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Accurate spatial dose delivery in radiotherapy is frequently complicated due to changes in the patient's internal anatomy during and in-between therapy segments. The recent introduction of hybrid MRI radiotherapy systems allows unequaled soft-tissue visualization during radiation delivery and can be used for dose reconstruction to quantify the impact of motion. To this end, knowledge of anatomical deformations obtained from continuous monitoring during treatment has to be combined with information on the spatio-temporal dose delivery to perform motion-compensated dose accumulation (MCDA). Here, the influence of the choice of deformable image registration algorithm, dose warping strategy, and magnetic resonance image resolution and signal-to-noise-ratio on the resulting MCDA is investigated. For a quantitative investigation, four 4D MRI-datasets representing typical patient observed motion patterns are generated using finite element modeling and serve as a gold standard. Energy delivery is simulated intra-fractionally in the deformed image space and, subsequently, MCDA-processed. Finally, the results are substantiated by comparing MCDA strategies on clinically acquired patient data. It is shown that MCDA is needed for correct quantitative dose reconstruction. For prostate treatments, using the energy per mass transfer dose warping strategy has the largest influence on decreasing dose estimation errors. [ABSTRACT FROM AUTHOR]

Image-guided radiotherapy (IGRT) allows observation of the location and shape of the tumor and organs-at-risk (OAR) over the course of a radiation cancer treatment. Such information may in turn be used for reducing geometric uncertainties during therapeutic planning, dose delivery and response assessment. However, given the multiple imaging modalities and/or contrasts potentially included within the imaging protocol over the course of the treatment, the current manual approach to determining tissue displacement may become time-consuming and error prone. In this context, variational multi-modal deformable image registration (DIR) algorithms allow automatic estimation of tumor and OAR deformations across the acquired images. In addition, they require short computational times and a low number of input parameters, which is particularly beneficial for online adaptive applications, which require on-the-fly adaptions with the patient on the treatment table. However, the majority of such DIR algorithms assume that all structures across the entire field-of-view (FOV) undergo a similar deformation pattern. Given that various anatomical structures may behave considerably different, this may lead to the estimation of anatomically implausible deformations at some locations, thus limiting their validity. Therefore, in this paper we propose an anatomically-adaptive variational multi-modal DIR algorithm, which employs a regionalized registration model in accordance with the local underlying anatomy. The algorithm was compared against two existing methods which employ global assumptions on the estimated deformations patterns. Compared to the existing approaches, the proposed method has demonstrated an improved anatomical plausibility of the estimated deformations over the entire FOV as well as displaying overall higher accuracy. Moreover, despite the more complex registration model, the proposed approach is very fast and thus suitable for online scenarios. Therefore, future adaptive IGRT workflows may benefit from an anatomically-adaptive registration model for precise contour propagation and dose accumulation, in areas showcasing considerable variations in anatomical properties. [ABSTRACT FROM AUTHOR]

This paper introduces the use of the proper generalized decomposition (PGD) method for the optical flow (OF) problem in a classical framework of Sobolev spaces, ie, optical flow methods including a robust energy for the data fidelity term together with a quadratic penalizer for the regularization term. A mathematical study of PGD methods is first presented for general regularization problems in the framework of (Hilbert) Sobolev spaces, and their convergence is then illustrated on OF computation. The convergence study is divided in two parts: (a) the weak convergence based on the Brézis‐Lieb decomposition and (b) the strong convergence based on a growth result on the sequence of descent directions. A practical PGD‐based OF implementation is then proposed and evaluated on freely available OF data sets. The proposed PGD‐based OF approach outperforms the corresponding non‐PGD implementation in terms of both accuracy and computation time for images containing a weak level of information, namely, low image resolution and/or low signal‐to‐noise ratio (SNR). [ABSTRACT FROM AUTHOR]

