Model-based Quality Assurance Research Articles

Unified Dosimetry Quality Audit Index: an integrated Monte Carlo model-based quality assurance ranking for radiotherapy treatment of glioblastoma multiforme

In the present research, we have developed a Unified Dosimetry Quality Audit Index (UDQAI) decision support system supplemented with treatment planning systems for radiation oncologists. This will aid the radiotherapy treatment of Glioblastoma Multiforme and is based on the Integrated Monte Carlo Model (IMC). IMC model is a quality assurance strategy for the computation of total dose, scatter dose deposition at the GBM site and healthy tissues/layers within the brain. It is a combination of Proliferation-Hypoxia-Invasion-Necrosis-Angiogenesis-Radiotherapy-Quality Assurance model, Radiation-induced damage-Quality Assurance model, Boltzmann radiation transport, Talaraich Tournoux image coordinate system for positioning of the tumour from the CT image and GBM treatment environments/patient case reports. The IMC model was validated by recreating GBM patient treatment environments on a novel computational heterogeneous phantom, the Mathematical Anthropomorphic Brain (MAB) phantom. Dose computations accomplished through water phantom, tissue-equivalent head phantoms are neither cost effective; nor patient-specific and are non-customised and less accurate. Thirty-Eight patient-specific GBM treatment environments were recreated on the MAB phantom. MAB phantom synthesis requires mimicking real human brain tissues/layers. Open-source protein databases such as UniProt, Swiss-model and Peptide were atlas employed to compute the elemental composition of different brain layers/tissues. Brain layers and tissues were synthesised as slabs using the Constructive Solid Geometry technique within the MAB phantom on the Electron Gamma Shower radiation transport platform. Phantom slab dimensions were computed by superimposing CT scan images of the brain with GBM and associated comorbidities on Talairach-Tournoux coordinate system. Slab surfaces of the phantom were defined by constructive solid geometry approach using quadratic equations. Energy deposition inside different slabs of phantom is calculated by Analog Monte Carlo game. Computed total dose and scatter dose deposition within the tumour and normal tissues/brain layers were graded by UDQAI which ensures planned dose delivery to the tumour site for radiation-induced cancer cell death minimising healthy tissue damages. The results of the present experimentation show that the proposed framework is promising and outperforms other recent deep learning-based decision systems. Deep learning-based decision systems are a hidden process which is unaware of the physical transport process of charged particles. UDQAI classification of treatment environments predicts that 76.32% of the total environs deposited a substantial amount of dose to the GBM locus. During treatment, healthy tissues and brain layers receive a part of transported energy. This fact is reinforced by the average deviation at the GBM site −8.2% on the contrary, healthy tissues encircling GBM reported −3.909%. These encouraging results would pave the way for the development of a biomathematical tumour growth model and Monte Carlo radiation transport-linked decision assist algorithm for radiation oncologists in the near future.

Islamic Education Model-Based Quality Assurance: A Case Study in Sekolah Mutiara Bali

This study seeks to describe Islamic education learning strategies that are modern and based output. By carrying the principle out of the box, the Islamic schools Sekolah Mutiara in Bali can lift Islamic education as a role model in other schools, especially in combining general studies with religion. The significance of this study lies in the base of the quality of education (quality assurance) which drafted carefully, where the quality of the primary standard used to print generation (students). With the model of qualitative approach was descriptive documentation, then the data is taken based on observation and documentation, then after analysis of data obtained through triangulation technique several important findings. 1) Implementation of quality assurance in Islamic schools “Mutiara” School can be seen in three aspects. First, learning model. The model is applied to the school is the social internalization of Islam, where all of the subject matter infiltrated by Islamic values. Second, habituation, ie habituation speaking, how to behave and interact with others coupled with morals and character. Third, skill training, where learners are given targets following the needs of the times like making machines, robot or any other technological tool. 2) the integrated curriculum. The curriculum used is the 2013 curriculum combined with the Islamic curriculum (JSIT Indonesia). By combining both this curriculum, then the resulting output can be the generation that controls the common knowledge in all its aspects. 3) The competence of educators. By looking at the methods and curriculum that are taken, then educators must be qualified to master and understand all the sciences.

Model-based quality assurance in railway infrastructure planning

Abstract A primary motive for adopting the methodology Building Information Modeling (BIM) in planning processes is to improve planning accuracy, cost security, and in turn quality. Up to now, however, a generally applicable, standardized means of validating design quality has been lacking. To address this shortcoming, this article presents 14 quality parameters in the domains of clash detection, semantics as well as quantities and costs, that apply to the field of infrastructure planning. The sets of rules outlined in the article are adaptable and extendable in order to respond flexibly to different model structures. The investigation focuses on how important and recurring tests can be carried out automatically and how to make the results analyzable in a transparent and standardized manner. The proposed concept thoroughly extends well-known methods such as attribute testing and clash detection analysis of the 3D model. Doing so, the paper presents a set of novel methods for quality assurance, including 4D clash detection and checks for semantic-geometric coherence. The paper discusses in detail: the influence of modeling errors on clash detection, the difference of 3D and 4D clashes, formal methods for checking the correct linkage between 3D BIM and the bill of quantities, formal approaches for checking the semantic-geometric coherence of BIM objects. The quality assurance concept presented in the article concludes with a standardized evaluation for the individual quality criteria using a school grading system, traffic light, and percentage scale. Finally, the concept is applied in a comprehensive case study on a large-scale infrastructure project and the results of the formal quality assessment are presented.

