Magnetic Resonance Imaging Variables Research Articles

Associations Between Cognitive Impairment and Neuroimaging in Patients with Multiple Sclerosis.

Multiple sclerosis (MS) is a debilitating inflammatory and neurodegenerative disease which commonly involves cognitive dysfunction. Magnetic resonance imaging (MRI) studies have shown that patients with MS (pwMS) have diffuse patterns of brain atrophy, however, the relationship between the presentation of cognitive dysfunction and brain tissue loss remains understudied. Given the integral function of thalamus as a central nervous system relay center and its involvement in various brain circuits, thalamic atrophy may play a key role in the development and progression of cognitive dysfunction. The purpose of this study is to examine the relationship between cognitive impairment in pwMS and thalamic atrophy. A total of 121 pwMS who had neuropsychological testing and quantitative MRI within 1 year of each were retrospectively identified. Grouped LASSO linear regression with 10-fold cross validation was used to estimate each neuropsychological test score with thalamic volume as the focal predictor and all other demographic and MRI metrics as covariates. Rates of impairment ranged from 19% to 44%. Results showed notable associations between thalamic volume and Symbol Digit Modalities Test (β= 0.11), Brief Visuospatial Memory Test, delayed (β = 0.12), California Verbal Learning Test, delayed and total (β = 0.24 and β = 0.15 respectively), and Trail Making Test Part A (β = -0.01), after adjusting for covariates. These findings demonstrate an independent association between thalamic volumes and processing speed and memory performance, after accounting for demographic, clinical, and other MRI variables, among pwMS.

Identifying individuals with non-Alzheimer's disease co-pathologies: A precision medicine approach to clinical trials in sporadic Alzheimer's disease.

Biomarkers remain mostly unavailable for non-Alzheimer's disease neuropathological changes (non-ADNC) such as transactive response DNA-binding protein 43 (TDP-43) proteinopathy, Lewy body disease (LBD), and cerebral amyloid angiopathy (CAA). A multilabel non-ADNC classifier using magnetic resonance imaging (MRI) signatures was developed for TDP-43, LBD, and CAA in an autopsy-confirmed cohort (N=214). A model using demographic, genetic, clinical, MRI, and ADNC variables (amyloid positive [Aβ+] and tau+) in autopsy-confirmed participants showed accuracies of 84% for TDP-43, 81% for LBD, and 81% to 93% for CAA, outperforming reference models without MRI and ADNC biomarkers. In an ADNI cohort (296 cognitively unimpaired, 401 mild cognitive impairment, 188 dementia), Aβ and tau explained 33% to 43% of variance in cognitive decline; imputed non-ADNC explained an additional 16% to 26%. Accounting for non-ADNC decreased the required sample size to detect a 30% effect on cognitive decline by up to 28%. Our results lead to a better understanding of the factors that influence cognitive decline and may lead to improvements in AD clinical trial design.

Biomarker, Imaging, and Clinical Factors Associated With Overt and Covert Stroke in Patients With Atrial Fibrillation.

Atrial fibrillation is a major risk factor for stroke and silent brain infarcts. We studied whether a multimodal approach offers additional insights to the CHA2DS2-VASc score in predicting stroke or new brain infarcts on magnetic resonance imaging (MRI) over a 2-year follow-up. Swiss-AF is a prospective, multicenter cohort study of patients with known atrial fibrillation. We included patients with available brain MRI both at enrollment and 2 years later. The dates of the baseline and follow-up visits ranged from March 2014 to November 2020. The primary outcome was assessed 2 years after baseline and was defined as a composite of clinically identified stroke or any new brain infarct on the 2-year MRI. We compared a multivariable logistic regression model including prespecified clinical, biomarker, and baseline MRI variables to the CHA2DS2-VASc score. We included 1232 patients, 89.8% of them taking oral anticoagulants. The primary outcome occurred in 78 patients (6.3%). The following baseline variables were included in the final multivariate model and were significantly associated with the primary outcome: white matter lesion volume in milliliters (adjusted odds ratio [aOR], 1.91 [95% CI, 1.45-2.56]), NT-proBNP (N-terminal pro-B-type natriuretic peptide; aOR, 1.75 [95% CI, 1.20-2.63]), GDF-15 (growth differentiation factor-15; aOR, 1.68 [95% CI, 1.11-2.53]), serum creatinine (aOR, 1.50 [95% CI, 1.02-2.22]), IL (interleukin)-6 (aOR, 1.37 [95% CI, 1.00-1.86]), and hFABP (heart-type fatty acid-binding protein; aOR, 0.48 [95% CI, 0.31-0.73]). Overall performance and discrimination of the new model was superior to that of the CHA2DS2-VASc score (C statistic, 0.82 [95% CI, 0.77-0.87] versus 0.64 [95% CI, 0.58-0.70]). In patients with atrial fibrillation, a model incorporating white matter lesion volume on baseline MRI and selected blood markers yielded new insights on residual stroke risk despite a high proportion of patients on oral anticoagulants. This may be relevant to develop further preventive measures.

