Transient brain structure changes after high phenylalanine exposure in adults with phenylketonuria.

Phenylketonuria is a rare metabolic disease resulting from a deficiency of the enzyme phenylalanine hydroxylase. Recent cross-sectional evidence suggests that early-treated adults with phenylketonuria exhibit alterations in cortical grey matter compared to healthy peers. However, the effects of high phenylalanine exposure on brain structure in adulthood need to be further elucidated. In this double-blind, randomised, placebo-controlled crossover trial, we investigated the impact of a four-week high phenylalanine exposure on the brain structure and its relationship to cognitive performance and metabolic parameters in early-treated adults with phenylketonuria. Twenty-eight adult patients with early-treated classical phenylketonuria (19-48 years) underwent magnetic resonance imaging before and after the four-week phenylalanine and placebo interventions (four timepoints). Structural T1-weighted images were preprocessed and evaluated using DL+DiReCT, a deep-learning-based tool for brain morphometric analysis. Cortical thickness, white matter volume, and ventricular volume were compared between the phenylalanine and placebo periods. Brain phenylalanine levels were measured using 1H spectroscopy. Blood levels of phenylalanine, tyrosine, and tryptophan were assessed at each of the four timepoints, along with performance in executive functions and attention. Blood phenylalanine levels were significantly higher after the phenylalanine period (1441µmol/L) than after the placebo period (873µmol/L, P<0.001). Morphometric analyses revealed a statistically significant decrease in cortical thickness in 17 out of 60 brain regions after the phenylalanine period compared to placebo. The largest decreases were observed in the right pars orbitalis (point estimate=-0.095mm, P<0.001) and the left lingual gyrus (point estimate=-0.070mm, P<0.001). Bilateral white matter and ventricular volumes were significantly increased after the phenylalanine period. However, the structural alterations in the Phe-placebo group returned to baseline measures following the washout and placebo period. Additionally, elevated blood and brain phenylalanine levels were related to increased bilateral white matter volume (rs=0.43 to 0.51, P≤0.036) and decreased cortical thickness (rs=-0.62 to -0.39, not surviving FDR correction) after the phenylalanine and placebo periods. Moreover, decreased cortical thickness was correlated with worse cognitive performance after both periods (rs=-0.54 to -0.40, not surviving FDR correction). These findings provide evidence that a four-week high phenylalanine exposure in adults with phenylketonuria results in transient reductions of the cortical grey matter and increases in white matter volume. Further research is needed to determine the potential long-term impact of high phenylalanine levels on brain structure and function in adults with phenylketonuria.

Sex differences in multiple sclerosis relapse presentation and outcome: a retrospective, monocentric study of 134 relapse events.

Background: Reporting of sex-specific analyses in multiple sclerosis (MS) is sparse. Disability accrual results from relapses (relapse-associated worsening) and independent thereof (progression independent of relapses). Objectives: A population of MS patients during relapse treated per standard of care was analyzed for sex differences and short-term relapse outcome (3-6 months) as measured by Expanded Disability Status Scale (EDSS) change. Design: Single-center retrospective study. Methods: We analyzed 134 MS relapses between March 2016 and August 2020. All events required relapse treatment (steroids and/or plasma exchange). Demographic, disease, and paraclinical characteristics [cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI)] were displayed separated by sex. Multivariable linear regression was run to identify factors associated with short-term EDSS change. Results: Mean age at relapse was 38.4 years (95% confidence interval: 36.3-40.4) with a proportion of 71.6% women in our cohort. Smoking was more than twice as prevalent in men (65.8%) than women (32.3%). In- and after-relapse EDSSs were higher in men [men: 3.3 (2.8-3.9), women: 2.7 (2.4-3.0); men: 3.0 (1.3-3.6); women: 1.8 (1.5-2.1)] despite similar relapse intervention. Paraclinical parameters revealed no sex differences. Our primary model identified female sex, younger age, and higher EDSS at relapse to be associated with EDSS improvement. A higher immunoglobulin G (IgG) quotient (CSF/serum) was associated with poorer short-term outcome [mean days between first relapse treatment and last EDSS assessment 130.2 (79.3-181.0)]. Conclusion: Sex and gender differences are important in outcome analyses of MS relapses. Effective treatment regimens need to respect putative markers for a worse outcome to modify long-term prognosis such as clinical and demographic variables, complemented by intrathecal IgG synthesis. Prospective trials should be designed to address these differences and confirm our results.

