Quality Assurance Tool Research Articles

Software Quality Assurace

Abstract: Software Quality Assurance (SQA) plays a pivotal role in the software development lifecycle, ensuring the delivery of high-quality software products. This abstract provides a comprehensive overview of the latest advancements in Software Quality Assurance methodologies, practices, and tools. The evolving landscape of software development, characterized by agile methodologies, DevOps practices, and continuous integration, has necessitated a reevaluation and enhancement of SQA processes. The abstract begins by elucidating the fundamental principles of SQA, emphasizing its critical role in detecting and preventing defects throughout the software development process. It explores the shift-left approach, where quality assurance is integrated early in the development cycle, and the benefits of this approach in terms of cost reduction and accelerated time-tomarket. Furthermore, the abstract delves into the integration of artificial intelligence (AI) and machine learning (ML) techniques in SQA processes. The use of AI-driven testing tools for automated test case generation, anomaly detection, and predictive analysis is explored as a means to enhance the efficiency and effectiveness of quality assurance activities. The abstract also discusses the challenges and ethical considerations associated with the use of AI in SQA. Additionally, the abstract highlights the importance of comprehensive test automation strategies in modern SQA. It outlines the advantages of continuous testing, test-driven development (TDD), and behavior-driven development (BDD) methodologies in ensuring robust software quality. The abstract also addresses the challenges of maintaining test automation suites and advocates for a balanced approach that combines automated and manual testing. The abstract concludes by emphasizing the need for a holistic and adaptive SQA framework that aligns with the dynamic nature of software development. It calls for ongoing research and collaboration in the SQA domain to address emerging challenges and capitalize on new opportunities for improving software quality

Feasibility of MPC enhanced couch as SRS/SBRT Pretreatment QA

Purpose: The purpose of this study was to investigate the feasibility of using the Winston-Lutz (WL) interchangeability with a Machine Performance Check-enhanced couch for pretreatment quality assurance (QA) of stereotactic radiotherapy (SRS) and stereotactic body radiation therapy (SBRT). The study employed the MPC with an electronic portal imaging device (EPID) to carry out geometric checks and verify the radiation isocenter. The isocenter size was assessed using the MultiMet cube and the MPC-enhanced couch module for SRS/SBRT pretreatment QA. Methods: The isocenter size of the MPC-enhanced couch module was compared to the WL measurements of the MultiMet cube. Measurements were taken at various gantry, collimator, and couch angles over a period of one month. The data from the cube were evaluated using PIPSRO and MultiMet (MMWL), including the offset targets. Various statistical tests were performed to evaluate the agreement, normality, separability, sensitivity, and specificity between the two methods. Results: The results showed isocenter sizes of 0.273 ± 0.065 mm, 0.293 ± 0.010 mm, and 0.209 ± 0.070 mm for PIPSPRO, MPC, and MMWL, respectively. The average bias was -0.0639 ± 0.1061 mm between MMWL and PIPSPRO, -0.0837 ± 0.0688 mm between MMWL and MPC, and 0.0198 ± 0.0696 mm between MPC and PIPSPRO. A Shapiro-Wilk test revealed no significant departure from normality for all tests and showed satisfactory discrimination through the area under the curve (AUC). A paired t-test analysis revealed a statistically significant difference between the mean isocenter size of the MPC and WL (MMPWL: t = 5.654, df = 29, p < 0.001; PIPSPRO: t = -1.483, DF = 29, p = 0.1488), and there was no significant difference within the WL test (t = 3.008, DF = 29, p = 0.0054). Conclusion: Despite the statistical test results, there was agreement between the MPC and WL radiation isocenter size that was within the requirement of the AAPM TG 142 tolerance (±1.0 mm). The MPC proved to be accurate, reproducible, and consistent throughout the measurements, making it an appropriate and effective pretreatment QA tool for SRS/SBRT.

Feasibility of Monte Carlo dropout-based uncertainty maps to evaluate deep learning-based synthetic CTs for adaptive proton therapy.

