Collimator Aperture Research Articles

Quality assurance for online adaptive radiotherapy: a secondary dose verification model with geometry-encoded U-Net

Abstract Background & Purpose: In online adaptive radiotherapy (ART), quick computation-based secondary dose verification is crucial for ensuring the quality of ART plans while the patient is positioned on the treatment couch. However, traditional dose verification algorithms are generally time-consuming, reducing the efficiency of ART workflow. This study aims to develop an ultra-fast deep-learning (DL) based secondary dose verification algorithm to accurately estimate dose distributions using CT and fluence maps (FMs). 
Methods: We integrated FMs into the CT image domain by explicitly resolving the geometry of treatment delivery. For each gantry angle, an FM was constructed based on the optimized multi-leaf collimator apertures and corresponding monitoring units (MUs). To effectively encode treatment beam configuration, the constructed FMs were back-projected to 30 cm away from the isocenter with respect to the exact geometry of the treatment machines. Then, a 3D U-Net was utilized to take the integrated CT and FM volume as input to estimate dose. Training and validation were performed on 381 prostate cancer cases, with an additional 40 testing cases for independent evaluation of model performance.
Results: The proposed model can estimate dose in ~15 ms for each patient. The average γ passing rate (3%/2mm, 10% threshold) for the estimated dose was 99.9% ± 0.15% on testing patients. The mean dose differences for the planning target volume (PTV) and organs at risk (OARs) were 0.07%±0.34% and 0.48%±0.72%, respectively.
Conclusion: We have developed a geometry-resolved DL framework for accurate dose estimation and demonstrated its potential in real-time online ART doses verification.

A mini review of plan quality and secondary cancer risk in CyberKnife M6 radiosurgery for benign intracranial tumors.

With advancements in medical technology, stereotactic radiosurgery (SRS) has become an essential option for treating benign intracranial tumors. Due to its minimal side effects and high local control rate, SRS is widely applied. This paper evaluates the plan quality and secondary cancer risk (SCR) in patients with benign intracranial tumors treated with the CyberKnife M6 system. The CyberKnife M6 robotic radiosurgery system features both multileaf collimator (MLC) and IRIS variable aperture collimator systems, providing different treatment options. The study included 15 patients treated with the CyberKnife M6 system, examining the differences in plan quality and SCR between MLC and IRIS systems. Results showed that MLC and IRIS plans had equal PTV (planning target volume) coverage (98.57% vs. 98.75%). However, MLC plans demonstrated better dose falloff and conformity index (CI: 1.81 ± 0.26 vs. 1.92 ± 0.27, P = 0.025). SCR assessment indicated that MLC plans had lower cancer risk estimates, with IRIS plans having average LAR (lifetime attributable risk) and EAR (excess absolute risk) values approximately 25% higher for cancer induction and 15% higher for sarcoma induction compared to MLC plans. The study showed that increasing tumor volume increases SCR probability, but there was no significant difference between different plans in PTV and brainstem analyses.

Bayesian optimization of a collimated HPGe detector model for Segmented Gamma Scanning

Segmented Gamma Scanning (SGS) is an important technique for quantifying gamma-emitting isotopes in radioactive waste packages. Collimated High-Purity Germanium (HPGe) detectors are commonly employed due to their superior resolution. However, calibrating HPGe detectors equipped with complex collimators poses challenges, especially regarding the modeling of the spatial response of the detector. This work introduces a calibration methodology for the Full Energy Peak Efficiency (FEPE) of HPGe detectors equipped with variable aperture collimators using Bayesian optimization to handle their complex geometries. The method and the model were then validated for the full range of application of the detector-collimator arrangement using experimental FEPE measurements, demonstrating the model’s potential for accurate SGS simulations.

Bricks non-destructive simulation testing method utilizing neutron radiography facility based on a 7Li(p,n)7Be reaction

The evaluation of non-destructive neutron radiography (NR) for examining the internal composition of various structural materials, has been the focus of extensive research. This manuscript uses non-destructive testing to generate three-dimensional radiographs of three different brick structural materials: glass block, magnesia-chrome, and lead to evaluate their capability to withstand fast neutrons and gammas emitted from a source. When neutrons with thermal or epithermal spectrum are required, the optimum combination for an accelerator was simulated using a 2.8 MeV proton beam on a lithium target. The presented facility tested both thermal and fast neutron radiography. This study examined various aperture diameters and collimator lengths. It found that implementing a special fast neutron filter significantly increased the thermal neutron content (TNC) with minimal impact on the thermal neutron flux. For fast neutron radiography, the study evaluated parameters such as geometric unsharpness, fast neutron flux, and the percentage of the uncollided fast neutron reaching the object. Both neutrons and photons from the source were used to inspect faults in a glass brick.

