Automated segmentation of epilepsy surgical resection cavities: Comparison of four methods to manual segmentation.

Accurate resection cavity segmentation on MRI is important for neuroimaging research involving epilepsy surgical outcomes. Manual segmentation, the gold standard, is highly labour intensive. Automated pipelines are an efficient potential solution; however, most have been developed for use following temporal epilepsy surgery. Our aim was to compare the accuracy of four automated segmentation pipelines following surgical resection in a mixed cohort of subjects following temporal or extra temporal epilepsy surgery. We identified 4 open-source automated segmentation pipelines. Epic-CHOP and ResectVol utilise SPM-12 within MATLAB, while Resseg and Deep Resection utilise 3D U-net convolutional neural networks. We manually segmented the resection cavity of 50 consecutive subjects who underwent epilepsy surgery (30 temporal, 20 extratemporal). We calculated Dice similarity coefficient (DSC) for each algorithm compared to the manual segmentation. No algorithm identified all resection cavities. ResectVol (n = 44, 88 %) and Epic-CHOP (n = 42, 84 %) were able to detect more resection cavities than Resseg (n = 22, 44 %, P < 0.001) and Deep Resection (n = 23, 46 %, P < 0.001). The SPM-based pipelines (Epic-CHOP and ResectVol) performed better than the deep learning-based pipelines in the overall and extratemporal surgery cohorts. In the temporal cohort, the SPM-based pipelines had higher detection rates, however there was no difference in the accuracy between methods. These pipelines could be applied to machine learning studies of outcome prediction to improve efficiency in pre-processing data, however human quality control is still required.

Association of Localizing 18F-FDG-PET Hypometabolism and Outcome Following Epilepsy Surgery: Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Although commonly used in the evaluation of patients for epilepsy surgery, the association between the detection of localizing 18fluorine fluorodeoxyglucose PET (18F-FDG-PET) hypometabolism and epilepsy surgery outcome is uncertain. We conducted a systematic review and meta-analysis to determine whether localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery. METHODS: A systematic literature search was undertaken. Eligible publications included evaluation with 18F-FDG-PET before epilepsy surgery, with ≥10 participants, and those that reported surgical outcome at ≥12 months. Random-effects meta-analysis was used to calculate the odds of achieving a favorable outcome, defined as Engel class I, International League Against Epilepsy class 1-2, or seizure-free, with localizing 18F-FDG-PET hypometabolism, defined as concordant with the epilepsy surgery resection zone. Meta-regression was used to characterize sources of heterogeneity. RESULTS: The database search identified 8,916 studies, of which 98 were included (total patients n = 4,104). Localizing 18F-FDG-PET hypometabolism was associated with favorable outcome after epilepsy surgery for all patients with odds ratio (OR) 2.68 (95% CI 2.08-3.45). Subgroup analysis yielded similar findings for those with (OR 2.64, 95% CI 1.54-4.52) and without epileptogenic lesion detected on MRI (OR 2.49, 95% CI 1.80-3.44). Concordance with EEG (OR 2.34, 95% CI 1.43-3.83), MRI (OR 1.69, 95% CI 1.19-2.40), and triple concordance with both (OR 2.20, 95% CI 1.32-3.64) was associated with higher odds of favorable outcome. By contrast, diffuse 18F-FDG-PET hypometabolism was associated with worse outcomes compared with focal hypometabolism (OR 0.34, 95% CI 0.22-0.54). DISCUSSION: Localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery, irrespective of the presence of an epileptogenic lesion on MRI. The extent of 18F-FDG-PET hypometabolism provides additional information, with diffuse hypometabolism associated with worse surgical outcome than focal 18F-FDG-PET hypometabolism. These findings support the incorporation of 18F-FDG-PET into routine noninvasive investigations for patients being evaluated for epilepsy surgery to improve epileptogenic zone localization and to aid patient selection for surgery.

Role of the glymphatic system and perivascular spaces as a potential biomarker for post-stroke epilepsy.

