Higher Pass Rates Research Articles

P14.16.A IS A LINAC WITH A 5MM MLC WIDTH REALLY A BARRIER TO IMPLEMENTING A HIGH-QUALITY COMPLEX SRS SERVICE?

Abstract BACKGROUND Stereotactic Radiosurgery (SRS) for patients with intracranial disease is increasing, especially for smaller and more numerous metastases. In England, Varian HyperArc using a Truebeam linac is nationally commissioned via benchmarking. HyperArc contains SRS-specific optimisation and non-coplanar VMAT delivery and is an attractive option due to its cost effectiveness compared with competing specialised platforms such as Elekta GammaKnife and Accuray CyberKnife. Depsite these benefits, the treatment of small targets or those with highly complex shapes is dominated by specialised platforms with a largely stated reason being perceived concern over delivered dosimetric certainty. This work assesses achievable dosimetric accuracy for complex SRS using Varian HyperArc suing a standard 120-leaf 5mm width MLC. MATERIAL AND METHODS Four patients with small and/or complex PTVs previously treated with CyberKnife at our institution were identified:26 metastases 24Gy/1f (PTV min. volume 0.01cc);5 metastases 24 Gy/1f (PTV min. volume 0.11cc);Pituitary adenoma 25Gy/1f (PTV width min. 5 mm near optics);Acoustic neuroma 21 Gy/3f (PTV width min. 3 mm near cochlea). Patients were re-planned with HyperArc using 4 arcs at 6FFF, emulating the prescription dose spillage (PDS) & modified gradient index (mGI) achieved in the CyberKnife plans. Plans were produced in Eclipse v17.1, calculated using the AAA algorithm (v 17.1.0.1) on a 1mm calculation grid. The plan was then transferred to a CT scan of an in-house water equivalent phantom containing radiochromic EBT3 film in clinically meaningful coronal and sagittal dose planes and re-calculated. All plans were delivered under image guidance and the 2D film dosimetry was compared with the calculated dose from Eclipse using a global 5%/1mm (TH 20%) gamma test using well-established absolute dose film methodology in Sun Nuclear SNC Patient (v 8.2). RESULTS In all cases, HyperArc had very similar plan quality to CyberKnife, with maximum dose gradients between 20-23% of prescription dose per mm beyond the PTV (up to 5.8Gy/mm). Up to 1mm geometric offset was permitted to allow for imaging localization & film registration uncertainty in the analysis. Mean gamma pass rates were 93.3% pre-alignment and 98.5% post-alignment. CONCLUSION The very high gamma pass rates achieved in this novel work illustrate excellent delivered dose accuracy for high-quality SRS plans. The use of a radiochromic film dosimetry allows for the demonstration of such accuracy using a standard Truebeam linac without the use of a high-definition MLC even for the smallest and most complex SRS targets. This work enables us to re-think previously held beliefs around perceived dosimetric limitations of multi-arc VMAT with a 5 mm MLC width for the delivery of high-quality SRS. Removing this barrier could start to bridge the existing gap in worldwide SRS service provision for patients.

Machine learning automated treatment planning for online magnetic resonance guided adaptive radiotherapy of prostate cancer

Background and purposeNo best practices currently exist for achieving high quality radiation therapy (RT) treatment plan adaptation during magnetic resonance (MR) guided RT of prostate cancer. This study validates the use of machine learning (ML) automated RT treatment plan adaptation and benchmarks it against current clinical RT plan adaptation methods. Materials and methodsWe trained an atlas-based ML automated treatment planning model using reference MR RT treatment plans (42.7 Gy in 7 fractions) from 46 patients with prostate cancer previously treated at our institution. For a held-out test set of 38 patients, retrospectively generated ML RT plans were compared to clinical human-generated adaptive RT plans for all 266 fractions. Differences in dose-volume metrics and clinical objective pass rates were evaluated using Wilcoxon tests (p < 0.05) and Exact McNemar tests (p < 0.05), respectively. ResultsCompared to clinical RT plans, ML RT plans significantly increased sparing and objective pass rates of the rectum, bladder, and left femur. The mean ± standard deviation of rectum D20 and D50 in ML RT plans were 2.5 ± 2.2 Gy and 1.6 ± 1.3 Gy lower than clinical RT plans, respectively, with 14 % higher pass rates; bladder D40 was 4.6 ± 2.9 Gy lower with a 20 % higher pass rate; and the left femur D5 was 0.8 ± 1.8 Gy lower with a 7 % higher pass rate. ConclusionsML automated RT treatment plan adaptation increases robustness to interfractional anatomical changes compared to current clinical adaptive RT practices by increasing compliance to treatment objectives.

