Diffusion-weighted MR imaging of the brain

Motion-induced phase-corrected homodyne reconstruction for partial Fourier single-shot diffusion-weighted echo planar imaging of the liver

Partial Fourier encoding is popular in single-shot (ss) diffusion-weighted (DW) echo planar imaging (EPI) because it enables a shorter echo time (TE) and, hence, improves the signal-to-noise-ratio. Motion during diffusion encoding causes k-space shifting and dispersion, which compromises the quality of the homodyne reconstruction. This work provides a comprehensive understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data in the presence of motion-induced phase and proposes the motion-induced phase-corrected homodyne (mpc-hdyne) reconstruction method to ameliorate these artifacts. Simulations with different types of motion-induced phase were performed to provide an understanding of the potential artifacts that occur in the homodyne reconstruction of partial Fourier ss-DW-EPI data. To correct for the artifacts, the mpc-hdyne reconstruction is proposed. The algorithm recenters k-space, updates the partial Fourier factor according to detected global k-space shifts, and removes low-resolution nonlinear phase before the conventional homodyne reconstruction. The mpc-hdyne reconstruction is tested on both simulation and in vivo data. Motion-induced phase can cause signal overestimation, worm artifacts, and signal loss in partial Fourier ss-DW-EPI data with the conventional homodyne reconstruction. Simulation and in vivo data showed that the proposed mpc-hdyne reconstruction ameliorated artifacts, yielding higher quality DW images compared with conventional homodyne reconstruction. Based on the understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data, the mpc-hdyne reconstruction was proposed and showed superior performance compared with the conventional homodyne reconstruction on both simulation and in vivo data.

Validation of daily 0.35 T diffusion-weighted MRI for MRI-guided glioblastoma radiotherapy

BACKGROUND

MRI-Linac systems enable daily diffusion-weighed imaging (DWI) MRI scans for assessing glioblastoma tumor changes with radiotherapy treatment.

PURPOSE

Our study assessed the image quality of echoplanar imaging (EPI)-DWI scans compared with turbo spin echo (TSE)-DWI scans at 0.35 Tesla (T) and compared the apparent diffusion coefficient (ADC) values and distortion of EPI-DWI on 0.35 T MRI-Linac compared to high-field diagnostic MRI scanners.

METHODS

The calibrated National Institute of Standards and Technology (NIST)/Quantitative Imaging Biomarkers Alliance (QIBA) Diffusion Phantom was scanned on a 0.35 T MRI-Linac, and 1.5 T and 3 T MRI with EPI-DWI. Five patients were scanned on a 0.35 T MRI-Linac with a TSE-DWI sequence, and five other patients were scanned with EPI-DWI on a 0.35 T MRI-Linac and a 3 T MRI. The quality of images was compared between the TSE-DWI and EPI-DWI on the 0.35 T MRI-Linac assessing signal-to-noise ratios and presence of artifacts. EPI-DWI ADC values and distortion magnitude were measured and compared between 0.35 T MRI-Linac and high-field MRI for both phantom and patient studies.

RESULTS

The average ADC differences between EPI-DWI acquired on the 0.35 T MRI-Linac, 1.5 T and 3 T MRI scanners and published references in the phantom study were 1.7%, 0.4% and 1.0%, respectively. Comparing the ADC values based on EPI-DWI in glioblastoma tumors, there was a 3.36% difference between 0.35 and 3 T measurements. Susceptibility-induced distortions in the EPI-DWI phantoms were 0.46 ± 1.51 mm for 0.35 MRI-Linac, 0.98 ± 0.51 mm for 1.5 T MRI and 1.14 ± 1.88 mm for 3 T MRI; for patients -0.47 ± 0.78 mm for 0.35 T and 1.73 ± 2.11 mm for 3 T MRIs. The mean deformable registration distortion for a phantom was 1.1 ± 0.22 mm, 3.5 ± 0.39 mm and 4.7 ± 0.37 mm for the 0.35 T MRI-Linac, 1.5 T MRI, and 3 T MRI scanners, respectively; for patients this distortion was -0.46 ± 0.57 mm for 0.35 T and 4.2 ± 0.41 mm for 3 T. EPI-DWI 0.35 T MRI-Linac images showed higher SNR and lack of artifacts compared with TSE-DWI, especially at higher b-values up to 1000 s/mm2.

CONCLUSION

EPI-DWI on a 0.35 T MRI-Linac showed superior image quality compared with TSE-DWI, minor and less distortions than high-field diagnostic scanners, and comparable ADC values in phantoms and glioblastoma tumors. EPI-DWI should be investigated on the 0.35 T MRI-Linac for prediction of early response in patients with glioblastoma.

Comparison of apparent diffusion coefficient (ADC) values obtained by echo planar imaging diffusion-weighted imaging (DWI) and radial acquisition regime DWI in low field MRI systems: A phantom study

INTRODUCTION

Diffusion-weighted imaging (DWI) with radial acquisition regime (RADAR; RADAR-DWI) is a fast spin echo (FSE)-based DWI imaging technique that is known to be robust to magnetic susceptibility artifacts and distortions as compared with echo planar imaging DWI (EPI-DWI). Several reports have suggested that the apparent diffusion coefficient (ADC) values obtained with FSE-based DWI are different from those obtained with EPI-DWI. The purpose of this study was to create phantoms that mimic the T2 and ADC values of various tissues and to demonstrate the ADC values obtained with RADAR-DWI and EPI-DWI in low-field magnetic resonance imaging (MRI) systems.

METHODS

Several phantoms were created using sucrose and manganese (II) chloride tetrahydrate mimicking various tissues. RADAR-DWI and EPI-DWI were used to scan the phantoms, and the obtained ADC values were compared.

RESULTS

The ADC values obtained with RADAR-DWI were significantly higher than those obtained with EPI-DWI for all phantoms (P < 0.05). The ADC values obtained by RADAR-DWI ranged from 0.70 ± 0.01 to 1.21 ± 0.02 ( × 10-3mm2s-1). Meanwhile, the ADC values obtained with EPI-DWI ranged from 0.59 ± 0.01 to 1.08 ± 0.05 ( × 10-3mm2s-1).

CONCLUSIONS

We created phantoms mimicking T2 and ADC values of various tissues and demonstrated the differences in ADC values obtained with RADAR-DWI and EPI-DWI using low-field MRI systems.

IMPLICATIONS FOR PRACTICE

ADC values obtained by RADAR-DWI are significantly higher than those obtained by EPI-DWI, with different cutoff values for various tumor malignancies between them.

T1-mapping characterization of two tumor types

T1 mapping is a quantitative method to characterize tissues with magnetic resonance imaging in a quick and efficient manner. It utilizes the relaxation rate of protons to depict the underlying structures within the imaging frame. While T1-mapping techniques are used with some frequency in areas such as cardiac imaging, their application for understanding malignancies and identifying tumor structures has yet to be thoroughly investigated. Utilizing a saturation recovery method to acquire T1 maps for two different tumor models has revealed that longitudinal relaxation mapping is sensitive enough to distinguish between normal and malignant tissue. This is seen even with decreased signal/noise ratios using small voxel sizes to obtain high-resolution images. In both tumor models, it was revealed that relaxation mapping recorded significantly different relaxation values between regions encapsulating the tumor, muscle, kidney, or spleen, as well as between the cell lines themselves. This indicates a potential future application of relaxation mapping as a method to fingerprint various stages of tumor development and may prove a useful measure to identify micro-metastases.

MRI predictors of long-term outcomes of neonatal hypoxic ischaemic encephalopathy: a primer for radiologists

This review aims to serve as a foundational resource for general radiologists, enhancing their understanding of the role of Magnetic Resonance Imaging (MRI) in early prognostication for newborns diagnosed with hypoxic ischaemic encephalopathy (HIE). The article explores the application of MRI as a predictive instrument for determining long-term outcomes in newborns affected by HIE. With HIE constituting a leading cause of neonatal mortality and severe long-term neurodevelopmental impairments, early identification of prognostic indicators is crucial for timely intervention and optimal clinical management. We examine current literature and recent advancements to provide an in-depth overview of MRI predictors, encompassing brain injury patterns, injury scoring systems, spectroscopy, and diffusion imaging. The potential of these MRI biomarkers in predicting long-term neurodevelopmental outcomes and the probability of epilepsy is also discussed.

Predicting glioblastoma recurrence using multiparametric MR imaging of non-enhancing peritumoral regions at baseline

Background

To assess the feasibility of multiparametric magnetic resonance imaging in predicting tumor recurrence in nonenhancing peritumoral regions in patients with glioblastoma at baseline.

Methods

Fifty-eight patients with recurrent glioblastoma underwent multiparametric magnetic resonance imaging, including T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging. Nonenhancing peritumoral regions with glioblastoma recurrence were identified by coregistering preoperative and post-recurrent magnetic resonance images. Regions of interest were placed in nonenhancing peritumoral regions with and without tumor recurrence to calculate the apparent diffusion coefficient value, and relative ratios of T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and cerebral blood volume values.

Results

Significant lower relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative apparent diffusion coefficient but higher relative cerebral blood volume values were found in the nonenhancing peritumoral regions with tumor recurrence than without recurrence (all P < 0.05). The threshold values ≥ 0.89 for relative cerebral blood volume provide the optimal performance for predicting the nonenhancing peritumoral regions with future tumor recurrence, with the sensitivity, specificity, and accuracy of 84.7%, 83.6%, and 85.8%, respectively. The combination of relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative cerebral blood volume can provide better predictive performance than relative cerebral blood volume (P = 0.015).

