Particle tracking, recognition and LET evaluation of out-of-field proton therapy delivered to a phantom with implants.

OBJECTIVE: This study aims to assess the composition of scattered particles generated in proton therapy for tumors situated proximal to titanium dental implants. The investigation involves decomposing the mixed field and recording Linear Energy Transfer (LET) spectra to quantify the influence of metallic dental inserts located behind the tumor. Approach: A therapeutic conformal proton beam was used to deliver the treatment plan to an anthropomorphic head phantom with two types of implants inserted in the target volume (made of titanium and plastic, respectively). The scattered radiation resulted during the irradiation was detected by a hybrid semiconductor pixel detector MiniPIX Timepix3 that was placed distal to the Spread-out Bragg peak. Visualization and field decomposition of stray radiation were generated using algorithms trained in particle recognition based on artificial intelligence convolution neural networks (AI CNN). Spectral sensitive aspects of the scattered radiation were collected using two angular positions of the detector relative to the beam direction: 0° and 60°. Results: Using AI CNN, 3 classes of particles were identified: protons, electrons & photons, and ions & fast neutrons. Placing a Titanium implant in the beam's path resulted in predominantly electrons and photons, contributing 52.2%, whereas for plastic implants, the contribution was 65.4%. Scattered protons comprised 45.5% and 31.9% with and without metal inserts, respectively. The LET spectra was derived for each group of particles identified, with values ranging from 0.01 to 7.5 keV·µm-1 for Titanium implants/plastic implants. The low-LET component was primarily composed of electrons and photons, while the high-LET component corresponded to protons and ions. Significance: This method, complemented by directional maps, holds potential for evaluating and validating treatment plans involving stray radiation near organs at risk, offering precise discrimination of the mixt field, enhancing in this way the LET calculation. .

Thermal neutron detection and track recognition method in reference and out-of-field radiotherapy FLASH electron fields using Timepix3 detectors.

Objective.This work presents a method for enhanced detection, imaging, and measurement of the thermal neutron flux.Approach. Measurements were performed in a water tank, while the detector is positioned out-of-field of a 20 MeV ultra-high pulse dose rate electron beam. A semiconductor pixel detector Timepix3 with a silicon sensor partially covered by a6LiF neutron converter was used to measure the flux, spatial, and time characteristics of the neutron field. To provide absolute measurements of thermal neutron flux, the detection efficiency calibration of the detectors was performed in a reference thermal neutron field. Neutron signals are recognized and discriminated against other particles such as gamma rays and x-rays. This is achieved by the resolving power of the pixel detector using machine learning algorithms and high-resolution pattern recognition analysis of the high-energy tracks created by thermal neutron interactions in the converter.Main results. The resulting thermal neutrons equivalent dose was obtained using conversion factor (2.13(10) pSv·cm2) from thermal neutron fluence to thermal neutron equivalent dose obtained by Monte Carlo simulations. The calibrated detectors were used to characterize scattered radiation created by electron beams. The results at 12.0 cm depth in the beam axis inside of the water for a delivered dose per pulse of 1.85 Gy (pulse length of 2.4µs) at the reference depth, showed a contribution of flux of 4.07(8) × 103particles·cm-2·s-1and equivalent dose of 1.73(3) nSv per pulse, which is lower by ∼9 orders of magnitude than the delivered dose.Significance. The presented methodology for in-water measurements and identification of characteristic thermal neutrons tracks serves for the selective quantification of equivalent dose made by thermal neutrons in out-of-field particle therapy.

Measurement of the time structure of FLASH beams using prompt gamma rays and secondary neutrons as surrogates.

