Purpose To determine the dosimetric effects of rotational errors on target coverage using volumetric modulated arc therapy (VMAT) for multi-target stereotactic radiosurgery (SRS). Methods and Materials This retrospective study includes 50 SRS cases, each with 2 intracranial planning target volumes (PTVs). Both PTVs were planned for simultaneous treatment to 21 Gy using a single-isocenter, non-coplanar VMAT SRS technique. Rotational errors of 0.5°, 1.0°, and 2.0° were simulated about all axes. The dose to 95% of the PTV (D95) and the volume covered by 95% of the prescribed dose (V95) were evaluated using multivariate analysis to determine how PTV coverage is related to PTV volume, PTV separation, and rotational error. Results At 0.5° rotational error, D95 values and V95 coverage rates were ≥ 95% in all cases. For rotational errors of 1.0°, 7% of targets had D95 and V95 values below 95%. Coverage worsened substantially when the rotational error increased to 2.0°: D95 and V95 values were > 95% for only 63% of the targets. Multivariate analysis showed that PTV volume and distance to isocenter were strong predictors of target coverage. Conclusions The effects of rotational errors on target coverage were studied across a broad range of SRS cases. In general, the risk of compromised coverage increases with decreasing target volume, increasing rotational error and increasing distance between targets. Multivariate regression models from this study may be used to quantify the dosimetric effects of rotational errors on target coverage given patient-specific input parameters of PTV volume and distance to isocenter.

The goal of intensity-modulated radiation therapy (IMRT) treatment plan optimization is to produce a cumulative dose distribution that satisfies both the dose prescription and the normal tissue dose constraints. The typical manual treatment planning process is iterative, time consuming, and highly dependent on the skill and experience of the planner. We have addressed this problem by developing a knowledgebased approach that utilizes a database of prior plans to leverage the planning expertise of physicians and physicists at our institution. We developed a case-similarity algorithm that uses mutual information to identify a similar matched case for a given query case, and various treatment parameters from the matched case are then adapted to derive new treatment plans that are patient specific.We used 10 randomly selected cases matched against a knowledge base of 100 cases to demonstrate that new, clinically acceptable IMRT treatment plans can be developed. This approach substantially reduced planning time by skipping all but the last few iterations of the optimization process. Additionally, we established a simple metric based on the areas under the curve (AUC) of the dose volume histogram (DVH), specifically for the planning target volume (PTV), rectum, and bladder. This plan quality metric was used to successfully rank order the plan quality of a collection of knowledgebased plans. Further, we used 100 pre-optimized plans (20 query x 5 matches) to show that the average normalized MI score can be used as a surrogate of overall plan quality.Plans of lower pre-optimized plan quality tended to improve substantially after optimization, though its final plan quality did not improve to the same level as a plan that has a higher pre-optimized plan quality to begin with. Optimization usually improved PTV coverage slightly while providing substantial dose sparing for both v bladder and rectum of 12.4% and 9.1% respectively. Lastly, we developed new treatment plans for cases selected from an outside institution matched against our sitespecific database. The knowledge-based plans are very comparable to the original manual plan, providing adequate PTV coverage as well as substantial improvement in dose sparing to the rectum and bladder.In conclusion, we found that a site-specific database of prior plans can be effectively used to design new treatment plans for our own institution as well as outside cases. Specifically, knowledge-based plans can provide clinically acceptable planning target volume coverage and clinically acceptable dose sparing to the rectum and bladder. This approach has been demonstrated to improve the efficiency of the treatment planning process, and may potentially improve the quality of patient care by enabling more consistent treatment planning across institutions.vi

Purpose: To characterize the risks of compromised coverage in single‐isocenter multiple‐lesion VMAT SRS. Methods: Fifty patients were selected retrospectively from our SRS program. Each patient had two lesions treated to ≥ 21 Gy. Single‐isocenter VMAT SRS plans were created in Eclipse. PTV volumes and distances from isocenter were recorded. PTV coverage (D95 and V95) was evaluated across rotational setup errors of 0.5, 1.0, or 2° applied to three axes. Coverage rates were analyzed versus volume, distance, and rotation. For a rotational error of 2°, lesion size and separation distance were compared across coverage rate levels using ANOVA. A multivariate logistic regression model was fit using generalized estimating equations (GEE), modeling the probability of a 95% V95/D95 rate or higher given lesion size and separation distance while accounting for intra‐patient correlation. The estimated probabilities from the GEE model were used to capture the operating conditions in a receiver operating characteristic (ROC) curve; area under the curve (AUC) was estimated. Results: Mean lesion volume and distance to isocenter are 0.96±1.25cc and 3.53±1.61cm. V95/D95 proportions above 95% range from 92‐100% when rotational errors are ≤1°. At 2.0° rotation, V95/D95 are >95% in only 62–64% of cases; V95 falls to 75% for <0.3cc lesions at 4cm yet remains >90% up to 6cm for lesions >0.9cc. V95 is <40% in an extreme case. The logistic regression analysis shows that lesion volume and distance to isocenter are independent predictors (p< 0.001) of V95/D95 rates exceeding 95%. The ROC derived from a GEE multivariate model has an AUC of 0.87. Conclusion: PTV coverage can be compromised substantially by rotational setup errors of 2°, in particular for <0.3cc lesions at distances >4cm from isocenter. Statistical analysis suggests that lesion volume and distance to isocenter could be used to select patients who are good candidates for single‐isocenter multiple‐lesion SRS.

Purpose: To create a knowledge‐based algorithm for prostate LDR brachytherapy treatment planning that standardizes plan quality using seed arrangements tailored to individual physician preferences while being fast enough for real‐time planning. Methods: A dataset of 130 prior cases was compiled for a physician with an active prostate seed implant practice. Ten cases were randomly selected to test the algorithm. Contours from the 120 library cases were registered to a common reference frame. Contour variations were characterized on a point by point basis using principle component analysis (PCA). A test case was converted to PCA vectors using the same process and then compared with each library case using a Mahalanobis distance to evaluate similarity. Rank order PCA scores were used to select the best‐matched library case. The seed arrangement was extracted from the best‐matched case and used as a starting point for planning the test case. Computational time was recorded. Any subsequent modifications were recorded that required input from a treatment planner to achieve an acceptable plan. Results: The computational time required to register contours from a test case and evaluate PCA similarity across the library was approximately 10s. Five of the ten test cases did not require any seed additions, deletions, or moves to obtain an acceptable plan. The remaining five test cases required on average 4.2 seed modifications. The time to complete manual plan modifications was less than 30s in all cases. Conclusion: A knowledge‐based treatment planning algorithm was developed for prostate LDR brachytherapy based on principle component analysis. Initial results suggest that this approach can be used to quickly create treatment plans that require few if any modifications by the treatment planner. In general, test case plans have seed arrangements which are very similar to prior cases, and thus are inherently tailored to physician preferences.

No abstract