An analysis of 134 acute relapses of multiple sclerosis reveal sex differences influencing recovery from relapse Sex-specific analyses are important in medicine, but more knowledge is still needed. Multiple sclerosis (MS) as an inflammatory disease of the brain and spinal cord mainly affects younger people who are at risk for development of disability. Disability may result from acute relapses of the disease that insufficiently recover. Our analysis aimed to assess sex differences with a special focus on the acute relapse and 3 to 6 months later on average. We collected existing data from our center and identified 134 relapse events with sufficient data for further analysis. All relapses were treated with medical (high-dose steroids) and/or interventional treatment (plasma exchange). We analyzed the influence of sex, age, smoking, relapse severity, relapse treatment and other treatment (immunotherapy) for MS. In a second analysis, cerebrospinal fluid (CSF) and imaging (MRI) parameters were included. Our cohort consisted of 72% women. The mean age was 38 years. Smoking was twice as common in men (66%) than in women (32%). Men also experienced more severe disability in and after the relapse. Several other factors were similar between men and women. Female sex and younger age were associated with lower disability after a relapse. Paradoxically, also higher disability in the relapse was associated with lower disability later on. This might be a statistical phenomenon and partly explained by overall low disability levels in our analysis. It might therefore not be true for more advanced disease stages with higher disability. The presence of a certain CSF marker (intrathecal IgG synthesis) was associated with higher disability after the relapse. Our analysis thus identified markers associated with different relapse recovery, male vs. female sex being one of them.

Simultaneous multi-region detection of GABA+ and Glx using 3D spatially resolved SLOW-editing and EPSI-readout at 7T.

GABA+ and Glx (glutamate and glutamine) are widely studied metabolites, yet the commonly used magnetic resonance spectroscopy (MRS) techniques have significant limitations, including sensitivity to B0 and B1+-inhomogeneities, limited bandwidth of MEGA-pulses, high SAR which is accentuated at 7T. To address these limitations, we propose SLOW-EPSI method, employing a large 3D MRSI coverage and achieving a high resolution down to 0.26 ml. Simulation results demonstrate the robustness of SLOW-editing for both GABA+ and Glx against B0 and B1+-inhomogeneities within the range of [-0.3, +0.3] ppm and [40 %, 250 %], respectively. Two protocols, both utilizing a 70 mm thick FOV slab, were employed to target distinct brain regions in vivo, differentiated by their orientation: transverse and tilted. Protocol 1 (n = 11) encompassed 5 locations (cortical gray matter, white matter, frontal lobe, parietal lobe, and cingulate gyrus). Protocol 2 (n = 5) involved 9 locations (cortical gray matter, white matter, frontal lobe, occipital lobe, cingulate gyrus, caudate nucleus, hippocampus, putamen, and inferior thalamus). Quantitative analysis of GABA+ and Glx was conducted in a stepwise manner. First, B1+/B1--inhomogeneities were corrected using water reference data. Next, GABA+ and Glx values were calculated employing spectral fitting. Finally, the GABA+ level for each selected region was compared to the global Glx within the same subject, generating the GABA+/Glx_global ratio. Our findings from two protocols indicate that the GABA+/Glx_global level in cortical gray matter was approximately 16 % higher than in white matter. Elevated GABA+/Glx_global levels acquired with protocol 2 were observed in specific regions such as the caudate nucleus (0.118±0.067), putamen (0.108±0.023), thalamus (0.092±0.036), and occipital cortex (0.091±0.010), when compared to the cortical gray matter (0.079±0.012). Overall, our results highlight the effectiveness of SLOW-EPSI as a robust and efficient technique for accurate measurements of GABA+ and Glx at 7T. In contrast to previous SVS and 2D-MRSI based editing sequences with which only one or a limited number of brain regions can be measured simultaneously, the method presented here measures GABA+ and Glx from any brain area and any arbitrarily shaped volume that can be flexibly selected after the examination. Quantification of GABA+ and Glx across multiple brain regions through spectral fitting is achievable with a 9-minute acquisition. Additionally, acquisition times of 18-27 min (GABA+) and 9-18 min (Glx) are required to generate 3D maps, which are constructed using Gaussian fitting and peak integration.