Machine learning using multimodal clinical, electroencephalographic, and magnetic resonance imaging data can predict incident depression in adults with epilepsy: A pilot study.

This study was undertaken to develop a multimodal machine learning (ML) approach for predicting incident depression in adults with epilepsy. We randomly selected 200 patients from the Calgary Comprehensive Epilepsy Program registry and linked their registry-based clinical data to their first-available clinical electroencephalogram (EEG) and magnetic resonance imaging (MRI) study. We excluded patients with a clinical or Neurological Disorders Depression Inventory for Epilepsy (NDDI-E)-based diagnosis of major depression at baseline. The NDDI-E was used to detect incident depression over a median of 2.4 years of follow-up (interquartile range [IQR] = 1.5-3.3 years). A ReliefF algorithm was applied to clinical as well as quantitative EEG and MRI parameters for feature selection. Six ML algorithms were trained and tested using stratified threefold cross-validation. Multiple metrics were used to assess model performances. Of 200 patients, 150 had EEG and MRI data of sufficient quality for ML, of whom 59 were excluded due to prevalent depression. Therefore, 91 patients (41 women) were included, with a median age of 29 (IQR = 22-44) years. A total of 42 features were selected by ReliefF, none of which was a quantitative MRI or EEG variable. All models had a sensitivity > 80%, and five of six had an F1 score ≥ .72. A multilayer perceptron model had the highest F1 score (median = .74, IQR = .71-.78) and sensitivity (84.3%). Median area under the receiver operating characteristic curve and normalized Matthews correlation coefficient were .70 (IQR = .64-.78) and .57 (IQR = .50-.65), respectively. Multimodal ML using baseline features can predict incident depression in this population. Our pilot models demonstrated high accuracy for depression prediction. However, overall performance and calibration can be improved. This model has promise for identifying those at risk for incident depression during follow-up, although efforts to refine it in larger populations along with external validation are required.

The role of lumbosacral paraspinal muscle degeneration and low vertebral bone mineral density on distal instrumentation-related problems following long-instrumented spinal fusion for degenerative lumbar scoliosis: a retrospective cohort study.