Deep learning has shown promising results to generate MRI-based synthetic CTs and to enable accurate proton dose calculations on MRIs. For clinical implementation of synthetic CTs, quality assurance tools that verify their quality and reliability are required but still lacking. This study aims to evaluate the predictive value of uncertainty maps generated with Monte Carlo dropout (MCD) for verifying proton dose calculations on deep-learning-based synthetic CTs (sCTs) derived from MRIs in online adaptive proton therapy. Two deep-learning models (DCNN and cycleGAN) were trained for CT image synthesis using 101 paired CT-MR images. sCT images were generated using MCD for each model by performing 10 inferences with activated dropout layers. The final sCT was obtained by averaging the inferred sCTs, while the uncertainty map was obtained from the HU variance corresponding to each voxel of 10 sCTs. The resulting uncertainty maps were compared to the observed HU-, range-, WET-, and dose-error maps between the sCT and planning CT. For range and WET errors, the generated uncertainty maps were projected along the 90-degree angle. To evaluate the dose distribution, a mask based on the 5%-isodose curve was applied to only include voxels along the beam paths. Pearson's correlation coefficients were calculated to determine the correlation between the uncertainty maps and HUs, range, WET, and dose errors. To evaluate the dosimetric accuracy of synthetic CTs, clinical proton treatment plans were recalculated and compared to the pCTs RESULTS: Evaluation of the correlation showed an average of r = 0.92 ± 0.03 and r = 0.92 ± 0.03 for errors between uncertainty-HU, r = 0.66 ± 0.09 and r = 0.62 ± 0.06 between uncertainty-range, r = 0.64 ± 0.06 and r = 0.58 ± 0.07 between uncertainty-WET, and r = 0.65 ± 0.09 and r = 0.67 ± 0.07 between uncertainty and dose difference for DCNN and cycleGAN model, respectively. Dosimetric comparison for target volumes showed an average 3%/3mm gamma pass rate of 99.76 ± 0.43 (DCNN) and 99.10 ± 1.27 (cycleGAN). The observed correlations between uncertainty maps and the various metrics (HU, range, WET, and dose errors) demonstrated the potential of MCD-based uncertainty maps as a reliable QA tool to evaluate the accuracy of deep learning-based sCTs.

A75Strengthening simulation quality assurance through the ‘Sim QA bundle’

The All Wales Simulation-Based Education and Training Strategy 2022 – 2027 specifies as one of its aims to promote quality assured simulation-based education and training across healthcare in Wales underpinned by standards and evaluated to ensure best practice in safe learning environments [1]. The Simulation Team at Health Education and Improvement Wales (HEIW) has been working closely with the simulation community in Wales to identify their needs through iterative consultation during meetings, focussed discussions and webinars. In 2021 stakeholders agreed that HEIW would promote the application of the Association for Simulated Practice in Healthcare (ASPiH) standards [2] and professional regulatory and statutory body standards relevant to SBET. Since then, a number of quality assurance tools as well as faculty development opportunities have been developed in order to embed these standards into simulation faculty development programmes and cascade their routine inclusion into everyday SBET practice. Quality assurance (QA) resources developed by the Simulation Team at HEIW between August 2021 and February 2023 were packaged as the ‘Sim QA Bundle’ ( HEIW Simulation Quality Assurance Bundle The ‘Sim QA Bundle’ consists of four components: Faculty development and continuous professional development (CPD): available resources include free access to the Essential Faculty Development Course, regular webinars, workshops and conferences. Content development: guidance provided includes a standardized scenario scripting template, with links to relevant literature. Content delivery: a standardized approach to debriefing has been developed which is supported by education opportunities and cognitive aids. Evaluation tools: generic evaluation forms have been designed to assess the learners’ experience, faculty perspectives and adherence to standards. The Simulation Quality Assurance Bundle provides a wide range of resources available to simulation practitioners in order to promote and support the delivery of high-quality simulation-based education and training across the healthcare workforce in Wales. Authors confirm that all relevant ethical standards for research conduct and dissemination have been met. The submitting author confirms that relevant ethical approval was granted, if applicable.

Development, comparative structural analysis, and first in vivo evaluation of acellular implanted highly compacted fibrin tubes for arterial bypass grafting

The generation of small-caliber vascular grafts remains a significant challenge within the field of tissue engineering. In pursuit of this objective, fibrin has emerged as a promising scaffold material. However, its lack of biomechanical strength has limited its utility in the construction of tissue engineered vascular grafts. We have previously reported about the implementation of centrifugal casting molding to generate compacted fibrin tubes with a highly increased biomechanical strength. In this study, we conducted a structural analysis of compacted fibrin tubes using the open-source software Fiji/BoneJ. The primary aim was to validate the hypothesis that the compaction of fibrin leads to a more complex structure characterized by increased crosslinking of fibrin fibers. Structural analysis revealed a strong correlation between fibrin's structure and its biomechanical strength. Moreover, we enhanced fibrin compaction in a subsequent dehydration process, leading to a significant increase of biomechanical strength. Thus, the presented method in combination with an adequate imaging, e.g., micro-CT, has substantial potential as a powerful tool for quality assurance in the development of fibrin-based vascular grafts. To validate this concept, acellular highly compacted fibrin tubes were implanted as substitutes of a segment of the carotid artery in a sheep model (n = 4). After 6 months explanted segments exhibited distinct remodeling, transitioning into newly formed arteries.