Association of internship with performance on American Board of Physical Medicine and Rehabilitation certification examinations.

Physical Medicine and Rehabilitation (PM&R) residents must complete twelve months of fundamental skills training prior to beginning PM&R residency. The objective of this study is to determine if characteristics of the first post-graduate year (PGY-1) impact performance on American Board of PM&R (ABPMR) initial certification examinations. A retrospective review was conducted on a deidentified ABPMR database of physicians who completed PM&R residency and took the Part I Examination between 2008 and 2022. Physicians who completed categorical residency programs in PM&R had higher pass rates on Part I than physicians who completed advanced programs. Physicians who completed a categorical program had higher scaled scores on the Part II Examination than physicians who completed either a transitional or non-transitional advanced program but pass rates did not differ. Completing less than 3 months of training in internal medicine prior to starting PM&R was associated with lower Part I and Part II Examination scaled scores than completing 3 or more months. Physicians who completed six or more months of internal medicine had higher Part I and Part II Examination pass rates and scaled scores than physicians who completed six or more months in surgery.

Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast. Still, it lacks electron density information, while cone beam CT (CBCT) lacks direct electron density calibration and is mainly used for patient positioning.Adopting MRI-only or CBCT-based adaptive radiotherapy eliminates the need for CT planning but presents challenges. Synthetic CT (sCT) generation techniques aim to address these challenges by using image synthesis to bridge the gap between MRI, CBCT, and CT. The SynthRAD2023 challenge was organized to compare synthetic CT generation methods using multi-center ground truth data from 1080 patients, divided into two tasks: (1) MRI-to-CT and (2) CBCT-to-CT. The evaluation included image similarity and dose-based metrics from proton and photon plans.The challenge attracted significant participation, with 617 registrations and 22/17 valid submissions for tasks 1/2. Top-performing teams achieved high structural similarity indices (≥0.87/0.90) and gamma pass rates for photon (≥98.1%/99.0%) and proton (≥97.3%/97.0%) plans. However, no significant correlation was found between image similarity metrics and dose accuracy, emphasizing the need for dose evaluation when assessing the clinical applicability of sCT.SynthRAD2023 facilitated the investigation and benchmarking of sCT generation techniques, providing insights for developing MRI-only and CBCT-based adaptive radiotherapy. It showcased the growing capacity of deep learning to produce high-quality sCT, reducing reliance on conventional CT for treatment planning.

Factors Associated With Economics Course Performance at a Large Associate Degree-Granting Institution

Economics courses are often offered at community colleges and other institutions that primarily confer associate degrees. Despite this, little research has been conducted on performance in economics courses focusing on students attending these institutions. I use multinomial logistic models to determine which factors are related to performance in both introductory macroeconomics and introductory microeconomics at a large institution that primarily confers associate degrees and finds several factors associated with performance in these courses. Among the findings are that citizenship status, foreign-born status, and gender are associated with academic performance in economics courses as noncitizens, foreign-born, and male students outperform their citizen, U.S.-born, and female counterparts in certain circumstances. Additional results show that in-person classes are associated with higher pass rates and lower withdrawal rates.

Research on Bearing Surface Scratch Detection Based on Improved YOLOV5.

