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ORIGINAL ARTICLE
Year : 2019  |  Volume : 22  |  Issue : 2  |  Page : 203-209
 

Fractional amplitude of low-frequency fluctuations and functional connectivity in comatose patients subjected to resting-state functional magnetic resonance imaging


1 Department of Magnatic Resonance Imaging, The First People's Hospital of Nanning, Nanning, China
2 Department of Magnatic Resonance Imaging, The First Affiliated Hospital of Henan University of TCM, Zhengzhou, China
3 Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
4 Guangxi Collaborative Innovation Center for Biomedicine; Life Science Institute, Guangxi Medical University, Nanning, China
5 Department of Radiology, Changsha Central Hospital, Changsha, China

Date of Web Publication9-Apr-2019

Correspondence Address:
Prof. Zisan Zeng
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi, Nanning 530021
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/aian.AIAN_420_17

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   Abstract 


Objective: The objective of the study is to investigate the changes of fractional amplitude of low-frequency fluctuations (fALFFs) and functional connectivity (FC) in the brain function of comatose patients with resting-state blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD-fMRI) and to discuss the underlying neurophysiological mechanism of disease. Materials and Methods: Resting-state BOLD-fMRI scans were conducted on 20 comatose patients and 20 age-matched and gender-matched controls. The differences of fALFF between two groups were analyzed with two-sample t-test; significant differences of connectivity between groups were acquired to calculate the FC of the precuneus with other brain regions. Results: Compared to the control group, the comatose patients exhibited a significant reduction in fALFF in various areas, including the right cingulate gyrus, left precuneus, right inferior parietal lobule, right superior parietal lobule, bilateral anterior/posterior central gyrus, middle frontal gyrus, right superior frontal gyrus, right superior temporal gyrus, and the bilateral cerebellar hemispheres (P < 0.05, Alphasim correction). Compared with controls, the brain region FC correlated with the precuneus reduced mainly located in the bilateral inferior parietal lobule, posterior central gyrus, lenticular nucleus, left anterior central gyrus, left medial frontal gyrus, left anterior lobe of the cerebellum, right insula, right transverse temporal gyri, and right thalamus. Regions whose FC increased include the left superior frontal gyrus, left side of the callosum, left superior parietal lobule, and both sides of the cingulate (P < 0.05, Alphasim correction). Conclusion: Measurements of fALFF and FC obtained by resting-state BOLD-fMRI could provide considerable information for the analysis and evaluation of the brain function of comatose patients from the perspective of local function and global functional network and provide the theoretical basis for the study of coma nerve physiological mechanism.


Keywords: Coma, fractional amplitude of low-frequency fluctuations, functional connectivity, resting-state blood-oxygenation-level-dependent functional magnetic resonance imaging


How to cite this article:
Huang L, Zheng Y, Zeng Z, Li M, Zhang L, Gao Y. Fractional amplitude of low-frequency fluctuations and functional connectivity in comatose patients subjected to resting-state functional magnetic resonance imaging. Ann Indian Acad Neurol 2019;22:203-9

How to cite this URL:
Huang L, Zheng Y, Zeng Z, Li M, Zhang L, Gao Y. Fractional amplitude of low-frequency fluctuations and functional connectivity in comatose patients subjected to resting-state functional magnetic resonance imaging. Ann Indian Acad Neurol [serial online] 2019 [cited 2019 Sep 15];22:203-9. Available from: http://www.annalsofian.org/text.asp?2019/22/2/203/255684

Lixuan Huang, Yan Zheng: These authors contributed equally to this work





   Introduction Top


Coma, a serious type of disturbance of consciousness, entails the complete loss of cognitive function.[1] Due to the rapid development of modern emergency medical treatment of brain diseases, the percentage of patients who die from brain disease has decreased, but the prevalence of disturbances of consciousness has substantially increased. Comatose patients comprise 3%–5% of the total number of emergency.[2] Assessing the brain function level and accurately and objectively predicting the recovery of brain function in comatose patients have become important problems that need to be resolved. In recent years, the studies of resting-state blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD-fMRI) provided a new way to solve these problems [3] and showed that the decreasing default network connectivity was in proportion to the comatose patients' degree of consciousness impairment.[4]