Artificial Intelligence-Driven Single-Shot PET Image Artifact Detection and Disentanglement: Toward Routine Clinical Image Quality Assurance.

Medical imaging artifacts compromise image quality and quantitative analysis and might confound interpretation and misguide clinical decision-making. The present work envisions and demonstrates a new paradigm PET image Quality Assurance NETwork (PET-QA-NET) in which various image artifacts are detected and disentangled from images without prior knowledge of a standard of reference or ground truth for routine PET image quality assurance. The network was trained and evaluated using training/validation/testing data sets consisting of 669/100/100 artifact-free oncological 18 F-FDG PET/CT images and subsequently fine-tuned and evaluated on 384 (20% for fine-tuning) scans from 8 different PET centers. The developed DL model was quantitatively assessed using various image quality metrics calculated for 22 volumes of interest defined on each scan. In addition, 200 additional 18 F-FDG PET/CT scans (this time with artifacts), generated using both CT-based attenuation and scatter correction (routine PET) and PET-QA-NET, were blindly evaluated by 2 nuclear medicine physicians for the presence of artifacts, diagnostic confidence, image quality, and the number of lesions detected in different body regions. Across the volumes of interest of 100 patients, SUV MAE values of 0.13 ± 0.04, 0.24 ± 0.1, and 0.21 ± 0.06 were reached for SUV mean , SUV max , and SUV peak , respectively (no statistically significant difference). Qualitative assessment showed a general trend of improved image quality and diagnostic confidence and reduced image artifacts for PET-QA-NET compared with routine CT-based attenuation and scatter correction. We developed a highly effective and reliable quality assurance tool that can be embedded routinely to detect and correct for 18 F-FDG PET image artifacts in clinical setting with notably improved PET image quality and quantitative capabilities.

Is it still necessary to perform measured based pre-treatment patient-specific QA for SRS HyperArc treatments?

The Mobius3D system was validated as a modern secondary check dosimetry system. In particular, our objective has been to assess the suitability of the M3D as pre-treatment patient-specific Quality Assurance (QA) tool for Stereotactic Radiosurgery (SRS) HyperArc (HA) treatments. We aimed to determine whether Mobius3D could safely replace the measurements-based patient-specific QA for this type of treatment. 30 SRS HA treatment plans for brain were selected. The dose distributions, calculated by Mobius and our routinely used algorithm (AcurosXB v.15.6), were compared using gamma analysis index and DVH parameters based on the patient's CT dataset. All 30 plans were then delivered across the ionization chamber in a homogeneous phantom and the measured dose was compared with both M3D and TPS calculated one. The plans were delivered and verified in terms of PSQA using the electronic portal imaging device (EPID) with Portal Dosimetry (PD) and myQA SRS (IBA Dosimetry) detector. Plans that achieved a global gamma passing rate (GPR) ≥ 97% based on 2%/2mm criteria, with both Mobius3D and the conventional methods were evaluated acceptable. Finally, we assessed the capability of the M3D system to detect errors related to the position of the Multi-Leaf Collimator (MLC) in comparison to the analyzed measurement-based systems. No relevant differences were observed in the comparison between the dose calculated on the CT-dataset by M3D and the TPS. Observed discrepancies are imputable to different used algorithms, but no discrepancies related to goodness of plans have been found. Average differences between calculated (M3D and TPS) vs measured dose with ionization chamber were 2.5% (from 0.41% to 3.2%) and 1.81% (from 0.66% to 2.65%), for M3D and TPS, respectively. All plans passed with a gamma passing rate>97% using conventional PSQA methods with a gamma criterion of 2% dose difference and 2mm distance-to-agreement. The average gamma passing rate for the M3D system was determined to be 99.4% (from 97.3% to 100%). Results from this study also demonstrated Mobius has better error detectability than conventional measurement-based systems. Our study shows Mobius3D could be a suitable alternative to conventional measured based QA methods for SRS HyperArc treatments.

