Advances in DTI studies for diagnoses and treatment of obsessive-compulsive disorder

This review summarizes the current state of neuroimaging research on obsessive-compulsive disorder (OCD) using diffusion tensor imaging (DTI), which allows for the examination of white matter abnormalities in the brain. DTI studies on individuals with obsessive-compulsive disorder (OCD) consistently demonstrate widespread reductions in white matter integrity in various regions of the brain, including the corpus callosum, anterior and posterior cingulate cortex, and prefrontal cortex, which are involved in emotion regulation, decision-making, and cognitive control. However, the reviewed studies often have small sample sizes, and findings vary between studies, highlighting the need for larger and more standardized studies. Furthermore, discerning between causal and consequential effects of OCD on white matter integrity poses a challenge. Addressing this issue may be facilitated through longitudinal studies, including those evaluating the impact of treatment interventions, to enhance the accuracy of DTI data acquisition and processing, thereby improving the validity and comparability of study outcomes. In summary, DTI studies provide valuable insights into the neural circuits and connectivity disruptions in OCD, and future studies may benefit from standardized data analysis and larger sample sizes to determine whether structural abnormalities could be potential biomarkers for early identification and treatment of OCD.

Multi-modal morphometric association study of subclinical depressive symptoms using voxel-based morphometry, cortical thickness, and diffusion tensor imaging (DTI)

BACKGROUND

Case-control studies in major depression have established numerous regional grey and white matter effects in fronto-limbic brain regions. Yet, brain structural studies of dimensional depressive psychopathology within the subclinical spectrum are still limited, in particular for multi-modal imaging approaches.

METHODS

Using voxel-based and surface-based morphometry (cortical thickness) in combination with diffusion tensor imaging (DTI) in a large non-clinical sample (N = 300), we correlated grey and white matter structural variation with subclinical depressive symptoms assessed with Beck's Depression inventory (BDI).

RESULTS

We found a significant decrease of axial diffusivity associated with higher BDI scores in the left hippocampal part of the cingulum bundle (p < 0.05, threshold free cluster enhanced [TFCE] p-value) and some grey matter trend results e.g., a non-linear negative correlation of cortical thickness with depressive symptom load in the right pre/postcentral cortex (pFWE = 0.054, family wise error [FWE] peak level corrected) and a trend in grey matter volume decrease in women in the inferior frontal gyrus (pFWE = 0.054).

LIMITATIONS

Since all grey matter effects disappear after FWE correction, we assume more stable effects in a larger, less homogenous sample enriched by help-seeking subjects covering a wider range of subclinical psychopathology.

CONCLUSION

Our study adds correlations between single depressive symptoms and brain structure to a growing literature. Since subclinical depression is increasingly recognised to be relevant in our understanding of manifest depression, early detection and identification of potential brain correlates of minor depressive symptoms has the potential to expand and reveal possible biomarkers and early psychological treatment.

Connectome alterations following perinatal deafness in the cat

Following sensory deprivation, areas and networks in the brain may adapt and reorganize to compensate for the loss of input. These adaptations are manifestations of compensatory crossmodal plasticity, which has been documented in both human and animal models of deafness-including the domestic cat. Although there are abundant examples of structural plasticity in deaf felines from retrograde tracer-based studies, there is a lack of diffusion-based knowledge involving this model compared to the current breadth of human research. The purpose of this study was to explore white matter structural adaptations in the perinatally-deafened cat via tractography, increasing the methodological overlap between species. Plasticity was examined by identifying unique group connections and assessing altered connectional strength throughout the entirety of the brain. Results revealed a largely preserved connectome containing a limited number of group-specific or altered connections focused within and between sensory networks, which is generally corroborated by deaf feline anatomical tracer literature. Furthermore, five hubs of cortical plasticity and altered communication following perinatal deafness were observed. The limited differences found in the present study suggest that deafness-induced crossmodal plasticity is largely built upon intrinsic structural connections, with limited remodeling of underlying white matter.

High angular resolution diffusion imaging (HARDI) of porcine menisci: a comparison of diffusion tensor imaging and generalized q-sampling imaging

Background

Diffusion magnetic resonance imaging (MRI) allows for the quantification of water diffusion properties in soft tissues. The goal of this study was to characterize the 3D collagen fiber network in the porcine meniscus using high angular resolution diffusion imaging (HARDI) acquisition with both diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI).

Methods

Porcine menisci (n=7) were scanned ex vivo using a three-dimensional (3D) HARDI spin-echo pulse sequence with an isotropic resolution of 500 µm at 7.0 Tesla. Both DTI and GQI reconstruction techniques were used to quantify the collagen fiber alignment and visualize the complex collagen network of the meniscus. The MRI findings were validated with conventional histology.

Results

DTI and GQI exhibited distinct fiber orientation maps in the meniscus using the same HARDI acquisition. We found that crossing fibers were only resolved with GQI, demonstrating the advantage of GQI over DTI to visualize the complex collagen fiber orientation in the meniscus. Furthermore, the MRI findings were consistent with conventional histology.

Conclusions

HARDI acquisition with GQI reconstruction more accurately resolves the complex 3D collagen architecture of the meniscus compared to DTI reconstruction. In the future, these technologies have the potential to nondestructively assess both normal and abnormal meniscal structure.

An exploratory study on the association between blood-based biomarkers and subacute neurometabolic changes following mild traumatic brain injury

BACKGROUND AND OBJECTIVES

Blood-based biomarkers and advanced neuroimaging modalities such as magnetic resonance spectroscopy (MRS) or diffusion tensor imaging (DTI) have enhanced our understanding of the pathophysiology of mild traumatic brain injury (mTBI). However, there is limited published data on how blood biomarkers relate to neuroimaging biomarkers post-mTBI.

METHODS

To investigate this, 30 patients with mTBI and 21 healthy controls were enrolled. Data was collected at two timepoints postinjury: acute, < 24 h, (blood) and subacute, four-to-six weeks, (blood and imaging). Interleukin (IL) 6 and 10 (inflammation), free thiols (systemic oxidative stress) and neurofilament light (NF-L) (axonal injury) were quantified in plasma. The neurometabolites total N-acetyl aspartate (tNAA) (neuronal energetics), Myo-Inositol (Ins) and total Choline (tCh) (inflammation) and, Glutathione (GSH, oxidative stress) were quantified using MRS.

RESULTS

Concentrations of IL-6 and IL-10 were significantly elevated in the acute phase post-mTBI, while NF-L was elevated only in the subacute phase. Total NAA was lowered in patients with mTBI, although this difference was only nominally significant (uncorrected P < 0.05). Within the patient group, acute IL-6 and subacute tNAA levels were negatively associated (r =  - 0.46, uncorrected-P = 0.01), albeit not at a threshold corrected for multiple testing (corrected-P = 0.17). When age was added as a covariate a significant increase in correlation magnitude was observed (ρ =  - 0.54, corrected-P = 0.03).

CONCLUSION

This study demonstrates potential associations between the intensity of the inflammatory response in the acute phase post-mTBI and neurometabolic perturbations in the subacute phase. Future studies should assess the longitudinal dynamics of blood-based and imaging biomarkers after injury.

Structural interhemispheric connectivity defects in mouse models of BBSOAS: Insights from high spatial resolution 3D white matter tractography

White matter (WM) tract formation and axonal pathfinding are major processes in brain development allowing to establish precise connections between targeted structures. Disruptions in axon pathfinding and connectivity impairments will lead to neural circuitry abnormalities, often associated with various neurodevelopmental disorders (NDDs). Among several neuroimaging methodologies, Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) technique that has the advantage of visualizing in 3D the WM tractography of the whole brain non-invasively. DTI is particularly valuable in unpinning structural tract connectivity defects of neural networks in NDDs. In this study, we used 3D DTI to unveil brain-specific tract defects in two mouse models lacking the Nr2f1 gene, which mutations in patients have been proven to cause an emerging NDD, called Bosch-Boonstra-Schaaf Optic Atrophy (BBSOAS). We aimed to investigate the impact of the lack of cortical Nr2f1 function on WM morphometry and tract microstructure quantifications. We found in both mutant mice partial loss of fibers and severe misrouting of the two major cortical commissural tracts, the corpus callosum, and the anterior commissure, as well as the two major hippocampal efferent tracts, the post-commissural fornix, and the ventral hippocampal commissure. DTI tract malformations were supported by 2D histology, 3D fluorescent imaging, and behavioral analyses. We propose that these interhemispheric connectivity impairments are consistent in explaining some cognitive defects described in BBSOAS patients, particularly altered information processing between the two brain hemispheres. Finally, our results highlight 3DDTI as a relevant neuroimaging modality that can provide appropriate morphometric biomarkers for further diagnosis of BBSOAS patients.

Dynamic monitoring of radiation-induced white matter microstructure injury in nasopharyngeal carcinoma via high-angular resolution diffusion imaging

PURPOSE

To investigate white matter microstructural abnormalities caused by radiotherapy in nasopharyngeal carcinoma (NPC) patients using MRI high-angular resolution diffusion imaging (HARDI).

METHODS

We included 127 patients with pathologically confirmed NPC: 36 in the pre-radiotherapy group, 29 in the acute response period (post-RT-AP), 23 in the early delayed period (post-RT-ED) group, and 39 in the late-delayed period (post-RT-LD) group. HARDI data were acquired for each patient, and dispersion parameters were calculated to compare the differences in specific fibre bundles among the groups. The Montreal Neurocognitive Assessment (MoCA) was used to evaluate neurocognitive function, and the correlations between dispersion parameters and MoCA were analysed.

