Magnetic resonance-guided direct shoulder arthrography for the detection of superior labrum anterior-posterior lesions using an open 1.0-T MRI scanner

Purpose: Direct magnetic resonance arthrography (MRA) offers increased diagnostic accuracy compared to conventional magnetic resonance imaging (MRI) in the detection of superior labrum anterior-posterior (SLAP) lesions. The aim of the present study was to present the technique of magnetic resonance-guided direct shoulder arthrography (MDSA), to evaluate the diagnostic value of this novel MRA procedure to detect SLAP lesions in comparison to the currently practiced MRI, and to correlate the radiological findings to the respective arthroscopic findings. Material and methods: Fifty-six patients with clinical signs of a SLAP lesion underwent both MRI examination and MDSA prior to arthroscopic surgery. The MRI of both interventions were compared with the arthroscopic findings. Statistical analysis was performed using the McNemar test. Results: Sensitivity, specificity, and accuracy for detecting SLAP lesions were 23%, 88%, and 54% on MRI and 80%, 81%, and 80% on MDSA, respectively. Sensitivity (p < 0.001) and accuracy (p = 0.001) in detection of SLAP lesions were significantly higher by MDSA whereas accuracy showed no significant differences (p = 0.625). Conclusions: The MDSA can be performed in an open 1.0-T MRI scanner with a high level of technical success and a reasonable methodical effort. The modification of MRA provides the requirements as a practicable routine shoulder magnetic resonance examination including arthrography to detect SLAP lesions. The diagnostic value is significantly better than MRI examinations without included arthrography, which currently predominates the clinical practice to investigate shoulder pathology

Experimental and numerical analysis of atmospheric propagation of high energy laser

The transmission of high power laser radiation through the atmosphere is influenced by turbulent motion of the air. As a result the beam experiences an alteration regarding its position and its distribution, which increases with increasing propagation length. In order to analyze the atmospheric influence on the laser beam propagation a disk laser with a maximum output power of 6 kW and a wavelength of 1.03 µm is operated on a 130 m long free transmission laser test range in Lampoldshausen. The test range is equipped with a variety of sensors, which continuously monitor the current status of the weather conditions. Power sensors and camera systems at the beginning and the end of the test range measure the laser beam parameters before and after propagation. The experimental results are compared with a numerical analysis of the laser beam propagation performed by the software TALAP (Turbulent Atmosphere and Laser Beam Propagation), developed at the Institute of Technical Physics of DLR. It is based on the Kolmogorov turbulence model, which considers turbulent cells of different scale sizes. First measurements of power transmission, diameter of the laser beam and variations of its center of gravity are performed on a sunny and on a rainy day. The results show a good correlations to the measurements of the turbulence strength and the visibility. A comparison to the numerical analysis has shown coincidences. Future measurements will be performed at different weather conditions and seasons. Experimental results will be used to modify the simulation software, if necessary

Standoff detection and classifcation procedure for bioorganic compounds by hyperspectral laser-induced fluorescence

The high and still increasing number of attacks by hazardous bioorganic materials makes enormous demands on their detection. A very high detection sensitivity and differentiability are essential, as well as a rapid identification with low false alarm rates. One single technology can hardly achieve this. Point sensors can collect and identify materials, but finding an appropriate position is time consuming and involves several risks. Laser based standoff detection, however, can immediately provide information on propagation and compound type of a released hazardous material. The coupling of both methods may illustrate a solution to optimize the acquisition and detection of hazardous substances. At DLR Lampoldshausen, bioorganic substances are measured, based on laser induced fluorescence (LIF), and subsequently classified. In this work, a procedure is presented, which utilizes lots of information (time-dependent spectral data, local information) and predicts the presence of hazardous substances by statistical data analysis. For that purpose, studies are carried out on a free transmission range at a distance of 22 m at two different excitation wavelengths alternating between 280 nm and 355 nm. Time-dependent fluorescence spectra are recorded by a gated intensified CCD camera (iCCD). An automated signal processing allows fast and deterministic data collection and a direct subsequent classification of the detected substances. The variation of the substance parameters (physical state, concentration) is included within this method

Value of diffusion weighted MR imaging as an early surrogate parameter for evaluation of tumor response to high-dose-rate brachytherapy of colorectal liver metastases