Stroke is one of the most common causes of acquired epilepsy, which can also result in disability and increased mortality rates particularly in elderly patients. No preventive treatment for post-stroke epilepsy is currently available. Development of such treatments has been greatly limited by the lack of biomarkers to reliably identify high-risk patients. The glymphatic system, including perivascular spaces (PVS), is the brain's waste clearance system, and enlargement or asymmetry of PVS (ePVS) is hypothesized to play a significant role in the pathogenesis of several neurological conditions. In this article, we discuss potential mechanisms for the role of perivascular spaces in the development of post-stroke epilepsy. Using advanced MR-imaging techniques, it has been shown that there is asymmetry and impairment of glymphatic function in the setting of ischemic stroke. Furthermore, studies have described a dysfunction of PVS in patients with different focal and generalized epilepsy syndromes. It is thought that inflammatory processes involving PVS and the blood-brain barrier, impairment of waste clearance, and sustained hypertension affecting the glymphatic system during a seizure may play a crucial role in epileptogenesis post-stroke. We hypothesize that impairment of the glymphatic system and asymmetry and dynamics of ePVS in the course of a stroke contribute to the development of PSE. Automated ePVS detection in stroke patients might thus assist in the identification of high-risk patients for post-stroke epilepsy trials. PLAIN LANGUAGE SUMMARY: Stroke often leads to epilepsy and is one of the main causes of epilepsy in elderly patients, with no preventative treatment available. The brain's waste removal system, called the glymphatic system which consists of perivascular spaces, may be involved. Enlargement or asymmetry of perivascular spaces could play a role in this and can be visualised with advanced brain imaging after a stroke. Detecting enlarged perivascular spaces in stroke patients could help identify those at risk for post-stroke epilepsy.

The Australian Traumatic Brain Injury Initiative: Systematic Review of Predictive Value of Biological Markers for People With Moderate-Severe Traumatic Brain Injury.

The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to co-design a data resource to predict outcomes for people with moderate-severe traumatic brain injury (TBI) across Australia. Fundamental to this resource is the data dictionary, which is an ontology of data items. Here, we report the systematic review and consensus process for inclusion of biological markers in the data dictionary. Standardized database searches were implemented from inception through April 2022. English-language studies evaluating association between a fluid, tissue, or imaging marker and any clinical outcome in at least 10 patients with moderate-severe TBI were included. Records were screened using a prioritization algorithm and saturation threshold in Research Screener. Full-length records were then screened in Covidence. A pre-defined algorithm was used to assign a judgement of predictive value to each observed association, and high-value predictors were discussed in a consensus process. Searches retrieved 106,593 records; 1,417 full-length records were screened, resulting in 546 included records. Two hundred thirty-nine individual markers were extracted, evaluated against 101 outcomes. Forty-one markers were judged to be high-value predictors of 15 outcomes. Fluid markers retained following the consensus process included ubiquitin C-terminal hydrolase L1 (UCH-L1), S100, and glial fibrillary acidic protein (GFAP). Imaging markers included computed tomography (CT) scores (e.g., Marshall scores), pathological observations (e.g., hemorrhage, midline shift), and magnetic resonance imaging (MRI) classification (e.g., diffuse axonal injury). Clinical context and time of sampling of potential predictive indicators are important considerations for utility. This systematic review and consensus process has identified fluid and imaging biomarkers with high predictive value of clinical and long-term outcomes following moderate-severe TBI.

Improving portable low-field MRI image quality through image-to-image translation using paired low- and high-field images.

Low-field portable magnetic resonance imaging (MRI) scanners are more accessible, cost-effective, sustainable with lower carbon emissions than superconducting high-field MRI scanners. However, the images produced have relatively poor image quality, lower signal-to-noise ratio, and limited spatial resolution. This study develops and investigates an image-to-image translation deep learning model, LoHiResGAN, to enhance the quality of low-field (64mT) MRI scans and generate synthetic high-field (3T) MRI scans. We employed a paired dataset comprising T1- and T2-weighted MRI sequences from the 64mT and 3T and compared the performance of the LoHiResGAN model with other state-of-the-art models, including GANs, CycleGAN, U-Net, and cGAN. Our proposed method demonstrates superior performance in terms of image quality metrics, such as normalized root-mean-squared error, structural similarity index measure, peak signal-to-noise ratio, and perception-based image quality evaluator. Additionally, we evaluated the accuracy of brain morphometry measurements for 33 brain regions across the original 3T, 64mT, and synthetic 3T images. The results indicate that the synthetic 3T images created using our proposed LoHiResGAN model significantly improve the image quality of low-field MRI data compared to other methods (GANs, CycleGAN, U-Net, cGAN) and provide more consistent brain morphometry measurements across various brain regions in reference to 3T. Synthetic images generated by our method demonstrated high quality both quantitatively and qualitatively. However, additional research, involving diverse datasets and clinical validation, is necessary to fully understand its applicability for clinical diagnostics, especially in settings where high-field MRI scanners are less accessible.