Early in 2008, the concept of fractional amplitude of low-frequency fluctuation (fALFF) was proposed,[5] which was defined as the average value of the amplitude frequency from 0.01 to 0.08 Hz that divided by the full spectrum power. It describes the level of spontaneous activity of each individual element in the resting state from all aspects of energy and is used to evaluate the local spontaneous activity levels of the brain. Functional connectivity (FC) is a technique used to analyze the neural activity and interaction between different brain regions.[6]

The concept of default mode network (DMN) is introduced by Raichle et al.[6] and it is based on the research of resting-state fMRI by Shulman et al.[7] and Mazoyer et al.[8] Several fixed areas of the human brain exhibit strong activity during the waking state when no brain tasks are occurring, which is the so-called resting state. The activity level of these specific brain regions appears to be consistently attenuated when participants receive different tasks or stimulation. Together, these brain areas form a functional neural network and the resting-state brain default network. Its presence is thought to reflect a default state of brain activity that is vital for brain functioning and possibly consciousness. Many current studies [9],[10] have demonstrated that the DMN encompasses the posterior cingulate cortex (PCC)/precuneus, mesiofrontal/anterior cingulate cortex, temporoparietal junction areas, and the hippocampus.

Because of the particularity of comatose patients, the use of resting-state BOLD-fMRI to study the default brain function of these patients was rare, and the changes of FC based on the precuneus – another node of the DMN in the comatose patients – were rarely reported. This sentence modified as “In the previous study, our team found that significant decrease of regional homogeneity (ReHo) in multiple brain regions of coma patients in the resting state, which suggested that the physiological mechanisms of unconsciousness is not only associated with a single abnormal brain region, but also associated with all the brain abnormalities. In the present study, our aim was to investigate the changes in the brain function of comatose patients and the role of resting-state fMRI in the evaluation of neurological function in coma patients using fALFF and FC measurements obtained through resting-state BOLD-fMRI.


   Materials and Methods Top


Participants

Twenty comatose patients were investigated in this study. The following groups of patients were included: (1) those patients diagnosed with coma with a Glasgow Coma Scale score ≤10 in the first 24 h; (2) those patients aged 18–80 years and with right handed; (3) those patients in a coma for more than a week; (4) those patients without mental illness and previous serious medical problems; (5) those patients without a history of alcoholism, drug abuse, and dependence; and (6) those patients with no use of any medicine that affects the level of brain function within 6 h before the imaging examination. According to the age- and gender-matching principle, 20 healthy people who were right handed and did not have a history of oral alcoholism, drug abuse, or dependence were selected as the control group. Informed consent to participate in the study was obtained from the healthy individuals and the legal surrogates of the patients.

Data acquisition

All data were collected using a 3.0-T PHILIPS superconducting MRI system (PHILIPS Medical System, Netherlands) with an 8-channel head coil. Structured data were obtained with T1-weighted three-dimensional fast field echo (156 slices with 1-mm thickness, repetition time [TR] = 20 ms, echo time [TE] = 3.5 ms, flip angle = 12°, field of view [FOV] = 240 mm × 240 mm, matrix size = 512 × 510, total scan duration of 6 min 45 s). In addition, functional data were obtained with echo-planar imaging (30 slices with 4-mm thickness, TR = 2000 ms, TE = 30 ms, flip angle = 90°, FOV = 240 mm × 240 mm, matrix size = 64 × 64, and total scan duration of 6 min 54 s). The participants were instructed to lie in the scanner with their eyes closed and stayed awake.

