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Patients with functional constipation (FCon) often suffer from mental and psychological problems. To explore the possible neurological interaction, we used resting-state functional magnetic imaging (RS-fMRI) to compare the alterations in intrinsic brain functional networks at multiple levels between patients with FCon and healthy controls (HC).Twenty-eight patients with FCon and twenty-nine HC were recruited for a series of examinations and RS-fMRI. Both graph theory analysis and functional connectivity (FC) analysis were used to investigate brain functional alterations between the two groups. Correlation analyses were performed among neuropsychological scores, clinical indexes, and neuroimaging data.Compared with the HC, the assortativity showed significantly increased in global level in patients with FCon. In regional level, we found obviously increased nodal degree and nodal efficiency in somatosensory network (SMN), decreased nodal degree, and increased nodal efficiency in default mode network (DMN) in the FCon group. Furthermore, FC analysis demonstrated several functional alterations within and between the networks, particularly including the SMN and visual network (VN) in sub-network and large-scale network analysis. Moreover, correlation analysis indicated that nodal metrics and aberrant FC among functional brain networks were associated with emotion and scores of constipation in patients with FCon.All these findings reflect the differences in intrinsic brain functional networks between FCon and HC. Our study highlighted SMN, DMN, and VN as critical network and may be involved in the neurophysiology of FCon, which may contribute to improve personalized treatment in patients with FCon.

Depression is a common occurrence in patients with Parkinson's disease (PD); however, its pathophysiology is still unclear. This study assessed the association between the integrity of white matter and depressive symptoms in patients with PD. 67 patients with PD were divided into a non-depressed PD group (ndPD, n = 30) and a depressed PD group (dPD, n = 37). The dPD group was further subdivided into a mild-moderately depressed PD (mdPD, n = 22) and a severely depressed PD group (sdPD, n = 15). Tract-Based Spatial Statistics was used to compare fractional anisotropy (FA) between groups. Region-of-interest analysis was used to explore changes in diffusivity indices in the regions showing FA abnormalities. The sdPD patients exhibited significantly reduced FA in the left superior longitudinal fasciculus, uncinate fasciculus, anterior corona radiata, corticospinal tract, and bilateral inferior fronto-occipital fasciculus when compared with the ndPD patients, but the decreased FA was within a smaller area when compared with the mdPD patients. No significant difference in FA was found between the mdPD and ndPD groups. Among the dPD patients, FA values in the left superior longitudinal fasciculus negatively correlated with BDI scores. Impaired white matter integrity in the prefronto-limbic/temporal circuitry, mainly in the left hemisphere, is associated with severe, but not mild-moderate depressive symptoms in patients with PD.

Background: The dural venous sinuses (DVS), in general, are frequently asymmetrical and display far more anatomical variations than arterial systems. A comprehensive study of the anatomy and variants of the DVS can help surgeons in the preoperative evaluation and management as well as minimizing possible complications in the following treatment. Methods: The current review was designed to provide a general overview of the normal anatomy and notable variants of the cerebral venous system as surveyed from the available literature. The pros and cons of different multimodal imaging methods for investigating DVS are also outlined. Finally, cases of various pathological entities are illustrated from our clinical practice. Conclusion: There are many anatomical variations and lesions involving the DVS. MRI examination can provide essential information both on anatomical variation and morphological or functional change of the offending DVS in most circumstances. Multimodal non-invasive venography protocols may become a feasible alternative to the classical digital subtraction angiography and would improve the diagnostic accuracy in future studies.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted ‘gold-standard’ subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Funder: National Institute for Health Research (NIHR) GOSH BRC, OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.

IntroductionOne outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualise on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide.MethodsThe Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonised a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance.ResultsOur pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. Overall, after including a border-zone around lesions, the developed MELD FCD surface-based algorithm had a sensitivity of 67% and a specificity of 54% on the withheld test cohort, and a sensitivity of 85% on a restricted subcohort of seizure free patients with FCD type IIB who had T1 and FLAIR MRI data.ConclusionsThis multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions.HighlightsThis large, multi-centre, multi-scanner neuroimaging cohort captures the heterogeneity of histopathological subtypes and imaging features of patients with FCD.We developed a robust and interpretable surface-based algorithm which detects FCDs with a sensitivity of 67% and a specificity of 54%.The algorithm generates individual patient reports that “open the AI black-box” highlighting predicted lesion locations, alongside the imaging features and their relative saliency to the classifier.

