Identifying the Alteration Patterns of Brain Functional Connectivity in Progressive Mild Cognitive Impairment Patients: A Longitudinal Whole-Brain Voxel-Wise Degree Analysis

Patients with mild cognitive impairment (MCI) are at high risk for developing Alzheimer’s disease (AD), while some of them may remain stable over decades. The underlying mechanism is still not fully understood. In this study, we aimed to explore the connectivity differences between progressive MCI (PMCI) and stable MCI (SMCI) individuals on a whole-brain scale and on a voxel-wise basis, and we also aimed to reveal the differential dynamic alternation patterns between these two disease subtypes. The resting-state functional magnetic resonance images of PMCI and SMCI patients at baseline and year-one were obtained from the Alzheimer’s Disease Neuroimaging Initiative dataset, and the progression was determined based on a three-year follow-up. A whole-brain voxel-wise degree map that was calculated based on graph-theory was constructed for each subject, and then the cross-sectional and longitudinal analyses on the degree maps were performed between PMCI and SMCI patients. In longitudinal analyses, compared with SMCI group, PMCI group showed decreased long-range degree in the left middle occipital/supramarginal gyrus, while the short-range degree was increased in the left supplementary motor area and middle frontal gyrus and decreased in the right middle temporal pole. A significant longitudinal alteration of decreased short-range degree in the right middle occipital was found in PMCI group. Taken together with previous evidence, our current findings may suggest that PMCI, compared with SMCI, might be a severe presentation of disease along the AD continuum, and the rapidly reduced degree in the right middle occipital gyrus may have indicative value for the disease progression. Moreover, the cross-sectional comparison results and corresponding receiver-operator characteristic-curves analyses may indicate that the baseline degree difference is not a good predictor of disease progression in MCI patients. Overall, these findings may provide objective evidence and an indicator to characterize the progression-related brain connectivity changes in MCI patients

Characterization of the Fiber Connectivity Profile of the Cerebral Cortex in Schizotypal Personality Disorder: A Pilot Study

Schizotypal personality disorder (SPD) is considered one of the classic disconnection syndromes. However, the specific cortical disconnectivity pattern has not been fully investigated. In this study, we aimed to explore significant alterations in whole-cortex structural connectivity in SPD individuals (SPDs) by combining the techniques of brain surface morphometry and white matter (WM) tractography. Diffusion and structural MR data were collected from twenty subjects with SPD (all males; age, 19.7 ± 0.9 yrs) and eighteen healthy controls (all males; age, 20.3 ± 1.0 yrs). To measure the structural connectivity for a given unit area of the cortex, the fiber connectivity density (FiCD) value was proposed and calculated as the sum of the fractional anisotropy of all the fibers connecting to that unit area in tractography. Then, the resultant whole-cortex FiCD maps were compared in a vertex-wise manner between SPDs and controls. Compared with normal controls, SPDs showed significantly decreased FiCD in the rostral middle frontal gyrus (crossing BA9 and BA10) and significantly increased FiCD in the anterior part of the fusiform/inferior temporal cortex (P < 0.05, Monte Carlo simulation corrected). Moreover, the gray matter volume extracted from the left rostral middle frontal cluster was observed to be significantly greater in the SPD group (P = 0.02). Overall, this study identifies a decrease in connectivity in the left middle frontal cortex as a key neural deficit at the whole-cortex level in SPD, thus providing insight into its neuropathological basis

Dynamic magnetic resonance imaging in assessing lung function in adolescent idiopathic scoliosis: a pilot study of comparison before and after posterior spinal fusion

