ArticleJournal of applied clinical medical physics2020
Patient-specific quality assurance using machine log files analysis for stereotactic body radiation therapy (SBRT).
Article in Journal of applied clinical medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Implementing log file-based patient-specific QA for VMAT plans: A comparative study of MobiusFX and measurement-based approaches.Journal of applied clinical medical physics · 2026Article
- Comparison of log file-based and measurement-based QA for detecting MLC positional errors and evaluating dosimetric impacts of MLC defects.Journal of applied clinical medical physics · 2025Article
- A pathway away from measurement-based patient-specific QA: A review of contemporary quality assurance for external-beam radiotherapy sub-systems.Journal of applied clinical medical physics · 2025Review
- Reporting Clinical Results of EPID-Based Patient-Specific Quality Assurance for Brain Stereotactic Radiosurgery/Radiation Therapy: Demonstrating the Feasibility of Same-Day Stereotactic Radiosurgery via HyperArc Delivery.Advances in radiation oncology · 2025Article
- Development of a log file analysis tool for proton patient QA, system performance tracking, and delivered dose reconstruction.Journal of applied clinical medical physics · 2023Article
- Deep Hybrid Learning Prediction of Patient-Specific Quality Assurance in Radiotherapy: Implementation in Clinical Routine.Diagnostics (Basel, Switzerland) · 2023Article
- A hybrid method to improve efficiency of patient specific SRS and SBRT QA using 3D secondary dose verification.Journal of applied clinical medical physics · 2023Article
- Insensitivity of machine log files to MLC leaf backlash and effect of MLC backlash on clinical dynamic MLC motion: An experimental investigation.Journal of applied clinical medical physics · 2022Article
- Comparison of dosimetric effects of MLC positional errors on VMAT and IMRT plans for SBRT radiotherapy in non-small cell lung cancer.PloS one · 2022Article
- An investigation of using log-file analysis for automated patient-specific quality assurance in MRgRT.Journal of applied clinical medical physics · 2021Article
- Sensitivity of Three Patient-Specific Quality Assurance Systems to MLC Aperture Errors With Volumetric Modulated Arc Therapy.Technology in cancer research & treatmentArticle
- Radiation Oncology Ransomware Attack Response Risk Analysis Using Failure Modes and Effects Analysis.Practical radiation oncologyArticle
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An in-house trajectory log analysis program (LOGQA) was developed to evaluate the delivery accuracy of volumetric-modulated arc therapy (VMAT) for stereotactic body radiation therapy (SBRT). Methods have been established in LOGQA to provide analysis on dose indices, gantry angles, and multi-leaf collimator (MLC) positions. Between March 2019 and May 2020, 120 VMAT SBRT plans of various treatment sites using flattening filter-free (FFF) mode were evaluated using both LOGQA and phantom measurements. Gantry angles, dose indices, and MLC positions were extracted from log and compared with each plan. Integrated transient fluence map (ITFM) was reconstructed from log to examine the deviation of delivered fluence against the planned one. Average correlation coefficient of dose index versus gantry angle and ITFM for all patients were 1.0000, indicating that the delivered beam parameters were in good agreement with planned values. Maximum deviation of gantry angles and monitor units (MU) of all patients were less than 0.2 degree and 0.03 % respectively. Regarding MLC positions, maximum and root-mean-square (RMS) deviations from planned values were less than 0.6 mm and 0.3 mm respectively, indicating that MLC positions during delivery followed planned values in precise manner. Results of LOGQA were consistent with measurement, where all gamma-index passing rates were larger than 95 %, with 2 %/2 mm criteria. Three types of intentional errors were introduced to patient plan for software validation. LOGQA was found to recognize the introduced errors of MLC positions, gantry angles, and dose indices with magnitudes of 1 mm, 1 degree, and 5 %, respectively, which were masked in phantom measurement. LOGQA was demonstrated to have the potential to reduce or even replace patient-specific QA measurements for SBRT plan delivery provided that the frequency and amount of measurement-based machine-specific QA can be increased to ensure the log files record real values of machine parameters.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.