Effects of Cardiac Abnormalities on the Brain, Revealed by Brain Magnetic Resonance Imaging and Genetics

Understanding the relationships between age-related changes in brain structure and cognitive function has been limited by inconsistent methods for assessing brain imaging, small sample sizes, and racially/ethnically homogeneous cohorts with biased selection based on risk factors. These limitations have prevented the generalizability of results from brain morphology studies. To determine the association of 3.0-T structural brain magnetic resonance (MR) imaging measurements with cognitive function in the multiracial/multiethnic, population-based Dallas Heart Study. Whole-brain, 2-dimensional, fluid-attenuated inversion recovery and 3-dimensional, magnetization-prepared, rapid acquisition with gradient echo MR imaging at 3.0 T was performed in 1645 Dallas Heart Study participants (mean [SD] age, 49.9 [10.5] years; age range, 19-85 years) who received both brain MR imaging and cognitive screening with the Montreal Cognitive Assessment between September 18, 2007, and December 28, 2009. Measurements were obtained for white matter hyperintensity volume, total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume. Linear regression and a best predictive model were developed to determine the association of MR imaging biomarkers with the Montreal Cognitive Assessment total score and domain-specific questions. High-resolution anatomical MR imaging was used to quantify brain volumes. Scores on the screening Montreal Cognitive Assessment were used for cognitive assessment in participants. After adjustment for demographic variables, total brain volume (P < .0001, standardized estimate [SE] = .1069), gray matter volume (P < .0001, SE = .1156), white matter volume (P = .008, SE = .0687), cerebrospinal fluid volume (P = .012, SE = -.0667), and hippocampal volume (P < .0001) were significantly associated with cognitive performance. A best predictive model identified gray matter volume (P < .001, SE = .0021), cerebrospinal fluid volume (P = .01, SE = .0024), and hippocampal volume (P = .004, SE = .1017) as 3 brain MR imaging biomarkers significantly associated with the Montreal Cognitive Assessment total score. Questions specific to the visuospatial domain were associated with the most brain MR imaging biomarkers (total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume), while questions specific to the orientation domain were associated with the least brain MR imaging biomarkers (only hippocampal volume). Brain MR imaging volumes, including total brain volume, gray matter volume, cerebrospinal fluid volume, and hippocampal volume, were independently associated with cognitive function and may be important early biomarkers of risk for cognitive insult in a young multiracial/multiethnic population. A best predictive model indicated that a combination of multiple neuroimaging biomarkers may be more effective than a single brain MR imaging volume measurement.

