[Acute lower gastrointestinal bleeding--an evidence-based algorithm for diagnosis and treatment]

Novel means to locate and treat lower gastrointestinal bleeding (lGB) allow to reduce the rate of required surgical interventions and help to limit the extend of resection. The risk stratification of patients with lGB is the primary step of our recommended treatment algorithm. Accordingly, risk stratifying instruments, which are only partly validated up to now, are gaining significance in lGB. Whereas, gastro-duodenoscopy and colonoscopy prior to angiography or scintigraphy are established diagnostic tools, capsule enteroscopy offers a novel approach to hemodynamic stable patients with lGB that are difficult to localize. With its every increasing sensitivity, Angio-Computer Tomography is likely to replace scintigraphy and diagnostic angiography in the very near future. In addition, recent advances in superselective microembolisation have been shown to have the potential rendering surgical interventions in a majority of patients with acute lGB unnecessary. The extend of required surgical resection is largely dependent on the success to localize the bleeding source of prior diagnostics. Only if the source is identified, a limited segmental resection should be performed. Should surgery be required, we suggest to maintain the effort to localize the bleeding, either by prior laparoscopy and/or by intraoperative entero-colonoscopy. Eventually, if the source of bleeding remains unclear total colectomy with ileorectal anastomosis represents the procedure of choice in patients with acute lGB.

Collapsed cone convolution and analytical anisotropic algorithm dose calculations compared to VMC++ Monte Carlo simulations in clinical cases

The purpose of this work was to study and quantify the differences in dose distributions computed with some of the newest dose calculation algorithms available in commercial planning systems. The study was done for clinical cases originally calculated with pencil beam convolution (PBC) where large density inhomogeneities were present. Three other dose algorithms were used: a pencil beam like algorithm, the anisotropic analytic algorithm (AAA), a convolution superposition algorithm, collapsed cone convolution (CCC), and a Monte Carlo program, voxel Monte Carlo (VMC++). The dose calculation algorithms were compared under static field irradiations at 6 MV and 15 MV using multileaf collimators and hard wedges where necessary. Five clinical cases were studied: three lung and two breast cases. We found that, in terms of accuracy, the CCC algorithm performed better overall than AAA compared to VMC++, but AAA remains an attractive option for routine use in the clinic due to its short computation times. Dose differences between the different algorithms and VMC++ for the median value of the planning target volume (PTV) were typically 0.4% (range: 0.0 to 1.4%) in the lung and -1.3% (range: -2.1 to -0.6%) in the breast for the few cases we analysed. As expected, PTV coverage and dose homogeneity turned out to be more critical in the lung than in the breast cases with respect to the accuracy of the dose calculation. This was observed in the dose volume histograms obtained from the Monte Carlo simulations.

Application and assessment of a robust elastic motion correction algorithm to dynamic MRI

The purpose of this study was to assess the performance of a new motion correction algorithm. Twenty-five dynamic MR mammography (MRM) data sets and 25 contrast-enhanced three-dimensional peripheral MR angiographic (MRA) data sets which were affected by patient motion of varying severeness were selected retrospectively from routine examinations. Anonymized data were registered by a new experimental elastic motion correction algorithm. The algorithm works by computing a similarity measure for the two volumes that takes into account expected signal changes due to the presence of a contrast agent while penalizing other signal changes caused by patient motion. A conjugate gradient method is used to find the best possible set of motion parameters that maximizes the similarity measures across the entire volume. Images before and after correction were visually evaluated and scored by experienced radiologists with respect to reduction of motion, improvement of image quality, disappearance of existing lesions or creation of artifactual lesions. It was found that the correction improves image quality (76% for MRM and 96% for MRA) and diagnosability (60% for MRM and 96% for MRA).

Testing the GlaaS algorithm for dose measurements on low- and high-energy photon beams using an amorphous silicon portal imager

