piglets investigated, 18 were in the experimental group and 18 in the control group. The HIBD model was established in newborn piglets by ligating the bilateral common carotid arteries and placing them into hypoxic chamber. All piglets underwent conventional MRI and DKI scans at 3, 6, 9, 12, 16, and 24 h postoperatively. Mean kurtosis (MK) and mean diffusivity (MD) maps were constructed. Then, the lesions were examined using light and electron microscopy and compared with DKI images. The MD value of the lesion area gradually decreased and the MK value gradually increased in the experimental group with time. The lesion areas gradually expanded with time; MK lesions were smaller than MD lesions. Light microscopy revealed neuronal swelling in the MK- and MD-matched and mismatched regions. Electron microscopy demonstrated obvious mitochondrial swelling and autophagosomes in the MK- and MD-matched region but normal mitochondrial morphology or mild swelling in the mismatched region. DKI can accurately evaluate early ischemic–hypoxic brain injury in newborn piglets.

Diffusion Tensor Imaging-Based Studies at the Group-Level Applied to Animal Models of Neurodegenerative Diseases

The understanding of human and non-human microstructural brain alterations in the course of neurodegenerative diseases has substantially improved by the non-invasive magnetic resonance imaging (MRI) technique of diffusion tensor imaging (DTI). Animal models (including disease or knockout models) allow for a variety of experimental manipulations, which are not applicable to humans. Thus, the DTI approach provides a promising tool for cross-species cross-sectional and longitudinal investigations of the neurobiological targets and mechanisms of neurodegeneration. This overview with a systematic review focuses on the principles of DTI analysis as used in studies at the group level in living preclinical models of neurodegeneration. The translational aspect from in-vivo animal models toward (clinical) applications in humans is covered as well as the DTI-based research of the non-human brains' microstructure, the methodological aspects in data processing and analysis, and data interpretation at different abstraction levels. The aim of integrating DTI in multiparametric or multimodal imaging protocols will allow the interrogation of DTI data in terms of directional flow of information and may identify the microstructural underpinnings of neurodegeneration-related patterns.

Correlations Between the Microstructural Changes of the Medial Temporal Cortex and Mild Cognitive Impairment in Patients With Cerebral Small Vascular Disease (cSVD): A Diffusion Kurtosis Imaging Study

Object: The purpose of our study was to investigate the microstructural changes of the medial temporal cortex in mild cognitive impairment (MCI) patients with cerebral small vascular disease (cSVD) using diffusion kurtosis imaging (DKI) and to examine whether DKI parameters are correlated with MCI. Method: A total of 82 cSVD patients admitted to the Department of Neurology Beijing Chaoyang Hospital, Capital Medical University, were retrospectively enrolled in this study. The Montreal cognitive assessment scale (MoCA) score was used to assess overall cognitive function. According to the presence or absence of MCI, these patients were divided into an MCI group (n = 48) and a non-MCI group (n = 34). The general clinical data of the two groups were collected and analyzed. The regions of interest (ROIs) in the medial temporal cortex were selected for investigation. The averaged values of DKI parameters were measured in each ROI and compared between the two groups, and the correlations between DKI parameters and MoCA score and between diffusion and kurtosis parameters were examined. Results: Compared to the non-MCI group, MCI patients showed significantly increased mean diffusion (MD) and radial diffusion (RD) and significantly decreased mean kurtosis (MK) in the left hippocampus (P = 0.005, 0.006, 0.002, respectively). In the left hippocampus, fractional anisotropy (FA), MK, radial kurtosis (RK), and kurtosis fractional anisotropy (KFA) showed significantly positive correlations with MoCA score (r = 0.374, 0.37, 0.392, 0.242, respectively, all P < 0.05), while MK and RD were negatively correlated with MoCA score (r = -0.227, -0.255, respectively, both P < 0.05). In the left parahippocampal region, axial kurtosis (AK) and KFA were positively correlated with MoCA score (r = 0.228, 0.282, respectively, both P < 0.05), while RK was positively correlated with MoCA score in the right parahippocampal region (r = 0.231, P < 0.05). Significant correlations of MD with MK, RD with RK, and FA with KFA were observed in the medial temporal cortex (r = -0.254, -0.395, 0.807, respectively, all P < 0.05) but not of axial diffusion (AD) with AK. Conclusion: The DKI technique can be used to observe microstructural changes of the medial temporal cortex in MCI patients with cSVD. The DKI-derived parameters might be a feasible means of evaluating patients with MCI.