Neuropsychiatric Significance of Subcortical Hyperintensity

Kidney Disease and Brain Health: Current Knowledge and Next Steps

Purpose: Heart failure (HF) affects almost all organs in our body through reduced organ perfusion and resultant neurohumoral alterations. Major depression is more prevalent in HF patients as compared with normal subjects, suggesting the possible interactions between the heart and the brain in HF. However, functional and structural brain changes in HF patients remain largely unclear. We thus prospectively performed Brain Assessment and Investigation in Heart Failure Trial (B-HeFT) (UMI08584), in which we investigated the interactions between the two vital organs by magnetic resonance (MR) imaging in Stage B/C HF patients. Methods: Stage B (n=14) and Stage C (n=16) HF patients, who were diagnosed by echocardiography and past HF symptoms, underwent brain and cardiac MR image acquisitions and questionnaires including the Minnesota Living with Heart Failure Questionnaire (Stage C, 38.5±6.5 vs. Stage B, 21.6±4.9, P<0.05) and the Beck depression inventory (Stage C, 11.9±2.3 vs. Stage B, 8.7±1.7, P=0.27). The brain MR images were analyzed to detect regional alterations in grey matter between Stage B and C groups as measured by grey matter probability values (a maximum value of 1). Left ventricular ejection fraction (LVEF), cardiac index (CI) and LV end-diastolic volume (LVEDV) were obtained from the cardiac MR images using Simpson's method. Results: Stage C and B groups did not differ in age (Stage C, 65.4±1.7 vs. Stage B, 63.3±3.7 years) or ischemic origin (Stage C, 50.0 vs. Stage B, 57.1%). Analysis of the cardiac MR images demonstrated significant cardiac remodeling in Stage C than in Stage B group, including reduced LVEF (Stage C, 34.2±4.3 vs. Stage B, 55.0±34.2%, P<0.01), increased LVEDV (Stage C, 194±25 vs. Stage B, 125±11 ml, P<0.05) and a tendency for reduced CI (Stage C, 2.2±0.2 vs. Stage B, 2.6±0.3 ml/m2/min, P=0.19). Analysis of the brain MR images identified grey matter reduction in Stage C as compared with Stage B group not only in regions associated with depressive symptoms such as the right hippocampus (Stage C, 0.559±0.016 vs. Stage B, 0.574±0.018, P<0.05) but also in the bilateral primary motor cortex (Stage C, 0.320±0.017 vs. Stage B, 0.337±0.016, P<0.05). There was a tendency for a positive correlation between increased LVEDV and grey matter reduction in the right hippocampus (Stage C, r=0.37, P=0.20; Stage B, r=0.28, P=0.34). Conclusion: These results indicate that HF is associated with cardiac remodeling along with grey matter reduction in the hippocampus and the primary motor cortex, which may be involved in depressive symptoms and reduced daily activity in HF patients.

SAT-LB19 Is There a Need to Use Gadolinium Contrast for Pituitary MRI in the Evaluation of Pediatric Short Stature and Growth Hormone Deficiency?

Automated tissue segmentation of brain magnetic resonance (MR) images has attracted extensive research attention. Many segmentation algorithms have been proposed for this issue. However, due to the existence of noise and intensity inhomogeneity in brain MR images, the accuracy of the segmentation results is usually unsatisfactory. In this paper, a high-accuracy brain MR image segmentation algorithm based on the information bottleneck (IB) method is presented. In this approach, the MR image is first mapped into a “local-feature space”, then the IB method segments the brain MR image through an information theoretic formulation in this local-feature space. It automatically segments the image into several clusters of voxels, by taking the intensity information and spatial information of voxels into account. Then, after the IB-based clustering, each cluster of voxels is classified into one type of brain tissue by threshold methods. The performance of the algorithm is studied based on both simulated and real T1-weighted 3D brain MR images. Our results show that, compared with other well-known brain image segmentation algorithms, the proposed algorithm can improve the accuracy of the segmentation results substantially.

The independent contribution of brain, spinal cord and gadolinium MRI in treatment decision in multiple sclerosis: A population-based retrospective study.

Morbidity and mortality after pediatric cardiac arrest are chiefly due to hypoxic-ischemic brain injury. Brain features seen on magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) after arrest may identify injury and aid in outcome assessments. To analyze the association of brain lesions seen on T2-weighted MRI and diffusion-weighted imaging and N-acetylaspartate (NAA) and lactate concentrations seen on MRS with 1-year outcomes after pediatric cardiac arrest. This multicenter cohort study took place in pediatric intensive care units at 14 US hospitals between May 16, 2017, and August 19, 2020. Children aged 48 hours to 17 years who were resuscitated from in-hospital or out-of-hospital cardiac arrest and who had a clinical brain MRI or MRS performed within 14 days postarrest were included in the study. Data were analyzed from January 2022 to February 2023. Brain MRI or MRS. The primary outcome was an unfavorable outcome (either death or survival with a Vineland Adaptive Behavior Scales, Third Edition, score of <70) at 1 year after cardiac arrest. MRI brain lesions were scored according to region and severity (0 = none, 1 = mild, 2 = moderate, 3 = severe) by 2 blinded pediatric neuroradiologists. MRI Injury Score was a sum of T2-weighted and diffusion-weighted imaging lesions in gray and white matter (maximum score, 34). MRS lactate and NAA concentrations in the basal ganglia, thalamus, and occipital-parietal white and gray matter were quantified. Logistic regression was performed to determine the association of MRI and MRS features with patient outcomes. A total of 98 children, including 66 children who underwent brain MRI (median [IQR] age, 1.0 [0.0-3.0] years; 28 girls [42.4%]; 46 White children [69.7%]) and 32 children who underwent brain MRS (median [IQR] age, 1.0 [0.0-9.5] years; 13 girls [40.6%]; 21 White children [65.6%]) were included in the study. In the MRI group, 23 children (34.8%) had an unfavorable outcome, and in the MRS group, 12 children (37.5%) had an unfavorable outcome. MRI Injury Scores were higher among children with an unfavorable outcome (median [IQR] score, 22 [7-32]) than children with a favorable outcome (median [IQR] score, 1 [0-8]). Increased lactate and decreased NAA in all 4 regions of interest were associated with an unfavorable outcome. In a multivariable logistic regression adjusted for clinical characteristics, increased MRI Injury Score (odds ratio, 1.12; 95% CI, 1.04-1.20) was associated with an unfavorable outcome. In this cohort study of children with cardiac arrest, brain features seen on MRI and MRS performed within 2 weeks after arrest were associated with 1-year outcomes, suggesting the utility of these imaging modalities to identify injury and assess outcomes.