CADMUS: A Novel MRI-Based Classification of Spontaneous Intracerebral Hemorrhage Associated With Cerebral Small Vessel Disease

BACKGROUND AND OBJECTIVES: Cerebral small vessel disease (SVD) is the major cause of intracerebral hemorrhage (ICH). There is no comprehensive, easily applicable classification of ICH subtypes according to the presumed underlying SVD using MRI. We developed an MRI-based classification for SVD-related ICH. METHODS: We performed a retrospective study in the prospectively collected Swiss Stroke Registry (SSR, 2013-2019) and the Stroke InvestiGation in North And central London (SIGNAL) cohort. Patients with nontraumatic, SVD-related ICH and available MRI within 3 months were classified as Cerebral Amyloid angiopathy (CAA), Deep perforator arteriopathy (DPA), Mixed CAA-DPA, or Undetermined SVD using hemorrhagic and nonhemorrhagic MRI markers (CADMUS classification). The primary outcome was inter-rater reliability using Gwet's AC1. Secondary outcomes were recurrent ICH/ischemic stroke at 3 months according to the CADMUS phenotype. We performed Firth penalized logistic regressions and competing risk analyses. RESULTS: The SSR cohort included 1,180 patients (median age [interquartile range] 73 [62-80] years, baseline NIH Stroke Scale 6 [2-12], 45.6% lobar hematoma, systolic blood pressure on admission 166 [145-185] mm Hg). The CADMUS phenotypes were as follows: mixed CAA-DPA (n = 751 patients, 63.6%), undetermined SVD (n = 203, 17.2%), CAA (n = 154, 13.1%), and DPA (n = 72, 6.3%), with a similar distribution in the SIGNAL cohort (n = 313). Inter-rater reliability was good (Gwet's AC1 for SSR/SIGNAL 0.69/0.74). During follow-up, 56 patients had 57 events (28 ICH, 29 ischemic strokes). Three-month event rates were comparable between the CADMUS phenotypes. DISCUSSION: CADMUS, a novel MRI-based classification for SVD-associated ICH, is feasible and reproducible and may improve the classification of ICH subtypes in clinical practice and research.

Growing importance of brain morphometry analysis in the clinical routine: The hidden impact of MR sequence parameters.

Volumetric assessment based on structural MRI is increasingly recognized as an auxiliary tool to visual reading, also in examinations acquired in the clinical routine. However, MRI acquisition parameters can significantly influence these measures, which must be considered when interpreting the results on an individual patient level. This Technical Note shall demonstrate the problem. Using data from a dedicated experiment, we show the influence of two crucial sequence parameters on the GM/WM contrast and their impact on the measured volumes. A simulated contrast derived from acquisition parameters TI/TR may serve as surrogate and is highly correlated (r=0.96) with the measured contrast.

Diagnosis of Small Unruptured Intracranial Aneurysms : Comparison of 7 T versus 3 T MRI.

PURPOSE: Differentiating normal anatomical variants such as an infundibulum or a vascular loop from true intracranial aneurysms is crucial for patient management. We hypothesize that high-resolution 7 T magnetic resonance imaging (MRI) improves the detection and characterization of normal anatomical variants that may otherwise be misdiagnosed as small unruptured aneurysms. METHODS: This is a retrospective, single-center study. All patients were scanned on a clinically approved 7 T MRI scanner and on a 3 T scanner. Image analysis was performed independently by three neuroradiologists blinded to clinical information. The presence of an unruptured intracranial aneurysm (UIA) and level of diagnostic certainty were assessed and the interrater agreement was calculated. If an aneurysm was present, the anatomic location and shape were recorded and compared. RESULTS: In total, 53 patients with equivocal cerebrovascular findings on 1.5 T or 3 T MRI referred for a 7T MRI examination were included. Aneurysms were suspected in 42 patients examined at 3 T and in 23 patients at 7 T (rate difference 36%, 95% confidence interval, CI, 19-53%, p-value < 0.001). Major disagreement between the field strengths was observed in the A1 segment of anterior cerebral artery/anterior communicating artery (A1/ACOM) complex. The interrater agreement among the readers on the presence of an aneurysm on 7 T MRI was higher than that for 3 T MRI (0.925, 95% CI 0.866-0.983 vs. 0.786, 95% CI 0.700-0.873). CONCLUSION: Our analysis demonstrates a significantly higher interrater agreement and improved diagnostic certainty when small intracranial aneurysms are visualized on 7 T MRI compared to 3 T. In a selected patient cohort, clinical implementation of 7 T MRI may help to establish the definitive diagnosis and thus have a beneficial impact on patient management.

Cerebral blood flow and white matter alterations in adults with phenylketonuria.