THE POTENTIAL OF BIOGENIC FRACTION ANALYSIS BY RADIOCARBON IN FOOD, DRUG, AND COSMETIC PRODUCTS

ABSTRACTBiobased content analysis is a well-established, analytically independent, standardized method to determine the biobased content of fuels and plastics, based on differences of the specific radiocarbon (14C) activity of fossil and recent biogenic compounds. This biogenic content analysis can be useful for the producers as a quality assurance tool, for the customers as feedback about the truly biobased products and for the control organizations as an independent analytical tool to prove the biological origin. More than 100 commercially available foods, cosmetics, and drug samples have been used for biobased carbon content analysis by accelerator mass spectrometry (AMS) 14C measurement to demonstrate the potential of this technique. Our results show that this measurement technique is a unique tool for the determination of biocontent in foodstuff and medical products. Most of the tested materials were nearly or completely biobased (≥ 98 pMC), and no completely fossil-based final product was detected. The lowest biogenic compound was measured in a vanilla aroma flavor. In 45 of the 102 samples selected a wide range (2–98%) presented fossil-based carbon content. The method can be applied for monitoring raw materials and final products for biobased content in the industry and consumer protection as well.

Pilot scale validation campaign of gel dosimetry for pre-treatment quality assurance in stereotactic radiotherapy

PurposeComplex stereotactic radiotherapy treatment plans require prior verification. A gel dosimetry system was developed and tested to serve as a high-resolution 3D dosimeter for Quality Assurance (QA) purposes. Materials and MethodsA modified version of a polyacrylamide polymer gel dosimeter based on chemical response inhibition was employed. Different sample geometries (cuvettes and phantoms) were manufactured for calibration and QA acquisitions. Irradiations were performed with a Varian Trilogy linac, and analyses of irradiated gel dosimeters were performed via MRI with a 1.5 T Philips Achieva at 1 mm3 or 2 mm3 isotropic spatial resolution. To assess reliability of polymer gel data, 54 stereotactic clinical treatment plans were delivered both on dosimetric gel phantoms and on the Delta4 dosimeter. Results from the two devices were evaluated through a global gamma index over a range of acceptance criteria and compared with each other. ResultsA quantitative and tunable control of dosimetric gel response sensitivity was achieved through chemical inhibition. An optimized MRI analysis protocol allowed to acquire high resolution phantom dose data in timeframes of ≈ 1 h. Conversion of gel dosimeter data into absorbed dose was achieved through internal calibration. Polymer gel dosimeters (2 mm3 resolution) and Delta4 presented an agreement within 4.8 % and 2.7 % at the 3 %/1 mm and 2 %/2 mm gamma criteria, respectively. ConclusionsGel dosimeters appear as promising tools for high resolution 3D QA. Added complexity of the gel dosimetry protocol may be justifiable in case of small target volumes and steep dose gradients.

Development of a silicone-based radio-fluorogenic dosimeter using dihydrorhodamine 6G

A silicon-based three-dimensional dosimeter can be formed in a free shape without a container and deformed because of its flexibility. Several studies have focused on enhancing its radiological characteristics and assessing its applicability as a quality assurance tool for image-guided and adaptive radiation therapy, considering motion and deformation. Here, we applied a fluorescence probe (dihydrorhodamine 6G, DHR6G) to a silicon elastomer as a new radiosensitive compound that converts nonfluorescent into fluorescent dyes using irradiation, and its fluorescence intensity increases linearly with the absorbed dose. In this study, we demonstrated a cost-effective synthesis method and optimized the composition conditions. The results showed that the DHR6G-SE prepared from 2.2 × 10−3 wt% DHR6G, 0.024 wt% pyridine, and a silicone elastomer (SE) (SILPOT TM 184, base/curing agent = 10/1) exhibited a linear increase in fluorescence with radiation exposure within a dose range of 0–8 Gy and a highly stable sensitivity for as long as 64 h. To demonstrate its container-less characteristics, the possibility of dosimetry for low-energy X-rays using DHR6G-SE was investigated.

Can Advanced Radiotherapy Clinical Trials be Conducted in Resources Limited Countries?

The Lancet Oncology Commission on Cancer in Sub-Saharan Africa (SSA) highlighted the region's increasing cancer incidence and mortality, and recommended a series of actions to address this growing crisis. One such approach recommended by the Commission to increase access to curative treatment is the use of hypofractionated radiotherapy (HFRT). Here we highlight the barriers and facilitators to launching HFRT in SSA, as identified through the HypoAfrica clinical trial. HypoAfrica is a longitudinal multi-center clinical trial that was launched in late 2021 at three centers in Nigeria, Tanzania, and South Africa. The goal of HypoAfrica was to assess the feasibility of implementing HFRT for localized prostate cancer in SSA. To date, 155 of 182 subjects have been enrolled in this study. During the last year, a team of radiation oncology professionals from Africa, Europe, Australia, and USA met once every Saturday and reviewed the sites' data to identify the barriers to the implementation of HFRT and find solutions to overcome these challenges. With the intent to expand HFRT trials and practice to new SSA countries and radiotherapy centers, we also conducted an online survey to elucidate the readiness of radiotherapy centers across SSA to perform HFRT. The major challenge identified by this team was securing high-quality data that will yield statistically significant results. Factors that contribute to quality data are: harmonization of machine and patient-specific quality assurance (QA) procedures across the centers, data quality harmonization, and challenges associated with machine maintenance. Immediate solutions implemented included introduction of low-cost QA tools for patient-specific QA measurements, ongoing training of the site's healthcare professionals, implementation of preventative maintenance for Linacs, and data centralization infrastructure. These actions have resulted in the production of a high-quality, standardized dataset. Planned longer-term solutions to HFRT challenges include implementation of ongoing training, telehealth for remote support and QA, and the creation of an Imaging and Radiation Oncology Core for Africa. The online survey indicated that 61% of respondents' institutions perform HFRT for palliative purposes, emphasizing the readiness of sites in SSA to utilize HFRT for curative purposes. The study serves as a useful guide for increasing access to HFRT treatment in resource-limited settings and for conducting multicenter radiotherapy clinical trials.