Objective. The aim of this study was to investigate the feasibility of online monitoring of irradiation time (IRT) and scan time for FLASH proton radiotherapy using a pixelated semiconductor detector.Approach. Measurements of the time structure of FLASH irradiations were performed using fast, pixelated spectral detectors based on the Timepix3 (TPX3) chips with two architectures: AdvaPIX-TPX3 and Minipix-TPX3. The latter has a fraction of its sensor coated with a material to increase sensitivity to neutrons. With little or no dead time and an ability to resolve events that are closely spaced in time (tens of nanoseconds), both detectors can accurately determine IRTs as long as pulse pile-up is avoided. To avoid pulse pile-up, the detectors were placed well beyond the Bragg peak or at a large scattering angle. Prompt gamma rays and secondary neutrons were registered in the detectors' sensors and IRTs were calculated based on timestamps of the first charge carriers (beam-on) and the last charge carriers (beam-off). In addition, scan times inx,y, and diagonal directions were measured. The experiment was carried out for various setups: (i) a single spot, (ii) a small animal field, (iii) a patient field, and (iv) an experiment using an anthropomorphic phantom to demonstratein vivoonline monitoring of IRT. All measurements were compared to vendor log files.Main results. Differences between measurements and log files for a single spot, a small animal field, and a patient field were within 1%, 0.3% and 1%, respectively.In vivomonitoring of IRTs (95-270 ms) was accurate within 0.1% for AdvaPIX-TPX3 and within 6.1% for Minipix-TPX3. The scan times inx,y, and diagonal directions were 4.0, 3.4, and 4.0 ms, respectively.Significance. Overall, the AdvaPIX-TPX3 can measure FLASH IRTs within 1% accuracy, indicating that prompt gamma rays are a good surrogate for primary protons. The Minipix-TPX3 showed a somewhat higher discrepancy, likely due to the late arrival of thermal neutrons to the detector sensor and lower readout speed. The scan times (3.4 ± 0.05 ms) in the 60 mm distance ofy-direction were slightly less than (4.0 ± 0.06 ms) in the 24 mm distance ofx-direction, confirming the much faster scanning speed of the Y magnets than that of X. Diagonal scan speed was limited by the slower X magnets.

Single proton LET characterization with the Timepix detector and artificial intelligence for advanced proton therapy treatment planning.

Objective.Protons have advantageous dose distributions and are increasingly used in cancer therapy. At the depth of the Bragg peak range, protons produce a mixed radiation field consisting of low- and high-linear energy transfer (LET) components, the latter of which is characterized by an increased ionization density on the microscopic scale associated with increased biological effectiveness. Prediction of the yield and LET of primary and secondary charged particles at a certain depth in the patient is performed by Monte Carlo simulations but is difficult to verify experimentally.Approach.Here, the results of measurements performed with Timepix detector in the mixed radiation field produced by a therapeutic proton beam in water are presented and compared to Monte Carlo simulations. The unique capability of the detector to perform high-resolution single particle tracking and identification enhanced by artificial intelligence allowed to resolve the particle type and measure the deposited energy of each particle comprising the mixed radiation field. Based on the collected data, biologically important physics parameters, the LET of single protons and dose-averaged LET, were computed.Main results.An accuracy over 95% was achieved for proton recognition with a developed neural network model. For recognized protons, the measured LET spectra generally agree with the results of Monte Carlo simulations. The mean difference between dose-averaged LET values obtained from measurements and simulations is 17%. We observed a broad spectrum of LET values ranging from a fraction of keVµm-1to about 10 keVµm-1for most of the measurements performed in the mixed radiation fields.Significance.It has been demonstrated that the introduced measurement method provides experimental data for validation of LETDor LET spectra in any treatment planning system. The simplicity and accessibility of the presented methodology make it easy to be translated into a clinical routine in any proton therapy facility.

Out-of-field measurements and simulations of a proton pencil beam in a wide range of dose rates using a Timepix3 detector: Dose rate, flux and LET.

Stray radiation produced by ultra-high dose-rates (UHDR) proton pencil beams is characterized using ASIC-chip semiconductor pixel detectors. A proton pencil beam with an energy of 220 MeV was utilized to deliver dose rates (DR) ranging from conventional radiotherapy DRs up to 270 Gy/s. A MiniPIX Timepix3 detector equipped with a silicon sensor and integrated readout electronics was used. The chip-sensor assembly and chipboard on water-equivalent backing were detached and immersed in the water-phantom. The deposited energy, particle flux, DR, and the linear energy transfer (LET(Si)) spectra were measured in the silicon sensor at different positions both laterally, at different depths, and behind the Bragg peak. At low-intensity beams, the detector is operated in the event-by-event data-driven mode for high-resolution spectral tracking of individual particles. This technique provides precise energy loss response and LET(Si) spectra with radiation field composition resolving power. At higher beam intensities a rescaling of LET(Si) can be performed as the distribution of the LET(Si) spectra exhibits the same characteristics regardless of the delivered DR. The integrated deposited energy and the absorbed dose can be thus measured in a wide range. A linear response of measured absorbed dose was obtained by gradually increasing the delivered DR to reach UHDR beams. Particle tracking of scattered radiation in data-driven mode could be performed at DRs up to 0.27 Gy/s. In integrated mode, the saturation limits were not reached at the measured out-of-field locations up to the delivered DR of over 270 Gy/s. A good agreement was found between measured and simulated absorbed doses.

