A novel geometry-based analysis of hippocampal morphometry in mesial temporal lobe epilepsy.

Hippocampal volumetry is an essential tool in researching and diagnosing mesial temporal lobe epilepsy (mTLE). However, it has a limited ability to detect subtle alterations in hippocampal morphometry. Here, we establish and apply a novel geometry-based tool that enables point-wise morphometric analysis based on an intrinsic coordinate system of the hippocampus. We hypothesized that this point-wise analysis uncovers structural alterations not measurable by volumetry, but associated with histological underpinnings and the neuropsychological profile of mTLE. We conducted a retrospective study in 204 individuals with mTLE and 57 age- and gender-matched healthy subjects. FreeSurfer-based segmentations of hippocampal subfields in 3T-MRI were subjected to a geometry-based analysis that resulted in a coordinate system of the hippocampal mid-surface and allowed for point-wise measurements of hippocampal thickness and other features. Using point-wise analysis, we found significantly lower thickness and higher FLAIR signal intensity in the entire affected hippocampus of individuals with hippocampal sclerosis (HS-mTLE). In the contralateral hippocampus of HS-mTLE and the affected hippocampus of MRI-negative mTLE, we observed significantly lower thickness in the presubiculum. Impaired verbal memory was associated with lower thickness in the left presubiculum. In HS-mTLE histological subtype 3, we observed higher curvature than in subtypes 1 and 2 (all p < .05). These findings could not be observed using conventional volumetry (Bonferroni-corrected p < .05). We show that point-wise measures of hippocampal morphometry can uncover structural alterations not measurable by volumetry while also reflecting histological underpinnings and verbal memory. This substantiates the prospect of their clinical application.

Seizure-mediated iron accumulation and dysregulated iron metabolism after status epilepticus and in temporal lobe epilepsy.

Neuronal dysfunction due to iron accumulation in conjunction with reactive oxygen species (ROS) could represent an important, yet underappreciated, component of the epileptogenic process. However, to date, alterations in iron metabolism in the epileptogenic brain have not been addressed in detail. Iron-related neuropathology and antioxidant metabolic processes were investigated in resected brain tissue from patients with temporal lobe epilepsy and hippocampal sclerosis (TLE-HS), post-mortem brain tissue from patients who died after status epilepticus (SE) as well as brain tissue from the electrically induced SE rat model of TLE. Magnetic susceptibility of the presumed seizure-onset zone from three patients with focal epilepsy was compared during and after seizure activity. Finally, the cellular effects of iron overload were studied in vitro using an acute mouse hippocampal slice preparation and cultured human fetal astrocytes. While iron-accumulating neurons had a pyknotic morphology, astrocytes appeared to acquire iron-sequestrating capacity as indicated by prominent ferritin expression and iron retention in the hippocampus of patients with SE or TLE. Interictal to postictal comparison revealed increased magnetic susceptibility in the seizure-onset zone of epilepsy patients. Post-SE rats had consistently higher hippocampal iron levels during the acute and chronic phase (when spontaneous recurrent seizures are evident). In vitro, in acute slices that were exposed to iron, neurons readily took up iron, which was exacerbated by induced epileptiform activity. Human astrocyte cultures challenged with iron and ROS increased their antioxidant and iron-binding capacity, but simultaneously developed a pro-inflammatory phenotype upon chronic exposure. These data suggest that seizure-mediated, chronic neuronal iron uptake might play a role in neuronal dysfunction/loss in TLE-HS. On the other hand, astrocytes sequester iron, specifically in chronic epilepsy. This function might transform astrocytes into a highly resistant, pro-inflammatory phenotype potentially contributing to pro-epileptogenic inflammatory processes.

Blood-brain barrier permeability measurement by biexponentially modeling whole-brain arterial spin labeling data with multiple T2 -weightings.