A Projection Integration Method for X-ray Collimator Design.

One of the recent trends in radiation therapy is to increaseconformal and accurate dose deliverysuch as in stereotactic radiosurgery (SRS). Treating small lesions and brain disorders requires the accurate placement of small radiation fields deep inside the human cranium.To design a collimator meeting these requirements, a new numerical concept was developed, which is presented here. The algorithm proposed here can generate beam profiles of plural collimation apertures and arbitrary initial beam spot distributions in a time-efficient method. It is an ideal tool to optimize collimator design for penumbra, dose rate, and field size. The intensity of the source beam spot is divided into slices, and each slice is projected onto the treatment plane at the isocenter through the collimator apertures.The illuminated field range and intensity are determined by geometry and the intensity of that slice of beam source, respectively.By integrating the projected intensity across all the slicesof the source profile, the profile on the treatment plane is obtained. The algorithm is used to generate beam profiles of a conical pencil beam collimator system and compare them to the Monte Carlo simulation as well as measurements. It canalso be used to demonstrate the impact of collimator shape on the beam penumbra, dose rate, and field size. The projection integration method provides a quick and informative tool for collimator design. The results were validated with the Monte Carlo simulation and measurements. This method was demonstrated to be effective for optimizing beam characteristics.

Calibration and performance evaluation of an N-type HPGe detector for a collimated and focused PGNAA system by experimental and Monte Carlo methods

The MCNP code was utilized to assess the operational status of an N-type high-purity germanium (HPGe) detector and to evaluate its potential for a collimated and focused Prompt Gamma Neutron Activation Analysis (PGNAA) detection system. In order to calibrate the detector, a narrow beam γ collimator was designed to scan the detector in both axial and radial directions. The curvature of the crystal front edge and the non-uniform description of the detector dead layer (DL) were taken into account when adjusting the effective crystal size. A collimated 137Cs γ source was used to assess the detection efficiency in the scanning experiments. Monte Carlo studies were performed using 0.662 MeV γ rays, and separately, a uniform γ-ray energy distribution from 0 to 1.6 MeV. Lastly, the effects of a collimation aperture with different sizes and different incident directions were considered to discuss the relationship between the spatial resolution and suitable measurement scenarios. Therefore, a detailed calibration method for non-uniform dead layers was introduced through a comparison between experiments and Monte Carlo simulations. This work reevaluates the performance of HPGe detectors and provides valuable data support for a detailed system design and γ spectroscopy analysis in future.

Feasibility of a Single-Fraction Stereotactic Dose of 30 Gy to Solitary Lung Lesions on Halcyon.

Purpose We sought to explore the feasibility of using the current co-planar Halcyon ring delivery system (RDS) with a novel multileaf collimator (MLC) aperture shape controller in delivering a single high dose of 30 Gy to solitary lung lesions via stereotactic body radiotherapy (SBRT). Materials and methods Thirteen non-small-cell lung cancer (NSCLC) patients previously treated with a single dose of 30 Gy to lung lesions via SBRT on the TrueBeam (6MV-FFF) using non-coplanar volumetric modulated arc therapy (VMAT) arcs were anonymized and replanned onto the Halcyon RDS (6MV-FFF) following RTOG-0915 single-fraction criteria. The Halcyon plans utilized a novel dynamic conformal arc (DCA)-based MLC-fitting approach before VMAT optimization with a user-defined aperture shape controller option. The clinical TrueBeam and Halcyon plans were compared via their protocol compliance, target conformity, gradient index, and dose to organs-at-risk (OAR). Treatment delivery efficacy and accuracy were assessed through end-to-end quality assurance (QA) tests on Halcyon and independent dose verification via in-house Monte Carlo (MC) second-check validation. Results All Halcyon lung SBRT plans met RTOG-0915 protocol's requirements for target coverage, conformity, and gradient indices, and maximum dose 2 cm away from the target (D2cm) while being statistically insignificant (p > 0.05) when compared to clinical TrueBeam plans. Additionally, Halcyon provided a similar dose to OAR except for the ribs, where Halcyon demonstrated a lower maximum dose (15.22 Gy vs 17.01 Gy, p < 0.001). However, Halcyon plans required a higher total monitor unit (8892 MU vs 7413 MU, p < 0.001), resulting in a higher beam modulation factor (2.96 MU/cGy vs 2.47 MU/cGy, p < 0.001) and an increase in beam-on time by a factor of 2.1 (11.11 min vs 5.3 min, p < 0.005). End-to-end QA measurements demonstrate that Halcyon plans were clinically acceptable with an average gamma passing rate of 99.8% for 2%/2mm criteria and independent MC 2nd checks within ±2.86%. Conclusion Our end-to-end testing and validation study demonstrates that by utilizing a DCA-based MLC aperture shape controller before VMAT optimization, Halcyon can be used for delivering a single dose of lung SBRT treatment. However, future improvements of Halcyon RDS are recommended to allow higher output rates, rotational couch corrections, and an integrated intrafraction motion management system that will further enhance Halcyon's capability for site-specific single dosage of SBRT.

