Comparative analysis of SmartArc‐based dual arc volumetric‐modulated arc radiotherapy (VMAT) versus intensity‐modulated radiotherapy (IMRT) for nasopharyngeal carcinoma

The purpose of this study was to investigate the potential benefits of using triple‐arc volumetric‐intensity modulated arc radiotherapy (RapidArc (RA)) for the treatment of early‐stage nasopharyngeal carcinoma (NPC). A comprehensive evaluation was performed including plan quality, integral doses, and peripheral doses. Twenty cases of stage I or II NPC were selected for this study. Nine‐field sliding window IMRT, double‐arc, and triple‐arc RA treatment plans were compared with respect to target coverage, dose conformity, critical organ sparing, and integral doses. Measurement of peripheral doses was performed using thermoluminescent dosimeters in an anthropomorphic phantom. While similar conformity and target coverage were achieved by the three types of plans, triple‐arc RA produced better sparing of parotid glands and spinal cord than double‐arc RA or IMRT. Double‐arc RA plans produced slightly inferior parotid sparing and dose homogeneity than the other two delivery methods. The monitor units (MU) required for triple‐arc were about 50% less than those of IMRT plans, while there was no significant difference in the required MUs between triple‐arc and double‐arc RA plans. The peripheral dose in triple‐arc RA was found to be 50% less compared to IMRT near abdominal and pelvic region. Triple‐arc RA improves both the plan quality and treatment efficiency compared with IMRT for the treatment of early stage NPC. It has become the preferred choice of treatment delivery method for early stage NPC at our center.PACS numbers: 87.53.Bn, 87.55.D, 87.55.de, 87.55.dk, 87.56.ng

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A comprehensive dosimetric evaluation of using RapidArc volumetric‐modulated arc therapy for the treatment of early‐stage nasopharyngeal carcinoma

Kan

Wong²,

Leung³

et al. 2012

“…Selected radiobiological parameters for normal tissue calculations (gEUD and NTCP). Values were obtained from AAPM TG-166 report and the studies by Burman et al, (58) Stavrev et al, (59) Huang et al, (60) and Lee et al (61) Parameters a α/β (Gy) TD 50 …”

Section: Discussionmentioning

confidence: 99%

“…Selected α/β values were 3 Gy for all the cases. Values for TD 50 , γ 50 , m, and n parameters were shown in the previous report, taken from the study by Burman et al (58) Additional γ 50 parameters were taken from studies by Stavrev et al (59) (cord and mandible), Huang et al (60) (inner ear), and Lee et al (61) (parotid gland). The γ 50 parameter for the pubic bone was taken as 4, similar to the value for the femoral head.…”

Section: H Radiobiological Parametersmentioning

confidence: 99%

Assessment of radiobiological metrics applied to patient‐specific QA process of VMAT prostate treatments

Clemente-Gutiérrez

Perez-Vara

Clavo-Herranz

et al. 2016

VMAT is a powerful technique to deliver hypofractionated prostate treatments. The lack of correlations between usual 2D pretreatment QA results and the clinical impact of possible mistakes has allowed the development of 3D verification systems. Dose determination on patient anatomy has provided clinical predictive capability to patient-specific QA process. Dose-volume metrics, as evaluation criteria, should be replaced or complemented by radiobiological indices. These metrics can be incorporated into individualized QA extracting the information for response parameters (gEUD, TCP, NTCP) from DVHs. The aim of this study is to assess the role of two 3D verification systems dealing with radiobiological metrics applied to a prostate VMAT QA program. Radiobiological calculations were performed for AAPM TG-166 test cases. Maximum differences were 9.3% for gEUD, -1.3% for TCP, and 5.3% for NTCP calculations. Gamma tests and DVH-based comparisons were carried out for both systems in order to assess their performance in 3D dose determination for prostate treatments (high-, intermediate-, and low-risk, as well as prostate bed patients). Mean gamma passing rates for all structures were better than 92.0% and 99.1% for both 2%/2 mm and 3%/3 mm criteria. Maximum discrepancies were (2.4% ± 0.8%) and (6.2% ± 1.3%) for targets and normal tissues, respectively. Values for gEUD, TCP, and NTCP were extracted from TPS and compared to the results obtained with the two systems. Three models were used for TCP calculations (Poisson, sigmoidal, and Niemierko) and two models for NTCP determinations (LKB and Niemierko). The maximum mean difference for gEUD calculations was (4.7% ± 1.3%); for TCP, the maximum discrepancy was (-2.4% ± 1.1%); and NTCP comparisons led to a maximum deviation of (1.5% ± 0.5%). The potential usefulness of biological metrics in patient-specific QA has been explored. Both systems have been successfully assessed as potential tools for evaluating the clinical outcome of a radiotherapy treatment in the scope of pretreatment QA.

A method to reconstruct and apply 3D primary fluence for treatment delivery verification

Shi

Mazur

et al. 2016

MotivationIn this study, a method is reported to perform IMRT and VMAT treatment delivery verification using 3D volumetric primary beam fluences reconstructed directly from planned beam parameters and treatment delivery records. The goals of this paper are to demonstrate that 1) 3D beam fluences can be reconstructed efficiently, 2) quality assurance (QA) based on the reconstructed 3D fluences is capable of detecting additional treatment delivery errors, particularly for VMAT plans, beyond those identifiable by other existing treatment delivery verification methods, and 3) QA results based on 3D fluence calculation (3DFC) are correlated with QA results based on physical phantom measurements and radiation dose recalculations.MethodsUsing beam parameters extracted from DICOM plan files and treatment delivery log files, 3D volumetric primary fluences are reconstructed by forward‐projecting the beam apertures, defined by the MLC leaf positions and modulated by beam MU values, at all gantry angles using first‐order ray tracing. Treatment delivery verifications are performed by comparing 3D fluences reconstructed using beam parameters in delivery log files against those reconstructed from treatment plans. Passing rates are then determined using both voxel intensity differences and a 3D gamma analysis. QA sensitivity to various sources of errors is defined as the observed differences in passing rates. Correlations between passing rates obtained from QA derived from both 3D fluence calculations and physical measurements are investigated prospectively using 20 clinical treatment plans with artificially introduced machine delivery errors.ResultsStudies with artificially introduced errors show that common treatment delivery problems including gantry angle errors, MU errors, jaw position errors, collimator rotation errors, and MLC leaf position errors were detectable at less than normal machine tolerances. The reported 3DFC QA method has greater sensitivity than measurement‐based QA methods. Statistical analysis‐based Spearman's correlations shows that the 3DFC QA passing rates are significantly correlated with passing rates of physical phantom measurement‐based QA methods.ConclusionAmong measurement‐less treatment delivery verification methods, the reported 3DFC method is less demanding than those based on full dose re‐calculations, and more comprehensive than those that solely checks beam parameters in treatment log files. With QA passing rates correlating to measurement‐based passing rates, the 3DFC QA results could be useful for complementing the physical phantom measurements, or verifying treatment deliveries when physical measurements are not available. For the past 4+ years, the reported method has been implemented at authors’ institution 1) as a complementary metric to physical phantom measurements for pretreatment, patient‐specific QA of IMRT and VMAT plans, and 2) as an important part of the log file‐based automated verification of daily patient treatment deliveries. It has been demonstrated to be useful in catching both treatment plan data transfer errors and treatment delivery problems.