BACKGROUND: Phenylketonuria (PKU) represents a congenital metabolic defect that disrupts the process of converting phenylalanine (Phe) into tyrosine. Earlier investigations have revealed diminished cognitive performance and changes in brain structure and function (including the presence of white matter lesions) among individuals affected by PKU. However, there exists limited understanding regarding cerebral blood flow (CBF) and its potential associations with cognition, white matter lesions, and metabolic parameters in patients with PKU, which we therefore aimed to investigate in this study. METHOD: Arterial spin labeling perfusion MRI was performed to measure CBF in 30 adults with early-treated classical PKU (median age 35.5 years) and 59 healthy controls (median age 30.0 years). For all participants, brain Phe levels were measured with 1H spectroscopy, and white matter lesions were rated by two neuroradiologists on T2 weighted images. White matter integrity was examined with diffusion tensor imaging (DTI). For patients only, concurrent plasma Phe levels were assessed after an overnight fasting period. Furthermore, past Phe levels were collected to estimate historical metabolic control. On the day of the MRI, each participant underwent a cognitive assessment measuring IQ and performance in executive functions, attention, and processing speed. RESULTS: No significant group difference was observed in global CBF between patients and controls (F (1, 87) = 3.81, p = 0.054). Investigating CBF on the level of cerebral arterial territories, reduced CBF was observed in the left middle and posterior cerebral artery (MCA and PCA), with the most prominent reduction of CBF in the anterior subdivision of the MCA (F (1, 87) = 6.15, p = 0.015, surviving FDR correction). White matter lesions in patients were associated with cerebral blood flow reduction in the affected structure. Particularly, patients with lesions in the occipital lobe showed significant CBF reductions in the left PCA (U = 352, p = 0.013, surviving FDR correction). Additionally, axial diffusivity measured with DTI was positively associated with CBF in the ACA and PCA (surviving FDR correction). Cerebral blood flow did not correlate with cognitive performance or metabolic parameters. CONCLUSION: The relationship between cerebral blood flow and white matter indicates a complex interplay between vascular health and white matter alterations in patients with PKU. It highlights the importance of considering a multifactorial model when investigating the impact of PKU on the brain.

Compromised white matter is related to lower cognitive performance in adults with phenylketonuria.

Despite increasing knowledge about the effects of phenylketonuria on brain structure and function, it is uncertain whether white matter microstructure is affected and if it is linked to patients' metabolic control or cognitive performance. Thus, we quantitatively assessed white matter characteristics in adults with phenylketonuria and assessed their relationship to concurrent brain and blood phenylalanine levels, historical metabolic control and cognitive performance. Diffusion tensor imaging and 1H spectroscopy were performed in 30 adults with early-treated classical phenylketonuria (median age 35.5 years) and 54 healthy controls (median age 29.3 years). Fractional anisotropy and mean, axial and radial diffusivity were investigated using tract-based spatial statistics, and white matter lesion load was evaluated. Brain phenylalanine levels were measured with 1H spectroscopy whereas concurrent plasma phenylalanine levels were assessed after an overnight fast. Retrospective phenylalanine levels were collected to estimate historical metabolic control, and a neuropsychological evaluation assessed the performance in executive functions, attention and processing speed. Widespread reductions in mean diffusivity, axial diffusivity and fractional anisotropy occurred in patients compared to controls. Mean diffusivity and axial diffusivity were decreased in several white matter tracts and were most restricted in the optic radiation (effect size rrb = 0.66 to 0.78, P < 0.001) and posterior corona radiata (rrb = 0.83 to 0.90, P < 0.001). Lower fractional anisotropy was found in the optic radiation and posterior corona radiata (rrb = 0.43 to 0.49, P < 0.001). White matter microstructure in patients was significantly associated with cognition. Specifically, inhibition was related to axial diffusivity in the external capsule (rs = -0.69, P < 0.001) and the superior (rs = -0.58, P < 0.001) and inferior longitudinal fasciculi (rs = -0.60, P < 0.001). Cognitive flexibility was associated with mean diffusivity of the posterior limb of the internal capsule (rs = -0.62, P < 0.001), and divided attention correlated with fractional anisotropy of the external capsule (rs = -0.61, P < 0.001). Neither concurrent nor historical metabolic control was significantly associated with white matter microstructure. White matter lesions were present in 29 out of 30 patients (96.7%), most often in the parietal and occipital lobes. However, total white matter lesion load scores were unrelated to patients' cognitive performance and metabolic control. In conclusion, our findings demonstrate that white matter alterations in early-treated phenylketonuria persist into adulthood, are most prominent in the posterior white matter and are likely to be driven by axonal damage. Furthermore, diffusion tensor imaging metrics in adults with phenylketonuria were related to performance in attention and executive functions.

Clinical Evaluation of a Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis.

