Medical Physics Research Articles

Alpha particle detection based on low leakage and high-barrier vertical PtOx/β-Ga2O3 Schottky barrier diode

High-performance radiation detectors are essential in many sectors spanning medical diagnostics, nuclear control, and particle physics. Ultrawide bandgap semiconductor materials have become one of the most promising candidates due to their excellent performance. Here, based on β-Ga2O3, a Schottky diode-type alpha particle detector was demonstrated. In order to reduce the reverse leakage current of the large-area device, the metal-oxide electrode PtOx was introduced to form high-barrier contacts (1.83 eV) with Ga2O3. The device exhibits a low leakage current density of 63 pA/cm2 at −100 V and apparent energy spectra of 241Am generated alpha particles with an energy of 5.486 MeV at various reverse voltages from −40 to −120 V. The charge collection efficiency (CCE) and energy resolution of the device (at −120 V) are 31.7% and 15.3%, respectively. Meanwhile, the mechanism of interaction between alpha particles and β-Ga2O3 was analyzed, and a 45° oblique incidence was adopted to increase the deposited energy of alpha particles in the depletion region. Furthermore, the differences between actual CCE and theoretical CCE are investigated as guidance for further improving detector performance. This work reveals the great potential and good prospects of Ga2O3 as an economical, efficient, and radiation-resistant ionizing radiation detector.

Dosimetric evaluation of adaptive planning for five-fraction gynecologic template-based interstitial brachytherapy

Purpose: The purpose of this work was to evaluate whether inter-fraction imaging and replanning enhance treatment delivery adherence to clinical planning objectives in the context of a 5-fraction template-based interstitial brachytherapy (TISB) approach for gynecologic cancer treatment. Methods and Materials: This retrospective study analyzed nineteen patients who underwent five fractions of interstitial brachytherapy over three days using the Syed-Neblett template. A verification CT scan was acquired for applicator assessment and reviewed by a radiation oncologist and medical physicist before each fraction. Eleven patients required replanning at least once during the treatment course. Replanning on the verification CT scan consisted of generating new target and organ-at-risk contours, digitizing catheter positions, and optimizing source dwell times to meet planning objectives. Dwell times and positions from the initial treatment plan were evaluated on the new contours to assess the dose that would have been delivered without replanning (non-adapted). Significance of non-adapted versus adapted dose differences were evaluated using a two-sided Wilcoxon sum rank test. Results: The average (min, max) change in dose (Gy) between the clinically delivered plans and the non-adapted plans were HR-CTV D90%: -6.5 (-0.6, -15.1), HR-CTV D98%: -6.5 (-0.4, -12.6), Bladder D2cc: -0.5 (0.0, -2.8), Bowel D2cc: -0.8 (0.0, -3.2), Rectum D2cc: -1.1 (0.0, -11.5), Sigmoid D2cc: -1.4 (-0.1, -5.4). Dosimetric changes in HR-CTV coverage were significantly improved with replanning while organ-at-risk differences were nonsignificant (p>0.05). Fraction 3 was the most common fraction indicated for replanning. Conclusions: Replanning template-based interstitial brachytherapy can improve target coverage and adherence to planning goals.

Deciphering the Radiation Dose Summary Page in Interventional Fluoroscopy.

Fluoroscopy is an advanced medical imaging modality that utilizes x-rays to acquire real-time images throughout a medical examination. It is commonly used in various procedures such as in interventional radiology, cardiac catheterization, and gastrointestinal and genitourinary studies. While fluoroscopy is a valuable diagnostic and therapeutic tool, it exposes patients and medical staff to ionizing radiation, which carries health risks. A radiation dose summary page is a report generated by the fluoroscope that displays important information about the procedure. It provides an overview of the radiation doses administered during a fluoroscopic procedure, as well as certain technical parameters used during the irradiation events. The contents of a radiation dose summary page may vary depending on the make and model of the fluoroscope but some common elements include the cumulative reference air kerma, which serves as a surrogate of radiation dose delivered to the patient, and the dose-area product, which takes account of the x-ray beam area and is a measure of the total amount of energy imparted on the patient. Other imaging acquisition parameters may be also included in the dose summary page, including tube voltage, tube current, pulse width, pulse rate, spectral filters, primary and secondary angles, and source-to-image distance. The radiation dose summary page for fluoroscopy is a useful tool for physicians, technologists, and medical physicists, allowing them to comprehend the technical details of a fluoroscopically guided procedure. ©RSNA, 2024.