RESULTS

In the right cingulum frontal parietal bundles, the fractional anisotropy value decreased to the lowest level post-RT-AP and then reversed and increased post-RT-ED and post-RT-LD. The mean, axial, and radial diffusivity were significantly increased in the post-RT-AP (p < 0.05) and decreased in the post-RT-ED and post-RT-LD groups to varying degrees. MoCA scores were decreased post-radiotherapy than those before radiotherapy (p = 0.005). MoCA and mean diffusivity exhibited a mild correlation in the left cingulum frontal parahippocampal bundle.

CONCLUSIONS

White matter tract changes detected by HARDI are potential biomarkers for monitoring radiotherapy-related brain damage in NPC patients.

Diffusion Imaging of the Spinal Cord: Clinical Applications

Spinal cord pathologic condition often presents as a neurologic emergency where timely and accurate diagnosis is critical to expedite appropriate treatment and minimize severe morbidity and even mortality. MR imaging is the gold standard imaging technique for diagnosing patients with suspected spinal cord pathologic condition. This review will focus on the basic principles of diffusion imaging and how spinal anatomy presents technical challenges to its application. Both the promises and shortcomings of spinal diffusion imaging will then be explored in the context of several clinical spinal cord pathologies for which diffusion has been evaluated.

Diagnostic efficacy of tract-specific diffusion tensor imaging in cervical spondylotic myelopathy with electrophysiological examination validation

PURPOSE

This study aimed to investigate the effectiveness of tract-specific diffusion tensor imaging (DTI) metrics in identifying the responsible segments for neurological dysfunction in cervical spondylotic myelopathy (CSM).

METHODS

The study encompassed nineteen participants diagnosed with CSM, including 10 males and 9 females. Additionally, a control group consisting of ten healthy caregivers (5 males and 5 females) were recruited with no symptoms and no compressions on magnetic resonance imaging (MRI). All participants underwent a comprehensive physical examination, MRI assessment, and DTI examination conducted by a senior chief physician. Several parameters were collected from the MR images, including the aspect ratio (defined as the anteroposterior diameter / the transverse diameter of the corresponding segment's spinal cord), transverse ratio (defined as the transverse diameter of the corresponding segment's spinal cord / the transverse diameter of the spinal cord at C2/3), and T2 high signal of the spinal cord. Furthermore, quantitative DTI metrics, such as axial diffusivity (AD), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA), were calculated using automatic region-of-interest (ROI) analysis for both whole spinal cord column and dorsal column. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic efficacy of the aspect ratio, transverse ratio, and DTI parameters. The area under the curve (AUC), sensitivity, and specificity were calculated. Intraoperative spinal cord electrophysiological examination was performed as the objective measure of spinal cord function during surgery.

RESULTS

As determined by electrophysiological examination, neurological dysfunction was found in 2 patients due to C3/4 compression, in 10 patients due to C4/5 compression, in 6 patients due to C5/6 compression, and in 1 patient due to C6/7 compression. The modified Japanese Orthopedic Association scale (mJOA) was 12.71 ± 1.55 in the CSM group, with 4.87 ± 0.72 for sensory nerve function and 5.05 ± 1.35 for motor nerve function. For the control group, none of the volunteers had neurological dysfunction. T2 high signal was found at the most stenotic segment in 13 patients of the CSM group. Considering all the cervical segments, the aspect ratio (AUC = 0.823, P = 0.001, Sensitivity = 68.42%, Specificity = 82.47%) was more capable of determining the responsible segment than transverse ratio (AUC = 0.661, P = 0.027, Sensitivity = 68.42%, Specificity = 67.01%). AD, MD, and RD were significantly higher while FA was significantly lower in the responsible segment than in the irresponsible segment (P < 0.05). The AUC of DTI-Dorsal column parameters (AD, MD, RD, FA) was larger than the corresponding parameters of the DTI (Whole spinal cord). AD of DTI-Dorsal Column possessed the greatest efficacy (AUC = 0.823, sensitivity = 84.21%, specificity = 77.32%) to determine the responsible segment, larger than AD of DTI-Whole spinal cord (AUC = 0.822, P = 0.001, Sensitivity = 89.47%, Specificity = 77.32%), aspect ratio (AUC = 0.823, P = 0.001, Sensitivity = 68.42%, Specificity = 82.47%) and transverse ratio (AUC = 0.661, P = 0.027, Sensitivity = 68.42%, Specificity = 67.01%). Subgroup analysis revealed that the diagnostic efficacy of DTI and MRI parameters was influenced by cervical spine segment.

CONCLUSIONS

When considering all cervical segments, AD from the DTI-Dorsal Column exhibited the most significant potential in identifying responsible segments. This potential was found to be superior to that of DTI-Whole spinal cord, aspect ratio, the most stenotic segment, T2 high signals, transverse ratio, motor nerve dysfunction, and sensory nerve dysfunction. The diagnostic effectiveness of both DTI and MRI parameters was notably influenced by the specific cervical spine segment.

Impact of truncating diffusion MRI scans on diffusional kurtosis imaging

OBJECTIVE

Diffusional kurtosis imaging (DKI) extends diffusion tensor imaging (DTI), characterizing non-Gaussian diffusion effects but requires longer acquisition times. To ensure the robustness of DKI parameters, data acquisition ordering should be optimized allowing for scan interruptions or shortening. Three methodologies were used to examine how reduced diffusion MRI scans impact DKI histogram-metrics: 1) the electrostatic repulsion model (OptEEM); 2) spherical codes (OptSC); 3) random (RandomTRUNC).

MATERIALS AND METHODS

Pre-acquired diffusion multi-shell data from 14 female healthy volunteers (29±5 years) were used to generate reordered data. For each strategy, subsets containing different amounts of the full dataset were generated. The subsampling effects were assessed on histogram-based DKI metrics from tract-based spatial statistics (TBSS) skeletonized maps. To evaluate each subsampling method on simulated data at different SNRs and the influence of subsampling on in vivo data, we used a 3-way and 2-way repeated measures ANOVA, respectively.

RESULTS

Simulations showed that subsampling had different effects depending on DKI parameter, with fractional anisotropy the most stable (up to 5% error) and radial kurtosis the least stable (up to 26% error). RandomTRUNC performed the worst while the others showed comparable results. Furthermore, the impact of subsampling varied across distinct histogram characteristics, the peak value the least affected (OptEEM: up to 5% error; OptSC: up to 7% error) and peak height (OptEEM: up to 8% error; OptSC: up to 11% error) the most affected.

CONCLUSION

The impact of truncation depends on specific histogram-based DKI metrics. The use of a strategy for optimizing the acquisition order is advisable to improve DKI robustness to exam interruptions.

Association of white matter microstructural alteration with non-suicidal self-injury behavior and visual working memory in adolescents with borderline personality disorder

BACKGROUND

Non-suicidal self-injurious behavior (NSSI) is the core characteristic of adolescent borderline personality disorder (BPD) and visual working memory is involved in the pathological processes of BPD. This study aimed to investigate alterations in white matter microstructure and their association with NSSI and visual working memory in adolescents with BPD.

METHODS

53 adolescents diagnosed with BPD and 39 healthy controls (HCs) were enrolled. White matter microstructure was assessed with the fractional anisotropy (FA) and mean diffusivity (MD) from diffusion tensor imaging (DTI). Correlation analysis was performed to assess the association between FA/MD and core features of BPD. A mediation analysis was performed to test whether the effects of white matter alterations on NSSI could be mediated by visual working memory.

RESULTS

Adolescents with BPD showed a reduced FA and an increased MD in the cortical-limbic and cortical-thalamus circuit when compared to the HCs (p < 0.05). Increased MD was positively correlated with NSSI, impulse control and identity disturbance (p < 0.05), and was negatively correlated with the score of visual reproduction. Reserved visual working memory masked the effects of white matter microstructural alterations on NSSI behavior.

CONCLUSIONS

White matter microstructural deficits in the cortical-limbic and cortical-thalamus circuits may be associated with NSSI and visual working memory in adolescents with BPD. Reserved visual working memory may protect against NSSI.

Diffusion tensor imaging changes of the cortico-thalamic-striatal tracts correlate with fatigue and disability in people with relapsing-remitting MS

PURPOSE

To investigate how the microstructural neural integrity of cortico-thalamic-striatal (CTS) tracts correlate with fatigue and disability over time. The primary outcome was diffusion tensor imaging (DTI) metrics change over time, and the secondary outcome was correlations with fatigue and disability in people with RRMS (pw-RRMS).

METHODS

76 clinically stable pw-RRMS and 43 matched healthy controls (HCs). The pw-RRMS cohort consisted of three different treatment subgroups. All participants underwent disability, cognitive, fatigue and mental health assessments. Structural and diffusion scans were performed at baseline (BL) and 2-year follow-up (2-YFU) for all participants. Fractional anisotropy (FA), mean, radial and axial diffusivities (MD, RD, AD) of normal-appearing white matter (NAWM) and white matter lesion (WML) in nine tracts-of-interests (TOIs) were estimated using our MRtrix3 in-house pipeline.

