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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 1 H-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.

•Novel SLOW-EPSI technique for accurate measurements of GABA+ and Glx at 7T.•Large 3D MRSI coverage with high resolution.•Robust to B0/B1+ for GABA+ and Glx editing.•9-minute acquisition for multi-region volume quantification.•3D mapping of GABA+ and Glx for investigations of local and global neuropsychiatric conditions. 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. [Display omitted]

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. Plain language summary 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.

BackgroundAsphericity (ASP) of the primary tumor’s metabolic tumor volume (MTV) in FDG-PET/CT is independently predictive for survival in patients with non-small cell lung cancer (NSCLC). However, comparability between PET systems may be limited. Therefore, reproducibility of ASP was evaluated at varying image reconstruction and acquisition times to assess feasibility of ASP assessment in multicenter studies. MethodsThis is a retrospective study of 50 patients with NSCLC (female 20; median age 69 years) undergoing pretherapeutic FDG-PET/CT (median 3.7 MBq/kg; 180 s/bed position). Reconstruction used OSEM with TOF4/16 (iterations 4; subsets 16; in-plane filter 2.0, 6.4 or 9.5 mm), TOF4/8 (4 it; 8 ss; filter 2.0/6.0/9.5 mm), PSF + TOF2/17 (2 it; 17 ss; filter 2.0/7.0/10.0 mm) or Bayesian-penalized likelihood (Q.Clear; beta, 600/1750/4000). Resulting reconstructed spatial resolution (FWHM) was determined from hot sphere inserts of a NEMA IEC phantom. Data with approx. 5-mm FWHM were retrospectively smoothed to achieve 7-mm FWHM. List mode data were rebinned for acquisition times of 120/90/60 s. Threshold-based delineation of primary tumor MTV was followed by evaluation of relative ASP/SUVmax/MTV differences between datasets and resulting proportions of discordantly classified cases. ResultsReconstructed resolution for narrow/medium/wide in-plane filter (or low/medium/high beta) was approx. 5/7/9 mm FWHM. Comparing different pairs of reconstructed resolution between TOF4/8, PSF + TOF2/17, Q.Clear and the reference algorithm TOF4/16, ASP differences was lowest at FWHM of 7 versus 7 mm. Proportions of discordant cases (ASP > 19.5% vs. ≤ 19.5%) were also lowest at 7 mm (TOF4/8, 2%; PSF + TOF2/17, 4%; Q.Clear, 10%). Smoothing of 5-mm data to 7-mm FWHM significantly reduced discordant cases (TOF4/8, 38% reduced to 2%; PSF + TOF2/17, 12% to 4%; Q.Clear, 10% to 6%), resulting in proportions comparable to original 7-mm data. Shorter acquisition time only increased proportions of discordant cases at < 90 s.ConclusionsASP differences were mainly determined by reconstructed spatial resolution, and multicenter studies should aim at comparable FWHM (e.g., 7 mm; determined by in-plane filter width). This reduces discordant cases (high vs. low ASP) to an acceptable proportion for TOF and PSF + TOF of < 5% (Q.Clear: 10%). Data with better resolution (i.e., lower FWHM) could be retrospectively smoothed to the desired FWHM, resulting in a comparable number of discordant cases.

ObjectiveUp to 60% of patients with metastatic, castration-resistant prostate cancer (mCRPC) treated with 177Lu prostate-specific membrane antigen (PSMA) radioligand therapy (RLT) achieves a partial biochemical response with a decrease of > 50% in prostate-specific antigen (PSA) levels. The remaining fractions, however, do not respond to RLT. The aim of this explorative analysis was to identify pre-therapeutic factors for the prediction of response.Methods46 patients [age = 68 years (50–87)] with mCRPC who consecutively underwent RLT with 177Lu PSMA [median applied activity = 6 GBq (2.9–6.2)] were included and analysed retrospectively. The association of different clinical and laboratory factors and parameters from pre-therapeutic 68Ga PSMA positron emission tomography (PET) with the outcome of RLT was tested (Fisher’s test). Outcome was defined as PSA changes 8 weeks after second RLT [partial response (PR), PSA decrease > 50%; progressive disease (PD), PSA increase ≥ 25%; stable disease (SD), others]. Significant predictive factors were combined in a predictive score.Results30% showed a post-treatment PR (median 73% PSA decrease), 35% SD (median 17% PSA decrease) and 35% PD (median 42% PSA increase). Significant predictors for PD were alkaline phosphatase (ALP) > 135 U/l (p = 0.002), PSA > 200 ng/ml (p = 0.036), and maximum standardized uptake value (SUVmax) of the “hottest lesion” in pre-therapeutic PET < 45 (p = 0.005). The predictive score including PSA, ALP and SUVmax could separate 2 distinct groups of patients: ≤ 2 predictive factors (19% PD) and 3 predictive factors (90% PD).ConclusionThe presented predictive score allowed a pre-therapeutic estimate of the expected response to 2 cycles of RLT. As our study was retrospective, prospective trials are needed for validation.

Cortical thickness measurements from MRI are increasingly used as biomarkers for neurodegenerative disease progression. However, variations in MRI acquisition parameters, such as inversion time (TI) and repetition time (TR), which are common in clinical settings, can compromise the reliability and sensitivity of these measurements. We fine‐tuned a deep‐learning‐based segmentation tool (DL+DiReCT) to reduce its dependence to image contrast variations by training it on simulated MPRAGE images derived from quantitative relaxation maps. Fine‐tuning markedly reduced contrast sensitivity, with the Pearson correlation coefficient decreasing from −0.644 -0.644 to 0.094 0.094 . Evaluation on a synthetic atrophy dataset demonstrated that our model accurately replicated atrophy trends with minimal underestimation, outperforming FreeSurfer and SynthSeg. When applied to a dataset of relapsing–remitting multiple sclerosis (RRMS) patients, the fine‐tuned model showed a substantial reduction in contrast sensitivity and maintained stable performance after controlling for covariates such as age, sex, field strength, and Expanded Disability Status Scale (EDSS) score. Overall, the proposed approach achieves robust contrast invariance without sacrificing sensitivity to cortical atrophy, offering a practical improvement for longitudinal and multi‐center clinical studies. Key Points Changes in MR acquisition settings, specifically of TI and TR, which are common in the clinical setting, affect WM/GM contrast, which in turn affects cortical thickness measurements. Deep learning models can be fine‐tuned on synthetic MRI simulation across different contrasts for more robust cortical thickness measurements. Left: Our finetuned model reduces dependence on image contrast significantly (top), while conserving sensitivity to synthetic atrophy (bottom). Right: For the finetuning procedure, MRIs with varying grey‐white contrast were synthesized using Deichmann's equations on T1 and PD maps. The segmentation ground truth for all synthetic images was generated by running FreeSurfer on the MRI with highest image contrast. Cortical thickness estimated with various methods was finally compared.

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. Brain morphometry can be derived reliably from contrast‐enhanced MRI using DL+DiReCT, a deep learning‐based morphometry tool. Making MR images acquired for clinical examinations with a contrast agent accessible for quantitative analysis is of interest for retrospective studies and potential future diagnostic support tools.

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. Does infection with SARS‐CoV‐2 in MS patients lead to a change in brain atrophy? MS is an ideal model disease to study the potential effects of infection with SARS‐CoV‐2 on brain atrophy, as longitudinal clinical and imaging data are abundant. In this proof‐of‐principle study, we found no evidence of accelerated atrophy of global gray matter volume but accelerated atrophy in the parahippocampal gyri.

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.