503 Implementation of the Website of Online Resources for the Learning and Development of Medical physicists (World of MP)

503 Implementation of the Website of Online Resources for the Learning and Development of Medical physicists (World of MP)

The Future Needs of External Beam Radiotherapy in Portugal Until 2040

AimsExternal beam radiotherapy (EBRT) is essential to offer an effective cancer treatment, but it needs to be accessible, well-timed, and high-quality. There is a global lack of radiotherapy infrastructure and investment that compromises the cancer outcomes. The authors aim to quantify the future needs of EBRT until 2040 to cover the future demand. Materials and methodsBased on the Global Cancer Observatory estimate for new cancer cases in Portugal for 2040 it was calculated the optimal number of EBRT courses. The OUP is the proportion of new cancer cases that should receive EBRT at least once. In line with the International Atomic Energy Agency (IAEA) DIrectory of RAdiotherapy Centres and European SocieTy for Radiotherapy and Oncology - Health Economics in Radiation Oncology guidelines, we estimated the number of EBRT machines / Megavoltage (MV) units needed. Also, the authors followed the IAEA staffing guidelines. ResultsThe calculated median increase in the optimal number of EBRT courses for the year 2040 was found to be 18% when compared to the requirements in 2020. The projected number of optimal EBRT courses for 2040 was estimated to be approximately 34.000. Consequently, a range of 18 to 30 new EBRT machines/ MV units will need to be installed to adequately address the growing demand. To meet this demand, it is anticipated that a total of 28 to 46 radiation oncologists, 22 to 36 medical physicists, and 61 to 102 radiation therapists will be required. ConclusionThe deficit of EBRT machines / MV units in Portugal will require a change in the cancer related – policies and an investment to offer full access to EBRT treatments.

Seventieth Annual Scientific Meeting of Canadian Organization of Medical Physicists, Delta Hotels, Regina, Saskatchewan, June 5–8, 2024

Seventieth Annual Scientific Meeting of Canadian Organization of Medical Physicists, Delta Hotels, Regina, Saskatchewan, June 5–8, 2024

502 All the way from the clinic to scientific publications: Hints and tips for medical physicists

502 All the way from the clinic to scientific publications: Hints and tips for medical physicists

504 The ESTRO-EFOMP core curriculum: a joint effort from European medical physics experts in Radiation oncology

504 The ESTRO-EFOMP core curriculum: a joint effort from European medical physics experts in Radiation oncology

Book review: The Physics of Radiotherapy X-rays and Electrons by Peter Metcalfe, Tomas Kron, Peter Hoban, Dean Cutajar and Nicholas Hardcastle : Medical Physics Publishing, 2023.

Book review: The Physics of Radiotherapy X-rays and Electrons by Peter Metcalfe, Tomas Kron, Peter Hoban, Dean Cutajar and Nicholas Hardcastle : Medical Physics Publishing, 2023.

505 Challenges and Opportunities in developing medical physics educational materials and promoting scholarship in Malaysia

505 Challenges and Opportunities in developing medical physics educational materials and promoting scholarship in Malaysia

Quality Assurance of Point and 2D Shear Wave Elastography through the Establishment of Baseline Data Using Phantoms.

Ultrasound elastography has been available on most modern systems; however, the implementation of quality processes tends to be ad hoc. It is essential for a medical physicist to benchmark elastography measurements on each system and track them over time, especially after major software upgrades or repairs. This study aims to establish baseline data using phantoms and monitor them for quality assurance in elastography. In this paper, we utilized two phantoms: a set of cylinders, each with a composite material with varying Young's moduli, and an anthropomorphic abdominal phantom containing a liver modeled to represent early-stage fibrosis. These phantoms were imaged using three ultrasound manufacturers' elastography functions with either point or 2D elastography. The abdominal phantom was also imaged using magnetic resonance elastography (MRE) as it is recognized as the non-invasive gold standard for staging liver fibrosis. The scaling factor was determined based on the data acquired using MR and US elastography from the same vendor. The ultrasound elastography measurements showed inconsistency between different manufacturers, but within the same manufacturer, the measurements showed high repeatability. In conclusion, we have established baseline data for quality assurance procedures and specified the criteria for the acceptable range in liver fibrosis phantoms during routine testing.