RESULTS

We found significant BL and 2-YFU differences in most diffusion metrics in TOIs in pw-RRMS compared to HCs (pFDR ≤ 0.001; false-detection-rate (FDR)-corrected). There was a significant decrease in WML diffusivities and an increase in FA over the follow-up period in most TOIs (pFDR ≤ 0.001). Additionally, there were no differences in DTI parameters across treatment groups. AD and MD were positively correlated with fatigue scores (r ≤ 0.33, p ≤ 0.01) in NAWM-TOIs, while disability (EDSS) was negatively correlated with FA in most NAWM-TOIs (|r|≤0.31, p ≤ 0.01) at both time points. Disability scores correlated with all diffusivity parameters (r ≤ 0.29, p ≤ 0.01) in most WML-TOIs at both time points.

CONCLUSION

Statistically significant changes in diffusion metrics in WML might be indicative of integrity improvement over two years in CTS tracts in clinically stable pw-RRMS. This finding represents structural changes within lesioned tracts. Measuring diffusivity in pw-RRMS affected tracts might be a relevant measure for future remyelination clinical trials.

Diffusion spectrum imaging based semi-automatic optic radiation tractography for vision preservation in SEEG-guided radiofrequency thermocoagulation

OBJECTIVE

To assess the efficacy and safety of stereoelectroencephalography (SEEG)-guided radiofrequency thermocoagulation (RFTC), using diffusion spectrum imaging (DSI) tractography to preoperatively delineate the optic radiation (OR) and reduce the risk of visual field defects (VFDs) where the epileptogenic zones (EZs) are located in or close to the eloquent visual areas.

METHODS

We prospectively followed up twenty-four consecutive patients (12 males and 12 females) who underwent SEEG-guided RFTC in or near the OR pathway. A distance of ≥ 3.5 mm away from the OR on the targeted electrodes contacts that exhibited relevant ictal onset patterns, IEDs and EES during SEEG recordings, was required as our selection criterion prior to performing RFTC, enough to theoretically prevent VFDs. Using default tracking parameters, the optic radiation was tracked semi-automatically in DSI-studio.

RESULTS

There were 12 male and 12 female patients ranging in age from 6 to 57 years, with follow-up period ranging from 6 to 37 months. Nineteen patients responded to RFTC (R+, 79.16 %), and 5 patients did not benefit from RFTC (R-, 20.83 %). The preoperative application of DSI semi-automatic based OR tractography was successful in the protection of the OR in all 24 patients. Three patients experienced a neurologic deficit following RFTC, and five patients had a partial quadrant visual field deficit prior to surgery that did not worsen, and none of the remaining nineteen patients had a quadrant visual field deficit.

CONCLUSION

Our study validates the safety and efficacy of SEEG-RFTC as a viable therapeutic approach for epileptic foci situated in or adjacent to the visual eloquent regions. We demonstrate that DSI-based tractography offers superior precision in delineating the OR compared to DTI. We establish that implementing a criterion of a minimum distance of ≥ 3.5 mm in radius from the OR on the targeted electrode contacts prior to conducting RFTC can effectively mitigate the risk of VFDs.

White matter predictors of PTSD: Testing different machine learning models in a sample of Black American women

BACKGROUND

Machine learning neuroimaging studies of posttraumatic stress disorder (PTSD) show promise for identifying neurobiological signatures of PTSD. However, studies to date, have largely evaluated a single machine learning approach, and few studies have examined white matter microstructure as a predictor of PTSD. Further, individuals from minoritized racial groups, specifically, Black individuals, who experience disproportionate trauma frequency, and have relatively higher rates of PTSD, have been underrepresented in these studies. We used four different machine learning models to test white matter microstructure classifiers of PTSD in a sample of trauma-exposed Black American women with and without PTSD.

METHOD

Participants included 45 Black women with PTSD and 89 trauma-exposed controls recruited from an ongoing trauma study. Current PTSD presence was estimated using the Clinician-Administered PTSD Scale. Average fractional anisotropy of 53 white matter tracts served as input features. Additional exploratory analysis incorporated estimates of interpersonal and structural racism exposure. Classification models included linear support vector machine, radial basis function support vector machine, multilayer perceptron, and random forest.

RESULTS

Performance varied notably between models. With white matter features along, linear support vector machine demonstrated the best model fit and reached an average AUC = 0.643. Inclusion of estimates of exposure to racism increased linear support vector machine performance (AUC = 0.808).

CONCLUSIONS

White matter microstructure had limited ability to predict PTSD presence in this sample. These results may indicate that the relationship between white matter microstructure and PTSD may be nuanced across race and gender spectrums.

Assessing traffic-related air pollution-induced fiber-specific white matter degradation associated with motor performance declines in aged rats

Fine particulate matter (PM2.5) is thought to exacerbate Parkinson's disease (PD) in the elderly, and early detection of PD progression may prevent further irreversible damage. Therefore, we used diffusion tensor imaging (DTI) for probing microstructural changes after late-life chronic traffic-related PM2.5 exposure. Herein, 1.5-year-old Fischer 344 rats were exposed to clean air (control), high-efficiency particulate air (HEPA)-filtered ambient air (HEPA group), and ambient traffic-related PM2.5 (PM2.5 group, 9.933 ± 1.021 µg/m3) for 3 months. Rotarod test, DTI tractographic analysis, and immunohistochemistry were performed in the end of study period. Aged rats exposed to PM2.5 exhibited motor impairment with decreased fractional anisotropy and tyrosine hydroxylase expression in olfactory and nigrostriatal circuits, indicating disrupted white matter integrity and dopaminergic (DA) neuronal loss. Additionally, increased radial diffusivity and lower expression of myelin basic protein in PM2.5 group suggested ageing progression of demyelination exacerbated by PM2.5 exposure. Significant production of tumor necrosis factor-α was also observed after PM2.5 exposure, revealing potential inflammation of injury to multiple fiber tracts of DA pathways. Microstructural changes demonstrated potential links between PM2.5-induced inflammatory white matter demyelination and behavioral performance, with indication of pre-manifestation of DTI-based biomarkers for early detection of PD progression in the elderly.

The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis

BACKGROUND

Information processing speed (IPS) deterioration is common in relapsing-remitting multiple sclerosis (RRMS) patients [1] and might severely affect quality of life and occupational activity. However, understanding of its neural substrate is not fully elucidated. We aimed to investigate the associations between MRI-derived metrics of neuroanatomical structures, including the tracts, and IPS.

METHODS

Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), and Color Trails Test (CTT) were used to evaluate IPS in 73 RRMS consecutive patients, all undergoing only interferon beta (IFN-β) therapy during the study. At the same time, 1.5T MRI including diffusion tensor imaging (DTI) data was acquired for each recruited subject. We analyzed volumetric and diffusion MRI measures (FreeSurfer 6.0) including normalized brain volume (NBV), cortical thickness (thk), white matter hypointensities (WMH), volume (vol), diffusion parameters: mean (MD), radial (RD), axial (AD) diffusivities, and fractional anisotropy (FA) of 18 major white-matter (WM) tracts. Multiple linear regression model with interaction resulted in distinguishing the neural substrate of IPS deficit in the IPS impaired subgroup of patients.

RESULTS

The most significant tract abnormalities contributing to IPS deficit were right inferior longitudinal fasciculus (R ILF) FA, forceps major (FMAJ) FA, forceps minor (FMIN) FA, R uncinate fasciculus (UNC) AD, R corticospinal tract (CST) FA, and left superior longitudinal fasciculus FA (L SLFT). Among volumetric MRI metrics, IPS deficit was associated with L and R thalamic vol. and cortical thickness of insular regions.

CONCLUSION

In this study, we showed that disconnection of the selected WM tracts, in addition to cortical and deep gray matter (GM) atrophy, might underlie IPS deficit in RRMS patients but more extensive studies are needed for precise associations.

Stability of longitudinal DTI metrics in MS with treatment of injectables, fingolimod and dimethyl fumarate

BACKGROUND AND PURPOSE

Diffusion MRI (dMRI) is sensitive to microstructural changes in white matter of people with relapse-remitting multiple sclerosis (pw-RRMS) that lead to progressive disability. The role of diffusion in assessing the efficacy of different therapies requires more investigation. This study aimed to evaluate selected dMRI metrics in normal-appearing white matter and white matter-lesion in pw-RRMS and healthy controls longitudinally and compare the effect of therapies given.

MATERIAL AND METHODS

Structural and dMRI scans were acquired from 78 pw-RRMS (29 injectables, 36 fingolimod, 13 dimethyl fumarate) and 43 HCs at baseline and 2-years follow-up. Changes in dMRI metrics and correlation with clinical parameters were evaluated.

RESULTS

Differences were observed in most clinical parameters between pw-RRMS and HCs at both timepoints (p ≤ 0.01). No significant differences in average changes over time were observed for any dMRI metric between treatment groups in either tissue type. Diffusion metrics in NAWM and WML correlated negatively with most cognitive domains, while FA correlated positively at baseline but only for NAWM at follow-up (p ≤ 0.05). FA correlated negatively with disability in NAWM and WML over time, while MD and RD correlated positively only in NAWM.

CONCLUSIONS

This is the first DTI study comparing the effect of different treatments on dMRI parameters over time in a stable cohort of pw-RRMS. The results suggest that brain microstructural changes in a stable MS cohort are similar to HCs independent of the therapies used.

