Determining the optimal dosimetric leaf gap setting for rounded leaf‐end multileaf collimator systems by simple test fields

Purpose Treatment planning system (TPS) dose calculation is sensitive to multileaf collimator (MLC) modeling, especially when treating with intensity‐modulated radiation therapy (IMRT) or VMAT. This study investigates the dosimetric impact of the MLC leaf‐tip model in a commercial TPS (RayStation v.6.1). The detectability of modeling errors was assessed through both measurements with an anthropomorphic head‐and‐neck phantom and patient‐specific IMRT QA using a 3D diode array. Methods and Materials An Agility MLC (Elekta Inc.) was commissioned in RayStation. Nine IMRT and VMAT plans were optimized to treat the head‐and‐neck phantom from the Imaging and Radiation Oncology Core Houston branch (IROC‐H). Dose distributions for each plan were re‐calculated on 27 beam models, varying leaf‐tip width (2.0, 4.5, and 6.5 mm) and leaf‐tip offset (−2.0 to +2.0 mm) values. Doses were compared to phantom TLD measurements. Patient‐specific IMRT QA was performed, and receiver‐operating characteristic (ROC) analysis was performed to determine the detectability of modeling errors. Results Dose calculations were very sensitive to leaf‐tip offset values. Offsets of ±1.0 mm resulted in dose differences up to 10% and 15% in the PTV and spinal cord TLDs respectively. Offsets of ±2.0 mm caused dose deviations up to 50% in the spinal cord TLD. Patient‐specific IMRT QA could not reliably detect these deviations, with an ROC area under the curve (AUC) value of 0.537 for a ±1.0 mm change in leaf‐tip offset, corresponding to >7% dose deviation. Leaf‐tip width had a modest dosimetric impact with <2% and 5.6% differences in the PTV and spinal cord TLDs respectively. Conclusions Small changes in the MLC leaf‐tip offset in this TPS model can cause large changes in the calculated dose for IMRT and VMAT plans that are difficult to identify through either dose curves or standard patient‐specific IMRT QA. These results may, in part, explain the reported high failure rate of IROC‐H phantom tests.

Section: Discussionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of the MLC leaf‐tip model in a commercial TPS: Dose calculation limitations and IROC‐H phantom failures

Koger

Price

Wang

et al. 2020

“…These test fields were: (a) the asynchronous sweeping gap (aSG) for sliding window beams and (b) the asynchronous oscillating sweeping gap (aOSG) for VMAT arcs. The detailed characteristics of these test fields are given in Hernandez et al and similar tests have also been proposed by other investigators . For each beam of aSG and aOSG tests, a tongue‐and‐groove index (TGi) was defined as the quotient of the distance between adjacent leaf ends “ s ” and the MLC gap size (meanGap) used: TGi = s /meanGap.…”

Section: Methodsmentioning

confidence: 99%

On the need for tuning the dosimetric leaf gap for stereotactic treatment plans in the Eclipse treatment planning system

Vieillevigne

Khamphan

Saez

et al. 2019

The dosimetric leaf gap (DLG) and tongue‐and‐groove (T&G) effects are critical aspects in the modeling of multileaf collimators (MLC) in the treatment planning system (TPS). In this study, we investigated the dosimetric impact of limitations associated with the T&G modeling in stereotactic plans and its relationship with the need for tuning the DLG in the Eclipse TPS. Measurements were carried out using Varian TrueBeam STx systems from two different institutions. Test fields presenting MLC patterns with several MLC gap sizes (meanGap) and different amounts of T&G effect (TGi) were first evaluated. Secondly, dynamic conformal arc (DCA) and volumetric modulated arc therapy (VMAT) deliveries of stereotactic cases were analyzed in terms of meanGap and TGi. Two DLG values were used in the TPS: the measured DLG (DLGmeas) and an optimal DLG (DLGopt). Measured and calculated doses were compared according to dose differences and gamma passing rates (GPR) with strict local gamma criteria of 2%/2 mm. The discrepancies were analyzed for DLGmeas and DLGopt, and their relationships with both TGi and meanGap were investigated. DCA arcs involved significantly lower TGi and larger meanGap than VMAT arcs (P < 0.0001). By using DLGmeas in the TPS, the dose discrepancies increased as TGi increased and meanGap decreased for both test fields and clinical plans. Dose discrepancies dramatically increased with the ratio TGi/meanGap. Adjusting the DLG value was then required to achieve acceptable calculations and configuring the TPS with DLGopt led to an excellent agreement with median GPRs (2%/2 mm) > 99% for both institutions. We also showed that DLGopt could be obtained from the results of the test fields. We demonstrated that the need for tuning the DLG is due to the limitations of the T&G modeling in the Eclipse TPS. A set of sweeping gap tests modified to incorporate T&G effects can be used to determine the optimal DLG value.

“…Nevertheless, TPS still uses the MLC leaves with flat ends to simplify the dose calculations and compensates the rounded leaf transmission by shifting the leaf positions . This shifting distance is called as a dosimetric leaf gap (DLG) and many trials have endeavored to find the optimal DLG, with the goal of minimizing uncertainty in the typical patient plan . However, variations in leaf end shape cause the dosimetric effect to vary due to the irregular shape and size of the resulting fields; therefore, each dosimetric effect should be verified individually .…”

Section: Introductionmentioning

confidence: 99%

Development of a Geant4‐based independent patient dose validation system with an elaborate multileaf collimator simulation model

Choi

Park

Shin

et al. 2019

Despite the improvements in the dose calculation models of the commercial treatment planning systems (TPS), their ability to accurately predict patient dose is still limited. One of the limitations is caused by the simplified model of the multileaf collimator (MLC). The aim of this study was to develop a Monte Carlo (MC) method‐based independent patient dose validation system with an elaborate MLC model for more accurate dose evaluation. Varian Clinac 2300 IX was simulated using Geant4 toolkits, after which MC commissioning with measurements was performed to validate the simulation model. A DICOM‐RT interface was developed to obtain the beam delivery conditions including the hundreds of MLC motions. Finally, the TPS dose distributions were compared with the MC dose distributions for water phantom cases and a patient case. Our results show that the TPS overestimated the absolute abutting leakage dose in the closed MLC field, with about 20% more of the maximum dose than that of the MC calculation. For water phantom cases, the dose distributions inside the target region were almost identical with the dose difference of less than 2%, while the dose near the edge of the target shows difference about 10% between Geant4 and TPS due to geometrical differences in MLC model. For the patient analysis, the Geant4 and TPS doses of all organs were matched well within 1.4% of the prescribed dose. However, for organs located in areas with high ratio of leaf pairs with distances less than 10 mm leaf pair (LP (<10mm)), the maximum dose of TPS was overestimated by about 3% of the prescribed dose. These dose comparison results demonstrate that our system for calculating the patient dose is quite accurate. Furthermore, if the MLC sequences in treatment plan have a large ratio of LP (short), more than 3% dose difference in normal tissue could be seen.