Preprocessing

The DPARSF software and the SPM8 software, which are based on the MATLAB software platform () The Data Processing Assistant for Resting-State fMRI (DPARSF, http://rfmri.org/DPARSF) and the Statistical Parametric Mapping (Spm8, http://www.fil.ion.ucl.ac.uk/spm), which are based on the MATLAB software platform (https://ww2.mathworks.cn/company /aboutus/contact_us.html?s_tid=gn_cntus), were used to analyze the data. The preprocessing steps consisted of (1) removing the first ten data points; (2) slice time correction; (3) three-dimensional motion correction (>3 mm, 3° was deleted); (4) spatial smoothing (full width at half maximum = 4 mm); (5) linear detrending; (6) normalize; and (7) temporally band-pass filtering (0.02 < f < 0.1 Hz) (fALFF data's band-pass filtering is after fALFF analysis).

Statistical analysis

Fractional amplitude of low-frequency fluctuation analysis

For the fALFF results, two-sample t-tests were used between the comatose patients and healthy controls. The area of P < 0.05 and voxel >16 was defined as a statistically significant difference with Alphasim correction.

Functional connectivity analysis

The precuneus as a node of the DMN was selected as the region of interest (ROI) in comatose patients, which was based on the result of fALFF analysis. The selected spherical radius was 6 mm. The coordinates of the Montreal Neurological Institute(MNI) space were −36, −75, and 33. To analyze FC, Fisher's r-to-z was used to transform the data to a normal distribution. Two-sample t-tests were used to detect the brain areas that have significantly different FC correlated with the precuneus between the two groups. The significance threshold was P < 0.05 (Alphasim correction).

The resulting images with abnormal activation were normalized to the OPENCH2 standard brain template with a resampling resolution of 3 mm × 3 mm × 3 mm by the Slice Viewer of Rest software (http://restfmri.net/forum/ZangYF_en): functional images were aligned to the structural image, and the structural image was aligned to the opench2 template. The strength of abnormal activation in the cluster level was recorded. Significant anatomical structures of the brain were positioned using xjView software (http://www.alivelearn.net/xjview/), and the regions of brain activation as well as the peak coordinate and the correlation strength (indicated by the t-test statistic “T,” the larger the T value, the stronger the correlation) were determined. The T values of the activated versus deactivated areas in two groups are summarized in the table.


   Results Top


Demographic statistics

Twenty comatose patients (4 – hypoxic-ischemic encephalopathy, 6 – cerebral infarction, 8 – cerebral trauma, and 2 – cerebral hemorrhage, and 13 males and 7 females, with the average age of 53.30 years) and 20 age-matched and gender-matched healthy controls (13 males and 7 females, with the average age of 55.60 years) were investigated. The differences in patient age were not statistically significant between the two groups based on the results from a two-sample t-test (P > 0.05).

Fractional amplitude of low-frequency fluctuation analysis

In the resting state, compared to the control group, the cerebral regions with a significant decrease in fALFF in the comatose patients included the right cingulate gyrus, left precuneus, right inferior parietal lobule, right superior parietal lobule, bilateral anterior/posterior central gyrus, middle frontal gyrus, right superior frontal gyrus, right superior temporal gyrus, and bilateral cerebellar hemispheres (P < 0.05, Alphasim correction) [Figure 1] and [Table 1].
Figure 1: Two-sample t-test between the comatose patient group and the control group in resting-state fractional amplitude of low-frequency fluctuation, P < 0.01, cluster size >16 voxels. Blue areas indicate the cerebral regions in which the fractional amplitude of low-frequency fluctuation of comatose patients was significantly lower than the control group

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Table 1: Statistical analysis of resting-state fractional amplitude of low-frequency fluctuation between the comatose patient group and the control group (P<0.01)

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Functional connectivity analysis

Compared with controls, the brain region FC correlated with the precuneus increased mainly located in the left superior frontal gyrus, left side of the callosum, left superior parietal lobule, and both sides of the cingulate (P < 0.05, Alphasim correction) [Figure 2] and [Table 2]. In addition, regions whose FC reduced include the bilateral inferior parietal lobule, posterior central gyrus, lenticular nucleus, left anterior central gyrus, left medial frontal gyrus, left anterior lobe of the cerebellum, right insula, right transverse temporal gyri, and right thalamus (P < 0.05, Alphasim correction) [Figure 3] and [Table 3].
Figure 2: Two-sample t-test between the comatose patient group and the control group in FC of the precuneus, P < 0.01, cluster size >16 voxels. Red areas indicate the cerebral regions with more noticeably increased function in the comatose patients than in the control group