Conclusion

The combined use of T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging can effectively estimate the risk of future tumor recurrence at baseline.

Multimodal Approach to Neurocognitive Function in People Living with HIV in the cART Era: A Comprehensive Review

Combination antiretroviral treatment (cART) has revolutionized the management of human immunodeficiency virus (HIV) and has markedly improved the disease burden and life expectancy of people living with HIV. HIV enters the central nervous system (CNS) early in the course of infection, establishes latency, and produces a pro-inflammatory milieu that may affect cognitive functions, even in the cART era. Whereas severe forms of neurocognitive impairment (NCI) such as HIV-associated dementia have declined over the last decades, milder forms have become more prevalent, are commonly multifactorial, and are associated with comorbidity burdens, mental health, cART neurotoxicity, and ageing. Since 2007, the Frascati criteria have been used to characterize and classify HIV-associated neurocognitive disorders (HAND) into three stages, namely asymptomatic neurocognitive impairment (ANI), mild neurocognitive disorder (MND), and HIV-associated dementia (HAD). These criteria are based on a comprehensive neuropsychological assessment that presupposes the availability of validated, demographically adjusted, and normative population data. Novel neuroimaging modalities and biomarkers have been proposed in order to complement NCI assessments, elucidate neuropathogenic mechanisms, and support HIV-associated NCI diagnosis, monitoring, and prognosis. By integrating neuropsychological assessments with biomarkers and neuroimaging into a holistic care approach, clinicians can enhance diagnostic accuracy, prognosis, and patient outcomes. This review interrogates the value of these modes of assessment and proposes a unified approach to NCI diagnosis.

Molecular Mechanisms of Ischemic Stroke: A Review Integrating Clinical Imaging and Therapeutic Perspectives

Ischemic stroke poses a significant global health challenge, necessitating ongoing exploration of its pathophysiology and treatment strategies. This comprehensive review integrates various aspects of ischemic stroke research, emphasizing crucial mechanisms, therapeutic approaches, and the role of clinical imaging in disease management. It discusses the multifaceted role of Netrin-1, highlighting its potential in promoting neurovascular repair and mitigating post-stroke neurological decline. It also examines the impact of blood-brain barrier permeability on stroke outcomes and explores alternative therapeutic targets such as statins and sphingosine-1-phosphate signaling. Neurocardiology investigations underscore the contribution of cardiac factors to post-stroke mortality, emphasizing the importance of understanding the brain-heart axis for targeted interventions. Additionally, the review advocates for early reperfusion and neuroprotective agents to counter-time-dependent excitotoxicity and inflammation, aiming to preserve tissue viability. Advanced imaging techniques, including DWI, PI, and MR angiography, are discussed for their role in evaluating ischemic penumbra evolution and guiding therapeutic decisions. By integrating molecular insights with imaging modalities, this interdisciplinary approach enhances our understanding of ischemic stroke and offers promising avenues for future research and clinical interventions to improve patient outcomes.

Diffusion-weighted imaging does not seem to be a predictor of consistency in pituitary adenomas

PURPOSE

To prospectively evaluate the usefulness of T1-weighted imaging (T1WI) and diffusion-weighted imaging (DWI) sequences in predicting the consistency of macroadenomas. In addition, to determine their values ​​as prognostic factors of surgical outcomes.

METHODS

Patients with pituitary macroadenoma and surgical indication were included. All patients underwent pre-surgical magnetic resonance imaging (MRI) that included the sequences T1WI before and after contrast administration and DWI with the apparent diffusion coefficient (ADC) map. Post-surgical MRI was performed at least 3 months after surgery. The consistency of the macroadenomas was evaluated at surgery, and they were grouped into soft and intermediate/hard adenomas. Mean ADC values, signal on T1WI and the ratio of tumor ADC values ​​to pons (ADCR) were compared with tumor consistency and grade of surgical resection.

RESULTS

A total of 80 patients were included. A softened consistency was found at surgery in 53 patients and hardened in 27 patients. The median ADC in the soft consistency group was 0.532 × 10-3 mm2/sec (0.306 - 1.096 × 10-3 mm2/sec), and in the intermediate/hard consistency group was 0.509 × 10-3 mm2/sec (0.308 - 0.818 × 10-3 mm2/sec). There was no significant difference between the median values ​​of ADC, ADCR and signal on T1W between the soft and hard tumor groups, or between patients with and without tumor residue.

CONCLUSION

Our results did not show usefulness of the DWI and T1WI for assessing the consistency of pituitary macroadenomas, nor as a predictor of the degree of surgical resection.

Highly accelerated multi-shot intravoxel incoherent motion diffusion-weighted imaging in brain enabled by parametric POCS-based multiplexed sensitivity encoding

Recently, intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has also been demonstrated as an imaging tool for applications in neurological and neurovascular diseases. However, the use of single-shot diffusion-weighted echo-planar imaging for IVIM DWI acquisition leads to suboptimal data quality: for instance, geometric distortion and deteriorated image quality at high spatial resolution. Although the recently commercialized multi-shot acquisition methods, such as multiplexed sensitivity encoding (MUSE), can attain high-resolution and high-quality DWI with signal-to-noise ratio (SNR) performance superior to that of the conventional parallel imaging method, the prolonged scan time associated with multi-shot acquisition is impractical for routine IVIM DWI. This study proposes an acquisition and reconstruction framework based on parametric-POCSMUSE to accelerate the four-shot IVIM DWI with 70% reduction of total scan time (13 min 8 s versus 4 min 8 s). First, the four-shot IVIM DWI scan with 17 b values was accelerated by acquiring only one segment per b value except for b values of 0 and 600 s/mm2 . Second, an IVIM-estimation scheme was integrated into the parametric-POCSMUSE to enable joint reconstruction of multi-b images from under-sampled four-shot IVIM DWI data. In vivo experiments on both healthy subjects and patients show that the proposed framework successfully produced multi-b DW images with significantly higher SNRs and lower reconstruction errors than did the conventional acceleration method based on parallel imaging. In addition, the IVIM quantitative maps estimated from the data produced by the proposed framework showed quality comparable to that of fully sampled MUSE-reconstructed images, suggesting that the proposed framework can enable highly accelerated multi-shot IVIM DWI without sacrificing data quality. In summary, the proposed framework can make multi-shot IVIM DWI feasible in a routine MRI examination, with reasonable scan time and improved geometric fidelity.

Clinical and imaging markers for the prognosis of acute ischemic stroke

Background and purpose

Significant differences in the outcomes observed in patients with acute ischemic stroke (AIS) have led to research investigations for identifying the predictors. In this retrospective study, we aimed to investigate the relationship of different clinical and imaging factors with the prognosis of AIS.

Materials and methods

All clinical and imaging metrics were compared between the good and poor prognosis groups according to the modified Rankin Scale (mRS) score at 90 days after discharge. Clinical factors included gender, age, NIHSS scores at admission, and other medical history risk factors. Imaging markers included the lesion's size and location, diffusion, and perfusion metrics of infarction core and peripheral regions, and the state of collateral circulation. Spearman's correlations were analyzed for age and imaging markers between the different groups. The Chi-square test and Cramer's V coefficient analysis were performed for gender, collateral circulation status, NIHSS score, and other stroke risk factors.

Results

A total of 89 patients with AIS were divided into the good (mRS score ≤ 2) and poor prognosis groups (mRS score ≥ 3). There were differences in NIHSS score at the admission; relative MK (rMK), relative MD (rMD), relative CBF (rCBF) of the infarction core; relative mean transit time (rMTT), relative time to peak (rTTP), and relative CBF (rCBF) of peripheral regions; and collateral circulation status between the two groups (p < 0.05). Among them, the rMK of infarction lesions had the strongest correlation with the mRS score at 90 days after discharge (r = 0.545, p < 0.001).

Conclusion

Perfusion and diffusion metrics could reflect the microstructure and blood flow characteristics of the lesion, which were the key factors for the salvage ability and prognosis of the infarction tissue. The characteristics of the infarction core and peripheral regions have different effects on the outcomes. Diffusion of infarction core has strong relations with the prognosis, whereas the time metrics (MTT, TTP) were more important for peripheral regions. MK had a more significant association with prognosis than MD. These factors were the primary markers influencing the prognosis of cerebral infarction patients.

Non-contrast dual-energy CT using X-map for acute ischemic stroke: region-specific comparison with simulated 120-kVp CT and diffusion-weighted MR images

PURPOSE

X-map is a non-contrast dual-energy CT (DECT) application to identify acute ischemic stroke (AIS). Our aim was to verify region-specific characteristics of early ischemic changes (EIC) on X-map compared with simulated 120-kVp mixed-CT image and DWI.

METHODS

Fifty AIS patients who underwent DECT and DWI were enrolled (mean age, 76 years; 34 men, 16 women). All datasets including mixed-CT image, X-map, and DWI were transformed into a standard brain atlas with 11 × 2 ROIs based on the ASPECTS + W system. ROIs with EIC on DWI, mixed-CT image, and X-map were defined as DWI-positive, mixed-CT-positive, and X-map-positive, and those with normal finding were DWI-negative, mixed-CT-negative, and X-map-negative respectively, in visual assessment by two neuroradiologists in consensus.