Optimization of Radiation Protection for Companions in Pediatric Chest Radiography

Aims: The objective of this study is to optimize the positioning of the companion during pediatric chest radiographic exams by analyzing the scattered radiation dose measured with an ionization chamber. Place and Duration of Study: The experimental study was conducted between February 2024 and April 2024, in the radiodiagnosis laboratory belonging to the Medical Physics and Radiology Technology courses at the Franciscan University (UFN) in the city of Santa Maria, Rio Grande do Sul. Methodology: A fixed conventional X-ray device and a phantom (simulating object) filled with 15 cm of water to represent a pediatric chest were used. The parameters of voltage (kV) and the product of current and time (mA.s) were kept constant. Measurements of the air KERMA (KAIR) were performed by positioning the dosimetric system at four points around the phantom (0º, 90º, 180º, and 270º), simulating the exposure conditions of the companion. Results: The results showed that the lowest radiation dose received by the companion at the gonadal level occurred at 90º around the table (cathode side), while the lowest dose at the lens level was at 270º (anode side). The highest dose at the gonadal level was observed at 180º, and the highest dose at the lens level was at 90º. Conclusion: It was concluded that the companion should position themselves on the anode side (270º), as the lens does not have lead protection, while protection is available for the rest of the body. This recommendation aims to optimize radiological safety for the companion.

PhoenixMR: A GPU-based MRI simulation framework with runtime-dynamic code execution.

Simulations of physical processes and behavior can provide unique insights and understanding of real-world problems. Magnetic Resonance Imaging (MRI) is an imaging technique with several components of complexity. Several of these components have been characterized and simulated in the past. However, several computational challenges prevent simulations from being simultaneously fast, flexible, and accurate. The simulation of MRI experiments is underutilized by medical physicists and researchers using currently available simulators due to reasons including speed, accuracy, and extensibility constraints. This paper introduces an innovative MRI simulation engine and framework that aims to overcome these issues making available realistic and fast MRIsimulation. Using the CUDA C/C++ programing language, an MRI simulation engine (PhoenixMR), incorporating a Turing-complete virtual machine (VM) to simulate abstract spatiotemporal complexities, was developed. This engine solves a set of time-discrete Bloch equationsusing the symmetric operator splitting technique. An extensible front-end framework package (written in Python) aids the use of PhoenixMR to simplify simulationdevelopment. The PhoenixMR library and front-end codes have been developed and tested. A set of example simulations were performed to demonstrate the ease of use and flexibility of simulation components such as geometrical setup, pulse sequence design, phantom design, and so forth. Initial validation of PhoenixMR is performed by comparing its accuracy and performance against a widely used MRI simulator using identical simulation parameters. Validation results show PhoenixMR simulations are three orders of magnitude faster. There is also strong agreement betweenmodels. A novel MRI simulation platform called PhoenixMR has been introduced. This research tool is designed to be usable by physicists and engineers interested in performing MRI simulations. Examples are shown demonstrating the accuracy, flexibility, and usability of PhoenixMR in several key areas of MRIsimulation.

Enhanced 3D dose prediction for hypofractionated SRS (gamma knife radiosurgery) in brain tumor using cascaded-deep-supervised convolutional neural network.

