Plan Evaluation Metrics Research Articles

MO‐EE‐A1‐06: Performance of MPC‐Based Adaptive Radiotherapy Optimization

Purpose: An adaptive re‐planning framework was used to account for tissue deformation during RT treatment courses. The framework is based on a multivariate control concept called model predictive control (MPC). A variety of control rules and optimization schemes were investigated using a prioritization‐based optimization method. Performance of the MPC control was evaluated with conventional evaluation metrics such as DVH, coverage, and homogeneity as well as model‐based plan evaluation metrics. Method and Materials: The Head/Neck IMRT treatment process was simulated using mid‐course CT scans, tracking treatment doses to tissues at the voxel level. Off‐line adaptation was performed with the changing patient model, updating the state of the process along with the dose‐to‐date information. Constrained optimizations were performed for re‐planning as well as for pre‐treatment planning. Multivariate control schemes including maximum constraint violation were utilized for re‐planning. Results: With the adaptation of the treatment plan to the patient‐specific anatomical changes, the predicted outputs could be efficiently controlled improving the robustness to those changes. Although the results show that the general trend in the predicted outputs follow the tissue volume changes, the clinical decision to re‐plan should be made by assessing the total predicted treatment output expectations. For cases investigated, a limited number (3∼4) of re‐plans were sufficient to control high priority outputs while the use of a tighter tolerance increased the number of re‐plans. Re‐plans were triggered mostly by the target coverage criteria. The studied course simulations indicate that significant changes are shown early in treatment. Therefore, frequent updates of the patient models may be necessary and critical to plan adaptation. Conclusion: The proposed multivariate control framework provided an intuitive method of articulating clinicians' decisions and priorities for re‐planning. In addition, the use of prioritization in re‐optimization may allow more efficient re‐planning which requires fewer planning resources.Supported in part by CA‐P01‐CA59827

How extensive of a 4D dataset is needed to estimate cumulative dose distribution plan evaluation metrics in conformal lung therapy?a)

The purpose of this study was to investigate the number of intermediate states required to adequately approximate the clinically relevant cumulative dose to deforming/moving thoracic anatomy in four-dimensional (4D) conformal radiotherapy that uses 6 MV photons to target tumors. Four patients were involved in this study. For the first three patients, computed tomography images acquired at exhale and inhale were available; they were registered using B-spline deformation model and the computed transformation was further used to simulate intermediate states between exhale and inhale. For the fourth patient, 4D-acquired, phase-sorted datasets were available and each dataset was registered with the exhale dataset. The exhale-inhale transformation was also used to simulate intermediate states in order to compare the cumulative doses computed using the actual and the simulated datasets. Doses to each state were calculated using the Dose Planning Method (DPM) Monte Carlo code and dose was accumulated for scoring on the exhale anatomy via the transformation matrices for each state and time weighting factors. Cumulative doses were estimated using increasing numbers of intermediate states and compared to simpler scenarios such as a "2-state" model which used only the exhale and inhale datasets or the dose received during the average phase of the breathing cycle. Dose distributions for each modeled state as well as the cumulative doses were assessed using dose volume histograms and several treatment evaluation metrics such as mean lung dose, normal tissue complication probability, and generalized uniform dose. Although significant "point dose" differences can exist between each breathing state, the differences decrease when cumulative doses are considered, and can become less significant yet in terms of evaluation metrics depending upon the clinical end point. This study suggests that for certain "clinical" end points of importance for lung cancer, satisfactory predictions of accumulated total dose to be received by the distorting anatomy can be achieved by calculating the dose to but a few (or even simply the average) phases of the breathing cycle.

Is uniform target dose possible in IMRT plans in the head and neck?

Purpose : Various published reports involving intensity-modulated radiotherapy (IMRT) plans developed using automated optimization (inverse planning) have demonstrated highly conformal plans. These reported conformal IMRT plans involve significant target dose inhomogeneity, including both overdosage and underdosage within the target volume. In this study, we demonstrate the development of optimized beamlet IMRT plans that satisfy rigorous dose homogeneity requirements for all target volumes (e.g., ±5%), while also sparing the parotids and other normal structures. Methods and Materials : The treatment plans of 15 patients with oropharyngeal cancer who were previously treated with forward-planned multisegmental IMRT were planned again using an automated optimization system developed in-house. The optimization system allows for variable sized beamlets computed using a three-dimensional convolution/superposition dose calculation and flexible cost functions derived from combinations of clinically relevant factors (costlets) that can include dose, dose-volume, and biologic model-based costlets. The current study compared optimized IMRT plans designed to treat the various planning target volumes to doses of 66, 60, and 54 Gy with varying target dose homogeneity while using a flexible optimization cost function to minimize the dose to the parotids, spinal cord, oral cavity, brainstem, submandibular nodes, and other structures. Results : In all cases, target dose uniformity was achieved through steeply varying dose-based costs. Differences in clinical plan evaluation metrics were evaluated for individual cases (eight different target homogeneity costlets), and for the entire cohort of plans. Highly conformal plans were achieved, with significant sparing of both the contralateral and ipsilateral parotid glands. As the homogeneity of the target dose distributions was allowed to decrease, increased sparing of the parotids (and other normal tissues) may be achieved. However, it was shown that relatively few patients would benefit from the use of increased target inhomogeneity, because the range of improvement in the parotid dose is relatively limited. Hot spots in the target volumes are shown to be unnecessary and do not assist in normal tissue sparing. Conclusion : Sparing of both parotids in patients receiving bilateral neck radiation can be achieved without compromising strict target dose homogeneity criteria. The geometry of the normal tissue and target anatomy are shown to be the major factor necessary to predict the parotid sparing that will be possible for any particular case.