Port, John D

Background: The potential long-term effects of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) infection on the brain structure have not yet been fully elucidated. Even though existing studies have reported structural changes in the post-COVID-19 period, the results remain highly inconsistent and controversial. As such, identifying an imaging biomarker for post-COVID brains is still under investigation. This review aims to comprehensively summarize the structural MRI (sMRI) studies that focus on volumetric brain changes at least two weeks following COVID-19 infection. Methods: A systematic literature search was conducted on PubMed, SCOPUS, Web of Science, EMBASE, and Google Scholar up to 9 September 2025. Studies that utilized sMRI to assess volumetric brain changes post-COVID at greater than two weeks following infection were included. Exclusion criteria encompassed research involving pediatric or adolescent populations and imaging modalities other than sMRI. Preprints, reviews, case reports, case series and post-mortem studies were also excluded. Results: Forty-one studies satisfied the inclusion criteria and consisted of 2895 patients and 1729 healthy controls. Despite the wide variability in image acquisition protocols, data processing methods, and comorbidities between studies, multiple studies reported statistically significant volumetric reductions in the hippocampus, amygdala, thalamus, basal ganglia, nucleus accumbens and the cerebellum months to years after infection, especially in older hospitalized patients with severe COVID-19. Conclusions: The emerging literature reports long-term volume changes across various brain regions in individuals previously infected with COVID-19; however, the evidence is inconsistent. Specific imaging biomarkers following exposure to SARS-CoV-2 infection and the underlying mechanisms of these changes are yet to be identified. Future studies with harmonized imaging protocols, longitudinal designs, and integrated biomarker and clinical data are needed to define robust biomarkers and elucidate the pathophysiology of these findings.

Abstract Insulin resistance (IR) is a modifiable risk factor for dementia, yet its effects on brain metabolism and function remain unclear. In older adults, greater IR was associated with reduced cerebral glucose uptake (indicating impaired mitochondrial metabolism), atrophy, and weakened connectivity between brain regions critical for cognition. In neuron-specific insulin receptor knockout mice, brain IR produced deficits in hippocampal- and prefrontal-dependent tasks accompanied by reduced brain mitochondrial ATP and elevated reactive oxygen species. To evaluate reversibility of IR-induced brain deficits, forty older adults with IR were randomized to 40-weeks of metformin or placebo. Metformin improved insulin sensitivity, increased brain glucose uptake, strengthened cognitive network connectivity, and preserved whole-brain and regional volumes implicated in decision-making and learning. Metformin also improved processing speed and working memory. Collectively, these findings highlight IR as a driver of brain metabolism and support the concept that insulin sensitization can prevent neurobiological deficits in older people with IR.

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.

Background: Spinal cord (SC) atrophy is a key imaging biomarker of progressive multiple sclerosis (MS). Progressive MS is more common in men and postmenopausal women. Objective: Investigate the impact of sex and menopause on SC measurements in persons with MS (pwMS). Methods: In pwMS and age- and sex-matched controls, upper cervical SC area from brain MRI (UCC brain ) was obtained. Impact of sex and menopause on UCC brain (adjusted for total intracranial volume) and its association with progression and disability, including MS functional composite (MSFC), were investigated. Results: UCC brain was smaller in pwMS ( n = 118, 51.4 ± 5.3 mm 2 ) than controls ( n = 118, 54.2 ± 4.4 mm 2 , p < 0.001) and inversely correlated with older age in pwMS ( r = −0.24, p = 0.010) but not in controls ( r = −0.025, p = 0.786). In 173 pwMS (413 brain MRIs), UCC brain was smaller in men (49.5 ± 5.9 mm 2 ) than women (51.6 ± 5.5 mm 2 , p = 0.001), postmenopausal women (49.4 ± 5.6 mm 2 ) than premenopausal women (52.9 ± 4.1 mm 2 , p < 0.001), and progressive (47.5 ± 5.6 mm 2 ) than relapsing MS (52.1 ± 5.2 mm 2 , p < 0.001). UCC brain also correlated with disease duration ( r = −0.39, p < 0.001), 9-hole peg test ( r = −0.26, p = 0.005), and severe ambulatory disability (Expanded Disability Status Scale ⩾6) ( r = −0.27, p < 0.001). Conclusion: UCC brain , a biomarker of progressive MS, is inversely associated with age, disease duration, male sex, and menopause, highlighting the potential impact of sex and hormones on neurodegeneration in MS.

Abstract This study aimed to evaluate the effect of intrathecal (IT) recombinant human arylsulfatase A (rhASA) on magnetic resonance imaging (MRI)‐assessed brain tissue changes in children with metachromatic leukodystrophy (MLD). In total, 510 MRI scans were collected from 12 intravenous (IV) rhASA‐treated children with MLD, 24 IT rhASA‐treated children with MLD, 32 children with untreated MLD, and 156 normally developing children. Linear mixed models were fitted to analyze the time courses of gray matter (GM) volume and fractional anisotropy (FA) in the posterior limb of the internal capsule. Time courses for demyelination load and FA in the centrum semiovale were visualized using locally estimated scatterplot smoothing regression curves. All assessed imaging parameters demonstrated structural evidence of neurological deterioration in children with MLD. GM volume was significantly lower at follow‐up (median duration, 104 weeks) in IV rhASA‐treated versus IT rhASA‐treated children. GM volume decline over time was steeper in children receiving low‐dose (10 or 30 mg) versus high‐dose (100 mg) IT rhASA. Similar effects were observed for demyelination. FA in the posterior limb of the internal capsule showed a higher trend over time in IT rhASA‐treated versus children with untreated MLD, but FA parameters were not different between children receiving the low doses versus those receiving the high dose. GM volume in IT rhASA‐treated children showed a strong positive correlation with 88‐item Gross Motor Function Measure score over time. In some children with MLD, IT administration of high‐dose rhASA may delay neurological deterioration (assessed using MRI), offering potential therapeutic benefit.

High-frequency repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) shows promise as a treatment for treatment-resistant depression in adolescents. Conventional rTMS coil placement strategies include the 5 cm, the Beam F3, and the magnetic resonance imaging (MRI) neuronavigation methods. The purpose of this study was to use electric field (E-field) models to compare the three targeting approaches to a computational E-field optimization coil placement method in depressed adolescents. Ten depressed adolescents (4 females, age: 15.9±1.1) participated in an open-label rTMS treatment study and were offered MRI-guided rTMS five times per week over 6–8 weeks. Head models were generated based on individual MRI images, and E-fields were simulated for the four targeting approaches. Results showed a significant difference in the induced E-fields at the L-DLPFC between the four targeting methods (χ2=24.7, p<0.001). Post hoc pairwise comparisons showed that there was a significant difference between any two of the targeting methods (Holm adjusted p<0.05), with the 5 cm rule producing the weakest E-field (46.0±17.4V/m), followed by the F3 method (87.4±35.4V/m), followed by MRI-guided (112.1±14.6V/m), and followed by the computational approach (130.1±18.1V/m). Variance analysis showed that there was a significant difference in sample variance between the groups (K2=8.0, p<0.05), with F3 having the largest variance. Participants who completed the full course of treatment had median E-fields correlated with depression symptom improvement (r=−0.77, p<0.05). E-field models revealed limitations of scalp-based methods compared to MRI guidance, suggesting computational optimization could enhance dose delivery to the target.