Protocol for Brain Magnetic Resonance Imaging and Extraction of Imaging‑Derived Phenotypes from the China Phenobank Project

Imaging-derived phenotypes(IDPs)have been increasingly used in population-based cohort studies in recent years.As widely reported,magnetic resonance imaging(MRI)is an important imaging modality for assessing the anatomical structure and function of the brain with high resolution and excellent soft-tissue contrast.The purpose of this article was to describe the imaging protocol of the brain MRI in the China Phenobank Project(CHPP).Each participant underwent a 30-min brain MRI scan as part of a 2-h whole-body imaging protocol in CHPP.The brain imaging sequences included T1-magnetization that prepared rapid gradient echo,T2 fuid-attenuated inversion-recovery,magnetic resonance angiography,difusion MRI,and resting-state functional MRI.The detailed descriptions of image acquisition,interpretation,and post-processing were provided in this article.The measured IDPs included volumes of brain subregions,cerebral vessel geometrical parameters,microstructural tracts,and function connectivity metrics.

Clinical and Brain Magnetic Resonance Imaging Features in a Cohort of Chinese Patients with Kearns-Sayre Syndrome

Background： Kearns-Sayre syndrome （KSS） is a mitochondrial DNA （mtDNA） deletion disorder characterized by a triad of onset before 20 years of age, ophthalmoplegia, and pigmentary retinopathy. The heart and central nervous system are commonly involved. We summarized clinical and brain magnetic resonance imaging （M RI） features of a cohort of Chinese KSS patients. Methods： Nineteen patients confirmed by muscle biopsy and mtDNA analysis were enrolled. We examined clinical profiles, mainly focusing on changes in electrocardiogram （ECG） and brain MRI. The correlation between genotype and phenotype was statistically analyzed. Results： The mean age of onset was 9.6 ＋ 4.3 years, with all developing the classic triad at the time of diagnosis. Heart conduction block was detected in 63.2%, with four initially presenting as bundle branch block and developing into complete atrioventricular block over 3-72 months. Brain MRI showed symmetric high-T2 signals in 100% of cerebral and cerebellar white matter, as well as brainstem, 46.7% of basal ganglia, and 53.3% of thalamus. There were two patterns of cerebral white matter involvements, one with selective subcortical U-fibers and the other with periventricular white matter. The size of mtDNA deletion did not significantly correlate with age of onset or percentage of ragged blue fibers on muscle pathology. Conclusions： The clinical features of KSS evolve dynamically, affecting the cardiac conduction system predominantly, highlighting the significance of ECG monitoring. Brain MRI showed changes involving both the white matter and deep gray nuclei. Clinical presentation or severity of muscle pathological changes is not related to the size of mtDNA deletions.

Functional magnetic resonance imaging evidence for activated functional brain areas following acupoint needling in the extremities

Totally three articles focusing on functional magnetic resonance imaging features of brain function in the activated brain regions of stroke patients undergoing acupuncture on the healthy limbs and healthy controls undergoing acupuncture on the lower extremities are published in three issues. We hope that our readers find these papers useful to their research.

Brain MRI Segmentation Using KFCM and Chan-Vese Model

To extract region of interests （ROI） in brain magnetic resonance imaging （MRI） with more than two objects and improve the segmentation accuracy, a hybrid model of a kemel-based fuzzy c-means （KFCM） clustering algorithm and Chan-Vese （CV） model for brain MRI segmentation is proposed. The approach consists of two succes- sive stages. Firstly, the KFCM is used to make a coarse segmentation, which achieves the automatic selection of initial contour. Then an improved CV model is utilized to subdivide the image. Fuzzy membership degree from KFCM clus- tering is incorporated into the fidelity term of the 2-phase piecewise constant CV model to obtain accurate multi-object segmentation. Experimental results show that the proposed model has advantages both in accuracy and in robustness to noise in comparison with fuzzy c-means （FCM） clustering, KFCM, and the hybrid model of FCM and CV on brain MRI segmentation.