RESULTS

EIC on X-maps were visually relevant to those on the other images: of 221 ROIs with mixed-CT-positive and X-map-positive, 198 (89.6%) were DWI-positive. X-map revealed moderate diagnostic accuracy for AIS compared with DWI in ROC curve analysis (AUC = 0.732). X-map identified EIC in deep white matter more sensitively than mixed-CT image: of 15 ROIs with mixed-CT-negative and X-map-positive in W segments, 14 (93.3%) were DWI-positive. X-map often showed EIC in cortical regions that were not detected on the other images: of 67 ROIs with mixed-CT-negative and X-map-positive in I and M1-M6 segments, 47 (70.1%) were DWI-negative.

CONCLUSIONS

X-map is useful to detect EIC, especially in deep white matter, and may also provide additional information in acute ischemic lesions where DWI cannot be detected.

Analysis of Diffusion-Weighted and T2-Weighted Imaging in the Prediction of Distinct Granulation Patterns of Somatotroph Adenomas

OBJECTIVE

The heterogeneity of the somatotroph adenomas, especially for sparsely granulated (SG) and densely granulated (DG) subtypes, has attracted great attention in identifying their imaging biomarker. The purpose of the current study was to compare the diagnostic performance of diffusion-weighted and T2-weighted magnetic resonance imaging (MRI) sequences for preoperatively distinguishing the granulation patterns of somatotroph adenomas.

METHODS

Thirty-two patients with a clinical diagnosis of somatotroph adenomas from October 2018 to March 2023 were included in this study. Coronal diffusion-weighted imaging (DWI) and T2-weighted MRI sequence data were collected from 3.0T MRI and compared between SG and DG groups. The immunohistochemistry was used to confirm the electron microscopy pathologic subtypes and Ki67 expression levels of somatotroph adenomas postoperatively.

RESULTS

Patients in the SG group had significantly higher signal intensity (SI) ratio of DWI (rDWI) (P < 0.001), lower SI ratio of apparent diffusion coefficient (rADC) (P < 0.001), and higher SI ratio of T2-weighted imaging (P = 0.011). The combined diagnosis index of rDWI and rADC had the highest diagnostic efficiency in predicting SG adenomas (sensitivity, 93.3%; specificity, 88.2%; P < 0.001). The rDWI and rADC values had positive and negative correlations with the Ki67 index and tumor maximum diameter, respectively. Lower rADC×103 was an independent predictor for SG adenomas.

CONCLUSIONS

Our results indicated that compared with previously used T2-weighted imaging, the DWI sequence, especially the combined diagnosis index of rDWI and rADC, could more efficiently distinguish the granulation patterns of somatotroph adenomas preoperatively.

Status epilepticus in BRAF-related cardio-facio-cutaneous syndrome: Focus on neuroimaging clues to physiopathology

OBJECTIVE

Cardio-facio-cutaneous syndrome (CFC) is a genetic disorder due to variants affecting genes coding key proteins of the Ras/MAPK signaling pathway. Among the different features of CFC, neurological involvement, including cerebral malformations and epilepsy, represents a common and clinically relevant aspect. Status epilepticus (SE) is a recurrent feature, especially in a specific subgroup of CFC patients with developmental and epileptic encephalopathy (DEE) and history of severe pharmacoresistant epilepsy. Here we dissect the features of SE in CFC patients with a particular focus on longitudinal magnetic resonance imaging (MRI) findings to identify clinical-radiological patterns and discuss the underlying physiopathology.

METHODS

We retrospectively analyzed clinical, electroencephalogram (EEG), and MRI data collected in a single center from a cohort of 23 patients with CFC carrying pathogenic BRAF variants who experienced SE during a 5-year period.

RESULTS

Seven episodes of SE were documented in 5 CFC patients who underwent EEG and MRI at baseline. MRI was performed during SE/within 72 hours from SE termination in 5/7 events. Acute/early post-ictal MRI findings showed heterogenous abnormalities: restricted diffusion in 2/7, focal area of pcASL perfusion change in 2/7, focal cortical T2/FLAIR hyperintensity in 2/7. Follow-up images were available for 4/7 SE. No acute changes were detected in 2/7 (MRI performed 4 days after SE termination).

SIGNIFICANCE

Acute focal neuroimaging changes concomitant with ictal EEG focus were present in 5/7 episodes, though with different findings. The heterogeneous patterns suggest different contributing factors, possibly including the presence of focal cortical malformations and autoinflammation. When cytotoxic edema is revealed by MRI, it can be followed by permanent structural damage, as already observed in other genetic conditions. A better understanding of the physiopathology will provide access to targeted treatments allowing to prevent long-term adverse neurological outcome.

PLAIN LANGUAGE SUMMARY

Cardio-facio-cutaneous syndrome is a genetic disorder that often causes prolonged seizures known as status epilepticus. This study has a focus on electroclinical and neuroimaging patterns in patients with cardio-facio-cutaneous syndrome. During these status epilepticus episodes, we found different abnormal brain imaging patterns in patients, indicating various causes like brain malformations and inflammation. Understanding these patterns could help doctors find specific treatments, protecting cardio-facio-cutaneous syndrome patients from long-term brain damage.

Neuromonitoring after Pediatric Cardiac Arrest: Cerebral Physiology and Injury Stratification

BACKGROUND

Significant long-term neurologic disability occurs in survivors of pediatric cardiac arrest, primarily due to hypoxic-ischemic brain injury. Postresuscitation care focuses on preventing secondary injury and the pathophysiologic cascade that leads to neuronal cell death. These injury processes include reperfusion injury, perturbations in cerebral blood flow, disturbed oxygen metabolism, impaired autoregulation, cerebral edema, and hyperthermia. Postresuscitation care also focuses on early injury stratification to allow clinicians to identify patients who could benefit from neuroprotective interventions in clinical trials and enable targeted therapeutics.

METHODS

In this review, we provide an overview of postcardiac arrest pathophysiology, explore the role of neuromonitoring in understanding postcardiac arrest cerebral physiology, and summarize the evidence supporting the use of neuromonitoring devices to guide pediatric postcardiac arrest care. We provide an in-depth review of the neuromonitoring modalities that measure cerebral perfusion, oxygenation, and function, as well as neuroimaging, serum biomarkers, and the implications of targeted temperature management.

RESULTS

For each modality, we provide an in-depth review of its impact on treatment, its ability to stratify hypoxic-ischemic brain injury severity, and its role in neuroprognostication.

CONCLUSION

Potential therapeutic targets and future directions are discussed, with the hope that multimodality monitoring can shift postarrest care from a one-size-fits-all model to an individualized model that uses cerebrovascular physiology to reduce secondary brain injury, increase accuracy of neuroprognostication, and improve outcomes.

Advancing noninvasive glioma classification with diffusion radiomics: Exploring the impact of signal intensity normalization

Background

This study investigates the influence of diffusion-weighted Magnetic Resonance Imaging (DWI-MRI) on radiomic-based prediction of glioma types according to molecular status and assesses the impact of DWI intensity normalization on model generalizability.

Methods

Radiomic features, compliant with image biomarker standardization initiative standards, were extracted from preoperative MRI of 549 patients with diffuse glioma, known IDH, and 1p19q-status. Anatomical sequences (T1, T1c, T2, FLAIR) underwent N4-Bias Field Correction (N4) and WhiteStripe normalization (N4/WS). Apparent diffusion coefficient (ADC) maps were normalized using N4 or N4/z-score. Nine machine-learning algorithms were trained for multiclass prediction of glioma types (IDH-mutant 1p/19q codeleted, IDH-mutant 1p/19q non-codeleted, IDH-wild type). Four approaches were compared: Anatomical, anatomical + ADC naive, anatomical + ADC N4, and anatomical + ADC N4/z-score. The University of California San Francisco (UCSF)-glioma dataset (n = 409) was used for external validation.

Results

Naïve-Bayes algorithms yielded overall the best performance on the internal test set. Adding ADC radiomics significantly improved AUC from 0.79 to 0.86 (P = .011) for the IDH-wild-type subgroup, but not for the other 2 glioma subgroups (P > .05). In the external UCSF dataset, the addition of ADC radiomics yielded a significantly higher AUC for the IDH-wild-type subgroup (P ≤ .001): 0.80 (N4/WS anatomical alone), 0.81 (anatomical + ADC naive), 0.81 (anatomical + ADC N4), and 0.88 (anatomical + ADC N4/z-score) as well as for the IDH-mutant 1p/19q non-codeleted subgroup (P < .012 each).

Conclusions

ADC radiomics can enhance the performance of conventional MRI-based radiomic models, particularly for IDH-wild-type glioma. The benefit of intensity normalization of ADC maps depends on the type and context of the used data.

Robust fiber orientation distribution function estimation using deep constrained spherical deconvolution for diffusion-weighted magnetic resonance imaging

Purpose

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a critical imaging method for capturing and modeling tissue microarchitecture at a millimeter scale. A common practice to model the measured DW-MRI signal is via fiber orientation distribution function (fODF). This function is the essential first step for the downstream tractography and connectivity analyses. With recent advantages in data sharing, large-scale multisite DW-MRI datasets are being made available for multisite studies. However, measurement variabilities (e.g., inter- and intrasite variability, hardware performance, and sequence design) are inevitable during the acquisition of DW-MRI. Most existing model-based methods [e.g., constrained spherical deconvolution (CSD)] and learning-based methods (e.g., deep learning) do not explicitly consider such variabilities in fODF modeling, which consequently leads to inferior performance on multisite and/or longitudinal diffusion studies.