A High-Sensitivity Benchtop X-Ray Fluorescence Emission Tomography (XFET) System With a Full-Ring of X-Ray Imaging-Spectrometers and a Compound-Eye Collimation Aperture.

The advent of metal-based drugs and metal nanoparticles as therapeutic agents in anti-tumor treatment has motivated the advancement of X-ray fluorescence computed tomography (XFCT) techniques. An XFCT imaging modality can detect, quantify, and image the biodistribution of metal elements using the X-ray fluorescence signal emitted upon X-ray irradiation. However, the majority of XFCT imaging systems and instrumentation developed so far rely on a single or a small number of detectors. This work introduces the first full-ring benchtop X-ray fluorescence emission tomography (XFET) system equipped with 24 solid-state detectors arranged in a hexagonal geometry and a 96-pinhole compound-eye collimator. We experimentally demonstrate the system's sensitivity and its capability of multi-element detection and quantification by performing imaging studies on an animal-sized phantom. In our preliminary studies, the phantom was irradiated with a pencil beam of X-rays produced using a low-powered polychromatic X-ray source (90kVp and 60W max power). This investigation shows a significant enhancement in the detection limit of gadolinium to as low as 0.1 mg/mL concentration. The results also illustrate the unique capabilities of the XFET system to simultaneously determine the spatial distribution and accurately quantify the concentrations of multiple metal elements.

Assessment of the axial resolution of a compact gamma camera with coded aperture collimator

PurposeHandheld gamma cameras with coded aperture collimators are under investigation for intraoperative imaging in nuclear medicine. Coded apertures are a promising collimation technique for applications such as lymph node localization due to their high sensitivity and the possibility of 3D imaging. We evaluated the axial resolution and computational performance of two reconstruction methods.MethodsAn experimental gamma camera was set up consisting of the pixelated semiconductor detector Timepix3 and MURA mask of rank 31 with round holes of 0.08 mm in diameter in a 0.11 mm thick Tungsten sheet. A set of measurements was taken where a point-like gamma source was placed centrally at 21 different positions within the range of 12–100 mm. For each source position, the detector image was reconstructed in 0.5 mm steps around the true source position, resulting in an image stack. The axial resolution was assessed by the full width at half maximum (FWHM) of the contrast-to-noise ratio (CNR) profile along the z-axis of the stack. Two reconstruction methods were compared: MURA Decoding and a 3D maximum likelihood expectation maximization algorithm (3D-MLEM).ResultsWhile taking 4400 times longer in computation, 3D-MLEM yielded a smaller axial FWHM and a higher CNR. The axial resolution degraded from 5.3 mm and 1.8 mm at 12 mm to 42.2 mm and 13.5 mm at 100 mm for MURA Decoding and 3D-MLEM respectively.ConclusionOur results show that the coded aperture enables the depth estimation of single point-like sources in the near field. Here, 3D-MLEM offered a better axial resolution but was computationally much slower than MURA Decoding, whose reconstruction time is compatible with real-time imaging.