Differentiation Between Multiple System Atrophy and Other Spinocerebellar Degenerations Using Diffusion Kurtosis Imaging

RATIONALE AND OBJECTIVE

Differentiation between multiple system atrophy (MSA) and other spinocerebellar degenerations showing cerebellar ataxia is often difficult. Hence, we investigated whether magnetic resonance diffusion kurtosis imaging (DKI) could detect pathological changes that occur in these patients and be used for differential diagnosis.

METHODS

Thirty-six subjects (12 patients with MSA accompanied by predominant cerebellar ataxia [MSA-C], 10 patients with spinocerebellar ataxias [SCAs] or sporadic adult-onset ataxia of unknown etiology [SAOA], and 14 healthy controls) were examined using 1.5- or 3-T magnetic resonance scanners. From the DKI data, the mean kurtosis, fractional anisotropy, and mean diffusivity values of the pontine crossing tract (PCT), middle cerebellar peduncle, and cerebellum were automatically measured, and the ratios against the values of the corpus callosum were calculated.

RESULTS

We found significant decreases in mean kurtosis and fractional anisotropy ratios in the PCT and middle cerebellar peduncle, and a significant increase in the mean diffusivity ratio in the PCT in the MSA-C group, as compared with the SCA/SAOA and control groups (p < 0.027-0.001). Among these metrics, there were no significant differences in the diagnostic performance. By contrast, the ratios in the cerebellum showed no significant differences between the MSA-C and SCA/SAOA groups but were significantly altered when compared with the controls (p < 0.001).

CONCLUSION

Quantitative DKI analyses can be used to differentiate between patients with MSA-C and those with SCA/SAOA.

Cerebral Damage after Carbon Monoxide Poisoning: A Longitudinal Diffusional Kurtosis Imaging Study

BACKGROUND AND PURPOSE

Previous DTI cross-sectional studies have showed the cerebral damage feature was different in the three clinical stages after carbon monoxide poisoning. Diffusional kurtosis imaging (DKI) is an advanced diffusion imaging model and considered to better provide microstructural contrast in comparison with DTI parameters. The primary aim of this study was to assess microstructural changes in gray and white matter with diffusional kurtosis imaging in the acute, delayed neuropsychiatric, and chronic phases after acute carbon monoxide (CO) poisoning. The secondary aim was to relate diffusional kurtosis imaging measures to neuropsychiatric outcomes of acute carbon monoxide poisoning.

MATERIALS AND METHODS

In all, 17 patients with acute carbon monoxide poisoning and 30 sex- and age-matched healthy volunteers were enrolled in the study. Patients were scanned within 1 week, 3-8 weeks, and 6 months after acute carbon monoxide poisoning. Diffusional kurtosis imaging metrics including mean kurtosis, mean diffusivity, fractional anisotropy, and kurtosis fractional anisotropy were measured in 11 ROIs and then further correlated with neuropsychiatric scores.

RESULTS

In WM, mean kurtosis tended to increase from the acute-to-delayed neuropsychiatric phases and then decrease in the chronic phase, while in GM mean kurtosis showed a constant decline. Contrary to mean kurtosis, mean diffusivity first decreased then tended to increase in WM, while in GM, from the acute to chronic phases, mean diffusivity showed a constant increase. In both WM and GM, the fractional anisotropy and kurtosis fractional anisotropy values progressively declined with time. Kurtosis fractional anisotropy showed the best diagnostic efficiency with an area under the curve of 0.812 (P = .000). Along with neuropsychiatric scores, kurtosis fractional anisotropy of the centrum semiovale and Digit Span Backward were most relevant (r = 0.476, P = .000).

CONCLUSIONS

Longitudinally, microstructural changes were inconsistent in WM and GM with time after acute carbon monoxide poisoning. Diffusional kurtosis imaging metrics provided important complementary information to quantify the damage to cognitive impairment.