Approach

In this paper, we propose a data-driven deep CSD method to explicitly constrain the scan-rescan variabilities for a more reproducible and robust estimation of brain microstructure from repeated DW-MRI scans. Specifically, the proposed method introduces a three-dimensional volumetric scanner-invariant regularization scheme during the fODF estimation. We study the Human Connectome Project (HCP) young adults test-retest group as well as the MASiVar dataset (with inter- and intrasite scan/rescan data). The Baltimore Longitudinal Study of Aging dataset is employed for external validation.

Results

From the experimental results, the proposed data-driven framework outperforms the existing benchmarks in repeated fODF estimation. By introducing the contrastive loss with scan/rescan data, the proposed method achieved a higher consistency while maintaining higher angular correlation coefficients with the CSD modeling. The proposed method is assessing the downstream connectivity analysis and shows increased performance in distinguishing subjects with different biomarkers.

Conclusion

We propose a deep CSD method to explicitly reduce the scan-rescan variabilities, so as to model a more reproducible and robust brain microstructure from repeated DW-MRI scans. The plug-and-play design of the proposed approach is potentially applicable to a wider range of data harmonization problems in neuroimaging.

Heterogeneous Diffusion Metrics Patterns in Delayed Encephalopathy After Acute Carbon Monoxide Poisoning: A Case Report

Delayed encephalopathy (DE) following acute carbon monoxide (CO) poisoning is characterized by a wide range of neurological symptoms, including akinetic mutism, cognitive impairment, and gait disturbances. Herein, we reported the case of a 61-year-old patient with DE after acute CO poisoning, who displayed heterogeneous patterns of cortical and subcortical structural integrity on diffusion tensor imaging (DTI). Four distinct patterns of diffusion tensor metrics (fractional anisotropy [FA] and mean diffusivity [MD]) were observed in the patient compared to age-matched controls (a decrease in FA and an increase in MD, a decrease in FA only, an increase in MD only, and an increase in FA and MD). This study revealed heterogeneous patterns of cortical and subcortical damage associated with DE after CO poisoning, contributing to a deeper understanding of the diverse clinical symptoms observed in this patient.

Magnetic resonance imaging features of presumed intracerebral hemorrhages in dogs show a significant association between apparent diffusion coefficient peripheral layer and estimated bleeding age and commonly exhibit a T2 blackout effect

In humans, intracranial hematomas commonly exhibit a T2 blackout effect (BOE) with diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps. Published descriptions of comparable findings in dogs with intracerebral hemorrhages are lacking. Aims of this retrospective observational study were to describe the appearance of presumed intracerebral hemorrhages (PICHs) in DWI regardless of the underlying etiology and presence of T2 blackout effect (T2 BOE) in dogs and to test potential associations with DWI and ADC findings versus the estimated age of the hemorrhage. Magnetic resonance imaging studies of dogs with presumed PICHs based on the combined evaluation of T2*W gradient echo and/or susceptibility-weighted imaging, T1W and T2W images were enrolled. The age of the hemorrhage was estimated according to published criteria based on T1W and T2W sequences. The association between the age of the hemorrhage and the appearance of each finding (stratified or mixed), their signal intensities in DWI/ADC and the presence of the T2 BOE, was evaluated. A total of 35 PICHs were included: 13 of them were stratified and 22 had a mixed aspect. Only the ADC appearance of the peripheral layer in stratified PICHs was significantly associated with estimated age of the hemorrhage (p = .033), being hypointense in all hyperacute cases and hypo-/isointense in acute cases. The T2 BOE was present in 29/35 PICHs. The DWI sequences showed limited utility to date PICHs in this study population. As in humans, the T2 BOE was commonly seen in DWI and ADC maps of dogs with PICHs.

Prognostic Neuroimaging Biomarkers in Acute Vascular Brain Injury and Traumatic Brain Injury

Prognostic imaging biomarkers after acute brain injury inform treatment decisions, track the progression of intracranial injury, and can be used in shared decision-making processes with families. Herein, key established biomarkers and prognostic scoring systems are surveyed in the literature, and their applications in clinical practice and clinical trials are discussed. Biomarkers in acute ischemic stroke include computed tomography (CT) hypodensity scoring, diffusion-weighted lesion volume, and core infarct size on perfusion imaging. Intracerebral hemorrhage biomarkers include hemorrhage volume, expansion, and location. Aneurysmal subarachnoid biomarkers include hemorrhage grading, presence of diffusion-restricting lesions, and acute hydrocephalus. Traumatic brain injury CT scoring systems, contusion expansion, and diffuse axonal injury grading are reviewed. Emerging biomarkers including white matter disease scoring, diffusion tensor imaging, and the automated calculation of scoring systems and volumetrics are discussed.

Biogenic Imaging Contrast Agents

Imaging contrast agents are widely investigated in preclinical and clinical studies, among which biogenic imaging contrast agents (BICAs) are developing rapidly and playing an increasingly important role in biomedical research ranging from subcellular level to individual level. The unique properties of BICAs, including expression by cells as reporters and specific genetic modification, facilitate various in vitro and in vivo studies, such as quantification of gene expression, observation of protein interactions, visualization of cellular proliferation, monitoring of metabolism, and detection of dysfunctions. Furthermore, in human body, BICAs are remarkably helpful for disease diagnosis when the dysregulation of these agents occurs and can be detected through imaging techniques. There are various BICAs matched with a set of imaging techniques, including fluorescent proteins for fluorescence imaging, gas vesicles for ultrasound imaging, and ferritin for magnetic resonance imaging. In addition, bimodal and multimodal imaging can be realized through combining the functions of different BICAs, which helps overcome the limitations of monomodal imaging. In this review, the focus is on the properties, mechanisms, applications, and future directions of BICAs.

Differences between early and late MRI in infants with neonatal encephalopathy following therapeutic hypothermia

BACKGROUND

MRI is the gold standard test to define brain injury in infants with neonatal encephalopathy(NE). As imaging findings evolve considerably over the first week, early imaging may not fully reflect the final nature of the injury. This study aimed to compare day 4 versus second week MRI in infants with NE.

METHODS

Retrospective cohort study including infants who received therapeutic hypothermia(TH) for NE and had two MRIs: early (≤7days) and late (>7days). MRIs were clinically reported and also reviewed by study investigators.

RESULTS

94infants with NE were included (40mild,49moderate,5severe). Twenty-four infants(26%) had a normal early scan of which 3/24(13%) had injury noted on repeat MRI. Seventy infants(74%) had abnormal findings noted on early MRI, of which 4/70(6%) had further evolution of injury while 11/70(16%) had complete resolution of findings. Applying a grading system resulted in a change of grade in 7 infants.

CONCLUSION

In infants who received TH for NE, 19% had changes noted between their early and late MRIs. While the impact on predicting neurodevelopmental outcome was not studied, relying solely on early MRI may overestimate injury in a proportion of infants and miss injury in others. Combining early and late MRI allows for better characterization of injury.

IMPACT

MRI is the gold standard tool to define brain injury in infants with NE, however, imaging findings evolve considerably over the first week of life. Most centers perform a single MRI on day 4 after rewarming. In our cohort, 19% of infants had a notable change in their MRI findings between early (within the first week) and late (beyond the first week) scans. Relying solely on early MRI may overestimate injury in a proportion of infants and miss injury in others. Combining early and late MRI following hypothermia allows for better characterization of brain injury.

Stimulated Raman scattering microscopy reveals a unique and steady nature of brain water dynamics

The biological activities of substances in the brain are shaped by their spatiotemporal dynamics in brain tissues, all of which are regulated by water dynamics. In contrast to solute dynamics, water dynamics have been poorly characterized, owing to the lack of appropriate analytical tools. To overcome this limitation, we apply stimulated Raman scattering multimodal multiphoton microscopy to live brain tissues. The microscopy system allows for the visualization of deuterated water, fluorescence-labeled solutes, and cellular structures at high spatiotemporal resolution, revealing that water moves faster than fluorescent molecules in brain tissues. Detailed analyses demonstrate that water, unlike solutes, diffuses homogeneously in brain tissues without differences between the intra- and the extracellular routes. Furthermore, we find that the water dynamics are steady during development and ischemia, when diffusions of solutes are severely affected. Thus, our approach reveals routes and uniquely robust properties of water diffusion in brain tissues.

Imaging of pediatric brain tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee/ASPNR White Paper

Tumors of the central nervous system are the most common solid malignancies in children and the most common cause of pediatric cancer-related mortality. Imaging plays a central role in diagnosis, staging, treatment planning, and response assessment of pediatric brain tumors. However, the substantial variability in brain tumor imaging protocols across institutions leads to variability in patient risk stratification and treatment decisions, and complicates comparisons of clinical trial results. This White Paper provides consensus-based imaging recommendations for evaluating pediatric patients with primary brain tumors. The proposed brain magnetic resonance imaging protocol recommendations balance advancements in imaging techniques with the practicality of deployment across most imaging centers.