<p>Abstract</p> <p>Background</p> <p>To assess the value of diffusion weighted imaging (DWI) as an early surrogate parameter for treatment response of colorectal liver metastases to image-guided single-fraction ¹⁹²Ir-high-dose-rate brachytherapy (HDR-BT).</p> <p>Methods</p> <p>Thirty patients with a total of 43 metastases underwent CT- or MRI-guided HDR-BT. In 13 of these patients a total of 15 additional lesions were identified, which were not treated at the initial session and served for comparison. Magnetic resonance imaging (MRI) including breathhold echoplanar DWI sequences was performed prior to therapy (baseline MRI), 2 days after HDR-BT (early MRI) as well as after 3 months (follow-up MRI). Tumor volume (TV) and intratumoral apparent diffusion coefficient (ADC) were measured independently by two radiologists. Statistical analysis was performed using univariate comparison, ANOVA and paired t test as well as Pearson's correlation.</p> <p>Results</p> <p>At early MRI no changes of TV and ADC were found for non-treated colorectal liver metastases. In contrast, mean TV of liver lesions treated with HDR-BT increased by 8.8% (<it>p </it>= 0.054) while mean tumor ADC decreased significantly by 11.4% (<it>p </it>< 0.001). At follow-up MRI mean TV of non-treated metastases increased by 50.8% (<it>p </it>= 0.027) without significant change of mean ADC values. In contrast, mean TV of treated lesions decreased by 47.0% (<it>p </it>= 0.026) while the mean ADC increased inversely by 28.6% compared to baseline values (<it>p </it>< 0.001; Pearson's correlation coefficient of r = -0.257; p < 0.001).</p> <p>Conclusions</p> <p>DWI is a promising imaging biomarker for early prediction of tumor response in patients with colorectal liver metastases treated with HDR-BT, yet the optimal interval between therapy and early follow-up needs to be elucidated.</p

Gravitational Atom in Compactified Extra Dimensions

We consider quantum mechanical effects of the modified Newtonian potential in the presence of extra compactified dimensions. We develop a method to solve the resulting Schroedinger equation and determine the energy shifts caused by the Yukawa-type corrections of the potential. We comment on the possibility of detecting the modified gravitational bound state Energy spectrum by present day and future experiments.Comment: 12 pages, 2 figure

Transcriptional signature of an adult brain tumor in Drosophila.

BACKGROUND: Mutations and gene expression alterations in brain tumors have been extensively investigated, however the causes of brain tumorigenesis are largely unknown. Animal models are necessary to correlate altered transcriptional activity and tumor phenotype and to better understand how these alterations cause malignant growth. In order to gain insights into the in vivo transcriptional activity associated with a brain tumor, we carried out genome-wide microarray expression analyses of an adult brain tumor in Drosophila caused by homozygous mutation in the tumor suppressor gene brain tumor (brat). RESULTS: Two independent genome-wide gene expression studies using two different oligonucleotide microarray platforms were used to compare the transcriptome of adult wildtype flies with mutants displaying the adult bratk06028 mutant brain tumor. Cross-validation and stringent statistical criteria identified a core transcriptional signature of brat(k06028) neoplastic tissue. We find significant expression level changes for 321 annotated genes associated with the adult neoplastic brat(k06028) tissue indicating elevated and aberrant metabolic and cell cycle activity, upregulation of the basal transcriptional machinery, as well as elevated and aberrant activity of ribosome synthesis and translation control. One fifth of these genes show homology to known mammalian genes involved in cancer formation. CONCLUSION: Our results identify for the first time the genome-wide transcriptional alterations associated with an adult brain tumor in Drosophila and reveal insights into the possible mechanisms of tumor formation caused by homozygous mutation of the translational repressor brat.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Use of machine learning to shorten observation-based screening and diagnosis of autism

The Autism Diagnostic Observation Schedule-Generic (ADOS) is one of the most widely used instruments for behavioral evaluation of autism spectrum disorders. It is composed of four modules, each tailored for a specific group of individuals based on their language and developmental level. On average, a module takes between 30 and 60 min to deliver. We used a series of machine-learning algorithms to study the complete set of scores from Module 1 of the ADOS available at the Autism Genetic Resource Exchange (AGRE) for 612 individuals with a classification of autism and 15 non-spectrum individuals from both AGRE and the Boston Autism Consortium (AC). Our analysis indicated that 8 of the 29 items contained in Module 1 of the ADOS were sufficient to classify autism with 100% accuracy. We further validated the accuracy of this eight-item classifier against complete sets of scores from two independent sources, a collection of 110 individuals with autism from AC and a collection of 336 individuals with autism from the Simons Foundation. In both cases, our classifier performed with nearly 100% sensitivity, correctly classifying all but two of the individuals from these two resources with a diagnosis of autism, and with 94% specificity on a collection of observed and simulated non-spectrum controls. The classifier contained several elements found in the ADOS algorithm, demonstrating high test validity, and also resulted in a quantitative score that measures classification confidence and extremeness of the phenotype. With incidence rates rising, the ability to classify autism effectively and quickly requires careful design of assessment and diagnostic tools. Given the brevity, accuracy and quantitative nature of the classifier, results from this study may prove valuable in the development of mobile tools for preliminary evaluation and clinical prioritization—in particular those focused on assessment of short home videos of children—that speed the pace of initial evaluation and broaden the reach to a significantly larger percentage of the population at risk