Reliability and validity of DTI-based indirect disconnection measures

White matter connections enable the interaction within and between brain networks. Brain lesions can cause structural disconnections that disrupt networks and thereby cognitive functions supported by them. In recent years, novel methods have been developed to quantify the extent of structural disconnection after focal lesions, using tractography data from healthy controls. These methods, however, are indirect and their reliability and validity have yet to be fully established. In this study, we present our implementation of this approach, in a tool supplemented by uncertainty metrics for the predictions overall and at voxel-level. These metrics give an indication of the reliability and are used to compare predictions with direct measures from patients' diffusion tensor imaging (DTI) data in a sample of 95 first-ever stroke patients. Results show that, except for small lesions, the tool can predict fiber loss with high reliability and compares well to direct patient DTI estimates. Clinical utility of the method was demonstrated using lesion data from a subset of patients suffering from hemianopia. Both tract-based measures outperformed lesion localization in mapping visual field defects and showed a network consistent with the known anatomy of the visual system. This study offers an important contribution to the validation of structural disconnection mapping. We show that indirect measures of structural disconnection can be a reliable and valid substitute for direct estimations of fiber loss after focal lesions. Moreover, based on these results, we argue that indirect structural disconnection measures may even be preferable to lower-quality single subject diffusion MRI when based on high-quality healthy control datasets.

Image data and computational grids for computing brain shift and solving the electrocorticography forward problem

This article describes the dataset applied in the research reported in NeuroImage article "Patient-specific solution of the electrocorticography forward problem in deforming brain" [1] that is available for download from the Zenodo data repository (https://zenodo.org/record/7687631) [2]. Preoperative structural and diffusion-weighted magnetic resonance (MR) and postoperative computed tomography (CT) images of a 12-year-old female epilepsy patient under evaluation for surgical intervention were obtained retrospectively from Boston Children's Hospital. We used these images to conduct the analysis at The University of Western Australia's Intelligent Systems for Medicine Laboratory using SlicerCBM [3], our open-source software extension for the 3D Slicer medical imaging platform. As part of the analysis, we processed the images to extract the patient-specific brain geometry; created computational grids, including a tetrahedral grid for the meshless solution of the biomechanical model and a regular hexahedral grid for the finite element solution of the electrocorticography forward problem; predicted the postoperative MRI and DTI that correspond to the brain configuration deformed by the placement of subdural electrodes using biomechanics-based image warping; and solved the patient-specific electrocorticography forward problem to compute the electric potential distribution within the patient's head using the original preoperative and predicted postoperative image data. The well-established and open-source file formats used in this dataset, including Nearly Raw Raster Data (NRRD) files for images, STL files for surface geometry, and Visualization Toolkit (VTK) files for computational grids, allow other research groups to easily reuse the data presented herein to solve the electrocorticography forward problem accounting for the brain shift caused by implantation of subdural grid electrodes.

Temperature measurement of intracranial cerebrospinal fluid using diffusion tensor imaging after revascularization surgery in Moyamoya disease

OBJECTIVE

Brain temperature monitoring using a catheter thermometer has been reported to be a useful technique to predict prognosis in neurosurgery. To investigate the possibility of measuring intracranial cerebrospinal fluid temperature for postoperative monitoring in patients with Moyamoya disease (MMD) after bypass surgery.

MATERIALS AND METHODS

This study evaluated fifteen patients with MMD who were indicated for bypass surgery. Diffusion tensor imaging for brain thermometry were performed on a 1.5-T MR scanner. Intracranial cerebrospinal fluid temperature with/without considering the fractional anisotropy component, body temperature, C-reactive protein levels, white blood cell count, and cerebral blood flow measured by ¹²³I-IMP single-photon emission computed tomography were obtained before surgery and 1-3 days after surgery. Pixel values considered to be signal outliers in fractional anisotropy processing were defined as cerebrospinal fluid noise index and calculated. Wilcoxon signed-rank test and effect size were performed to compare the changes before and after revascularization. Spearman's rho correlation coefficient was used to analyze the correlations between each parameter. Statistical significance was defined as p < 0.05.

RESULTS

All parameter values became significantly higher compared to those measured before revascularization (p < 0.01 in all cases). The effect sizes were largest for the cerebrospinal fluid temperature with fractional anisotropy processing and for C-reactive protein levels (Rank-biserial correlation = 1.0). The cerebrospinal fluid noise index and cerebrospinal fluid temperatures with fractional anisotropy processing (r = 0.84, p < 0.0001) or without fractional anisotropy processing (r = 0.95, p < 0.0001) showed highly significant positive correlations. Although no significant correlation was observed, cerebrospinal fluid temperatures with fractional anisotropy had small or moderately positive correlations with cerebral blood flow, body temperature, C-reactive protein levels, and white blood cell count (r = 0.37, 0.42, 0.41, and 0.44, respectively; p > 0.05).

CONCLUSION

Our findings suggest the possibility of postoperative monitoring for MMD patients by measuring intracranial cerebrospinal fluid temperature with fractional anisotropy processing. Intracranial cerebrospinal fluid temperature might be considered as combined response since cerebrospinal fluid, body temperature, and inflammation are equally correlated.

Current State of Diffusion-Weighted Imaging and Diffusion Tensor Imaging for Traumatic Brain Injury Prognostication

Advanced imaging techniques are needed to assist in providing a prognosis for patients with traumatic brain injury (TBI), particularly mild TBI (mTBI). Diffusion tensor imaging (DTI) is one promising advanced imaging technique, but has shown variable results in patients with TBI and is not without limitations, especially when considering individual patients. Efforts to resolve these limitations are being explored and include developing advanced diffusion techniques, creating a normative database, improving study design, and testing machine learning algorithms. This article will review the fundamentals of DTI, providing an overview of the current state of its utility in evaluating and providing prognosis in patients with TBI.

Adult lifespan maturation and degeneration patterns in gray and white matter: A mean apparent propagator (MAP) MRI study

The relationship between brain microstructure and aging has been the subject of intense study, with diffusion MRI perhaps the most effective modality for elucidating these associations. Here, we used the mean apparent propagator (MAP)-MRI framework, which is suitable to characterize complex microstructure, to investigate age-related cerebral differences in a cohort of cognitively unimpaired participants and compared the results to those derived using diffusion tensor imaging. We studied MAP-MRI metrics, among them the non-Gaussianity (NG) and propagator anisotropy (PA), and established an opposing pattern in white matter of higher NG alongside lower PA among older adults, likely indicative of axonal degradation. In gray matter, however, these two indices were consistent with one another, and exhibited regional pattern heterogeneity compared to other microstructural parameters, which could indicate fewer neuronal projections across cortical layers along with an increased glial concentration. In addition, we report regional variations in the magnitude of age-related microstructural differences consistent with the posterior-anterior shift in aging paradigm. These results encourage further investigations in cognitive impairments and neurodegeneration.

Diffusion tensor imaging of the brain in Pompe disease

Enzyme replacement therapy has drastically changed prospects of patients with Pompe disease, a progressive metabolic myopathy. As classic infantile patients survive due to treatment, they exhibit progressive white matter abnormalities, while brain involvement in late-onset patients is not fully elucidated. To study the underlying microstructure of white matter, we acquired structural (T1, T2, FLAIR) and diffusion tensor imaging (DTI) of the brain in 12 classic infantile patients (age 5-20 years) and 18 late-onset Pompe patients (age 11-56 years). Structural images were scored according to a rating scale for classic infantile patients. Fractional anisotropy (FA) and mean diffusivity (MD) from classic infantile patients were compared to a reference population, using a Wilcoxon signed-rank, one sample test. Effect sizes (Hedges' G) were used to compare DTI metrics across different tracts. For late-onset patients, results were compared to (reported) tractography data on normal aging. In classic infantile patients, we found a significant lower FA and higher MD (p < 0.01) compared to the reference population. Large-association fibers were most severely affected. Classic infantile patients with advanced white matter abnormalities on structural MRI showed the largest deviations from the reference population. FA and MD were similar for younger and older late-onset patients in large WM-association fibers. We conclude that, while no deviations from typical neurodevelopment were found in late-onset patients, classic infantile Pompe patients showed quantifiable, substantially altered white matter microstructure, which corresponded with disease stage on structural MRI. DTI holds promise to monitor therapy response in future therapies targeting the brain.

HIV peripheral neuropathy-related degeneration of white matter tracts to sensorimotor cortex

Human immunodeficiency virus-associated distal sensory polyneuropathy (HIV-DSP) affects up to 50% of people with HIV and is associated with depression, unemployment, and generally worsened quality of life. Previous work on the cortical mechanism of HIV neuropathy found decreased gray matter volume in the bilateral midbrain, thalamus, and posterior cingulate cortex, but structural connectivity in this context remains under-studied. Here we examine alterations in white matter microstructure using diffusion imaging, hypothesizing that cortical white matter degeneration would be observed in continuation of the peripheral white matter atrophy previously observed in HIV-DSP. Male HIV seropositive patients (n = 57) experiencing varying degrees of HIV neuropathy underwent single-shell diffusion tensor imaging with 51 sampling directions. The scans were pooled using tractography and connectometry to create a quantitative map of white matter tract integrity, measured in generalized fractional anisotropy (GFA). The relationship between GFA and neuropathy severity was evaluated with linear regression. Correction for multiple comparisons was done using false discovery rate (FDR), a statistical method commonly used in genomics and imaging to minimize false positives when thousands of individual comparisons are made. Neuropathy severity was associated with decreased GFA along thalamocortical radiations leading along the lateral thalamus to sensorimotor cortex, with r = -0.405 (p < 0.001; FDR), as well as with the superior bilateral cingulum (r = -0.346 (p < 0.05; FDR)). Among a population of HIV neuropathy patients, greater neuropathy severity was correlated with lower white matter integrity running from midbrain to somatosensory cortex. This suggests ascending deafferentation extending from damaged peripheral nerves further downstream than seen previously, into the axons of third-order neurons. There is also evidence of cingulum degeneration, implying some more complex mechanism beyond the ascending atrophy observed here.