Clinical infections in neurosurgical oncology: An overview

Central nervous system (CNS) infections are urgent conditions with high morbidity and mortality. Bacteria, viruses, parasites or fungi can cause them. Intracranial infections after craniotomies are an important complication of treatment, especially in oncological patients that are already immunologically compromised due to the disease and treatment. The consequence of CNS infections in oncological patients includes longer treatment with antibiotics, additional surgical procedures, higher treatment costs and poorer treatment outcomes. Additionally, the management of primary pathology may be prolonged or postponed as a result of the active infection. By introducing new and improved protocols, tightening controls on their implementation, constantly educating the entire team involved in patient treatment and educating both patients and relatives, the incidence of infections can be reduced effectively.

Pitfalls of Diffusion-Weighted Imaging: Clinical Utility of T2 Shine-through and T2 Black-out for Musculoskeletal Diseases

Diffusion-weighted imaging (DWI) with an apparent diffusion coefficient (ADC) value is a relatively new magnetic resonance imaging (MRI) sequence that provides functional information on the lesion by measuring the microscopic movement of water molecules. While numerous studies have evaluated the promising role of DWI in musculoskeletal radiology, most have focused on tumorous diseases related to cellularity. This review article aims to summarize DWI-acquisition techniques, considering pitfalls such as T2 shine-through and T2 black-out, and their usefulness in interpreting musculoskeletal diseases with imaging. DWI is based on the Brownian motion of water molecules within the tissue, achieved by applying diffusion-sensitizing gradients. Regardless of the cellularity of the lesion, several pitfalls must be considered when interpreting DWI with ADC values in musculoskeletal radiology. This review discusses the application of DWI in musculoskeletal diseases, including tumor and tumor mimickers, as well as non-tumorous diseases, with a focus on lesions demonstrating T2 shine-through and T2 black-out effects. Understanding these pitfalls of DWI can provide clinically useful information, increase diagnostic accuracy, and improve patient management when added to conventional MRI in musculoskeletal diseases.

Tumefactive Demyelination in MOG Ab-Associated Disease, Multiple Sclerosis, and AQP-4-IgG-Positive Neuromyelitis Optica Spectrum Disorder

BACKGROUND AND OBJECTIVES

Studies on tumefactive brain lesions in myelin oligodendrocyte glycoprotein-immunoglobulin G (IgG)-associated disease (MOGAD) are lacking. We sought to characterize the frequency clinical, laboratory, and MRI features of these lesions in MOGAD and compare them with those in multiple sclerosis (MS) and aquaporin-4-IgG-positive neuromyelitis optica spectrum disorder (AQP4+NMOSD).

METHODS

We retrospectively searched 194 patients with MOGAD and 359 patients with AQP4+NMOSD with clinical/MRI details available from the Mayo Clinic databases and included those with ≥1 tumefactive brain lesion (maximum transverse diameter ≥2 cm) on MRI. Patients with tumefactive MS were identified using the Mayo Clinic medical record linkage system. Binary multivariable stepwise logistic regression identified independent predictors of MOGAD diagnosis; Cox proportional regression models were used to assess the risk of relapsing disease and gait aid in patients with tumefactive MOGAD vs those with nontumefactive MOGAD.

RESULTS

We included 108 patients with tumefactive demyelination (MOGAD = 43; AQP4+NMOSD = 16; and MS = 49). Tumefactive lesions were more frequent among those with MOGAD (43/194 [22%]) than among those with AQP4+NMOSD (16/359 [5%], p < 0.001). Risk of relapse and need for gait aid were similar in tumefactive and nontumefactive MOGAD. Clinical features more frequent in MOGAD than in MS included headache (18/43 [42%] vs 10/49 [20%]; p = 0.03) and somnolence (12/43 [28%] vs 2/49 [4%]; p = 0.003), the latter also more frequent than in AQP4+NMOSD (0/16 [0%]; p = 0.02). The presence of peripheral T2-hypointense rim, T1-hypointensity, diffusion restriction (particularly an arc pattern), ring enhancement, and Baló-like or cystic appearance favored MS over MOGAD (p ≤ 0.001). MRI features were broadly similar in MOGAD and AQP4+NMOSD, except for more frequent diffusion restriction in AQP4+NMOSD (10/15 [67%]) than in MOGAD (11/42 [26%], p = 0.005). CSF analysis revealed less frequent positive oligoclonal bands in MOGAD (2/37 [5%]) than in MS (30/43 [70%], p < 0.001) and higher median white cell count in MOGAD than in MS (33 vs 6 cells/μL, p < 0.001). At baseline, independent predictors of MOGAD diagnosis were the presence of somnolence/headache, absence of T2-hypointense rim, lack of T1-hypointensity, and no diffusion restriction (Nagelkerke R 2 = 0.67). Tumefactive lesion resolution was more common in MOGAD than in MS or AQP4+NMOSD and improved model performance.

DISCUSSION

Tumefactive lesions are frequent in MOGAD but not associated with a worse prognosis. The clinical, MRI, and CSF attributes of tumefactive MOGAD differ from those of tumefactive MS and are more similar to those of tumefactive AQP4+NMOSD with the exception of lesion resolution, which favors MOGAD.

Case Report: Late spontaneous orbital subperiosteal hematoma after endoscopic sinonasal tumor resection

INTRODUCTION AND IMPORTANCE

We report a case of spontaneous subperiosteal orbital hematoma many years after endoscopic sinonasal resection of malignancy.

CASE PRESENTATION

A 50-year-old female with a six-year history of endoscopic sinonasal resection of a poorly differentiated neuroendocrine tumor presented with two days of worsening frontal headache and left periocular swelling. A subperiosteal abscess was initially suspected on CT; however, MRI sequences revealed changes consistent with the diagnosis of hematoma. A conservative approach was justified based on the clinico-radiologic features. Progressive clinical resolution was noted over three weeks. Two monthly follow-up MRI revealed resolution of the orbital findings with no features to indicate recurrence of malignancy.

CLINICAL DISCUSSION

Subperiosteal pathologies can be clinically challenging to differentiate. Differing radiodensities on CT may help differentiate between them but is not always reliable. MRI is more sensitive and is the preferred imaging modality.

CONCLUSION

Spontaneous orbital hematomas are self-resolving, and surgical exploration may be avoided in the absence of complications. Therefore, it is beneficial to recognize it as a potential late complication of extensive endoscopic endonasal surgery. Characteristic features on MRI can aid diagnosis.

Peritumoral ADC Values Correlate with the MGMT Methylation Status in Patients with Glioblastoma

Different results have been reported concerning the relationship of the apparent diffusion coefficient (ADC) values and the status of methylation as the promoter gene for the enzyme methylguanine-DNA methyltransferase (MGMT) in patients with glioblastomas (GBs). The aim of this study was to investigate if there were correlations between the ADC values of the enhancing tumor and peritumoral areas of GBs and the MGMT methylation status. In this retrospective study, we included 42 patients with newly diagnosed unilocular GB with one MRI study prior to any treatment and histopathological data. After co-registration of ADC maps with T1-weighted sequences after contrast administration and dynamic susceptibility contrast (DSC) perfusion, we manually selected one region-of-interest (ROI) in the enhancing and perfused tumor and one ROI in the peritumoral white matter. Both ROIs were mirrored in the healthy hemisphere for normalization. In the peritumoral white matter, absolute and normalized ADC values were significantly higher in patients with MGMT-unmethylated tumors, as compared to patients with MGMT-methylated tumors (absolute values p = 0.002, normalized p = 0.0007). There were no significant differences in the enhancing tumor parts. The ADC values in the peritumoral region correlated with MGMT methylation status, confirmed by normalized ADC values. In contrast to other studies, we could not find a correlation between the ADC values or the normalized ADC values and the MGMT methylation status in the enhancing tumor parts.

Deep Constrained Spherical Deconvolution for Robust Harmonization

Diffusion weighted magnetic resonance imaging (DW-MRI) captures tissue microarchitecture at millimeter scale. With recent advantages in data sharing, large-scale multi-site DW-MRI datasets are being made available for multi-site studies. However, DW-MRI suffers from measurement variability (e.g., inter- and intra-site variability, hardware performance, and sequence design), which consequently yields inferior performance on multi-site and/or longitudinal diffusion studies. In this study, we propose a novel, deep learning-based method to harmonize DW-MRI signals for a more reproducible and robust estimation of microstructure. Our method introduces a data-driven scanner-invariant regularization scheme to model a more robust fiber orientation distribution function (FODF) estimation. We study the Human Connectome Project (HCP) young adults test-retest group as well as the MASiVar dataset (with inter- and intra-site scan/rescan data). The 8th order spherical harmonics coefficients are employed as data representation. The results show that the proposed harmonization approach maintains higher angular correlation coefficients (ACC) with the ground truth signals (0.954 versus 0.942), while achieves higher consistency of FODF signals for intra-scanner data (0.891 versus 0.826), as compared with the baseline supervised deep learning scheme. Furthermore, the proposed data-driven framework is flexible and potentially applicable to a wider range of data harmonization problems in neuroimaging.

A new perspective of molecular diffusion by nuclear magnetic resonance

The diffusion-weighted NMR signal acquired using Pulse Field Gradient (PFG) techniques, allows for extrapolating microstructural information from porous materials and biological tissues. In recent years there has been a multiplication of diffusion models expressed by parametric functions to fit the experimental data. However, clear-cut criteria for the model selection are lacking. In this paper, we develop a theoretical framework for the interpretation of NMR attenuation signals in the case of Gaussian systems with stationary increments. The full expression of the Stejskal-Tanner formula for normal diffusing systems is devised, together with its extension to the domain of anomalous diffusion. The range of applicability of the relevant parametric functions to fit the PFG data can be fully determined by means of appropriate checks to ascertain the correctness of the fit. Furthermore, the exact expression for diffusion weighted NMR signals pertaining to Brownian yet non-Gaussian processes is also derived, accompanied by the proper check to establish its contextual relevance. The analysis provided is particularly useful in the context of medical MRI and clinical practise where the hardware limitations do not allow the use of narrow pulse gradients.