Standardized evaluation of hand-off documentation of ICU boarders in the emergency department.

The boarding of ICU patients in the emergency department (ED) represents a considerable risk to patient safety. This study aims to describe the generation of a rubric to ensure the fidelity of vital, written hand-off between ED teams. We performed a mixed methods design to develop a scoring rubric to evaluate written hand-off communication of medical ICU boarders between ED teams during the COVID-19 pandemic. The primary outcome was the quality of the written hand-off as agreed upon by the inter-user agreement. Our secondary outcome included variability in written quality as a function of the number of separate and distinct ED teams at the point of the transition of care. There was a moderate inter-user agreement with rubric scoring (κ=0.70 [95% confidence interval, 0.66-0.75]). The overall trend noted that several key elements, including code status, performed interventions, and contingency planning, were infrequently documented. We effectively created a quality assurance tool for ED ICU boarders that ensures relevant and vital information is relayed between ED teams. Our analysis demonstrated that all relevant information is only sometimes present in the hand-off.

Development of an Anthropomorphic Heterogeneous Female Pelvic Phantom and Its Comparison with a Homogeneous Phantom in Advance Radiation Therapy: Dosimetry Analysis.

Accurate dosimetry is crucial in radiotherapy to ensure optimal radiation dose delivery to the tumor while sparing healthy tissues. Traditional dosimetry techniques using homogeneous phantoms may not accurately represent the complex anatomical variations in cervical cancer patients, highlighting the need to compare dosimetry results obtained from different phantom models. The aim of this study is to design and evaluate an anthropomorphic heterogeneous female pelvic (AHFP) phantom for radiotherapy quality assurance in cervical cancer treatment. Thirty RapidArc plans designed for cervical cancer patients were exported to both the RW3 homogeneous phantom and the anthropomorphic heterogeneous pelvic phantom. Dose calculations were performed using the anisotropic analytic algorithm (AAA), and the plans were delivered using a linear accelerator (LA). Dose measurements were obtained using a 0.6 cc ion chamber. The percentage (%) variation between planned and measured doses was calculated and analyzed. Additionally, relative dosimetry was performed for various target locations using RapidArc and IMRT treatment techniques. The AHFP phantom demonstrated excellent agreement between measured and expected dose distributions, making it a reliable quality assurance tool in radiotherapy. The results reveal that the percentage variation between planned and measured doses for all RapidArc quality assurance (QA) plans using the AHFP phantom is 10.67% (maximum value), 2.31% (minimum value), and 6.89% (average value), with a standard deviation (SD) of 2.565 (t = 3.21604, p = 0.001063). Also, for the percentage of variation between homogeneous and AHFP phantoms, the t-value is -11.17016 and the p-value is <0.00001. The result is thus significant at p < 0.05. We can see that the outcomes differ significantly due to the influence of heterogeneous media. Also, the average gamma values in RapidArc plans are 0.29, 0.32, and 0.35 (g ≤ 1) and IMRT plans are 0.45, 0.44, and 0.42 (g ≤ 1) for targets 1, 2, and 3, respectively. The AHFP phantom results show more dose variability than homogenous phantom outcomes. Also, the AHFP phantom was found to be suitable for QA evaluation.