Bearings are crucial components of machinery and equipment, and it is essential to inspect them thoroughly to ensure a high pass rate. Currently, bearing scratch detection is primarily carried out manually, which cannot meet industrial demands. This study presents research on the detection of bearing surface scratches. An improved YOLOV5 network, named YOLOV5-CDG, is proposed for detecting bearing surface defects using scratch images as targets. The YOLOV5-CDG model is based on the YOLOV5 network model with the addition of a Coordinate Attention (CA) mechanism module, fusion of Deformable Convolutional Networks (DCNs), and a combination with the GhostNet lightweight network. To achieve bearing surface scratch detection, a machine vision-based bearing surface scratch sensor system is established, and a self-made bearing surface scratch dataset is produced as the basis. The scratch detection final Average Precision (AP) value is 97%, which is 3.4% higher than that of YOLOV5. Additionally, the model has an accuracy of 99.46% for detecting defective and qualified products. The average detection time per image is 263.4 ms on the CPU device and 12.2 ms on the GPU device, demonstrating excellent performance in terms of both speed and accuracy. Furthermore, this study analyzes and compares the detection results of various models, demonstrating that the proposed method satisfies the requirements for detecting scratches on bearing surfaces in industrial settings.

The Effect of Time Variables as Predictors of Senior Secondary School Students' Mathematical Performance Department of Mathematics Education Freetown Polytechnic

This study aimed to investigate the effect of time variables as predictors of senior secondary school students' mathematical performance in Kossoh Town, Western Rural. The time variables considered in this study included the time of day when the math test was administered, the amount of time spent studying math outside of school, and the time of year when the test was taken. A sample of 250 Senior Secondary School Students from different public schools participated in the study. They were administered a standardized math test at three different times of the day (morning, afternoon, and evening), and their scores were recorded. Additionally, the students were asked to report the amount of time they spent studying math outside of school and the time of year when they took the test. The results of the study indicated that the performance of girls in the mathematics tests varied depending on the time of the day and their age group. The highest pass rates were observed in the morning and the lowest in the evening. Additionally, older girls and boys (above 20) generally had lower pass rates compared to younger age groups. This means time variables had a significant impact on the students' mathematical performance. Furthermore Students who took the test in the morning scored higher on average compared to those who took the test in the afternoon or evening. Additionally, students who reported studying math outside of school for a longer period of time had higher scores on the test. Finally, students who took the test later in the school year scored higher compared to those who took the test earlier in the year. Overall, the findings of this study suggest that time variables play a crucial role in predicting Senior Secondary School.

Evaluation of imprecision in the different detection methods of Zn based on 5 years of data from an external quality assessment program in China

BackgroundThis study examines the imprecision of zinc (Zn) measurements across various clinical detection methods by analyzing the external quality assessment (EQA) data from 2018 to 2022. The findings of this study aim to offer recommendations for enhancing Zn measurements. MethodsParticipating laboratories were grouped into peer categories based on the detection methods. The robust mean and coefficient of variation (CV) of the samples were calculated following ISO 13528 guidelines. The evaluation criteria for optimal, desirable, and minimum allowable imprecision in Zn estimation are 2.50%, 5.05%, and 7.55%, respectively, based on biological variation. Furthermore, the study examined inter-lab CVs, inter-method bias, and the passing rate. The impact of sample concentration on CVs and the pass rate was also investigated. ResultsOver the past five years, 4283 laboratories participated in the EQA program, showing a high pass rate that improved as sample concentration increased. Differential pulse polarography (DPP) demonstrated stable and low CVs (0.61–1.86%). Although differential pulse stripping (DPS) was less stable than DPP, it still exhibited a low CV (0.71–3.10%). Graphite furnace atomic absorption spectrometry (GFAAS) and flame atomic absorption spectrometry (FAAS) performed similarly and displayed stable CVs (2.39–4.42%) within the acceptable range of desirable imprecision (5.05%). However, the CVs for ICP-MS were unacceptable in three out of the five years (5.28–6.20%). In 2022, the number of participating laboratories for DDP, DPS, GFAAS, FAAS and ICP-MS is 131, 35, 35, 820 and 72, respectively. ConclusionThis study provides reliable insights into the imprecision of Zn measurements in clinical laboratories. The findings indicate that additional efforts are required to reduce the imprecision of ICP-MS in Zn measurements.