Association Between Quantitative Diffusion-Weighted Magnetic Resonance Neuroimaging and Outcome After Pediatric Cardiac Arrest

BACKGROUND AND OBJECTIVES

Diffusion MRI can quantify the extent of hypoxic-ischemic brain injury after cardiac arrest. Our objective was to determine the association between the adult-derived threshold of apparent diffusion coefficient (ADC) <650 × 10-6 mm2/s in >10% of brain tissue and an unfavorable outcome after pediatric cardiac arrest. Since ADC decreases exponentially as a function of increasing age, we determined the association between (1) having >10% of brain tissue below a novel age-dependent ADC threshold, and (2) age-normalized whole-brain mean ADC and unfavorable outcome.

METHODS

This was a retrospective study of patients aged ≤18 years who had cardiac arrest and a clinically obtained brain MRI within 7 days. The primary outcome was unfavorable neurologic status at hospital discharge based on the Pediatric Cerebral Performance Category score. ADC images were extracted from 3-direction diffusion imaging. We determined whether each patient had >10% of voxels with an ADC below prespecified thresholds. We computed the whole-brain mean ADC for each patient.

RESULTS

One hundred thirty-four patients were analyzed. Patients with ADC <650 × 10-6 mm2/s in >10% of voxels had 15 times higher odds (95% CI 5-65) of an unfavorable outcome compared with patients with ADC <650 × 10-6 mm2/s (area under the receiver operating characteristic curve [AUROC] 0.72 [95% CI 0.63-0.80]). These ADC criteria had a sensitivity and specificity of 0.49 and 0.94, respectively, and positive and negative predictive values of 0.93 and 0.52, respectively, for an unfavorable outcome. The age-dependent ADC threshold that yielded optimal sensitivity and specificity for unfavorable outcomes was <300 × 10-6 mm2/s below each patient's predicted whole-brain mean ADC. The sensitivity, specificity, and positive and negative predictive values for this ADC threshold were 0.53, 0.96, 0.96, and 0.54, respectively (odds ratio [OR] 26.4 [95% CI 7.5-168.3]; AUROC 0.74 [95% CI 0.66-0.83]). Lower age-normalized whole-brain mean ADC was also associated with an unfavorable outcome (OR 0.42 [0.24-0.64], AUROC 0.76 [95% CI 0.66-0.82]).

DISCUSSION

Quantitative diffusion thresholds on MRI within 7 days after cardiac arrest were associated with an unfavorable outcome in children. The age-independent ADC threshold was highly specific for predicting an unfavorable outcome. However, the specificity and sensitivity increased when using age-dependent ADC thresholds. Age-dependent ADC thresholds may improve prognostic accuracy and require further investigation in larger cohorts.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that quantitative diffusion-weighted imaging within 7 days postarrest can predict an unfavorable clinical outcome in children.

Contribution of advanced neuro-imaging (MR diffusion, perfusion and proton spectroscopy) in differentiation between low grade gliomas GII and MR morphologically similar non neoplastic lesions

Background

Non-neoplastic brain lesions can be misdiagnosed as low-grade gliomas. Conventional magnetic resonance (MR) imaging may be non-specific. Additional imaging modalities such as spectroscopy (MRS), perfusion and diffusion imaging aid in diagnosis of such lesions. However, contradictory and overlapping results are still present. Hence, our purpose was to evaluate the role of advanced neuro-imaging in differentiation between low-grade gliomas (WHO grade II) and MR morphologically similar non-neoplastic lesions and to prove which modality has the most accurate results in differentiation.

Results

All patients were classified into two main groups: patients with low-grade glioma (n = 12; mean age, 38.8 ± 16; 8 males) and patients with non-neoplastic lesions (n = 27; mean age, 36.6 ± 15; 19 males) based on the histopathological and clinical–radiological diagnosis. Using ROC curve analysis, a threshold value of 0.93 for rCBV (AUC = 0.875, PPV = 92%, NPV = 71.4%) and a threshold value of 2.5 for Cho/NAA (AUC = 0.829, PPV = 92%, NPV = 71.4%) had 85.2% sensitivity and 83.3% specificity for predicting neoplastic lesions. The area under the curve (AUC) of ROC analysis was good for relative cerebral blood volume (rCBV) and Cho/NAA ratios (> 0.80) and fair for Cho/Cr and NAA/Cr ratios (0.70–0.80). When the rCBV measurements were combined with MRS ratios, significant improvement was observed in the area under the curve (AUC) (0.969) with improved diagnostic accuracy (89.7%) and sensitivity (88.9%).

Conclusions

Evaluation of rCBV and metabolite ratios at MRS, particularly Cho/NAA ratio, may be helpful in differentiating low-grade gliomas from non-neoplastic lesions. The combination of dynamic susceptibility contrast (DSC) perfusion and MRS can significantly improve the diagnostic accuracy and can help avoiding the need for an invasive biopsy.

Klebsiella pneumoniae sepsis complicated with central nervous system involvement: A case series

Central nervous system (CNS) infection with Klebsiella pneumoniae can be a complication of invasive liver abscess syndrome; however, CNS infections due to K. pneumoniae without liver abscesses are rare. We report three fatal cases of CNS infection due to K. pneumoniae that lacked liver abscesses during the initial investigation.

Elevation of brain ADC (apparent diffusion coefficient) in HIV-associated neurocognitive disorders and evolution after treatment: A pilot study

BACKGROUND

Thirty to 50% of HIV-infected patients develop HIV-Associated Neurocognitive Disorders (HAND) despite virological control. The previously published Neuro+3 study showed their neurocognitive status can be improved by intensifying antiviral therapy. Our study is a part of the Neuro3+ study and aims to study apparent diffusion coefficient (ADC) as a biomarker for neurological improvement.

PATIENTS AND METHODS

We prospectively included 31 patients with HAND. They received therapy with better CNS Penetration Effectiveness (CPE) score with two-year follow-up. Cognitive status was assessed at day 0 (D0) and week 96 (W96) using Frascati 3-stage classification and Global Deficit Score (GDS). Brain MRI at D0 and W96 assessed morphological data (white matter hyperintensities, opportunistic infections, ischemic lesions, atrophy) and measured whole brain apparent diffusion coefficient (ADC). We compared their data with a control group of 20 healthy patients with similar ages and sex ratio.

RESULTS

After ARV intensification, cognitive status was significantly improved: GDS (n = 1,4 vs 1,0 p = 0.01) and Frascati scale (2HAD/22MND/7ANI vs 1HAD/8MND/17ANI p = 0.001). Mean ADC was significantly higher in patients at inclusion than in controls (0.88 × 10^-3 mm²/s ± 0.06 vs 0.81 × 10^-3 mm²/s ± 0.04, p = 0.0001). ADC decreased after treatment (0.88 × 10^-3 mm²/s ± 0.06 vs 0.85 × 10^-3 mm²/s ± 0.06 (p = 0,04). In subgroup analysis, ADC significantly decreased in clinically improved patients (0.89 × 10^-3 mm²/s ± 0.07 vs 0.85 × 10^-3 mm²/s ± 0.07 (p = 0,03)) and did not significantly change in non-clinically improved patients (0.86 × 10^-3 mm²/s ± 0.07 vs 0.84 × 10^-3 mm²/s ± 0.07 (p = 0,31)). After treatment, there was no significant difference between patients and controls (0.85 × 10^-3 mm²/s ± 0.06 vs 0.81 × 10^-3 mm²/s ± 0.04, p = 0.17).

CONCLUSION

Whole-brain ADC is a good biomarker of HIV-associated neurocognitive disorders. It is significantly increased in patients with HAND compared with controls and significantly decreases after treatment. It is all the more important to have a quantitative biomarker as conventional imaging does not contribute to the diagnosis.

Comparison of TGSE-BLADE DWI, RESOLVE DWI, and SS-EPI DWI in healthy volunteers and patients after cerebral aneurysm clipping

Diffusion-weighted magnetic resonance imaging is prone to have susceptibility artifacts in an inhomogeneous magnetic field. We compared distortion and artifacts among three diffusion acquisition techniques (single-shot echo-planar imaging [SS-EPI DWI], readout-segmented EPI [RESOLVE DWI], and 2D turbo gradient- and spin-echo diffusion-weighted imaging with non-Cartesian BLADE trajectory [TGSE-BLADE DWI]) in healthy volunteers and in patients with a cerebral aneurysm clip. Seventeen healthy volunteers and 20 patients who had undergone surgical cerebral aneurysm clipping were prospectively enrolled. SS-EPI DWI, RESOLVE DWI, and TGSE-BLADE DWI of the brain were performed using 3 T scanners. Distortion was the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI near air-bone interfaces in healthy volunteers (P < 0.001). Length of clip-induced artifact and distortion near the metal clip were the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI (P < 0.01). Image quality scores for geometric distortion, susceptibility artifacts, and overall image quality in both healthy volunteers and patients were the best in TGSE-BLADE DWI, and better in RESOLVE DWI than SS-EPI DWI (P < 0.001). Among the three DWI sequences, image quality was the best in TGSE-BLADE DWI in terms of distortion and artifacts, in both healthy volunteers and patients with an aneurysm clip.

