Bounding tractogram redundancy.

Introduction: In tractography, redundancy poses a significant challenge, often resulting in tractograms that include anatomically implausible streamlines or those that fail to represent the brain's white matter architecture accurately. Current filtering methods aim to refine tractograms by addressing these issues, but they lack a unified measure of redundancy and can be computationally demanding. Methods: We propose a novel framework to quantify tractogram redundancy based on filtering tractogram subsets without endorsing a specific filtering algorithm. Our approach defines redundancy based on the anatomical plausibility and diffusion signal representation of streamlines, establishing both lower and upper bounds for the number of false-positive streamlines and the tractogram redundancy. Results: We applied this framework to tractograms from the Human Connectome Project, using geometrical plausibility and statistical methods informed by the streamlined attributes and ensemble consensus. Our results establish bounds for the tractogram redundancy and the false-discovery rate of the tractograms. Conclusion: This study advances the understanding of tractogram redundancy and supports the refinement of tractography methods. Future research will focus on further validating the proposed framework and exploring tractogram compression possibilities.

Therapeutic DBS for OCD Suppresses the Default Mode Network.

Background: Deep brain stimulation (DBS) of the anterior limb of the internal capsule (ALIC) is an emerging treatment for severe, refractory obsessive-compulsive disorder (OCD). The therapeutic effects of DBS are hypothesized to be mediated by direct modulation of a distributed cortico-striato-thalmo-cortical network underlying OCD symptoms. However, the exact underlying mechanism by which DBS exerts its therapeutic effects still remains unclear. Method: In five participants receiving DBS for severe, refractory OCD (3 responders, 2 non-responders), we conducted a DBS On/Off cycling paradigm during the acquisition of functional MRI to determine the network effects of stimulation across a variety of bipolar configurations. We also performed tractography using diffusion-weighted imaging (DWI) to relate the functional impact of DBS to the underlying structural connectivity between active stimulation contacts and functional brain networks. Results: We found that therapeutic DBS had a distributed effect, suppressing BOLD activity within regions such as the orbitofrontal cortex, dorsomedial prefrontal cortex, and subthalamic nuclei compared to non-therapeutic configurations. Many of the regions suppressed by therapeutic DBS were components of the default mode network (DMN). Moreover, the estimated stimulation field from the therapeutic configurations exhibited significant structural connectivity to core nodes of the DMN. Conclusions: Therapeutic DBS for OCD suppresses BOLD activity within a distributed set of regions within the DMN relative to non-therapeutic configurations. We propose that these effects may be mediated by interruption of communication through structural white matter connections surrounding the DBS active contacts.

Laser interstitial thermal therapy of a single nodule in a complex epileptic network with multiple periventricular nodular heterotopias.

Surgical management of drug-resistant epilepsy (DRE) in patients with multiple periventricular nodular heterotopias (PVNHs) is challenging. Identifying the location of seizure onset within these complex epileptic networks is difficult, and open resection carries risks of injury to surrounding functional white matter tracts such as optic radiations (ORs). The authors demonstrate tractography-assisted laser ablation of a single nodule in a patient with DRE and multiple PVNHs. Following surgery, visual fields were intact, highlighting the benefits of OR tractographic reconstruction. At 12 months postoperatively, the patient remained seizure free, suggesting the potential efficacy of targeting a single heterotopia within complex networks in well-selected cases. The video can be found here: https://stream.cadmore.media/r10.3171/2024.4.FOCVID2417.

Impact of Sleeve Gastrectomy on Brain Structural Integrity.