Gamma Knife radiosurgery (GKRS) is a well-established technique in radiation therapy (RT) for treating small-size brain tumors. It administers highly concentrated doses during each treatment fraction, with even minor dose errors posing a significant risk of causing severe damage to healthy tissues. It underscores the critical need for precise and meticulous precision in GKRS. However, the planning process for GKRS is complex and time-consuming, heavily reliant on the expertise of medical physicists. Incorporating deep learning approaches for GKRS dose prediction can reduce this dependency, improve planning efficiency and homogeneity, streamline clinical workflows, and reduce patient lagging times. Despite this, precise Gamma Knife plan dose distribution prediction using existing models remains a significant challenge. The complexity stems from the intricate nature of dose distributions, subtle contrasts in CT scans, and the interdependence of dosimetric metrics. To overcome these challenges, we have developed a "Cascaded-Deep-Supervised" Convolutional Neural Network (CDS-CNN) that employs a hybrid-weighted optimization scheme. Our innovative method incorporates multi-level deep supervision and a strategic sequential multi-network training approach. It enables the extraction of intra-slice and inter-slice features, leading to more realistic dose predictions with additional contextual information. CDS-CNN was trained and evaluated using data from 105 brain cancer patients who underwent GKRS treatment, with 85 cases used for training and 20 for testing. Quantitative assessments and statistical analyses demonstrated high consistency between the predicted dose distributions and the reference doses from the treatment planning system (TPS). The 3D overall gamma passing rates (GPRs) reached 97.15% ± 1.36% (3mm/3%, 10% threshold), surpassing the previous best performance by 2.53% using the 3D Dense U-Net model. When evaluated against more stringent criteria (2mm/3%, 10% threshold, and 1mm/3%, 10% threshold), the overall GPRs still achieved 96.53% ± 1.08% and 95.03% ± 1.18%. Furthermore, the average target coverage (TC) was 98.33% ± 1.16%, dose selectivity (DS) was 0.57 ± 0.10, gradient index (GI) was 2.69 ± 0.30, and homogeneity index (HI) was 1.79 ± 0.09. Compared to the 3D Dense U-Net, CDS-CNN predictions demonstrated a 3.5% improvement in TC, and CDS-CNN's dose prediction yielded better outcomes than the 3D Dense U-Net across all evaluation criteria. The experimental results demonstrated that the proposed CDS-CNN model outperformed other models in predicting GKRS dose distributions, with predictions closely matching the TPS doses.

Investigating the optical and magnetic properties of engineered multifunctional graphene oxide and potential application in medical physics and nonlinear optics‏

Herein, the synthesis of multifunctional engineered GOs with the structure of GO@Fe3O4-ligands-CdTe quantum dots (QDs) by an environment-friendly aqueous method was reported. l-cystein (Cys), 3-trimethoxysilyl-propanethiol (TMSP), and glutathione (GSH) were selected as ligands. The as-prepared GO@Fe3O4-ligands-CdTe QDs hybrid nanostructures were characterized by different methods. The findings indicate that the nanocomposites of GO@Fe3O4–ligands–CdTe QDs demonstrate superparamagnetic properties at room temperature. The saturation magnetization values for GO@Fe3O4, GO@Fe3O4-Cys-CdTe, GO@Fe3O4-GSH-CdTe, and GO@Fe3O4-TMSP-CdTe, are 25, 14, 16, and 2 emu g−1, respectively. These nanocomposites show stable and strong luminescence at 580-600 nm. The magnetic nanostructures also reveal the absorption wavelength at 300-490 nm. Using TMSP ligand as a bridge between QDs and magnetic GOs, the luminescence of the nanostructure has not decreased much compared to CdTe QDs. The use of Cys ligand preserves the saturation magnetism of the nanocomposite more than magnetic GO, and the dispersed nanostructure is stable in water. Furthermore, the transverse and longitudinal optical (TO and LO) phonon modes of prepared GO@Fe3O4–ligands–CdTe QDs were obtained by Kramers-Kronig (KK) relations based on fourier-transform infrared (FTIR) spectroscopy. The Z-scan results show that the type of used ligand has a great effect on the nonlinear optical (NLO) properties of the final product. The largest NLO parameters are related to GO@Fe3O4- TMSP -CdTe QDs, and the values of nonlinear absorption coefficient and nonlinear refractive index were obtained as 2.17×10−3(cm/W) and10.27×10−8(cm2/W), respectively. As a result, GO@Fe3O4–ligands–CdTe QDs nanostructures can be considered as promising multifunctional nanostructures for various biomedical applications and NLO devices.