Research on a New Flow Measurement for Intelligent Injection Tools

Intelligent separate injection technology can achieve continuous monitoring data of layered water Injection wells. So it can find out the inefficient water circulating formation timely. Then the water injection schemes can be adjusted in real-time to ensure the high water injection pass rate. It can also increase the working efficiency of the workers’ because of its automatic mode.But its prime cost is high, which limits its large-scale industrialization application in fine layered water injection wells. The key part is the intelligent water distributor in the intelligent separate injection technology. The cost of electromagnetic flow meter accounts for 38% in the intelligent water distributor. The paper intends to research on flow measurement without flow meter to reduce the high-cost. The pressure difference equation was established for flow rate and the opening ratio of the nozzle using the dimensionless analysis method. The empirical parameters of the equation were obtained through laboratory experiments. The pressure sensors are used to monitor the pressure of water injection wells while achieving the measurement of layered flow rate.The laboratory experiments results indicate that the calculated flow rate obtained by this method coincides well with the standard flow rate. The relative error is less than 12%. Then,it provides a new flow measurement method for intelligent injection tools. The most significant feature is that the flow meter is no longer mandatory for intelligent water distributors. Due to the cheaper cost that it provides a technical support for the large-scale industrialization application of intelligent separate injection technology in fine layered water injection wells.

A study on hearing screening using oto-acoustic emissions in newborns delivered by normal vaginal delivery and lower segment caesarean section

Background: Hearing is one of the most complex systems of the human body and is a skill involved in the human social evolution. It has been estimated that around 900 million people by the end of 2050, will probably suffer from hearing loss. Our study aims to find out the correlation between the mode of delivery and the effect it has on newborn hearing screening. Methods: The Prospective study on 136 Newborn babies who were delivered in JLN Hospital &amp; Research Centre, Bhilai, Chhattisgarh during October 2020 to August 2021. After obtaining detailed history all newborns underwent TEOAE screening and the data were then compared with the available literature. Results: We observed normal vaginal delivery newborns have passed the test by 97.91% and 89.58% when compared to LSCS delivered infants 97.15% and 86.36% in screening and diagnostic frequency respectively. COVID-19 infection was seen in 2.94% of pregnant mothers in the 3rd trimester. There were no babies who required BERA in our study Conclusions: Normal vaginally delivered newborns have higher pass rate in TEOAE test when compared with LSCS delivered babies. Covid-19 infection in antenatal mother can influence the outcome in 1st TEOAE tests. The pass rate in TEOAE hearing test in the screening frequency is found to be greater when compared with diagnostic frequencies. In a developing country like India, Universal hearing screening programs needs to be reached out to the most remote parts of the country, in order to identify at risk infants for hearing loss.

Magnetic resonance imaging respirators: a randomized crossover trial to assess respiratory protection, usability, and comfort.

Many available facepiece filtering respirators contain ferromagnetic components, which may cause significant problems in the magnetic resonance imaging (MRI) environment. We conducted a randomized crossover trial to assess the effectiveness, usability, and comfort of 3 types of respirators, judged to be "conditionally MRI safe" with an aluminum nosepiece (Halyard 46727 duckbill-type respirators and Care Essentials MSK-002 bifold cup-type respirators) or "MRI safe" completely metal free (Eagle AG2200 semirigid cup-type respirators). We recruited 120 participants to undergo a quantitative fit test (QNFT) on each of the 3 respirators in a randomized order. Participants then completed a usability and comfort assessment of each respirator. There were significant differences in the QNFT pass rates (51% for Halyard 46727, 73% for Care Essentials MSK-002, and 86% for Eagle AG2200, P < .001). The first-time fit test pass rate and overall fit factor were significantly higher for Eagle AG2200 compared with the other 2 respirators. Eagle AG2200 scored the lowest ratings in the ease of use and overall comfort. There were no significant differences in other modalities, including the seal rating, breathability, firmness, and overall assessment. Our study supports the utility of the Eagle AG2200 and Care Essentials MSK-002 respirators for healthcare professionals working in an MRI environment, based on their high QNFT pass rates and reasonably good overall usability and comfort scores. Eagle AG2200 is unique because of its metal-free construction. However, its comparatively lower usability and comfort ratings raise questions about practicality, which may be improved by greater user training.