Blood-brain barrier (BBB) permeability assessment remains of ongoing interest in clinical practice and research. Transitions between intravascular (IV) and extravascular (EV) gray matter (GM) compartments may provide information regarding the microstructural status of the BBB. Due to different transverse relaxation times (T2 ) of water protons in vessels and GM, it is possible to determine the compartment in which these protons are located. This work presents and investigates the feasibility of a simplified analytical approach for compartmentalizing the proportions of magnetically marked water protons into IV and EV GM components by biexponentially modeling T2 -weighted arterial spin labeling (ASL) data. Numerous model assumptions were used to stabilize the fit and achieve in vivo applicability. Particularly, transverse relaxation times of IV and EV water protons were determined from the analysis of two supporting T2 -weighted ASL measurements, utilizing a monoexponential signal model. This stabilized a two-parameter biexponential fit of ASL data with T2 preparation (PLD = 0.9/1.2/1.5/1.8 s, TET2Prep = 0/30/40/60/80/120/160 ms), which thereby robustly provided estimates of the IV and EV compartment fractions. Experiments were conducted with three healthy volunteers in a 3 T scanner. Averaged over all subjects, the labeled water protons inherit T2,IV = 200 ± 18 ms initially and adapt T2,EV = 91 ± 2 ms with a longer retention time in cerebral structures. Accordingly, the EVlocated ASL signal fraction rises with increasing PLD from 0.31 ± 0.11 at the shortest PLD of 0.9 s to 0.73 ± 0.02 at the longest PLD of 1.8s. These results indicate a transition of the water protons from IV to EV space. The findings support the potential of biexponential modeling for compartmentalizing ASL spin fractions between IV and EV space. The novel integration of monoexponential parameter estimates stabilizes the two-compartment model fit, suggesting that this technique is suitable for robustly estimating the BBB permeability in vivo.

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.

INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, the gold standard TSPO PET quantification method includes a 90 min scan and continuous arterial blood sampling, which is challenging to perform on a routine basis. In this work, we determine what information is required for a simplified quantification approach using a machine learning algorithm. MATERIALS AND METHODS: We analyzed data from 18 patients with ischemic stroke who received 0-90 min [18F]GE-180 PET as well as T1-weigted (T1w), FLAIR, and arterial spin labeling (ASL) MRI scans. During PET scans, five manual venous blood samples at 5, 15, 30, 60, and 85 min post injection (p.i.) were drawn, and plasma activity concentration was measured. Total distribution volume (VT) was calculated using Logan plot with the full dynamic PET and an image-derived input function (IDIF) from the carotid arteries. IDIF was scaled by a calibration factor derived from all the measured plasma activity concentrations. The calculated VT values were used for training a random forest regressor. As input features for the model, we used three late PET frames (60-70, 70-80, and 80-90 min p.i.), the ASL image reflecting perfusion, the voxel coordinates, the lesion mask, and the five plasma activity concentrations. The algorithm was validated with the leave-one-out approach. To estimate the impact of the individual features on the algorithm's performance, we used Shapley Additive Explanations (SHAP). Having determined that the three late PET frames and the plasma activity concentrations were the most important features, we tested a simplified quantification approach consisting of dividing a late PET frame by a plasma activity concentration. All the combinations of frames/samples were compared by means of concordance correlation coefficient and Bland-Altman plots. RESULTS: When using all the input features, the algorithm predicted VT values with high accuracy (87.8 ±â€¯8.3%) for both lesion and non-lesion voxels. The SHAP values demonstrated high impact of the late PET frames (60-70, 70-80, and 80-90 min p.i.) and plasma activity concentrations on the VT prediction, while the influence of the ASL-derived perfusion, voxel coordinates, and the lesion mask was low. Among all the combinations of the late PET frames and plasma activity concentrations, the 70-80 min p.i. frame divided by the 30 min p.i. plasma sample produced the closest VT estimate in the ischemic lesion. CONCLUSION: Reliable TSPO PET quantification is achievable by using a single late PET frame divided by a late blood sample activity concentration.

An open presurgery MRI dataset of people with epilepsy and focal cortical dysplasia type II.

Automated detection of lesions using artificial intelligence creates new standards in medical imaging. For people with epilepsy, automated detection of focal cortical dysplasias (FCDs) is widely used because subtle FCDs often escape conventional neuroradiological diagnosis. Accurate recognition of FCDs, however, is of outstanding importance for affected people, as surgical resection of the dysplastic cortex is associated with a high chance of postsurgical seizure freedom. Here, we make publicly available a dataset of 85 people affected by epilepsy due to FCD type II and 85 healthy control persons. We publish 3D-T1 and 3D-FLAIR, manually labeled regions of interest, and carefully selected clinical features. The open presurgery MRI dataset may be used to validate existing automated algorithms of FCD detection as well as to create new approaches. Most importantly, it will enable comparability of already existing approaches and support a more widespread use of automated lesion detection tools.