To examine the association between brain magnetic resonance imaging (MRI) characteristics and executive function and bimanual performance in children with unilateral cerebral palsy (CP). Clinical MRI brain scans were classified as: (1) predominant pathological pattern (normal, white matter injury [WMI]; grey matter injury; focal vascular insults [FVI]; malformations; or miscellaneous); and (2) focal lesions (frontal, basal ganglia, and/or thalamus). Assessments included: (1) bimanual performance; (2) unimanual dexterity; and (3) executive function tasks (information processing, attention control, cognitive flexibility, and goal setting) and behavioural ratings (parent). From 131 recruited children, 60 were ineligible for analysis, leaving 71 children (47 males, 24 females) in the final sample (mean age 9y [SD 2y], 6y-12y 8mo). Brain MRIs were WMI (69%) and FVI (31%); and frontal (59%), thalamic (45%), basal ganglia (37%), and basal ganglia plus thalamic (21%). Bimanual performance was lower in FVI versus WMI (p<0.003), and with frontal (p=0.36), basal ganglia (p=0.032), and thalamic/basal ganglia lesions (p=0.013). Other than information processing, executive function tasks were not associated with predominant pattern. Frontal lesions predicted attention control (p=0.049) and cognitive flexibility (p=0.009) but not goal setting, information processing, or behavioural ratings. Clinical brain MRI predicts cognitive and motor outcomes when focal lesions and predominate lesion patterns are considered. What this paper adds Early brain magnetic resonance imaging (MRI) predicts bimanual performance and cognitive outcomes. Brain MRI may identify children requiring targeted interventions. Basal ganglia with/without thalamic lesions predicted bimanual performance. Frontal lesions were associated with attention control and cognitive flexibility. Brain MRI predominant patterns predicted motor, not cognitive outcomes, other than information processing.

Sepsis often codevelops with brain damage, and the mechanisms underlying sepsis-related brain damage have been elucidated. However, only a few studies have reported the diagnostic imaging assessments for brain damage in sepsis. Therefore, in this study, we analyzed the brain magnetic resonance (MR) imaging (MRI) findings of patients with sepsis. This single-center prospective observational study included 71 patients with sepsis who underwent brain MRI, regardless of the presence or absence of shocks and acute neurological abnormalities. The MR images were classified according to the presence or absence of acute cerebral ischemia and leukoencephalopathy, with normal findings indicating neither condition. The MR images of 18 patients (25.3%) showed acute cerebral ischemia and leukoencephalopathy. Furthermore, 44 patients (62.0%) had only leukoencephalopathy. In terms of patient demographic characteristics and neurological outcomes, significant differences were noted among patients with acute cerebral ischemia findings, those with leukoencephalopathy findings, and those with neither. There were significant differences in age (P = 0.0296), neurological findings (P = 0.0057), number of days in the intensive care unit (P = 0.0239), acute disseminated intravascular coagulation score during hospitalization (P = 0.0363), and the Katz index at discharge or transfer (P = 0.0020) among these groups. Among patients with sepsis, 25.3% showed acute cerebral ischemia findings on brain MRI, regardless of illness severity, including hypoxia and hypotension, and presence of shock. Abnormal MRI findings were also observed in patients without acute brain dysfunction. Importantly, abnormal brain MRI findings were associated with worse neurological outcomes.