INTRODUCTION: Potential brain structural differences in people with obesity (PwO) who achieve over or less than 50% excess weight loss (EWL) after sleeve gastrectomy (SG) are currently unknown. We compared measures of gray matter volume (GMV) and white matter (WM) microstructural integrity of PwO who achieved over or less than 50% EWL after SG with a group of controls with obesity (CwO) without a past history of metabolic bariatric surgery. METHODS: Sixty-two PwO underwent 1.5 T MRI scanning: 24 who achieved more than 50% of EWL after SG ("group a"), 18 who achieved less than 50% EWL after SG ("group b"), and 20 CwO ("group c"). Voxel-based morphometry and tract-based spatial Statistics analyses were performed to investigate GMV and WM differences among groups. Multiple regression analyses were performed to investigate relationships between structural and psychological measures. RESULTS: Group a demonstrated significantly lower GMV loss and higher WM microstructural integrity with respect to group b and c in some cortical regions and several WM tracts. Positive correlations were observed in group a between WM integrity and several psychological measures; the lower the WM integrity, the higher the mental distress, emotional dysregulation, and binge eating behavior. CONCLUSION: The present results gain a new understanding of the neural mechanisms of outcome in patients who undergo SG. We found limited GMV changes and extensive WM microstructural differences between PwO who achieved over or less than 50% EWL after SG, which may be due to higher vulnerability of WM to the metabolic dysfunction present in PwO.

Prospective longitudinal cohort study of quantitative muscle magnetic resonance imaging in a healthy control population.

Quantitative muscle magnetic resonance imaging (qMRI) is a valuable methodology for assessing muscular injuries and neuromuscular disorders. Notably, muscle diffusion tensor imaging (DTI) gives insights into muscle microstructural and macrostructural characteristics. However, the long-term reproducibility and robustness of these measurements remain relatively unexplored. The purpose of this prospective longitudinal cohort study was to assess the long-term robustness and range of variation of qMRI parameters, especially DTI metrics, in the lower extremity muscles of healthy controls under real-life conditions. Twelve volunteers (seven females, age 44.1 ± 12.1 years, body mass index 23.3 ± 2.0 kg/m2) underwent five leg muscle MRI sessions every 20 ± 4 weeks over a total period of 1.5 years. A multiecho gradient-echo Dixon-based sequence, a multiecho spin-echo T2-mapping sequence, and a spin-echo echo planar imaging diffusion-weighted sequence were acquired bilaterally with a Philips 3-T Achieva MR System using a 16-channel torso coil. Fifteen leg muscles were segmented in both lower extremities. qMRI parameters, including fat fraction (FF), water T2 relaxation time, and the diffusion metrics fractional anisotropy (FA) and mean diffusivity (MD), were evaluated. Coefficients of variance (wsCV) and intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of qMRI parameters. The standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated to determine the range of variation. All tests were applied to all muscles and, subsequently, to each muscle separately. wsCV showed good reproducibility (≤ 10%) for all qMRI parameters in all muscles. The ICCs revealed excellent agreement between time points (FF = 0.980, water T2 = 0.941, FA = 0.952, MD = 0.948). Random measurement errors assessed by SEM and the MDC were low (< 12%). In conclusion, in this study, we showed that qMRI parameters in healthy volunteers living normal lives are stable over 18 months, thereby defining a benchmark for the expected range of variation over time.

Brain Tumor Anatomy with Tractography Fluorescence and Confocal Endoscopy.

Tractography fluorescence and confocal endomicroscopy are complementary technologies to targeted tumor resection, and it is certain that as our technology for fluorescent probes continues to evolve, the confocal microscope will continue to be refined. Recent work suggests that intraoperative high-resolution augmented reality endomicroscopy, a real-time alternative to invasive biopsy and histopathology, has the potential to better quantify tumor burden at the final stages of surgery and ultimately to improve patient outcomes when combined with wide-field imaging approaches. Additional studies are needed to further elucidate the clinical benefits of these new technologies for brain tumor patients.

Chronic cannabis use associated with subcortical topological reorganization of structural connectivity in adults.

BACKGROUND: Cannabis is commonly used in the United States. However, chronic cannabis use has been linked to alterations in white matter (WM) integrity. Studies investigating WM in people who use cannabis (PWC) have produced varying results, which may be due to a variety of factors, including a focus on individual WM tracts. Here, we examined WM connectivity using a module-based approach to help clarify whether cannabis use is associated with differences in WM organization. METHODS: Connectomics is used to map complex networks of inter and intra-connected cortical and subcortical regions. A key concept of brain organization is the presence of groups of densely interconnected regions, referred to as modules. Here, we used WM structural connectivity estimates to compare connectome organization between adults who used cannabis regularly (n=53), and adults who did not use cannabis (n=60). We quantified aspects of network organization both across the whole brain and within specific modules. RESULTS: There were no significant results between groups after correcting for multiple comparisons for whole-brain metrics. When considering group differences in network organization metrics for 10 identified modules, we observed that adult PWC showed higher within-module degree, local efficiency, and network strength in a right subcortical module relative to adults that did not use cannabis. CONCLUSIONS: These results suggest that cannabis use in adults is associated with alterations of subcortical WM network organization. The observed differences in WM organization may be due to the involvement of the endocannabinoid system in the alteration of WM growth processes.

