Using overlap volume histogram and IMRT plan data to guide and automate VMAT planning: a head-and-neck case study.

PURPOSE: To investigate whether an overlap volume histogram (OVH)-driven planning application using an intensity-modulated radiation therapy (IMRT) database can guide and automate volumetric-modulated arc therapy (VMAT) planning for head-and-neck cancer. METHODS: Based on comparable head-and-neck dosimetric results between planner-generated VMAT and IMRT plans, an inhouse developed, OVH-driven automated planning application containing a database of prior clinical head-and-neck IMRT plans is built into Pinnacle(3) SmartArc for VMAT planning. Double-arc VMAT plans of four oropharynx, four nasopharynx, and four larynx patients are generated and compared with corresponding clinical IMRT plans. RESULTS: Each VMAT plan is automatically generated in two optimization rounds, while the average number of optimization rounds in generating a clinical IMRT plan is 43. In VMAT plans, statistical superiority (p < 0.01) in sparing of the cord+4 mm, brainstem, brachial plexus, larynx, and inner ear is observed with a slight degradation in low-dose-level planning target volume (PTV) coverage. On average, D(0.1 cc) to the cord+4 mm, brainstem and brachial plexus is reduced by 3.7, 4.9, and 1.6 Gy, respectively; V(50 Gy) to the larynx is reduced by 5.3%; mean dose to the inner ear is reduced by 4.4 Gy; V(95) of low-dose-level PTV coverage is reduced by 0.3% with p = 0.25. CONCLUSIONS: IMRT-data-driven VMAT planning offers a potential method for generating VMAT plans that are comparable to IMRT plans in terms of dosimetric quality.

Fully automated simultaneous integrated boosted-intensity modulated radiation therapy treatment planning is feasible for head-and-neck cancer: a prospective clinical study.

PURPOSE: To prospectively determine whether overlap volume histogram (OVH)-driven, automated simultaneous integrated boosted (SIB)-intensity-modulated radiation therapy (IMRT) treatment planning for head-and-neck cancer can be implemented in clinics. METHODS AND MATERIALS: A prospective study was designed to compare fully automated plans (APs) created by an OVH-driven, automated planning application with clinical plans (CPs) created by dosimetrists in a 3-dose-level (70 Gy, 63 Gy, and 58.1 Gy), head-and-neck SIB-IMRT planning. Because primary organ sparing (cord, brain, brainstem, mandible, and optic nerve/chiasm) always received the highest priority in clinical planning, the study aimed to show the noninferiority of APs with respect to PTV coverage and secondary organ sparing (parotid, brachial plexus, esophagus, larynx, inner ear, and oral mucosa). The sample size was determined a priori by a superiority hypothesis test that had 85% power to detect a 4% dose decrease in secondary organ sparing with a 2-sided alpha level of 0.05. A generalized estimating equation (GEE) regression model was used for statistical comparison. RESULTS: Forty consecutive patients were accrued from July to December 2010. GEE analysis indicated that in APs, overall average dose to the secondary organs was reduced by 1.16 (95% CI = 0.09-2.33) with P=.04, overall average PTV coverage was increased by 0.26% (95% CI = 0.06-0.47) with P=.02 and overall average dose to the primary organs was reduced by 1.14 Gy (95% CI = 0.45-1.8) with P=.004. A physician determined that all APs could be delivered to patients, and APs were clinically superior in 27 of 40 cases. CONCLUSIONS: The application can be implemented in clinics as a fast, reliable, and consistent way of generating plans that need only minor adjustments to meet specific clinical needs.

A method for deriving a 4D-interpolated balanced planning target for mobile tumor radiotherapy.