MK-curve - Characterizing the relation between mean kurtosis and alterations in the diffusion MRI signal

Diffusion kurtosis imaging (DKI) is a diffusion MRI (dMRI) technique to quantify brain microstructural properties. While DKI measures are sensitive to tissue alterations, they are also affected by signal alterations caused by imaging artifacts such as noise, motion and Gibbs ringing. Consequently, DKI often yields output parameter values (e.g. mean kurtosis; MK) that are implausible. These include implausible values that are outside of the range dictated by physics/biology, and visually apparent implausible values that form unexpected discontinuities, being too high or too low comparing with their neighborhood. These implausible values will introduce bias into any following data analyses (e.g. between-population statistical computation). Existing studies have attempted to correct implausible DKI parameter values in multiple ways; however, these approaches are not always effective. In this study, we propose a novel method for detecting and correcting voxels with implausible values to enable improved DKI parameter estimation. In particular, we focus on MK parameter estimation. We first characterize the relation between MK and alterations in the dMRI signal including diffusion weighted images (DWIs) and the baseline (b0) images. This is done by calculating MK for a range of synthetic DWI or b0 for each voxel, and generating curves (MK-curve) representing how alterations to the input dMRI signals affect the resulting output MK. We find that voxels with implausible MK values are more likely caused by artifacts in the b0 images than artifacts in DWIs with higher b-values. Accordingly, two characteristic b0 values, which define a range of synthetic b0 values that generate implausible MK values, are identified on the MK-curve. Based on this characterization, we propose an automatic approach for detection of voxels with implausible MK values by comparing a voxel's original b0 signal to the identified two characteristic b0 values, along with a correction strategy to replace the original b0 in each detected implausible voxel with a synthetic b0 value computed from the MK-curve. We evaluate the method on a DKI phantom dataset and dMRI datasets from the Human Connectome Project (HCP), and we compare the proposed correction method with other previously proposed correction methods. Results show that our proposed method is able to identify and correct most voxels with implausible DKI parameter values as well as voxels with implausible diffusion tensor parameter values.

Abnormal cerebral microstructures revealed by diffusion kurtosis imaging in amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease in which cerebral structural impairment is a consistent feature.

PURPOSE

To investigate cerebral microstructural changes in ALS using diffusion kurtosis imaging (DKI) for the first time.

STUDY TYPE

Prospective.

SUBJECTS

Eighteen ALS patients and 20 healthy controls.

FIELD STRENGTH/SEQUENCE

DKI images were obtained by a spin-echo echo-planar imaging sequence on a 3T MRI scanner, with three b-values (0, 1000, and 2000 s/mm² ) and 64 diffusion encoding directions.

ASSESSMENT

The revised ALS Functional Rating Scale (ALSFRS-R) was administered to assess disease severity, and the symptom duration and disease progression rate were also recorded. Voxel-based analysis was applied to examine the alteration of DKI metrics (ie, mean kurtosis metrics [MK], axial kurtosis [AK], and radial kurtosis [RK]) and the conventional diffusion metrics (ie, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity).

STATISTICAL TESTS

Student's t-test, chi-square test, and Pearson correlation analysis.

RESULTS

ALS patients showed MK reductions in gray matter areas, including the bilateral precentral gyrus, bilateral paracentral lobule, and left anterior cingulate gyrus; they also showed decreased MK values in white matter (WM) in the bilateral precentral gyrus, bilateral corona radiata, bilateral middle corpus callosum, left occipital lobe, and right superior parietal lobule. The spatial distribution of the regions with reduced RK was similar to those with decreased MK. No significant AK difference was found between groups. The correlation analysis revealed significant associations between DKI metrics and clinical assessments such as ALSFRS-R score and disease duration. Additionally, several WM regions showed between-group differences in conventional diffusion metrics; but the spatial extent was smaller than that with reduced DKI metrics.

DATA CONCLUSION

The reduction in DKI metrics indicates decreased microstructural complexity in ALS, involving both motor-related areas and extramotor regions. DKI metrics can serve as potential biomarkers for assessing disease severity.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:554-562.