At present, it is still challenging to predict the clinical outcome of acute ischemic stroke (AIS). In this retrospective study, we explored whether radiomics features extracted from fluid-attenuated inversion recovery (FLAIR) and apparent diffusion coefficient (ADC) images can predict clinical outcome of patients with AIS. Patients with AIS were divided into a training (n = 110) and an external validation (n = 80) sets. A total of 753 radiomics features were extracted from each FLAIR and ADC image of the 190 patients. Interquartile range (IQR), Wilcoxon rank sum test, and least absolute shrinkage and selection operator (LASSO) were used to reduce the feature dimension. The six strongest radiomics features were related to an unfavorable outcome of AIS. A logistic regression analysis was employed for selection of potential predominating clinical and conventional magnetic resonance imaging (MRI) factors. Subsequently, we developed several models based on clinical and conventional MRI factors and radiomics features to predict the outcome of AIS patients. For predicting unfavorable outcome [modified Rankin scale (mRS) > 2] in the training set, the area under the receiver operating characteristic curve (AUC) of ADC radiomics model was 0.772, FLAIR radiomics model 0.731, ADC and FLAIR radiomics model 0.815, clinical model 0.791, and clinical and conventional MRI model 0.782. In the external validation set, the AUCs for the prediction with ADC radiomics model was 0.792, FLAIR radiomics model 0.707, ADC and FLAIR radiomics model 0.825, clinical model 0.763, and clinical and conventional MRI model 0.751. When adding radiomics features to the combined model, the AUCs for predicting unfavorable outcome in the training and external validation sets were 0.926 and 0.864, respectively. Our results indicate that the radiomics features extracted from FLAIR and ADC can be instrumental biomarkers to predict unfavorable clinical outcome of AIS and would additionally improve predictive performance when adding to combined model.

BACKGROUND AND PURPOSE: The relationship between brain β-amyloid and regional atrophy is still incompletely understood in elderly individuals at risk of dementia. Here, we studied the associations between brain β-amyloid load and regional GM and WM volumes in older adults who were clinically evaluated as being at increased risk of cognitive decline based on cardiovascular risk factors. MATERIALS AND METHODS: Forty subjects (63–81 years of age) were recruited as part of a larger study, the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability. Neuroimaging consisted of PET using (11)C Pittsburgh compound-B and T1-weighted 3D MR imaging for the measurement of brain β-amyloid and GM and WM volumes, respectively. All subjects underwent clinical, genetic, and neuropsychological evaluations for the assessment of cognitive function and the identification of cardiovascular risk factors. RESULTS: Sixteen subjects were visually evaluated as showing cortical β-amyloid (positive for β-amyloid). In the voxel-by-voxel analyses, no significant differences were found in GM and WM volumes between the samples positive and negative for β-amyloid. However, in the sample positive for β-amyloid, increases in (11)C Pittsburgh compound-B uptake were associated with reductions in GM volume in the left prefrontal (P = .02) and right temporal lobes (P = .04). CONCLUSIONS: Our results show a significant association between increases in brain β-amyloid and reductions in regional GM volume in individuals at increased risk of cognitive decline. This evidence is consistent with a model in which increases in β-amyloid incite neurodegeneration in memory systems before cognitive impairment manifests.

Copyright © 2021– The authors. Background: How the relationship between obesity and MRI-defined neural properties varies across distinct stages of cognitive impairment due to Alzheimer’s disease is unclear. Objective: We used multimodal neuroimaging to clarify this relationship. Methods: Scans were acquired from 47 patients clinically diagnosed with mild Alzheimer’s disease dementia, 68 patients with mild cognitive impairment, and 57 cognitively healthy individuals. Voxel-wise associations were run between maps of gray matter volume, white matter integrity, and cerebral blood flow, and global/visceral obesity. Results: Negative associations were found in cognitively healthy individuals between obesity and white matter integrity and cerebral blood flow of temporo-parietal regions. In mild cognitive impairment, negative associations emerged in frontal, temporal, and brainstem regions. In mild dementia, a positive association was found between obesity and gray matter volume around the right temporoparietal junction. Conclusion: Obesity might contribute toward neural tissue vulnerability in cognitively healthy individuals and mild cognitive impairment, while a healthy weight in mild Alzheimer’s disease dementia could help preserve brain structure in the presence of age and disease-related weight loss. European Union Seventh Framework Programme (FP7/2007– 2013) under grant agreement no. 601055, VPH-DARE@IT; Neurocare; University of Sheffield, Faculty of Medicine, Dentistry and Health PhD scholarship.