<p>Abstract</p> <p>Background</p> <p>Restrictive impairment is the commonest reported pulmonary deficit in AIS, which improves following surgical operation. However, exact mechanism of how improvement is brought about is unknown. Dynamic fast breath-hold (BH)-MR imaging is a recent advance which provides direct quantitative visual assessment of pulmonary function. By using above technique, change in lung volume, chest wall and diaphragmatic motion in AIS patients before and six months after posterior spinal fusion surgery were measured.</p> <p>Methods</p> <p>16 patients with severe right-sided predominant thoracic scoliosis (standing Cobb's angle 50° -82°, mean 60°) received posterior spinal fusion without thoracoplasty were recruited into this study. BH-MR sequences were used to obtain coronal images of the whole chest during full inspiration and expiration. The following measurements were assessed: (1) inspiratory, expiratory and change in lung volume; (2) change in anteroposterior (AP) and transverse (TS) diameter of the chest wall at two levels: carina and apex (3) change in diaphragmatic heights. The changes in parameters before and after operation were compared using Wilcoxon signed ranks test. Patients were also asked to score their breathing effort before and after operation using a scale of 1–9 with ascending order of effort. The degree of spinal surgical correction at three planes was also assessed by reformatted MR images and correction rate of Cobb's angle was calculated.</p> <p>Results</p> <p>The individual or total inspiratory and expiratory volume showed slight but insignificant increase after operation. There was significantly increase in bilateral TS chest wall movement at carina level and increase in bilateral diaphragmatic movements between inspiration and expiration. The AP chest wall movements, however, did not significantly change.</p> <p>The median breathing effort after operation was lower than that before operation (p < 0.05).</p> <p>There was significant reduction in coronal Cobb's angle after operation but the change in sagittal and axial angle at scoliosis apex was not significant.</p> <p>Conclusion</p> <p>There is improvement of lateral chest wall and diaphragmatic motions in AIS patients six months after posterior spinal fusion, associated with subjective symptomatic improvement. Lung volumes however, do not significantly change after operation. BH-MR is novel non-invasive method for long term post operative assessment of pulmonary function in AIS patients.</p

Renal screening in children after exposure to low dose melamine in Hong Kong: cross sectional study

Objective To investigate the renal outcomes of children after exposure to low dose melamine in Hong Kong

A Chinese Herbal Decoction, Danggui Buxue Tang, Stimulates Proliferation, Differentiation and Gene Expression of Cultured Osteosarcoma Cells: Genomic Approach to Reveal Specific Gene Activation

Danggui Buxue Tang (DBT), a Chinese herbal decoction used to treat ailments in women, contains Radix Astragali (Huangqi; RA) and Radix Angelicae Sinensis (Danggui; RAS). When DBT was applied onto cultured MG-63 cells, an increase of cell proliferation and differentiation of MG-63 cell were revealed: both of these effects were significantly higher in DBT than RA or RAS extract. To search for the biological markers that are specifically regulated by DBT, DNA microarray was used to reveal the gene expression profiling of DBT in MG-63 cells as compared to that of RA- or RAS-treated cells. Amongst 883 DBT-regulated genes, 403 of them are specifically regulated by DBT treatment, including CCL-2, CCL-7, CCL-8, and galectin-9. The signaling cascade of this DBT-regulated gene expression was also elucidated in cultured MG-63 cells. The current results reveal the potential usage of this herbal decoction in treating osteoporosis and suggest the uniqueness of Chinese herbal decoction that requires a well-defined formulation. The DBT-regulated genes in the culture could serve as biological responsive markers for quality assurance of the herbal preparation

Comparison of 3D and 2D characterization of spinal geometry from biplanar X-rays: a large cohort study

Background: Biplanar X-ray system providing anteroposterior and sagittal plane with an ultra-low radiation dose and in weight-bearing position is increasingly used for spine imaging. The original three-dimensional (3D) reconstruction method from biplanar X-rays has been widely used for clinical parameters, however, the main issue is that manual adjustments of the 3D model was quite time-consuming and limited to thoracolumbar spine. A quasi-automated 3D reconstruction method of the spine from cervical vertebra to pelvis was proposed, which proved fast and accurate in 57 patients with adolescent idiopathic scoliosis. The aim of this study was to compare the newly developed technique of quasi-automatic 3D measurement with classical 2D measurements in a large cohort. Methods: A total of 494 adults with biplanar EOS X-ray scanning were included in this study and divided into health and deformity group according to the presence of spinal deformity. The proposed method of quasi-automatic 3D measurement was applied to all these subjects. The radiographic parameters included: thoracic kyphosis (TK), lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), sagittal vertical axis (SVA), T1 pelvic angle (TPA) in sagittal plane, and cobb angle in coronal plane. Comparison was made between quasi-automatic and manual measurement. Results: The mean age was 53.7±19.9 years old. In the whole population, the mean differences between the two methods were 3.9° for TK (30.5°±9.9° vs. 26.5°±9.3°, P30°, respectively. Correlation analysis showed r2 for all clinical parameters ranged from 0.667 to 0.923. On average, the new method takes 5 minutes to compute all the parameters for one case. Conclusions: In conclusion, this ergonomic and efficient quasi-automatic method for full spine proved fast and accurate measurement in a large population, which showed great potential in extensive clinical applicatio