Imaging the neurovascular unit in health and neurodegeneration: a scoping review of interdependencies between MRI measures.

The neurovascular unit (NVU) is a complex structure that facilitates nutrient delivery and metabolic waste clearance, forms the blood-brain barrier (BBB), and supports fluid homeostasis in the brain. The integrity of NVU subcomponents can be measured in vivo using magnetic resonance imaging (MRI), including quantification of enlarged perivascular spaces (ePVS), BBB permeability, cerebral perfusion and extracellular free water. The breakdown of NVU subparts is individually associated with aging, pathology, and cognition. However, how these subcomponents interact as a system, and how interdependencies are impacted by pathology remains unclear. This systematic scoping review identified 26 studies that investigated the inter-relationships between multiple subcomponents of the NVU in nonclinical and neurodegenerative populations using MRI. A further 112 studies investigated associations between the NVU and white matter hyperintensities (WMH). We identify two putative clusters of NVU interdependencies: a 'vascular' cluster comprising BBB permeability, perfusion and basal ganglia ePVS; and a 'fluid' cluster comprising ePVS, free water and WMH. Emerging evidence suggests that subcomponent coupling within these clusters may be differentially related to aging, neurovascular injury or neurodegenerative pathology.

STAREE-Mind Imaging Study: a randomised placebo-controlled trial of atorvastatin for prevention of cerebrovascular decline and neurodegeneration in older individuals.

Introduction: Cerebrovascular disease and neurodegeneration are causes of cognitive decline and dementia, for which primary prevention options are currently lacking. Statins are well-tolerated and widely available medications that potentially have neuroprotective effects. The STAREE-Mind Imaging Study is a randomised, double-blind, placebo-controlled clinical trial that will investigate the impact of atorvastatin on markers of neurovascular health and brain atrophy in a healthy, older population using MRI. This is a nested substudy of the 'Statins for Reducing Events in the Elderly' (STAREE) primary prevention trial. Methods: Participants aged 70 years or older (n=340) will be randomised to atorvastatin or placebo. Comprehensive brain MRI assessment will be undertaken at baseline and up to 4 years follow-up, including structural, diffusion, perfusion and susceptibility imaging. The primary outcome measures will be change in brain free water fraction (a composite marker of vascular leakage, neuroinflammation and neurodegeneration) and white matter hyperintensity volume (small vessel disease). Secondary outcomes will include change in perivascular space volume (glymphatic drainage), cortical thickness, hippocampal volume, microbleeds and lacunae, prefrontal cerebral perfusion and white matter microstructure. Ethics and dissemination: Academic publications from this work will address the current uncertainty regarding the impact of statins on brain structure and vascular integrity. This study will inform the utility of repurposing these well-tolerated, inexpensive and widely available drugs for primary prevention of neurological outcomes in older individuals. Ethics approval was given by Monash University Human Research Ethics Committee, Protocol 12206. Trial registration number: ClinicalTrials.gov Identifier: NCT05586750.