Decreased Mean Kurtosis in the Putamen is a Diagnostic Feature of Minimal Hepatic Encephalopathy in Patients with Cirrhosis

Objective To prevent the development of overt hepatic encephalopathy, the early intervention for minimal hepatic encephalopathy (MHE) based on an accurate diagnosis is essential. This study investigated whether or not magnetic resonance diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) could detect brain microstructure abnormalities in MHE. The aim was to confirm whether or not brain microstructure abnormalities detected by magnetic resonance (MR) imaging could be used for the diagnosis of MHE. Methods Thirty-two subjects were prospectively examined with a 3-T MR scanner. Tract-based spatial statistics and region of interest analyses of diffusion imaging were performed to compare the mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) values between patients with and without minimal hepatic encephalopathy. The diagnostic performance for the detection of MHE was assessed with a receiver operating characteristic analysis. Results Ten subjects were diagnosed with MHE by neuropsychological testing. After the exclusion of unsuitable subjects, we analyzed 9 subjects with MHE and 14 without MHE. The patients with MHE had a reduced MK in the widespread white matter. We also found significant decreases in the MK in the caudate nucleus, putamen, globus pallidus, and/or thalamus in the subjects with MHE. The MK in the putamen showed the best diagnostic performance for differentiating the subjects with MHE from those without MHE (cut-off value, 0.74; sensitivity, 0.89; specificity, 0.86). Conclusion DKI detects changes in the cerebral white matter and basal ganglia regions of patients with MHE more sensitively than DTI. The MK values in the putamen can be a useful marker for diagnosing MHE from cirrhotic patients without MHE.

Microstructural brain abnormalities correlate with neurocognitive dysfunction in minimal hepatic encephalopathy: a diffusion kurtosis imaging study

PURPOSE

To investigate the diffusion kurtosis imaging (DKI) in early minimal hepatic encephalopathy (MHE) diagnosis and evaluate the correlations between changes in DKI metrics and cognitive performance.

METHODS

We enrolled 116 cirrhosis patients, divided into non-HE (n = 61) and MHE (n = 55), and 46 normal controls (NCs). All patients underwent cognitive testing before magnetic resonance imaging. DKI metrics were calculated through whole-brain voxel-based analysis (VBA) and differences between the groups were assessed. Pearson correlation between the DKI metrics and cognitive performance was analysed. The receiver operating characteristic (ROC) curve was used to analyse the diagnostic efficiency of DKI metrics for MHE.

RESULTS

MHE patients had significantly altered DKI metrics in a wide range of regions; lower fractional anisotropy (FA) and higher mean diffusivity (MD) are mainly located in the corpus callosum, left temporal white matter (WM), and right medial frontal WM. Furthermore, significantly altered kurtosis metrics included lower mean kurtosis (MK) in the corpus callosum and left thalamus, lower radial kurtosis (RK) in the corpus callosum, and lower axial kurtosis (AK) in the right anterior thalamic radiation. Alterations in axial diffusivity (AD), radial diffusivity (RD), and MD were closely correlated with cognitive scores. The ROC curves indicated AD in the forceps minor had the highest predictive performance for MHE in the cirrhosis patients (area under curve = 0.801, sensitivity = 77.05%, specificity = 74.55%).

CONCLUSIONS

Altered DKI metrics indicate brain microstructure abnormalities in MHE patients, some of which may be used as neuroimaging markers for early MHE diagnosis.

Transcranial magnetic resonance-guided focused ultrasound surgery at 1.5T: a technical note

Magnetic resonance-guided focused ultrasound is one of the emerging non-invasive technologies offering both image guidance and thermal monitoring. In recent years transcranial application of this technology is starting to impact heavily the neuroscience field. We present here the imaging protocol and the technological methods successfully used with a transcranial magnetic resonance-guided focused ultrasound system certified for clinical treatments of functional neurological disorders, integrated for the first time with a 1.5T magnetic resonance scanner. Compared to the body radiofrequency coil (the one commonly used with transcranial magnetic resonance-guided focused ultrasound system integrated with 3T magnetic resonance scanners), the use of a dedicated two channel coil enabled a signal-to-noise ratio gain up to five times higher.

An evidence-based approach to assess the accuracy of diffusion kurtosis imaging in characterization of gliomas

OBJECTIVE

Accurate and noninvasive pathologic grading of glioma patients before surgery was crucial to guiding clinicians to select appropriate treatment and improve patient prognosis. This study was performed to investigate the potential diagnostic value of diffusion kurtosis imaging (DKI) to distinguish high-grade gliomas (HGGs) from low-grade gliomas (LGGs) based on an evidence-based approach.