OBJECTIVE: To evaluate the influence of quantitative reports (QReports) on the radiological assessment of hippocampal sclerosis (HS) from MRI of patients with epilepsy in a setting mimicking clinical reality. METHODS: The study included 40 patients with epilepsy, among them 20 with structural abnormalities in the mesial temporal lobe (13 with HS). Six raters blinded to the diagnosis assessed the 3T MRI in two rounds, first using MRI only and later with both MRI and the QReport. Results were evaluated using inter-rater agreement (Fleiss' kappa [Formula: see text]) and comparison with a consensus of two radiological experts derived from clinical and imaging data, including 7T MRI. RESULTS: For the primary outcome, diagnosis of HS, the mean accuracy of the raters improved from 77.5% with MRI only to 86.3% with the additional QReport (effect size [Formula: see text]). Inter-rater agreement increased from [Formula: see text] to [Formula: see text]. Five of the six raters reached higher accuracies, and all reported higher confidence when using the QReports. CONCLUSION: In this pre-use clinical evaluation study, we demonstrated clinical feasibility and usefulness as well as the potential impact of a previously suggested imaging biomarker for radiological assessment of HS.

α-D-Glucose as a non-radioactive MRS tracer for metabolic studies of the brain.

Changes in brain glucose metabolism occur in many neurological disorders as well as during aging. Most studies on the uptake of glucose in the brain use positron emission tomography, which requires injection of a radioactive tracer. Our study shows that ultra-high-field 1H-MRS can be used to measure α-D-glucose at 5.22 ppm in vivo, and the α-D-glucose can be used as a radiation-free tracer in the human brain.

Accurate prediction of isocitrate dehydrogenase -mutation status of gliomas using SLOW-editing magnetic resonance spectroscopic imaging at 7 T MR.

Background: 2-hydroxy-glutarate (2HG) is a metabolite that accumulates in isocitrate dehydrogenase (IDH)-mutated gliomas and can be detected noninvasively using MR spectroscopy. However, due to the low concentration of 2HG, established magnetic resonance spectroscopic imaging (MRSI) techniques at the low field have limitations with respect to signal-to-noise and to the spatial resolution that can be obtained within clinically acceptable measurement times. Recently a tailored editing method for 2HG detection at 7 Tesla (7 T) named SLOW-EPSI was developed. The underlying prospective study aimed to compare SLOW-EPSI to established techniques at 7 T and 3 T for IDH-mutation status determination. Methods: The applied sequences were MEGA-SVS and MEGA-CSI at both field strengths and SLOW-EPSI at 7 T only. Measurements were performed on a MAGNETOM-Terra 7 T MR-scanner in clinical mode using a Nova 1Tx32Rx head coil and on a 3 T MAGNETOM-Prisma scanner with a standard 32-channel head coil. Results: Fourteen patients with suspected glioma were enrolled. Histopathological confirmation was available in 12 patients. IDH mutation was confirmed in 9 out of 12 cases and 3 cases were characterized as IDH wildtype. SLOW-EPSI at 7 T showed the highest accuracy for IDH-status prediction (91.7% accuracy, 11 of the 12 predictions correct with 1 false negative case). At 7 T, MEGA-CSI had an accuracy of 58.3% and MEGA-SVS had an accuracy of 75%. At 3 T, MEGA-CSI showed an accuracy of 63.6% and MEGA-SVS of 33.3%. The co-edited cystathionine was detected in 2 out of 3 oligodendroglioma cases with 1p/19q codeletion. Conclusions: Depending on the pulse sequence, spectral editing can be a powerful tool for the noninvasive determination of the IDH status. SLOW-editing EPSI sequence is the preferable pulse sequence when used at 7 T for IDH-status characterization.

Large-scale transient peri-ictal perfusion magnetic resonance imaging abnormalities detected by quantitative image analysis.

Epileptic seizures require a rapid and safe diagnosis to minimize the time from onset to adequate treatment. Some epileptic seizures can be diagnosed clinically with the respective expertise. For more subtle seizures, imaging is mandatory to rule out treatable structural lesions and potentially life-threatening conditions. MRI perfusion abnormalities associated with epileptic seizures have been reported in CT and MRI studies. However, the interpretation of transient peri-ictal MRI abnormalities is routinely based on qualitative visual analysis and therefore reader dependent. In this retrospective study, we investigated the diagnostic yield of visual analysis of perfusion MRI during ictal and postictal states based on comparative expert ratings in 51 patients. We further propose an automated semi-quantitative method for perfusion analysis to determine perfusion abnormalities observed during ictal and postictal MRI using dynamic susceptibility contrast MRI, which we validated on a subcohort of 27 patients. The semi-quantitative method provides a parcellation of 3D T1-weighted images into 32 standardized cortical regions of interests and subcortical grey matter structures based on a recently proposed method, direct cortical thickness estimation using deep learning-based anatomy segmentation and cortex parcellation for brain anatomy segmentation. Standard perfusion maps from a Food and Drug Administration-approved image analysis tool (Olea Sphere 3.0) were co-registered and investigated for region-wise differences between ictal and postictal states. These results were compared against the visual analysis of two readers experienced in functional image analysis in epilepsy. In the ictal group, cortical hyperperfusion was present in 17/18 patients (94% sensitivity), whereas in the postictal cohort, cortical hypoperfusion was present only in 9/33 (27%) patients while 24/33 (73%) showed normal perfusion. The (semi-)quantitative dynamic susceptibility contrast MRI perfusion analysis indicated increased thalamic perfusion in the ictal cohort and hypoperfusion in the postictal cohort. Visual ratings between expert readers performed well on the patient level, but visual rating agreement was low for analysis of subregions of the brain. The asymmetry of the automated image analysis correlated significantly with the visual consensus ratings of both readers. We conclude that expert analysis of dynamic susceptibility contrast MRI effectively discriminates ictal versus postictal perfusion patterns. Automated perfusion evaluation revealed favourable interpretability and correlated well with the classification of the visual ratings. It may therefore be employed for high-throughput, large-scale perfusion analysis in extended cohorts, especially for research questions with limited expert rater capacity.