This study aimed to confirm the role of paraspinal muscle degeneration and low vertebral bone mineral density (vBMD) of the lumbosacral region in the development of distal instrumentation-related problems (DIPs) in degenerative lumbar scoliosis (DLS) patients undergoing long-instrumented spinal fusion. From 2013 to 2019, 125 DLS patients with 24-month follow-up after long-instrumented spinal fusion in Beijing Chao-Yang Hospital were retrospectively recruited and divided into DIP and non-DIP groups. Demographic characteristics, surgical data, and radiographic parameters were statistically compared between the groups. Degeneration of the paraspinal muscle was evaluated using the relative gross cross-sectional area (rGCSA), relative functional cross-sectional area (rFCSA), ratio of the rFCSA to rGCSA, gross muscle-fat index, and functional muscle-fat index of the multifidus (MF), erector spinae (ES), paraspinal extensor muscle (PSE), and psoas major determined by preoperative magnetic resonance imaging (MRI). The vBMD of the lumbosacral region and lower instrumented vertebra (LIV) was assessed using Hounsfield unit (HU) values determined by computed tomography (CT) scans. The DeLong test was performed to select MRI and CT scan variables. Multivariable logistic regression analysis was applied to determine the independent predictive factors of DIPs. The incidence of DIPs was 16.0% (20/105). There were no significant differences in demographic characteristics or surgical data between the groups. The rFCSAs of the MF (65.74±21.51 vs. 92.37±21.68; P<0.001), ES (82.67±21.44 vs. 111.48±24.21; P<0.001) and PSE (144.31±36.12 vs. 208.48±41.57; P<0.001) and the HU values of the lumbosacral region (103.80±22.64 vs.. 132.19±19.17; P<0.001) and LIV (111.70±23.23 vs. 128.69±20.70; P=0.005) were significantly lower in the DIP group. Significantly less preoperative pelvic tilt and greater postoperative lumbosacral lordosis and sagittal vertical axis (SVA) values were observed in the DIP group. The rFCSA of the PSE, the HU value of the lumbosacral region, and the postoperative SVA value were detected as independent predictive factors of DIPs. Lower muscularity of the PSE, a lower vBMD of the lumbosacral region, and postoperative sagittal malalignment were independent predictive factors of DIPs. Surgeons should emphasize the preoperative evaluation of paraspinal muscle and bone mass in DLS patients.

Biomarker evidence of neurodegeneration in chronic kidney disease, in a general population

AbstractBackgroundProgressive decline in cognition and renal function are both related to ageing. The estimated global prevalence of dementia was 55 million people in 2019, a number expected to increase to 139 million by 2050. Furthermore, chronic kidney disease (CKD) is the second fastest growing cause of death globally. Few studies have examined the link between these conditions. In this study, we examine CKD and estimated glomerular filtration rate (eGFR) in relation to plasma neurofilament light protein (P‐NfL) and volumetric magnetic resonance imaging (MRI) measures of Alzheimer’s disease‐specific and general neurodegeneration.MethodUsing a cross‐sectional design, 744 participants from the Gothenburg H70 Birth cohort 1944 study, conducted in 2014‐2016, underwent MRI examination and blood draws. Plasma NfL concentration was measured using a Single molecule array (Simoa) assay. eGFR was calculated from creatinine and used for CKD diagnosis. CKD was defined as an estimated glomerular filtration rate below 60 mL/min/1.73 m2. Measurements of biomarker evidence of neurodegeneration were compared between participants with and without CKD. Correlations were also performed against eGFR. A logistic regression model adjusting for known risk factors for CKD was performed.ResultP‐NfL was significantly higher in participants with CKD (p&lt;0.001). No difference was seen in any MRI variables. Only P‐NfL correlated with eGFR (R = ‐0.25, p&lt;0.001), and there was a significant correlation both in participants with and without CKD (R = ‐0.44, p&lt;0.001 and R = ‐0.18, p&lt;0.001 respectively). Furthermore, in a logistic regression model, P‐NfL was a significant predictor of CKD independent of known risk factors including age, sex, education, smoking, hypertension, diabetes, BMI, fasting glucose, LDL‐cholesterol, CRP, and homocysteine (OR (CI); 3.231 (1.743: 5.990), p&lt;0.001).ConclusionOur observations suggest that neurodegeneration measured as P‐NfL is a predictor of CKD, independent of hypertension and diabetes. The origin of NfL, and the potential influence on the utilization of P‐NfL as a marker of neurodegeneration in individuals with CKD, should be assessed in future studies.

Association between H-type Hypertension and White Matter Hyperintensity in Patients with Acute Ischemic Stroke.

