Öz, Gülin

Introduction Neurological post-acute sequelae of COVID-19 (neuroPASC) are associated with persistent cognitive dysfunction and quality-of-life decline. We aimed to identify clinical, behavioral and sociodemographic factors associated with neuroPASC symptom burden two years after COVID-19 among individuals without prior neurological disease. Methods In this prospective, observational study, individuals with neuroPASC ( n = 102) and controls without symptomatic COVID-19 ( n = 74), all without prior neurological, psychiatric, or post-viral conditions, were enrolled between February 2022 and June 2024 across five academic sites. An unsupervised algorithm identified clusters with differing self-reported neurological symptom burden within the neuroPASC group. Functional differences between clusters were evaluated using quality-of-life, neurological and cognitive evaluations. Demographics, behavioral history, comorbidities, and blood biomarkers were compared across clusters and controls. Multivariable logistic regression assessed predictors of neuroPASC severity, including demographics, body-mass-index, Charlson Comorbidity Index, Framingham Risk Score, pre-existing endocrine/metabolic and/or gastrointestinal/hepatobiliary conditions, COVID-19 vaccination prior to infection, hospitalization during acute infection, and cumulative alcohol use. Results Two clusters emerged based on neurological symptom burden, labeled “high-burden” and “low-burden” neuroPASC, reflecting differences in the number and frequency of symptoms. Both clusters had deficits in quality-of-life and cognitive function compared to controls, with greater impairment in high-burden than low-burden neuroPASC. The clusters did not differ by sex, education, tobacco and cannabis use, blood pressure, body-mass-index, HbA1C, days since infection, hospitalization during COVID-19, pre-COVID vaccination rate, antibody-positivity, inflammation, and neurodegeneration biomarkers. The high-burden cluster was older and exhibited higher comorbidity burden and greater cumulative alcohol use compared with the low-burden cluster and controls. Pre-existing endocrine/metabolic and gastrointestinal/hepatobiliary conditions were more common in high-burden (63%) than in low-burden neuroPASC (35%). After adjusting for clinical and demographic factors, these pre-existing conditions remained the only independent predictor of severity, conferring a 3.5-fold increase in the odds of high-burden versus low-burden neuroPASC. Discussion Older age, higher comorbidity burden, greater cumulative alcohol use, and endocrine/metabolic and gastrointestinal conditions, rather than acute COVID-19 severity, were observed in the high-burden neuroPASC cluster. After multivariable adjustment, only pre-existing endocrine/metabolic and/or gastrointestinal/hepatobiliary conditions remained independently associated with high-burden neuroPASC, conferring a 3.5-fold increase in odds and highlighting the need for targeted post-infection monitoring in at-risk patients.

The study assesses the relationship between thalamic proton-MR spectroscopy (1H-MRS) metabolites and thalamic 11C-ER176 translocator-protein positron emission tomography (TSPO-PET) standardized uptake value ratios (SUVR) to advance our understanding of thalamic involvement in multiple sclerosis (MS)-associated neurodegeneration and disability. In this prospective cross-sectional study, patients with MS (pwMS) and controls underwent 3T-MRI, 1H-MRS, and 11C-ER176-PET targeting the thalamus. MRI-derived thalamic volume was normalized by intracranial volume. 1H-MRS metabolites—N-acetylaspartate (NAA), glutamate (Glu), glutamine (Gln), total choline (tCho), and myo-inositol (mIns)—were normalized to total creatine (tCr). Clinical disability was evaluated using MS-specific tests of Expanded Disability Status Scale-EDSS and MS-functional composite-MSFC (including Paced Auditory Serial Addition Test-PASAT). Compared to controls (n = 30), pwMS (n = 21) exhibited smaller thalamic volume, higher thalamic 1H-MRS mIns/tCr (putative gliosis marker), and higher thalamic 11C-ER176-PET SUVR (glial density marker). In pwMS, higher thalamic mIns/tCr (r = −0.67) and tCho/tCr (r = −0.52) correlated with smaller thalamic volume. In pwMS, higher thalamic mIns/tCr correlated with higher thalamic 11C-ER176-PET SUVR (r = 0.48) and decreased cognitive function (PASAT, rho = −0.48). In controls, decreased thalamic NAA/tCr correlated with increased thalamic 11C-ER176-PET SUVR (r = −0.41). Thalamus, a core central nervous system relay, is affected early in MS disease course. Glial-mediated innate immune activation in the thalamus, evaluated by increased 1H-MRS mIns/tCr and 11C-ER176-PET SUVR, is associated with loss of thalamic volume and increased disability in pwMS. The multimodal imaging approach with 1H-MRS mIns/tCr and 11C-ER176-PET SUVR emerges as potential glial biomarkers, to better understand disease mechanisms and evaluate therapeutic interventions targeting glial activity in MS.