Mapping the impact of age and APOE risk factors for late onset Alzheimer's disease on long range brain connections through multiscale bundle analysis.

Alzheimer's disease currently has no cure and is usually detected too late for interventions to be effective. In this study we have focused on cognitively normal subjects to study the impact of risk factors on their long-range brain connections. To detect vulnerable connections, we devised a multiscale, hierarchical method for spatial clustering of the whole brain tractogram and examined the impact of age and APOE allelic variation on cognitive abilities and bundle properties including texture e.g., mean fractional anisotropy, variability, and geometric properties including streamline length, volume, and shape, as well as asymmetry. We found that the third level subdivision in the bundle hierarchy provided the most sensitive ability to detect age and genotype differences associated with risk factors. Our results indicate that frontal bundles were a major age predictor, while the occipital cortex and cerebellar connections were important risk predictors that were heavily genotype dependent, and showed accelerated decline in fractional anisotropy, shape similarity, and increased asymmetry. Cognitive metrics related to olfactory memory were mapped to bundles, providing possible early markers of neurodegeneration. In addition, physiological metrics such as diastolic blood pressure were associated with changes in white matter tracts. Our novel method for a data driven analysis of sensitive changes in tractography may differentiate populations at risk for AD and isolate specific vulnerable networks.

Multi-metric predictors of radiofrequency-treated trigeminal neuralgias.

Evaluation of neurovascular compression-related trigeminal neuralgia (NVC-TN) and its resolution through microvascular decompression are demonstrable by MRI and intraoperatively [Leal et al. (Atrophic changes in the trigeminal nerves of patients with trigeminal neuralgia due to neurovascular compression and their association with the severity of compression and clinical outcomes: Clinical article. J Neurosurg. 2014;120(6):1484-1495)]. Non-NVC-TNs treated by radiofrequency (RF) lack such detectable features. Multimodal integration of pre-surgical diffusion tensor imaging (DTI) and volumetry (VOL) with intraoperative neurophysiology (ION) could improve understanding and performance of RF among non-NVC-TN. We hypothesized that DTI disturbances' localization (central relay versus peripherally) rather than their values bares the most significant predictive value upon outcome and that ION could quantitatively both localize and assist RF of affected branches. The first pre-surgical step evaluated the differences between affected and non-affected sides (by DTI and VOL). Four TN's segments were studied, from peripheral to central relay: Meckel's cave-trigeminal ganglion (MC-TGN), cisternal portion, root entry zone (REZ) and spinal tract [Lin et al. (Flatness of the Meckel cave may cause primary trigeminal neuralgia: A radiomics-based study. J Headache Pain. 2021;22(1):104)]. In the second intraoperative step, we used both ION and patient's testimonies to confirm the localization of the affected branch, evolving hypoesthesia, pain reduction and monitoring of adverse effects [Sindou (Neurophysiological navigation in the trigeminal nerve: Use of masticatory responses and facial motor responses evoked by electrical stimulation of the trigeminal rootlets for RF-thermorhizotomy guidance. Stereotact Funct Neurosurg. 1999;73(1-4):117-121); Sindou and Tatli (Traitement de la névralgie trigéminale par thermorhizotomie. Neurochirurgie. 2009;55(2):203-210)]. Last and postoperatively, each data set's features and correlation with short-term (3 months) and long-term outcomes (23.5 ± 6.7 months) were independently analysed and blind to each other. Finally, we designed a multimodal predictive model. Sixteen non-NVC-TN patients (mean 53.6 ± SD years old) with mean duration of 6.56 ± 4.1 years (75% right TN; 43.8% V3) were included. After 23.5 ± 6.7 months, 14/16 were good responders. Age, gender, TN duration and side/branch did not correlate with outcomes. Affected sides showed significant DTI disturbances in both peripheral (MC-TGNs) and central-relay (REZ) segments. However, worse outcome correlated only with REZ-located DTI disturbances (P = 0.04; r = 0.53). Concerning volumetry, affected MC-TGNs were abnormally flatter: lower volumes and surface area correlated with worse outcomes (both P = 0.033; r = 0.55 and 0.77, respectively). Intraoperatively, ION could not differ the affected from non-affected branch. However, the magnitude of ION's amplitude reduction (ION-Δ-Amplitude) had the most significant correlation with outcomes (r = 0.86; P < 0.00006). It was higher among responders [68.4% (50-82%)], and a <40% reduction characterized non-responders [36.7% (0-40%)]. Multiple regression showed that ION-Δ-Amplitude, centrally located only REZ DTI integrity and MC-TGN flatness explain 82.2% of the variance of post-RF visual analogue score. Integration of pre-surgical DTI-VOL with ION-Δ-Amplitude suggests a multi-metric predictive model of post-RF outcome in non-NVC-TN. In multiple regression, central-relay REZ DTI disturbances and insufficiently reduced excitability (<40%) predicted worse outcome. Quantitative fine-tuned ION tools should be sought for peri-operative evaluation of the affected branches.

Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data.

Purpose: The study aimed to (1) assess the feasibility constrained spherical deconvolution (CSD) tractography to reconstruct crossing fiber bundles with unsedated neonatal diffusion MRI (dMRI), and (2) demonstrate the impact of spatial and angular resolution and processing settings on tractography and derived quantitative measures. Methods: For the purpose of this study, the term-equivalent dMRIs (single-shell b800, and b2000, both 5 b0, and 45 gradient directions) of two moderate-late preterm infants (with and without motion artifacts) from a local cohort [Brain Imaging in Moderate-late Preterm infants (BIMP) study; Calgary, Canada] and one infant from the developing human connectome project with high-quality dMRI (using the b2600 shell, comprising 20 b0 and 128 gradient directions, from the multi-shell dataset) were selected. Diffusion tensor imaging (DTI) and CSD tractography were compared on b800 and b2000 dMRI. Varying image resolution modifications, (pre-)processing and tractography settings were tested to assess their impact on tractography. Each experiment involved visualizing local modeling and tractography for the corpus callosum and corticospinal tracts, and assessment of morphological and diffusion measures. Results: Contrary to DTI, CSD enabled reconstruction of crossing fibers. Tractography was susceptible to image resolution, (pre-) processing and tractography settings. In addition to visual variations, settings were found to affect streamline count, length, and diffusion measures (fractional anisotropy and mean diffusivity). Diffusion measures exhibited variations of up to 23%. Conclusion: Reconstruction of crossing fiber bundles using CSD tractography with unsedated neonatal dMRI data is feasible. Tractography settings affected streamline reconstruction, warranting careful documentation of methods for reproducibility and comparison of cohorts.

Sex-related variability of white matter tracts in the whole HCP cohort.

Behavioral differences between men and women have been studied extensively, as have differences in brain anatomy. However, most studies have focused on differences in gray matter, while white matter has been much less studied. We conducted a comprehensive study of 77 deep white matter tracts to analyze their volumetric and microstructural variability between men and women in the full Human Connectome Project (HCP) cohort of 1065 healthy individuals aged 22-35 years. We found a significant difference in total brain volume between men and women (+ 12.6% in men), consistent with the literature. 16 tracts showed significant volumetric differences between men and women, one of which stood out due to a larger effect size: the corpus callosum genu, which was larger in women (+ 7.3% in women, p = 5.76 × 10-19). In addition, we found several differences in microstructural parameters between men and women, both using standard Diffusion Tensor Imaging (DTI) parameters and more complex microstructural parameters from the Neurite Orientation Dispersion and Density Imaging (NODDI) model, with the tracts showing the greatest differences belonging to motor (cortico-spinal tracts, cortico-cerebellar tracts) or limbic (cingulum, fornix, thalamo-temporal radiations) systems. These microstructural differences may be related to known behavioral differences between the sexes in timed motor performance, aggressiveness/impulsivity, and social cognition.