White matter hyperintensity (WMH) is related to the increased risk of ischemic stroke. It is unclear if H-type hypertension(H-type HBP) is associated with periventricular WMH (PWMH) and deep WMH (DWMH) of acute ischemic stroke. This study investigated the correlation between H-type HBP and the severity of PWMH and DWMH in acute ischemic stroke. Consecutive patients with acute ischemic stroke were included in this cross-sectional observational study. The patients were divided into the following groups: the normal group, the simple hypertension group(Simple HBP), the simple hyperhomocysteinemia group(Simple HHcy) and the H-type HBP group. MR imaging and relevant clinical variables were obtained from the medical records. PWMH and DWMH were rated by using the Fazekas scale(score 0-3). All patients were defined to have moderate-severe PWMH or DWMH (score 2-3) and no or mild group (score 0-1). Multivariate binary logistic regression analysis was performed to determine the relationship between H-type HBP and the severity of PWMH and DWMH. Among 542 patients, 227 had moderate-severe PWMH and 228 had moderate-severe DWMH. Compared to the no or mild group, patients with moderate-severe PWMH (median age: 73 vs. 63 years) and DWMH (median age: 70 vs. 65.5 years) were older. Compared to the no or mild group, moderate-severe PWMH and DWMH were associated with a history of ischemic stroke (moderate-severe PWMH vs. no or mild group 20.7% vs. 11.7%, p = 0.004；moderate-severe DWMH vs. no or mild group 20.2% vs. 12.1%, p = 0.010); We found that H-type HBP was an independent risk factor for PWMH(OR 2.64, 95% CI 1.34-5.21) and DWMH (OR 3.64, 95% CI 1.82-7.26) after adjusting for the effect of relevant risk factors. This study suggests that H-type HBP is associated with the severity of PWMH and DWMH in acute ischemic stroke patients, which deserves further prevention measures.

Image or scope: Magnetic resonance imaging and endoscopic testing for exocrine and endocrine pancreatic insufficiency in children

ObjectivesWe sought to evaluate associations between Magnetic Resonance Imaging (MRI) findings, exocrine pancreatic insufficiency (EPI) and endocrine insufficiency (prediabetes or diabetes) in children. MethodsThis was a retrospective study that included patients<21 years of age who underwent MRI and endoscopic pancreatic function testing (ePFT; reference standard for pancreatic exocrine function) within 3 months. MRI variables included pancreas parenchymal volume, secreted fluid volume in response to secretin, and T1 relaxation time. Data were analyzed for the full sample as well as the subset without acute pancreatitis (AP) at the time of imaging. ResultsOf 72 patients, 56% (40/72) were female with median age 11.4 years. A 5 mL decrease in pancreas parenchymal volume was associated with increased odds of exocrine pancreatic dysfunction by both ePFT (OR = 1.16, p = 0.02 full sample; OR = 1.29, p = 0.01 no-AP subset), and fecal elastase (OR = 1.16, p = 0.04 full sample; OR = 1.23, p = 0.02 no-AP subset). Pancreas parenchymal volume had an AUC 0.71 (95% CI: 0.59, 0.83) for predicting exocrine pancreatic dysfunction by ePFT and when combined with sex and presence of AP had an AUC of 0.82 (95% CI: 0.72, 0.92).Regarding endocrine function, decreased pancreas parenchymal volume was associated with increased odds of diabetes (OR = 1.16, p = 0.03), and T1 relaxation time predicted glycemic outcomes with an AUC 0.78 (95% CI: 0.55–1), 91% specificity and 73% sensitivity. ConclusionsPancreas parenchymal volume is an MRI marker of exocrine and endocrine pancreatic dysfunction in children. A model including sex, AP, and pancreas volume best predicted exocrine status. T1 relaxation time is also an MRI marker of endocrine insufficiency.

Magnetic resonance imaging and fractal analysis findings in temporomandibular joints with disk perforation

This study compared magnetic resonance imaging (MRI) findings and fractal dimension (FD) values in the temporomandibular joints (TMJs) of study patients with disk perforation vs control patients. Of 75 TMJs examined with MRI for characteristics of the disk and condyle, 45 were included in the study group and 30 in the control group. MRI findings and FD values were compared for significance of differences between the groups. The frequency of subclassifications was analyzed for differences between the two forms of disk configuration and grades of effusion. Mean FD values were analyzed for differences among subclassifications of MRI findings and between groups. Examination of MRI variables revealed that the study group had significantly greater frequencies of flattened disks, disk displacement, flattening and combined defects in condylar morphology, and grade 2 effusion (P=.001) Joints with perforated disks had a large percentage of normal disk-condyle relationships (73.3%). Significant differences were discovered between biconcave and flattened disk configuration in the frequencies of internal disk status and condylar morphology. FD values of all patients varied significantly among the subclassifications of disk configuration, internal disk status, and effusion. Mean FD values were significantly lower in the study group with perforated disks (1.07) compared with the control group (1.20, P=.001). MRI variables and FD can be useful in investigating intra-articular TMJ status.