White matter brain changes in chronic pancreatitis: A 7-year longitudinal follow-up study

BACKGROUND/OBJECTIVES

The progression of cerebral white matter changes over time has not been explored in chronic pancreatitis (CP). We aimed to characterize such alterations in individuals with CP at baseline and after 7-years as compared with controls and to explore associations to risk factors and clinical parameters.

METHODS

Diffusion tensor imaging was used to evaluate 20 individuals with CP and 13 healthy controls at baseline and after 7-years (CP: n = 9, controls: n = 11). Tract-based spatial statistics were used to assess whole-brain white matter structure, extract significant fractional anisotropy (FA) clusters between groups, mean FA skeleton, mean FA and mean diffusivity (MD). FA of the extracted significant clusters between groups were used for regression analyses with risk factors and clinical parameters, including duration of CP, smoking, and diabetes.

RESULTS

At baseline, widespread reductions in FA were found in CP compared to controls involving corpus callosum, the anterior, posterior thalamic radiation, and superior and posterior corona radiata (cluster volume: 49,431 mm³, all P < 0.05). At baseline, also the mean FA (P = 0.004) and FA skeleton (P = 0.002) were reduced in CP compared to controls. FA of the extracted significant cluster was associated with the daily tobacco use (P = 0.001) and duration of CP (P = 0.010). At follow-up, the whole-brain FA skeleton was reduced by 1.7% for both CP individuals and controls (P = 0.878).

CONCLUSION

Individuals with CP had widespread cerebral white matter alterations at baseline that can likely be explained by the CP disease and exposure to toxic substances. Otherwise, further progression resembles that in healthy controls.

Evaluating white matter alterations in Parkinson's disease-related parkin S/N167 mutation carriers using tract-based spatial statistics

Background

Genetic susceptibility plays an important role in the pathogenesis of Parkinson’s disease (PD). parkin S/N167 mutations may increase the risk of PD and affect white matter fibers in the brain. This cross-sectional study explored the effects of gene polymorphisms on white matter fiber damage in PD.

Methods

In all, 54 cases were enrolled in the study, including PD patients carrying parkin gene S/N167 mutations (G/A), PD patients without gene S/N167 mutations (G/G), and healthy controls (HC). The whole-brain white matter fiber skeleton was analyzed using the tract-based spatial statistics (TBSS) method. Two-way analysis of variance (ANOVA) and post hoc tests were used for data analyses.

Results

Two classification methods were used; one was based on disease classification, with 26 patients in the PD group (n=12 G/G, n=14 G/A) and 28 in the HC group (n=15 G/G, n=13 G/A), and the other was based on genetic classification, with 27 patients in the G/G group and 27 in the G/A group. In the G/A group, there was a wide range of significant changes in fractional anisotropy (FA), radial diffusivity (RD), and mean diffusivity (MD) values (P<0.05). There was also a significant decrease in FA in the PD-G/A group compared with the PD-G/G and HC-G/A groups (P<0.05).

Conclusions

There were more extensive brain white matter fiber damage and changes in PD patients; the G/A polymorphism may cause more extensive brain white matter damage.

Diffusion Tensor Imaging of the Dentate Nucleus After Repeated Administration of Gadobutrol in Children

This study aimed to investigate possible signal changes in the dentate nucleus (DN) on diffusion tensor imaging (DTI) after administration of gadobutrol in a pediatric cohort. Total of 50 pediatric patients (mean age: 6.2 ± 4.3 years) with normal renal function exposed exclusively to the macrocyclic GBCA (mcGBCA) gadobutrol and 50 age- and sex-matched control patients with nonpathological neuroimaging findings (and no GBCA administration). Mean diffusivity (MD) and fractional anisotropy (FA) values were determined in the DN. A paired t test was performed to compare FA, MD values, and DN-to-middle cerebral peduncle (MCP) T1WI SI ratios between children exposed to gadobutrol and controls. Pearson correlation analysis was conducted to determine any correlation between FA and MD values as well as T1WI SI ratios and confounding parameters. The mean FA values of DN was significantly lower in children with mcGBCA than in the control group (p < 0.001; non-GBCA group, 0.299 ± 0.03; mcGBCA group, 0.254 ± 0.05), but no significant difference of the T1WI SI ratio was noted between the mcGBCA group (0.946 ± 0.06) and the control group (0.963 ± 0.05; p = 0.336). There was also a significant MD value difference between mcGBCA group and control group (p < 0.001; non-GBCA group, 0.152 ± 0.02 × 10^-3 mm²/s; mcGBCA group, 0.173 ± 0.03 × 10^-3 mm²/s). A significant correlation was identified between FA/MD values and the number of mcGBCA administration (FA; correlation coefficient =  - 0.355, p = 0.011 and MD; correlation coefficient = 0.334, p = 0.018). The administration of the gadobutrol was associated with higher MD and lower FA values in DN suggesting a difference in cerebellar tissue integrity between children exposed to mcGBCAs and control group.

Alterations in white matter microarchitecture in adolescents and young adults with major depressive disorder: A voxel-based meta-analysis of diffusion tensor imaging

Adolescents and young adults are at a critical stage of life development, and depression can have serious consequences. In recent decades, an increasing number of diffusion tensor imaging (DTI) studies of major depressive disorder (MDD) have reported inconsistent alterations in white matter (WM) microarchitecture. To rule out the confounding effects of age, we conducted a meta-analysis of fractional anisotropy (FA) in adolescents and young adults with MDD to identify abnormalities in WM involved in the pathogenesis of MDD using anisotropic effect-size signed differential mapping (AES-SDM). The pooled meta-analysis revealed significantly lower FA mainly in the corpus callosum (CC) extending to the left anterior thalamic projections (ATP) and left cortico-spinal projection (CSP) in depressed adolescents and young adults than that in healthy controls. A reduction in FA was also identified in the right frontal orbito-polar tract (FOPT) extending to the right inferior fronto-occipital fasciculus (IFOF). In the meta-regression analysis, the mean age of patients, percentage of female patients and duration of depression were not linearly associated with abnormalities in FA. These results constitute robust evidence that abnormalities in WM microarchitecture in the interhemispheric connections and frontal-subcortical neuronal circuits may contribute to the pathogenesis of MDD during adolescence and young adulthood.

DKI enhances the sensitivity and interpretability of age-related DTI patterns in the white matter of UK biobank participants

Studies of healthy brain aging traditionally report diffusivity patterns associated with white matter degeneration using diffusion tensor imaging (DTI), which assumes that diffusion measured at typical b-values (approximately 1000 s/mm²) is Gaussian. Diffusion kurtosis imaging (DKI) is an extension of DTI that measures non-Gaussian diffusion (kurtosis) to better capture microenvironmental processes by incorporating additional data at a higher b-value. In this study, using diffusion data (b-values of 1000 and 2000 s/mm²) from 700 UK Biobank participants aged 46-80, we investigate (1) the extent of novel information gained from adding diffusional kurtosis to diffusivity observations in aging, and (2) how conventional DTI metrics in aging compare with diffusivity metrics derived from DKI, which are corrected for kurtosis. We establish a pattern of lower kurtosis alongside higher diffusivity among older adults, with kurtosis generally being more sensitive to age than diffusivity. We also find discrepancies between diffusivity metrics derived from DTI and DKI, emphasizing the importance of accounting for non-Gaussian diffusion when interpreting age-related diffusivity patterns.

Combining MRI and cognitive evaluation to classify concussion in university athletes

Current methods of concussion assessment lack the objectivity and reliability to detect neurological injury. This multi-site study uses combinations of neuroimaging (diffusion tensor imaging and resting state functional MRI) and cognitive measures to train algorithms to detect the presence of concussion in university athletes. Athletes (29 concussed, 48 controls) completed symptom reports, brief cognitive evaluation, and MRI within 72 h of injury. Hierarchical linear regression compared groups on cognitive and neuroimaging measures while controlling for sex and data collection site. Logistic regression and support vector machine models were trained using cognitive and neuroimaging measures and evaluated for overall accuracy, sensitivity, and specificity. Concussed athletes reported greater symptoms than controls (∆R² = 0.32, p < .001), and performed worse on tests of concentration (∆R² = 0.07, p < .05) and delayed memory (∆R² = 0.17, p < .001). Concussed athletes showed lower functional connectivity within the frontoparietal and primary visual networks (p < .05), but did not differ on mean diffusivity and fractional anisotropy. Of the cognitive measures, classifiers trained using delayed memory yielded the best performance with overall accuracy of 71%, though sensitivity was poor at 46%. Of the neuroimaging measures, classifiers trained using mean diffusivity yielded similar accuracy. Combining cognitive measures with mean diffusivity increased overall accuracy to 74% and sensitivity to 64%, comparable to the sensitivity of symptom report. Trained algorithms incorporating both MRI and cognitive performance variables can reliably detect common neurobiological sequelae of acute concussion. The integration of multi-modal data can serve as an objective, reliable tool in the assessment and diagnosis of concussion.