Radiochirurgie des névralgies trigéminales avec accélérateur linéaire dédié sans cadre invasif : de la mise en service de l’appareil aux premiers résultats cliniques

PurposeRadiosurgery for the treatment of trigeminal neuralgia delivers a very high dose in a single fraction, over a few millimeters, at a single isocenter placed along the nerve. We present here the different steps that have been performed to validate small beams by conical collimators, and report the clinical results of the first patients treated on Novalis Tx®, frameless. Material and methodsFirst, the geometric accuracy of 4 and 6mm conical collimators was evaluated using Winston-Lutz tests; then dosimetric data acquisition was performed using high spatial resolution detectors (PTW 60019 microdiamond and a PTW 60017 E-diode). The corrective factors of the TRS 483 report were applied to calculate the collimator aperture factors. These dosimetric data were then compared with the data implemented in the iPlan® treatment planning system. Then end-to-end tests were performed to control the entire treatment process using an anthropomorphic phantom “STEEV”. Between 2020 and 2022, 18 patients were treated for refractory trigeminal neuralgia on Novalis Tx®, frameless, with Exactrac® repositioning. A total of 17 patients were evaluated (one was lost to follow-up) using the BNI score for pain assessment and MRI with a median follow-up of 12 months. ResultsThe quality criteria of geometric and dosimetric accuracy were met for the 6-mm cone but not for the 4-mm cone. All patients were treated with a 6-mm cone with a dose of 90Gy prescribed at the isocenter at the root entry zone. Initial pain control was obtained in 70.5% of our patients, and 53% maintained pain control with a median follow-up of 12 months. All recurrences occurred within 3 to 6 months after radiosurgery. No brainstem toxicity was observed. Six patients had non-disabling facial hypoesthesia, half of whom already had pretreatment hypoesthesia. ConclusionThe treatment of trigeminal neuralgia on a dedicated linear accelerator is a highly technical treatment whose accuracy and safety are paramount. The physical measurements allowed the commissioning of the technique with a 6mm cone. Our first clinical results are in accordance with the literature.

Methods to maximize detector count rates on small-angle neutron scattering diffractometers at reactor sources: II. Optimizing sample, source and detector sizes

Methods for maximizing the detector count rate for the same scattering angle range and resolution are related to choosing the optimum pinhole collimation parameters which include the source and sample aperture sizes and collimation lengths on small-angle neutron scattering diffractometers located at reactor neutron sources. Calculations and experimental measurements are presented that show enhancements in count rate with the same q-resolution can be achieved by combining both longer flight paths with larger source and sample apertures and beam stop sizes. To be able to both accommodate the larger beam sizes at the detector and to maintain the same range in scattering angle, existing and new detector placement strategies are presented that extend the scattering angle range beyond what is capable with a single 2-D detector.

EDIRNet: an unsupervised deformable registration model for X-ray and neutron images.

For high-precision industrial non-destructive testing, multimodal image registration technology can be employed to register X-ray and neutron images. X-ray and neutron image registration algorithms usually use conventional methods through iterative optimization. These methods will increase the cost of registration time and require more initialization parameters. The imaging results of internal sample structures can suffer from edge blurring due to the influence of a neutron beam collimator aperture, X-ray focal point, and imaging angles. We present an unsupervised learning model, EDIRNet, based on deep learning for deformable registration of X-ray and neutron images. We define the registration process as a function capable of estimating the flow field from input images. By leveraging deep learning techniques, we effectively parameterize this function. Consequently, given a registration image, our optimized network parameters enable rapid and direct estimation of the flow field between the images. We design an attention-based edge enhancement module to enhance the edge features of the image. For evaluating our presented network model, we utilize a dataset including 552 pairs of X-ray and neutron images. The experimental results show that the registration accuracy of EDIRNet reaches 93.09%. Compared with traditional algorithms, the accuracy of EDIRNet is improved by 3.17%, and the registration time is reduced by 28.75s.

Deep Learning-Based Single-View Fluorescence Dose Reconstruction for 3D Dosimetry