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

Spinal cord and gadolinium (Gd)-enhanced magnetic resonance imaging (MRI) can provide additional information to brain MRI to determine prognosis of multiple sclerosis (MS). However, the real-world impact of routine use of brain MRI with spinal cord and/or Gd sequences is unknown. Our aim was to evaluate the effect of brain, spinal cord and Gd MRI on treatment decisions in MS. In this 2015-2020 population-based study, we performed a retrospective analysis on MS patients resident in the Campania Region (South Italy), with disease modifying treatment (DMT) prescription (n=6,161). DMTs were classified as platform (dimethyl fumarate, glatiramer acetate, interferon-beta, peg-interferon-beta, teriflunomide), or high-efficacy (alemtuzumab, cladribine, fingolimod, natalizumab, ocrelizumab). We evaluated the association between binary MRI variables and switch from platform to high-efficacy DMT using multivariable logistic regression. The likelihood of switch from platform to high-efficacy DMT was 47% higher when including post-Gd acquisitions to brain and/or spinal cord MRI, 59% higher when including spinal cord acquisitions to brain MRI, and 132% higher when including any MRI compared with no MRI (all p<0.05). The likelihood of switch to high-efficacy DMT decreased over time from treatment start. Our results show that spinal cord and Gd MRI acquisitions can provide relevant information to influence subsequent treatment decisions, especially in early treatment phases, compared with stand-alone brain MRI.

MRI characteristics for predicting histological subtypes in patients with uterine cervical adenocarcinoma

PurposeTo evaluate the magnetic resonance imaging (MRI) findings of uterine cervical adenocarcinoma for predicting different histological subtypes. Materials and methodsWe retrospectively analyzed MRI findings of 76 consecutive patients with histopathologically-confirmed uterine cervical adenocarcinoma undergoing preoperative MRI examination. An experienced pathologist classified the histological subtypes based on World Health Organization’s 2020 classification and into human papillomavirus (HPV)-associated adenocarcinomas (HPVAs, n = 54) (usual type and variants) and HPV-independent adenocarcinomas (HPVIs, n = 22) (gastric type adenocarcinoma (GAS), clear cell type, and other types). Different MRI variables were compared quantitatively and qualitatively between HPVA and HPVI and between GAS and non-GAS tumor types. ResultsThe maximum tumor diameter was significantly greater in HPVIs than HPVAs (41.9 ± 18.6 vs 32.7 ± 15.6 mm; p < 0.05). Heterogeneous enhancement on fat-suppressed gadolinium-enhanced T1-weighted images was more frequently seen in HPVIs than HPVAs (62 % vs 15 %; p < 0.01) and in GASs than non-GASs (78 % vs 16 %; p < 0.01). Also, infiltrative growth pattern (58 % vs 20 %; p < 0.05) and intratumoral cyst formation (83 % vs 47 %) (p < 0.05) were more frequent in GASs than non-GASs. ConclusionsCompared with HPVAs, HPVIs tend to have a larger tumor size with heterogeneous enhancement, of which GASs frequently show infiltrative growth patterns with intratumoral cyst formation and heterogeneous enhancement.

Interobserver Variability and Accuracy of Preoperative CT and MRI in Pancreatic Ductal Adenocarcinoma Size Estimation: A Retrospective Cohort Study.