Accurately and quickly differentiating true progression from pseudoprogression in glioma patients is still a challenge. This study aims to explore if dynamic susceptibility contrast- (DSC-) MRI can improve the evaluation of glioma progression. We enrolled 65 glioma patients with suspected gadolinium-enhancing lesion. Longitudinal MRI follow-up (mean 590 days, range: 210–2670 days) or re-operation (n = 3) was used to confirm true progression (n = 51) and pseudoprogression (n = 14). We assessed the diagnostic performance of each MRI variable and the different combinations. Our results showed that the relative cerebral blood volume (rCBV) in the true progression group (1.094, 95%CI: 1.135–1.636) was significantly higher than that of the pseudoprogression group (0.541 ± 0.154) p < 0.001 . Among the 18 patients who had serial DSC-MRI, the rCBV of the progression group (0.480, 95%CI: 0.173–0.810) differed significantly from pseudoprogression (-0.083, 95%CI: −1.138–0.620) group p = 0.015 . With an rCBV threshold of 0.743, the sensitivity and specificity for discriminating true progression from pseudoprogression were 76.5% and 92.9%, respectively. The Cho/Cr and Cho/NAA ratios of the true progression group (2.520, 95%CI: 2.331–2.773; 2.414 ± 0.665, respectively) were higher than those of the pseudoprogression group (1.719 ± 0.664; 1.499 ± 0.500, respectively) ( p = 0.001 , p < 0.001 , respectively). The areas under ROC curve (AUCs) of enhancement pattern, MRS, and DSC-MRI for the differentiation were 0.782, 0.881, and 0.912, respectively. Interestingly, when combined enhancement pattern, MRS, and DSC-MRI variables, the AUC was 0.965 and achieved sensitivity 90.2% and specificity 100.0%. Our results suggest that DSC-MRI can significantly improve the diagnostic performance for identifying glioma progression. DSC-MRI combined with conventional MRI may promptly distinguish true gliomas progression from pseudoprogression when the suspected gadolinium-enhancing lesion was found, without the need for a long-term follow-up.

Objectives. The respiration could decrease the time synchronization between odor stimulation and data acquisition, consequently deteriorating the functional activation and hemodynamic response function (HRF) in olfactory functional magnetic resonance imaging (fMRI) with a conventional repetition time (TR). In this study, we aimed to investigate whether simultaneous multislice (SMS) technology with reduced TR could improve the blood oxygen level-dependent (BOLD) activation and optimize HRF modeling in olfactory fMRI. Methods. Sixteen young healthy subjects with normal olfaction underwent olfactory fMRI on a 3T MRI scanner using a 64 channel head coil. FMRI data were acquired using SMS acceleration at three different TRs: 3000 ms, 1000 ms, and 500 ms. Both metrics of BOLD activation (activated voxels, mean, and maximum t -scores) and the HRF modeling (response height and time to peak) were calculated in the bilateral amygdalae, hippocampi, and insulae. Results. The 500 ms and 1000 ms TRs both significantly improved the number of activated voxels, mean, and maximum t -score in the amygdalae and insulae, compared with a 3000 ms TR (all P < 0.05 ). But the increase of these metrics in the hippocampi did not reach a statistical significance (all P > 0.05 ). No significant difference in any BOLD activation metrics between TR 500 ms and 1000 ms was observed in all regions of interest (ROIs) (all P > 0.05 ). The HRF curves showed that higher response height and shorter time to peak in all ROIs were obtained at 500 ms and 1000 ms TRs compared to 3000 ms TR. TR 500 ms had a more significant effect on response height than TR 1000 ms in the amygdalae ( P = 0.017 ), and there was no significant difference in time to peak between TR 500 ms and 1000 ms in all ROIs (all P > 0.05 ). Conclusions. The fast image acquisition technique of SMS with reduced TR could significantly improve the functional activation and HRF curve in olfactory fMRI.

