Air pressure-induced susceptibility changes in vascular reactivity studies using BOLD MRI.

PURPOSE: To investigate whether compressed air during air-cuff inflation in vascular reactivity studies could induce aberrant blood oxygenation level-dependent (BOLD) signal change. MATERIALS AND METHODS: Magnetic resonance imaging (MRI) experiments were performed on a whole-body 3 T scanner. The pattern of T2* signal change measured from a phantom simulating the lower limb was assessed while a thigh cuff was inflated and deflated. MR spectroscopy was performed on a head phantom wrapped using a hand-cuff to determine the relationship between water peak linewidth and applied cuff pressure. Calf muscles from 14 normal subjects were examined to identify aberrant T2* signal changes in the occluded and nonoccluded legs. RESULTS: A sudden T2* signal drop was observed in the phantom on initiation of cuff inflation with subsequent signal change being dependent on cuff pressure. Water peak linewidth increased linearly with cuff pressure (r(2) = 0.94). Aberrant T2* signal changes were observed in both the occluded and nonoccluded legs. CONCLUSION: Compressed air due to cuff inflation directly affects local magnetic field susceptibility. The T2* sequence is sensitive to local field disturbances induced by an inflated cuff. Muscle BOLD results are affected by high-pressure air, with a sudden drop in T2* signal being a characteristic feature of this induced effect.

Relationship between hip bone mineral density and lumbar disc degeneration: a study in elderly subjects using an eight-level MRI-based disc degeneration grading system.

PURPOSE: To study the relationship between hip bone mineral density (BMD), lumbar disc degeneration, and lumbar disc space narrowing in elderly subjects. MATERIALS AND METHODS: The study cohort comprised 196 females and 163 males (age range, 67-89 years) with no age difference between the two groups. Anteroposterior total hip areal BMD was measured with DXA and lumbar spine MRI was acquired using a 1.5 Tesla scanner. Lumbar disc degeneration was assessed using an eight-level grading system wherein each grade represents a stepwise progression from normal disc to severe disc degeneration and disc space narrowing. RESULTS: After controlling for the age effect, no significant relationship was observed between total hip T-score status and severity of disc degeneration. There was no significant difference in total hip BMD in the subjects with or without the disc space narrowing (P < 0.05). Female subjects are more likely to have a narrowed disc space than males at all levels, and being statistically significant at L3/4 and L4/5 levels, and with an overall significance of P = 0.007. CONCLUSION: There was no association observed between hip BMD and lumbar disc degeneration. Elderly females were more likely to have a narrowed lumbar disc space than elderly males.

Proximal femur bone marrow blood perfusion indices are reduced in hypertensive rats: a dynamic contrast-enhanced MRI study.

PURPOSE: To investigate the differences in proximal femoral bone marrow blood perfusion indices between hypertensive and normotensive rats using perfusion magnetic resonance imaging (MRI). MATERIALS AND METHODS: Six-month-old male spontaneously hypertensive rats (SHR) and Wistar Kyoto rats (WKY) were used (12 of each). Dynamic contrast-enhanced MRI of the right hip was performed after bolus injection of Gd-DOTA administered through a tail vein cannula. In all, 800 images were acquired at 0.6 sec/image. Regions of interest (ROIs) were drawn comprising the medullary component of proximal femoral shaft and femoral head. MRI maximum enhancement (E(max)) and enhancement slope (E(slope)) were analyzed. RESULTS: The E(max) and E(slope) of proximal femoral shaft and femoral head of SHR were significantly lower than those of WKY (E(max): 107.4 +/- 18.2% vs. 130.6 +/- 21.5%, P = 0.009, and 76.0 +/- 12.5% vs. 97.9 +/- 6.9%, P < 0.001, respectively; E(slope): 3.01 +/- 0.63%/sec vs. 3.75 +/- 0.74%/sec, P = 0.016, and 1.95 +/- 0.33%/sec vs. 2.28 +/- 0.28%/sec, P = 0.012, respectively). The E(max) and E(slope) of femoral head were significantly lower than those of proximal femoral shaft in both SHR and WKY (P < 0.001). In both SHR and WKY, proximal femoral shaft and femoral head had a rather different contrast enhancement pattern. CONCLUSION: Proximal femoral shaft and femoral head bone marrow blood perfusion indices were significantly lower in hypertensive rats than in normotensive rats. Femoral head bone marrow was less perfused than proximal femoral shaft in both rats.