Purpose: To assess interobserver variability and accuracy of preoperative computed tomography (CT) and magnetic resonance imaging (MRI) in pancreatic ductal adenocarcinoma (PDAC) size estimation using surgical specimens as standard of reference. Methods: Patients with PDAC who underwent preoperative CT and MRI examinations before surgery were included. PDAC largest axial dimension was measured by 2 readers on 8 MRI sequence and 2 CT imaging phases (pancreatic parenchymal and portal venous). Measurements were compared to actual tumour size at pathologic examination. Interobserver variability was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plots. Differences in tumour size (Δdiameter) between imaging and actual tumour size were searched using Wilcoxon rank sum test. Results: Twenty-nine patients (16 men; median age, 70years) with surgically resected PDAC were included. Interobserver reproducibility was good to excellent for all MRI sequences and the 2 CT imaging phases with ICCs between .862 (95%CI: .692-.942) for fat-saturated in-phase T1-weighted sequence and .955 (95%CI: .898-.980) for portal venous phase CT images. Best accuracy in PDAC size measurement was obtained with pancreatic parenchymal phase CT images with median Δdiameters of -2mm for both readers, mean relative differences of -9% and -6% and no significant differences with dimensions at histopathological analysis (P = .051). All MRI sequences led to significant underestimation of PDAC size (median Δdiameters, -6 to -1mm; mean relative differences, -21% to -11%). Conclusions: Most accurate measurement of PDAC size is obtained with CT images obtained during the pancreatic parenchymal phase. MRI results in significant underestimation of PDAC size.

MR Imaging Volumetric Response after Yttrium-90 Radioembolization for Colorectal Liver Metastases: Predictability at Baseline and Correlation with Survival

PurposeTo prove the utility of magnetic resonance (MR) imaging response as a surrogate end point of treatment efficacy and survival after yttrium-90 transarterial radioembolization (TARE) for colorectal liver metastases (CRLMs), and to investigate whether outcomes can be predicted at baseline using MR imaging or clinical variables. Materials and MethodsA total of 50 (135) patients with TARE for CRLMs between August 2008 and January 2020 and peri-interventional MR imaging within defined timeframes were included for tumor segmentation. Pretreatment and posttreatment target tumor volumes were measured according to the volumetric Response Evaluation Criteria In Solid Tumors (vRECIST) and the quantitative European Association for the Study of the Liver (qEASL) criteria. Cox regression models were used to analyze the impact of MR morphologic response, vascularity at baseline, and clinical variables on patient survival. Logistic regression analyses were used to evaluate the predictors of MR morphologic response at baseline. ResultsThe median survival was 337 days (95% confidence interval [CI], 243–431). As opposed to the vRECIST, the application of the qEASL criteria 3 months after the treatment allowed for a significant (P < .05) separation of the survival curves for partial response, stable disease, and progressive disease with a median survival of 412 days (95% CI, 57–767) in responders. High tumor burden and technetium-99m lung shunt significantly decreased the probability of survival. MR morphologic response was not predictable at baseline using imaging or clinical data. ConclusionsMR response according to the qEASL criteria outperformed the vRECIST in measuring the biologic impact of TARE and predicting patient survival. Baseline contrast enhancement did not predict MR response to treatment, which may reflect elevated dose requirements in tumors with a high proportion of viable tumor volume.

Impact of liver fibrosis and nodules formation on hemodynamics in young adults after total cavopulmonary connection. A magnetic resonance study.

BackgroundThe aim of this study was to analyze the relation between the hepatic fibrosis markers, liver morphology and hemodynamics assessed by magnetic resonance imaging (MRI) after total cavopulmonary connection (TCPC).Materials and methodsAdult patients after TCPC performed in childhood between 1993 and 2003 are the subjects of this observational study. The follow-up protocol consisted of clinical and echocardiographic examination, liver elastography, cardiopulmonary exercise test, MRI hemodynamics and liver morphology assessment and direct enhanced liver fibrosis (ELF) test.ResultsThe cohort consisted of 39 patients (46% female) with a median age at study 26 (IQR 23–28) years and interval from TCPC 21 (IQR 20–23) years. There was no correlation between ELF test and any MRI variables, but procollagen III amino-terminal peptide (PIIINP), a single component of ELF test, correlated significantly with ventricular end-diastolic volume (r = 0.33; p = 0.042) and inferior vena cava flow (r = 0.47; p = 0.003). Fifteen (38%) patients with liver nodules had compared to other 24 patients higher end-diastolic volume (ml/m2) 102.8 ± 20.0 vs. 88.2 ± 17.7; p = 0.023, respectively. PIIINP correlated significantly with inferior vena cava flow (r = 0.56; p = 0.030) and with end-diastolic volume (r = 0.53; p = 0.043), but only in patients with liver nodules.ConclusionGradual progression of liver fibrosis, particularly hepatic arterialization caused by liver nodules formation, increases inferior vena cava flow and subsequent ventricular volume overload may further compromise single ventricle functional reserve in adult patients after TCPC.