Hypothermia reduces glymphatic transportation in traumatic edematous brain assessed by intrathecal dynamic contrast-enhanced MRI

The glymphatic system has recently been shown to clear brain extracellular solutes and can be extensively impaired after traumatic brain injury (TBI). Despite hypothermia being identified as a protective method for the injured brain via minimizing the formation of edema in the animal study, little is known about how hypothermia affects the glymphatic system following TBI. We use dynamic contrast-enhanced MRI (DCE-MRI) following cisterna magna infusion with a low molecular weight contrast agent to track glymphatic transport in male Sprague-Dawley rats following TBI with hypothermia treatment and use diffusion-weighted imaging (DWI) sequence to identify edema after TBI, and further distinguish between vasogenic and cytotoxic edema. We found that hypothermia could attenuate brain edema, as demonstrated by smaller injured lesions and less vasogenic edema in most brain subregions. However, in contrast to reducing cerebral edema, hypothermia exacerbated the reduction of efficiency of glymphatic transportation after TBI. This deterioration of glymphatic drainage was present brain-wide and showed hemispherical asymmetry and regional heterogeneity across the brain, associated with vasogenic edema. Moreover, our data show that glymphatic transport reduction and vasogenic edema are closely related to reducing perivascular aquaporin-4 (AQP4) expression. The suppression of glymphatic transportation might eliminate the benefits of brain edema reduction induced by hypothermia and provide an alternative pathophysiological factor indicating injury to the brain after TBI. Thus, this study poses a novel emphasis on the potential role of hypothermia in managing severe TBI.

The utility of diffusion-weighted imaging in patients with spinal cord infarction: difference from the findings of neuromyelitis optica spectrum disorder

Background

Magnetic resonance imaging (MRI) plays a crucial role in diagnosing spinal cord infarction (SCI). However, the findings are often indistinguishable from those of other intramedullary diseases, such as neuromyelitis optica spectrum disorder (NMOSD). Although diffusion-weighted imaging (DWI) is a promising technique, the utility for discriminating SCI from NMOSD remains unclear because the DWI findings of acute NMOSD lesions have not been investigated in detail.

Methods

Clinical and MRI findings were retrospectively evaluated in 15 and 12 patients with acute SCI and NMOSD, respectively. First, clinical characteristics were compared between the SCI and NMOSD groups. Second, MRI abnormalities were examined to find differences between these groups. Third, in the SCI group, factors influencing T2 and DWI abnormalities were analyzed using the mixed-effects logistic regression analysis.

Results

The proportion of female patients was higher in the NMOSD group (92%) than in the SCI (40%). The time from symptom onset to nadir was smaller in the SCI group (median [interquartile range]; 4 [0.1–8.3] hours) than in the NMOSD (252 [162–576]). On T2-weighted images, SCI lesions had smaller length than NMOSD (2 [1–2] and 5 [2–7] vertebral segments, respectively). Focal lesions within the T9–L2 level were found only in patients with SCI. DWI hyperintensity was observed both in the SCI (frequency, 100%) and NMOSD (60%) groups. On apparent diffusion coefficient (ADC) maps, the hyperintensities of SCI had corresponding hypointensities, whereas those of NMOSD were isointense and a large portion of NMOSD lesions had hyperintense signals. Owl’s eyes sign and pencil-like hyperintensity, typically reported as T2 findings suggestive of SCI, were also found on DWI. Posterior linear hyperintensity was frequently detected on DWI in patients with posterior spinal artery infarction. The presence of MRI abnormality revealing SCI was modeled with the time from symptom onset, imaging sequence and plane, and affected vascular territory.

Conclusions

DWI and ADC maps help distinguish SCI from NMOSD. The time from symptom onset, imaging sequence, and imaging plane should be considered when MRI findings are interpreted in patients with suspected SCI.

Effects of Insular Cortex on Post-Stroke Dysphagia: A Systematic Review and Meta Analysis

Objective: To investigate the relationship of lobar and deep brain regions with post-stroke dysphagia (PSD). Method: The databases of Medline, Embase, Web of Science, and Cochrane Library were searched from the establishment to May 2022. Studies that investigated the effects of lesions in lobar and deep brain regions on swallowing function after stroke were screened. The primary outcomes were PSD-related brain regions (including aspiration-related and oral transit time-related brain regions). The secondary outcomes were the incidence rate of PSD. The brain regions with the most overlap in the included studies were considered to be most relevant to PSD, and were presented as percentages. Data were compared utilizing the t-tests for continuous variables and χ2 for frequency-based variables. Result: A total of 24 studies and 2306 patients were included. The PSD-related lobar and deep brain regions included the insular cortex, frontal lobe, temporal gyrus, basal ganglia, postcentral, precentral, precuneus, corona radiate, etc. Among these brain regions, the insular cortex was most frequently reported (taking up 54.2%) in the included studies. Furthermore, the total incidence rate of PSD was around 40.4%, and the incidence of male was nearly 2.57 times as much as that of female (χ2 = 196.17, p < 0.001). Conclusions: In lobar and deep brain regions, the insular cortex may be most relevant to PSD and aspiration, which may be a potentially promising target in the treatment of PSD.

Glioma segmentation with DWI weighted images, conventional anatomical images, and post-contrast enhancement magnetic resonance imaging images by U-Net

Glioma segmentation is believed to be one of the most important stages of treatment management. Recent developments in magnetic resonance imaging (MRI) protocols have led to a renewed interest in using automatic glioma segmentation with different MRI image weights. U-Net is a major area of interest within the field of automatic glioma segmentation. This paper examines the impact of different input MRI image-weight on the U-Net output performance for glioma segmentation. One hundred forty-nine glioma patients were scanned with a 1.5T MRI scanner. The main MRI image-weights acquired are diffusion-weighted imaging (DWI) weighted images (b50, b500, b1000, Apparent diffusion coefficient (ADC) map, Exponential apparent diffusion coefficient (eADC) map), anatomical image-weights (T₂, T₁, T₂-FLAIR), and post enhancement image-weights (T₁Gd). The U-Net and data augmentation are used to segment the glioma tumors. Having the Dice coefficient and accuracy enabled us to compare our results with the previous study. The first set of analyses examined the impact of epoch number on the accuracy of U-Net, and n_epoch = 20 was selected for U-Net training. The mean Dice coefficient for b50, b500, b1000, ADC map, eADC map, T₂, T₁, T₂-FLAIR, and T₁Gd image weights for glioma segmentation with U-Net were calculated 0.892, 0.872, 0.752, 0.931, 0.944, 0.762, 0.721, 0.896, 0.694 respectively. This study has found that, DWI image-weights have a higher diagnostic value for glioma segmentation with U-Net in comparison with anatomical image-weights and post enhancement image-weights. The results of this investigation show that ADC and eADC maps have higher performance for glioma segmentation with U-Net.

A Preliminary Study of Alterations in Iron Disposal and Neural Activity in Ischemic Stroke

Purpose

The study aimed to evaluate the postrehabilitation changes in deep gray matter (DGM) nuclei, corticospinal tract (CST), and motor cortex area, involved in motor tasks in patients with ischemic stroke.

Methods

Three patients participated in this study, who had experienced an ischemic stroke on the left side of the brain. They underwent a standard rehabilitation program for four consecutive weeks, including transcranial direct current stimulation (tDCS), neuromuscular electrical stimulation (NMES), and occupational therapy. The patients' motor ability was evaluated by Fugl-Meyer assessment-upper extremity (FMA-UE) and Wolf motor function test (WMFT). Multimodal magnetic resonance imaging (MRI) was acquired from the patients by a 3 Tesla machine before and after the rehabilitation. The magnetic susceptibility changes were examined in DGM nuclei including the bilateral caudate (CA), putamen (PT), globus pallidus (GP), and thalamus (TH) using quantitative susceptibility mapping (QSM). Functional MRI (fMRI) in the motor cortex areas was acquired to evaluate the postrehab functional motor activity. The three-dimensional corticospinal tract (CST) was reconstructed using diffusion-weighted imaging (DWI) and diffusion tensor tractography (DTT), and the fractional anisotropy (FA) was measured along the tract. Ultimately, the relationship between the structural and functional changes was evaluated in CST and motor cortex.

Results

Postrehabilitation FMA-UE and WMFT scores increased for all patients compared to the prerehabilitation. QSM analysis revealed increasing in susceptibility values in GP and CA in all patients at the ipsilesional hemisphere. By fMRI analysis, the ipsilesional hemisphere demonstrated an increase in functional activity in motor areas for all 3 patients. In the ipsilesional hemisphere, the fractional anisotropy (FA) was increased in CST in two patients, while the mean diffusivity (MD) was decreased in CA in a patient, in PT and TH in another patient, and in PT in two patients.

Conclusion

This preliminary study demonstrates that the magnetic susceptibility may decrease at some ipsilesional DGM nuclei after tDCS, NMES, and occupational therapy for patients with ischemic stroke, suggesting a drop in the level of iron deposition, which may be associated with an increase in the level of activity in motor cortex after rehabilitation.