The Correlation Analysis Between DTI Network Parameters and AVLT Scale Scores of Alzheimer's Disease.

Neuroimaging and neuropsychology are employed to investigate the pathological features and clinical characteristics of Alzheimer's disease (AD) in order to find a method for the precise treatment. Diffusion tensor imaging (DTI) provides a non-intrusive examination of cranial nerve diseases which can help us observe the microstructure of neuron fibers. Building the brain network provides a chance to reveal the significance of specific brain region and the relevance among different regions. In this study, we propose a completely novel method to analyze AD. First whole brain network is built on the basis of a novel segmentation atlas, and global graph theoretical parameters are calculated to evaluate the characteristic of whole brain. Then graph theoretical parameters of specific brain regions are extracted based on whole brain network. Finally neuropsychology scale are employed and we analyze the correlation between graph theoretical parameters of specific regions and scale scores. Our results illustrate the connection between neuroimaging data and neuropsychological scores, and provide a reasonable explanation for the potential connection between clinical performance and physiological brain lesions of AD patients.

Multivariate Analysis of White Matter Structural Networks of Alzheimer's Disease.

The connectome-wide association studies exploring association between brain connectome and disease phenotypes have suffered from massive number of comparisons. In this paper, we propose to apply a multivariate distance-based analytic framework on brain white matter (WM) structural networks invaded by Alzheimer's disease (AD). Eighty-three subjects including patients with AD, amnestic mild cognitive impairment (aMCI) and healthy subjects were scanned with dMRI. By constructing WM structural network for each individual, we used both multivariate and traditional univariate statistical models to complimentarily analyze network pattern and fiber strength changes due to AD. WM connections linked with several brain structures were found significantly changed between AD group and normal controls. No significant findings were observed between aMCI group and normal controls. Our results demonstrate the sensitivity of the combined connectome-based analytic framework in detecting abnormalities of structural brain network.

A Novel Multimodal MRI Analysis for Alzheimer's Disease Based on Convolutional Neural Network.

Recent years, Alzheimer's disease (AD) has become a significant threat to human health while the accurate screening and diagnosis of AD remain a tough problem. Multimodal Magnetic resonance imaging (MRI) can help to identify the variation of brain function and structure in a non-invasive way. Deep learning, especially the convolutional neural networks (CNN), can be utilized to automatically detect appropriate features for classification, which is well adapted for computer-aided AD screening and identification. This paper proposed a multimodal MRI analytical method based on CNN, which is also suitable for single type MRI data analysis. First, the human brain network connectivity matrix were extracted from multimodal MRI data, used as the input data for CNN. Then a novel CNN framework was proposed to process the network matrix and classify AD, amnestic mild cognitive impairment (aMCI) patients and normal controls (NC). The advantage of this method lies in that we combined multimodal MRI information through CNN convolution kernel, and achieved a higher classification accuracy. In our experiments, the comprehensive classification accuracy of AD, aMCI patients and NC was as high as 92.06% when using multimodal MRI data as input, which is effective enough to provide a reference for multimodal MRI data analysis.

Effects of the physiological parameters on the signal-to-noise ratio of single myoelectric channel.

BACKGROUND: An important measure of the performance of a myoelectric (ME) control system for powered artificial limbs is the signal-to-noise ratio (SNR) at the output of ME channel. However, few studies illustrated the neuron-muscular interactive effects on the SNR at ME control channel output. In order to obtain a comprehensive understanding on the relationship between the physiology of individual motor unit and the ME control performance, this study investigates the effects of physiological factors on the SNR of single ME channel by an analytical and simulation approach, where the SNR is defined as the ratio of the mean squared value estimation at the channel output and the variance of the estimation. METHODS: Mathematical models are formulated based on three fundamental elements: a motoneuron firing mechanism, motor unit action potential (MUAP) module, and signal processor. Myoelectric signals of a motor unit are synthesized with different physiological parameters, and the corresponding SNR of single ME channel is numerically calculated. Effects of physiological multi factors on the SNR are investigated, including properties of the motoneuron, MUAP waveform, recruitment order, and firing pattern, etc. RESULTS: The results of the mathematical model, supported by simulation, indicate that the SNR of a single ME channel is associated with the voluntary contraction level. We showed that a model-based approach can provide insight into the key factors and bioprocess in ME control. The results of this modelling work can be potentially used in the improvement of ME control performance and for the training of amputees with powered prostheses. CONCLUSION: The SNR of single ME channel is a force, neuronal and muscular property dependent parameter. The theoretical model provides possible guidance to enhance the SNR of ME channel by controlling physiological variables or conscious contraction level.