Evaluation of Cs-137 and natural radionuclides on different marine biota (crustacean and fishes) along Beheira governorate Coast-Egypt: RESRAD biota

Purpose This work will focused on the environmental and radio-ecological impacts occurred on an Egyptian coastal region, based on the radiochemical measurement of 238U, 137Cs, 232Th, 40K. The novelty of the study was cleared by the using of new technique showing the integration of two biological RESRAD models, lead to a probabilistic estimation of the radionuclides bioaccumulation in different consumed marine organisms and determination the probability of human cancer risk at different ages. Material and methods The 20 water samples were collected and mounted into clean containers, and their decay products, were measured in Bq.L−1, using different quality assurance tools. The study will used different statistical analysis and different RESRAD modeling codes were used in the study to predict the degree of environmental and radio-ecological impacts at the studied area, this will be helpful in order to define the impacts resulted from the transferring and accumulation of different radionuclides. Results showed that the highest human dose conversion factor values of (5, 10, 15, with adult ages) were measured in Th-232 (mrem/pCi) while the lowest ingestion conversion factors values were observed in artificial 137Cs. On the other hand the highest values of external risk factor in case of (5, 10, 15 with adult age) were observed in artificial Cs-137(mrem/pCi), while the lowest value of external risk factor with the same ages were observed in U-238. This will lead to continual monitoring of artificial Cs-137 in different marine coastal regions. The arrangement of the bioaccumulation value (BIV) in Bq.kg−1 which being calculated by using RESRAD-Biota in case of crustacean animals will be as follow: U-238 > Th-232 > Cs-137, while the arrangement of BIV in case of fish animals will be: Cs-137 > U-232 > Th-232. On the other hand the arrangement of Internal Dose Conversion factors in case of crustacean animals will be: U-238 > Th-232 > Cs-137. While the arrangement of Internal Dose Conversion factors in case of fish animals will be: Cs-137> Th-232 > U-238. Conclusion RESRAD code’s results showed that the arrangement of the bioaccumulation and Dose Conversion factors were depend on the type of marine living organism. RESRAD code also showed that there are increments of the calculated external risk factor values which resulted from the adult than all the infants (5,10 and 15 ages) ages this may be related to the continuous replacement of new human’s body cells during the growth stages. The study results showed that, environmental bioaccumulation impacts of the artificial Cs-137 were very effective in both marine living organisms and human as this will support the relation between the ingestion Cs-137 in the body(inside the soft tissues), and the probability of the human cancer risk. On the other hand, study results showed the importance of using RESRAD BIOA code for the EIA's ecological and radiological studies which should be done for any future industrial coastal .projects.

Establishment and interpretation of the gamma pass rate prediction model based on radiomics for different intensity-modulated radiotherapy techniques in the pelvis

Backgroundand objectives: Implementation of patient-specific quality assurance (PSQA) is a crucial aspect of precise radiotherapy. Various machine learning-based models have showed potential as virtual quality assurance tools, being capable of accurately predicting the dose verification results of fixed-beam intensity-modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) plans, thereby ensuring safe and efficient treatment for patients. However, there has been no research yet that simultaneously integrates different IMRT techniques to predict the gamma pass rate (GPR) and explain the model.Methods: Retrospective analysis of the 3D dosimetric verification results based on measurements with gamma pass rate criteria of 3%/2 mm and 10% dose threshold of 409 pelvic IMRT and VMAT plans was carried out. Radiomics features were extracted from the dose files, from which the XGBoost algorithm based on SHapley Additive exPlanations (SHAP) values was used to select the optimal feature subset as the input for the prediction model. The study employed four different machine learning algorithms, namely, random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), to construct predictive models. Sensitivity, specificity, F1 score, and AUC value were calculated to evaluate the classification performance of these models. The SHAP values were utilized to perform a related interpretive analysis on the best performing model.Results: The sensitivities and specificities of the RF, AdaBoost, XGBoost, and LightGBM models were 0.96, 0.82, 0.93, and 0.89, and 0.38, 0.54, 0.62, and 0.62, respectively. The F1 scores and area under the curve (AUC) values were 0.86, 0.81, 0.88, and 0.86, and 0.81, 0.77, 0.85, and 0.83, respectively. The explanation of the model output based on SHAP values can provide a reference basis for medical physicists when adjusting the plan, thereby improving the efficiency and quality of treatment plans.Conclusion: It is feasible to use a machine learning method based on radiomics to establish a gamma pass rate classification prediction model for IMRT and VMAT plans in the pelvis. The XGBoost model performs better in classification than the other three tree-based ensemble models, and global explanations and single-sample explanations of the model output through SHAP values may offer reference for medical physicists to provide high-quality plans, promoting the clinical application and implementation of GPR prediction models, and providing safe and efficient personalized QA management for patients.

Angular correction methodology and characterization of a high-resolution CMOS array for patient specific quality assurance on a robotic arm linac.

