Search Results (90)

Background and Objectives: The objective of this research is to make a comparative evaluation of the correlation between the volumetric examination of subcortical cerebral regions and white matter hyperintensities classified according to the Fazekas scoring system. Materials and Methods: A total of 236 cases with cranial MRI studies were retrospectively analyzed. This study included patients aged over 45 years who had white matter hyperintensities and who did not have a prior stroke diagnosis. White matter hyperintensities were evaluated in axial FLAIR images according to Fazekas’s grading scale. Patients with Fazekas 0 and 1 were grouped in group 1 and the patients with Fazekas 2 and 3 were grouped in group 2. MRI data processing and subcortical volumetric analyses were performed using the volBrain MRI brain volumetry system. Results: There were statistically significant differences between groups 1 and 2 in terms of cerebrospinal fluid total brain white and gray matter (p < 0.001), total brain white and gray matter (p = 0.009), total cerebrum (p < 0.001), accumbens (p < 0.001), thalamus (p < 0.001), frontal lobe (p < 0.001), parietal lobe (p < 0.001), and lateral ventricle (p < 0.001) volumes. Conclusions: Our study finds a strong link between white matter hyperintensity burden and brain atrophy. This includes volume reductions in total brain white and gray matter, frontal and parietal lobe atrophy, increased cerebrospinal fluid (CSF), and atrophy in specific brain regions such as the accumbens and thalamus. Full article

Background: Huntington’s disease (HD) is a neurodegenerative disorder caused by a CAG repeat expansion in the HTT gene, with a rare juvenile-onset form (JoHD) marked by early, rigid motor symptoms. This study examined cortical and subcortical resting-state connectivity in JoHD, hypothesizing preserved cortical networks but altered striatal connectivity, in line with early subcortical atrophy despite relatively spared cortical volume. Methods: Participants included children and young adults with clinician-confirmed Juvenile-Onset Huntington’s Disease (JoHD; n = 19) and gene-non-expanded (GNE) controls (n = 64), both drawn from longitudinal studies at the University of Iowa. Resting-state functional MRI scans were analyzed to assess canonical cortical network and striatal connectivity, and linear mixed-effects models tested group differences and associations with motor, cognitive, and clinical outcomes. Results: JoHD participants showed reduced connectivity within the left somatomotor network and striatal circuits, despite largely typical cortical network connectivity. Striatal connectivity was associated with disease burden and cognitive ability, while left somatomotor connectivity was unrelated to clinical outcomes. Conclusions: These findings support the hypothesis of antagonistic pleiotropy in JoHD, where early neural advantages—such as relatively preserved or possibly enhanced cortical function—may contribute to later striatal vulnerability and degeneration. The observed left-lateralized somatomotor hypoconnectivity aligns with prior volumetric and gene expression research, highlighting the role of excitotoxic glutamatergic input and the selective vulnerability of high-functioning circuits in disease progression. Full article

Introduction: Previous neuroimaging studies have reported structural brain alterations and local network hyperexcitability in terms of increased slow-wave electroencephalography (EEG) activity in patients with borderline personality disorder (BPD). In particular, intermittent rhythmic delta and theta activity (IRDA/IRTA) has drawn attention in mental health contexts due to its links with metabolic imbalances, neuronal stress, and emotional dysregulation—processes that are highly pertinent to BPD. These functional disturbances may be reflected in corresponding structural brain changes. The current study investigated cortical thickness and subcortical volumes in BPD and examined their associations with IRDA/IRTA events per minute, symptom severity, and neuropsychological measures. Methods: Seventy female BPD patients and 36 age-matched female healthy controls (HC) were included (for clinical EEG comparisons even 72 patients were available). IRDA/IRTA rates were assessed using an automatic independent component analyses (ICA) approach. T1-weighted MRI data were obtained using a MAGNETOM Prisma 3T system and analyzed with FreeSurfer (version 7.2) for subcortical structures and CAT12 for cortical thickness and global volume measurements. Psychometric assessments included questionnaires such as Borderline Symptom List (BSL-23) and Inventory of Personality Organization (IPO). Neuropsychological performance was evaluated with the Test for Attentional Performance (TAP), Culture Fair Intelligence Test (CFT-20-R), and Verbal Learning and Memory Test (VLMT). Results: Between-group comparisons exhibited no significant increase in IRDA/IRTA rates or structural abnormalities between the BPD and HC group. However, within the BPD group, cortical thickness of the right isthmus of the cingulate gyrus negatively correlated with the IRDA/IRTA difference (after minus before hyperventilation, HV; p < 0.001). Furthermore, BPD symptom severity (BSL-23) and IPO scores positively correlated with the thickness of the right rostral anterior cingulate cortex (p < 0.001), and IPO scores were associated with the thickness of the right temporal pole (p < 0.001). Intrinsic alertness (TAP) significantly correlated with relative cerebellar volume (p = 0.01). Discussion: While no group-level structural abnormalities were observed, correlations between EEG slowing, BPD symptom severity, and alertness with cortical thickness and/or subcortical volumes suggest a potential role of the anterior cingulate cortex, temporal pole, and cerebellum in emotion regulation and cognitive functioning in BPD. Future research employing multimodal EEG-MRI approaches may provide deeper insights into the neural mechanisms underlying BPD and guide personalized therapeutic strategies. Full article