Utility of Acute and Subacute Blood Biomarkers to Assist Diagnosis in CT-Negative Isolated Mild Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: Blood biomarkers glial fibrillary acidic protein (GFAP) and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) have recently been Food and Drug Administration approved as predictors of intracranial lesions on CT after mild traumatic brain injury (mTBI). However, most cases with mTBI are CT negative, and no biomarkers are approved to assist diagnosis in these individuals. In this study, we aimed to determine the optimal combination of blood biomarkers to assist mTBI diagnosis in otherwise healthy adults younger than 50 years presenting to an emergency department within 6 hours of injury. To further understand the utility of biomarkers, we assessed how biological sex, presence or absence of loss of consciousness and/or post-traumatic amnesia (LOC/PTA), and delayed presentation affected classification performance. METHODS: Blood samples, symptom questionnaires, and cognitive tests were prospectively conducted for participants with mTBI recruited from The Alfred Hospital Level 1 Emergency & Trauma Center and uninjured controls. Follow-up testing was conducted at 7 days. Simoa quantified plasma GFAP, UCH-L1, tau, neurofilament light chain (NfL), interleukin (IL)-6, and IL-1ß. Area under the receiver operating characteristic (AUC) analysis assessed classification accuracy for diagnosed mTBI, and logistic regression models identified optimal biomarker combinations. RESULTS: Plasma IL-6 (AUC 0.91, 95% CI 0.86-0.96), GFAP (AUC 0.85, 95% CI 0.78-0.93), and UCH-L1 (AUC 0.79, 95% CI 0.70-0.88) best differentiated mTBI (n = 74) from controls (n = 44) acutely (<6 hours), with NfL (AUC 0.81, 95% CI 0.72-0.90) the only marker to have such utility subacutely (7 days). Biomarker performance was similar between sexes and for participants with and without LOC/PTA, with the exception at 7 days, where GFAP and IL-6 retained some utility in female participants (GFAP: AUC 0.71, 95% CI 0.55-0.88; IL-6: AUC 0.71, 95% CI 0.55-0.87) and in those with LOC/PTA (GFAP: AUC 0.73, 95% CI 0.59-0.86; IL-6: AUC 0.71, 95% CI 0.57-0.84). Acute IL-6 (R 2 = 0.50, 95% CI 0.34-0.64) outperformed GFAP and UCH-L1 combined (R 2 = 0.35, 95% CI 0.17-0.50), with the best acute model featuring GFAP and IL-6 (R 2 = 0.54, 95% CI 0.34-0.68). DISCUSSION: These findings indicate that adding IL-6 to a panel of brain-specific proteins such as GFAP and UCH-L1 might assist in the acute diagnosis of mTBI in adults younger than 50 years. Multiple markers had high classification accuracy in participants without LOC/PTA. When compared with the best-performing acute markers, subacute measures of plasma NfL resulted in minimal reduction in classification accuracy. Future studies will investigate the optimal time frame over which plasma IL-6 might assist diagnostic decisions and how extracranial trauma affects utility.

Reduced total number of enlarged perivascular spaces in post-traumatic epilepsy patients with unilateral lesions - a feasibility study.

BACKGROUND: We investigated the value of automated enlarged perivascular spaces (ePVS) quantification to distinguish chronic traumatic brain injury (TBI) patients with post-traumatic epilepsy (PTE+) from chronic TBI patients without PTE (PTE-) in a feasibility study. METHODS: Patients with and without PTE were recruited and underwent an MRI post-TBI. Multimodal auto identification of ePVS algorithm was applied to T1-weighted MRIs to segment ePVS. The total number of ePVS was calculated and corrected for white matter volume, and an asymmetry index (AI) derived. RESULTS: PTE was diagnosed in 7 out of the 99 participants (male=69) after a median time of less than one year since injury (range 10-22). Brain lesions were observed in all 7 PTE+ cases (unilateral=4, 57%; bilateral=3, 43%) as compared to 40 PTE- cases (total 44%; unilateral=17, 42%; bilateral=23, 58%). There was a significant difference between PTE+ (M=1.21e-4, IQR [8.89e-5]) and PTE- cases (M=2.79e-4, IQR [6.25e-5]) in total corrected numbers of ePVS in patients with unilateral lesions (p=0.024). No differences in AI, trauma severity and lesion volume were seen between groups. CONCLUSION: This study has shown that automated quantification of ePVS is feasible and provided initial evidence that individuals with PTE with unilateral lesions may have fewer ePVS compared to TBI patients without epilepsy. Further studies with larger sample sizes should be conducted to determine the value of ePVS quantification as a PTE-biomarker.

The RSNA Cervical Spine Fracture CT Dataset.

This dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/.

Quantitative analysis of MR T2 relaxation times in neck muscles.

T2 relaxation times (T2 times) are different between resting and exercised muscles and between muscles of healthy subjects and subjects with muscle pathology. However, studies specifically focusing on neck muscles are lacking. Furthermore, normative neck muscle T2 times are not well defined and methodology used to analyse T2 times in neck muscles is not robust. We analysed T2 times in key neck muscles and explored factors affecting variability between muscles. 20 healthy subjects were recruited. Two circular regions of interest (ROIs) were drawn in two mutually exclusive regions within neck muscles on T2 weighted images and values averaged. ROI measurements were performed by a co-investigator, supervised by a neuro-radiologist. For the first ten subjects, measurements were done from C1-T1. For the remaining subjects, ROIs were drawn at two pre-determined levels. Two MRIs were repeated at 31 degrees acquisition to evaluate the effect of muscle fibre orientation. ROI values were translated into T2 times. Results showed semispinalis capitis had the longest T2 times (range 46.88-51.42 ms), followed by splenius capitis (range 47.37-48.33 ms), trapezius (range 45.27-47.46 ms), levator scapulae (range 43.17-45.63 ms) and sternocleidomastoid (range 38.45-42.91 ms). T2 times did not vary along length of muscles and were unaffected by muscle fibre orientation (P > 0.05). T2 times of splenius capitis correlated significantly with age at C2/C3 and C5/C6 levels and trapezius at C7/T1 level. Gender did not influence relaxation times (P > 0.05). In conclusion, results of normative neck muscle T2 time values and factors influencing the T2 times could serve as a reference for future MR analysis of neck muscles. The methodology used may also be useful for related studies of neck muscles.