Time to bury the chisel: a continuous dorsal association tract system.

The arcuate fasciculus may be subdivided into a tract directly connecting frontal and temporal lobes and a pair of indirect subtracts in which the fronto-temporal connection is mediated by connections to the inferior parietal lobe. This tripartition has been advanced as an improvement over the centuries-old consensus that the lateral dorsal association fibers form a continuous system with no discernible discrete parts. Moreover, it has been used as the anatomical basis for functional hypotheses regarding linguistic abilities. Ex hypothesi, damage to the indirect subtracts leads to deficits in the repetition of multi-word sequences, whereas damage to the direct subtract leads to deficits in the immediate reproduction of single multisyllabic words. We argue that this partitioning of the dorsal association tract system enjoys no special anatomical status, and the search for the anatomical substrates of linguistic abilities should not be constrained by it. Instead, the merit of any postulated partitioning should primarily be judged on the basis of whether it enlightens or obfuscates our understanding of the behavior of patients in which individual subtracts are damaged.

TractoSCR: a novel supervised contrastive regression framework for prediction of neurocognitive measures using multi-site harmonized diffusion MRI tractography.

Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose a novel deep regression method, namely TractoSCR, that allows full supervision for contrastive learning in regression tasks using diffusion MRI tractography. TractoSCR performs supervised contrastive learning by using the absolute difference between continuous regression labels (i.e., neurocognitive scores) to determine positive and negative pairs. We apply TractoSCR to analyze a large-scale dataset including multi-site harmonized diffusion MRI and neurocognitive data from 8,735 participants in the Adolescent Brain Cognitive Development (ABCD) Study. We extract white matter microstructural measures using a fine parcellation of white matter tractography into fiber clusters. Using these measures, we predict three scores related to domains of higher-order cognition (general cognitive ability, executive function, and learning/memory). To identify important fiber clusters for prediction of these neurocognitive scores, we propose a permutation feature importance method for high-dimensional data. We find that TractoSCR obtains significantly higher accuracy of neurocognitive score prediction compared to other state-of-the-art methods. We find that the most predictive fiber clusters are predominantly located within the superficial white matter and projection tracts, particularly the superficial frontal white matter and striato-frontal connections. Overall, our results demonstrate the utility of contrastive representation learning methods for regression, and in particular for improving neuroimaging-based prediction of higher-order cognitive abilities. Our code will be available at: https://github.com/SlicerDMRI/TractoSCR.

Beyond the surface: how ex-vivo diffusion-weighted imaging reveals large animal brain microstructure and connectivity.

Diffusion-weighted Imaging (DWI) is an effective and state-of-the-art neuroimaging method that non-invasively reveals the microstructure and connectivity of tissues. Recently, novel applications of the DWI technique in studying large brains through ex-vivo imaging enabled researchers to gain insights into the complex neural architecture in different species such as those of Perissodactyla (e.g., horses and rhinos), Artiodactyla (e.g., bovids, swines, and cetaceans), and Carnivora (e.g., felids, canids, and pinnipeds). Classical in-vivo tract-tracing methods are usually considered unsuitable for ethical and practical reasons, in large animals or protected species. Ex-vivo DWI-based tractography offers the chance to examine the microstructure and connectivity of formalin-fixed tissues with scan times and precision that is not feasible in-vivo. This paper explores DWI's application to ex-vivo brains of large animals, highlighting the unique insights it offers into the structure of sometimes phylogenetically different neural networks, the connectivity of white matter tracts, and comparative evolutionary adaptations. Here, we also summarize the challenges, concerns, and perspectives of ex-vivo DWI that will shape the future of the field in large brains.

A reproducible pipeline for parcellation of the anterior limb of the internal capsule.

