Impact of MLC properties and IMRT technique in meningioma and head-and-neck treatments

Purpose: The impact of multileaf collimator (MLC) design and IMRT technique on plan quality and delivery improvements for head-and-neck and meningioma patients is compared in a planning study. Material and methods: Ten previously treated patients (5 head-and-neck, 5 meningioma) were re-planned for step-and-shoot IMRT (ssIMRT),sliding window IMRT (dMLC) and VMAT using the MLCi2 without (-) and with (+) interdigitation and the Agility-MLC attached to an Elekta 6MV linac. This results in nine plans per patient. Consistent patient individual optimization parameters are used. Plans are generated using the research tool Hyperion V2.4 (equivalent to Elekta Monaco 3.2) with hard constraints for critical structures and objectives for target structures. For VMAT plans, the improved segment shape optimization is used. Critical structures are evaluated based on QUANTEC criteria. PTV coverage is compared by EUD, D-mean, homogeneity and conformity. Additionally, MU/plan, treatment times and number of segments are evaluated. Results: As constrained optimization is used, all plans fulfill the hard constraints. Doses to critical structures do not differ more than 1Gy between the nine generated plans for each patient. Only larynx, parotids and eyes differ up to 1.5Gy (D-mean or D-max) or 7 % (volume-constraint) due to (1) increased scatter,(2) not avoiding structures when using the full range of gantry rotation and (3) improved leaf sequencing with advanced segment shape optimization for VMAT plans. EUD, Dmean, homogeneity and conformity are improved using the Agility-MLC. However, PTV coverage is more affected by technique. MU increase with the use of dMLC and VMAT, while the MU are reduced by using the Agility-MLC. Fastest treatments are always achieved using Agility-MLC, especially in combination with VMAT. Conclusion: Fastest treatments with the best PTV coverage are found for VMAT plans with Agility-MLC, achieving the same sparing of healthy tissue compared to the other combinations of ssIMRT, dMLC and VMAT with either MLCi2(-/+) or Agility

Normal tissue complication models for clinically relevant acute esophagitis (>= grade 2) in patients treated with dose differentiated accelerated radiotherapy (DART-bid)

Background: One of the primary dose-limiting toxicities during thoracic irradiation is acute esophagitis (AE). The aim of this study is to investigate dosimetric and clinical predictors for AE grade >= 2 in patients treated with accelerated radiotherapy for locally advanced non-small cell lung cancer (NSCLC). Patients and methods: 66 NSCLC patients were included in the present analysis: 4 stage II, 44 stage IIIA and 18 stage IIIB. All patients received induction chemotherapy followed by dose differentiated accelerated radiotherapy (DART-bid). Depending on size (mean of three perpendicular diameters) tumors were binned in four dose groups: 6 cm 90 Gy. Patients were treated in 3D target splitting technique. In order to estimate the normal tissue complication probability (NTCP),two Lyman models and the cutoff-logistic regression model were fitted to the data with AE >= grade 2 as statistical endpoint. Inter-model comparison was performed with the corrected Akaike information criterion (AIC(c)),which calculates the model's quality of fit (likelihood value) in relation to its complexity (i.e. number of variables in the model) corrected by the number of patients in the dataset. Toxicity was documented prospectively according to RTOG. Results: The median follow up was 686 days (range 84-2921 days), 23/66 patients (35 %) experienced AE >= grade 2. The actuarial local control rates were 72.6 % and 59.4 % at 2 and 3 years, regional control was 91 % at both time points. The Lyman-MED model (D50 = 32.8 Gy, m = 0.48) and the cutoff dose model (D-c = 38 Gy) provide the most efficient fit to the current dataset. On multivariate analysis V38 (volume of the esophagus that receives 38 Gy or above, 95 %-CI 28.2-57.3) was the most significant predictor of AE >= grade 2 (HR = 1.05, CI 1.01-1.09, p = 0.007). Conclusion: Following high-dose accelerated radiotherapy the rate of AE >= grade 2 is slightly lower than reported for concomitant radio-chemotherapy with the additional benefit of markedly increased loco-regional tumor control. In the current patient cohort the most significant predictor of AE was found to be V38. A second clinically useful parameter in treatment planning may be MED (mean esophageal dose)

Impact of MLC properties and IMRT technique in meningioma and head-and-neck treatments

Purpose: The impact of multileaf collimator (MLC) design and IMRT technique on plan quality and delivery improvements for head-and-neck and meningioma patients is compared in a planning study. Material and methods: Ten previously treated patients (5 head-and-neck, 5 meningioma) were re-planned for step-and-shoot IMRT (ssIMRT),sliding window IMRT (dMLC) and VMAT using the MLCi2 without (-) and with (+) interdigitation and the Agility-MLC attached to an Elekta 6MV linac. This results in nine plans per patient. Consistent patient individual optimization parameters are used. Plans are generated using the research tool Hyperion V2.4 (equivalent to Elekta Monaco 3.2) with hard constraints for critical structures and objectives for target structures. For VMAT plans, the improved segment shape optimization is used. Critical structures are evaluated based on QUANTEC criteria. PTV coverage is compared by EUD, D-mean, homogeneity and conformity. Additionally, MU/plan, treatment times and number of segments are evaluated. Results: As constrained optimization is used, all plans fulfill the hard constraints. Doses to critical structures do not differ more than 1Gy between the nine generated plans for each patient. Only larynx, parotids and eyes differ up to 1.5Gy (D-mean or D-max) or 7 % (volume-constraint) due to (1) increased scatter,(2) not avoiding structures when using the full range of gantry rotation and (3) improved leaf sequencing with advanced segment shape optimization for VMAT plans. EUD, Dmean, homogeneity and conformity are improved using the Agility-MLC. However, PTV coverage is more affected by technique. MU increase with the use of dMLC and VMAT, while the MU are reduced by using the Agility-MLC. Fastest treatments are always achieved using Agility-MLC, especially in combination with VMAT. Conclusion: Fastest treatments with the best PTV coverage are found for VMAT plans with Agility-MLC, achieving the same sparing of healthy tissue compared to the other combinations of ssIMRT, dMLC and VMAT with either MLCi2(-/+) or Agility