Radiation Dose prediction for Cervical Cancer Patients Using IMRT Technique with a Machine Learning Model Based on Support Vector Regression (SVR)

Cervical cancer poses significant global health challenges, necessitating innovative treatment approaches. This study explores the integration of Support Vector Regression (SVR) in predicting radiation doses for cervical cancer radiotherapy, aiming to enhance the precision of Intensity Modulated Radiation Therapy (IMRT). We developed and validated an SVR model using datasets of 102 and 173 cervical cancer cases to predict dose distributions based on radiomic and dosiomic features. Our methodology involved pre-processing, feature extraction, data normalization, and rigorous training and testing of the model. Results indicated that larger, more diverse datasets significantly improve predictive accuracy, with the model demonstrating robust performance metrics. Notably, the study highlights the critical role of dataset size over stage uniformity in model reliability. These findings underscore the potential of machine learning in refining radiotherapy planning, reducing the workload on medical physicists, and improving patient outcomes. Future research should focus on expanding dataset sizes and enhancing model precision, particularly for challenging anatomical regions. This study paves the way for more personalized and effective radiotherapy planning, benefiting both clinicians and patients.

Prediction of Radiation Therapy Dose Distribution Using Random Forest Algorithm in Volumetric Modulated Arc Therapy Technique for Brain Cancer

Optimization of radiation dose distribution in clinical planning using a Treatment Planning System (TPS) for radiotherapy patients is crucial to achieving a balance between therapeutic effectiveness and patient safety. However, this process is time-consuming and relies heavily on the expertise of medical physicists. In this study, dose prediction using machine learning was performed on the Planning Target Volume (PTV) and Organ at Risk (OAR) for brain cancer cases using the Volumetric Modulated Arc Therapy (VMAT) planning technique. The planning DICOM data were extracted for radiomic and dosiomic values, which were then used as input and output in this study using a random forest algorithm model. Model evaluation results indicated that the random forest model's performance in predicting dose had a Mean Square Error (MSE) value of 0.018. The Homogeneity Index (HI) and Conformity Index (CI) values for the clinical data were 0.136±0.134 and 0.939±0.131 respectively, while the predicted results were 0.136±0.039 and 0.949±0.006, with p-values for PTV and OAR features > 0.05. Thus, it can be concluded that the random forest model is effective in predicting dose for PTV brain cancer and OAR and can function as a reference in the planning process.

Radioluminescence Dosimetry in Modern Radiation Therapy

Accurate and precise measurement of radiation energy delivered to and absorbed by the patient's tissue is of great importance in radiation therapy (RT) quality assurance. Radioluminescence (RL) dosimetry has shown great potential for high spatiotemporal resolution dose measurement of RT fields. Implementation of efficient RL dosimetry in RT requires multidisciplinary effort and skills in optics, medical physics, radiation physics, electronics, and imaging science. In this review, a wide overview of fundamentals and applications of RL properties of media for RT dosimetry with emphasis on their potential use for multidimensional, small‐field, and ultra‐high dose rate RT dosimetry is provided.

Examining Beam Matching in the Commissioning of a Halcyon Accelerator

This study aims to describe the steps needed to be made in developing a commissioning report of a Halcyon linear accelerator utilizing the manufacturer’s golden beam data (GBD) as a reference in making the evaluation. The platform herein has determined the performance alignment of our local machine with the GBD obtained through comprehensive analyses. This made use of the gamma index and relative dose difference. This paper details the methodologies and outcomes of comparing local measurements against GBD during commissioning. For the Halcyon linear accelerator, dosimetric data, including percentage depth doses, dose profiles, and output factors, were acquired using a three-dimensional scanning water tank and various ionization chambers. The GBD were exported from the treatment planning system and compared to the measurements. To evaluate the agreement between the GBD and measurements, gamma index and relative dose difference analyses were conducted. For field sizes greater than 4 × 4 cm2, percentage depth doses and beam profiles, the gamma indices between GBD and measurements were less than 1%/1 mm. The gamma indices were found to be slightly greater for field sizes 2 × 2 cm2 and 4 × 4 cm2, remaining within 2%/2 mm, satisfying the American Association of Physicists in Medicine Medical Physics Practice Guideline 5 for commissioning and quality assurance of mega-volt photon beams. Deviations in the output factor between the GBD and measurements were not significant, remaining within 1%. The GBD data were evaluated in the commissioning of a Halcyon linear accelerator, with analyses being made of the gamma index and relative dose difference. The gamma index analysis is shown to be an effective method for comprehensively evaluating deviations between the GBD and measurements in the beam matching process.

Balancing precision and safety: the crucial imperative of radiation dose optimization in radiology and the role of certified medical physicists in quality assessment

Balancing precision and safety: the crucial imperative of radiation dose optimization in radiology and the role of certified medical physicists in quality assessment