Modulatory effects of acupuncture on brain networks in mild cognitive impairment patients

Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in brain activation induced by acupuncture. Thus, the time course of the therapeutic effects of acupuncture remains unclear. In this study, 32 patients with amnestic mild cognitive impairment were randomly divided into two groups, where they received either Tiaoshen Yizhi acupuncture or sham acupoint acupuncture. The needles were either twirled at Tiaoshen Yizhi acupoints, including Sishencong（EX-HN1）, Yintang（EX-HN3）, Neiguan（PC6）, Taixi（KI3）, Fenglong（ST40）, and Taichong（LR3）, or at related sham acupoints at a depth of approximately 15 mm, an angle of ± 60°, and a rate of approximately 120 times per minute. Acupuncture was conducted for 4 consecutive weeks, five times per week, on weekdays. Resting-state functional magnetic resonance imaging indicated that connections between cognition-related regions such as the insula, dorsolateral prefrontal cortex, hippocampus, thalamus, inferior parietal lobule, and anterior cingulate cortex increased after acupuncture at Tiaoshen Yizhi acupoints. The insula, dorsolateral prefrontal cortex, and hippocampus acted as central brain hubs. Patients in the Tiaoshen Yizhi group exhibited improved cognitive performance after acupuncture. In the sham acupoint acupuncture group, connections between brain regions were dispersed, and we found no differences in cognitive function following the treatment. These results indicate that acupuncture at Tiaoshen Yizhi acupoints can regulate brain networks by increasing connectivity between cognition-related regions, thereby improving cognitive function in patients with mild cognitive impairment.

Early Tumor Diagnosis in Brain MR Images via Deep Convolutional Neural Network Model

Machine learning based image analysis for predicting and diagnosing certain diseases has been entirely trustworthy and even as efficient as a domain expert’s inspection.However,the style of non-transparency functioning by a trained machine learning system poses a more significant impediment for seamless knowledge trajectory,clinical mapping,and delusion tracing.In this proposed study,a deep learning based framework that employs deep convolution neural network(Deep-CNN),by utilizing both clinical presentations and conventional magnetic resonance imaging(MRI)investigations,for diagnosing tumors is explored.This research aims to develop a model that can be used for abnormality detection over MRI data quite efficiently with high accuracy.This research is based on deep learning and Deep-CNN was deployed to examine the MR brain image for tracing the tumor.The system runs on Tensor flow and uses a feature extraction module in DeepCNN to elicit the factors of that part of the image from where underlying issues are identified and subsequently succeeded in prediction of the disease in the MR image.The results of this study showed that our model did not have any adverse effect on classification,achieved higher accuracy than the peers in recent years,and attained good detection outcomes including case of abnormality.In the future work,further improvement can be made by designing models that can drastically reduce the parameter space without affecting classification accuracy.

A brief report on MRI investigation of experimental traumatic brain injury

Traumatic brain injury is a major cause of death and disability. This is a brief report based on a symposium presentation to the 2014 Chinese Neurotrauma Association Meeting in San Francisco, USA. It covers the work from our laboratory in applying multimodal MRI to study experimental traumatic brain injury in rats with comparisons made to behavioral tests and histology. MRI protocols include structural, perfusion, manganese-enhanced, diffusion-tensor MRI, and MRI of blood-brain barrier integrity and cerebrovascular reactivity.

Decoding brain responses to pixelized images in the primary visual cortex: implications for visual cortical prostheses

Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only ＂see＂ pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex（the implant area） is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine（LSVM） as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern.

Continuous representation of human portraits and natural scenery in human ventral temporal cortex: evidence from functional magnetic resonance imaging

Background Functional magnetic resonance imaging (fMRI) has become a powerful tool for tracking human brain activity in vivo. This technique is mainly based on blood oxygenation level dependence (BOLD) contrast. In the present study, we employed this newly developed technique to characterize the neural representations of human portraits and natural sceneries in the human brain.Methods Nine subjects were scanned with a 1.5 T magnetic resonance imaging (MRI) scanner using gradient-recalled echo and echo-planar imaging (GRE-EPI) pulse sequence while they were visually presented with 3 types of white-black photographs: natural scenery, human portraits, and scrambled nonsense pictures. Multiple linear regression was used to identify brain regions responding preferentially to each type of stimulus and common regions for both human portraits and natural scenery. The relative contributions of each type of stimulus to activation in these regions were examined using linear combinations of a general linear test.Results Multiple linear regression analysis revealed two distinct but adjacent regions in both sides of the ventral temporal cortex. The medial region preferentially responded to natural scenery, whereas the lateral one preferentially responded to the human portraits. The general linear test further revealed a distribution gradient such that a change from portraits to scenes shifted areas of activation from lateral to medial.Conclusions The boundary between portrait-associated and scenery-associated areas is not as clear as previously demonstrated. The representations of portraits and scenes in ventral temporal cortex appear to be continuous and overlap.