The GLAaS algorithm for pretreatment intensity modulation radiation therapy absolute dose verification based on the use of amorphous silicon detectors, as described in Nicolini et al. [G. Nicolini, A. Fogliata, E. Vanetti, A. Clivio, and L. Cozzi, Med. Phys. 33, 2839-2851 (2006)], was tested under a variety of experimental conditions to investigate its robustness, the possibility of using it in different clinics and its performance. GLAaS was therefore tested on a low-energy Varian Clinac (6 MV) equipped with an amorphous silicon Portal Vision PV-aS500 with electronic readout IAS2 and on a high-energy Clinac (6 and 15 MV) equipped with a PV-aS1000 and IAS3 electronics. Tests were performed for three calibration conditions: A: adding buildup on the top of the cassette such that SDD-SSD = d(max) and comparing measurements with corresponding doses computed at d(max), B: without adding any buildup on the top of the cassette and considering only the intrinsic water-equivalent thickness of the electronic portal imaging devices device (0.8 cm), and C: without adding any buildup on the top of the cassette but comparing measurements against doses computed at d(max). This procedure is similar to that usually applied when in vivo dosimetry is performed with solid state diodes without sufficient buildup material. Quantitatively, the gamma index (gamma), as described by Low et al. [D. A. Low, W. B. Harms, S. Mutic, and J. A. Purdy, Med. Phys. 25, 656-660 (1998)], was assessed. The gamma index was computed for a distance to agreement (DTA) of 3 mm. The dose difference deltaD was considered as 2%, 3%, and 4%. As a measure of the quality of results, the fraction of field area with gamma larger than 1 (%FA) was scored. Results over a set of 50 test samples (including fields from head and neck, breast, prostate, anal canal, and brain cases) and from the long-term routine usage, demonstrated the robustness and stability of GLAaS. In general, the mean values of %FA remain below 3% for deltaD equal or larger than 3%, while they are slightly larger for deltaD = 2% with %FA in the range from 3% to 8%. Since its introduction in routine practice, 1453 fields have been verified with GLAaS at the authors' institute (6 MV beam). Using a DTA of 3 mm and a deltaD of 4% the authors obtained %FA = 0.9 +/- 1.1 for the entire data set while, stratifying according to the dose calculation algorithm, they observed: %FA = 0.7 +/- 0.9 for fields computed with the analytical anisotropic algorithm and %FA = 2.4 +/- 1.3 for pencil-beam based fields with a statistically significant difference between the two groups. If data are stratified according to field splitting, they observed %FA = 0.8 +/- 1.0 for split fields and 1.0 +/- 1.2 for nonsplit fields without any significant difference.

A two-microphone noise reduction system for cochlear implant users with nearby microphones. Part I: Signal processing algorithm design and development

Users of cochlear implant systems, that is, of auditory aids which stimulate the auditory nerve at the cochlea electrically, often complain about poor speech understanding in noisy environments. Despite the proven advantages of multimicrophone directional noise reduction systems for conventional hearing aids, only one major manufacturer has so far implemented such a system in a product, presumably because of the added power consumption and size. We present a physically small (intermicrophone distance 7 mm) and computationally inexpensive adaptive noise reduction system suitable for behind-the-ear cochlear implant speech processors. Supporting algorithms, which allow the adjustment of the opening angle and the maximum noise suppression, are proposed and evaluated. A portable real-time device for test in real acoustic environments is presented.

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Automatic algorithm for monitoring systolic pressure variation and difference in pulse pressure

BACKGROUND: Difference in pulse pressure (dPP) reliably predicts fluid responsiveness in patients. We have developed a respiratory variation (RV) monitoring device (RV monitor), which continuously records both airway pressure and arterial blood pressure (ABP). We compared the RV monitor measurements with manual dPP measurements. METHODS: ABP and airway pressure (PAW) from 24 patients were recorded. Data were fed to the RV monitor to calculate dPP and systolic pressure variation in two different ways: (a) considering both ABP and PAW (RV algorithm) and (b) ABP only (RV(slim) algorithm). Additionally, ABP and PAW were recorded intraoperatively in 10-min intervals for later calculation of dPP by manual assessment. Interobserver variability was determined. Manual dPP assessments were used for comparison with automated measurements. To estimate the importance of the PAW signal, RV(slim) measurements were compared with RV measurements. RESULTS: For the 24 patients, 174 measurements (6-10 per patient) were recorded. Six observers assessed dPP manually in the first 8 patients (10-min interval, 53 measurements); no interobserver variability occurred using a computer-assisted method. Bland-Altman analysis showed acceptable bias and limits of agreement of the 2 automated methods compared with the manual method (RV: -0.33% +/- 8.72% and RV(slim): -1.74% +/- 7.97%). The difference between RV measurements and RV(slim) measurements is small (bias -1.05%, limits of agreement 5.67%). CONCLUSIONS: Measurements of the automated device are comparable with measurements obtained by human observers, who use a computer-assisted method. The importance of the PAW signal is questionable.

JExample: Exploiting Dependencies Between Tests to Improve Defect Localization

To quickly localize defects, we want our attention to be focussed on relevant failing tests. We propose to improve defect localization by exploiting dependencies between tests, using a JUnit extension called JExample. In a case study, a monolithic white-box test suite for a complex algorithm is refactored into two traditional JUnit style tests and to JExample. Of the three refactorings, JExample reports five times fewer defect locations and slightly better performance (-8-12\%), while having similar maintenance characteristics. Compared to the original implementation, JExample greatly improves maintainability due the improved factorization following the accepted test quality guidelines. As such, JExample combines the benefits of test chains with test quality aspects of JUnit style testing.