Chemotherapy-related cognitive impairment termed «chemobrain» is a prevalent complication in breast cancer survivors that requires early detection for the development of novel therapeutic approaches. Magnetic resonance voxel morphometry (MR morphometry), due to its high sensitivity, might be employed for the evaluation of the early changes in the volumes of brain structures in order to explore the «chemobrain» condition. Methods: The open, prospective, single-center study enrolled 86 breast cancer survivors (43.3 ± 4.4 years) and age-matched 28 healthy female volunteers (44.0 ± 5.68). Conventional MR sequences (T1- and T2-weighted, TIRM, DWI, MPRAGE) were obtained in three mutually perpendicular planes to exclude an organ pathology of the brain. Additionally, the MPRAGE sequence was performed for subsequent MR morphometry of the volume of brain structures using the open VolBrain program. The evaluation was performed at two follow-up visits 6 months and 3 years after the completion of BC treatment. Results: According to the MR morphometry, breast cancer survivors presented with significantly decreased volumes of brain structures (including total brain volume, cerebellum volume, subcortical gray matter, etc.) as compared to healthy volunteers. Evaluation over the follow-up period of 3 years did not show the restoration of brain volume structures. Conclusions: The data obtained employing MR morphometry revealed significant reductions (that were not detected on the conventional MR sequences) in both gray and white matter in breast cancer survivors following chemotherapy. This comprehensive analysis indicated the utility of MR morphometry in detecting subtle yet statistically significant neuroanatomical changes associated with cognitive and motor impairments in patients, which can in turn provide valuable insights into the extent of structural brain alterations, helping to identify specific regions that are most affected by treatment. Full article

Background/Objectives: Chronotypes significantly influence sleep quality, daily performance, and overall activity levels. Although there is growing evidence indicating that individuals with a late chronotype are more likely to experience cognitive decline, the specific neural mechanisms that contribute to this risk remain unclear. This study aims to explore the relationship between morning and evening preferences and the volumes of subcortical structures in a young, healthy population. Methods: A total of 123 participants (80 females), aged between 18 and 35 years, were recruited. They underwent MRI scans and completed several self-reported assessments, including the morningness–eveningness scale of the Chronotype Questionnaire (ChQ-ME), the amplitude scale of the Chronotype Questionnaire (ChQ-AM), the Epworth Sleepiness Scale (ESS), and the Pittsburgh Sleep Quality Index (PSQI). Participants were classified into early chronotype (EC) and late chronotype (LC) groups based on their ChQ-ME scores. High-resolution T1-weighted imaging was utilized to analyze the volumes of subcortical structures and hippocampal subfields. Results: The volumetric analysis indicated that the LC group showed significant reductions in the right Caudate (p = 0.03) and the left SR-SL-SM (p = 0.03) compared to the EC group. Additionally, a notable leftward hemispheric laterality of the Subiculum (p = 0.048) was observed in the EC group relative to the LC group. Furthermore, the ChQ-AM revealed significant positive (r = 0.23) and negative (r = −0.19) correlations with the volumes of the left thalamus and right amygdala, respectively. The PSQI demonstrated a significant negative correlation (r = −0.21) with the right SR-SL-SM, while the ESS indicated a significant positive correlation (r = 0.24) with the left SR-SL-SM. Multiple regression analysis indicated that variations in daytime sleepiness are linked to the change of the left SR-SL-SM volume. Conclusions: Overall, the findings suggest that chronotype preferences are associated with the changes in the volumes of subcortical structures and hippocampal subfields and highlight the role of chronotypes in the neural mechanisms of these brain structures. Full article