Associations of Enlarged Perivascular Spaces With Brain Lesions, Brain Age, and Clinical Outcomes in Chronic Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: Enlarged perivascular spaces (ePVS) have been identified as a key signature of glymphatic system dysfunction in neurologic conditions. The incidence and clinical implications of ePVS after traumatic brain injury (TBI) are not yet understood. We investigated whether individuals with chronic moderate-to-severe TBI had an increased burden of ePVS and whether ePVS burden is modulated by the presence of focal lesions, older brain age, and poorer sleep quality. We examined whether an increased burden of ePVS was associated with poorer cognitive and emotional outcomes. METHODS: Using a cross-sectional design, participants with a single moderate-to-severe chronic TBI (sustained ≥10 years ago) were recruited from an inpatient rehabilitation program. Control participants were recruited from the community. Participants underwent 3T brain MRI, neuropsychological assessment, and clinical evaluations. ePVS burden in white matter was quantified using automated segmentation. The relationship between the number of ePVS, group membership, focal lesions, brain age, current sleep quality, and outcome was modeled using negative binomial and linear regressions. RESULTS: This study included 100 participants with TBI (70% male; mean age = 56.8 years) and 75 control participants (54.3% male; mean age = 59.8 years). The TBI group had a significantly greater burden of ePVS (prevalence ratio rate [PRR] = 1.29, p = 0.013, 95% CI 1.05-1.57). The presence of bilateral lesions was associated with greater ePVS burden (PRR = 1.41, p = 0.021, 95% CI 1.05-1.90). There was no association between ePVS burden, sleep quality (PRR = 1.01, p = 0.491, 95% CI 0.98-1.048), and sleep duration (PRR = 1.03, p = 0.556, 95% CI 0.92-1.16). ePVS was associated with verbal memory (ß = -0.42, p = 0.006, 95% CI -0.72 to -0.12), but not with other cognitive domains. The burden of ePVS was not associated with emotional distress (ß = -0.70, p = 0.461, 95% CI -2.57 to 1.17) or brain age (PRR = 1.00, p = 0.665, 95% CI 0.99-1.02). DISCUSSION: TBI is associated with a greater burden of ePVS, especially when there have been bilateral brain lesions. ePVS was associated with reduced verbal memory performance. ePVS may indicate ongoing impairments in glymphatic system function in the chronic postinjury period.

Automated Methods for Detecting and Quantitation of Enlarged Perivascular spaces on MRI.

The brain's glymphatic system is a network of intracerebral vessels that function to remove "waste products" such as degraded proteins from the brain. It comprises of the vasculature, perivascular spaces (PVS), and astrocytes. Poor glymphatic function has been implicated in numerous diseases; however, its contribution is still unknown. Efforts have been made to image the glymphatic system to further assess its role in the pathogenesis of different diseases. Numerous imaging modalities have been utilized including two-photon microscopy and contrast-enhanced magnetic resonance imaging (MRI). However, these are associated with limitations for clinical use. PVS form a part of the glymphatic system and can be visualized on standard MRI sequences when enlarged. It is thought that PVS become enlarged secondary to poor glymphatic drainage of metabolites. Thus, quantitating PVS could be a good surrogate marker for glymphatic function. Numerous manual rating scales have been developed to measure the PVS number and size on MRI scans; however, these are associated with many limitations. Instead, automated methods have been created to measure PVS more accurately in different diseases. In this review, we discuss the imaging techniques currently available to visualize the glymphatic system as well as the automated methods currently available to measure PVS, and the strengths and limitations associated with each technique. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Perivascular spaces as a marker of disease severity and neurodegeneration in patients with behavioral variant frontotemporal dementia.