3D dose distribution measurement is crucial for precise radiotherapy. Radiation-excited fluorescence imaging has potential for the 3D dosimetry with high spatial resolution, but multiple fluorescence images from different view-angles are required for analytical reconstruction techniques. Furthermore, the imaging data are contaminated by anisotropic Cherenkov light emission and statistical noise. This project aims to establish a novel deep learning-based model to predict 3D dose distributions from a single-view 2D fluorescence image while simultaneously removing the adverse effects of Cherenkov signals and other noises. A total of 124 single-aperture static photon beams were delivered to an acrylic tank containing 1 g/L quinine hemisulfate water solution with varying aperture shapes and collimator angle. The emitted optical signals were detected by a low-cost CMOS camera for 20 seconds, and image pre-processing was performed to obtain input 2D fluorescence images with 0.3 × 0.3 mm spatial resolution. 3D back-projected dose distribution images were also calculated from the input fluorescence images. Ground-truth of 3D dose distributions and 2D field map images were obtained from a clinical treatment planning system with 1.4 × 1.4 × 1.4 mm spatial resolution. The proposed deep learning-based dose reconstruction method involved 3 steps. First, 2D fluence map images at the bottom plane of the tank were predicted from the fluorescence images by using a customized convolutional neural network (CNN). Second, the predicted fluence map images were transformed into the 2D field map images on the isocenter plane by applying perspective transformation. Finally, 2D dose distributions at a given radiological depth were calculated by using the predicted field map images, the back-projected dose distribution images, and the radiological depth value as inputs of a shallow CNN. Both CNN models were trained separately, and the 3D dose distributions were predicted by concatenating the output 2D dose distributions at various radiological depths. The proposed CNN model yielded accurate 2D field map images. Averaged Dice similarity coefficient and mean absolute error of the field maps in the test data was 92.0% ± 4.6% and 0.0132 ± 0.0113, respectively. Moreover, our deep learning-based approach was able to predict accurate 3D dose distributions from the 2D fluorescence images. Mean squared error and averaged 3D gamma passing ratio (3%/3mm) were 9.55 mGy ± 6.8 mGy and 86.3% ± 9.86%, respectively. Theproposed deep learning-based method calculated accurate 3D dose distributions from a single-view 2D fluorescence image. Since this technique require only a single CMOS camera image and fluorescent material, it can be readily used for any external radiotherapy modalities, including SRS/SBRT with small fields. This method is useful for acquiring 3D dose distribution data for precise dose verification within a few seconds.

Monte Carlo and experimental evaluation of a Timepix4 compact gamma camera for coded aperture nuclear medicine imaging with depth resolution

PurposeWe designed a prototype compact gamma camera (MediPROBE4) for nuclear medicine tasks, including radio-guided surgery and sentinel lymph node imaging with a 99mTc radiotracer. We performed Monte Carlo (MC) simulations for image performance assessment, and first spectroscopic imaging tests with a 300 μm thick silicon detector. MethodsThe hand-held camera (1 kg weight) is based on a Timepix4 readout circuit for photon-counting, energy-sensitive, hybrid pixel detectors (24.6 × 28.2 mm2 sensitive area, 55 μm pixel pitch), developed by the Medipix4 Collaboration. The camera design adopts a CdTe detector (1 or 2 mm thick) bump-bonded to a Timepix4 readout chip and a coded aperture collimator with 0.25 mm diameter round holes made of 3D printed 1-mm thick tungsten. Image reconstruction is performed via autocorrelation deconvolution. ResultsGeant4 MC simulations showed that, for a 99mTc source in air, at 50 mm source-collimator distance, the estimated collimator sensitivity (4 × 10−4) is 292 times larger than that of a single hole in the mask; the system sensitivity is 0.22 cps/kBq (2 mm CdTe); the lateral spatial resolution is 1.7 mm FWHM. The estimated axial longitudinal resolution is 8.2 mm FWHM at 40 mm distance. First experimental tests with a 300 μm thick Silicon pixel detector bump-bonded to a Timepix4 chip and a high-resolution coded aperture collimator showed time-over-threshold and time-of-arrival capabilities with 241Am and 133Ba gamma-ray sources. ConclusionsMC simulations and validation lab tests showed the expected performance of the MediPROBE4 compact gamma camera for gamma-ray 3D imaging.

Dosimetrical assessment of jaw tracking technique in volumetric modulated arc therapy for a sample of patients with lateralised targets

Abstract Introduction: In modulated radiotherapy treatments with the jaw tracking technique (JTT), the collimator jaws can dynamically follow the multileaf collimator apertures and reduce radiation leakage. This reduction protects normal tissue from unwanted doses. Previous research has highlighted the importance of defining which patients will benefit most from JTT. Besides, some authors have expressed their concerns about possible increases in monitor units (MUs). Treatments of patients with peripheral targets and isocentre located in the patient’s midline are of particular interest. The current work assessed the effect of JTT on these cases. Methods: JTT plans for thirty-two patients were compared to plans with the static jaws technique. The volumes of normal tissue receiving 5 Gy (V5), 10 Gy (V10) and 20 Gy (V20), mean dose (Dmean), target coverage parameters D95, D2% and Paddick’s conformity index (PCI) were compared. MUs were also registered for comparisons. The decrease in the jaws opening with JTT was correlated to the decrease in dose values in normal tissue. Results: Small decreases were observed in D95 and in D2% values, without statistical significance. A 5% average decrease in PCI values was noticed as well as significant decreases in V5, V10 and Dmean values, 9% on average. A 3% decrease in V20 was also observed. The number of MUs decreased by 2%. A significant correlation was found between the reduction of the secondary collimation opening areas and the dose delivered to normal tissue. Conclusions: JTT technique improved normal tissue protection in volumetric modulated arc therapy treatments for the patients included in the present study.