To develop an angular correction methodology and characterize a high-resolution complementary metal-oxide-semiconductor (CMOS) array for patient specific quality assurance on a robotic arm linear accelerator. Beam path files from the treatment planning software (TPS) were used to calculate the angle of radiation beam with respect to the detector plane. Beams from multiple discrete angles were delivered to the CMOS detector array and an angular dependency look up table (LUT) was created. The LUT was then used to correct for the angular dependency of the detector. An iso-centric 5mm fixed cone, non iso-centric multi-target fixed cone, 10mm Iris and a multi-leaf collimator (MLC) based collimated plan were delivered to the phantom and compared to the TPS with and without angular correction applied. Additionally, the CMOS array was compared to gafchromic film and a diode array. Large errors of up to 30% were observed for oblique angles. When angular correction was applied, the gamma passing rate increased from 99.2% to 100% (average gamma value decreased from 0.29 to 0.14) for the 5-mm iso-centric cone plan. Similarly, the passing rate increased from 84.0% to 100% for the Iris plan and from 49.98% to 98.4% for the MLC plan when angular correction was applied. For the multi-target plan, applying angular correction improved the gamma passing rate from 94% to 99.6%. The 5mm iso-centric fixed cone plan was also delivered to film, and the gamma passing rate was 91.3% when using gafchromic film as the reference dataset, whereas the diode array provided insufficient sampling for this plan. A methodology of calculating the beam angle based on the beam path files was developed and validated. The array was demonstrated to be superior to other quality assurance tools because of its sub-millimeter spatial resolution and immediate read out of the results.

A structured FMEA approach to optimizing combinations of plan-specific quality assurance techniques for IMRT and VMAT QA.

Many commercial tools are available for plan-specific quality assurance (QA) of radiotherapy plans, with their functionality assessed in isolation. However, multiple QA tools are required to review the full range of potential errors. It is important to assess their effectiveness in combination with each other to look for ways to both streamline the QA process and to make certain that errors of high impact and/or high occurrence are caught before reaching patient treatment. To develop a structured method to assess the effective risk reduction of combinations of QA methods for IMRT/VMAT treatments. First, a structured prospective risk assessment was performed to establish the major failure modes (FMs) of IMRT/VMAT QA, and assign occurrence (O), severity (S), and baseline detectability (BD) rankings to them. The baseline assumed that chart checks and linear accelerator QA was performed, but no plan-specific secondary dose calculation or measurement was done. Second, the detectability of each FM for two secondary dose calculation methods and four plan measurement methods (point-based dose calculation, Monte-Carlo-based dose calculation, 2D fluence-based measurement, 2.5D phantom-based measurement, log file analysis with dose recalculation, and log file analysis combined with MLC QA) was determined. Third, we used a minimum detectability approach in addition to each FM's occurrence and severity to determine the optimal combination of QA methods.We analyzed the cumulative risk priority number of eight combinations of QA methods. The analysis was done on (1) all FMs, (2) FMs with high severity, (3) FMs with high-risk priority numbers (RPN) of O*S*BD, and (4) on FMs with both high severity and high RPN. Our analysis resulted in 54 FMs, including commissioning, planning, data transfer, and linear accelerator failures. 1D secondary dose calculation plus measurement provided a 19%-22% risk reduction from baseline. 1D/3D secondary dose calculation plus log files created a 25%-32% reduction. 3D secondary dose calculation plus measurement resulted in a 27%-34% reduction. 3D secondary dose calculation plus log files with additional machine QA provided the greatest reduction of 31%-42%. This novel structured approach to comparing combinations of QA methods will allow us to optimize our procedures, with the goal of detecting all clinically significant FMs. Our results show that log-file QA with 3D dose recalculation and supplemental machine QA provides better risk reduction than measurement-based QA. This work builds evidence to justify reducing or eliminating measurement-based PSQA with an independent 3D dose verification, log-file measurement, and appropriate supplementation of machine QA. The process also highlights FMs that cannot be caught by pre-treatment QA, prompting us to consider future directions for on-treatment QA.

Evaluation of intraoperative neuromonitoring (IONM) data with the Mainz IONM Quality Assurance and Analysis tool