The imaging signs which can accurately predict survival prognosis after standard treatment of high-grade glioma (HGG) are highly desirable. This study aims to explore the role of new enhancement beyond radiation field (NERF) in the survival prediction in patients with post-treatment HGG. The present study included 142 pathologically confirmed HGG patients who had received standard treatment. NERF, as well as other conventional MR findings and clinical variables, were included in univariate and multivariate analyses for evaluating their impactions on progression-free survival (PFS) and overall survival (OS). Univariate analysis showed that histological grade ( p = 0.008 ) and NERF ( p = 0.001 ) were the prognostic variables for poor PFS, whereas histological grade ( p = 0.017 ), NERF ( p = 0.001 ), and new subventricular zone enhancement (nSVZE) ( p = 0.001 ) were prognostic variables for poor OS. The multivariate analysis showed that NERF (HR 3.93; 95% CI 1.93–8.01; p = 0.001 ) and nSVZE (HR 3.92; 95% CI 1.95–7.89; p = 0.001 ) were the prognostic variables for poor OS. However, only nSVZE was (HR 3.29; 95% CI 2.04–5.28; p = 0.001 ) the prognostic variable for poor PFS. When combining the NERF with the clinical and other MR variables, the highest AUC (0.924) and specificity (0.899) for predicting poor OS were achieved. The location of new developed enhancements relevant to high dose radiation field appears to be the main determinant of their prognostic value. Our results suggest that the new enhancement beyond radiation field can improve the survival prediction in patients with HGG after standard treatment.

Background: Early pathological changes in white matter microstructure can be studied using the diffusion tensor imaging (DTI). It is not only important to study these subtle pathological changes leading to cognitive decline, but also to ascertain how an intervention would impact the white matter microstructure and cognition in persons at-risk of dementia. Objectives: To study the impact of a multidomain lifestyle intervention on white matter and cognitive changes during the 2-year Finnish Geriatric Intervention Study to prevent Cognitive Impairment and Disability (FINGER), a randomized controlled trial in at-risk older individuals (age 60–77 years) from the general population. Methods: This exploratory study consisted of a subsample of 60 FINGER participants. Participants were randomized to either a multidomain intervention (diet, exercise, cognitive training, and vascular risk management, n = 34) or control group (general health advice, n = 26). All underwent baseline and 2-year brain DTI. Changes in fractional anisotropy (FA), diffusivity along domain (F1) and non-domain (F2) diffusion orientations, mean diffusivity (MD), axial diffusivity (AxD), radial diffusivity (RD), and their correlations with cognitive changes during the 2-year multidomain intervention were analyzed. Results: FA decreased, and cognition improved more in the intervention group compared to the control group (p

The importance of early interventions in Alzheimer’s disease (AD) emphasizes the need to accurately and efficiently identify at-risk individuals. Although many dementia prediction models have been developed, there are fewer studies focusing on detection of brain pathology. We developed a model for identification of amyloid-PET positivity using data on demographics, vascular factors, cognition, APOE genotype, and structural MRI, including regional brain volumes, cortical thickness and a visual medial temporal lobe atrophy (MTA) rating. We also analyzed the relative importance of different factors when added to the overall model. The model used baseline data from the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) exploratory PET sub-study. Participants were at risk for dementia, but without dementia or cognitive impairment. Their mean age was 71 years. Participants underwent a brain 3T MRI and PiB-PET imaging. PiB images were visually determined as positive or negative. Cognition was measured using a modified version of the Neuropsychological Test Battery. Body mass index (BMI) and hypertension were used as cardiovascular risk factors in the model. Demographic factors included age, gender and years of education. The model was built using the Disease State Index (DSI) machine learning algorithm. Of the 48 participants, 20 (42%) were rated as Aβ positive. Compared with the Aβ negative group, the Aβ positive group had a higher proportion of APOE ε4 carriers (53 vs. 14%), lower executive functioning, lower brain volumes, and higher visual MTA rating. AUC [95% CI] for the complete model was 0.78 [0.65–0.91]. MRI was the most effective factor, especially brain volumes and visual MTA rating but not cortical thickness. APOE was nearly as effective as MRI in improving detection of amyloid positivity. The model with the best performance (AUC 0.82 [0.71–0.93]) was achieved by combining APOE and MRI. Our findings suggest that combining demographic data, vascular risk factors, cognitive performance, APOE genotype, and brain MRI measures can help identify Aβ positivity. Detecting amyloid positivity could reduce invasive and costly assessments during the screening process in clinical trials.