Background: Behavioural Variant Frontotemporal Dementia (bvFTD) is a rapidly progressing neurodegenerative proteinopathy. Perivascular spaces (PVS) form a part of the brain's glymphatic clearance system. When enlarged due to poor glymphatic clearance of toxic proteins, PVS become larger and more conspicuous on MRI. Therefore, enlarged PVS may be a useful biomarker of disease severity and progression in neurodegenerative proteinopathies such as bvFTD. This study aimed to determine the utility of PVS as a biomarker of disease progression in patients with bvFTD. Materials and methods: Serial baseline and week 52 MRIs acquired from ten patients with bvFTD prospectively recruited and followed in a Phase 1b open label trial of sodium selenate for bvFTD were used in this study. An automated algorithm quantified PVS on MRI, which was visually inspected and validated by a member of the study team. The number and volume of PVS were extracted and mixed models used to assess the relationship between PVS burden and other measures of disease (cognition, carer burden scale, protein biomarkers). Additional exploratory analysis investigated PVS burden in patients who appeared to not progress over the 12 months of selenate treatment (i.e., "non-progressors"). Results: Overall, PVS cluster number (ß = -3.27, CI [-7.80 - 1.27], p = 0.267) and PVS volume (ß = -36.8, CI [-84.9 - 11.3], p = 0.171) did not change over the paired MRI scans 12 months apart. There was association between cognition total composite scores and the PVS burden (PVS cluster ß = -0.802e-3, CI [9.45e - 3 - -6.60e - 3, p ≤ 0.001; PVS volume ß = -1.30e - 3, CI [-1.55e - 3 - -1.05e - 3], p ≤ 0.001), as well as between the change in the cognition total composite score and the change in PVS volume (ß = 4.36e - 3, CI [1.33e - 3 - 7.40e - 3], p = 0.046) over the trial period. There was a significant association between CSF t-tau and the number of PVS clusters (ß = 2.845, CI [0.630 - 5.06], p = 0.036). Additionally, there was a significant relationship between the change in CSF t-tau and the change in the number of PVS (ß = 1.54, CI [0.918 - 2.16], p < 0.001) and PVS volume (ß = 13.8, CI [6.37 - 21.1], p = 0.003) over the trial period. An association was found between the change in NfL and the change in PVS volume (ß = 1.40, CI [0.272 - 2.52], p = 0.045) over time. Within the "non-progressor" group (n = 7), there was a significant relationship between the change in the CSF total-tau (t-tau) levels and the change in the PVS burden (PVS cluster (ß = 1.46, CI [0.577 - 2.34], p = 0.014; PVS volume ß = 14.6, CI [3.86 - 25.4], p = 0.032) over the trial period. Additionally, there was evidence of a significant relationship between the change in NfL levels and the change in the PVS burden over time (PVS cluster ß = 0.296, CI [0.229 - 0.361], p ≤ 0.001; PVS volume ß = 3.67, CI [2.42 - 4.92], p = 0.002). Conclusion: Analysis of serial MRI scans 12 months apart in patients with bvFTD demonstrated a relationship between PVS burden and disease severity as measured by the total cognitive composite score and CSF t-tau. Further studies are needed to confirm PVS as a robust marker of neurodegeneration in proteinopathies.

Perivascular spaces as a potential biomarker of Alzheimer's disease.

Alzheimer's disease (AD) is a highly damaging disease that affects one's cognition and memory and presents an increasing societal and economic burden globally. Considerable research has gone into understanding AD; however, there is still a lack of effective biomarkers that aid in early diagnosis and intervention. The recent discovery of the glymphatic system and associated Perivascular Spaces (PVS) has led to the theory that enlarged PVS (ePVS) may be an indicator of AD progression and act as an early diagnostic marker. Visible on Magnetic Resonance Imaging (MRI), PVS appear to enlarge when known biomarkers of AD, amyloid-ß and tau, accumulate. The central goal of ePVS and AD research is to determine when ePVS occurs in AD progression and if ePVS are causal or epiphenomena. Furthermore, if ePVS are indeed causative, interventions promoting glymphatic clearance are an attractive target for research. However, it is necessary first to ascertain where on the pathological progression of AD ePVS occurs. This review aims to examine the knowledge gap that exists in understanding the contribution of ePVS to AD. It is essential to understand whether ePVS in the brain correlate with increased regional tau distribution and global or regional Amyloid-ß distribution and to determine if these spaces increase proportionally over time as individuals experience neurodegeneration. This review demonstrates that ePVS are associated with reduced glymphatic clearance and that this reduced clearance is associated with an increase in amyloid-ß. However, it is not yet understood if ePVS are the outcome or driver of protein accumulation. Further, it is not yet clear if ePVS volume and number change longitudinally. Ultimately, it is vital to determine early diagnostic criteria and early interventions for AD to ease the burden it presents to the world; ePVS may be able to fulfill this role and therefore merit further research.