Background/Objectives: Low-grade inflammation in the form of microglial activation may be involved in neurodegenerative and vascular dementias. Subcortical small-vessel disease (SSVD) is the main form of vascular dementia, associated with brain barrier dysfunction and endothelial and monocyte activation. IL-6 and IL-17A are known proinflammatory cytokines that contribute to the disruption of blood–brain barrier integrity and microvascular dysfunction, features that are central to SSVD pathophysiological pathways. We herein compared cerebrospinal fluid (CSF) IL-6 and IL-17A concentrations in SSVD and AD patients as well as control subjects and examined the potential associations among IL-6 and IL-17A levels with cognitive and ΜRΙ changes. The albumin quotient (Qalb) was also calculated. Methods: CSF IL-6 and IL-17A (18 SSVD, 17 AD, and 12 healthy controls) were measured with solid-phase sandwich ELISAs, while albumin levels were measured by immunonephelometry. MMSE, FAB, and the CLOX tests were used for cognitive assessment and MRI was used for atrophy and white matter hyperintensities. Results: Significantly elevated CSF levels of Qalb and IL-6 were found in SSVD patients compared to both AD (p = 0.02) and controls (p = 0.002), respectively. Moreover, CSF IL-6 levels displayed a significant inverse correlation with CLOX2 scores (r = −0.641, p = 0.02), as well as a positive correlation with the total normalized CSF volume (r = 0.7, p = 0.01). CSF IL-17A levels were found to be reduced in SSVD patients, compared to controls and AD patients (p < 0.0001 and p = 0.002, respectively). The IL-6/IL-17A ratio with a cut-off value > 1.004 displayed a sensitivity of 83.33% (95%CI; 60.78% to 94.16%) and a specificity of 68.97% (95%CI; 50.77% to 82.72%) for the discrimination of SSVD from AD patients and controls. Conclusions: In the present pilot single-center study, we found increased CSF IL-6 and IL-6/IL-17A ratio levels in SSVD patients that correlated with reduced scores in the CLOX2 test and increased CSF volume. These preliminary findings deserve further evaluation in larger cohorts in order to elucidate their potential as surrogate biomarkers for the discrimination of SSVD from AD pathology. Full article

Background and Objectives: Hemiplegic or unilateral cerebral palsy (UCP) is primarily characterized by motor impairment, mainly affecting the upper limb. Research has centered on factors influencing the varying degrees of motor deficit in UCP, using neuroscience advancements for in vivo exploration of brain structure (morphometry) and cortical reorganization (functional magnetic resonance imaging (fMRI)). This study aims to evaluate functional activation in the motor cortex in UCP and to explore how lesion characteristics and timing affect neuroplasticity and motor function. Materials and Methods: Between 2017 and 2021, structural and functional MRIs were performed on 44 UCP patients (mean age 15.5 years, 24 males, 20 females), all with Manual Ability Classification System (MACS) levels I-III and Intelligence Quotient (IQ) ≥ 50. The lesion characteristics of size, type, and time of occurrence (ante-, peri-, or early postnatal) were analyzed. An association was sought between the characteristics of the lesion and the degree of motor deficit of the upper limb, as determined by the MACS level. fMRI assessed cortical activation during a finger-tapping task for the paretic hand and compared activation patterns based on lesion characteristics. Results: Six lesion types were identified, with arterial ischemic stroke being the most common and largest in volume. Lesion size strongly correlated with patients’ MACS levels, while lesion type and timing showed no association with the severity of motor impairment classified by MACS. Motor reorganization varied, with activation occurring ipsi-, contra-, or bilaterally to the affected hand, depending on lesion size and type. Smaller, subcortical lesions primarily showed ipsilesional activation, while larger, cortical lesions did not exhibit a specific group activation, possibly due to varying individual reorganization. No association was found between the lesion timing and the reorganization model. Conclusions: Motor functional reorganization in UCP is closely linked to lesion characteristics, with smaller, subcortical lesions favoring typical organization in the contralateral motor cortex. The timing of the lesion does not significantly affect cortical reorganization. Lesion size was a key determinant of motor function, whereas lesion type (e.g., ischemic stroke) and timing (early vs. late occurrence) were less critical for predicting functional outcome. Full article