Background: Cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) biomarkers of neurodegenerative diseases are relatively sensitive and specific in highly curated research cohorts, but proper validation for clinical use is mostly missing. Objective: We studied these biomarkers in a novel memory clinic cohort with a variety of different neurodegenerative diseases. Methods: This study consisted of 191 patients with subjective or objective cognitive impairment who underwent neurological, CSF biomarker (Aβ42, p-tau, and tau) and T1-weighted MRI examinations at Kuopio University Hospital. We assessed CSF and imaging biomarkers, including structural MRI focused on volumetric and cortical thickness analyses, across groups stratified based on different clinical diagnoses, including Alzheimer’s disease (AD), frontotemporal dementia, dementia with Lewy bodies, Parkinson’s disease, vascular dementia, and mild cognitive impairment (MCI), and subjects with no evidence of neurodegenerative disease underlying the cognitive symptoms. Imaging biomarkers were also studied by profiling subjects according to the novel amyloid, tau, and, neurodegeneration (AT(N)) classification. Results: Numerous imaging variables differed by clinical diagnosis, including hippocampal, amygdalar and inferior lateral ventricular volumes and entorhinal, lingual, inferior parietal and isthmus cingulate cortical thicknesses, at a false discovery rate (FDR)-corrected threshold for significance (analysis of covariance; p

Aims To investigate the relationship between peripheral leukocyte dynamics and the outcome of large hemispheric infarction (LHI) patients. Methods Patients with acute LHI admitted to the neuro‐intensive care unit of Xuanwu Hospital from 2013 to 2017 were prospectively enrolled and followed up for 6 months after LHI. Results A total of 84 LHI patients were included, 38 patients suffered brain herniation and 20 patients died from stroke. Compared to patients with benign course, LHI patients with fatal outcome showed larger infarcts and more severe brain edema (P 7.14 × 109/L had higher risk of brain herniation [odds ratio (OR) = 7.5, 95% CI: 2.0‐28.1, P = .001], and patients with D2 neutrophils > 7.79 × 109/L had a higher risk of death (OR = 5.8, 95% CI: 1.2‐27.0, P = .015). Conclusion Early peripheral neutrophil count after stroke relates to infarct size and the fatal outcome of LHI patients, which might help guiding acute LHI management such as reduction of intracranial pressure and potential antiinflammatory therapy in the future.

Background Giant cell reparative granuloma (GCRG) is a rare benign tumor. The jawbone is the most common site of occurrence, followed by sphenoid bone, craniofacial bone, hand and foot bones. The etiology of GCRG is unknown but may be related to an intraosseous hemorrhage following trauma. Despite its benign nature, it could be locally aggressive. To our knowledge, no spinal epidural GCRG case has been reported. Case Description A case of man aged 32 years who presented with upper right limb numbness and weakness. Computed tomography showed a round soft tissue mass in the spinal canal at the C7-T1 level. The mass showed isointensity on T1-weighted images, hypointensity on T2-weighted images, and significant enhancement on postcontrast T1-weighted images. The mass localized in the epidural space and was surgically resected. The histologic diagnosis was consistent with GCRG. Conclusions Spinal epidural GCRG is rare and is hardly considered in the differential diagnosis. Preoperative diagnosis of GCRG is challenging, and the definitive diagnosis could only be made by pathological examination. Surgical resection is probably an effective therapy for relief of symptoms.

ObjectiveTo investigate brain amyloid pathology in a dementia-risk population defined as cardiovascular risk factors, aging, and dementia risk (CAIDE) score of at least 6 but with normal cognition and to examine associations between brain amyloid load and cognitive performance and vascular risk factors.MethodsA subgroup of 48 individuals from the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) main study participated in brain 11C-Pittsburgh compound B (PiB)-PET imaging, brain MRI, and neuropsychological assessment at the beginning of the study. Lifestyle/vascular risk factors were determined as body mass index, blood pressure, total and low-density lipoprotein cholesterol, and glucose homeostasis model assessment. White matter lesions were visually rated from MRIs by a semiquantitative Fazekas score.ResultsTwenty participants (42%) had a positive PiB-PET on visual analysis. The PiB-positive group performed worse in executive functioning tests, included more participants with APOE ε4 allele (50%), and showed slightly better glucose homeostasis compared to PiB-negative participants. PiB-positive and -negative participants did not differ significantly in other cognitive domain scores or other vascular risk factors. There was no significant difference in Fazekas score between the PiB groups.ConclusionsThe high percentage of PiB-positive participants provides evidence of a successful recruitment process of the at-risk population in the main FINGER intervention trial. The results suggest a possible association between early brain amyloid accumulation and decline in executive functions. APOE ε4 was clearly associated with amyloid positivity, but no other risk factor was found to be associated with positive PiB-PET.