4D-MRI is a promising tool for organ exploration, target delineation and treatment planning. Intra-scan motion artifacts may be greatly reduced by increasing the imaging frame rate. However, poor signal-to-noise ratios (SNR) are observed when increasing spatial and/or frame number per physiological cycle, in particular in the abdomen. In the current work, the proposed 4D-MRI method favored spatial resolution, frame number, isotropic voxels and large field-of-view (FOV) during MR-acquisition. The consequential SNR penalty in the reconstructed data is addressed retrospectively using an iterative back-projection (IBP) algorithm. Practically, after computing individual spatial 3D deformations present in the images using a deformable image registration (DIR) algorithm, each 3D image is individually enhanced by fusing several successive frames in its local temporal neighborood, these latter being likely to cover common independent informations. A tuning parameter allows one to freely readjust the balance between temporal resolution and precision of the 4D-MRI. The benefit of the method was quantitatively evaluated on the thorax of 6 mice under free breathing using a clinically acceptable duration. Improved 4D cardiac imaging was also shown in the heart of 1 mice. Obtained results are compared to theoretical expectations and discussed. The proposed implementation is easily parallelizable and optimized 4D-MRI could thereby be obtained with a clinically acceptable duration. [ABSTRACT FROM AUTHOR]

The identification of sterilization agents is mandatory to achieve sterilization mechanisms in low-pressure discharges. A detailed account of each agent is required for improvements, development and establishment of plasma sterilization as an alternative to traditional sterilization processes. Sterilization agents are VUV and UV radiation, photodesorption producing volatile species and etching of spore coat and membrane. This work focuses on VUV and UV radiation as a sterilization agent of Bacillus atrophaeus spores. Four wavelength ranges are distinguished: the emission spectra above 300 nm, above 235 nm, above 112 nm and a full emission spectrum including active species. The range from 235 up to 300 nm without active species is identified to be the most capable for sterilizing Bacillus atrophaeus spores. [ABSTRACT FROM AUTHOR]

Cerebral metabolic changes that concur to motor and/or cognitive disorders in actively drinking alcoholics are not well established. We tested the hypothesis that chronic alcoholics exhibit profound alterations in the cerebral metabolism of scyllo-inositol. Brain metabolism was explored in nine actively drinking and 11 recently detoxified chronic alcoholics by in vivo brain 1H-MRS and in vitro 1H-MRS of blood serum and cerebrospinal fluid. The cohort was composed of individuals with acute, subacute or chronic encephalopathy or without any clinical encephalopathy. Chronic alcoholism is associated with a hitherto unrecognized accumulation of brain scyllo-inositol. Our results suggest that scyllo-inositol is produced within the central nervous system and shows a diffuse but heterogenous distribution in brain where it can persist several weeks after detoxification. Its highest levels were observed in subjects with a clinically symptomatic alcohol-related encephalopathy. When detected, brain scyllo-inositol takes part in a metabolic encephalopathy since it is associated with reduced N-acetylaspartate and increased creatine. High levels of cerebral scyllo-inositol are correlated with altered glial and neuronal metabolism. Our findings suggest that the accumulation of scyllo-inositol may precede and take part in the development of symptomatic alcoholic metabolic encephalopathy. [ABSTRACT FROM AUTHOR]

For the successful completion of medical interventional procedures, several concepts, such as daily positioning compensation, dose accumulation or delineation propagation, rely on establishing a spatial coherence between planning images and images acquired at different time instants over the course of the therapy. To meet this need, image-based motion estimation and compensation relies on fast, automatic, accurate and precise registration algorithms. However, image registration quickly becomes a challenging and computationally intensive task, especially when multiple imaging modalities are involved. In the current study, a novel framework is introduced to reduce the computational overhead of variational registration methods. The proposed framework selects representative voxels of the registration process, based on a supervoxel algorithm. Costly calculations are hereby restrained to a subset of voxels, leading to a less expensive spatial regularized interpolation process. The novel framework is tested in conjunction with the recently proposed EVolution multi-modal registration method. This results in an algorithm requiring a low number of input parameters, is easily parallelizable and provides an elastic voxel-wise deformation with a subvoxel accuracy. The performance of the proposed accelerated registration method is evaluated on cross-contrast abdominal T1/T2 MR-scans undergoing a known deformation and annotated CT-images of the lung. We also analyze the ability of the method to capture slow physiological drifts during MR-guided high intensity focused ultrasound therapies and to perform multi-modal CT/MR registration in the abdomen. Results have shown that computation time can be reduced by 75% on the same hardware with no negative impact on the accuracy. [ABSTRACT FROM AUTHOR]