PURPOSE: Tumor control and normal tissue toxicity are strongly correlated to the tumor and normal tissue volumes receiving high prescribed dose levels in the course of radiotherapy. Planning target definition is, therefore, crucial to ensure favorable clinical outcomes. This is especially important for stereotactic body radiation therapy of lung cancers, characterized by high fractional doses and steep dose gradients. The shift in recent years from population-based to patient-specific treatment margins, as facilitated by the emergence of 4D medical imaging capabilities, is a major improvement. The commonly used motion-encompassing, or internal-target volume (ITV), target definition approach provides a high likelihood of coverage for the mobile tumor but inevitably exposes healthy tissue to high prescribed dose levels. The goal of this work was to generate an interpolated balanced planning target that takes into account both tumor coverage and normal tissue sparing from high prescribed dose levels, thereby improving on the ITV approach. METHODS: For each 4DCT dataset, 4D deformable image registration was used to derive two bounding targets, namely, a 4D-intersection and a 4D-composite target which minimized normal tissue exposure to high prescribed dose levels and maximized tumor coverage, respectively. Through definition of an "effective overlap volume histogram" the authors derived an "interpolated balanced planning target" intended to balance normal tissue sparing from prescribed doses with tumor coverage. To demonstrate the dosimetric efficacy of the interpolated balanced planning target, the authors performed 4D treatment planning based on deformable image registration of 4D-CT data for five previously treated lung cancer patients. Two 4D plans were generated per patient, one based on the interpolated balanced planning target and the other based on the conventional ITV target. Plans were compared for tumor coverage and the degree of normal tissue sparing resulting from the new approach was quantified. RESULTS: Analysis of the 4D dose distributions from all five patients showed that while achieving tumor coverage comparable to the ITV approach, the new planning target definition resulted in reductions of lung V(10), V(20), and V(30) of 6.3% ± 1.7%, 10.6% ± 3.9%, and 12.9% ± 5.5%, respectively, as well as reductions in mean lung dose, mean dose to the GTV-ring and mean heart dose of 8.8% ± 2.5%, 7.2% ± 2.5%, and 10.6% ± 3.6%, respectively. CONCLUSIONS: The authors have developed a simple and systematic approach to generate a 4D-interpolated balanced planning target volume that implicitly incorporates the dynamics of respiratory-organ motion without requiring 4D-dose computation or optimization. Preliminary results based on 4D-CT data of five previously treated lung patients showed that this new planning target approach may improve normal tissue sparing without sacrificing tumor coverage.

Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma.

PURPOSE: To develop a model to assess the quality of an IMRT treatment plan using data of prior patients with pancreatic adenocarcinoma. METHODS: The dose to an organ at risk (OAR) depends in large part on its orientation and distance to the planning target volume (PTV). A database of 33 previously treated patients with pancreatic cancer was queried to find patients with less favorable PTV-OAR configuration than a new case. The minimal achieved dose among the selected patients should also be achievable for the OAR of the new case. This way the achievable doses to the OARs of 25 randomly selected pancreas cancer patients were predicted. The patients were replanned to verify if the predicted dose could be achieved. The new plans were compared to their original clinical plans. RESULTS: The predicted doses were achieved within 1 and 2 Gy for more than 82% and 94% of the patients, respectively, and were a good approximation of the minimal achievable doses. The improvement after replanning was 1.4 Gy (range 0-4.6 Gy) and 1.7 Gy (range 0-6.3 Gy) for the mean dose to the liver and the kidneys, respectively, without compromising target coverage or increasing radiation dose to the bowel, cord or stomach. CONCLUSIONS: The model could accurately predict the achievable doses, leading to a considerable decrease in dose to the OARs and an increase in treatment planning efficiency.

Data-driven approach to generating achievable dose-volume histogram objectives in intensity-modulated radiotherapy planning.

PURPOSE: To propose a method of intensity-modulated radiotherapy (IMRT) planning that generates achievable dose-volume histogram (DVH) objectives using a database containing geometric and dosimetric information of previous patients. METHODS AND MATERIALS: The overlap volume histogram (OVH) is used to compare the spatial relationships between the organs at risk and targets of a new patient with those of previous patients in a database. From the OVH analysis, the DVH objectives of the new patient were generated from the database and used as the initial planning goals. In a retrospective OVH-assisted planning demonstration, 15 patients were randomly selected from a database containing clinical plans (CPs) of 91 previous head-and-neck patients treated by a three-level IMRT-simultaneous integrated boost technique. OVH-assisted plans (OPs) were planned in a leave-one-out manner by a planner who had no knowledge of CPs. Thus, DVH objectives of an OP were generated from a subdatabase containing the information of the other 90 patients. Those DVH objectives were then used as the initial planning goals in IMRT optimization. Planning efficiency was evaluated by the number of clicks of the "Start Optimization" button in the course of planning. Although the Pinnacle(3) treatment planning system allows planners to interactively adjust the DVH parameters during optimization, planners in our institution have never used this function in planning. RESULTS: The average clicks required for completing the CP and OP was 27.6 and 1.9, respectively (p <.00001); three OPs were finished within a single click. Ten more patient's cord + 4 mm reached the sparing goal D(0.1cc) <44 Gy (p <.0001), where D(0.1cc) represents the dose corresponding to 0.1 cc. For planning target volume uniformity, conformity, and other organ at risk sparing, the OPs were at least comparable with the CPs. Additionally, the averages of D(0.1cc) to the cord + 4 mm decreased by 6.9 Gy (p <.0001); averages of D(0.1cc) to the brainstem decreased by 7.7 Gy (p <.005). The averages of V(30 Gy) to the contralateral parotid decreased by 8.7% (p <.0001), where V(30 Gy) represents the percentage volume corresponding to 30 Gy. CONCLUSION: The method heralds the possibility of automated IMRT planning.