Background Nutrition is an important modifiable risk factor in Alzheimer's disease. Previous trials of the multinutrient Fortasyn Connect showed benefits in mild Alzheimer's disease dementia. LipiDiDiet investigated the effects of Fortasyn Connect on cognition and related measures in prodromal Alzheimer's disease. Here, we report the 24-month results of the trial. Methods LipiDiDiet was a 24-month randomised, controlled, double-blind, parallel-group, multicentre trial (11 sites in Finland, Germany, the Netherlands, and Sweden), with optional 12-month double-blind extensions. The trial enrolled individuals with prodromal Alzheimer's disease, defined according to the International Working Group (IWG)-1 criteria. Participants were randomly assigned (1:1) to active product (125 mL once-a-day drink containing Fortasyn Connect) or control product. Randomisation was computer-generated centrally in blocks of four, stratified by site. All study personnel and participants were masked to treatment assignment. The primary endpoint was change in a neuropsychological test battery (NTB) score. Analysis was by modified intention to treat. Safety analyses included all participants who consumed at least one study product dose. This trial is registered with the Dutch Trial Register, number NTR1705. Findings Between April 20, 2009, and July 3, 2013, 311 of 382 participants screened were randomly assigned to the active group (n=153) or control group (n=158). Mean change in NTB primary endpoint was −0·028 (SD 0·453) in the active group and −0·108 (0·528) in the control group; estimated mean treatment difference was 0·098 (95% CI −0·041 to 0·237; p=0·166). The decline in the control group was less than the prestudy estimate of −0·4 during 24 months. 66 (21%) participants dropped out of the study. Serious adverse events occurred in 34 (22%) participants in the active group and 30 (19%) in control group (p=0·487), none of which were regarded as related to the study intervention. Interpretation The intervention had no significant effect on the NTB primary endpoint over 2 years in prodromal Alzheimer's disease. However, cognitive decline in this population was much lower than expected, rendering the primary endpoint inadequately powered. Group differences on secondary endpoints of disease progression measuring cognition and function and hippocampal atrophy were observed. Further study of nutritional approaches with larger sample sizes, longer duration, or a primary endpoint more sensitive in this pre-dementia population, is needed., published version, peerReviewed

Alcohol-related white matter (WM) microstructural changes have not been fully elucidated in adolescents. We aimed to investigate influences of subclinical alcohol use during adolescence on WM microstructure and to characterize those with serum metabolic alterations. 35 moderate-to-heavy drinkers (15 males, 20 females) and 27 controls (12 males, 15 females) were selected based on their ten-year Alcohol Use Disorders Identification Test scores measured at three time points. Magnetic resonance imaging was conducted at endpoint time. Whole brain analysis of fractional anisotropy (FA) was performed. Diffusivity indices in the significant regions were computed for between-group comparisons and correlation analyses with serum metabolite concentrations. Decreased FA was found in moderate-to-heavy drinking men in anterior corpus callosum, superior/anterior corona radiata and right inferior fronto-occipital fasciculus, accompanied by increased radial diffusivity and a smaller area of reduced axial diffusivity, which correlated with serum metabolites playing roles in energy metabolism, myelination and axonal degeneration. No significant difference in FA was detected between female or mixed-gender moderate-to-heavy drinking subjects and controls, supporting gender differences in the relationship between adolescent alcohol use and neurodevelopmental trajectories. Future researches with longitudinal imaging data are warranted for comprehensive evaluation on potentially reversible effects of alcohol use over adolescent brain.