Medical imaging is currently employed in the diagnosis, planning, delivery and response monitoring of cancer treatments. Due to physiological motion and/or treatment response, the shape and location of the pathology and organs-at-risk may change over time. Establishing their location within the acquired images is therefore paramount for an accurate treatment delivery and monitoring. A feasible solution for tracking anatomical changes during an image-guided cancer treatment is provided by image registration algorithms. Such methods are, however, often built upon elements originating from the computer vision/graphics domain. Since the original design of such elements did not take into consideration the material properties of particular biological tissues, the anatomical plausibility of the estimated deformations may not be guaranteed. In the current work we adapt two existing variational registration algorithms, namely Horn–Schunck and EVolution, to online soft tissue tracking. This is achieved by enforcing an incompressibility constraint on the estimated deformations during the registration process. The existing and the modified registration methods were comparatively tested against several quality assurance criteria on abdominal in vivo MR and CT data. These criteria included: the Dice similarity coefficient (DSC), the Jaccard index, the target registration error (TRE) and three additional criteria evaluating the anatomical plausibility of the estimated deformations. Results demonstrated that both the original and the modified registration methods have similar registration capabilities in high-contrast areas, with DSC and Jaccard index values predominantly in the 0.8–0.9 range and an average TRE of 1.6–2.0 mm. In contrast-devoid regions of the liver and kidneys, however, the three additional quality assurance criteria have indicated a considerable improvement of the anatomical plausibility of the deformations estimated by the incompressibility-constrained methods. Moreover, the proposed registration models maintain the potential of the original methods for online image-based guidance of cancer treatments. [ABSTRACT FROM AUTHOR]

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of  ∼1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions. [ABSTRACT FROM AUTHOR]

MR-guided high-dose-rate (HDR) brachytherapy has gained increasing interest as a treatment for patients with localized prostate cancer because of the superior value of MRI for tumor and surrounding tissues localization. To enable needle insertion into the prostate with the patient in the MR bore, a single needle MR-compatible robotic system involving needle-by-needle dose delivery has been developed at our institution. Throughout the intervention, dose delivery may be impaired by: (1) sub-optimal needle positioning caused by e.g. needle bending, (2) intra-operative internal organ motion such as prostate rotations or swelling, or intra-procedural rectum or bladder filling. This may result in failure to reach clinical constraints. To assess the first aforementioned challenge, a recent study from our research group demonstrated that the deposited dose may be greatly improved by real-time adaptive planning with feedback on the actual needle positioning. However, the needle insertion sequence is left to the doctor and therefore, this may result in sub-optimal dose delivery. In this manuscript, a new method is proposed to determine and update automatically the needle insertion sequence. This strategy is based on the determination of the most sensitive needle track. The sensitivity of a needle track is defined as its impact on the dose distribution in case of sub-optimal positioning. A stochastic criterion is thus presented to determine each needle track sensitivity based on needle insertion simulations. To assess the proposed sequencing strategy, HDR prostate brachytherapy was simulated on 11 patients with varying number of needle insertions. Sub-optimal needle positioning was simulated at each insertion (modeled by typical random angulation errors). In 91% of the scenarios, the dose distribution improved when the needle was inserted into the most compared to the least sensitive needle track. The computation time for sequencing was less than 6 s per needle track. The proposed needle insertion sequencing can therefore assist in delivering an optimal dose in HDR prostate brachytherapy. [ABSTRACT FROM AUTHOR]