Anti-neurochondrin antibody as a biomarker in primary autoimmune cerebellar ataxia-a case report and review of the literature.

BACKGROUND AND PURPOSE: Neuronal autoantibodies can support the diagnosis of primary autoimmune cerebellar ataxia (PACA). Knowledge of PACA is still sparce. This article aims to highlight the relevance of anti-neurochondrin antibodies and possible therapeutical consequences in people with PACA. METHODS: This is a case presentation and literature review of PACA associated with anti-neurochondrin antibodies. RESULTS: A 33-year-old man noticed reduced control of the right leg in May 2020. During his first clinic appointment at our institution in September 2021, he complained about gait imbalance, fine motor disorders, tremor, intermittent diplopia and slurred speech. He presented a pancerebellar syndrome with stance, gait and limb ataxia, scanning speech and oculomotor dysfunction. Within 3 months the symptoms progressed. An initial cerebral magnetic resonance imaging, June 2020, was normal, but follow-up imaging in October 2021 and July 2022 revealed marked cerebellar atrophy (29% volume loss). Cerebrospinal fluid analysis showed lymphocytic pleocytosis of 11 x 103 /L (normal range 0-4) and oligoclonal bands type II. Anti-neurochondrin antibodies (immunoglobulin G) were detected in serum (1:10,000) and cerebrospinal fluid (1:320, by cell-based indirect immunofluorescence assay and immunoblot, analysed by the EUROIMMUN laboratory). After ruling out alternative causes and neoplasia, diagnosis of PACA was given and immunotherapy (steroids and cyclophosphamide) was started in January 2022. In March 2022 a stabilization of disease was observed. CONCLUSION: Cerebellar ataxia associated with anti-neurochondrin antibodies has only been described in 19 cases; however, the number of unrecognized PACAs may be higher. As anti-neurochondrin antibodies target an intracellular antigen and exhibit a mainly cytotoxic T-cell-mediated pathogenesis, important therapeutic implications may result. Because of the severe and rapid clinical progression, aggressive immunotherapy was warranted. This case highlights the need for rapid diagnosis and therapy in PACA, as stabilization and even improvement of symptoms are attainable.

Reliable brain morphometry from contrast-enhanced T1w-MRI in patients with multiple sclerosis.

Brain morphometry is usually based on non-enhanced (pre-contrast) T1-weighted MRI. However, such dedicated protocols are sometimes missing in clinical examinations. Instead, an image with a contrast agent is often available. Existing tools such as FreeSurfer yield unreliable results when applied to contrast-enhanced (CE) images. Consequently, these acquisitions are excluded from retrospective morphometry studies, which reduces the sample size. We hypothesize that deep learning (DL)-based morphometry methods can extract morphometric measures also from contrast-enhanced MRI. We have extended DL+DiReCT to cope with contrast-enhanced MRI. Training data for our DL-based model were enriched with non-enhanced and CE image pairs from the same session. The segmentations were derived with FreeSurfer from the non-enhanced image and used as ground truth for the coregistered CE image. A longitudinal dataset of patients with multiple sclerosis (MS), comprising relapsing remitting (RRMS) and primary progressive (PPMS) subgroups, was used for the evaluation. Global and regional cortical thickness derived from non-enhanced and CE images were contrasted to results from FreeSurfer. Correlation coefficients of global mean cortical thickness between non-enhanced and CE images were significantly larger with DL+DiReCT (r = 0.92) than with FreeSurfer (r = 0.75). When comparing the longitudinal atrophy rates between the two MS subgroups, the effect sizes between PPMS and RRMS were higher with DL+DiReCT both for non-enhanced (d = -0.304) and CE images (d = -0.169) than for FreeSurfer (non-enhanced d = -0.111, CE d = 0.085). In conclusion, brain morphometry can be derived reliably from contrast-enhanced MRI using DL-based morphometry tools, making additional cases available for analysis and potential future diagnostic morphometry tools.