A statistical approach for achievable dose querying in IMRT planning.

The task of IMRT planning, particularly in head-and-neck cancer, is a difficult one, often requiring days of work from a trained dosimetrist. One of the main challenges is the prescription of achievable target doses that will be used to optimize a treatment plan. This work explores a data-driven approach in which effort spent on past plans is used to assist in the planning of new patients. Using a database of treated patients, we identify the features of patient geometry that are correlated with received dose and use these to prescribe target dose levels for new patients. We incorporate our approach in a quality-control system, identifying patients with organs that received a dose significantly higher than the one recommended by our method. For all these patients, we have found that a replan using our predicted dose results in noticeable sparing of the organ without compromising dose to other treatment volumes.

Patient geometry-driven information retrieval for IMRT treatment plan quality control.

PURPOSE: Intensity modulated radiation therapy (IMRT) treatment plan quality depends on the planner's level of experience and the amount of time the planner invests in developing the plan. Planners often unwittingly accept plans when further sparing of the organs at risk (OARs) is possible. The authors propose a method of IMRT treatment plan quality control that helps planners to evaluate the doses of the OARs upon completion of a new plan. METHODS: It is achieved by comparing the geometric configurations of the OARs and targets of a new patient with those of prior patients, whose plans are maintained in a database. They introduce the concept of a shape relationship descriptor and, specifically, the overlap volume histogram (OVH) to describe the spatial configuration of an OAR with respect to a target. The OVH provides a way to infer the likely DVHs of the OARs by comparing the relative spatial configurations between patients. A database of prior patients is built to serve as an external reference. At the conclusion of a new plan, planners search through the database and identify related patients by comparing the OAR-target geometric relationships of the new patient with those of prior patients. The treatment plans of these related patients are retrieved from the database and guide planners in determining whether lower doses delivered to the OARs in the new plan are feasible. RESULTS: Preliminary evaluation is promising. In this evaluation, they applied the analysis to the parotid DVHs of 32 prior head-and-neck patients, whose plans are maintained in a database. Each parotid was queried against the other 63 parotids to determine whether a lower dose was possible. The 17 parotids that promised the greatest reduction in D50 (DVH dose at 50% volume) were flagged. These 17 parotids came from 13 patients. The method also indicated that the doses of the other nine parotids of the 13 patients could not be reduced, so they were included in the replanning process as controls. Replanning with an effort to reduce D50 was conducted on these 26 parotids. After replanning, the average reductions for D50 of the 17 flagged parotids and nine unflagged parotids were 6.6 and 1.9 Gy, respectively. These results demonstrate that the quality control method has accurately identified not only the parotids that require dose reductions but also those for which dose reductions are marginal. Originally, 11 of out the 17 flagged parotids did not meet the Radiation Therapy Oncology Group sparing goal of V(30 Gy) < 50%. Replanning reduced them to three. Additionally, PTV coverage and OAR sparing of the original plans were compared to those of the replans by using pairwise Wilcoxon p test. The statistical comparisons show that replanning compromised neither PTV coverage nor OAR sparing. CONCLUSIONS: This method provides an effective quality control mechanism for evaluating the DVHs of the OARs. Adoption of such a method will advance the quality of current IMRT planning, providing better treatment plan consistency.

A shape relationship descriptor for radiation therapy planning.

In this paper we address the challenge of matching patient geometry to facilitate the design of patient treatment plans in radiotherapy. To this end we propose a novel shape descriptor, the Overlap Volume Histogram, which provides a rotation and translation invariant representation of a patient's organs at risk relative to the tumor volume. Using our descriptor, it is possible to accurately identify database patients with similar constellations of organ and tumor geometries, enabling the transfer of treatment plans between patients with similar geometries, We demonstrate the utility of our method for such tasks by outperforming state of the art shape descriptors in the retrieval of patients with similar treatment plans. We also preliminarily show its potential as a quality control tool by demonstrating how it is used to identify an organ at risk whose dose can be significantly reduced.