The use of magnetic resonance (MR) thermometry for the monitoring of thermal ablation is rapidly expanding. However, this technique remains challenging for the monitoring of the treatment of cardiac arrhythmia by radiofrequency ablation due to the heart displacement with respiration and contraction. Recent studies have addressed this problem by compensating in-plane motion in real-time with optical-flow based tracking technique. However, these algorithms are sensitive to local variation of signal intensity on magnitude images associated with tissue heating. In this study, an optical-flow algorithm was combined with a principal component analysis method to reduce the impact of such effects. The proposed method was integrated to a fully automatic cardiac MR thermometry pipeline, compatible with a future clinical workflow. It was evaluated on nine healthy volunteers under free breathing conditions, on a phantom and in vivo on the left ventricle of a sheep. The results showed that local intensity changes in magnitude images had lower impact on motion estimation with the proposed method. Using this strategy, the temperature mapping accuracy was significantly improved. [ABSTRACT FROM AUTHOR]

In radiotherapy, abdominal and thoracic sites are candidates for performing motion tracking. With real-time control it is possible to adjust the multileaf collimator (MLC) position to the target position. However, positions are not perfectly matched and position errors arise from system delays and complicated response of the electromechanic MLC system. Although, it is possible to compensate parts of these errors by using predictors, residual errors remain and need to be compensated to retain target coverage. This work presents a method to statistically describe tracking errors and to automatically derive a patient-specific, per-segment margin to compensate the arising underdosage on-line, i.e. during plan delivery. The statistics of the geometric error between intended and actual machine position are derived using kernel density estimators. Subsequently a margin is calculated on-line according to a selected coverage parameter, which determines the amount of accepted underdosage. The margin is then applied onto the actual segment to accommodate the positioning errors in the enlarged segment. The proof-of-concept was tested in an on-line tracking experiment and showed the ability to recover underdosages for two test cases, increasing in the underdosed area about and , respectively. The used dose model was able to predict the loss of dose due to tracking errors and could be used to infer the necessary margins. The implementation had a running time of 23 ms which is compatible with real-time requirements of MLC tracking systems. The auto-adaptivity to machine and patient characteristics makes the technique a generic yet intuitive candidate to avoid underdosages due to MLC tracking errors. [ABSTRACT FROM AUTHOR]

Image registration is part of a large variety of medical applications including diagnosis, monitoring disease progression and/or treatment effectiveness and, more recently, therapy guidance. Such applications usually involve several imaging modalities such as ultrasound, computed tomography, positron emission tomography, x-ray or magnetic resonance imaging, either separately or combined. In the current work, we propose a non-rigid multi-modal registration method (namely EVolution: an edge-based variational method for non-rigid multi-modal image registration) that aims at maximizing edge alignment between the images being registered. The proposed algorithm requires only contrasts between physiological tissues, preferably present in both image modalities, and assumes deformable/elastic tissues. Given both is shown to be well suitable for non-rigid co-registration across different image types/contrasts (T1/T2) as well as different modalities (CT/MRI). This is achieved using a variational scheme that provides a fast algorithm with a low number of control parameters. Results obtained on an annotated CT data set were comparable to the ones provided by state-of-the-art multi-modal image registration algorithms, for all tested experimental conditions (image pre-filtering, image intensity variation, noise perturbation). Moreover, we demonstrate that, compared to existing approaches, our method possesses increased robustness to transient structures (i.e. that are only present in some of the images). [ABSTRACT FROM AUTHOR]

American Foulbrood is a severe, notifiable disease of the honey bee. It is caused by infection of bee larvae with spores of the gram-positive bacterium Paenibacillus larvae. Spores of this organism are found in high numbers in an infected hive and are highly resistant to physical and chemical inactivation methods. The procedures to rehabilitate affected apiaries often result in the destruction of beehive material. In this study we assess the suitability of a double inductively coupled low pressure plasma as a non-destructive, yet effective alternative inactivation method for bacterial spores of the model organism Bacillus subtilis on beehive material. Plasma treatment was able to effectively remove spores from wax, which, under protocols currently established in veterinary practice, normally is destroyed by ignition or autoclaved for sterilization. Spores were removed from wooden surfaces with efficacies significantly higher than methods currently used in veterinary practice, such as scorching by flame treatment. In addition, we were able to non-destructively remove spores from the highly delicate honeycomb wax structures, potentially making treatment of beehive material with double inductively coupled low pressure plasma part of a fast and reliable method to rehabilitate infected bee colonies with the potential to re-use honeycombs. [ABSTRACT FROM AUTHOR]