METHODS

Relevant articles that used DKI to distinguish HGG from LGG in Embase, PubMed, China Knowledge Resource Integrated database (CNKI), Web of Knowledge, and Cochrane Libraries databases were electronically searched to April 31, 2018 by 2 reviewers. All analysis was performed by using Meta-disc1.4 and Stata. Influence factors on the diagnostic accuracy were evaluated using meta-regression analysis.

RESULTS

Five eligible studies were included in this meta-analysis. The pooled sensitivity (SEN) and specificity (SPE) was 91% (confidence interval [CI]: 0.78-0.96; P = .02) and 91% (CI: 0.80-0.97; P = .01). The pooled data showed that diagnostic odds ratio (DOR) of DKI was 79.75 (CI: 31.57-201.45). The area under the curve (AUC) of summary receiver operating characteristic curve was 0.96. There is no evidence that our research has a threshold effect (Spearman correlation coefficient: 0.300, P = .624) and publication bias. Meta regression analysis identified that country, language, field strength, and parameter of magnetic resonance imaging had no significant effect on diagnostic performance.

CONCLUSION

The present meta-analysis shows that the mean kurtosis values derived from DKI may be useful in characterization of gliomas with high sensitivity and specificity. Taken into consideration the small sample of this study, we need to be cautious when interpreting the results of this study.

Value of diffusion kurtosis imaging in assessing low-grade gliomas

BACKGROUND

Diffusion kurtosis imaging (DKI) measures have been shown to provide increased sensitivity relative to diffusion tensor imaging (DTI) in detecting pathologies.

PURPOSE

To compare the sensitivity of DKI-derived kurtosis and diffusion maps for assessment of low-grade gliomas (LGG).

STUDY TYPE

Prospective study.

POPULATION

In all, 19 LGG patients and 26 healthy control subjects were recruited.

FIELD STRENGTH/SEQUENCE

Echo-planar-imaging diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner.

ASSESSMENT

Maps for mean, axial, and radial diffusivity (MD, AD, and RD) and kurtosis (MK, AK, and RK), and fractional anisotropy (FA) were evaluated in the tumor, perilesional white matter, and contralateral normal-appearing white matter regions.

STATISTICAL TESTING

General linear models (GLM), Cohen's d for effect size estimates, false discovery rate (FDR) for multiple corrections, Cochran Q-test.

RESULTS

Pairwise differences were observed for all diffusion and kurtosis measures between the studied regions (FDR P < 0.001), except an FA map that failed to show significant differences between the lesion and perilesional white matter (FDR P = 0.373). Effect size analysis showed that kurtosis metrics were found to be 18.8% (RK, P = 0.144) to 29.1% (AK, P < 0.05) more sensitive in discriminating perilesional regions from the lesion than corresponding diffusion metrics, whereas AK provided a 25.0% (P < 0.05) increase in sensitivity in discriminating perilesional and contralateral white matter. RK was found to be the most sensitive to contralateral white matter differences between low-grade gliomas and controls, with MK and RK providing a significantly greater sensitivity of 587.2% (P < 0.001) and 320.7% (P < 0.001) than MD and RD, respectively.

DATA CONCLUSION

Kurtosis maps showed increased sensitivity, as compared to counterpart diffusion maps, for evaluation of microstructural changes in gliomas with a 3-6-fold increment in assessing changes in contralateral white matter.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;48:1551-1558.

Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain

PURPOSE

To compare estimates for the diffusional kurtosis in brain as obtained from a cumulant expansion (CE) of the diffusion MRI (dMRI) signal and from q-space (QS) imaging.

THEORY AND METHODS

For the CE estimates of the kurtosis, the CE was truncated to quadratic order in the b-value and fit to the dMRI signal for b-values from 0 up to 2000s/mm². For the QS estimates, b-values ranging from 0 up to 10,000s/mm² were used to determine the diffusion displacement probability density function (dPDF) via Stejskal's formula. The kurtosis was then calculated directly from the second and fourth order moments of the dPDF. These two approximations were studied for in vivo human data obtained on a 3T MRI scanner using three orthogonal diffusion encoding directions.

