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		<title>BMC Medical Imaging - Latest articles</title>
		<link>http://www.biomedcentral.com/bmcmedimaging/</link>
		<description>The latest articles from BMC Medical Imaging (ISSN 1471-2342) published by 
				
				BioMed Central
		</description>
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				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/13"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/12"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/11"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/10"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/9"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/8"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/7"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/6"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/5"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/4"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2342/8/3"/>			    
            
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		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/13">
            
            <title>Extended Field Laser Confocal Microscopy (EFLCM): 
Combining automated gigapixel image capture with in silico virtual microscopy
</title>
			<description>Background:
Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has recently been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture.MethodUsing the combination of microlens enhanced Nipkow spinning disc confocal illumination together with fully automated image capture and large scale in silico image processing we have developed a system allowing the acquisition, presentation and analysis of maximum resolution confocal panorama images of several Gigapixel size. We call the method Extended Field Laser Confocal Microscopy (EFLCM).
Results:
We show using the EFLCM technique that it is possible to create a continuous confocal multi-colour mosaic from thousands of individually captured images. EFLCM can digitize and analyze histological slides, sections of entire rodent organ and full size embryos. It can also record hundreds of thousands cultured cells at multiple wavelength in single event or time-lapse fashion on fixed slides, in live cell imaging chambers or microtiter plates. 
Conclusions:
The observer independent image capture of EFLCM allows quantitative measurements of fluorescence intensities and morphological parameters on a large number of cells. EFLCM therefore bridges the gap between the mainly illustrative fluorescence microscopy and purely quantitative flow cytometry. EFLCM can also be used as high content analysis (HCA) instrument for automated screening processes.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/13</link>
			
			 	<dc:creator>Emilie Flaberg, Per Sabelstrom, Christer Strandh and Laszlo Szekely</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:13</dc:source>
			<dc:date>2008-07-16</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-13</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>13</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-16</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/12">
            
            <title>Does applying the Canadian Cervical Spine rule reduce cervical spine radiography rates in alert patients with blunt trauma to the neck? A retrospective analysis</title>
			<description>Background:
A cautious outlook towards neck injuries has been the norm to avoid missing cervical spine injuries. Consequently there has been an increased use of cervical spine radiography. The Canadian Cervical Spine rule was proposed to reduce unnecessary use of cervical spine radiography in alert and stable patients. Our aim was to see whether applying the Canadian Cervical Spine rule reduced the need for cervical spine radiography without missing significant cervical spine injuries.
Methods:
This was a retrospective study conducted in 2 hospitals. 114 alert and stable patients who had cervical spine radiographs for suspected neck injuries were included in the study. Data on patient demographics, high risk &amp; low risk factors as per the Canadian Cervical Spine rule and cervical spine radiography results were collected and analysed.
Results:
28 patients were included in the high risk category according to the Canadian Cervical Spine rule. 86 patients fell into the low risk category. If the Canadian Cervical Spine rule was applied, there would have been a significant reduction in cervical spine radiographs as 86/114 patients (75.4%) would not have needed cervical spine radiograph. 2/114 patients who had significant cervical spine injuries would have been identified when the Canadian Cervical Spine rule was applied.
Conclusion:
Applying the Canadian Cervical Spine rule for neck injuries in alert and stable patients would have reduced the use of cervical spine radiographs without missing out significant cervical spine injuries. This relates to reduction in radiation exposure to patients and health care costs.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/12</link>
			
			 	<dc:creator>Ulfin Rethnam, Rajam Yesupalan and Giri Gandham</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:12</dc:source>
			<dc:date>2008-06-16</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-12</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>12</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-16</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/11">
            
