LUCID: A Cherenkov Tube Based Detector for Monitoring the ATLAS Experiment Luminosity

The LUCID (LUminosity Cherenkov Integrating Detector) apparatus is composed by two symmetric arms deployed at about 17 m from the ATLAS interaction point. The purpose of this detector, which will be installed in january 2008, is to monitor the luminosity delivered by the LHC machine to the ATLAS experiment. An absolute luminosity calibration is needed and it will be provided by a Roman Pot type detector with the two arms placed at about 240 m from the interaction point. Each arm of the LUCID detector is based on an aluminum vessel containing 20 Cherenkov tubes, 15 mm diameter and 1500 mm length, filled with C4F10 radiator gas at 1.5 bar. The Cherenkov light generated by charged particles above the threshold is collected by photomultiplier tubes (PMT) directly placed at the tubes end. The challenging aspect of this detector is its readout in an environment characterized by the high dose of radiation (about 0.7 Mrad/year at 10^33cm^2 s^-1) it must withstand. In order to fulfill these radiation hardness requirements the design of this detector went through extensive R&D whose main results will be presented at the conference. In the talk the test beam results relative to the two studied readout schemes (the second one, besides the one mentioned above, being based on quartz optical fibers transferring the Cherenkov light to multi-anode PMT placed at some distance from the detector) will be presented and relevance will be given to the criteria adopted to choose the one representing the baseline. Particular emphasis will be given to the results of radiation hardness tests performed on quartz window PMT (20 Mrad of gamma rays)

Gaussian Processes for real-time 3D motion and uncertainty estimation during MR-guided radiotherapy

Respiratory motion during radiotherapy causes uncertainty in the tumor's location, which is typically addressed by an increased radiation area and a decreased dose. As a result, the treatments' efficacy is reduced. The recently proposed hybrid MR-linac scanner holds the promise to efficiently deal with such respiratory motion through real-time adaptive MR-guided radiotherapy (MRgRT). For MRgRT, motion-fields should be estimated from MR-data and the radiotherapy plan should be adapted in real-time according to the estimated motion-fields. All of this should be performed with a total latency of maximally 200 ms, including data acquisition and reconstruction. A measure of confidence in such estimated motion-fields is highly desirable, for instance to ensure the patient's safety in case of unexpected and undesirable motion. In this work, we propose a framework based on Gaussian Processes to infer 3D motion-fields and uncertainty maps in real-time from only three readouts of MR-data. We demonstrated an inference frame rate up to 69 Hz including data acquisition and reconstruction, thereby exploiting the limited amount of required MR-data. Additionally, we designed a rejection criterion based on the motion-field uncertainty maps to demonstrate the framework's potential for quality assurance. The framework was validated in silico and in vivo on healthy volunteer data (n=5) acquired using an MR-linac, thereby taking into account different breathing patterns and controlled bulk motion. Results indicate end-point-errors with a 75th percentile below 1mm in silico, and a correct detection of erroneous motion estimates with the rejection criterion. Altogether, the results show the potential of the framework for application in real-time MR-guided radiotherapy with an MR-linac.Comment: This manuscript has supplementary files which can be downloaded at https://surfdrive.surf. nl/files/index.php/s/scLts9nJYXfbLMx. The files include videos that show reconstructed motion-fields and spatial uncertainty maps. See the Appendix for a description of all individual file

The effect of quarantine due to Covid-19 pandemic on seizure frequency in 102 adult people with epilepsy from Apulia and Basilicata regions, Southern Italy