Quantum dots (QDs) have emerged as promising tools in advancing multiphoton microscopy (MPM) for deep brain imaging, addressing long-standing challenges in resolution, penetration depth, and light–tissue interactions. MPM, which relies on nonlinear photon absorption, enables fluorescence imaging within defined volumes, effectively reducing background noise and photobleaching. However, achieving greater depths remains limited by light scattering and absorption, compounded by the need for balanced laser power to avoid tissue damage. QDs, nanoscale semiconductor particles with unique optical properties, offer substantial advantages over traditional fluorophores, including high quantum yields, large absorption cross-sections, superior photostability, and tunable emission spectra. These properties enhance signal to background ratio at increased depths and reduce scattering effects, making QDs ideal for imaging subcortical regions like the hippocampus without extensive microscope modifications. Studies have demonstrated the capability of QDs to achieve imaging depths up to 2100 μm, far exceeding that of conventional fluorophores. Beyond structural imaging, QDs facilitate functional imaging applications, such as high-resolution tracking of hemodynamic responses and neural activity, supporting investigations of neuronal dynamics and blood flow in vivo. Their stability enables long-term, targeted drug delivery and photodynamic therapy, presenting potential therapeutic applications in treating brain tumors, Alzheimer’s disease, and traumatic brain injury. This review highlights the impact of QDs on MPM, their effectiveness in overcoming light attenuation in deep tissue, and their expanding role in diagnosing and treating neurological disorders, positioning them as transformative agents for both brain imaging and intervention. Full article

Neurodegenerative diseases (NDs), such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early detection is crucial for effective intervention strategies, this study investigates whether the structural analysis of selected brain regions, including volumes and their spatial relationships obtained from regular T1-weighted MRI scans (N = 168, PPMI database), can model stages of PD using standard machine learning (ML) techniques. Thus, diverse ML models, including Logistic Regression, Random Forest, Support Vector Classifier, and Rough Sets, were trained and evaluated. Models used volumes, Euclidean, and Cosine distances of subcortical brain structures relative to the thalamus to differentiate among control (HC), prodromal (PR), and PD groups. Based on three separate experiments, the Logistic Regression approach was optimal, providing low feature complexity and strong predictive performance (accuracy: 85%, precision: 88%, recall: 85%) in PD-stage recognition. Using interpretable metrics, such as the volume- and centroid-based spatial distances, models achieved high diagnostic accuracy, presenting a promising framework for early-stage PD identification based on MRI scans. Full article

Background: Perinatal asphyxia is a major cause of neonatal morbidity and mortality, often resulting in hypoxic-ischemic encephalopathy (HIE) with long-term neurodevelopmental impairments. While therapeutic hypothermia has emerged as a promising intervention to reduce brain damage, its specific impact on key brain structures and long-term neurodevelopmental outcomes remains underexplored. This study aims to evaluate the effects of therapeutic hypothermia on brain volumetry, cortical thickness, and neurodevelopment in term neonates with perinatal asphyxia. Methods: This prospective cohort study enrolled 34 term neonates with perinatal asphyxia, with 12 receiving therapeutic hypothermia and 22 serving as controls without hypothermia. Brain MRI data were analyzed using Infant FreeSurfer to quantify the basal ganglia volumes, gray matter, white matter, cerebellum, cortical gyri, and cortical thickness. Neurodevelopmental outcomes were assessed at 18 and 24 months, using the Bayley Scale III, evaluating the motor, cognitive, and language domains. Genetic analyses, including next-generation sequencing (NGS) and microarray testing, were performed to investigate potential neurodevelopmental markers and confounding factors. Results: Neonates treated with hypothermia demonstrated significantly larger gray and white matter volumes, with a 3.7-fold increase in gray matter (p = 0.025) and a 2.2-fold increase in white matter (p = 0.025). Hippocampal volume increased 3.4-fold (p = 0.032) in the hypothermia group. However, no significant volumetric differences were observed in the cerebellum, thalamus, or other subcortical regions. Moderate correlations were found between white matter volume and cognitive outcomes, but these associations were not statistically significant. Conclusions: Therapeutic hypothermia appears to have region-specific neuroprotective effects, particularly in gray and white matter and the hippocampus, which may contribute to improved neurodevelopmental outcomes. However, the impact was not uniform across all brain structures. Further research is needed, to investigate the long-term benefits and to optimize therapeutic strategies by integrating advanced neuroimaging techniques and genetic insights. Full article