Background The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) was a multicenter randomized controlled trial that reported beneficial effects on cognition for a 2-year multimodal intervention (diet, exercise, cognitive training, vascular risk monitoring) versus control (general health advice). This study reports exploratory analyses of brain MRI measures. Methods FINGER targeted 1260 older individuals from the general Finnish population. Participants were 60–77 years old, at increased risk for dementia but without dementia/substantial cognitive impairment. Brain MRI scans were available for 132 participants (68 intervention, 64 control) at baseline and 112 participants (59 intervention, 53 control) at 2 years. MRI measures included regional brain volumes, cortical thickness, and white matter lesion (WML) volume. Cognition was assessed at baseline and 1- and 2-year visits using a comprehensive neuropsychological test battery. We investigated the (1) differences between the intervention and control groups in change in MRI outcomes (FreeSurfer 5.3) and (2) post hoc sub-group analyses of intervention effects on cognition in participants with more versus less pronounced structural brain changes at baseline (mixed-effects regression models, Stata 12). Results No significant differences between the intervention and control groups were found on the changes in MRI measures. Beneficial intervention effects on processing speed were more pronounced in individuals with higher baseline cortical thickness in Alzheimer’s disease signature areas (composite measure of entorhinal, inferior and middle temporal, and fusiform regions). The randomization group × time × cortical thickness interaction coefficient was 0.198 (p = 0.021). A similar trend was observed for higher hippocampal volume (group × time × hippocampus volume interaction coefficient 0.1149, p = 0.085). Conclusions The FINGER MRI exploratory sub-study did not show significant differences between the intervention and control groups on changes in regional brain volumes, regional cortical thicknesses, or WML volume after 2 years in at-risk elderly without substantial impairment. The cognitive benefits on processing speed of the FINGER intervention may be more pronounced in individuals with fewer structural brain changes on MRI at baseline. This suggests that preventive strategies may be more effective if started early, before the occurrence of more pronounced structural brain changes. Trial registration ClinicalTrials.gov, NCT01041989. Registered January 5, 2010.

Purpose To evaluate the diagnostic efficacy of virtual touch tissue quantification (VTQ) and contrast-enhanced ultrasonography (CEUS), separately and in combination, in diagnosing malignant focal liver lesions (FLLs). Methods Forty-six patients with 55 FLLs (28 benign and 27 malignant) underwent both VTQ and CEUS. The diagnostic values of VTQ and CEUS, alone and in combination, were compared. Results The diagnostic sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of CEUS were 92.6% (25/27), 96.4% (27/28), 94.5% (52/55), 96.2% (25/26), and 93.1% (27/29), respectively. The diagnostic sensitivity, specificity, accuracy, PPV, and NPV of VTQ with a cutoff of 2.22 m/s were 51.9% (14/27), 85.7% (24/28), 69.1% (38/55), 77.8% (14/18), and 64.9% (24/37), respectively. The diagnostic sensitivity, specificity, accuracy, PPV, and NPV of VTQ and CEUS combined were 96.3% (26/27), 82.1% (23/28), 89.1% (49/55), 83.9% (26/31), and 95.8% (23/24), respectively. Comparing the accuracies of the three methods, the diagnostic values of CEUS and of the combination of CEUS with VTQ were significantly higher than those of VTQ alone (p ≤ 0.01). There was no significant difference between the combination of CEUS with VTQ and CEUS (p = 0.49). Conclusions CEUS is superior to VTQ in diagnosing malignant FLLs. Adding VTQ to CEUS did not improve the diagnosis of FLLs. © 2016 Wiley Periodicals, Inc. J Clin Ultrasound, 2016

Background Evaluating the acute ischemic volume on diffusion-weighted imaging (DWI) in the middle cerebral artery (MCA) territory would predict outcome. Purpose To investigate the correlations between maximum area with restricted diffusion (MaxA), the orthogonal diameters (OD) as well as lesion volume on DWI, and to explore the role of MaxA and OD on predicting unfavorable outcome after an acute MCA ischemic stroke. Material and Methods Sixty consecutive adult patients, including modified Rankin Scale score (mRS) ≤2 (n = 31) and mRS > 2 (n = 29) groups, were retrospectively enrolled. The MaxA and OD of lesions were assessed at the slice containing the largest infarction size on DWI images. We compared the prediction efficiencies of these methods on unfavorable outcomes. Results The correlation coefficients between the MaxA and infarction volume and OD and infarction volume were 0.982 ( P 2 for MaxA, and ≥38.1 for the arithmetic product of OD, the AUCs of infarction volume, MaxA, and OD for predicting an unfavorable outcome were 0.818, 0.821, and 0.820, respectively. Conclusion Since they correlated well with the infarction volume, MaxA and OD assessed on DWI were time-saving and achieved comparable diagnostic efficiencies; thus, they may represent alternative imaging markers for predicting unfavorable outcomes of acute ischemic stroke in MCA territory.