Individual differences in visual evoked potential latency are associated with variance in brain tissue volume in people with multiple sclerosis: An analysis of brain function-structure correlates

Visual evoked potentials (VEP) index visual pathway functioning, and are often used for clinical assessment and as outcome measures in people with multiple sclerosis (PwMS). VEPs may also reflect broader neural disturbances that extend beyond the visual system, but this possibility requires further investigation. In the present study, we examined the hypothesis that delayed latency of the P100 component of the VEP would be associated with broader structural changes in the brain in PwMS. We obtained VEP latency for a standard pattern-reversal checkerboard stimulus paradigm, in addition to Magnetic Resonance Imaging (MRI) measures of whole brain volume (WBV), gray matter volume (GMV), white matter volume (WMV), and T2-weighted fluid attenuated inversion recovery (FLAIR) white matter lesion volume (FLV). Correlation analyses indicated that prolonged VEP latency was significantly associated with lower WBV, GMV, and WMV, and greater FLV. VEP latency remained significantly associated with WBV, GMV, and WMV even after controlling for the variance associated with inter-ocular latency, age, time between VEP and MRI assessments, and other MRI variables. VEP latency delays were most pronounced in PwMS that exhibited low volume in both white and gray matter simultaneously. Furthermore, PwMS that had delayed VEP latency based on a clinically relevant cutoff (VEP latency ≥ 113 ms) in both eyes had lower WBV, GMV, and WMV and greater FLV in comparison to PwMS that had normal VEP latency in one or both eyes. The findings suggest that PwMS that have delayed latency in both eyes may be particularly at risk for exhibiting greater brain atrophy and lesion volume. These analyses also indicate that VEP latency may index combined gray matter and white matter disturbances, and therefore broader network connectivity and efficiency. VEP latency may therefore provide a surrogate marker of broader structural disturbances in the brain in MS.

Low Serum Insulin-like Growth Factor-I Is Associated with Decline in Hippocampal Volume in Stable Mild Cognitive Impairment but not in Alzheimer’s Disease

Background:Serum insulin-like growth factor-I (IGF-I) has shown some association with hippocampal volume in healthy subjects, but this relation has not been investigated in stable mild cognitive impairment (sMCI) or Alzheimer’s disease (AD).Objective:At a single memory clinic, we investigated whether serum IGF-I was associated with baseline magnetic resonance imaging (MRI)-estimated brain volumes and longitudinal alterations, defined as annualized changes, up to 6 years of follow-up.Methods:A prospective study of patients with sMCI (n = 110) and AD (n = 60). Brain regions included the hippocampus and amygdala as well as the temporal, parietal, frontal, and occipital lobes, respectively.Results:Serum IGF-I was statistically similar in sMCI and AD patients (112 versus 123 ng/mL, p = 0.31). In sMCI, serum IGF-I correlated positively with all baseline MRI variables except for the occipital lobe, and there was also a positive correlation between serum IGF-I and the annualized change in hippocampal volume (rs = 0.32, p = 0.02). Furthermore, sMCI patients having serum IGF-I above the median had lower annual loss of hippocampal volume than those with IGF-I below the median (p = 0.02). In contrast, in AD patients, IGF-I did not associate with baseline levels or annualized changes in brain volumes.Conclusion:In sMCI patients, our results suggest that IGF-I exerted neuroprotective effects on the brain, thereby maintaining hippocampal volume. In AD, serum IGF-I did not associate with brain volumes, indicating that IGF-I could not induce neuroprotection in this disease. This supports the notion of IGF-I resistance in AD.

Predictive Scale for Amyloid PET Positivity Based on Clinical and MRI Variables in Patients with Amnestic Mild Cognitive Impairment.