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Table 2: Differences in functional connectivity of the precuneus between the comatose patient group and the control group (P<0.01)

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Figure 3: Two-sample t-test between the comatose patient group and control group in FC of the precuneus, P < 0.01, cluster size >16 voxels. Blue areas indicate the cerebral regions with more noticeably decreased function in the comatose patients than in the control group

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Table 3: Differences in functional connectivity of the precuneus between the comatose patient group and the control group (P<0.01)

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   Discussion Top


In recent years, the theory and clinical application of resting-state BOLD-fMRI technology has been advanced. Currently, the most frequently used data analysis methods include ReHo, ALFF, fALFF, and FC. These data analysis methods are used to extract resting-state BOLD-fMRI data for different diseases, and they greatly assist with the understanding of altered brain networks. In this study, the fALFF algorithm that was used can directly induce spontaneous activity of neurons to allow determination of the extent of variation of the BOLD signal relative to the baseline energy metabolism. Thus, fALFF can be used to observe brain activity in the resting state from the viewpoint of spontaneous neuronal activity, and the results are more direct and reliable. FC, another analysis algorithm used in this study, describes brain areas or nerve clusters that are not continuous, although they have a specific spatial distance and possess a certain synchronization or correlation in time.[6] In 2004, Sporns et al.[11] proposed a more precise definition of FC consisting of “a statistical dependency model caused by nonlinear dynamic activity of neurons or neuronal groups within the scope defined by anatomical connections.” FC is commonly used to measure the degree of correlation between various brain regions.

This study measured fALFF data of the whole brain from the low-frequency oscillation characteristics of the resting-state BOLD-fMRI signal, and the results indicated that compared to the control group, the comatose patients exhibited a significant reduction of fALFF in various brain regions including the right cingulate gyrus, left precuneus, right inferior parietal lobule, right superior parietal lobule, bilateral anterior/posterior central gyrus, middle frontal gyrus, right superior frontal gyrus, right superior temporal gyrus, and bilateral cerebellar hemispheres. These brain regions are similar to the default network configuration that has been validated by multiple studies;[9],[12] however, the spontaneous activity was reduced. According to this, we can speculate that the comatose patient group maintained the basic default network structure, but it was significantly reduced. Thus, we can presume that the pathogenesis of coma and disorders or defects of the default network structure are closely related.

The posterior cingulate/precuneus is a key node of the brain DMN in the resting state, as confirmed by multiple studies.[13] Our study found that the fALFF of those regions in comatose patients was reduced, which is closely related to the loss of cognitive function. Our study found that in both sides of the anterior central gyrus and the posterior central gyrus, the fALFF was significantly reduced, suggesting that spontaneous neural activity in these brain regions is decreased in coma patients, which could be the underlying reason for disorders of voluntary movement functions and sensory systems in comatose patients. The superior temporal gyrus is responsible for auditory speech, and the middle frontal gyrus primarily manages language processing. The fALFF was decreased in those regions in this study, indicating the lack of consciousness and function in comatose patients.

The superior parietal lobule mainly manages the integration of touch, pressure sensation, and proprioception; the decreases in fALFF lead to the inability to recognize the structure, size, and shape of objects in comatose patients. Currently, it is believed that the visual language center is located in the inferior parietal lobule.[14] The decreases in fALFF in those brain regions of comatose patients also suggest that although visual impairment is not present, the patients have reading impairments. The decreases in fALFF in the cerebellar hemisphere may explain the decline of body muscle tone and coordination in comatose patients. In our present study, we found that some of the brain regions in which the activity level was significantly decreased in comatose patients compared with that in the control group were located in the default network structure and some were not. Therefore, the decreased level of consciousness of comatose patients may not completely be attributable to disorders of the brain default network, but it can be speculated that an inextricable link exists between disorders of the default network and the serious decline in the level of awareness in unconscious patients.