Knowledge-Based Planning for Identifying High-Risk Stereotactic Ablative Radiation Therapy Treatment Plans for Lung Tumors Larger Than 5 cm

Stereotactic ablative body radiation therapy (SABR) for lung tumors ≥5cm can be associated with more toxicitythan that for smaller tumors. We investigated the relationship between dosimetry and toxicity and used a knowledge-based planning solution to retrospectively perform individualized treatment plan quality assurance (QA) with the aim of identifying where planning could have been improved. Previous retrospective analysis of 53 patients with primary or recurrent non-small cell lung cancer ≥5cm, treated with 5- or 8-fraction volumetric modulated arc therapy SABR between 2008 and 2014, showed 30% with grade ≥3 toxicity. During this period, several improvements were made to departmental planning protocols. RapidPlan was used to compare dosimetry of patients with or without grade ≥3 toxicity. A model comprising plans from patients without toxicity and compliant with the current planning protocol was used to provide QA for the plans from patients who had toxicity. Sixteen of 53 patients had grade ≥3 toxicity, including 10 with radiation pneumonitis (RP), 3 with lung hemorrhage (1 of these also had RP), and 1 with airway stenosis/atelectasis. RP was again shown to be significantly correlated with contralateral and total-lung V5 and mean lung dose. The 4 highest contralateral-lung doses belonged to patients with RP. Five of 10 clinical plans in patients with RP had a contralateral-lung mean dose up to 2.5 times higher than that of the knowledge-based plan. For 2 of 3 patients with lung hemorrhage and 1 with airway stenosis/atelectasis, the clinical plans had the highest proximal bronchial tree doses, which was also higher than in plans from the model. In 8 patients with grade ≥3 toxicity, clinical plans had dosimetry similar to that in the predictions from the model. A "no-toxicity" RapidPlan model identified the potential for dosimetric improvement in nearly 50% of historical treatment plans from patients with grade ≥3 toxicity after SABR for lung tumors ≥5cm. Model-based QA may be useful for benchmarking treatment planning protocols in routine practice and in clinical studies.

Compass model-based quality assurance for stereotactic VMAT treatment plans

PurposeTo use Compass as a model-based quality assurance (QA) tool for stereotactic body radiation therapy (SBRT) and stereotactic radiation therapy (SRT) volumetric modulated arc therapy (VMAT) treatment plans calculated with Eclipse treatment planning system (TPS). Materials and methodsTwenty clinical stereotactic VMAT SBRT and SRT treatment plans were blindly selected for evaluation. Those plans included four different treatment sites: prostate, brain, lung and body. The plans were evaluated against dose-volume histogram (DVH) parameters and 2D and 3D gamma analysis. The dose calculated with Eclipse treatment planning system (TPS) was compared to Compass calculated dose (CCD) and Compass reconstructed dose (CRD). ResultsThe maximum differences in mean dose of planning target volume (PTV) were 2.7 ± 1.0% between AAA and Acuros XB calculation algorithm TPS dose, −7.6 ± 3.5% between Eclipse TPS dose and CCD dose and −5.9 ± 3.7% between Eclipse TPS dose and CRD dose for both Eclipse calculation algorithms, respectively. 2D gamma analysis was not able to identify all the cases that 3D gamma analysis specified for further verification. ConclusionsCompass is suitable for QA of SBRT and SRT treatment plans. However, the QA process should include wide set of DVH-based dose parameters and 3D gamma analysis should be the preferred method when performing clinical patient QA. The results suggest that the Compass should not be used for smaller field sizes than 3 × 3 cm2 or the beam model should be adjusted separately for both small (FS ≤ 3 cm) and large (FS > 3 cm) field sizes.

Efficient and reliable 3D dose quality assurance for IMRT by combining independent dose calculations with measurements

Advanced radiotherapy treatments require appropriate quality assurance (QA) to verify 3D dose distributions. Moreover, increase in patient numbers demand efficient QA-methods. In this study, a time efficient method that combines model-based QA and measurement-based QA was developed; i.e., the hybrid-QA. The purpose of this study was to determine the reliability of the model-based QA and to evaluate time efficiency of the hybrid-QA method. Accuracy of the model-based QA was determined by comparison of COMPASS calculated dose with Monte Carlo calculations for heterogeneous media. In total, 330 intensity modulated radiation therapy (IMRT) treatment plans were evaluated based on the mean gamma index (GI) with criteria of 3%∕3mm and classification of PASS (GI ≤ 0.4), EVAL (0.4 < GI > 0.6), and FAIL (GI ≥ 0.6). Agreement between model-based QA and measurement-based QA was determined for 48 treatment plans, and linac stability was verified for 15 months. Finally, time efficiency improvement of the hybrid-QA was quantified for four representative treatment plans. COMPASS calculated dose was in agreement with Monte Carlo dose, with a maximum error of 3.2% in heterogeneous media with high density (2.4 g∕cm(3)). Hybrid-QA results for IMRT treatment plans showed an excellent PASS rate of 98% for all cases. Model-based QA was in agreement with measurement-based QA, as shown by a minimal difference in GI of 0.03 ± 0.08. Linac stability was high with an average GI of 0.28 ± 0.04. The hybrid-QA method resulted in a time efficiency improvement of 15 min per treatment plan QA compared to measurement-based QA. The hybrid-QA method is adequate for efficient and accurate 3D dose verification. It combines time efficiency of model-based QA with reliability of measurement-based QA and is suitable for implementation within any radiotherapy department.