RESULTS

The whole brain mean values for the CE and QS kurtosis estimates differed by 16% or less in each of the considered diffusion encoding directions, and the Pearson correlation coefficients all exceeded 0.85. Nonetheless, there were large discrepancies in many voxels, particularly those with either very high or very low kurtoses relative to the mean values.

CONCLUSION

Estimates of the diffusional kurtosis in brain obtained using CE and QS approximations are strongly correlated, suggesting that they encode similar information. However, for the choice of b-values employed here, there may be substantial differences, depending on the properties of the diffusion microenvironment in each voxel.

Comprehensive analysis of early fractional anisotropy changes in acute ischemic stroke

BACKGROUND AND PURPOSE

Cerebral ischemia leads to a rapid decrease of the apparent diffusion coefficient. For fractional anisotropy both increase and decrease have been reported in acute ischemic stroke. Aim of this study was to characterize early water diffusion changes in a homogenous group of acute stroke patients and to clarify the issue of early fractional anisotropy changes and their relation to time from symptom onset.

METHODS

MRI data of patients with acute ischemic stroke examined by diffusion tensor imaging within 8h after symptom were analyzed. We calculated fractional anisotropy, eigenvalues and the isotropic and anisotropic components of the diffusion tensor. The values were calculated as ratios between the ischemic lesion and a mirror region in the unaffected side and correlated with clinical parameters.

RESULTS

We included 63 patients: 49% female, mean age 69 ± 14 years, median NIHSS on admission 9 (IQR 4-14). For the whole sample, mean fractional anisotropy was increased (ratio: 1.083 ± 0.168), while all other diffusion parameters were decreased. Both the isotropic and anisotropic component of the diffusion tensor were decreased with a more pronounced decrease of the isotropic component (ratios: isotropic = 0.730 ± 0.106, anisotropic = 0.788 ± 0.127; p<0.001). There was no correlation of fractional anisotropy with time from symptom onset. Looking at individual patients, fractional anisotropy was increased in 70%. There were no differences in clinical characteristics between patients with increased and decreased fractional anisotropy.

CONCLUSION

Fractional anisotropy increase in acute stroke results from a more pronounced decrease of the isotropic diffusion component and is not related to time from symptom onset. Thus, fractional anisotropy is not helpful as a surrogate marker of lesion age in the very first hours of stroke.

Quantitative diffusion tensor imaging analysis does not distinguish pediatric canines with mucopolysaccharidosis I from control canines

Purpose We compared fractional anisotropy and radial diffusivity measurements between pediatric canines affected with mucopolysaccharidosis I and pediatric control canines. We hypothesized that lower fractional anisotropy and higher radial diffusivity values, consistent with dysmyelination, would be present in the mucopolysaccharidosis I cohort. Methods Six canine brains, three affected with mucopolysaccharidosis I and three unaffected, were euthanized at 7 weeks and imaged using a 7T small-animal magnetic resonance imaging system. Average fractional anisotropy and radial diffusivity values were calculated for four white-matter regions based on 100 regions of interest per region per specimen. A 95% confidence interval was calculated for each mean value. Results No difference was seen in fractional anisotropy or radial diffusivity values between mucopolysaccharidosis affected and unaffected brains in any region. In particular, the 95% confidence intervals for mucopolysaccharidosis affected and unaffected canines frequently overlapped for both fractional anisotropy and radial diffusivity measurements. In addition, in some brain regions a large range of fractional anisotropy and radial diffusivity values were seen within the same cohort. Conclusion The fractional anisotropy and radial diffusivity values of white matter did not differ between pediatric mucopolysaccharidosis affected canines and pediatric control canines. Possible explanations include: (a) a lack of white matter tissue differences between mucopolysaccharidosis affected and unaffected brains at early disease stages; (b) diffusion tensor imaging does not detect any existing differences; (c) inflammatory processes such as astrogliosis produce changes that offset the decreased fractional anisotropy values and increased radial diffusivity values that are expected in dysmyelination; and (d) our sample size was insufficient to detect differences. Further studies correlating diffusion tensor imaging findings to histology are warranted.