PurposeAdvanced MRS protocols improve data quality and reproducibility relative to vendor‐provided protocols; however, they are challenging to incorporate into the clinical workflow and require local MRS expertise for successful implementation. Here, we developed an automated advanced MRS acquisition protocol at 3T to facilitate acquisition of high‐quality spectroscopic data without local MRS expertise.MethodsFirst, a B0 shimming protocol was selected for automation by comparing 3 widely used B0 algorithms (2 vendor protocols and FAST(EST)MAP). Next, voxel‐based B0 and B1 calibrations were incorporated into the consensus‐recommended semi‐LASER sequence and combined with an automated VOI prescription tool, a recently developed method for automated voxel prescription. The efficiency of collecting single‐voxel data from a clinical cohort (N = 40) with the automated protocol (calibration time and fraction of usable datasets) was compared with the nonautomated semi‐LASER protocol (N = 35) whereby all prescan calibrations were executed manually in the academic hospital setting with rotating MR technologists in the neuroradiology unit.ResultsA multi‐iteration FAST(EST)MAP protocol resulted in narrower water linewidths than vendor’s B0 shim protocols for data acquired from 6 brain locations (p < 1e‐5) and was selected for automation. The automated B0 and B1 calibrations resulted in a time saving of ~4.5 minutes per voxel relative to the same advanced protocol executed manually. All spectra acquired with the automated protocol were usable, whereas only 86% of those collected with the manual protocol were usable and spectral quality was more variable.ConclusionThe plug‐and‐play advanced MRS protocol allows automated acquisition of high‐quality MRS data with high success rate and consistency on a clinical 3T platform.

In vivo MRS is a non‐invasive measurement technique used not only in humans, but also in animal models using high‐field magnets. MRS enables the measurement of metabolite concentrations as well as metabolic rates and their modifications in healthy animals and disease models. Such data open the way to a deeper understanding of the underlying biochemistry, related disturbances and mechanisms taking place during or prior to symptoms and tissue changes. In this work, we focus on the main preclinical 1H, 31P and 13C MRS approaches to study brain metabolism in rodent models, with the aim of providing general experts’ consensus recommendations (animal models, anesthesia, data acquisition protocols). An overview of the main practical differences in preclinical compared with clinical MRS studies is presented, as well as the additional biochemical information that can be obtained in animal models in terms of metabolite concentrations and metabolic flux measurements. The properties of high‐field preclinical MRS and the technical limitations are also described.

Abstract The semi‐adiabatic localization by adiabatic selective refocusing (sLASER) sequence provides single‐shot full intensity signal with clean localization and minimal chemical shift displacement error and was recommended by the international MRS Consensus Group as the preferred localization sequence at high‐ and ultra‐high fields. Across‐vendor standardization of the sLASER sequence at 3 tesla has been challenging due to the B 1 requirements of the adiabatic inversion pulses and maximum B 1 limitations on some platforms. The aims of this study were to design a short‐echo sLASER sequence that can be executed within a B 1 limit of 15 μT by taking advantage of gradient‐modulated RF pulses, to implement it on three major platforms and to evaluate the between‐vendor reproducibility of its perfomance with phantoms and in vivo. In addition, voxel‐based first and second order B 0 shimming and voxel‐based B 1 adjustments of RF pulses were implemented on all platforms. Amongst the gradient‐modulated pulses considered (GOIA, FOCI and BASSI), GOIA‐WURST was identified as the optimal refocusing pulse that provides good voxel selection within a maximum B 1 of 15 μT based on localization efficiency, contamination error and ripple artifacts of the inversion profile. An sLASER sequence (30 ms echo time) that incorporates VAPOR water suppression and 3D outer volume suppression was implemented with identical parameters (RF pulse type and duration, spoiler gradients and inter‐pulse delays) on GE, Philips and Siemens and generated identical spectra on the GE ‘Braino’ phantom between vendors. High‐quality spectra were consistently obtained in multiple regions (cerebellar white matter, hippocampus, pons, posterior cingulate cortex and putamen) in the human brain across vendors (5 subjects scanned per vendor per region; mean signal‐to‐noise ratio > 33; mean water linewidth between 6.5 Hz to 11.4 Hz). The harmonized sLASER protocol is expected to produce high reproducibility of MRS across sites thereby allowing large multi‐site studies with clinical cohorts.

Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good‐quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi‐adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.

PurposeTo develop a fast and automated volume‐of‐interest (VOI) prescription pipeline (AutoVOI) for single‐voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter‐ and intra‐subject consistency of VOI prescription.MethodsAutoVOI was designed to transfer pre‐defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T1‐weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem.ResultsThe AutoVOI pipeline includes skull stripping, non‐linear registration of the atlas to the subject's brain, and computation of the VOI coordinates and angulations using a minimum oriented bounding box algorithm. When compared against manual prescription, AutoVOI showed higher intra‐ and inter‐subject spatial consistency, as quantified by generalized Dice coefficients (GDC), lower intra‐ and inter‐subject variability in tissue composition (gray matter, white matter, and cerebrospinal fluid) and higher or equal accuracy, as quantified by GDC of prescribed VOI with targeted tissues. High quality spectra were obtained on Siemens and Philips 3T systems from 6 automatically prescribed VOIs by the tool.ConclusionRobust automatic VOI prescription is feasible and can help facilitate clinical adoption of MRS by avoiding operator dependence of manual selection.

ABSTRACTBACKGROUND AND PURPOSEGlutamate levels may be informative about the declining neuronal health in the central nervous system. We used an advanced proton MR spectroscopy (1H‐MRS) protocol composed of semi‐localization by adiabatic selective refocusing (sLASER) localization and FAST(EST)MAP shimming for detection of alterations in brain glutamate concentrations in patients with amnestic mild cognitive impairment.METHODSParticipants with amnestic mild cognitive impairment (n= 14; median age = 80) and age‐ and sex‐matched clinically normal controls (n= 32; median age = 79) from the population‐based Mayo Clinic Study of Aging were recruited prospectively to the 3T single‐voxel1H‐MRS study that examined metabolite changes in the posterior cingulate gyri. To be included, controls had to have low β‐amyloid load on [11C] Pittsburgh Compound B (PiB)‐PET (standard uptake value ratio; SUVr < 1.42) and patients with amnestic mild cognitive impairment had to have high β‐amyloid load (SUVr ≥ 1.42).RESULTSGlutamate concentration and the glutamate/myo‐inositol ratio were lower in patients with amnestic mild cognitive impairment than clinically normal controls (P< .05). Higher global cortical PiB‐PET SUVr correlated with lower glutamate/myo‐inositol (r= –.3,P= .04).CONCLUSIONSThe advanced sLASER with FAST(EST)MAP shimming is a promising protocol for identifying glutamate alterations. Advanced1H‐MRS protocols may add to the understanding of early Alzheimer's disease pathophysiology through detection of glutamate concentration in posterior cingulate gyri of individuals with amnestic mild cognitive impairment.

PurposeTo investigate the utility of an advanced magnetic resonance spectroscopy (MRS) protocol in the clinical setting, and to compare the localization accuracy, spectral quality, and quantification repeatability between this advanced and the conventional vendor‐provided MRS protocol on a clinical 3T platform.MethodsProton spectra were measured from the posterior cingulate cortices in 30 healthy elderly subjects by clinical MR technologists using a vendor‐provided (point resolved spectroscopy with advanced 3D gradient‐echo B0 shimming) and an advanced (semi‐LASER with FAST(EST)MAP shimming) protocol, in random order. Spectra were quantified with LCModel using standard pipelines for the clinical and research settings, respectively.ResultsThe advanced protocol outperformed the vendor‐provided protocol in localization accuracy (chemical‐shift‐displacement error: 2.0%/ppm, semi‐LASER versus 11.6%/ppm, point resolved spectroscopy), spectral quality (water linewidth: 6.1 ± 1.8 Hz, FAST(EST)MAP versus 10.5 ± 3.7 Hz, 3D gradient echo; P < 7e‐6; residual water: 0.08 ± 0.12%, VAPOR versus 0.45 ± 0.50%, WET; P < 2e‐5) and within‐session repeatability of metabolite concentrations, particularly of low signal‐to‐noise ratio data with two to eight averages (test‐retest coefficients of variance of metabolite concentrations, P < 0.01). Concentrations of J‐coupled metabolites such as γ‐aminobutyric acid and glutamate were biased when using the default pipeline with simulated macromolecules.ConclusionsThe quality of MRS data can be improved using advanced acquisition and analysis protocols on standard 3T hardware in the clinical setting, which can facilitate robust applications in central nervous system diseases. Magn Reson Med 79:1241–1250, 2018. © 2017 International Society for Magnetic Resonance in Medicine.