The presence of amyloid-β (Aβ) deposition is considered important in patients with amnestic mild cognitive impairment (aMCI), since they can progress to Alzheimer’s disease dementia. Amyloid positron emission tomography (PET) has been used for detecting Aβ deposition, but its high cost is a significant barrier for clinical usage. Therefore, we aimed to develop a new predictive scale for amyloid PET positivity using easily accessible tools. Overall, 161 aMCI patients were recruited from six memory clinics and underwent neuropsychological tests, brain magnetic resonance imaging (MRI), apolipoprotein E (APOE) genotype testing, and amyloid PET. Among the potential predictors, verbal and visual memory tests, medial temporal lobe atrophy, APOE genotype, and age showed significant differences between the Aβ-positive and Aβ-negative groups and were combined to make a model for predicting amyloid PET positivity with the area under the curve (AUC) of 0.856. Based on the best model, we developed the new predictive scale comprising integers, which had an optimal cutoff score ≥ 3. The new predictive scale was validated in another cohort of 98 participants and showed a good performance with AUC of 0.835. This new predictive scale with accessible variables may be useful for predicting Aβ positivity in aMCI patients in clinical practice.

Effects of Vascular Comorbidity on Cognition in Multiple Sclerosis Are Partially Mediated by Changes in Brain Structure.

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.

Superiority of Brain and Spinal Injury Center Score for Assessing Injury Severity and Predicting Prognosis in Patients with Acute Traumatic Spinal Cord Injury.

The goal of this study was to evaluate the interrelationship between different magnetic resonance (MR) imaging measures and their validity in assessing the severity of acute traumatic spinal cord injury (tSCI) and predicting neurological outcomes. We performed apreoperative multicenter cohort study of 89patients with acute tSCI and preoperative MR imaging within 24 h after injury. We assessed several MR imaging measures of injury, including axial grade (Brain and Spinal Injury Center [BASIC] score), sagittal grade, length of injury, maximum canal compromise (MCC), and maximum spinal cord compression (MSCC). Principal component analysis (PCA) was applied to evaluate the interrelationship between different MR imaging measures. Spearman correlation and regression analyses were applied to assess injury severity and predict neurological impairment. The severity was assessed by the American Spinal Injury Association Impairment Scale (AIS) at admission, while neurological outcome was defined by AIS grade change at 6weeks, AIS grade and SCIM score at 1 year after surgery. The PCA identified 2clusters of MR imaging variables related to 1)measures of intrinsic cord signal abnormality (BASIC score, sagittal grade and length of injury) and 2)measures of extrinsic cord compression (MCC and MSCC). Neurological outcome and injury severity were best accounted for by MR imaging measures of intrinsic cord signal abnormalities, with the BASIC score representing the most accurate predictor of short-term and long-term neurological outcomes. We determined the superior significance of the BASIC score in assessing injury severity, predicting early AIS improvement, AIS grade and SCIM score at 1year compared with other MR imaging measures.

Magnetic resonance imaging adds prognostic value to EEG after pediatric cardiac arrest

AimTo investigate how combined electrographic and radiologic data inform outcomes in children after cardiac arrest. MethodsRetrospective observational study of children admitted to the pediatric intensive care unit (PICU) of a tertiary children’s hospital with diagnosis of cardiac arrest from 2009 to 2016. The first 20 min of electroencephalogram (EEG) background was blindly scored. Presence and location of magnetic resonance imaging (MRI) diffusion-weighted image (DWI) abnormalities were correlated with T2-weighted signal. Outcomes were categorized using Pediatric Cerebral Performance Category (PCPC) scores at hospital discharge, with “poor outcome” reflecting a PCPC score of 4–6. Logistic regression models examined the association of EEG and MRI variables with outcome. Results41 children met inclusion criteria and had both post-arrest EEG monitoring within 72 hours after ROSC and brain MRI performed within 8 days. Among the 19 children with poor outcome, 10 children did not survive to discharge. Severely abnormal EEG background (p < 0.0001) and any diffusion restriction (p < 0.0001) were associated with poor outcome. The area under the ROC curve (AUC) for identifying outcome based on EEG background alone was 0.86, which improved to 0.94 with combined EEG and MRI data (p = 0.02). ConclusionDiffusion abnormalities on MRI within 8 days after ROSC add to the prognostic value of EEG background in children surviving cardiac arrest.