White matter changes in patients with mild traumatic brain injury: MRI perspective

This review focuses on white matter (WM) changes in mild traumatic brain injury (mTBI) as assessed by multimodal MRI. All the peer reviewed publications on WM changes in mTBI from January 2011 through September 2016 are included in this review. This review is organized as follows: introduction to mTBI, the basics of multimodal MRI techniques that are potentially useful for probing the WM integrity, summary and critical evaluation of the published literature on the application of multimodal MRI techniques to assess the changes of WM in mTBI, and correlation of MRI measures with behavioral deficits. The MRI–pathology correlation studies based on preclinical models of mTBI are also reviewed. Finally, the author's perspective of future research directions is described.

Functional MRI vs. navigated TMS to optimize M1 seed volume delineation for DTI tractography. A prospective study in patients with brain tumours adjacent to the corticospinal tract

BACKGROUND

DTI-based tractography is an increasingly important tool for planning brain surgery in patients suffering from brain tumours. However, there is an ongoing debate which tracking approaches yield the most valid results. Especially the use of functional localizer data such as navigated transcranial magnetic stimulation (nTMS) or functional magnetic resonance imaging (fMRI) seem to improve fibre tracking data in conditions where anatomical landmarks are less informative due to tumour-induced distortions of the gyral anatomy. We here compared which of the two localizer techniques yields more plausible results with respect to mapping different functional portions of the corticospinal tract (CST) in brain tumour patients.

METHODS

The CSTs of 18 patients with intracranial tumours in the vicinity of the primary motor area (M1) were investigated by means of deterministic DTI. The core zone of the tumour-adjacent hand, foot and/or tongue M1 representation served as cortical regions of interest (ROIs). M1 core zones were defined by both the nTMS hot-spots and the fMRI local activation maxima. In addition, for all patients, a subcortical ROI at the level of the inferior anterior pons was implemented into the tracking algorithm in order to improve the anatomical specificity of CST reconstructions. As intra-individual control, we additionally tracked the CST of the hand motor region of the unaffected, i.e., non-lesional hemisphere, again comparing fMRI and nTMS M1 seeds. The plausibility of the fMRI-ROI- vs. nTMS-ROI-based fibre trajectories was assessed by a-priori defined anatomical criteria. Moreover, the anatomical relationship of different fibre courses was compared regarding their distribution in the anterior-posterior direction as well as their location within the posterior limb of the internal capsule (PLIC).

RESULTS

Overall, higher plausibility rates were observed for the use of nTMS- as compared to fMRI-defined cortical ROIs (p < 0.05) in tumour vicinity. On the non-lesional hemisphere, however, equally good plausibility rates (100%) were observed for both localizer techniques. fMRI-originated fibres generally followed a more posterior course relative to the nTMS-based tracts (p < 0.01) in both the lesional and non-lesional hemisphere.

CONCLUSION

NTMS achieved better tracking results than fMRI in conditions when the cortical tract origin (M1) was located in close vicinity to a brain tumour, probably influencing neurovascular coupling. Hence, especially in situations with altered BOLD signal physiology, nTMS seems to be the method of choice in order to identify seed regions for CST mapping in patients.

Cerebral hemispheric low-grade glial tumors in children: preoperative anatomic assessment with MRI and DTI

PURPOSE

The aims of this study are to analyze how the nature and the behavior of low-grade glial tumors (LGGT) in children may correlate with the anatomy of the cerebral hemispheres and to evaluate the consequent impact of diffusion tensor imaging (DTI) techniques in the presurgical assessment.

METHODS

This is a combined review of a series of 155 cases of LGGT and of the recent literature on the subject.

RESULTS

The cases retrieved from our data bank were divided in central hemispheric tumors (basal ganglia and thalami) (36 cases), glioneuronal cortical-based tumors (49 cases), and glial tumors of the cerebral mantle (70 cases). A close correlation was found in the thalamus between the primary location of the tumor (juxta-ventricular, inferior, lateral, bilateral) and its extension (ventricular lumen, midbrain and mesial temporal, globus pallidus, respectively) which may relate to the connectivity. Among the glioneuronal tumors, most gangliogliomas were located in the temporal lobe and especially in the mesial temporal structures. In addition, the morphologic feature of the ganglioglioma was different there from the neocortical areas. As a complementary approach, DTI data may assist in evaluating the structure and the extension of the LGGT, in addition to planning the surgical strategy.

CONCLUSIONS

In the cerebral hemispheres like in the rest of the central nervous system, there is some degree of correlation between the anatomy and the nature, appearance, and behavior of the LGGT in children.