            <title>Computer-assisted assessment of the Human Epidermal Growth Factor Receptor 2 immunohistochemical assay in imaged histologic sections using a membrane isolation algorithm and quantitative analysis of positive controls</title>
			<description>Background:
Breast cancers that overexpress the human epidermal growth factor receptor 2 (HER2) are eligible for effective biologically targeted therapies, such as trastuzumab. However, accurately determining HER2 overexpression, especially in immunohistochemically equivocal cases, remains a challenge. Manual analysis of HER2 expression is dependent on the assessment of membrane staining as well as comparisons with positive controls. In spite of the strides that have been made to standardize the assessment process, intra- and inter-observer discrepancies in scoring is not uncommon. In this manuscript we describe a pathologist assisted, computer-based continuous scoring approach for increasing the precision and reproducibility of assessing imaged breast tissue specimens.
Methods:
Computer-assisted analysis on HER2 IHC is compared with manual scoring and fluorescence in situ hybridization results on a test set of 99 digitally imaged breast cancer cases enriched with equivocally scored (2+) cases. Image features are generated based on the staining profile of the positive control tissue and pixels delineated by a newly developed Membrane Isolation Algorithm. Evaluation of results was performed using Receiver Operator Characteristic (ROC) analysis.
Results:
A computer-aided diagnostic approach has been developed using a membrane isolation algorithm and quantitative use of positive immunostaining controls. By incorporating internal positive controls into feature analysis a greater Area Under the Curve (AUC) in ROC analysis was achieved than feature analysis without positive controls. Evaluation of HER2 immunostaining that utilized membrane pixels, controls, and percent area stained showed significantly greater AUC than manual scoring, and significantly less false positive rate when used to evaluate immunohistochemically equivocal cases.
Conclusion:
It has been shown that by incorporating both a membrane isolation algorithm and analysis of known positive controls a computer-assisted diagnostic algorithm was developed that can reproducibly score HER2 status in IHC stained clinical breast cancer specimens. For equivocal scoring cases, this approach performed better than standard manual evaluation as assessed by ROC analysis in our test samples. Finally, there exists potential for utilizing image-analysis techniques for improving HER2 scoring at the immunohistochemically equivocal range.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/11</link>
			
			 	<dc:creator>Bonnie H Hall, Monica Ianosi-Irimie, Parisa Javidian, Wenjin Chen, Shridar Ganesan and David J Foran</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:11</dc:source>
			<dc:date>2008-06-05</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-11</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>11</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-05</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/10">
            
            <title>Internet Image Viewer (iiV)</title>
			<description>Background:
Visualizing 3-dimensional (3-D) datasets is an important part of modern neuroimaging research. Many tools address this problem; however, they often fail to address specific needs and flexibility, such as the ability to work with different data formats, to control how and what data are displayed, to interact with values, and to undo mistakes.
Results:
iiV, an interactive software program for displaying 3-D brain images, is described. This tool was programmed to solve basic problems in 3-D data visualization. It is written in Java so it is extensible, is platform independent, and can display images within web pages.iiV displays 3-D images as 2-dimensional (2-D) slices with each slice being an independent object with independent features such as location, zoom, colors, labels, etc. Feature manipulation becomes easier by having a full set of editing capabilities including the following: undo or redo changes; drag, copy, delete and paste objects; and save objects with their features to a file for future editing. It can read multiple standard positron emission tomography (PET) and magnetic resonance imaging (MRI) file formats like ECAT, ECAT7, ANALYZE, NIfTI-1 and DICOM. We present sample applications to illustrate some of the features and capabilities.
Conclusion:
iiV is an image display tool with many useful features. It is highly extensible, platform independent, and web-compatible. This report summarizes its features and applications, while illustrating iiV's usefulness to the biomedical imaging community.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/10</link>
			
			 	<dc:creator>Joel T Lee, Kristin R Munch, John V Carlis and Jos&#233; V Pardo</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:10</dc:source>
			<dc:date>2008-05-29</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-10</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>10</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-05-29</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/9">
            
            <title>Automatic volumetry on MR brain images can support diagnostic decision making</title>
			<description>Background:
Diagnostic decisions in clinical imaging currently rely almost exclusively on visual image interpretation. This can lead to uncertainty, for example in dementia disease, where some of the changes resemble those of normal ageing. We hypothesized that extracting volumetric data from patients' MR brain images, relating them to reference data and presenting the results as a colour overlay on the grey scale data would aid diagnostic readers in classifying dementia disease versus normal ageing.
Methods:
A proof-of-concept forced-choice reader study was designed using MR brain images from 36 subjects. Images were segmented into 43 regions using an automatic atlas registration-based label propagation procedure. Seven subjects had clinically probable AD, the remaining 29 of a similar age range were used as controls. Seven of the control subject data sets were selected at random to be presented along with the seven AD datasets to two readers, who were blinded to all clinical and demographic information except age and gender. Readers were asked to review the grey scale MR images and to record their choice of diagnosis (AD or non-AD) along with their confidence in this decision. Afterwards, readers were given the option to switch on a false-colour overlay representing the relative size of the segmented structures. Colorization was based on the size rank of the test subject when compared with a reference group consisting of the 22 control subjects who were not used as review subjects. The readers were then asked to record whether and how the additional information had an impact on their diagnostic confidence.
Results:
The size rank colour overlays were useful in 18 of 28 diagnoses, as determined by their impact on readers' diagnostic confidence. A not useful result was found in 6 of 28 cases. The impact of the additional information on diagnostic confidence was significant (p &lt; 0.02).
Conclusion:
Volumetric anatomical information extracted from brain images using automatic segmentation and presented as colour overlays can support diagnostic decision making.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/9</link>
			