Deep Learning-Based Fluorescence Light Discrimination for High Spatial Resolution Radiotherapy Dose Verification

<h3>Purpose/Objective(s)</h3> High spatial resolution quality assurance techniques are crucial to assess complex dose distributions of modern radiotherapy. Radiation-excited fluorescence imaging has great potential for real-time absolute dosimetry with high spatial resolution. However, the imaging data are generally contaminated by noise due to Cherenkov and scattered lights. This project aims to establish a novel deep learning-based model to correct the fluorescence images for accurate dosimetric applications. <h3>Materials/Methods</h3> An acrylic box phantom containing 1 g/L quinine hemisulfate water solution was constructed. 200 MU single-aperture static beams were delivered to the phantom with varying aperture shapes, gantry angle and collimator angle, and emitted fluorescent signals were detected by a digital camera in 2.0 frames per second cine mode. Temporal filtering and down-sampling were applied to obtain fluorescence images with 1 × 1 mm spatial resolution at the isocenter plane. 2D projected dose distributions were obtained by performing forward projection calculation of the 3D dose distributions calculated by a clinical treatment planning system. The acquired noisy fluorescence images and projected dose distributions were set to inputs and labels of the deep learning modeling, respectively. A 22-layer 2D residual convolutional neural network (CNN) was generated, and 200-epoch supervised learning was performed using 73 training data. For evaluation, accuracy of the calculated projected dose distributions was compared with that of a conventional scatter-kernel deconvolution method. <h3>Results</h3> The deep learning model yielded accurate projected 3D dose distributions with high spatial resolution. In contrast to the conventional method based purely on the analysis of florescence imaging signal, our deep learning-based approach was able to mitigate the adverse effects of Cherenkov and other optical noises. Mean squared error of 7 normalized projected dose distributions in test data were improved from 0.053 for uncorrected to 0.029 for CNN-corrected images. Computation time requiring to calculate a projected dose distribution was 0.2 second with a GPU workstation. <h3>Conclusion</h3> The proposed deep learning-based method improves the fluorescence image quality and the accuracy of dose distribution measurements in nearly real time. This technique will also be applied to Cherenkov radiation removal or signal denoising in other fluorescence imaging modalities. This method will provide an accurate absolute dose verification tool with high spatial resolution.

Testing of an enhanced leaf model for improved dose calculation in a commercial treatment planning system.

With the ever-increasing complexity of dynamic radiotherapy treatments, dose calculation algorithms are challenged to accurately calculate the dose resulting from small, on- and off-axis multileaf collimator (MLC) aperture movements. Although the currently available Eclipse (Varian Medical Systems, Palo Alto) dose calculation algorithms still use a simplified, binary MLC model, a more advanced and detailed modeling of the MLC could be beneficial for the dose calculation precision of high-end treatments. To improve the modeling of the MLC in the dose calculation algorithms of the Eclipse treatment planning system, an enhanced MLC attenuation model was constructed through ray tracing through the actual leaf designs for the most commonly used Varian MLC types. The enhanced leaf model (ELM) thus includes the rounded leaf tip shape, the drive screw cutout, and the leaf body thickness. The purpose of this work is to test out this new model and explore possible improvements compared to the previous model. Dose calculations were performed in a research Eclipse environment equipped with the original and enhanced MLC model. Measurements were performed on TrueBeam and on Halcyon dual MLC treatment units. Dedicated static and dynamic MLC test plans were designed to challenge the dose calculation and highlight differences between both models while keeping the experimental setup simple in order to minimize measurement uncertainties. Measurements were performed with single ion chambers, 2D ion chamber arrays and film. The improved MLC model considerably improves the accuracy of the dose calculation for the test fields used in this study. For the TrueBeam MLC, improvements are most prominent for off-axis dose delivery through narrow (static or dynamic) MLC gaps. For 3mm narrow sweeping gap deliveries at 12cm off-axis, the advanced model agrees within 2% with the measurement, in contrast to the 12% deviation observed with the original MLC model. For the Halcyon MLC, improvements are especially prominent when the leaves of both MLC stacks are aligned, regardless of their position in the field. Sweeping gap measurements improve from a 7%-10% deviation with the original model to within 2% with the new model. Although test fields designed in this study emphasize the flaws in the original MLC dose calculation model, the enhanced MLC model resolves all of the observed discrepancies, showing excellent on- and off-axis agreements with all of the performed measurements.