Cognitive control related network analysis: A novel way to measure neuron fiber connection of Alzheimer's disease.

Effective measurement of cognitive impairment caused by Alzheimer's disease (AD) will provide a chance for early medical intervention and delay the disease onset. Diffusion tensor imaging (DTI) provides a non-intrusive examination of cranial nerve diseases which can help us observe the microstructure of neuron fibers. Cognitive control network (CCN) consists of the brain regions that highly related to human self-control. In this study, hub-and-spoke model which was widely used in transportation and sociology area had been employed to analyze the relationship of CCN and other regions under its control, cognitive control related network (CCRN) was built by applying this model. Local and global graph theoretical parameters were calculated and went through statistical analysis. Significant difference had been found in the scale of local as well as global which may represent the impairment of cognitive control ability. This result may provide a potential bio-marker for the loss of connection caused by Alzheimer's disease.

Structural changes of cingulate cortex in post stroke depression.

Disruption of neural connections among regions regulating mood and cognition rather than cerebrovascular lesions may contribute to post-stroke depression (PSD). In this paper, we hypothesized that structural abnormalities in white matter structure like cingulate cortex induced by focal infarcts would play a role in mood regulation or depression after stroke onset. Various DTI coefficients including FA, RD and ADC with multiple signal distribution measurements were collected and statistically analyzed. The results identify significant differences in volume and multiple diffusion indices of DTI intensity distribution in cingulate cortex between PSD patients and the normal control. It indicates the neuronal loss secondary to demyelination in cingulate cortex due to stroke. Additionally, the volume loss of cingulate cortex in PSD patients observed in the results may further demonstrate the reduction of glial cells in cingulate cortex, as the axonal number/size changed little.

A simulation study on marrow fat effect on biomechanics of vertebra bone.

Trabecular bone and bone marrow are main components of cancellous bone. Most mechanical studies for bone mainly focus on hard tissues, while if bone marrow contributes to bone biomechanics is not clear yet. This study was proposed to investigate marrow fat effect on trabecular bone biomechanics by simulation. Finite element (FE) bone models were established based on quantitative CT images at L3 lumbar spine, from which trabecular structures with and without marrow fat were investigated respectively. Auni-static compressive test was applied on the proposed models until to the appearance of fracture. Simulation results showed that trabecular models filled with marrow fat had about 3%-9% less maximum stress in volume than models with only trabeculae. However, its average stress in volume was about 9%-56% larger than those with only trabeculae. The strain energy density of the bone model with marrow fat showed a more uniformed distribution. As a conclusion, marrow fat has contributions to the bone mechanics. It can balance the stress distribution of the bone tissue, which may reduce bone deformation under a compressive loading. The mixture of trabecular structure and marrow fat would be against higher compress load before the failure point.

A fast atlas pre-selection procedure for multi-atlas based brain segmentation.

Multi-atlas based MR image segmentation has been recognized as a quantitative analysis approach for brain. For such purpose, atlas databases keep increasing to include various anatomical characteristics of human brain. Atlas pre-selection becomes a necessary step for efficient and accurate automated segmentation of human brain images. In this study, we proposed a method of atlas pre-selection for target image segmentation on the MriCloud platform, which is a state-of-the-art multi-atlas based segmentation tool. In the MRIcloud pipeline, segmentation of lateral ventricle (LV) label is generated as an additional input in the segmentation pipeline. Under this circumstance, similarity of the LV label between target image and atlases was adopted as the atlas ranking scheme. Dice overlap coefficient was calculated and taken as the quantitative measure for atlas ranking. Segmentation results based on the proposed method were compared with that based on atlas pre-selection by mutual information (MI) between images. The final segmentation results showed a comparable accuracy of the proposed method with that from MI based atlas pre-selection. However, the computation load for the atlas pre-selection was speeded up by about 20 times compared to MI based pre-selection. The proposed method provides a promising assistance for quantitative analysis of brain images.