Clinical and prognostic implications of rim restriction following glioma surgery

Rim restriction surrounding the resection cavity of glioma is often seen on immediate post-op diffusion-weighted imaging (DWI). The etiology and clinical impact of rim restriction are unknown. We evaluated the incidence, risk factors and clinical consequences of this finding. We evaluated patients that underwent surgery for low-grade glioma (LGG) and glioblastoma (GBM) without stroke on post-operative imaging. Analyses encompassed pre- and postoperative clinical, radiological, intraoperative monitoring, survival, functional and neurocognitive outcomes. Between 2013 and 2017, 63 LGG and 209 GBM patients (272 in total) underwent surgical resection and were included in our cohort. Post-op rim restriction was demonstrated in 68 patients, 32% (n = 20) of LGG and 23% (n = 48) of GBM patients. Risk factors for restriction included temporal tumors in GBM (p = 0.025) and insular tumors in LGG (p = 0.09), including longer surgery duration in LGG (p = 0.008). After a 1-year follow-up, LGG patients operated on their dominant with post-op restriction had a higher rate of speech deficits (46 vs 9%, p = 0.004). Rim restriction on postoperative imaging is associated with longer duration of glioma surgery and potentially linked to brain retraction. It apparently has no direct clinical consequences, but is linked to higher rates of speech deficits in LGG dominant-side surgeries.

The landscape of brain tumor mimics in neuro-oncology practice

BACKGROUND AND OBJECTIVE

Differentiating neoplastic and non-neoplastic brain lesions is essential to make management recommendations and convey prognosis, but the distinction between brain tumors and their mimics in practice may prove challenging. The aim of this study is to provide the incidence of brain tumor mimics in the neuro-oncology setting and describe this patient subset.

METHODS

Retrospective study of adult patients referred to the Division of Neuro-oncology for a presumed diagnosis of brain tumor from January 1, 2005 through December 31, 2017, who later satisfied the diagnosis of a non-neoplastic entity based on neuroimaging, clinical course, and/or histopathology evaluation. We classified tumor mimic entities according to clinical, radiologic, and laboratory characteristics that correlated with the diagnosis.

RESULTS

The incidence of brain tumor mimics was 3.4% (132/3897). The etiologies of the non-neoplastic entities were vascular (35%), inflammatory non-demyelinating (26%), demyelinating (15%), cysts (10%), infectious (9%), and miscellaneous (5%). In our study, 38% of patients underwent biopsy to determine diagnosis, but in 26%, the biopsy was inconclusive.

DISCUSSION

Brain tumor mimics represent a small but important subset of the neuro-oncology referrals. Vascular, inflammatory, and demyelinating etiologies represent two-thirds of cases. Recognizing the clinical, radiologic and laboratory characteristics of such entities may improve resource utilization and prevent unnecessary as well as potentially harmful diagnostic and therapeutic interventions.

The Value of First-Order Features Based on the Apparent Diffusion Coefficient Map in Evaluating the Therapeutic Effect of Low-Intensity Pulsed Ultrasound for Acute Traumatic Brain Injury With a Rat Model

Purpose

In order to evaluate the neuroprotective effect of low-intensity pulsed ultrasound (LIPUS) for acute traumatic brain injury (TBI), we studied the potential of apparent diffusion coefficient (ADC) values and ADC-derived first-order features regarding this problem.

Methods

Forty-five male Sprague Dawley rats (sham group: 15, TBI group: 15, LIPUS treated: 15) were enrolled and underwent magnetic resonance imaging. Scanning layers were acquired using a multi-shot readout segmentation of long variable echo trains (RESOLVE) to decrease distortion. The ultrasound transducer was applied to the designated region in the injured cortical areas using a conical collimator and was filled with an ultrasound coupling gel. Regions of interest were manually delineated in the center of the damaged cortex on the diffusion weighted images (b = 800 s/mm²) layer by layer for the TBI and LIPUS treated groups using the open-source software ITK-SNAP. Before analysis and modeling, the features were normalized using a z-score method, and a logistic regression model with a backward filtering method was employed to perform the modeling. The entire process was completed using the R language.

Results

During the observation time, the ADC values ipsilateral to the trauma in the TBI and LIPUS groups increased rapidly up to 24 h. After statistical analysis, the 10th percentile, 90th percentile, mean, skewness, and uniformity demonstrated a significant difference among three groups. The receiver operating characteristic curve (ROC) analysis shows that the combined LR model exhibited the highest area under the curve value (AUC: 0.96).

Conclusion

The combined LR model of first-order features based on the ADC map can acquire a higher diagnostic performance than each feature only in evaluating the neuroprotective effect of LIPUS for TBI. Models based on first-order features may have potential value in predicting the therapeutic effect of LIPUS in clinical practice in the future.

Pituitary MRI Standard and Advanced Sequences: Role in the Diagnosis and Characterization of Pituitary Adenomas

Pituitary adenomas (PAs) represent the most frequently found lesions in the sellar region; however, several other lesions may be encountered in this region, such as meningiomas, craniopharyngiomas, and aneurysms. High-quality imaging is fundamental for diagnosis, characterization, and guidance of treatment planning of PAs. Sellar magnetic resonance imaging (MRI) is considered the imaging modality of choice for the evaluation of lesions in the sella turcica. The sellar MRI standard protocol includes coronal and sagittal T1-weighted spin-echo sequencing with and without gadolinium-based contrast agent and coronal T2-weighted (T2w) fast-spin echo sequencing. A systematic MRI approach to the pituitary region generally provides information that includes the size and shape of the PA, the presence of cysts or hemorrhage within the tumor, its relationship with the optic pathways and surrounding structures, potential cavernous sinus invasion, sphenoid sinus pneumatization type, and differential diagnosis with other sellar lesions. The standard protocol is sufficient for the evaluation of most cases; however, some advanced techniques (susceptibility imaging, diffusion-weighted imaging, 3D T2w high-resolution sequences, magnetic resonance elastography, perfusion-weighted imaging) may render additional information, which may be important for some cases. In this "approach to the patient" manuscript, we will discuss the use of standard and advanced MRI sequences in the diagnosis and characterization of PAs, including MRI features associated with treatment response that may aid in presurgical evaluation and planning, and red flags that may point to an alternative diagnosis.

Dermoid Cysts of the Asterion: An Unusual Location for Unusual Dermoids, Radiological Findings and Neurosurgical Implications

Asterion is an uncommon site for lesions, especially dermoid cysts. We report a case series of three asterional intracranial dermoid cysts, which, to the best of our knowledge, have never been described before. Patients presented with non-specific symptoms and underwent surgical excision of the lesions. It is crucial to correctly diagnose intracranial masses and to identify their relationships with surrounding anatomical structures, especially if the location is unusual as the asterion, to plan surgery. The challenge of this tumor location is to preserve the venous drainage system during surgical procedures, because of the contiguity between the asterion and the transverse–sigmoid junction. Rupturing or damaging of the venous drainage system have been proven to be catastrophic because they lengthen surgical time and present dire consequences for patients. In conclusion, it is crucial to familiarize with atypical dermoid presentation to ensure proper diagnoses and to perform adequate imaging for optimal surgical planning.

Tumor Connectomics: Mapping the Intra-Tumoral Complex Interaction Network Using Machine Learning

The high-level relationships that form complex networks within tumors and between surrounding tissue is challenging and not fully understood. To better understand these tumoral networks, we developed a tumor connectomics framework (TCF) based on graph theory with machine learning to model the complex interactions within and around the tumor microenvironment that are detectable on imaging. The TCF characterization model was tested with independent datasets of breast, brain, and prostate lesions with corresponding validation datasets in breast and brain cancer. The TCF network connections were modeled using graph metrics of centrality, average path length (APL), and clustering from multiparametric MRI with IsoSVM. The Matthews Correlation Coefficient (MCC), Area Under the Curve-ROC, and Precision-Recall (AUC-ROC and AUC-PR) were used for statistical analysis. The TCF classified the breast and brain tumor cohorts with an IsoSVM AUC-PR and MCC of 0.86, 0.63 and 0.85, 0.65, respectively. The TCF benign breast lesions had a significantly higher clustering coefficient and degree centrality than malignant TCFs. Grade 2 brain tumors demonstrated higher connectivity compared to Grade 4 tumors with increased degree centrality and clustering coefficients. Gleason 7 prostate lesions had increased betweenness centrality and APL compared to Gleason 6 lesions with AUC-PR and MCC ranging from 0.90 to 0.99 and 0.73 to 0.87, respectively. These TCF findings were similar in the validation breast and brain datasets. In conclusion, we present a new method for tumor characterization and visualization that results in a better understanding of the global and regional connections within the lesion and surrounding tissue.

Beyond Diffusion Tensor MRI Methods for Improved Characterization of the Brain after Ischemic Stroke: A Review

Ischemic stroke is a worldwide problem, with 15 million people experiencing a stroke annually. MR imaging is a valuable tool for understanding and assessing brain changes after stroke and predicting recovery. Of particular interest is the use of diffusion MR imaging in the nonacute stage 1-30 days poststroke. Thousands of articles have been published on the use of diffusion MR imaging in stroke, including several recent articles reviewing the use of DTI for stroke. The goal of this work was to survey and put into context the recent use of diffusion MR imaging methods beyond DTI, including diffusional kurtosis, generalized fractional anisotropy, spherical harmonics methods, and neurite orientation and dispersion models, in patients poststroke. Early studies report that these types of beyond-DTI methods outperform DTI metrics either in being more sensitive to poststroke changes or by better predicting outcome motor scores. More and larger studies are needed to confirm the improved prediction of stroke recovery with the beyond-DTI methods.