Planning and delivery in HN‐IMRT has been challenging for the Elekta linac because of numerous machine limitations. Direct aperture optimization (DAO) algorithms have had success in simplifying the planning process and improving plan quality. Commercial adaptations of DAO allow for widespread use in many clinics; however clinical validation of these methods is still needed. In this work we evaluated Pinnacle3 commercial software for HN‐IMRT on the Elekta linac. The purpose was to find a set of planning parameters that are applicable to most patients and optimal in terms of plan quality, delivery efficiency, and dosimetric accuracy. Four types of plans were created for each of 12 patients: ideal fluence optimization (FO), conventional two‐step optimization (TS), segment weight optimization (SW), and direct machine parameter optimization (DMPO). Maximum number of segments (NS) and minimum segment area (MSA) were varied in DMPO. Results showed DMPO plans have the best optimization scores and dosimetric indices, and the most consistent IMRT output among patients. At larger NS (≥80), plan quality decreases with increasing MSA as expected, except for MSA<8 cm2, suggesting presence of local minima in DMPO. Segment area and MUs can vary significantly between optimization methods and parameter settings; however, the quantity ‘integral MU’ remains constant. Irradiation time is linearly proportional to total plan segments, weakly dependent on MUs and independent of MSA. Dosimetric accuracy is independent of DMPO parameters. The superior quality of DMPO makes it the choice for HN‐IMRT on Elekta linacs and its consistency allows development of ‘class solutions’. However, planners should be aware of the local minima issue when pushing parameters to the limit such as NS<80 and MSA<8 cm2. The optimal set of parameters should be chosen to balance plan quality and delivery efficiency based on a systematic evaluation of the planning technique and system constraints.PACS number: PACS: 87.55.D, 87.55.de

Dose distributions in HN‐IMRT are complex and may be sensitive to the treatment uncertainties. The goals of this study were to evaluate: 1) dose differences between plan and actual delivery and implications on margin requirement for HN‐IMRT with rigid setup errors; 2) dose distribution complexity on setup error sensitivity; and 3) agreement between average dose and cumulative dose in fractionated radiotherapy. Rigid setup errors for HN‐IMRT patients were measured using cone‐beam CT (CBCT) for 30 patients and 896 fractions. These were applied to plans for 12 HN patients who underwent simultaneous integrated boost (SIB) IMRT treatment. Dose distributions were recalculated at each fraction and summed into cumulative dose. Measured setup errors were scaled by factors of 2–4 to investigate margin adequacy. Two plans, direct machine parameter optimization (DMPO) and fluence only (FO), were available for each patient to represent plans of different complexity. Normalized dosimetric indices, conformity index (CI) and conformation number (CN) were used in the evaluation. It was found that current 5 mm margins are more than adequate to compensate for rigid setup errors, and that standard margin recipes overestimate margins for rigid setup error in SIB HN‐IMRT because of differences in acceptance criteria used in margin evaluation. The CTV‐to‐PTV margins can be effectively reduced to 1.9 mm and 1.5 mm for CTV1 and CTV2. Plans of higher complexity and sharper dose gradients are more sensitive to setup error and require larger margins. The CI and CN are not recommended for cumulative dose evaluation because of inconsistent definition of target volumes used. For fractionated radiotherapy in HN‐IMRT, the average fractional dose does not represent the true cumulative dose received by the patient through voxel‐by‐voxel summation, primarily due to the setup error characteristics, where the random component is larger than systematic and different target regions get underdosed at each fraction.PACS numbers: 87.53.Kn, 87.53.Tf.

Purpose: High dose gradients offered by IMRT increase the sensitivity of treatment to setup errors compared to conventional treatments. We evaluated the dosimetric effects of setup error on HN‐IMRT using actual patient CBCT measurements. The purposes were to evaluate the dosimetric effects of setup error and determine required planning margins. Method and Materials: The CBCT data from 30 patients and 896 treatment sessions were collected and analyzed. They were applied retrospectively to 12 HN‐IMRT patient plans to reconstruct the cumulative dose distributions received by patients. A range of setup errors was simulated by scaling up the measurement to investigate the margin adequacy. Both deliverable and ideal fluence optimization methods were evaluated to study the dependence on dose gradient. Effects on treatment dose distributions were evaluated using dosimetric indices, conformity index (CI) and conformation number (CN). Results: Current 5 mm planning margin is more than adequate to compensate for the rigid setup error existing in the clinic. To maintain the same target coverage as in original plan, a margin of 1.7 mm to CTV1 and 1.3 mm to CTV2 is necessary. The CIs were closest to 1 for deliverable plan, and greater than 1 in cumulative dose. The CNs were significantly less than 1, making it unsuitable for treatment cumulative dose evaluation. Sharper dose gradients in FO plan increases the sensitivity to setup error with greater dose delivery errors in treatments. Conclusion: The standard margin recipes significantly overestimate the required margins for rigid setup error in HN‐IMRT, probably due to different prescription requirement. However, additional margins are necessary for other uncertainties such as tumor shrinkage and non‐rigid setup error. Plans with sharper dose gradients are more sensitive to setup error and will require larger margins. The use of conformation number is not recommended to evaluate cumulative doses.

Purpose: Planning and delivery in HN‐IMRT is challenging for Elekta linacs because of numerous constraints on beam delivery systems. The purpose of this study is to find a set of planning parameters that are applicable to most patients and optimal in terms of plan quality, delivery efficiency and dosimetric accuracy. Method and Materials: Four types of plans were created for each of 12 patients: ideal fluence optimization (FO), conventional two‐step optimization (TS) consisting of FO followed by MLC conversion, segment weight optimization (SW) and direct machine parameter optimization (DMPO). Maximum number of segments (NS) and minimum segment area (MSA) were varied in DMPO. Plan quality was evaluated based on score, dose distributions and dosimetric indices. Delivery efficiency was evaluated by irradiation time, and dosimetric accuracy by Mapcheck. Results: Plan quality deviates most from ideal FO for TS, with slight improvement for SW. DMPO is the closest to FO with the least variation among patients. NS of 80–160 in DMPO yield optimal plans. At larger NS (⩾80), plan quality decreases with MSA as expected, except for MSA <8cm2, which suggests presence of local minima in the DMPO algorithm. The irradiation time is strongly dependent on the plan segments (NSactual), weakly dependent on MUs, and independent of MSA. Typical plans with 79 segments and 8cm2 MSA have ∼747 MU and take ∼ 8 minutes to deliver; this increases to ∼13 minutes for 158 segments. Dosimetric accuracy is independent of DMPO parameters. Conclusion: The superior quality of DMPO plans makes it ideal for planning HN‐IMRT on Elekta linacs and its consistency allows development of class solutions. However, the vulnerability of local minima warrants such a study to systematically evaluate the effect of parameters in new planning techniques. The optimal set of parameters should be chosen to balance plan quality and delivery efficiency.