Submillimeter T1 atlas for subject-specific abnormality detection at 7T.

PURPOSE: Studies at 3T have shown that T1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. METHODS: T1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T1 values was established by modeling the T1 inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. RESULTS: The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results. CONCLUSION: A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.

Multiple sclerosis as a model to investigate SARS-CoV-2 effect on brain atrophy.

INTRODUCTION: Data on structural brain changes after infection with SARS-CoV-2 is sparse. We postulate multiple sclerosis as a model to study the effects of SARS-CoV-2 on brain atrophy due to the unique availability of longitudinal imaging data in this patient group, enabling assessment of intraindividual brain atrophy rates. METHODS: Global and regional cortical gray matter volumes were derived from structural MRIs using FreeSurfer. A linear model was fitted to the measures of the matching pre-SARS-CoV-2 images with age as an explanatory variable. The residuals were used to determine whether the post-SARS-CoV-2 volumes differed significantly from the baseline. RESULTS: Fourteen RRMS patients with a total of 113 longitudinal magnetic resonance images were retrospectively analyzed. We found no acceleration of brain atrophy after infection with SARS-CoV-2 for global gray matter volume (p = 0.17). However, on the regional level, parahippocampal gyri showed a tendency toward volume reduction (p = 0.0076), suggesting accelerated atrophy during or after infection. CONCLUSIONS: Our results illustrate the opportunity of using longitudinal MRIs from existing MS registries to study brain changes associated with SARS-CoV-2 infections. We would like to address the global MS community with a call for action to use the available cohorts, reproduce the proposed analysis, and pool the results.

Clinical neuroimaging in intracerebral haemorrhage related to cerebral small vessel disease: contemporary practice and emerging concepts.

INTRODUCTION: About 80% of all non-traumatic intracerebral hemorrhage (ICH) are caused by the sporadic cerebral small vessel diseases deep perforator arteriopathy (DPA, also termed hypertensive arteriopathy or arteriolosclerosis) and cerebral amyloid angiopathy (CAA), though these frequently co-exist in older people. Contemporary neuroimaging (MRI and CT) detects an increasing spectrum of hemorrhagic and non-hemorrhagic imaging biomarkers of small vessel disease which may identify the underlying arteriopathies. AREAS COVERED: We discuss biomarkers for cerebral small vessel disease subtypes in ICH, and explore their implications for clinical practice and research. EXPERT OPINION: ICH is not a single disease, but results from a defined range of vascular pathologies with important implications for prognosis and treatment. The terms 'primary' and 'hypertensive' ICH are poorly defined and should be avoided, as they encourage incomplete investigation and classification. Imaging-based criteria for CAA will show improved diagnostic accuracy, but specific imaging biomarkers of DPA are needed. Ultra-high-field 7 T-MRI using structural and quantitative MRI may provide further insights into mechanisms and pathophysiology of small vessel disease. We expect neuroimaging biomarkers and classifications to allow personalized treatments (e.g. antithrombotic drugs) in clinical practice and to improve patient selection and monitoring in trials of targeted therapies directed at the underlying arteriopathies.

A Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis Derived From Deep Learning-Based Segmentation of T1w-MRI.

PURPOSE: Hippocampal volumetry is an important biomarker to quantify atrophy in patients with mesial temporal lobe epilepsy. We investigate the sensitivity of automated segmentation methods to support radiological assessments of hippocampal sclerosis (HS). Results from FreeSurfer and FSL-FIRST are contrasted to a deep learning (DL)-based segmentation method. MATERIALS AND METHODS: We used T1-weighted MRI scans from 105 patients with epilepsy and 354 healthy controls. FreeSurfer, FSL, and a DL-based method were applied for brain anatomy segmentation. We calculated effect sizes (Cohen's d) between left/right HS and healthy controls based on the asymmetry of hippocampal volumes. Additionally, we derived 14 shape features from the segmentations and determined the most discriminating feature to identify patients with hippocampal sclerosis by a support vector machine (SVM). RESULTS: Deep learning-based segmentation of the hippocampus was the most sensitive to detecting HS. The effect sizes of the volume asymmetries were larger with the DL-based segmentations (HS left d= -4.2, right = 4.2) than with FreeSurfer (left= -3.1, right = 3.7) and FSL (left= -2.3, right = 2.5). For the classification based on the shape features, the surface-to-volume ratio was identified as the most important feature. Its absolute asymmetry yielded a higher area under the curve (AUC) for the deep learning-based segmentation (AUC = 0.87) than for FreeSurfer (0.85) and FSL (0.78) to dichotomize HS from other epilepsy cases. The robustness estimated from repeated scans was statistically significantly higher with DL than all other methods. CONCLUSION: Our findings suggest that deep learning-based segmentation methods yield a higher sensitivity to quantify hippocampal sclerosis than atlas-based methods and derived shape features are more robust. We propose an increased asymmetry in the surface-to-volume ratio of the hippocampus as an easy-to-interpret quantitative imaging biomarker for HS.