A novel proton counting detector and method for the validation of tissue and implant material maps for Monte Carlo dose calculation.

The presence of artificial implants complicates the delivery of proton therapy due to inaccurate characterization of both the implant and the surrounding tissues. In this work, we describe a method to characterize implant and human tissue mimicking materials in terms of relative stopping power (RSP) using a novel proton counting detector. Each proton is tracked by directly measuring the deposited energy along the proton track using a fast, pixelated spectral detector AdvaPIX-TPX3 (TPX3). We considered three scenarios to characterize the RSPs. First, in-air measurements were made in the presence of metal rods (Al, Ti and CoCr) and bone. Then, measurements of energy perturbations in the presence of metal implants and bone in an anthropomorphic phantom were performed. Finally, sampling of cumulative stopping power (CSP) of the phantom were made at different locations of the anthropomorphic phantom. CSP and RSP information were extracted from energy spectra at each beam path. To quantify the RSP of metal rods we used the shift in the most probable energy (MPE) of CSP from the reference CSP without a rod. Overall, the RSPs were determined as 1.48, 2.06, 3.08, and 5.53 from in-air measurements; 1.44, 1.97, 2.98, and 5.44 from in-phantom measurements, for bone, Al, Ti and CoCr, respectively. Additionally, we sampled CSP for multiple paths of the anthropomorphic phantom ranging from 18.63 to 25.23 cm deriving RSP of soft tissues and bones in agreement within 1.6% of TOPAS simulations. Using minimum error of these multiple CSP, optimal mass densities were derived for soft tissue and bone and they are within 1% of vendor-provided nominal densities. The preliminary data obtained indicates the proposed novel method can be used for the validation of material and density maps, required by proton Monte Carlo Dose calculation, provided by competing multi-energy computed tomography and metal artifact reduction techniques.

The feasibility of integrating the Omaha system data across home care agencies and vendors.

Federal and state initiatives are aligning around the goal that by 2014 all Americans will have electronic health records to support access to their health information any time and anywhere. As a key healthcare provider, nursing data must be included to enhance patient safety, effectiveness, and efficiency of care that is patient-centric. The purpose of this study was to test the feasibility of abstracting, integrating, and comparing the effective use of a standardized terminology, the Omaha System, across software vendors and 15 home care agencies. Results showed that the 2900 patients in this study had an average of four problems on care plans, with interventions most frequently addressing surveillance (39%) and teaching (30%). Findings in this study support the feasibility of integrating data across software vendors and agencies as well as the usefulness for describing care provided in home care. However, before exchanging data across systems, data quality issues found in this study need attention. There were missing data for 10.8% of patients as well as concerns about the validity of using the problem rating scale for outcomes. Strategies for effective use of standardized nursing terminologies are recommended.

Variation in detection of adenomas and polyps by colonoscopy and change over time with a performance improvement program.

BACKGROUND & AIMS: There has been no prospective, community-based study to track changes in adenoma detection by individual physicians over time and to determine the effectiveness of targeted educational interventions. METHODS: We prospectively collected information on 47,253 screening colonoscopies in average-risk individuals 50 years and older performed by a community-based practice in the Twin Cities of Minnesota. During a period of 3 years, 5 specific interventions were implemented; each was designed to improve adenoma detection rates. Controlling for patient-related and procedure-related factors, rates of adenoma detection and 3-year trends for individual physicians were plotted, and intraclass correlation coefficients were calculated. Generalized estimating equations were used to identify factors associated with detection of adenomas and polyps. RESULTS: At least 1 polyp and 1 adenoma were found in 36% and 22% of examinations, respectively. Adenoma detection rates by endoscopists ranged from 10%-39%. There was no significant improvement during the study period despite planned, systematic interventions. Factors associated with adenoma detection included age of the patient (odds ratio [OR], 1.02; 95% confidence interval [CI], 1.02-1.02), male sex (OR, 1.53; 95% CI, 1.34-1.74), and adequate preparation quality (OR, 2.26; 95% CI, 1.64-3.12). CONCLUSIONS: The detection of adenomas by individual physicians during a 3-year period varied and did not appear to change between individual endoscopists, despite planned, systematic interventions. This indicates that other targeted interventions might be required to improve adenoma detection rates among experienced, community gastroenterologists.