			 	<dc:creator>Rolf A Heckemann, Alexander Hammers, Daniel Rueckert, Richard I Aviv, Christopher J Harvey and Joseph V Hajnal</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:9</dc:source>
			<dc:date>2008-05-23</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-9</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>9</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-05-23</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/8">
            
            <title>Application of reinforcement learning for segmentation of transrectal ultrasound images</title>
			<description>Background:
Among different medical image modalities, ultrasound imaging has a very widespread clinical use. But, due to some factors, such as poor image contrast, noise and missing or diffuse boundaries, the ultrasound images are inherently difficult to segment. An important application is estimation of the location and volume of the prostate in transrectal ultrasound (TRUS) images. For this purpose, manual segmentation is a tedious and time consuming procedure.
Methods:
We introduce a new method for the segmentation of the prostate in transrectal ultrasound images, using a reinforcement learning scheme. This algorithm is used to find the appropriate local values for sub-images and to extract the prostate. It contains an offline stage, where the reinforcement learning agent uses some images and manually segmented versions of these images to learn from. The reinforcement agent is provided with reward/punishment, determined objectively to explore/exploit the solution space. After this stage, the agent has acquired knowledge stored in the Q-matrix. The agent can then use this knowledge for new input images to extract a coarse version of the prostate.
Results:
We have carried out experiments to segment TRUS images. The results demonstrate the potential of this approach in the field of medical image segmentation.
Conclusion:
By using the proposed method, we can find the appropriate local values and segment the prostate. This approach can be used for segmentation tasks containing one object of interest. To improve this prototype, more investigations are needed.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/8</link>
			
			 	<dc:creator>Farhang Sahba, Hamid R Tizhoosh and Magdy MA Salama</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:8</dc:source>
			<dc:date>2008-04-22</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-8</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>8</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-04-22</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/7">
            
            <title>Data-driven haemodynamic response function extraction using Fourier-wavelet regularised deconvolution</title>
			<description>Background:
We present a simple, data-driven method to extract haemodynamic response functions (HRF) from functional magnetic resonance imaging (fMRI) time series, based on the Fourier-wavelet regularised deconvolution (ForWaRD) technique. HRF data are required for many fMRI applications, such as defining region-specific HRFs, effciently representing a general HRF, or comparing subject-specific HRFs.
Results:
ForWaRD is applied to fMRI time signals, after removing low-frequency trends by a wavelet-based method, and the output of ForWaRD is a time series of volumes, containing the HRF in each voxel. Compared to more complex methods, this extraction algorithm requires few assumptions (separability of signal and noise in the frequency and wavelet domains and the general linear model) and it is fast (HRF extraction from a single fMRI data set takes about the same time as spatial resampling). The extraction method is tested on simulated event-related activation signals, contaminated with noise from a time series of real MRI images. An application for HRF data is demonstrated in a simple event-related experiment: data are extracted from a region with significant effects of interest in a first time series. A continuous-time HRF is obtained by fitting a nonlinear function to the discrete HRF coeffcients, and is then used to analyse a later time series.
Conclusion:
With the parameters used in this paper, the extraction method presented here is very robust to changes in signal properties. Comparison of analyses with fitted HRFs and with a canonical HRF shows that a subject-specific, regional HRF significantly improves detection power. Sensitivity and specificity increase not only in the region from which the HRFs are extracted, but also in other regions of interest.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/7</link>
			
			 	<dc:creator>Alle Meije Wink, Hans Hoogduin and Jos BTM Roerdink</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:7</dc:source>
			<dc:date>2008-04-10</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-7</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>7</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-04-10</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/6">
            