BACKGROUND: The anterior limb of the internal capsule (ALIC) is a white matter structure connecting the prefrontal cortex (PFC) to the brainstem, thalamus, and subthalamic nucleus. It is a target for deep brain stimulation (DBS) for obsessive-compulsive disorder. There is strong interest in improving DBS targeting by using diffusion tractography to reconstruct and target specific ALIC fiber pathways, but this methodology is susceptible to errors and lacks validation. To address these limitations, we developed a novel diffusion tractography pipeline that generates reliable and biologically validated ALIC white matter reconstructions. METHODS: Following algorithm development and refinement, we analyzed 43 control subjects each with 2 sets of 3T MRI data and a subset of 5 controls with 7T data from the Human Connectome Project. We generated 22 segmented ALIC fiber bundles (11 per hemisphere) based on prefrontal PFC regions of interest, and we analyzed the relationships among bundles. RESULTS: We successfully reproduced the topographies established by prior anatomical work using images acquired at both 3T and 7T. Quantitative assessment demonstrated significantly smaller intra-subject variability relative to inter-subject variability for both test and retest groups across all but one PFC region. We examined the overlap between fibers from different PFC regions and a response tract for obsessive-compulsive disorder deep brain stimulation, and we reconstructed the PFC hyperdirect pathway using a modified version of our pipeline. DISCUSSION: Our dMRI algorithm reliably generates biologically validated ALIC white matter reconstructions, allowing for more precise modelling of fibers for neuromodulation therapies.

Mapping short association fibre connectivity up to V3 in the human brain in vivo.

Short association fibres (SAF) are the most abundant fibre pathways in the human white matter. Until recently, SAF could not be mapped comprehensively in vivo because diffusion weighted magnetic resonance imaging with sufficiently high spatial resolution needed to map these thin and short pathways was not possible. Recent developments in acquisition hardware and sequences allowed us to create a dedicated in vivo method for mapping the SAF based on sub-millimetre spatial resolution diffusion weighted tractography, which we validated in the human primary (V1) and secondary (V2) visual cortex against the expected SAF retinotopic order. Here, we extended our original study to assess the feasibility of the method to map SAF in higher cortical areas by including SAF up to V3. Our results reproduced the expected retinotopic order of SAF in the V2-V3 and V1-V3 stream, demonstrating greater robustness to the shorter V1-V2 and V2-V3 than the longer V1-V3 connections. The demonstrated ability of the method to map higher-order SAF connectivity patterns in vivo is an important step towards its application across the brain.

White matter substrates underlying morphological awareness deficit in Chinese children with developmental dyslexia.

BACKGROUND: Morphological awareness (MA) deficit is strongly associated with Chinese developmental dyslexia (DD). However, little is known about the white matter substrates underlying the MA deficit in Chinese children with DD. METHODS: In the current study, 34 Chinese children with DD and 42 typical developmental (TD) children were recruited to complete a diffusion magnetic resonance imaging scan and cognitive tests for MA. We conducted linear regression to test the correlation between MA and DTI metrics, the structural abnormalities of the tracts related to MA, and the interaction effect of DTI metrics by group on MA. RESULTS: First, MA was significant related to the right inferior occipito-frontal fascicle (IFO) and inferior longitudinal fsciculus (ILF), the bilateral thalamo-occipital (T_OCC) and the left arcuate fasciculus (AF); second, compared to TD children, Chinese children with DD had lower axial diffusivity (AD) in the right IFO and T_OCC; third, there were significant interactions between metrics (fractional anisotropy (FA) and radial diffusivity (RD)) of the right IFO and MA in groups. The FA and RD of the right IFO were significantly associated with MA in children with DD but not in TD children. CONCLUSION: In conclusion, compared to TD children, Chinese children with DD had axonal degeneration not only in the ventral tract (the right IFO) but also the visuospatial tract (the right T_OCC) which were associated with their MA deficit. And Chinese MA involved not only the ventral tracts, but also the visuospatial pathway and dorsal tracts.

Anatomically constrained tractography of the fetal brain.

Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis of the brain white matter and structural connectivity assessment. However, due to the low fetal dMRI data quality and the challenging nature of tractography, existing methods tend to produce highly inaccurate results. They generate many false streamlines while failing to reconstruct the streamlines that constitute the major white matter tracts. In this paper, we advocate for anatomically constrained tractography based on an accurate segmentation of the fetal brain tissue directly in the dMRI space. We develop a deep learning method to compute the segmentation automatically. Experiments on independent test data show that this method can accurately segment the fetal brain tissue and drastically improve the tractography results. It enables the reconstruction of highly curved tracts such as optic radiations. Importantly, our method infers the tissue segmentation and streamline propagation direction from a diffusion tensor fit to the dMRI data, making it applicable to routine fetal dMRI scans. The proposed method can facilitate the study of fetal brain white matter tracts with dMRI.