Retrospective analysis and prospective validation of an AI-based software for intracranial haemorrhage detection at a high-volume trauma centre.

Rapid detection of intracranial haemorrhage (ICH) is crucial for assessing patients with neurological symptoms. Prioritising these urgent scans for reporting presents a challenge for radiologists. Artificial intelligence (AI) offers a solution to enable radiologists to triage urgent scans and reduce reporting errors. This study aims to evaluate the accuracy of an ICH-detection AI software and whether it benefits a high-volume trauma centre in terms of triage and reducing diagnostic errors. A peer review of head CT scans performed prior to the implementation of the AI was conducted to identify the department's current miss-rate. Once implemented, the AI software was validated using CT scans performed over one month, and was reviewed by a neuroradiologist. The turn-around-time was calculated as the time taken from scan completion to report finalisation. 2916 head CT scans and reports were reviewed as part of the audit. The AI software flagged 20 cases that were negative-by-report. Two of these were true-misses that had no follow-up imaging. Both patients were followed up and exhibited no long-term neurological sequelae. For ICH-positive scans, there was an increase in TAT in the total sample (35.6%), and a statistically insignificant decrease in TAT in the emergency (- 5.1%) and outpatient (- 14.2%) cohorts. The AI software was tested on a sample of real-world data from a high-volume Australian centre. The diagnostic accuracy was comparable to that reported in literature. The study demonstrated the institution's low miss-rate and short reporting time, therefore any improvements from the use of AI would be marginal and challenging to measure.

18F-FDG-PET hypometabolism as a predictor of favourable outcome in epilepsy surgery: protocol for a systematic review and meta-analysis.

INTRODUCTION: A substantial proportion of patients who undergo surgery for drug resistant focal epilepsy do not become seizure free. While some factors, such as the detection of hippocampal sclerosis or a resectable lesion on MRI and electroencephalogram-MRI concordance, can predict favourable outcomes in epilepsy surgery, the prognostic value of the detection of focal hypometabolism with 18F-fluorodeoxyglucose positive emission tomography (18F-FDG-PET) hypometabolism is uncertain. We propose a protocol for a systematic review and meta-analysis to examine whether localisation with 18F-FDG-PET hypometabolism predicts favourable outcomes in epilepsy surgery. METHODS AND ANALYSIS: A systematic literature search of Medline, Embase and Web of Science will be undertaken. Publications which include evaluation with 18F-FDG-PET prior to surgery for drug resistant focal epilepsy, and which report ≥12 months of postoperative surgical outcome data will be included. Non-human, non-English language publications, publications with fewer than 10 participants and unpublished data will be excluded. Screening and full-text review of publications for inclusion will be undertaken by two independent investigators, with discrepancies resolved by consensus or a third investigator. Data will be extracted and pooled using random effects meta-analysis, with heterogeneity quantified using the I2 analysis. ETHICS AND DISSEMINATION: Ethics approval is not required. Once complete, the systematic review will be published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42022324823.

Gradient Patterns of Age-Related Diffusivity Changes in Cerebral White Matter.