The carcinoembryonic antigen, glypican‑3 (GPC3), is a putative therapeutic target and diagnostic marker of hepatoma. In the present study, a monoclonal antibody (mAb) specifically against GPC3 was obtained via cloning the sequence of GPC3 via polymerase chain reaction and inserting it into a pET16b vector prior to transfection into Escherichia coli (E. coli) BL21. BALB/c mice were immunized with 20 µg purified antigen by intrasplenic embedding. Splenocytes and mouse myeloma cells SP2/0 were fused; then, the hybridoma cells were screened by an indirect ELISA. The properties of the mAb were examined by western blotting and immunofluorescence analysis against the purified protein. The results revealed that the prokaryotic expression vector of GPC3 had been successfully generated and GPC3 was stably expressed in E. coli BL21. A stable hybridoma cell line, 2F3, was generated in the present study, which produced mAbs against GPC3. The mAb 2F3 had a high antibody titer and the isotype was identified as IgG1/κ; 2F3 hybridomas had a median chromosome number of 98. Western blot and immunofluorescence analyses revealed that 2F3 specifically recognized recombinant and native GPC3. The 2F3 clone was proposed as a stable secretor of this mAb against GPC3. The results of present study indicated that the successful preparation of recombinant GPC3 protein and an anti‑human GPC3 mouse mAb may be provide a basis for developments in the diagnosis and treatment of liver cancer.

Ewing sarcoma/peripheral primitive neuroectodermal tumors (ES/pPNET), a member of the Ewing sarcoma family of tumors, is a malignant soft tissue tumor with small undifferentiated neuroectodermal cells. Primary trachea-bronchial ES/pPNET is very rare. The most common pulmonary ES is due to a metastasis. We describe a case of ES/pPNET which originated in the left basal trunk bronchus. The patient was a 30-year-old male, presenting with irritable cough and fever for 10 days. A tumor of 60 mm in diameter was found in the left basal trunk bronchus, extending to the left lower lobe. No distant metastases were detected. Histopathological examination revealed a malignancy of ES/pPNET with a diffuse proliferation of round cells, a Flexner-Wintersteiner rosette formation and positive staining for CD99. The patient was successfully treated with a combination of left lower lobectomy and adjuvant chemotherapy and has remained disease-free for approximately 18 months at follow-up. This case highlights that ES/pPNET should be considered as a differential diagnosis in cases of trachea-bronchial tumors.

Aims: We assessed the value of automated MRI quantification methods in the differential diagnosis of behavioral-variant frontotemporal dementia (bvFTD) from Alzheimer disease (AD), Lewy body dementia (LBD), and subjective memory complaints (SMC). We also examined the role of the C9ORF72-related genetic status in the differentiation sensitivity. Methods: The MRI scans of 50 patients with bvFTD (17 C9ORF72 expansion carriers) were analyzed using 6 quantification methods as follows: voxel-based morphometry (VBM), tensor-based morphometry, volumetry (VOL), manifold learning, grading, and white-matter hyperintensities. Each patient was then individually compared to an independent reference group in order to attain diagnostic suggestions. Results: Only VBM and VOL showed utility in correctly identifying bvFTD from our set of data. The overall classification sensitivity of bvFTD with VOL + VBM achieved a total sensitivity of 60%. Using VOL + VBM, 32% were misclassified as having LBD. There was a trend of higher values for classification sensitivity of the C9ORF72 expansion carriers than noncarriers. Conclusion: VOL, VBM, and their combination are effective in differential diagnostics between bvFTD and AD or SMC. However, MRI atrophy profiles for bvFTD and LBD are too similar for a reliable differentiation with the quantification methods tested in this study.

Schizophrenia is characterized by the disorder of "social brain". However, the alternation of connectivity density in brain areas of schizophrenia patients remains largely unknown. In this study, we successfully created a rat model of schizophrenia by the transfection of EGR3 gene into rat brain. We then investigated the connectivity density of schizophrenia susceptible regions in rat brain using functional magnetic resonance imaging (fMRI) in combination with multivariate Granger causality (GC) model. We found that the average signal strength in prefrontal lobe and hippocampus of schizophrenia model group was significantly higher than the control group. Bidirectional Granger causality connection was observed between hippocampus and thalamic in schizophrenia model group. Both connectivity density and Granger causality connection were changed in prefrontal lobe, hippocampus and thalamus after risperidone treatment. Our results indicated that fMRI in combination with GC connection analysis may be used as an important method in diagnosis of schizophrenia and evaluation the effect of antipsychotic treatment. These findings support the connectivity disorder hypothesis of schizophrenia and increase our understanding of the neural mechanisms of schizophrenia. (C) 2015 The Authors. Published by Elsevier Inc.