Transcranial direct current stimulation to modulate brain reactivity to food cues in overweight and obese adults: study protocol for a randomized controlled trial with fMRI (NeuroStim-Obesity)

Background

With increasing obese populations worldwide, developing interventions to modulate food-related brain processes and functions is particularly important. Evidence suggests that transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex (DLPFC) may modulate the reward–control balance towards facilitation of cognitive control and possible suppression of reward-related mechanisms that drive food cue-induced craving. This protocol describes a clinical trial that investigates the neurocognitive mechanisms of action for tDCS to modulate food cue-reactivity and cravings in people with obesity.

Method

The NeuroStim-Obesity trial is a prospective, randomized, sham-controlled, double-blind single-session tDCS trial targeting food craving in those with obesity or overweighed. Once randomized, 64 adults with obesity or overweighed complete one session in which they receive either active or sham tDCS over the DLPFC (anode F4 and cathode F3, 2 mA intensity for 20 min). The primary outcome is change in neural response to the food cue-reactivity task in the ventral striatum after a single-session bilateral tDCS compared to sham stimulation. Secondary outcomes include changes in food craving evaluated by the Food Craving Questionnaire-State (FCQ-S). We will also explore the predictive role of brain structure and functional networks assessed by structural and functional magnetic resonance imaging (MRI) during both task performance and the resting-state that are acquired pre- and post-intervention to predict response to tDCS.

Discussion

The results will provide novel insight into neuroscience for the efficacy of tDCS and will advance the field towards precision medicine for obesity. Exploratory results will examine the potential predictive biomarkers for tDCS response and eventually provide personalized intervention for the treatment of obesity.

Trial registration

Iranian Registry of Clinical Trials (IRCT) IRCT20121020011172N4. Retrospectively registered on 4 June 2020

Fiber tracing and microstructural characterization among audiovisual integration brain regions in neonates compared with young adults

Audiovisual integration has been related with cognitive-processing and behavioral advantages, as well as with various socio-cognitive disorders. While some studies have identified brain regions instantiating this ability shortly after birth, little is known about the structural pathways connecting them. The goal of the present study was to reconstruct fiber tracts linking AVI regions in the newborn in-vivo brain and assess their adult-likeness by comparing them with analogous fiber tracts of young adults. We performed probabilistic tractography and compared connective probabilities between a sample of term-born neonates (N = 311; the Developing Human Connectome Project (dHCP, http://www.developingconnectome.org) and young adults (N = 311 The Human Connectome Project; https://www.humanconnectome.org/) by means of a classification algorithm. Furthermore, we computed Dice coefficients to assess between-group spatial similarity of the reconstructed fibers and used diffusion metrics to characterize neonates' AVI brain network in terms of microstructural properties, interhemispheric differences and the association with perinatal covariates and biological sex. Overall, our results indicate that the AVI fiber bundles were successfully reconstructed in a vast majority of neonates, similarly to adults. Connective probability distributional similarities and spatial overlaps of AVI fibers between the two groups differed across the reconstructed fibers. There was a rank-order correspondence of the fibers' connective strengths across the groups. Additionally, the study revealed patterns of diffusion metrics in line with early white matter developmental trajectories and a developmental advantage for females. Altogether, these findings deliver evidence of meaningful structural connections among AVI regions in the newborn in-vivo brain.

Brain Network Connectivity and Executive Function in Children with Previous Infantile Hydrocephalus

INTRODUCTION

Infantile hydrocephalus is a condition in which there is an abnormal build-up of cerebrospinal fluid in the ventricles within the first few months of life, which puts pressure on surrounding brain tissues. Compression of the developing brain increases the risk of secondary brain injury and cognitive disabilities.

METHODS

In this study, we used diffusion-weighted imaging and resting-state functional MRI to investigate the effects of ventricle dilatation on structural and functional brain networks in children with shunted infantile hydrocephalus and examined how these brain changes may impact executive function.

RESULTS

We found that children with hydrocephalus have altered structural and functional connectivity between and within large-scale networks. Moreover, hyperconnectivity between the ventral attention and default mode network in children with hydrocephalus correlated with reduced executive function scores. Compared to typically developing age-matched control participants, our patient population also had lower fractional anisotropy in posterior white matter.

DISCUSSION

Overall, these findings suggest that infantile hydrocephalus has long-term effects on brain network connectivity, white matter development, and executive function in children at school-age. Future work will examine the relationship between ventricular volumes prior to shunt placement in infancy and brain network development throughout childhood.

Treatment-resistant schizophrenia: Addressing white matter integrity, intracortical glutamate levels, clinical and cognitive profiles between early- and adult-onset patients

BACKGROUND

Treatment-resistance in schizophrenia is 30-40%. Its neurobiology remains unclear; to explore it, we conducted a combined spectrometry/tractography/cognitive battery and psychopathological rating study on patients with treatment-resistant schizophrenia (TRS), dividing the sample into early-onset (N = 21) and adult-onset TRS (N = 20). Previous studies did not differentiate between early- (onset 13-18 years) and adult-onset (>18 years at formal diagnosis of schizophrenia) TRS.

METHODS

We evaluated cross-sectionally 41 TRS patients (26 male and 15 female) and 20 matched healthy controls (HCs) with psychopathological and cognitive testing prior to participating in brain imaging scanning using magnetic resonance spectroscopy and diffusion tensor imaging to determine the relationship between their symptoms and their glutamate levels and white matter integrity.

RESULTS

TRS patients scored lower than HCs on all cognitive domains; early-onset patients performed better than adult-onset patients only on the Symbol Coding domain. TRS correlated with symptom severity, especially negative symptoms. Glutamate levels and glutamate/creatine were increased in anterior cingulate cortex. Diffusion tensor imaging showed low fractional anisotropy in TRS patients in specific white matter tracts compared to HCs (bilateral anterior thalamic radiation, cortico-spinal tract, forceps minor, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus, and right uncinate fasciculus).

CONCLUSIONS

We identified specific magnetic resonance spectroscopy and diffusion tensor imaging alterations in TRS patients. Adult-onset TRS differed little from early-onset TRS on most measures; this points to alterations being present since the outset of schizophrenia and may constitute a biological signature of treatment-resistance.

Sex differences in microstructural alterations in the corpus callosum tracts in drug-naïve children with ADHD

Widespread alterations in the corpus callosum (CC) microstructure and organization have been found in children with attention-deficit/hyperactivity disorder (ADHD); however, few studies have investigated the diffusion characteristics and volume of transcallosal fiber tracts defined by specific cortical projections in ADHD, which is important for identifying distinct functional interhemispheric connection abnormalities. In the current study, an automated fiber-tract quantification (AFQ) approach based on diffusion tensor imaging identified seven CC tracts according to their cortical projections and estimated diffusion parameters and volume among 76 drug-naïve ADHD patients (53 boys and 23 girls) and 37 typically developing children (TDC) (20 boys and 17 girls) matched for age, IQ, and handedness. We found significantly lower fractional anisotropy (FA) in the occipital and superior parietal tracts and higher mean diffusivity (MD) in the posterior, superior parietal and anterior frontal tracts in children with ADHD compared with TDC. In addition, lower FA and higher radial diffusivity (RD) in the occipital callosal tract were significantly associated with higher hyperactivity and impulsivity performance in ADHD. In addition, sex-by-diagnosis interactions were observed in the occipital, posterior and superior parietal tracts. Girls with ADHD showed decreased FA and volume in the occipital tract, which were significantly associated with increased impulsivity performance and poor response control, and increased MD in the posterior and superior parietal callosal tracts, which were significantly associated with increased inattention performance, whereas boys with ADHD merely showed decreased volume in the frontal tract. Our results elucidated that sex-specific alterations in the CC tracts potentially underlie ADHD symptomatology and further suggested a differential contribution of abnormalities in different CC tracts to impulsivity and inattention among girls with ADHD.

Age-related differences in white matter microstructure measured by advanced diffusion MRI in healthy older adults at risk for Alzheimer's disease

Neurite orientation dispersion and density imaging (NODDI) is an advanced diffusion imaging technique, which can detect more distinct microstructural features compared to conventional Diffusion Tensor Imaging (DTI). NODDI allows the signal to be divided into multiple water compartments and derive measures for orientation dispersion index (ODI), neurite density index (NDI) and volume fraction of isotropic diffusion compartment (FISO). This study aimed to investigate which diffusion metric-fractional anisotropy (FA), mean diffusivity (MD), NDI, ODI, or FISO-is most influenced by aging and reflects cognitive function in a population of healthy older adults at risk for Alzheimer's disease (AD). Age was significantly associated with all but one diffusion parameters and regions of interest. NDI and MD in the cingulate region adjacent to the cingulate cortex showed a significant association with a composite measure of Executive Function and was proven to partially mediate the relationship between aging and Executive Function decline. These results suggest that both DTI and NODDI parameters are sensitive to age-related differences in white matter regions vulnerable to aging, particularly among older adults at risk for AD.

Assessment of peripheral neuropathy in type 2 diabetes by diffusion tensor imaging

BACKGROUND

To evaluate the diagnostic accuracy of diffusion tensor imaging (DTI) in diabetic peripheral neuropathy (DPN) for patients with type 2 diabetes and detect the correlations with electrophysiology.