Abstract Background Intraoperative neuromonitoring is widely used in thyroid and parathyroid surgery to prevent unilateral and especially bilateral recurrent nerve paresis. Reference values for amplitude and latency for the recurrent laryngeal nerve and vagus nerve have been published. However, data quality measures that exclude errors of the underlying intraoperative neuromonitoring (IONM) data (immanent software errors, false data labelling) before statistical analysis have not yet been implemented. Methods The authors developed an easy-to-use application (the Mainz IONM Quality Assurance and Analysis tool) using the programming language R. This tool allows visualization, automated and manual correction, and statistical analysis of complete raw data sets (electromyogram signals of all stimulations) from intermittent and continuous neuromonitoring in thyroid and parathyroid surgery. The Mainz IONM Quality Assurance and Analysis tool was used to evaluate IONM data generated and exported from ‘C2’ and ‘C2 Xplore’ neuromonitoring devices (inomed Medizintechnik GmbH) after surgery. For the first time, reference values for latency and amplitude were calculated based on ‘cleaned’ IONM data. Results Intraoperative neuromonitoring data files of 1935 patients consecutively operated on from June 2014 to May 2020 were included. Of 1921 readable files, 34 were excluded for missing data labelling. Automated plausibility checks revealed: less than 3 per cent device errors for electromyogram signal detection; 1138 files (approximately 60 per cent) contained potential labelling errors or inconsistencies necessitating manual review; and 915 files (48.5 per cent) were indeed erroneous. Mean(s.d.) reference onset latencies for the left vagus nerve, right vagus nerve, recurrent laryngeal nerve, and external branch of the superior laryngeal nerve were 6.8(1.1), 4.2(0.8), 2.5(1.1), and 2.1(0.5) ms, respectively. Conclusion Due to high error frequencies, IONM data should undergo in-depth review and multi-step cleaning processes before analysis to standardize scientific reporting. Device software calculates latencies differently; therefore reference values are device-specific (latency) and/or set-up-specific (amplitude). Novel C2-specific reference values for latency and amplitude deviate considerably from published values.

Clinical target volume delineation quality assurance for MRI-guided prostate radiotherapy using deep learning with uncertainty estimation

Background and purposePrevious studies on automatic delineation quality assurance (QA) have mostly focused on CT-based planning. As MRI-guided radiotherapy is increasingly utilized in prostate cancer treatment, there is a need for more research on MRI-specific automatic QA. This work proposes a clinical target volume (CTV) delineation QA framework based on deep learning (DL) for MRI-guided prostate radiotherapy. Materials and methodsThe proposed workflow utilized a 3D dropblock ResUnet++ (DB-ResUnet++) to generate multiple segmentation predictions via Monte Carlo dropout which were used to compute an average delineation and area of uncertainty. A logistic regression (LR) classifier was employed to classify the manual delineation as pass or discrepancy based on the spatial association between the manual delineation and the network’s outputs. This approach was evaluated on a multicentre MRI-only prostate radiotherapy dataset and compared with our previously published QA framework based on AN-AG Unet. ResultsThe proposed framework achieved an area under the receiver operating curve (AUROC) of 0.92, a true positive rate (TPR) of 0.92 and a false positive rate of 0.09 with an average processing time per delineation of 1.3 min. Compared with our previous work using AN-AG Unet, this method generated fewer false positive detections at the same TPR with a much faster processing speed. ConclusionTo the best of our knowledge, this is the first study to propose an automatic delineation QA tool using DL with uncertainty estimation for MRI-guided prostate radiotherapy, which can potentially be used for reviewing prostate CTV delineation in multicentre clinical trials.

Pre-filter analysis for retrieval of microphysical particle parameters: a quality-assurance method applied to 3 backscatter (β) +2 extinction (α) optical data taken with HSRL/Raman lidar.

We analyze the solution space of 3β+2α optical data inferred from lidar measurements, i.e., backscatter coefficients at three wavelengths and extinction coefficients at two wavelengths. These optical data are governed by microphysical parameters that can be expressed in terms of particle size distribution, effective radius, and complex refractive index (CRI). In our analysis, we consider two scenarios of the solution space. First, it can be expressed in terms of monomodal particle size distributions represented either by fine modes or by coarse modes. Secondly, the particle size distributions contain a fine mode as well as a coarse mode. Consideration of both scenarios and different values of the effective radius and CRI allows us to find synthetic 3β+2α optical data and corresponding intensive parameters (IPs) such as lidar ratios, backscatter- and extinction-related Ångström exponents at the available measurement wavelengths. Based on interdependencies between synthetic IPs and various microphysical properties, the qualitative and quantitative criteria for the optical data quality-assurance tool are developed. We derive the conditions of smoothness, closeness, convergence, and stability of the solution space for the quantitative criteria to test the quality of the 3β+2α optical data. Our novel methodology, to the best of our knowledge, can be used not only for particles of spherical shape, but also for cases in which particles are irregularly shaped. Another strength of our methodology is that it also works for the case of a size-dependent and wavelength-dependent CRI. We show the potential of this methodology for a measurement case from the ORACLES campaign. Data were taken with NASA Langley's airborne HSRL-2 instrument on September 24, 2016.