Objective: following the COVID-19 pandemic, a quarantine was imposed to all of regions Italy by 9th March until 3rd May 2020. We investigated the effect of COVID-19 infection and quarantine on seizure frequency in adult people with epilepsy (PwE) of Apulia and Basilicata regions, Southern Italy. Methods: This is an observational, retrospective study based on prospective data collection of 102 successive PWE. The frequency of seizures was evaluated during pre-quarantine (January- February), quarantine (March-April), and post-quarantine period (May-June), while PwE were divided into A) cases responding to treatment with ≤ 1 seizure per year; B) cases responding to treatment with 2-5 seizure per year; C) cases with drug-resistant epilepsy with ≤ 4 seizures per month; D) cases with drug-resistant epilepsy with 5-10 seizures per month. PwE underwent several self-report questionnaires regarding therapeutic compliance, mood, stress and sleep during quarantine period. Results: Approximately 50 % of PwE showed seizure frequency changes (22.55 % an increase and 27.45 % a reduction) during quarantine. Seizure frequency significantly (p < 0.05) increased in PwE responding to treatment with ≤ 1 seizure per year, while significantly (p < 0.05) reduced in PwE with drug-resistant epilepsy with 5-10 seizures per month. The data was not influenced by therapeutic adherence, sleep and depression. The analysis of anxiety showed a moderate level of anxiety in PwE responding to treatment with < 1 seizure per year, while moderate stress was perceived by all PwE. Seizure frequency changes were related to quarantine, but not to COVID-19 infection. In fact, unlike other regions of Italy, particularly Northern Italy, Apulia and Basilicata regions were less affected by COVID-19 infection, and almost all PwE recognized the quarantine as a stressful event. Emotional distress and anxiety due to social isolation, but also the relative reduction of triggers for epileptic seizures were the most important factors for changes in seizure frequency. Conclusions: Our study adds to the growing concern that the indirect effects of COVID-19 pandemic will far outstrip the direct consequences of the infection

Non-rigid 3D motion estimation at high temporal resolution from prospectively undersampled k-space data using low-rank MR-MOTUS

With the recent introduction of the MR-LINAC, an MR-scanner combined with a radiotherapy LINAC, MR-based motion estimation has become of increasing interest to (retrospectively) characterize tumor and organs-at-risk motion during radiotherapy. To this extent, we introduce low-rank MR-MOTUS, a framework to retrospectively reconstruct time-resolved non-rigid 3D+t motion-fields from a single low-resolution reference image and prospectively undersampled k-space data acquired during motion. Low-rank MR-MOTUS exploits spatio-temporal correlations in internal body motion with a low-rank motion model, and inverts a signal model that relates motion-fields directly to a reference image and k-space data. The low-rank model reduces the degrees-of-freedom, memory consumption and reconstruction times by assuming a factorization of space-time motion-fields in spatial and temporal components. Low-rank MR-MOTUS was employed to estimate motion in 2D/3D abdominothoracic scans and 3D head scans. Data were acquired using golden-ratio radial readouts. Reconstructed 2D and 3D respiratory motion-fields were respectively validated against time-resolved and respiratory-resolved image reconstructions, and the head motion against static image reconstructions from fully-sampled data acquired right before and right after the motion. Results show that 2D+t respiratory motion can be estimated retrospectively at 40.8 motion-fields-per-second, 3D+t respiratory motion at 7.6 motion-fields-per-second and 3D+t head-neck motion at 9.3 motion-fields-per-second. The validations show good consistency with image reconstructions. The proposed framework can estimate time-resolved non-rigid 3D motion-fields, which allows to characterize drifts and intra and inter-cycle patterns in breathing motion during radiotherapy, and could form the basis for real-time MR-guided radiotherapy.Comment: 18 pages main text, 8 main figures, 1 main table, 12 supporting videos, 2 supporting figures, 1 supporting information PDF. Submitted to Magnetic Resonance in Medicine as Full Pape

Development and tests of a new prototype detector for the XAFS beamline at Elettra Synchrotron in Trieste

The XAFS beamline at Elettra Synchrotron in Trieste combines X-ray absorption spectroscopy and X-ray diffraction to provide chemically specific structural information of materials. It operates in the energy range 2.4-27 keV by using a silicon double reflection Bragg monochromator. The fluorescence measurement is performed in place of the absorption spectroscopy when the sample transparency is too low for transmission measurements or the element to study is too diluted in the sample. We report on the development and on the preliminary tests of a new prototype detector based on Silicon Drift Detectors technology and the SIRIO ultra low noise front-end ASIC. The new system will be able to reduce drastically the time needed to perform fluorescence measurements, while keeping a short dead time and maintaining an adequate energy resolution to perform spectroscopy. The custom-made silicon sensor and the electronics are designed specifically for the beamline requirements.Comment: Proceeding of the 6YRM 12th-14th Oct 2015 - L'Aquila (Italy). Accepted for publication on Journal of Physics: Conference Serie