Miniaturizing a Chip-Scale Spectrometer Using Local Strain Engineering and Total-Variation Regularized Reconstruction.

A wafer-thin chip-scale portable spectrometer suitable for wearable applications based on a reconstructive algorithm was demonstrated. A total of 16 spectral encoders that simultaneously functioned as photodetectors were monolithically integrated on a chip area of 0.16 mm2 by applying local strain engineering in compressively strained InGaN/GaN multiple quantum well heterostructures. The built-in GaN pn junction enabled a direct photocurrent measurement. A non-negative least-squares (NNLS) algorithm with total-variation regularization and a choice of a proper kernel function was shown to deliver a decent spectral reconstruction performance in the wavelength range of 400-645 nm. The accuracies of spectral peak positions and intensity ratios between peaks were found to be 0.97% and 10.4%, respectively. No external optics, such as collimation optics and apertures, were used, enabled by angle-insensitive light-harvesting structures, including an array of cone-shaped backreflectors fabricated on the underside of the sapphire substrate.

IBA myQA SRS Detector for CyberKnife Robotic Radiosurgery Quality Assurance

The IBA myQA® SRS high-resolution solid-state detector was evaluated in the context of robotic radiosurgery delivered using CyberKnife®. The performance was investigated for periodic machine delivery quality assurance (DQA) and patient-specific treatment verification. myQA® SRS is a 140 × 120 mm CMOS matrix with 400 µm resolution, allocated in a cylindrical ABS phantom topped by a hemispheric cap. Evaluations included: periodic DQA tests, angular response, dose-rate dependence and Iris variable aperture collimator field size measurements. For patient-specific QA various intracranial targets were studied (Gamma Index, 3%/1 mm agreement criteria), taking into account also the detector’s angular response. Results for periodic DQA were in accordance with the machine commissioning data. Dose-rate dependence was confirmed, and angular response tests resulted in a signal decay &gt;5% when beams were delivered outside a ±50° amplitude cone with respect to the vertical direction. Concerning patient-specific QA, &gt;50° angled beams elimination led to a Gamma Index passing rates improvement ranging between +3% and +115%. IBA myQA® SRS proved to be a suitable device for many CyberKnife® constancy DQA checks, providing high-resolution real-time results. Patient-specific Gamma tests showed high passing rates once angular dependence corrections were performed, even in high complexity treatments such as those for trigeminal neuralgia targets.

ANALISA DISTRIBUSI DOSIS PADA FANTOM HOMOGEN DAN INHOMOGEN DENGAN SIMULASI MONTE CARLO

Monte Carlo simulation with electron gamma shower (EGSnrc) code can produce 3-dimensional dose distribution data. The percent depth dose curve (PDD), dose profile, and isodose curve can be extracted through this 3-dimensional data. In this study, a photon source with an energy of 2 MeV is placed at the source to surface distance (SSD) from the phantom surface by adjusting the collimator aperture which is used to control the size of the exposure field. The SSD distance was varied at a distance of 50 cm, 70 cm, 80 cm, 90 cm, and 100 cm. The size of the exposure area is also varied by 2 × 2 cm 2 , 5 × 5 cm 2 , 7 × 7 cm 2 , and 10 × 10 cm 2 . The dose distribution analysis was carried out on homogeneous phantoms containing water and inhomogeneous phantoms containing tissue/bone/lung/bone/tissue material. The PDD curve and dose profile represent dose changes with depth and x or y direction, respectively. The PDD curve on a homogeneous phantom shows an increase in the value on the surface of the phantom to the depth with the maximum dose. This curve then decreases gradually with increasing depth. Inhomogeneous ghosts show spikes in the border region of the two media with different densities. This is due to the contribution of the backscattered electrons generated by the bone media and into the tissue media. This phenomenon is also seen in the isodose curve for inhomogeneous phantoms.