We have previously demonstrated the feasibility of monitoring ultrasound-mediated uptake of a hydrophilic model drug in real time with dynamic confocal fluorescence microscopy. In this study, we evaluate and correct the impact of photobleaching to improve the accuracy of pharmacokinetic parameter estimates. To model photobleaching of the fluorescent model drug SYTOX Green, a photobleaching process was added to the current two-compartment model describing cell uptake. After collection of the uptake profile, a second acquisition was performed when SYTOX Green was equilibrated, to evaluate the photobleaching rate experimentally. Photobleaching rates up to 5.0 10−3 s−1 were measured when applying power densities up to 0.2 W.cm−2. By applying the three-compartment model, the model drug uptake rate of 6.0 10−3 s−1 was measured independent of the applied laser power. The impact of photobleaching on uptake rate estimates measured by dynamic fluorescence microscopy was evaluated. Subsequent compensation improved the accuracy of pharmacokinetic parameter estimates in the cell population subjected to sonopermeabilization. [ABSTRACT FROM AUTHOR]

Magnetic resonance (MR) guided high intensity focused ultrasound and external beam radiotherapy interventions, which we shall refer to as beam therapies/interventions, are promising techniques for the non-invasive ablation of tumours in abdominal organs. However, therapeutic energy delivery in these areas becomes challenging due to the continuous displacement of the organs with respiration. Previous studies have addressed this problem by coupling high-framerate MR-imaging with a tracking technique based on the algorithm proposed by Horn and Schunck (H and S), which was chosen due to its fast convergence rate and highly parallelisable numerical scheme. Such characteristics were shown to be indispensable for the real-time guidance of beam therapies. In its original form, however, the algorithm is sensitive to local grey-level intensity variations not attributed to motion such as those that occur, for example, in the proximity of pulsating arteries.In this study, an improved motion estimation strategy which reduces the impact of such effects is proposed. Displacements are estimated through the minimisation of a variation of the H and S functional for which the quadratic data fidelity term was replaced with a term based on the linear L1norm, resulting in what we have called an L2–L1 functional.The proposed method was tested in the livers and kidneys of two healthy volunteers under free-breathing conditions, on a data set comprising 3000 images equally divided between the volunteers. The results show that, compared to the existing approaches, our method demonstrates a greater robustness to local grey-level intensity variations introduced by arterial pulsations. Additionally, the computational time required by our implementation make it compatible with the work-flow of real-time MR-guided beam interventions.To the best of our knowledge this study was the first to analyse the behaviour of an L1-based optical flow functional in an applicative context: real-time MR-guidance of beam therapies in moving organs. [ABSTRACT FROM AUTHOR]

For quality assurance and adaptive radiotherapy, validation of the actual delivered dose is crucial.Intrafractional anatomy changes cannot be captured satisfactorily during treatment with hitherto available imaging modalitites. Consequently, dose calculations are based on the assumption of static anatomy throughout the treatment. However, intra- and interfraction anatomy is dynamic and changes can be significant.In this paper, we investigate the use of an MR-linac as a dose tracking modality for the validation of treatments in abdominal targets where both respiratory and long-term peristaltic and drift motion occur.The on-line MR imaging capability of the modality provides the means to perform respiratory gating of both delivery and acquisition yielding a model-free respiratory motion management under free breathing conditions.In parallel to the treatment, the volumetric patient anatomy was captured and used to calculate the applied dose. Subsequently, the individual doses were warped back to the planning grid to obtain the actual dose accumulated over the entire treatment duration. Ultimately, the planned dose was validated by comparison with the accumulated dose.Representative for a site subject to breathing modulation, two kidney cases (25 Gy target dose) demonstrated the working principle on volunteer data and simulated delivery. The proposed workflow successfully showed its ability to track local dosimetric changes. Integration of the on-line anatomy information could reveal local dose variations  −2.3–1.5 Gy in the target volume of a volunteer dataset. In the adjacent organs at risk, high local dose errors ranging from  −2.5 to 1.9 Gy could be traced back. [ABSTRACT FROM AUTHOR]