The precuneus was considered as one of the most important nodes of the DMN in comatose patients.[15],[16] It may contain a wide range of differentiated cortical fibers that are responsible for collecting information from local or surrounding areas and allocate those resources. The precuneus has four main categorical features: visual-spatial imagery, episodic memory extraction, processing, and maintaining self-consciousness.[17] Functional neuroimaging studies have found that the functions of the precuneus, the adjacent PCC, and the prefrontal-temporoparietal association area are noticeably reduced in patients in a persistent vegetative state. If the patients regain consciousness, the precuneus will show the earliest recovery of activity.[18] The most important reason is that fALFF results showed that the left precuneus was significantly reduced in coma patients. Hence, the left precuneus was used as the ROI of the FC.

This study showed that compared to the control group, the degree of the FC was significantly reduced in some brain regions of comatose patients, and some connections to brain regions were lost, including those to the bilateral inferior parietal lobule, posterior central gyrus, lenticular nucleus, left anterior central gyrus, left medial frontal gyrus, left anterior lobe of the cerebellum, right insula, left transverse temporal gyrus, and right thalamus.

The results indicate that FC barriers were present between the precuneus and those brain regions. Through the study of the abnormal connections of neural networks in these regions, we can determine the abnormal neuropathological mechanisms of coma. Tsai et al.[10] confirmed that the absence of FC of the precuneus is an important factor that leads to disturbances of consciousness when studied in coma patients with reduced brain FC. Integration of the results from previous [13] and our studies indicates that the precuneus plays an important role in maintaining human consciousness.

In addition, our study also identified some cerebral regions whose FC noticeably increased in comatose patients including the left superior frontal gyrus, left side of the callosum, left superior parietal lobule, and both sides of the cingulate. In a study of the cognitive function of comatose patients, Caravasso et al.[19] observed that the degree of increased brain FC is consistent with the recovery of consciousness in coma patients, suggesting that the remodeling of brain FC could be an important stimulator of cognitive function recovery. Similarly, we hypothesize that the increased degree of FC of those brain regions could be associated with compensatory remodeling.


   Conclusion Top


Our study found that the normal and coma patients both maintained the basic default network structure, but it was significantly reduced in the coma patients; compared with normal, spontaneous activity of multiple brain areas was reduced in coma patients, which is related to the abnormality of the brain function network. The degree of the FC correlated with the precuneus was significantly reduced in some brain regions of comatose patients; we can indicate that the precuneus plays an important role in maintaining human consciousness. Measurements of fALFF and FC obtained by resting-state BOLD-fMRI have a unique advantage for the analysis and evaluation of the brain function in comatose patients, providing valuable information for the fundamental research of neural mechanisms of coma. However, to investigate the detailed mechanisms and predictive value of the changes in comatose patients, further study with larger samples of patients is necessary. The entire precuneus was considered in this study, but some scholars [20] have determined that the precuneus can be subdivided into three parts, each with different functional connections, which requires further study to analyze the functional connections based on each part of previous.

Acknowledgments

This work was supported by grants from the Natural Science Foundation of Guangxi Province, China (2014GXNSFAA118192), and the Foundation of Guangxi Educational Committee, China (ZD2014032).

Financial support and sponsorship

This work was supported by grants from the Natural Science Foundation of Guangxi Province, China (2014GXNSFAA118192), and Foundation of Guangxi Educational Committee, China (ZD2014032).

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Haupt WF, Hansen HC, Janzen RW, Firsching R, Galldiks N. Coma and cerebral imaging. Springerplus 2015;4:180.  Back to cited text no. 1
    
2.
Wang NN, Xu JM, Wang ZP. Application of magnetic resonance diffusion tensor imaging in intracerebral hemorrhage. Chin J Rehabil Theory Pract 2011;17:443-5.  Back to cited text no. 2
    
3.
Demertzi A, Antonopoulos G, Heine L, Voss HU, Crone JS, de Los Angeles C, et al. Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain 2015;138:2619-31.  Back to cited text no. 3
    
4.
Vanhaudenhuyse A, Noirhomme Q, Tshibanda LJ, Bruno MA, Boveroux P, Schnakers C, et al. Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. Brain 2010;133:161-71.  Back to cited text no. 4
    