Poor health literacy associated with stronger perceived barriers to breast cancer screening and overestimated breast cancer risk

BackgroundLow health literacy (HL) is negatively associated with mammography screening uptake. However, evidence of the links between poor HL and low mammography screening participation is scarce.MethodsWe conducted a cross-sectional questionnaire survey among participants of a cancer screening program. We measured HL using a validated Chinese instrument. We assessed breast cancer screening-related beliefs using the Health Belief Model and the accuracy of risk perception. We used multivariable regression models to estimate the relationship between HL and the outcomes.ResultsA total of 821 females were included. 264 (32.2%) had excellent or sufficient, 353 (43.0%) had problematic, and 204 (24.8%) had inadequate health literacy (IHL). Women with IHL were more likely to agree that high price (β = -0.211, 95% CI -0.354 to -0.069), lack of time (β = -0.219, 95% CI -0.351 to -0.088), inconvenient service time (β = -0.291, 95% CI -0.421 to -0.160), long waiting time (β = -0.305, 95% CI -0.447 to -0.164), fear of positive results (β = -0.200, 95% CI -0.342 to -0.058), embarrassment (β = -0.225, 95% CI -0.364 to -0.086), fear of pain (β = -0.154, 95% CI -0.298 to -0.010), fear of radiation (β = -0.177, 95% CI -0.298 to -0.056), lack of knowledge on service location (β = -0.475, 95% CI -0.615 to -0.335), and lack of knowledge on mammography (β = -0.360, 95% CI -0.492 to -0.228) were barriers. They were also less likely to have an accurate breast cancer risk perception (aOR 0.572, 95% CI 0.341 to 0.956).ConclusionWomen with lower HL could have stronger perceived barriers to BC screening and an over-estimation of their breast cancer risk. Tackling emotional and knowledge barriers, financial and logistical assistance, and guidance on risk perception are needed to increase their breast cancer screening uptake

Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B-0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p &lt; 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.</p

Adaptive distance metric learning for diffusion tensor image segmentation.

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework

Evaluation of the Reliability and the Performance of Magnetic Resonance Imaging Radiomics in the Presence of Randomly Generated Irrelevant Features for Prostate Cancer

Radiomics has the potential to aid prostate cancer (PC) diagnoses and prediction by analyzing and modeling quantitative features extracted from clinical imaging. However, its reliability has been a concern, possibly due to its high-dimensional nature. This study aims to quantitatively investigate the impact of randomly generated irrelevant features on MRI radiomics feature selection, modeling, and performance by progressively adding randomly generated features. Two multiparametric-MRI radiomics PC datasets were used (dataset 1 (n = 260), dataset 2 (n = 100)). The endpoint was to differentiate pathology-confirmed clinically significant (Gleason score (GS) ≥ 7) from insignificant (GS < 7) PC. Random features were generated at 12 levels with a 10% increment from 0% to 100% and an additional 5%. Three feature selection algorithms and two classifiers were used to build the models. The area under the curve and accuracy were used to evaluate the model’s performance. Feature importance was calculated to assess features’ contributions to the models. The metrics of each model were compared using an ANOVA test with a Bonferroni correction. A slight tendency to select more random features with the increasing number of random features introduced to the datasets was observed. However, the performance of the radiomics-built models was not significantly affected, which was partially due to the higher contribution of radiomics features toward the models compared to the random features. These reliability effects also vary among datasets. In conclusion, while the inclusion of additional random features may still slightly impact the performance of the feature selection, it may not have a substantial impact on the MRI radiomics model performance