The current concept of brain aging proposes three gradient patterns of changes in white matter that occur during healthy brain aging: antero-posterior, supero-inferior, and the myelodegeneration-retrogenesis (or the "last-in-first-out") concept. The aim of this study was to correlate white matter diffusivity measures (fractional anisotropy-FA, mean diffusivity-MD, radial diffusivity-RD, and axial diffusivity-AD) in healthy volunteers with chronological age and education level, in order to potentially incorporate the findings with proposed patterns of physiological brain aging. The study was performed on 75 healthy participants of both sexes, with an average age of 37.32 ± 11.91 years underwent brain magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI). DTI was performed using tract-based spatial statistics (TBSS), with the analysis of four parameters: FA, MD, RD, and AD. Skeletonized measures were averaged in 29 regions of interest in white matter. Correlations between age and DTI measures and between education-level and DTI measures were performed using Pearson's correlation test. To correct for multiple comparisons, we applied a Bonferroni correction to the p-values. Significance was set at p ≤ 0.001. A significant negative correlation of FA with age was observed in posterior thalamic radiation (PTR) (p< 0.001). A significant positive correlation between age and MD was observed in sagittal stratum (SS) (p< 0.001), between age and RD in PTR, SS, and retrolenticular internal capsule (p< 0.001), and between age and AD in the body of the corpus callosum (p< 0.001). There were no significant correlations of DTI parameters with educational level. According to our study, RD showed the richest correlations with age, out of all DTI metrics. FA, MD, and RD showed significant changes in the diffusivity of projection fibers, while AD presented diffusivity changes in the commissural fibers. The observed heterogeneity in diffusivity changes across the brain cannot be explained by a single aging gradient pattern, since it seems that different patterns of degradation are true for different fiber tracts that no currently available theory can globally explain age-related changes in the brain. Additional factors, such as the effect of somatosensory decline, should be included as one of the important covariables to the existing patterns.

Longitudinal tracking of axonal loss using diffusion magnetic resonance imaging in multiple sclerosis.

Axonal loss in the CNS is a key driver of progressive neurological impairments in people with multiple sclerosis. Currently, there are no established methods for tracking axonal loss clinically. This study aimed to determine the sensitivity of longitudinal diffusion MRI-derived fibre-specific measures of axonal loss in people with multiple sclerosis. Fibre measures were derived from diffusion MRI acquired as part of a standard radiological MRI protocol and were compared (i) to establish measures of neuro-axonal degeneration: brain parenchymal fraction and retinal nerve fibre layer thickness and (ii) between different disease stages: clinically isolated syndrome and early/late relapsing-remitting multiple sclerosis. Retrospectively identified data from 59 people with multiple sclerosis (18 clinically isolated syndrome, 22 early and 19 late relapsing-remitting) who underwent diffusion MRI as part of their routine clinical monitoring were collated and analysed. Twenty-six patients had 1-year and 14 patients had a 2-year follow-up. Brain parenchymal fraction was calculated from 3D MRI scans, and fibre-specific measures were calculated from diffusion MRI using multi-tissue constrained spherical deconvolution. At each study visit, patients underwent optical coherence tomography to determine retinal nerve fibre layer thickness, and standard neurological assessment expanded the disability status scale. We found a significant annual fibre-specific neuro-axonal degeneration (mean ± SD = -3.49 ± 3.32%, P < 0.001) that was ∼7 times larger than the annual change of brain parenchymal fraction (-0.53 ± 0.95%, P < 0.001), and more than four times larger than annual retinal nerve fibre layer thinning (-0.75 ± 2.50% P = 0.036). Only fibre-specific measures showed a significant difference in annual degeneration between the disease stages (P = 0.029). Reduced brain parenchymal fraction, retinal nerve fibre layer thickness and fibre-specific measures were moderately related to higher expanded disability status scale (rho = -0.368, rho = -0.408 and rho = -0.365, respectively). Fibre-specific measures can be measured from data collected within a standard radiological multiple sclerosis study and are substantially more sensitive to longitudinal change compared with brain atrophy and retinal nerve fibre layer thinning.

The effect of prolonged spaceflight on cerebrospinal fluid and perivascular spaces of astronauts and cosmonauts.

Long-duration spaceflight induces changes to the brain and cerebrospinal fluid compartments and visual acuity problems known as spaceflight-associated neuro-ocular syndrome (SANS). The clinical relevance of these changes and whether they equally affect crews of different space agencies remain unknown. We used MRI to analyze the alterations occurring in the perivascular spaces (PVS) in NASA and European Space Agency astronauts and Roscosmos cosmonauts after a 6-mo spaceflight on the International Space Station (ISS). We found increased volume of basal ganglia PVS and white matter PVS (WM-PVS) after spaceflight, which was more prominent in the NASA crew than the Roscosmos crew. Moreover, both crews demonstrated a similar degree of lateral ventricle enlargement and decreased subarachnoid space at the vertex, which was correlated with WM-PVS enlargement. As all crews experienced the same environment aboard the ISS, the differences in WM-PVS enlargement may have been due to, among other factors, differences in the use of countermeasures and high-resistive exercise regimes, which can influence brain fluid redistribution. Moreover, NASA astronauts who developed SANS had greater pre- and postflight WM-PVS volumes than those unaffected. These results provide evidence for a potential link between WM-PVS fluid and SANS.