QRS detection by lifting scheme constructing multi-resolution morphological decomposition.

QRS complex detecting algorithm is core of ECG auto-diagnosis method and deeply influences cardiac cycle division for signal compression. However, ECG signals collected by noninvasive surface electrodes areusually mixed with several kinds of interference, and its waveform variation is the main reason for the hard realization of ECG processing. This paper proposes a QRS complex detecting algorithm based on multi-resolution mathematical morphological decomposition. This algorithm possesses superiorities in R peak detection of both mathematical morphological method and multi-resolution decomposition. Moreover, a lifting constructing method with Maximizationupdating operator is adopted to further improve the algorithm performance. And an efficient R peak search-back algorithm is employed to reduce the false positives (FP) and false negatives (FN). The proposed algorithm provides a good performance applying to MIT-BIH Arrhythmia Database, and achieves over 99% detection rate, sensitivity and positive predictivity, respectively, and calculation burden is low. Therefore, the proposed method is appropriate for portable medical devices in Telemedicine system.

A preliminary study of DTI Fingerprinting on stroke analysis.

DTI (Diffusion Tensor Imaging) is a well-known MRI (Magnetic Resonance Imaging) technique which provides useful structural information about human brain. However, the quantitative measurement to physiological variation of subtypes of ischemic stroke is not available. An automatically quantitative method for DTI analysis will enhance the DTI application in clinics. In this study, we proposed a DTI Fingerprinting technology to quantitatively analyze white matter tissue, which was applied in stroke classification. The TBSS (Tract Based Spatial Statistics) method was employed to generate mask automatically. To evaluate the clustering performance of the automatic method, lesion ROI (Region of Interest) is manually drawn on the DWI images as a reference. The results from the DTI Fingerprinting were compared with those obtained from the reference ROIs. It indicates that the DTI Fingerprinting could identify different states of ischemic stroke and has promising potential to provide a more comprehensive measure of the DTI data. Further development should be carried out to improve DTI Fingerprinting technology in clinics.

A simulation study of marrow fat effect on bone biomechanics.

Bone marrow was assumed to be negligible on the aspect of bone mechanical behavior, where bone mass and bone mineral density were most studied. As a result, if the bone marrow, especially the marrow fat, plays a role in the bone mechanical properties is unknown yet. Marrow fat content was found increased in osteoporotic bone. However, the relationship between such change of bone marrow and bone strength is not clear yet. This study was proposed to investigate the effect of marrow fat on the bone biomechanical performance by computer simulations. A finite element model was established based on trabecular structure extracted from quantitative CT at L3 vertebrae. Simulations were conducted on the models with and without marrow fat under the same condition, respectively. The results showed that the cancellous bone with marrow fat had a 7.56%~18.81% higher maximum stress in trabeculae. Further, trabeculae with higher Young's modulus tend to sustain a higher maximum compressive stress when considering the marrow fat. As a conclusion, the marrow fat has effect on bone biomechanics, which cannot be ignored. Such effect in osteoporosis should be further investigated in deep.

BOLD effect on calf muscle groups in elderly females with different bone mineral density.

This study examined the BOLD effect on calf muscles in elderly subjects with different bone mineral density. The purpose was to investigate the oxygenation characteristics in different calf muscle groups for the elderly females and compare the muscle oxygenation among groups with different bone mineral density. Temporary vascular occlusion was induced with air-cuff compression of the thigh and BOLD-MRI data curve was fitted to derive quantitative parameters. Three muscle groups, gastrocnemius muscle (lateral head), soleus muscle, and tibialis anterior muscle, were investigated individually. Quantitative CT measurement was conducted on each subject, based on which subjects were classified into normal, osteopenia, and osteoporosis groups. The BOLD signal in soleus muscle showed the lowest minimum ischemic value during ischemia and the steepest slope during hyperemia. As soleus muscle is mainly composed by slow-twitch oxidative muscle fibers, current results may be due to a higher vascular bed density and better endothelial function in such muscle. By t-test, the half-life of the BOLD signal decay during ischemia in both gastrocnemius and soleus muscles was significantly prolonged in osteoporosis group, indicating a degenerated muscular oxygen metabolic capacity in osteoporotic patients.