Focal high-dose-rate (HDR) for prostate cancer has gained increasing interest as an alternative to whole gland therapy as it may contribute to the reduction of treatment related toxicity. For focal treatment, optimal needle guidance and placement is warranted. This can be achieved under MR guidance. However, MR-guided needle placement is currently not possible due to space restrictions in the closed MR bore. To overcome this problem, a MR-compatible, single-divergent needle-implant robotic device is under development at the University Medical Centre, Utrecht: placed between the legs of the patient inside the MR bore, this robot will tap the needle in a divergent pattern from a single rotation point into the tissue. This rotation point is just beneath the perineal skin to have access to the focal prostate tumor lesion. Currently, there is no treatment planning system commercially available which allows optimization of the dose distribution with such needle arrangement. The aim of this work is to develop an automatic inverse dose planning optimization tool for focal HDR prostate brachytherapy with needle insertions in a divergent configuration. A complete optimizer workflow is proposed which includes the determination of (1) the position of the center of rotation, (2) the needle angulations and (3) the dwell times. Unlike most currently used optimizers, no prior selection or adjustment of input parameters such as minimum or maximum dose or weight coefficients for treatment region and organs at risk is required. To test this optimizer, a planning study was performed on ten patients (treatment volumes ranged from 8.5 cm3to 23.3 cm3) by using 2–14 needle insertions. The total computation time of the optimizer workflow was below 20 min and a clinically acceptable plan was reached on average using only four needle insertions. [ABSTRACT FROM AUTHOR]

Image processing such as deformable image registration finds its way into radiotherapy as a means to track non-rigid anatomy. With the advent of magnetic resonance imaging (MRI) guided radiotherapy, intrafraction anatomy snapshots become technically feasible.MRI provides the needed tissue signal for high-fidelity image registration. However, acquisitions, especially in 3D, take a considerable amount of time. Pushing towards real-time adaptive radiotherapy, MRI needs to be accelerated without degrading the quality of information.In this paper, we investigate the impact of image resolution on the quality of motion estimations. Potentially, spatially undersampled images yield comparable motion estimations. At the same time, their acquisition times would reduce greatly due to the sparser sampling. In order to substantiate this hypothesis, exemplary 4D datasets of the abdomen were downsampled gradually. Subsequently, spatiotemporal deformations are extracted consistently using the same motion estimation for each downsampled dataset. Errors between the original and the respectively downsampled version of the dataset are then evaluated.Compared to ground-truth, results show high similarity of deformations estimated from downsampled image data. Using a dataset with voxel size, deformation fields could be recovered well up to a downsampling factor of 2, i.e. . In a therapy guidance scenario MRI, imaging speed could accordingly increase approximately fourfold, with acceptable loss of estimated motion quality. [ABSTRACT FROM AUTHOR]

MR-guided HIFU ablation is a promising technique for the non-invasive treatment of breast cancer. A phase I study was performed to assess the safety and treatment accuracy and precision of MR-HIFU ablation in breast cancer patients () using a newly developed MR-HIFU platform dedicated to applications in the breast. In this paper a technical analysis of the performance of the dedicated breast MR-HIFU system during breast tumors ablation is described. The main points of investigation were the spatial targeting accuracy and precision of the system and the performance of real-time respiration-corrected MR thermometry.The mean targeting accuracy was in the range of 2.4–2.6 mm, whereas the mean targeting precision was in the range of 1.5–1.8 mm. To correct for respiration-induced magnetic field fluctuations during MR temperature mapping a look-up-table (LUT)-based correction method was used. An optimized procedural sedation protocol in combination with the LUT-based correction method allowed for precise MR thermometry during the ablation procedure (temperature standard deviation <3 °C). No unwanted heating in the near field (i.e. skin) nor in the far field (pectoral muscle) was detected.The newly developed dedicated breast MR-HIFU system allows for safe, accurate and precise ablation of breast tumors. [ABSTRACT FROM AUTHOR]