            <title>Ultrasound evaluation in combination with finger extension force measurements of the forearm musculus extensor digitorum communis in healthy subjects</title>
			<description>Background:
The aim of this study was to evaluate the usefulness of an ultrasound-based method of examining extensor muscle architecture, especially the parameters important for force development. This paper presents the combination of two non-invasive methods for studying the extensor muscle architecture using ultrasound simultaneously with finger extension force measurements.
Methods:
M. extensor digitorum communis (EDC) was examined in 40 healthy subjects, 20 women and 20 men, aged 35&#8211;73 years. Ultrasound measurements were made in a relaxed position of the hand as well as in full contraction. Muscle cross-sectional area (CSA), pennation angle and contraction patterns were measured with ultrasound, and muscle volume and fascicle length were also estimated. Finger extension force was measured using a newly developed finger force measurement device.
Results:
The following muscle parameters were determined: CSA, circumference, thickness, pennation angles and changes in shape of the muscle CSA. The mean EDC volume in men was 28.3 cm3 and in women 16.6 cm3. The mean CSA was 2.54 cm2 for men and 1.84 cm2 for women. The mean pennation angle for men was 6.5&#176; and for women 5.5&#176;. The mean muscle thickness for men was 1.2 cm and for women 0.76 cm. The mean fascicle length for men was 7.3 cm and for women 5.0 cm. Significant differences were found between men and women regarding EDC volume (p &lt; 0.001), CSA (p &lt; 0.001), pennation angle (p &lt; 0.05), muscle thickness (p &lt; 0.001), fascicle length (p &lt; 0.001) and finger force (p &lt; 0.001). Changes in the shape of muscle architecture during contraction were more pronounced in men than women (p &lt; 0.01). The mean finger extension force for men was 96.7 N and for women 39.6 N. Muscle parameters related to the extension force differed between men and women. For men the muscle volume and muscle CSA were related to extension force, while for women muscle thickness was related to the extension force.
Conclusion:
Ultrasound is a useful tool for studying muscle architectures in EDC. Muscle parameters of importance for force development were identified. Knowledge concerning the correlation between muscle dynamics and force is of importance for the development of new hand training programmes and rehabilitation after surgery.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/6</link>
			
			 	<dc:creator>Sofia Brorsson, Anna Nilsdotter, Marita Hilliges, Christer Sollerman and Ylva Aurell</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:6</dc:source>
			<dc:date>2008-03-03</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-6</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>6</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-03-03</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/5">
            
            <title>Abdominal ultrasonography in HIV/AIDS patients in southwestern Nigeria</title>
			<description>Background:
Though the major target of the HIV-virus is the immune system, the frequency of abdominal disorders in HIV/AIDS patients has been reported to be second only to pulmonary disease. These abdominal manifestations may be on the increase as the use of antiretroviral therapy has increased life expectancy and improved quality of life. Ultrasonography is an easy to perform, non invasive, inexpensive and safe imaging technique that is invaluable in Africa where AIDS is most prevalent and where sophisticated diagnostic tools are not readily available. Purpose: To describe the findings and evaluate the clinical utility of abdominal ultrasonography in HIV/AIDS patients in Ibadan, Nigeria
Methods:
A Prospective evaluation of the abdominal ultrasonography of 391 HIV-positive patients as well as 391 age and sex-matched HIV-negative patients were carried out at the University College Hospital, Ibadan.
Results:
Of the 391 cases studied, 260 (66.5%) were females; the mean age was 38.02 years, (range 15&#8211;66 years). The disease was most prevalent in the 4th decade with an incidence of 40.4%. Compared with the HIV-negative individuals, the HIV+ group of patients had a significantly higher proportion of splenomegaly (13.5% vs. 7.7%; p &lt; 0.01), lymphadenopathy (2.0% vs. 1.3%; p &lt; 0.70), and renal abnormalities (8.4% vs. 3.8%; p &lt; 0.02). There were no differences in hepatic and pancreatic abnormalities between the HIV+ and HIV- groups. There were significantly fewer gallstones in the HIV+ group (1.4% vs. 5.1%; p &lt; 0.01).
Conclusion:
AIDS is a multi-systemic disease and its demographic and clinical pattern remains the same globally. Ultrasonography is optimally suited for its clinical management especially in Africa. Its accuracy and sensitivity may be much improved with clinico-pathologic correlation which may not be readily available in developing countries; further studies may provide this much needed diagnostic algorithms.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/5</link>
			