The Effects of Technical Science on Learner Performance and possible Technical Vocational Career Choices

Technical vocational education and training (TVET) colleges offer technical vocational professions through a more vocational than academic curriculum. The addition of mathematics and physical science to the technical school curriculum led to a high failure rate and an increase in dropout rates because many students failed these two subjects. The department of basic education (DBE) established technical mathematics and technical science as alternatives to mathematics and physical science in these schools in an effort to address these issues. This study explored the effect of technical science on the technical high school pass rates following its implementation. Qualitative data methods was used to analyse physical science and technical content documents as well as pass rates descriptively. Findings for this study showed that technical science had less weight in the exam and less challenging content than physical science. After the advent of technical science, the pass rates for physical science rose considerably, though they were also inconsistent. Additionally, several schools stopped teaching technical science even after their students excelled in it. The study recommends that more investigation be done into the effects of technical science on learners' readiness for technical vocational careers and reasons for some schools to drop technical science. Keywords: learner performance, pass rates, physical science technical science, TVET colleges, vocational careers

Solving worded real-world problems using simultaneous equations by pre-service mathematics teachers in regional Australia: Performances and implications

&lt;abstract&gt; &lt;p&gt;Studies have shown that solving worded real-world problems is a difficult challenge for pre-service secondary mathematics teachers engaging study in most tertiary institutions. This case study reports the performances of three groups of regional pre-service mathematics teachers in their attempts to solve three different worded real-world problems through simultaneous equations in their formal assessments. These students were the first-year pre-service mathematics teachers enrolled in an undergraduate education program in a regional university in Australia. Their performances are compared by statistical analysis. The result of this study indicates that design of the word questions should consider challenging tasks appropriate for the students to achieve the pedagogical purpose in solving real-life problems that can best facilitate training the students towards becoming knowledgeable and motivated mathematics teachers for secondary schools, rather than ideologically making a levelling field with less challenging problems to achieve a high pass rate mandated by many institutions.&lt;/p&gt; &lt;/abstract&gt;

Leveraging GAN-based CBCT-to-CT translation models for enhanced image quality and accurate photon and proton dose calculation in adaptive radiotherapy

PurposeTo develop a deep learning-based network for CBCT-to-CT translation. This approach aims to enhance CBCT image quality and enable more accurate photon and proton dose calculation in adaptive radiotherapy. MethodsThe proposed network is based on a simple generative adversarial network (GAN) and task-specific loss functions. The CBCT images were input into the network for synthetic CT (sCT) generation with regularization loss in the form of gradient loss (between CBCT and sCT) and style loss (between registered planning CT and sCT) to preserve the CBCT structural information and obtain accurate HU values through CT style transfer, respectively. CBCT and planning CT images collected from 58 patients with pelvic lesions were used for training. The model performance was quantitatively and qualitatively evaluated and compared to that of three other models (Res-G, CycleGAN and CUT). Quantitative analysis was performed to assess the noise reduction and dosimetric improvement achieved by the proposed network. The performance of the model was evaluated in an additional 6 pelvic patients. ResultsThe best visual effects on the test data were achieved using our model, which showed detailed information preservation and artifact removal ability. Quantitative values of 13.02 ± 4.40 HU, 56.59 ± 20.58 HU, 37.53 ± 3.06 dB and 93.43 ± 1.23% were obtained for the MAE, RSME, PSNR and SSIM, respectively. Our sCT also showed CT-like noise levels, with a mean global noise level (GNL) of 3.31 ± 0.32 HU. The dosimetric evaluation revealed a gamma pass rate higher than 99% under all criteria for photon treatment and high pass rates of 95.77 ± 1.21% (2%/2 mm) and 98.07 ± 0.45% (3%/3 mm)) for proton treatment. ConclusionWe introduce novel task-specific loss functions into a GAN-based network for generating high-quality sCT images. The model also has an excellent ability to remove artifacts and suppress noise. Dosimetric results show the potential for integration into the clinical ART workflow.