Large Phenotypic Variation of Individuals from a Family with a Novel ASPM Mutation Associated with Microcephaly, Epilepsy, and Behavioral and Cognitive Deficits.

Here, we report a consanguineous family harboring a novel homozygous frame-shift mutation in ASPM leading to a truncation of the ASPM protein after amino acid position 1830. The phenotype of the patients was associated with microcephaly, epilepsy, and behavioral and cognitive deficits. Despite the obvious genetic similarity, the affected patients show a considerable phenotypic heterogeneity regarding the degree of mental retardation, presence of epilepsy and MRI findings. Interestingly, the degree of mental retardation and the presence of epilepsy correlates well with the severity of abnormalities detected in brain MRI. On the other hand, we detected no evidence for substantial nonsense-mediated ASPM transcript decay in blood samples. This indicates that other factors than ASPM expression levels are relevant for the variability of structural changes in brain morphology seen in patients with primary hereditary microcephaly caused by ASPM mutations.

Reliability and Reproducibility of Hadamard Encoded Pseudo-Continuous Arterial Spin Labeling in Healthy Elderly.

The perfusion parameters cerebral blood flow (CBF) and arterial transit time (ATT) measured with arterial spin labeling (ASL) magnetic resonance imaging (MRI) provide valuable essentials to assess the integrity of cerebral tissue. Brain perfusion changes, due to aging, an intervention, or neurodegenerative diseases for example, could be investigated in longitudinal ASL studies with reliable ASL sequences. Generally, pseudo-continuous ASL (pCASL) is preferred because of its larger signal-to-noise ratio (SNR) compared to pulsed ASL (PASL) techniques. Available pCASL versions differ regarding their feature details. To date only little is known about the reliability and reproducibility of CBF and ATT measures obtained with the innovative Hadamard encoded pCASL variant, especially if applied on participants in old age. Therefore, we investigated an in-house developed Hadamard encoded pCASL sequence on a group of healthy elderly at two different 3 Tesla Siemens MRI systems (Skyra and mMR Biograph) and evaluated CBF and ATT reliability and reproducibility for several regions-of-interests (ROI). Calculated within-subject coefficients of variation (wsCV) demonstrated an excellent reliability of perfusion measures, whereas ATT appeared to be even more reliable than CBF [e.g., wsCV(CBF) = 2.9% vs. wsCV(ATT) = 2.3% for a gray matter (GM) ROI on Skyra system]. Additionally, a substantial agreement of perfusion values acquired on both MRI systems with an inter-session interval of 78 ± 17.6 days was shown by high corresponding intra-class correlation (ICC) coefficients [e.g., ICC(CBF) = 0.704 and ICC(ATT) = 0.754 for a GM ROI]. The usability of this novel Hadamard encoded pCASL sequence might improve future follow-up perfusion studies of the aging and/or diseased brain.

Reliability of quantitative transverse relaxation time mapping with [Formula: see text]-prepared whole brain pCASL.

Arterial spin labeling (ASL) is increasingly applied for cerebral blood flow mapping, but [Formula: see text] relaxation of the ASL signal magnetization is often ignored, although it may be clinically relevant. To investigate the extent, to which quantitative [Formula: see text] values in gray matter (GM) obtained by pseudocontinuous ASL (pCASL) perfusion MRI can be reproduced, are reliable and a potential neuroscientific biomarker, a prospective study was performed with ten healthy volunteers (5F,28 ± 3y) at a 3 T scanner. A [Formula: see text]-prepared pCASL sequence enabled the measurement of quantitative [Formula: see text] and perfusion maps. [Formula: see text] times were modeled per voxel and analyzed within four GM-regions-of-interest (ROI). The intraclass correlation coefficients (ICCs) of the quantified ASL-[Formula: see text] varied across brain regions. When averaged across subjects and postlabeling delays (PLDs), the ICCs ranged from reasonable values in parietal regions (ICC = 0.56) to smaller values in frontal regions (ICC = 0.36). Corresponding subject-averaged within-subject coefficients of variation (WSCVs) showed good test-retest measurement precision ([Formula: see text] for all PLDs), but more pronounced inter-subject variance. Reliability and precision of quantified ASL-[Formula: see text] were region-, PLD- and subject-specific, showing fair to robust results in occipital, parietal and temporal ROIs. The results give rise to consider the method for future cerebral studies, where variable perfusion or altered [Formula: see text] times are suspected.