METHODS

A total of 27 patients with type 2 diabetes with DPN, 24 patients with type 2 diabetes without peripheral neuropathy (NDPN), as well as 32 healthy controls (HC) were enrolled in this study. Clinical examinations and neurophysiologic tests were used to determine the presence of DPN. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of peripheral nerves, including the tibial nerve (TN) and common peroneal nerve (CPN), were calculated. Receiver operating characteristic (ROC) analysis was performed for FA and ADC values. Pearson's correlation coefficient was used to assess the correlation between DTI and electrophysiology parameters in the patient group.

RESULTS

The tibial and common peroneal nerve FAs were lowest (P=0.003, 0.001, respectively) and ADC was highest (P=0.004, 0.005, respectively) in the DPN group. The FA value of the axonal injury group was lower than that in the demyelination group (P=0.035, 0.01, respectively), while the ADC value was higher (P=0.02, 0.01, respectively). In the DPN group, FA value was positively correlated with motor conduction velocity (MCV) (tibial nerve: r=0.420, P=0.007; common peroneal nerve: r=0.581, P<0.001) and motor amplitude (MA) (tibial nerve: r=0.623, P<0.001; common peroneal nerve: r=0.513; P=0.001), while ADC values was negatively correlated with MCV (tibial nerve: r=-0.320, P=0.044; common peroneal nerve: r=-0.569; P<0.001), and MA (tibial nerve: r=-0.491, P=0.001; common peroneal nerve: r=-0.524; P=0.001).

CONCLUSIONS

With a lower FA value and higher ADC value, DTI accurately discriminated DPN. The DTI multi-parameter quantitative analysis of peripheral nerves differentiated DPN axonal injury from the demyelinating lesion, and hence, could be applied in the diagnosis of DPN.

Utility of DTI (Diffusion Tensor Imaging) Metrics to Study Microstructural Changes of Trigeminal Nerve in Patients with Trigeminal Neuralgia (TN)

AIMS

To study the trigeminal nerve tractography and assessment of diffusion tensor imaging (DTI) parameters by comparing the values of fractional anisotropy (FA) of trigeminal (V) nerve on the affected side with that of the unaffected opposite side.

MATERIALS AND METHODS

Prospective comparative study done for one year included 30 patients who presented with trigeminal neuralgia and 30 controls who did not have any present or past history of neurological or neurosurgical symptoms were enrolled in the study.

RESULTS

Most common age of presentation of TN is >50 years, and the commonly involved branch is V2 (maxillary branch of the trigeminal nerve). Most of the patients were having symptoms for more than 1 year. The superior cerebellar artery was the most common vessel compressing the V nerve at the root entry zone (REZ), followed in the order by anterior inferior cerebellar artery and petrosal vein. Neurovascular compression (NVC) was more commonly seen in the study group when compared with the control group. In all the patients in the study group, fractional anisotropy (FA) was decreased on the affected side as compared to the unaffected side. In the study group, 10 patients were having NVC on both sides, but FA was significantly decreased only on the affected side. No significant difference in FA values at the REZ of bilateral V nerves in the control group.

CONCLUSION

DTI metrics of the trigeminal nerve is a very helpful imaging technique in patients with trigeminal neuralgia. It not only helps in anatomical imaging but also reinforces the association between NVC and TN.

Diffusion Tensor Orientation as a Microstructural MRI Marker of Mossy Fiber Sprouting After TBI in Rats

Diffusion tensor imaging (DTI) metrics are highly sensitive to microstructural brain alterations and are potentially useful imaging biomarkers for underlying neuropathologic changes after experimental and human traumatic brain injury (TBI). As potential imaging biomarkers require direct correlation with neuropathologic alterations for validation and interpretation, this study systematically examined neuropathologic abnormalities underlying alterations in DTI metrics in the hippocampus and cortex following controlled cortical impact (CCI) in rats. Ex vivo DTI metrics were directly compared with a comprehensive histologic battery for neurodegeneration, microgliosis, astrocytosis, and mossy fiber sprouting by Timm histochemistry at carefully matched locations immediately, 48 hours, and 4 weeks after injury. DTI abnormalities corresponded to spatially overlapping but temporally distinct neuropathologic alterations representing an aggregate measure of dynamic tissue damage and reorganization. Prominent DTI alterations of were observed for both the immediate and acute intervals after injury and associated with neurodegeneration and inflammation. In the chronic period, diffusion tensor orientation in the hilus of the dentate gyrus became prominently abnormal and was identified as a reliable structural biomarker for mossy fiber sprouting after CCI in rats, suggesting potential application as a biomarker to follow secondary progression in experimental and human TBI.

Resilience and young people's brain structure, function and connectivity: A systematic review

Although negative early life experiences are associated with an increased risk of developing psychopathology, some individuals exposed to childhood adversity demonstrate psychological resilience. Little is known about the neural correlates of resilience, especially in young people. To address this gap, we conducted a systematic review of neuroimaging studies of resilience in youth. The PubMed, Web of Science, Scopus, and PsycINFO databases were searched; 5,482 studies were identified. Following title/abstract screening, and full reading of the remaining articles, 22 studies based on 19 unique datasets were included. We found preliminary evidence that resilience is associated with structural, functional, and connectivity differences in young people, as assessed using structural and functional MRI and diffusion tensor imaging methods. Despite heterogeneity in definitions/assessment of resilience and a limited number of studies, the neuroimaging literature suggests some convergence across modalities regarding brain regions linked to resilience (especially the prefrontal cortex). Future studies would benefit from adopting longitudinal designs, broader conceptualisations of resilience that capture the impact of adversity exposure, and a dimensional approach to psychopathology.

Characteristics of the corpus callosum in chronic schizophrenia treated with clozapine or risperidone and those never-treated

BACKGROUND

The corpus callosum (CC) deficits have been well documented in chronic schizophrenia. However, the long-term impacts of antipsychotic monotherapies on callosal anatomy remain unclear. This cross-sectional study sought to explore micro- and macro-structural characteristics of the CC in never-treated patients and those with long-term mono-antipsychotic treatment.

METHODS

The study included 23 clozapine-treated schizophrenia patients (CT-SCZ), 19 risperidone-treated schizophrenia patients (RT-SCZ), 23 never-treated schizophrenia patients (NT-SCZ), and 35 healthy controls (HCs). High resolution structural images and diffusion tensor imaging (DTI) data for each participant were obtained via a 3.0 T MR scanner. FreeSurfer was used to examine the volumes and fractional anisotropy (FA) values of the CC for each participant.

RESULTS

There were significant deficits in the total and sub-regional CC volume and white matter integrity in NT-SCZ in comparison with healthy subjects. Compared with NT-SCZ, both CT-SCZ and RT-SCZ showed significantly increased FA values in the anterior CC region, while only RT-SCZ showed significantly increased volume in the mid-anterior CC region. Moreover, the volume of the mid-anterior CC region was significantly smaller in CT-SCZ compared to HCs. No correlations of clinical symptoms with callosal metrics were observed in schizophrenia patients.

CONCLUSIONS

Our findings provide insight into micro- and macro-structural characteristics of the CC in chronic schizophrenia patients with or without antipsychotics. These results suggest that the pathology itself is responsible for cerebral abnormalities in schizophrenia and that chronic exposure to antipsychotics may have an impact on white matter structure of schizophrenia patients, especially in those with risperidone treatment.

New and Advanced Magnetic Resonance Imaging Diagnostic Imaging Techniques in the Evaluation of Cranial Nerves and the Skull Base

The skull base and cranial nerves are technically challenging to evaluate using magnetic resonance (MR) imaging, owing to a combination of anatomic complexity and artifacts. However, improvements in hardware, software and sequence development seek to address these challenges. This section will discuss cranial nerve imaging, with particular attention to the techniques, applications and limitations of MR neurography, diffusion tensor imaging and tractography. Advanced MR imaging techniques for skull base pathology will also be discussed, including diffusion-weighted imaging, perfusion and permeability imaging, with a particular focus on practical applications.

In vivo restricted diffusion imaging (RDI) is sensitive to differences in axonal density in typical children and adults

The ability to dissociate axonal density in vivo from other microstructural properties is important for the diagnosis and treatment of neurologic disease, and new methods to do so are being developed. We investigated one such method-restricted diffusion imaging (RDI)-to see whether it can more accurately replicate histological axonal density patterns in the corpus callosum (CC) of adults and children compared to diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and generalized q-sampling imaging (GQI) methods. To do so, we compared known axonal density patterns defined by histology to diffusion-weighted imaging (DWI) scans of 840 healthy 20- to 40-year-old adults, and to DWI scans of 129 typically developing 7-month-old to 18-year-old children and adolescents. Contrast analyses were used to compare pattern similarities between the in vivo metric and previously published histological density models. We found that RDI was effective at mapping axonal density of small (Cohen's d = 2.60) and large fiber sizes (Cohen's d = 2.84) in adults. The same pattern was observed in the developing sample (Cohen's d = 3.09 and 3.78, respectively). Other metrics, notably NODDI's intracellular volume fraction in adults and GQI generalized fractional anisotropy in children, were also sensitive metrics. In conclusion, the study showed that the novel RDI metric is sensitive to density of small and large axons in adults and children, with both single- and multi-shell acquisition DWI data. Its effectiveness and availability to be used on standard as well as advanced DWI acquisitions makes it a promising method in clinical settings.