1. Kamakshya P. Patra, MD* 2. Jeffrey D. Lancaster, MD* 3. Jeffery Hogg, MD† 4. Jeffrey S. Carpenter, MD† 1. *Department of Pediatrics, Section of Hospital Pediatrics, West Virginia University Children’s Hospital, Morgantown, WV. 2. †Department of Neuroradiology, West Virginia University Health Sciences Center, Morgantown, WV. * Abbreviations: ADHD: : attention-deficit/hyperactivity disorder CSF: : cerebrospinal fluid CT: : computed tomography DWI: : diffusion-weighted magnetic resonance imaging FLAIR: : fluid-attenuated inversion recovery fMRI: : functional magnetic resonance imaging MRI: : magnetic resonance imaging MRV: : magnetic resonance venography NAA: : N -acetylaspartate SDH: : subdural hematoma Because of recent advances in magnetic resonance imaging (MRI) techniques, pediatricians should be aware of the different modalities and their unique advantages and appropriateness in different clinical situations. After completing this article, readers should be able to: 1. Understand the pros and cons of MRI and computed tomography of the brain. 2. Know the basic principles of MRI and its different image modalities. 3. Be aware of the appropriateness of different modalities in specific clinical situations. Magnetic resonance imaging (MRI) is based on the absorption and emission of radiofrequency energy by hydrogen protons whose spin is influenced by changing magnetic fields (0.3 to 1.5 T). Unlike computed tomography (CT), there is no radiation exposure. T1-weighted images cause fat (eg, myelin in white matter) to appear bright and water (eg, cerebrospinal fluid [CSF] or edema) to appear dark on this sequence. The gray-white interfaces of the brain are well depicted on these sequences, especially if with the images are thinly sliced. T2-weighted images cause water (eg, CSF and edema) to appear bright and fat to appear dark. The MRI-based intravenous contrast agents (eg, gadolinium) are frequently used in T1-weighted images (Fig 1A and B) to make serum appear bright. The blood-brain barrier typically serves to limit the passage of many molecules out of the blood vessels. If disease processes break down this barrier (such as infection, tumors, or inflammation), intravenous contrast agents can cross into the brain, causing areas of contrast entry to appear very bright. Figure 1. T1-weighted image at the level of midbrain. A. The cerebrospinal fluid (CSF) appears dark. B. The CSF appears bright. Note the gray and white matter differentiation …

ObjectiveVascular comorbidities are associated with reduced cognitive performance and with changes in brain structure in people with multiple sclerosis (MS). Understanding causal pathways is necessary to support the design of interventions to mitigate the impacts of comorbidities, and to monitor their effectiveness. We assessed the inter-relationships among vascular comorbidity, cognition and brain structure in people with MS.MethodsAdults with neurologist-confirmed MS reported comorbidities, and underwent assessment of their blood pressure, HbA1c, and cognitive functioning (i.e., Symbol Digit Modalities Test, California Verbal Learning Test, Brief Visuospatial Memory Test-Revised, and verbal fluency). Test scores were converted to age-, sex-, and education-adjusted z-scores. Whole brain magnetic resonance imaging (MRI) was completed, from which measures of thalamic and hippocampal volumes, and mean diffusivity of gray matter and normal-appearing white matter were converted to age and sex-adjusted z-scores. Canonical correlation analysis was used to identify linear combinations of cognitive measures (cognitive variate) and MRI measures (MRI variate) that accounted for the most correlation between the cognitive and MRI measures. Regression analyses were used to test whether MRI measures mediated the relationships between the number of vascular comorbidities and cognition measures.ResultsOf 105 participants, most were women (84.8%) with a mean (SD) age of 51.8 (12.8) years and age of symptom onset of 29.4 (10.5) years. Vascular comorbidity was common, with 35.2% of participants reporting one, 15.2% reporting two, and 8.6% reporting three or more. Canonical correlation analysis of the cognitive and MRI variables identified one pair of variates (Pillai's trace = 0.45, p = 0.0035). The biggest contributors to the cognitive variate were the SDMT and CVLT-II, and to the MRI variate were gray matter MD and thalamic volume. The correlation between cognitive and MRI variates was 0.50; these variates were used in regression analyses. On regression analysis, vascular comorbidity was associated with the MRI variate, and with the cognitive variate. After adjusting for the MRI variate, vascular comorbidity was not associated with the cognitive variate.ConclusionVascular comorbidity is associated with lower cognitive function in people with MS and this association is partially mediated via changes in brain macrostructure and microstructure.