Background and Purpose: Perivascular spaces (PVS) are usually enlarged in small vessel disease (SVD). However, the significance of PVS patterns in different locations is uncertain. Hence, we analyzed the distribution of PVS in patients with a recent small subcortical infarct (RSSI) and their correlation with clinical and imaging factors. Materials and Methods: In a cohort of 71 patients with an RSSI with complete clinical data, including the Pittsburgh Sleep Quality Index (PSQI), we segmented PVS in white matter (WM-PVS), basal ganglia (BG-PVS), and brainstems (BS-PVS) on 3T-MRI T2-weighted sequences, obtaining fractional volumes (%), and calculated the WM/BG-PVS ratio. We analyzed the Pearson’s correlation coefficients between PVS regional loads. We used normalized PVS measures to assess the associations with clinical and MRI-SVD features (white matter hyperintensities (WMHs), number of lacunes, and microbleeds) in univariable and multivariable linear regressions adjusted for age, sex, and hypertension. Results: In our cohort (mean age 70 years; 27% female), the Pearson’s correlation coefficients between WM-PVS/BG-PVS, WM-PVS/BS-PVS, and BG-PVS/BS-PVS were 0.67, 0.61, and 0.59 (all p < 0.001). In the adjusted models, BG-PVS were associated with lacunes (p = 0.034), WMHs (p = 0.006), and microbleeds (p = 0.017); WM-PVS with lacunes (p = 0.003); while BS-PVS showed no associations. The WM/BG-PVS ratio was associated with lacunes (p = 0.018) and the PSQI (p = 0.046). Conclusions: PVS burdens in different regions are highly correlated in patients with RSSI but with different SVD patterns. Sleep quality impairment might affect waste removal mechanisms differently in the WM and BG regions. Full article

Background: The aim of this review is to highlight the new advance of predictive and explainable artificial intelligence for neuroimaging applications. Methods: Data came from 30 original studies in PubMed with the following search terms: “neuroimaging” (title) together with “machine learning” (title) or ”deep learning” (title). The 30 original studies were eligible according to the following criteria: the participants with the dependent variable of brain image or associated disease; the interventions/comparisons of artificial intelligence; the outcomes of accuracy, the area under the curve (AUC), and/or variable importance; the publication year of 2019 or later; and the publication language of English. Results: The performance outcomes reported were within 58–96 for accuracy (%), 66–97 for sensitivity (%), 76–98 for specificity (%), and 70–98 for the AUC (%). The support vector machine and the convolutional neural network registered the best performance (AUC 98%) for the classifications of low- vs. high-grade glioma and brain conditions, respectively. Likewise, the random forest delivered the best performance (root mean square error 1) for the regression of brain conditions. The following factors were discovered to be major predictors of brain image or associated disease: (demographic) age, education, sex; (health-related) alpha desynchronization, Alzheimer’s disease stage, CD4, depression, distress, mild behavioral impairment, RNA sequencing; (neuroimaging) abnormal amyloid-β, amplitude of low-frequency fluctuation, cortical thickness, functional connectivity, fractal dimension measure, gray matter volume, left amygdala activity, left hippocampal volume, plasma neurofilament light, right cerebellum, regional homogeneity, right middle occipital gyrus, surface area, sub-cortical volume. Conclusion: Predictive and explainable artificial intelligence provide an effective, non-invasive decision support system for neuroimaging applications. Full article