Comparison of results and age-related changes in establishing reference intervals for CEA, AFP, CA125, and CA199 using four indirect methods

•The reference intervals calculated using RefineR, Kosmic, TMC, and non-parametric methods are similar.•TMC algorithm is more robust, demonstrates a high pass rate among the four methods and has the ability to automatically isolate outliers.•The reference intervals of CA125 and CA199 showed significant differences between age and sex.

Comparison of diffuse correlation spectroscopy analytical models for measuring cerebral blood flow in adults.

Although multilayer analytical models have been proposed to enhance brain sensitivity of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow, the traditional homogeneous model remains dominant in clinical applications. Rigorous in vivo comparison of these analytical models is lacking. We compare the performance of different analytical models to estimate a cerebral blood flow index (CBFi) with DCS in adults. Resting-state data were obtained on a cohort of 20 adult patients with subarachnoid hemorrhage. Data at 1 and 2.5cm source-detector separations were analyzed with the homogenous, two-layer, and three-layer models to estimate scalp blood flow index and CBFi. The performance of each model was quantified via fitting convergence, fit stability, brain-to-scalp flow ratio (BSR), and correlation with transcranial Doppler ultrasound (TCD) measurements of cerebral blood flow velocity in the middle cerebral artery (MCA). The homogeneous model has the highest pass rate (100%), lowest coefficient of variation (CV) at rest (median [IQR] at 1Hz of 0.18 [0.13, 0.22]), and most significant correlation with MCA blood flow velocities (, ) compared with both the two- and three-layer models. The multilayer model pass rate was significantly correlated with extracerebral layer thicknesses. Discarding datasets with non-physiological BSRs increased the correlation between DCS measured CBFi and TCD measured MCA velocities for all models. We found that the homogeneous model has the highest pass rate, lowest CV at rest, and most significant correlation with MCA blood flow velocities. Results from the multilayer models should be taken with caution because they suffer from lower pass rates and higher coefficients of variation at rest and can converge to non-physiological values for CBFi. Future work is needed to validate these models in vivo, and novel approaches are merited to improve the performance of the multimodel models.

A Descriptive Learning Analytics: An Online Learning Programmes and Load-shedding Conundrum

Electricity load-shedding in South Africa has become a new challenge for students pursuing online learning following the Covid-19 outbreak. This article thus investigated the way load-shedding affects students in pursuing the Advanced Certificate in Teaching (ACT) programmes. Pre-Covid-19 and during load-shedding data between 2018 and 2022 was gathered and analysed using a descriptive learning analytics tool. The research took place at a South African university where the researcher is currently employed. Learning analytics data has been available for years, but it is now being effectively harnessed to improve learning and teaching through relatively recent developments in learning analytics tools. However, the load-shedding conundrum works against this objective of harnessing learning and teaching. Research has also shown that in the least developed countries, effective e-learning practices face significant barriers, primarily stemming from insufficient infrastructure, economic challenges, low levels of computer literacy, and the added challenge of power outages. Using a constructivist paradigm, the study employed a mixed qualitative approach, which included desktop historical data and semi-structured interviews. Three participants were purposely selected because of their role in overseeing ACT students situated in both rural and urban areas. The study revealed that numerous programmes were discontinued, enrollment declined, ACT Blended shifted to e-learning, persisting load-shedding conundrum affected e-learning, a low throughput rate, and digital illiteracy contributed to an increased rate of student dropouts. This research recommends that universities should embrace the evolution of e-learning through the digitalisation of learning processes to enhance efficiency. Keywords: Load-shedding, E-learning, Learning Analytics Tools, Declined Enrolment, Low Throughput Rate vs High Distinction Module Pass Rate