SLOW: A novel spectral editing method for whole-brain MRSI at ultra high magnetic field.

PURPOSE: At ultra-high field (UHF), B1+ -inhomogeneities and high specific absorption rate (SAR) of adiabatic slice-selective RF-pulses make spatial resolved spectral-editing extremely challenging with the conventional MEGA-approach. The purpose of the study was to develop a whole-brain resolved spectral-editing MRSI at UHF (UHF, B0 ≥ 7T) within clinical acceptable measurement-time and minimal chemical-shift-displacement-artifacts (CSDA) allowing for simultaneous GABA/Glx-, 2HG-, and PE-editing on a clinical approved 7T-scanner. METHODS: Slice-selective adiabatic refocusing RF-pulses (2π-SSAP) dominate the SAR to the patient in (semi)LASER based MEGA-editing sequences, causing large CSDA and long measurement times to fulfill SAR requirements, even using SAR-minimized GOIA-pulses. Therefore, a novel type of spectral-editing, called SLOW-editing, using two different pairs of phase-compensated chemical-shift selective adiabatic refocusing-pulses (2π-CSAP) with different refocusing bandwidths were investigated to overcome these problems. RESULTS: Compared to conventional echo-planar spectroscopic imaging (EPSI) and MEGA-editing, SLOW-editing shows robust refocusing and editing performance despite to B1+ -inhomogeneity, and robustness to B0 -inhomogeneities (0.2 ppm ≥ ΔB0  ≥ -0.2 ppm). The narrow bandwidth (∼0.6-0.8 kHz) CSAP reduces the SAR by 92%, RF peak power by 84%, in-excitation slab CSDA by 77%, and has no in-plane CSDA. Furthermore, the CSAP implicitly dephases water, lipid and all the other signals outside of range (≥ 4.6 ppm and ≤1.4 ppm), resulting in additional water and lipid suppression (factors ≥ 1000s) at zero SAR-cost, and no spectral aliasing artifacts. CONCLUSION: A new spectral-editing has been developed that is especially suitable for UHF, and was successfully applied for 2HG, GABA+, PE, and Glx-editing within 10 min clinical acceptable measurement time.

Neural correlates of working memory and its association with metabolic parameters in early-treated adults with phenylketonuria.

BACKGROUND: Phenylketonuria (PKU) is an inborn error of metabolism affecting the conversion of phenylalanine (Phe) into tyrosine. Previous research has found cognitive and functional brain alterations in individuals with PKU even if treated early. However, little is known about working memory processing and its association with task performance and metabolic parameters. The aim of the present study was to examine neural correlates of working memory and its association with metabolic parameters in early-treated adults with PKU. METHODS: This cross-sectional study included 20 early-treated adults with PKU (mean age: 31.4 years ± 9.0) and 40 healthy controls with comparable age, sex, and education (mean age: 29.8 years ± 8.2). All participants underwent functional magnetic resonance imaging (fMRI) of working memory to evaluate the fronto-parietal working memory network. Fasting blood samples were collected from the individuals with PKU to acquire a concurrent plasma amino acid profile, and retrospective Phe concentrations were obtained to estimate an index of dietary control. RESULTS: On a cognitive level, early-treated adults with PKU displayed significantly lower accuracy but comparable reaction time in the working memory task compared to the control group. Whole-brain analyses did not reveal differences in working memory-related neural activation between the groups. Exploratory region-of-interest (ROI) analyses indicated reduced neural activation in the left and right middle frontal gyri and the right superior frontal gyrus in the PKU group compared to the control group. However, none of the ROI analyses survived correction for multiple comparisons. Neural activation was related to concurrent Phe, tyrosine, and tryptophan concentrations but not to retrospective Phe concentrations. CONCLUSION: In early-treated adults with PKU, cognitive performance and neural activation are slightly altered, a result that is partly related to metabolic parameters. This study offers a rare insight into the complex interplay between metabolic parameters, neural activation, and cognitive performance in a sample of individuals with PKU.