Bone marrow perfusion of proximal femur varied with BMD--a longitudinal study by DCE-MRI.

This study investigated bone marrow perfusion at proximal femur varying with bone mineral density (BMD) and aging over 4 years. Dynamic contrast enhanced MRI data was extracted pixel-by-pixel and classified into 3 patterns to indicate the perfusion function. Eighty-seven elderly females were involved. A notable reduced perfusion as a whole was observed in osteoporotic subjects. Moreover, perfusion distribution varies as BMD decreases, especially at the area crossing the femoral neck to the shaft. Consistent for all subjects, the perfusion decreases significantly from the lesser trochanter to the greater trochanter. Further, the subjects with good bone marrow perfusion would keep stable BMD after 4 years, while for those with bad perfusion, their BMD consistently decreased over 4 years. The results indicated that the bone marrow perfusion function interacts with bone modeling and could have a long term effect on BMD. A good perfusion function would help to keep the bone health.

Relationship between marrow perfusion and bone mineral density: a pharmacokinetic study of DCE-MRI.

A reduced bone perfusion has been found for osteoporotic subjects in previous studies. However, the physiological changes underlying the varied perfusion function is not well known yet. Tofts model is one of the most frequently used pharmacokinetic models in analyzing perfusion process. This study modified the Tofts model by replacing the arterial input function (AIF) by a new algorithm. The modified model was then employed to analyze vertebral bone marrow perfusion in subjects with different bone mineral density (BMD). Eighty-two male subjects were involved in this study and classified into three groups (normal, osteopenia, and osteoporosis) according to T-score. BMD was measured by dual-energy X-ray absorptiometry (DXA). The quantitative parameters derived from the pharmacokinetic model, K(trans) (extravasation transfer efficiency for blood perfusion) and v(e) (extravascular extracellular space for blood perfusion), showed a significant reduction in subjects with lower BMD, respectively. The results suggested that with the bone mineral content lost, the vascular wall properties as well as the bone marrow content may also vary. The resultant perfusion change may also influence the bone nutrition supply in reverse.

Perfusion and bone mineral density as function of vertebral level at lumbar spine.

The objective of this study is to characterize perfusion and bone mineral density (BMD) in the lumbar spine as a function of level and anatomic location. Fourteen male subjects with healthy vertebral endplates were selected to avoid gender and endplate disease influence. The bone perfusion and BMD of different vertebral level (L1-L4) were measured by the dynamic contrast enhancement MRI (DCE MRI) and the dual-energy X-ray absorptiometry (DXA) respectively. Perfusion parameters showed a significant negative correlation with upper to lower vertebral levels while inverse observation was found for BMD. The results indicated that the perfusion and BMD are as function of vertebral level and anatomic location at lumbar spine. The BMD varying with vertebral level may be determined by the biomechanical usage at the lumbar spine, where the lower levels sustain more mechanical forces. Perfusion changes along the lumbar spine level suggested that the bone marrow component could be different when BMD varies, which needs further histological verification.

Spectral analysis of pulse transit time variability and its coherence with other cardiovascular variabilities.

Pulse transit time (PTT) has been reported correlated with heart rate (HR) and blood pressure (BP), however, the results are not consistent in different investigations. Towards a better understanding of the underlying mechanisms of the PTT changes, this study compares the power spectrum density of the variability in PTT with that in HR and BP under rest and post-exercise physiological conditions. Coherence function is also examined to quantify the strength of coupling between paired variabilities. The results show that the pulse transit time variability (PTTV) has significant coherence (>0.5) with heart rate variability (HRV) and blood pressure variability (BPV) under all physiological conditions at high frequency (HF). However, at the low frequency (LF) band, the coherence reduced to insignificance immediately after the exercise (< or =5 minutes after exercise) and then return back to significant level 9 minutes after the exercise. The results show that PTTV is strongly coupled with HRV and BPV at the HF, indicating that the parasympathetic modulation could be the main cause of PTTV. The unstable coupling relationship of PTTV with BPV at LF should raise caution in the beat-to-beat BP estimation by PTT in the dynamic situation.