Background: Brain magnetic resonance imaging (MRI) of infants with congenital heart disease (CHD) shows brain immaturity assessed via a cortical-based semi-quantitative score. Our primary aim was to develop an infant paralimbic-related subcortical-based semi-quantitative dysmaturation score, termed brain dysplasia score (BDS), to detect abnormalities in CHD infants compared to healthy controls and secondarily to predict clinical outcomes. We also validated our BDS in a preclinical mouse model of hypoplastic left heart syndrome. Methods: A paralimbic-related subcortical BDS, derived from structural MRIs of infants with CHD, was compared to healthy controls and correlated with clinical risk factors, regional cerebral volumes, feeding, and 18-month neurodevelopmental outcomes. The BDS was validated in a known CHD mouse model named Ohia with two disease-causing genes, Sap130 and Pchda9. To relate clinical findings, RNA-Seq was completed on Ohia animals. Findings: BDS showed high incidence of paralimbic-related subcortical abnormalities (including olfactory, cerebellar, and hippocampal abnormalities) in CHD infants (n = 215) compared to healthy controls (n = 92). BDS correlated with reduced cortical maturation, developmental delay, poor language and feeding outcomes, and increased length of stay. Ohia animals (n = 63) showed similar BDS findings, and RNA-Seq analysis showed altered neurodevelopmental and feeding pathways. Sap130 mutants correlated with a more severe BDS, whereas Pcdha9 correlated with a milder phenotype. Conclusions: Our BDS is sensitive to dysmaturational differences between CHD and healthy controls and predictive of poor outcomes. A similar spectrum of paralimbic and subcortical abnormalities exists between human and Ohia mutants, suggesting a common genetic mechanistic etiology. Full article

Extremely preterm birth entails an increased risk for multimorbidity and the prevalence of developmental deficits because this risk is negatively correlated to the number of gestation weeks. This work evaluated subcortical volume changes in children born extremely preterm who received Katona neurohabilitation, as well as the effects of subcortical volume and treatment adherence on their three-year-old neurodevelopment outcomes. Fifteen extremely preterm-born participants were treated from two months to two years old and followed up until past three years of age. The participants received Katona neurohabilitation, which provides vestibular and proprioceptive stimulation and promotes movement integration through the early, intensive practice of human-specific elementary movements. Subcortical brain volumes from magnetic resonance images were obtained at the beginning and after treatment. Also, treatment adherence to Katona neurohabilitation and neurodevelopment outcomes were measured. The results showed that absolute subcortical volumes increased after treatment; however, when adjusted by intracranial volume, these volumes decreased. Subcortical function inhibition allows cortical control and increased connectivity, which may explain decreased adjusted volume. Regression analyses showed that after-treatment hippocampal volumes had a discrete predictive value. However, treatment adherence showed a clear effect on mental and psychomotor neurodevelopment. Thus, the effectiveness of Katona neurohabilitation is constrained by treatment adherence. Full article

Background and objectives: The premanifest phase of Huntington’s disease (HD) is characterized by the absence of motor symptoms and exhibits structural changes in imaging that precede clinical manifestation. This study aimed to analyze volumetric changes identified through brain magnetic resonance imaging (MRI) processed using artificial intelligence (AI) software in premanifest HD individuals, focusing on the relationship between CAG triplet expansion and structural biomarkers. Methods: The study included 36 individuals descending from families affected by HD in the Department of Atlántico. Sociodemographic data were collected, followed by peripheral blood sampling to extract genomic DNA for quantifying CAG trinucleotide repeats in the Huntingtin gene. Brain volumes were evaluated using AI software (Entelai/IMEXHS, v4.3.4) based on MRI volumetric images. Correlations between brain volumes and variables such as age, sex, and disease status were determined. All analyses were conducted using SPSS (v. IBM SPSS Statistics 26), with significance set at p < 0.05. Results: The analysis of brain volumes according to CAG repeat expansion shows that individuals with ≥40 repeats evidence significant increases in cerebrospinal fluid (CSF) volume and subcortical structures such as the amygdalae and left caudate nucleus, along with marked reductions in cerebral white matter, the cerebellum, brainstem, and left pallidum. In contrast, those with <40 repeats show minimal or moderate volumetric changes, primarily in white matter and CSF. Conclusions: These findings suggest that CAG expansion selectively impacts key brain regions, potentially influencing the progression of Huntington’s disease, and that AI in neuroimaging could identify structural biomarkers long before clinical symptoms appear. Full article