Need-Based Game Design: Developing a CT Game Based on Educational Needs

According to reports and previous research, present and future society show a high need for citizens with technical skills, such as computer programming. The need for technical competent citizens can however be challenging for higher education institutions to accommodate due to low numbers of students in higher education computer science. But also due to the high drop-out rates and low pass rates in introductory programming courses. With that said, it is important to both recruit new students to computer science and to support those who already study the subject, to meet the demands of the present and the future. An approach that has shown great promise in motivating students while still keeping focus on the learning aspects in education, is game-based learning (GBL). To facilitate support in higher education computer science, more specifically courses in fundamental programming, this study had the aim of identifying important design concepts in the development of a need-based educational game on computational thinking (CT). Skills related to programming have commonly been organized as part of the CT concept. To identify the educational needs, e-mail interviews were conducted with teachers that teach higher education courses on computer programming in Swedish universities. Based in an on-going design science project to create a learning game on computational thinking for higher education, the study discusses and compare the identified needs with design theories, such as affordances, emotional design, and sustainable design. The conclusion is a conceptual design of the educational game with a set of recommendations for a need-based game design in educational context.

Comparison of four commercial dose calculation algorithms in different evaluation tests.

Accurate and fast dose calculation is crucial in modern radiation therapy. Four dose calculation algorithms (AAA, AXB, CCC, and MC) are available in Varian Eclipse and RaySearch Laboratories RayStation Treatment Planning Systems (TPSs). This study aims to evaluate and compare dosimetric accuracy of the four dose calculation algorithms applying to homogeneous and heterogeneous media, VMAT plans (based on AAPM TG-119 test cases), and the surface and buildup regions. The four algorithms are assessed in homogeneous (IAEA-TECDOCE 1540) and heterogeneous (IAEA-TECDOC 1583) media. Dosimetric evaluation accuracy for VMAT plans is then analyzed, along with the evaluation of the accuracy of algorithms applying to the surface and buildup regions. Tests conducted in homogeneous media revealed that all algorithms exhibit dose deviations within 5% for various conditions, with pass rates exceeding 95% based on recommended tolerances. Additionally, the tests conducted in heterogeneous media demonstrate high pass rates for all algorithms, with a 100% pass rate observed for 6 MV and mostly 100% pass rate for 15 MV, except for CCC, which achieves a pass rate of 94%. The results of gamma index pass rate (GIPR) for dose calculation algorithms in IMRT fields show that GIPR (3% /3 mm) for all four algorithms in all evaluated tests based on TG119, are greater than 97%. The results of the algorithm testing for the accuracy of superficial dose reveal variations in dose differences, ranging from -11.9% to 7.03% for 15 MV and -9.5% to 3.3% for 6 MV, respectively. It is noteworthy that the AXB and MC algorithms demonstrate relatively lower discrepancies compared to the other algorithms. This study shows that generally, two dose calculation algorithms (AXB and MC) that calculate dose in medium have better accuracy than other two dose calculation algorithms (CCC and AAA) that calculate dose to water.

Using a chat-based informed consent tool in large-scale genomic research.

We implemented a chatbot consent tool to shift the time burden from study staff in support of a national genomics research study. We created an Institutional Review Board-approved script for automated chat-based consent. We compared data from prospective participants who used the tool or had traditional consent conversations with study staff. Chat-based consent, completed on a user's schedule, was shorter than the traditional conversation. This did not lead to a significant change in affirmative consents. Within affirmative consents and declines, more prospective participants completed the chat-based process. A quiz to assess chat-based consent user understanding had a high pass rate with no reported negative experiences. Our report shows that a structured script can convey important information while realizing the benefits of automation and burden shifting. Analysis suggests that it may be advantageous to use chatbots to scale this rate-limiting step in large research projects.