			 	<dc:creator>Millicent O Obajimi, Mojisola O Atalabi, Godwin I Ogbole, Adenike T Adeniji-Sofoluwe, Atinuke M Agunloye, Ademola J Adekanmi, Yvonne U Osuagwu, Sefiat A Olarinoye, Mojisola A Olusola-Bello, Ayotunde O Ogunseyinde, Yetunde A Aken'Ova and Isaac F Adewole</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:5</dc:source>
			<dc:date>2008-02-29</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-5</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>5</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-02-29</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/4">
            
            <title>Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping</title>
			<description>Background:
Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets.
Methods:
The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM).
Results:
A significant area of hypoperfusion (P &lt; 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM.
Conclusion:
The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/4</link>
			
			 	<dc:creator>Anthony J McGoron, Michael Capille, Michael F Georgiou, Pablo Sanchez, Juan Solano, Manuel Gonzalez-Brito and John W Kuluz</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:4</dc:source>
			<dc:date>2008-02-29</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-4</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>4</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-02-29</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2342/8/3">
            
            <title>Using magnetic resonance microscopy to study the growth dynamics of a glioma spheroid in collagen I: A case study</title>
			<description>Background:
Highly malignant gliomas are characterized by rapid growth, extensive local tissue infiltration and the resulting overall dismal clinical outcome. Gaining any additional insights into the complex interaction between this aggressive brain tumor and its microenvironment is therefore critical. Currently, the standard imaging modalities to investigate the crucial interface between tumor growth and invasion in vitro are light and confocal laser scanning microscopy. While immensely useful in cell culture, integrating these modalities with this cancer's clinical imaging method of choice, i.e. MRI, is a non-trivial endeavour. However, this integration is necessary, should advanced computational modeling be able to utilize these in vitro data to eventually predict growth behaviour in vivo. We therefore argue that employing the same imaging modality for both the experimental setting and the clinical situation it represents should have significant value from a data integration perspective. In this case study, we have investigated the feasibility of using a specific form of MRI, i.e. magnetic resonance microscopy or MRM, to study the expansion dynamics of a multicellular tumor spheroid in a collagen type I gel.
Methods:
An U87mEGFR human giloblastoma multicellular spheroid (MTS) containing approximately 4&#183;103 cells was generated and pipetted into a collagen I gel. The sample was then imaged using a T2-weighted 3D spoiled gradient echo pulse sequence on a 14T MRI scanner over a period of 12 hours with a temporal resolution of 3 hours at room temperature. Standard histopathology was performed on the MRM sample, as well as on control samples.
Results:
We were able to acquire three-dimensional MR images with a spatial resolution of 24 &#215; 24 &#215; 24 &#956;m3. Our MRM data successfully documented the volumetric growth dynamics of an MTS in a collagen I gel over the 12-hour period. The histopathology results confirmed cell viability in the MRM sample, yet displayed distinct patterns of cell proliferation and invasion as compared to control.
Conclusion:
In this study, we demonstrate that a specific form of MRI, i.e. magnetic resonance microscopy or MRM, can be used to study the dynamic growth of a multicellular tumor spheroid (MTS) with a single cell scale spatial resolution that approaches the level of light microscopy. We argue that MRM can be employed as a complementary non-invasive tool to characterize microscopic MTS expansion, and thus, together with integrative computational modeling, may allow bridging of the experimental and clinical scales more readily.</description>
			<link>http://www.biomedcentral.com/1471-2342/8/3</link>
			
			 	<dc:creator>Shuning Huang, David Vader, Zhihui Wang, Anat Stemmer-Rachamimov, David A Weitz, Guangping Dai, Bruce R Rosen and Thomas S Deisboeck</dc:creator>
			
			<dc:source>BMC Medical Imaging 2008, 8:3</dc:source>
			<dc:date>2008-01-29</dc:date>
			<dc:identifier>doi:10.1186/1471-2342-8-3</dc:identifier>
			
			
							
					<prism:publicationName>BMC Medical Imaging</prism:publicationName>
					
			
							
					<prism:issn>1471-2342</prism:issn>
					
			
							
					<prism:volume>8</prism:volume>
					
			
							
					<prism:startingPage>3</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-01-29</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
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