Correlation of MR imaging and histopathology after partial resection of normal rabbit brain

Abstract Objectives To investigate the findings of magnetic resonance (MR) imaging and histopathology in early postoperative normal brain, and to define the correlation between MR images and histopathology. Methods Thirty-six New Zealand rabbits weighing 2.0 to 3.0*!kg were divided into 10 groups according to different postoperative days: 1 to 10 days. A partial resection of the parietooccipital region was performed under usual aseptic conditions after the animals were anesthetized intravenously with 3% pentobarbital (30*!mg/kg). MR imaging procedures consisted of pre- and postcontrast scanning and were carried out on postoperative days 1 to 10. Brain tissue samples were prepared for examination immediately after MR scanning. Histopathological examination was done under light both and electron microscopes. The findings of MR imaging were compared with histopathologic findings.Results Surgical margin contrast enhancement on MR images could be seen 24 hours after surgery. The degree of contrast enhancement increased gradually up to 5 days postoperation, and no remarkable changes were present from days 5 to 10. Disruption of the blood brain barrier (BBB) was the main cause of contrast enhancement during the first 3 postoperative days. After that period, the mechanism responsible for contrast enhancement was the formation of neovascularity and a broken BBB. An increase in the amount of neovascularity played a predominant role in contrast enhancement in normal postoperative brain tissue. Conclusions The features of enhanced MR images present at the surgical margin followed a typical time course during the early postoperative period. The role of neovascularity and BBB disruption in the formation of contrast enhancement at the surgical margin varies with time. Knowledge of the features of contrast enhancement in postoperative MR images of normal brain can help in differentiating benign changes from residual malignant glioma.

Functional organization of complex brain networks modulated by acupuncture at different acupoints belonging to the same anatomic segment

Background Noninvasive functional magnetic resonance imaging （fMRI） techniques have opened a ＂window＂ into the brain, allowing us to investigate the anatomical and physiological function involving acupuncture needling. Imaging its sustained effect rather than acute effect on the brain networks may further help elucidate the mechanisms by which acupuncture achieves its therapeutic effects. In this study, we aimed to investigate the functional brain networks during the post-resting state following acupuncture at KI3 in comparison with acupuncture at GB40. Methods Needling at acupoints GB40 and KI3 was performed in twelve subjects. Six minutes of scanning at rest were adopted before and after acupuncture at different acupoints. Then we divided the whole brain into 39 regions and constructed functional brain networks during the post-acupuncture resting states （PARS）. Results For direct comparisons, increased correlations during post-resting state following acupuncture at KI3 compared to resting state （RS） were primarily located between the dorsolateral prefrontal cortex （DLPFC） and post temporal cortex, ventromedial prefrontal cortex （vmPFC） and post temporal cortex. These brain regions were all cognitive-related functions. In contrast, the increased connections between the anterior insula and temporal cortex mainly emerged following acupuncture at GB40 compared with the RS. Conclusions The present study demonstrates that acupuncture at different acupoints belonging to the same anatomic segment can exert different modulatory effects on the reorganizations of post-acupuncture RS networks. The heterogeneous modulation patterns between twoconditions may relate to the functional specific modulatory effects of acupuncture.

A Survey of MRI-Based Brain Tumor Segmentation Methods

Brain tumor segmentation aims to separate the different tumor tissues such as active cells, necrotic core,and edema from normal brain tissues of White Matter（WM）, Gray Matter（GM）, and Cerebrospinal Fluid（CSF）. MRIbased brain tumor segmentation studies are attracting more and more attention in recent years due to non-invasive imaging and good soft tissue contrast of Magnetic Resonance Imaging（MRI） images. With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting brain tumor are becoming more and more mature and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for MRI-based brain tumor segmentation methods. Firstly, a brief introduction to brain tumors and imaging modalities of brain tumors is given. Then, the preprocessing operations and the state of the art methods of MRI-based brain tumor segmentation are introduced. Moreover, the evaluation and validation of the results of MRI-based brain tumor segmentation are discussed. Finally, an objective assessment is presented and future developments and trends are addressed for MRI-based brain tumor segmentation methods.