Sex matters: association between callous-unemotional traits and uncinate fasciculus microstructure in youths with conduct disorder

Among youths with conduct disorder, those with callous-unemotional traits are at increased risk for persistent antisocial behaviour. Although callous-unemotional traits have been found to be associated with white-matter brain abnormalities, previous diffusion imaging studies were conducted in small samples, preventing examination of potential sex by callous-unemotional traits interaction effects on white matter. Here, we used tract-based spatial statistics at a whole-brain level and within regions of interest to compare the white matter correlates of callous-unemotional traits in female vs. male youths with conduct disorder, in a sample (n = 124) recruited through a multi-site protocol. A sex-specific association between callous-unemotional traits and white matter was found in the left uncinate fasciculus, where callous-unemotional traits were positively associated with axial diffusivity in males, while an opposite pattern was found in females. These findings are in line with previous studies suggesting that the uncinate fasciculus is a key tract implicated in the development of psychopathy, but also add to recent evidence showing that sexual dimorphism needs to be taken into account when examining the structural correlates of mental disorders in general, and callous-unemotional traits in conduct disorder in particular.

Altered microstructural properties of superficial white matter in patients with Parkinson's disease

Parkinson's disease (PD), a chronic neurodegenerative disease, is characterized by sensorimotor and cognitive deficits. Previous diffusion tensor imaging (DTI) studies found abnormal DTI metrics in white matter bundles, such as the corpus callosum, cingulate, and frontal-parietal bundles, in PD patients. These studies mainly focused on alterations in microstructural features of long-range bundles within the deep white matter (DWM) that connects pairs of distant cortical regions. However, less is known about the DTI metrics of the superficial white matter (SWM) that connects local cortical regions in PD patients. To determine whether the DTI metrics of the SWM were different between the PD patients and the healthy controls, we recruited DTI data from 34 PD patients and 29 gender- and age-matched healthy controls. Using a probabilistic tractographic approach, we first defined a population-based SWM mask across all the subjects. Using a tract-based spatial statistical (TBSS) analytic approach, we then identified the SWM bundles showing abnormal DTI metrics in the PD patients. We found that the PD patients showed significantly lower DTI metrics in the SWM bundles connecting the sensorimotor cortex, cingulate cortex, posterior parietal cortex (PPC), and parieto-occipital cortex than the healthy controls. We also found that the clinical measures in the PD patients was significantly negatively correlated with the fractional anisotropy in the SWM (FA_SWM) that connects core regions in the default mode network (DMN). The FA_SWM in the bundles that connected the PPC was significantly positively correlated with cognitive performance in the PD patients. Our findings suggest that SWM may serve as the brain structural basis underlying the sensorimotor deficits and cognitive degeneration in PD patients.

Measuring decline in white matter integrity after systemic treatment for breast cancer: omitting skeletonization enhances sensitivity

Chemotherapy for non-central nervous system cancers is associated with abnormalities in brain structure and function. Diffusion tensor imaging (DTI) allows for studying in vivo microstructural changes in brain white matter. Tract-based spatial statistics (TBSS) is a widely used processing pipeline in which DTI data are typically normalized to a generic DTI template and then 'skeletonized' to compensate for misregistration effects. However, this approach greatly reduces the overall white matter volume that is subjected to statistical analysis, leading to information loss. Here, we present a re-analysis of longitudinal data previously analyzed with standard TBSS (Menning et al., BIB 2018, 324-334). For our current approach, we constructed a pipeline with an optimized registration method in Advanced Normalization Tools (ANTs) where DTI data are registered to a study-specific, high-resolution T1 template and the skeletonization step is omitted. In a head to head comparison, we show that with our novel approach breast cancer survivors who had received chemotherapy plus or minus endocrine therapy (BC + SYST, n = 26) showed a global decline in overall FA that was not present in breast cancer survivors who did not receive systemic therapy (BC-SYST, n = 23) or women without a cancer diagnosis (no cancer controls, NC, n = 30). With the standard TBSS approach we did not find any group differences. Moreover, voxel-based analysis for our novel pipeline showed a widespread decline in FA in the BC + SYST compared to the NC group. Interestingly, the BC-SYST group also showed a decline in FA compared to the NC group, although in much less voxels. These results were not found with the standard TBSS approach. We demonstrate that a modified processing pipeline makes DTI data more sensitive to detecting changes in white matter integrity in non-CNS cancer patients after treatment, particularly chemotherapy.

Ensemble Learning for Multiple Sclerosis Disability Estimation Using Brain Structural Connectivity

BACKGROUND

Multiple Sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system characterized by demyelination and neurodegeneration processes. It leads to different clinical courses and degrees of disability that need to be anticipated by the neurologist for personalized therapy. Recently, machine learning (ML) techniques have reached a high level of performance in brain disease diagnosis and/or prognosis, but the decision process of a trained ML system is typically non-transparent. Using brain structural connectivity data, a fully automatic ensemble learning model, augmented with an interpretable model, is proposed for the estimation of MS patients' disability, measured by the Expanded Disability Status Scale (EDSS).

METHOD

An ensemble of four boosting-based models (GBM, XGBoost, CatBoost, LightBoost) organized following a stacking generalization scheme, was developed using DTI-based structural connectivity data. In addition, an interpretable model based on conditional logistic regression was developed to explain the best performances in terms of white matter (WM) links for three classes of EDSS (Low, Medium, High).

RESULTS

The ensemble model reached excellent level of performance (RMSE of 0.92 ± 0.28) compared to single-based models and provided a better EDSS estimation using DTI-based structural connectivity data compared to conventional MRI measures associated with patient data (age, gender and disease duration). Used for interpretation of the estimation process, the counterfactual method showed the importance of certain brain networks, corresponding mainly to left hemisphere WM links, connecting the left superior temporal with the left posterior cingulate and the right precuneus gray matter regions, and the inter-hemispheric WM links constituting the corpus callosum. Also, a better accuracy estimation was found for the high disability class.

CONCLUSION

The combination of advanced ML models and sensitive techniques such as DTI-based structural connectivity demonstrated to be useful for the estimation of MS patients' disability and to point out the most important brain WM networks involved in disability.

Estimates of brain age for gray matter and white matter in younger and older adults: Insights into human intelligence

Aging entails a multifaceted complex of changes in macro- and micro-structural properties of human brain gray matter (GM) and white matter (WM) tissues, as well as in intellectual abilities. To better capture tissue-specific brain aging, we combined volume and distribution properties of diffusivity indices to derive subject-specific age scores for each tissue. We compared age-related variance between younger and older adults for GM and WM age scores, and tested whether tissue-specific age scores could explain different effects of aging on fluid (Gf) and crystalized (Gc) intelligence in younger and older adults. Chronological age was strongly associated with GM (R2 = 0.73) and WM (R2 = 0.57) age scores. The GM age score accounted for significantly more variance in chronological age in younger relative to older adults (p < 0.001), whereas the WM age score accounted for significantly more variance in chronological age in older compared to younger adults (p < 0.025). Consistent with existing literature, younger adults outperformed older adults in Gf while older adults outperformed younger adults in Gc. The GM age score was negatively associated with Gf in younger adults (p < 0.02), whereas the WM age score was negatively associated with Gc in older adults (p < 0.02). Our results provide evidence for differences in the effects of age on GM and WM in younger versus older adults that may contribute to age-related differences in Gf and Gc.

Improved white matter integrity after contralateral seventh cervical nerve transfer measured by tractographic representation

Contralateral C7 (CC7) nerve transfer surgery was shown to significantly improve the spasticity condition and the motor function of paralyzed arms. However, the involvement of the white matter tract in the recovery process is not well established. We here investigated the possible biologic explanation for this phenomenon. A 62-year-old female patient, who suffered from spastic hemiparesis due to intracranial hemorrhage, underwent CC7 transfer surgery 13 years after the initial stroke event. Six months after the surgery, the patient's Modified Ashworth Scale and Fugl-Myere score improved, even though no specific rehabilitation programs were applied. Diffusion tensor imaging (DTI) was performed before and 6 months after the surgery. The pre-surgery DTI showed both ipsilesional and contralesional CST from the cerebral peduncles to the cortices. After surgery, however, only the contralesional CST was observed. In conclusion, functional alterations of the brain white matter tract after CC7 nerve transfer surgery possibly provided a neurophysiological substrate for ameliorating the spasticity and improving the motor function in a spastic hemiplegia patient.

Long-term coordinated microstructural disruptions of the developing neocortex and subcortical white matter after early postnatal systemic inflammation

Severe postnatal systemic infection is highly associated with persistent disturbances in brain development and neurobehavioral outcomes in survivors of preterm birth. However, the contribution of less severe but prolonged postnatal infection and inflammation to such disturbances is unclear. Further, the ability of modern imaging techniques to detect the underlying changes in cellular microstructure of the brain in these infants remains to be validated. We used high-field ex-vivo MRI, neurohistopathology, and behavioral tests in newborn rats to demonstrate that prolonged postnatal systemic inflammation causes subtle, persisting disturbances in brain development, with neurodevelopmental delays and mild motor impairments. Diffusion-tensor MRI and neurite orientation dispersion and density imaging (NODDI) revealed delayed maturation of neocortical and subcortical white matter microstructure. Analysis of pyramidal neurons showed that the cortical deficits involved impaired dendritic arborization and spine formation. Analysis of oligodendrocytes showed that the white matter deficits involved impaired oligodendrocyte maturation and axonal myelination. These findings indicate that prolonged postnatal inflammation, without severe infection, may critically contribute to the diffuse spectrum of brain pathology and subtle long-term disability in preterm infants, with a cellular mechanism involving oligodendrocyte and neuronal dysmaturation. NODDI may be useful for clinical detection of these microstructural deficits.