For motion adaptive radiotherapy, dynamic multileaf collimator tracking can be employed to reduce treatment margins by steering the beam according to the organ motion.The Elekta Agility 160 MLC has hitherto not been evaluated for its tracking suitability. Both dosimetric performance and latency are key figures and need to be assessed generically, independent of the used motion sensor.In this paper, we propose the use of harmonic functions directly fed to the MLC to determine its latency during continuous motion. Furthermore, a control variable is extracted from a camera system and fed to the MLC. Using this setup, film dosimetry and subsequent γ statistics are performed, evaluating the response when tracking (MRI)-based physiologic motion in a closed-loop.The delay attributed to the MLC itself was shown to be a minor contributor to the overall feedback chain as compared to the impact of imaging components such as MRI sequences. Delay showed a linear phase behaviour of the MLC employed in continuously dynamic applications, which enables a general MLC-characterization. Using the exemplary feedback chain, dosimetry showed a vast increase in pass rate employing γ statistics.In this early stage, the tracking performance of the Agility using the test bench yielded promising results, making the technique eligible for translation to tracking using clinical imaging modalities. [ABSTRACT FROM AUTHOR]

The incorrect surface density of bacteria (4 x 106 cm-2) on the agar plate was given in the right column, line 16, on page 3 in section 3 'Substrate preparation'. The correct surface coverage was 2.2 x 103 cm-2. This surface coverage was selected to obtain a homogeneous surface coverage after 18 hours of incubation at 37 degC. The term 'monolayer surface coverage' in the same section is used to stress the fact that there is no multilayer of bacteria during the treatment and that the shadowing effects can be neglected. However, the surface is not fully covered by one continuous layer of bacteria. This error and ambiguity in the use of the term 'monolayer surface coverage' does not affect the interpretation of the results and conclusions in the article. Additionally, the names of Volker Schulz-von der Gathen and Nikolas Knake have been misspelled in the 'Acknowledgments'. The authors apologize for any inconvenience and confusion they may have caused. [ABSTRACT FROM AUTHOR]

Cold atmospheric pressure plasmas can be used for treatment of living tissues or for inactivation of bacteria or biological macromolecules. The treatment is usually characterized by a combined effect of UV and VUV radiation, reactive species and ions. This combination is usually beneficial for the effectiveness of the treatment but it makes the study of fundamental interaction mechanisms very difficult. Here we report on an effective separation of VUV/UV photons and heavy reactive species in the effluent of a microscale atmospheric pressure plasma jet (u-APPJ). The separation is realized by an additional flow of helium gas under well-defined flow conditions, which deflects heavy particles in the effluent without affecting the VUV and UV photons. Both components of the effluent, the photons and the reactive species, can be used separately or in combination for sample treatment. The results of treatment of a model plasma polymer film and vegetative Bacillus subtilis and Escherichia coli cells are shown and discussed. A simple model of the He gas flow and reaction kinetics of oxygen atoms in the gas phase and at the surface is used to provide a better understanding of the processes in the plasma effluent. The new jet modification, called X-Jet for its appearance, will simplify the investigation of interaction mechanisms of atmospheric pressure plasmas with biological samples. [ABSTRACT FROM AUTHOR]

Non-equilibrium low pressure-plasma discharges are extensively studied for their high potential in the field of sterilization and decontamination of medical devices. This increased interest in plasma discharges arises from, among other reasons, their capability not only to inactivate bacterial spores but also to eliminate, destroy or remove pathogenic biomolecules and thus to provide a one-step process assuring safety of treated instruments. However, recent studies have shown that optimal conditions leading to inactivation of spores and physical removal of pathogens differ significantly--the efficiency of spores sterilization is above all dependent on the UV radiation intensity, whereas high etching rates are connected with the presence of the etching agent, typically atomic oxygen. The aim of this contribution is to discuss and demonstrate the feasibility of Ar/N2/O2 low-pressure inductively coupled plasma discharges as an option to provide intense UV radiation while maintaining the high etching rates of biomolecules. [ABSTRACT FROM AUTHOR]