Comparison of T1-weighted landmark placement and ROI transfer onto diffusion-weighted EPI sequences for targeted tractography tasks in the optic nerve.

Diffusion-based tractography in the optic nerve requires sampling strategies assisted by anatomical landmark information (regions of interest [ROIs]). We aimed to investigate the feasibility of expert-placed, high-resolution T1-weighted ROI-data transfer onto lower spatial resolution diffusion-weighted images. Slab volumes from 20 volunteers were acquired and preprocessed including distortion bias correction and artifact reduction. Constrained spherical deconvolution was used to generate a directional diffusion information grid (fibre orientation distribution-model [FOD]). Three neuroradiologists marked landmarks on both diffusion imaging variants and structural datasets. Structural ROI information (volumetric interpolated breath-hold sequence [VIBE]) was respectively registered (linear with 6/12 degrees of freedom [DOF]) onto single-shot EPI (ss-EPI) and readout-segmented EPI (rs-EPI) volumes, respectively. All eight ROI/FOD-combinations were compared in a targeted tractography task of the optic nerve pathway. Inter-rater reliability for placed ROIs among experts was highest in VIBE images (lower confidence interval 0.84 to 0.97, mean 0.91) and lower in both ss-EPI (0.61 to 0.95, mean 0.79) and rs-EPI (0.59 to 0.86, mean 0.70). Tractography success rate based on streamline selection performance was highest in VIBE-drawn ROIs registered (6-DOF) onto rs-EPI FOD (70.0% over 5%-threshold, capped to failed ratio 39/16) followed by both 12-DOF-registered (67.5%; 41/16) and nonregistered VIBE (67.5%; 40/23). On ss-EPI FOD, VIBE-ROI-datasets obtained fewer streamlines overall with each at 55.0% above 5%-threshold and with lower capped to failed ratio (6-DOF: 35/36; 12-DOF: 34/34, nonregistered 33/36). The combination of VIBE-placed ROIs (highest inter-rater reliability) with 6-DOF registration onto rs-EPI targets (best streamline selection performance) is most suitable for white matter template generation required in group studies.

Diffusion Tensor Imaging (DTI) Biomarker Alterations in Brain Metastases and Comparable Tumors: A Systematic Review of DTI and Tractography Findings.

BACKGROUND: Brain metastases (BMs) are the most frequent tumors of the central nervous system. Diffusion tensor imaging (DTI) is a magnetic resonance imaging technique that provides insights into brain microstructural alterations and tensor metrics and generates tractography to visualize white matter fiber tracts based on diffusion directionality. This systematic review assessed evidence from DTI biomarker alterations in BMs and comparable tumors such as glioblastoma. METHODS: PubMed, Scopus, and Web of Science were searched, and published between January 2000 and August 2023. The key inclusion criteria were studies reporting DTI metrics in BMs and comparisons with other tumors. Data on study characteristics, tumor types, sample details, and main DTI findings were extracted. RESULTS: Fifty-seven studies with 1592 BM patients and 1578 comparable brain tumors were included. Peritumoral fractional anisotropy (FA) consistently differentiates BMs from primary brain tumors, whereas intratumoral FA shows limited discriminatory power. Mean diffusivity increased in BMs versus comparators. Intratumoral metrics were less consistent but revealed differences in BM origin. Axial and radial diffusivity have provided insights into the effects of radiation, tumor origin, and infiltration. Axial diffusivity/radial diffusivity differentiated tumor infiltration from vasogenic edema. Tractography revealed anatomical relationships between white matter tracts and BMs. In addition, tractography-guided BM surgery and radiotherapy planning are required. Machine learning models incorporating DTI biomarkers/metrics accurately classified BMs versus comparators and improved diagnostic classification. CONCLUSIONS: DTI metrics provide noninvasive biomarkers for distinguishing BMs from other tumors and predicting outcomes. Key metrics included peritumoral FA and mean diffusivity.