Real-time myocardial landmark tracking for MRI-guided cardiac radio-ablation using Gaussian Processes

The high speed of cardiorespiratory motion introduces a unique challenge for cardiac stereotactic radio-ablation (STAR) treatments with the MR-linac. Such treatments require tracking myocardial landmarks with a maximum latency of 100 ms, which includes the acquisition of the required data. The aim of this study is to present a new method that allows to track myocardial landmarks from few readouts of MRI data, thereby achieving a latency sufficient for STAR treatments. We present a tracking framework that requires only few readouts of k-space data as input, which can be acquired at least an order of magnitude faster than MR-images. Combined with the real-time tracking speed of a probabilistic machine learning framework called Gaussian Processes, this allows to track myocardial landmarks with a sufficiently low latency for cardiac STAR guidance, including both the acquisition of required data, and the tracking inference. The framework is demonstrated in 2D on a motion phantom, and in vivo on volunteers and a ventricular tachycardia (arrhythmia) patient. Moreover, the feasibility of an extension to 3D was demonstrated by in silico 3D experiments with a digital motion phantom. The framework was compared with template matching - a reference, image-based, method - and linear regression methods. Results indicate an order of magnitude lower total latency (<10 ms) for the proposed framework in comparison with alternative methods. The root-mean-square-distances and mean end-point-distance with the reference tracking method was less than 0.8 mm for all experiments, showing excellent (sub-voxel) agreement. The high accuracy in combination with a total latency of less than 10 ms - including data acquisition and processing - make the proposed method a suitable candidate for tracking during STAR treatments

GPU-accelerated Bloch simulations and MR-STAT reconstructions using the Julia programming language

PURPOSE: MR-STAT is a relatively new multiparametric quantitative MRI technique in which quantitative paramater maps are obtained by solving a large-scale nonlinear optimization problem. Managing reconstruction times is one of the main challenges of MR-STAT. In this work we leverage GPU hardware to reduce MR-STAT reconstruction times. A highly optimized, GPU-compatible Bloch simulation toolbox is developed as part of this work that can be utilized for other quantitative MRI techniques as well. METHODS: The Julia programming language was used to develop a flexible yet highly performant and GPU-compatible Bloch simulation toolbox called BlochSimulators.jl. The runtime performance of the toolbox is benchmarked against other Bloch simulation toolboxes. Furthermore, a (partially matrix-free) modification of a previously presented (matrix-free) MR-STAT reconstruction algorithm is proposed and implemented using the Julia language on GPU hardware. The proposed algorithm is combined with BlochSimulators.jl and the resulting MR-STAT reconstruction times on GPU hardware are compared to previously presented MR-STAT reconstruction times. RESULTS: The BlochSimulators.jl package demonstrates superior runtime performance on both CPU and GPU hardware when compared to other existing Bloch simulation toolboxes. The GPU-accelerated partially matrix-free MR-STAT reconstruction algorithm, which relies on BlochSimulators.jl, allows for reconstructions of 68 seconds per two-dimensional (2D slice). CONCLUSION: By combining the proposed Bloch simulation toolbox and the partially matrix-free reconstruction algorithm, 2D MR-STAT reconstructions can be performed in the order of one minute on a modern GPU card. The Bloch simulation toolbox can be utilized for other quantitative MRI techniques as well, for example for online dictionary generation for MR Fingerprinting

Open and Hidden Charm Production in 920 GeV Proton-Nucleus Collisions

The HERA-B collaboration has studied the production of charmonium and open charm states in collisions of 920 GeV protons with wire targets of different materials. The acceptance of the HERA-B spectrometer covers negative values of xF up to xF=-0.3 and a broad range in transverse momentum from 0.0 to 4.8 GeV/c. The studies presented in this paper include J/psi differential distributions and the suppression of J/psi production in nuclear media. Furthermore, production cross sections and cross section ratios for open charm mesons are discussed.Comment: 5 pages, 9 figures, to be published in the proceedings of the 6th International Conference on Hyperons, Charm & Beauty Hadrons (BEACH04), Chicago, IL, June 27 - July 3, 200