5.
Zou QH, Zhu CZ, Yang Y, Zuo XN, Long XY, Cao QJ, et al. An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF. J Neurosci Methods 2008;172:137-41.  Back to cited text no. 5
    
6.
Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL, et al. A default mode of brain function. Proc Natl Acad Sci U S A 2001;98:676-82.  Back to cited text no. 6
    
7.
Shulman GL, Fiez JA, Corbetta M, Buckner RL, Miezin FM, Raichle ME, et al. Common blood flow changes across visual tasks: II. Decreases in cerebral cortex. J Cogn Neurosci 1997;9:648-63.  Back to cited text no. 7
    
8.
Mazoyer B, Zago L, Mellet E, Bricogne S, Etard O, Houdé O, et al. Cortical networks for working memory and executive functions sustain the conscious resting state in man. Brain Res Bull 2001;54:287-98.  Back to cited text no. 8
    
9.
Heine L, Soddu A, Gómez F, Vanhaudenhuyse A, Tshibanda L, Thonnard M, et al. Resting state networks and consciousness: Alterations of multiple resting state network connectivity in physiological, pharmacological, and pathological consciousness states. Front Psychol 2012;3:295.  Back to cited text no. 9
    
10.
Tsai YH, Yuan R, Huang YC, Yeh MY, Lin CP, Biswal BB, et al. Disruption of brain connectivity in acute stroke patients with early impairment in consciousness. Front Psychol 2014;4:956.  Back to cited text no. 10
    
11.
Sporns O, Chialvo DR, Kaiser M, Hilgetag CC. Organization, development and function of complex brain networks. Trends Cogn Sci 2004;8:418-25.  Back to cited text no. 11
    
12.
Guldenmund P, Vanhaudenhuyse A, Boly M, Laureys S, Soddu A. A default mode of brain function in altered states of consciousness. Arch Ital Biol 2012;150:107-21.  Back to cited text no. 12
    
13.
Lant ND, Gonzalez-Lara LE, Owen AM, Fernández-Espejo D. Relationship between the anterior forebrain mesocircuit and the default mode network in the structural bases of disorders of consciousness. Neuroimage Clin 2016;10:27-35.  Back to cited text no. 13
    
14.
Zeng ZS, Gao Y, Long LL. Regional brain functional connectivity in coma patients at restings tate: fMRI study. Neuroradiology 2012;28:823-5, 834.  Back to cited text no. 14
    
15.
Crone JS, Schurz M, Höller Y, Bergmann J, Monti M, Schmid E, et al. Impaired consciousness is linked to changes in effective connectivity of the posterior cingulate cortex within the default mode network. Neuroimage 2015;110:101-9.  Back to cited text no. 15
    
16.
Hannawi Y, Lindquist MA, Caffo BS, Sair HI, Stevens RD. Resting brain activity in disorders of consciousness: A systematic review and meta-analysis. Neurology 2015;84:1272-80.  Back to cited text no. 16
    
17.
Cavanna AE, Trimble MR. The precuneus: A review of its functional anatomy and behavioural correlates. Brain 2006;129:564-83.  Back to cited text no. 17
    
18.
Laureys S, Goldman S, Phillips C, Van Bogaert P, Aerts J, Luxen A, et al. Impaired effective cortical connectivity in vegetative state: Preliminary investigation using PET. Neuroimage 1999;9:377-82.  Back to cited text no. 18
    
19.
Falletta Caravasso C, De Pasquale F, Ciurli P, Catani S, Formisano R, Sabatini U, et al. The default mode network connectivity predicts cognitive recovery in severe acquired brain injured patients: A longitudinal study. J Neurotrauma 2016;33:1247-62.  Back to cited text no. 19
    
20.
Margulies DS, Vincent JL, Kelly C, Lohmann G, Uddin LQ, Biswal BB, et al. Precuneus shares intrinsic functional architecture in humans and monkeys. Proc Natl Acad Sci U S A 2009;106:20069-74.  Back to cited text no. 20
    


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