Background: Enthesitis-related arthritis (ERA), a subset of juvenile idiopathic arthritis (JIA), is characterized by frequent involvement of the sacroiliac (SI) joints. Objective: The aim of this study was to assess the effectiveness of zero echo time (ZTE) magnetic resonance imaging (MRI) in identifying structural lesions in patients with ERA. Conventional MRI pulse sequences often struggle to adequately visualize osseous and calcified tissues. Materials and methods: All MRI examinations were conducted using a 1.5-T (T) scanner. The MRI protocol included standard sequences such as fat-suppressed axial T2-weighted, axial T1-weighted, coronal short tau inversion recovery (STIR), and axial T2-weighted sequences. In addition to conventional MRI, a ZTE sequence was employed. Low-dose computed tomography (CT) served as the reference standard and was performed using a 640-multislice CT device. Structural lesions, including erosions, sclerosis, and changes in joint space, were compared between imaging modalities. Results: A total of 20 patients were included in the study (12 boys, 8 girls), with a median age at diagnosis of 14 years. ZTE-MRI demonstrated similar sensitivity to low-dose CT in detecting erosion (7 vs 8, P = 0.707). The interclass correlation coefficient (ICC) between low-dose CT and ZTE-MRI was 0.993 (P < 0.001), indicating excellent agreement. Moreover, ZTE-MRI showed strong agreement with low-dose CT in detecting sclerosis (ICC = 0.954, P < 0.001) and changes in joint space (ICC = 0.998, P < 0.001). Conclusions: Zero echo time imaging shows promise in providing sacroiliac joint visualization comparable to low-dose CT scans, thereby improving the detection of subtle erosion and sclerosis in these joints. Graphical

Background/Objectives: Assessing structural damage in pediatric sacroiliitis is challenging, necessitating radiation-free alternatives to computed tomography (CT). This study evaluated the diagnostic performance of advanced MRI sequences—3D-MENSA (Multi-Echo in Steady-State Acquisition), 3D-MERGE (Multiple-Echo Recombined Gradient Echo), and Zero Echo Time (ZTE)—against conventional T1-weighted sequences for detecting structural lesions. Low-dose computed tomography (LDCT) served as the reference standard. A secondary objective was to qualitatively assess the visibility of active inflammatory lesions and fat metaplasia. Methods: In this cross-sectional study, 23 pediatric patients with enthesitis-related arthritis (ERA) were included. To adhere strictly to radiation safety principles, the study used pre-existing ldCT datasets from a clinical cohort as the reference standard. No new CT scans were performed for this study. Structural lesions (erosions, sclerosis, and joint-space changes) were independently scored by two blinded radiologists. Interobserver agreement was assessed using intraclass correlation coefficients (ICC). Results: Advanced sequences (ZTE, 3D-MENSA, 3D-MERGE) demonstrated high agreement with ldCT for erosion detection (ICC range: 0.924–0.998) and significantly outperformed conventional T1-weighted MRI (ICC: 0.707). 3D-MENSA provided distinct contrast, effectively differentiating the ligamentous component of the sacroiliac joint from both the synovial component and the adjacent bone cortex. Qualitatively, 3D-MENSA also identified bone marrow edema and fat metaplasia, which cannot be visualized by ZTE or ldCT. Conclusions: 3D-MENSA and 3D-MERGE enable comprehensive evaluation of structural sacroiliitis lesions in pediatric patients with diagnostic accuracy comparable to ldCT. Specifically, 3D-MENSA demonstrates the potential to detect both active and chronic lesions in a single, rapid, radiation-free acquisition. These findings suggest that it should be considered for routine pediatric imaging protocols.

Seronegative autoimmune encephalitis (SNAE) is an increasingly recognized entity in pediatric neurology, yet quantitative neuroimaging data remain scarce. This study aimed to evaluate regional brain volumetric differences between children diagnosed with SNAE and age- and sex-matched healthy controls using automated MRI volumetry. Fifteen children with SNAE (median age 12 years; 9 males, 6 females) and 45 age- and sex-matched healthy controls were enrolled. Three-dimensional T1-weighted MRI data were processed using the volBrain automated brain volumetry pipeline. Patients with SNAE demonstrated significantly reduced volumes in whole brain (p = 0.005), grey matter (p = 0.001), thalamus (p = 0.001), putamen (p < 0.001), caudate (p = 0.002), pallidum (p < 0.001), hippocampus (p = 0.027), and cerebellum (p < 0.001) compared with healthy controls. White matter, amygdala, and brainstem volumes did not differ significantly. ROC analysis revealed pallidum volume as the best discriminator (AUC = 0.889), followed by putamen (AUC = 0.884) and cerebellum (AUC = 0.810). In multivariate logistic regression after LASSO feature selection, cerebellum volume was the sole independent predictor (adjusted OR = 12.14, p = 0.030). Children with SNAE exhibit widespread subcortical and cerebellar volume loss. Pallidum volume demonstrates the highest discriminative ability and may serve as a potential quantitative imaging biomarker. These findings suggest that SNAE leads to significant structural brain changes even in the absence of identifiable autoantibodies.

Background/Objectives: This study evaluated automated magnetic resonance imaging (MRI) volumetry for characterizing structural brain changes in Alzheimer’s disease (AD), mild cognitive impairment (MCI), and cognitively healthy controls (HC), and examined its association with cognitive performance. Methods: This retrospective observational study included consecutively enrolled individuals aged ≥65 years. AD dementia and MCI were diagnosed according to the 2011 National Institute on Aging–Alzheimer’s Association (NIA-AA) clinical criteria. Automated volumetric analysis of structural MRI was used to obtain the total intracranial volume-normalized cortical and subcortical volumes, cerebrospinal fluid (CSF) compartments, and hemispheric asymmetry indices. Between-group comparisons were corrected using the Benjamini–Hochberg false discovery rate. Prespecified volumetric markers were evaluated using receiver operating characteristic analysis and internally validated logistic regression models. Results: The study included 102 participants (34 per group). Compared with HC, the AD group showed lower total cerebrum, right hippocampal, and anterior cingulate gyrus (ACgG) volumes and higher CSF volumes. Compared with MCI, the AD group exhibited lower thalamic and caudate volumes. CSF volume showed the highest individual discriminative performance for differentiating AD from HC (AUC = 0.837), whereas the combined hippocampal–ACgG–CSF model showed the best performance for differentiating MCI from HC (AUC = 0.826). After adjustment for diagnostic group, cognitive performance remained positively associated with hippocampal volume and negatively with CSF and lateral ventricular volumes. Conclusions: Automated MRI volumetry may support the quantitative assessment of neurodegeneration in clinically defined AD and MCI. Combined volumetric markers improved discrimination between MCI and HC, although these findings require external validation in larger, longitudinal, biomarker-characterized cohorts.