Objective:This study aims to evaluate the magnetic resonance imaging (MRI) brain patterns among hypoxic-ischemic encephalopathy (HIE) babies who underwent post-cooling MRI brain as well as to correlate the post-cooling brain scoring with patient's neurodevelopmental outcome at 2 years.Subjects and Methods:It was a retrospective cross sectional study carried out at a tertiary university hospital. Record of patients diagnosed with neonatal HIE from 2007 until 2016 who completed 72 h of cooling therapy and had MRI brain within 2 weeks of life were included in this study. A new scoring system by Trivedi et al. that emphasizes on subcortical deep gray matter and posterior limb internal capsule injury were utilized upon MRI assessment, using TW, T2W, and diffusion-weighted imaging (DWI) sequences. Cumulative MRI brain score was obtained and graded as none, mild, moderate, and severe brain injury. The MRI brain scoring was then correlated with patient's 2 years neurodevelopmental outcome using Fisher's Exact Test.Results:A total of 23 patients were eligible of which 19 term neonates were included. 13% of these neonates (n = 3) had mild MRI brain injury grading with 52.2% (n = 12) moderate and 34.8% (n = 8) severe. There was no significant correlation seen between MRI brain grading and developmental outcome at 2 years old (P > 0.05).Conclusion:There was no significant correlation between neonatal MRI brain injury grading and 2 years neurodevelopmental outcome. Nevertheless, the new MRI brain scoring by Trivedi et al. is reproducible and comprehensive as it involves various important brain structures, assessed from different MRI sequences.

Segmentation of bias field induced brain MR images using rough sets and stomped-t distribution

Central nervous system (CNS) involvement has been observed in 14-80% of patients with systemic lupus erythematosus (SLE). Magnetic resonance imaging (MRI) is an appropriate method for evaluating CNS involvement in these patients. Clinical manifestations and MRI findings of CNS lupus should be differentiated from other mimicking diseases such as multiple sclerosis (MS). The aim of this study was to evaluate the prevalence and extent of brain and cervical cord MRI lesions of lupus patients. The relationship between neurological signs and symptoms and MRI findings were evaluated as well. Fifty SLE patients who had been referred to the rheumatology clinic of our hospital within 2009 were included in a cross sectional study. All patients fulfilled the revised 1981 American College of Rheumatology (ACR) criteria for SLE. We evaluated the neurological signs and symptoms and brain and cervical MRI findings in these patients. Forty-one patients (82%) were female and nine (18%) were male. The mean age was 30.1 ± 9.3 years. Twenty eight (56%) patients had an abnormal brain MRI. No one showed any abnormality in the cervical MRI. The lesions in 20 patients were similar to demyelinative plaques. Seventeen patients with abnormal brain MRI were neurologically asymptomatic. There was only a significant relationship between neurological motor manifestations and brain MRI abnormal findings. Unlike the brain, cervical MRI abnormality and especially asymptomatic cord involvement in MRI is quite rare in SLE patients. This finding may be helpful to differentiate SLE from other CNS disorders such as MS.