PURPOSE: To evaluate and develop optimum inverse treatment planning strategies for the treatment of concave targets adjacent to normal tissue structures. METHODS AND MATERIALS: Optimized dose distributions were designed using an idealized geometry consisting of a cylindrical phantom with a concave kidney-shaped target (PTV) and cylindrical normal tissues (NT) placed 5-13 mm from the target. Targets with radii of curvature from 1 to 2.75 cm were paired with normal tissues with radii between 0.5 and 2.25 cm. The target was constrained to a prescription dose of 100% and minimum and maximum doses of 95% and 105% with relative penalties of 25. Maximum dose constraint parameters for the NT varied from 10% to 70% with penalties from 10 to 1000. Plans were evaluated using the PTV uniformity index (PTV D(max)/PTV D(95)) and maximum normal tissue doses (NT D(max)/PTV D(95)). RESULTS: In nearly all situations, the achievable PTV uniformity index and the maximum NT dose exceeded the corresponding constraints. This was particularly true for small PTV-NT separations (5-8 mm) or strict NT dose constraints (10%-30%), where the achievable doses differed from the requested by 30% or more. The same constraint parameters applied to different PTV-NT separations yielded different dose distributions. For most geometries, a range of constraints could be identified that would lead to acceptable plans. The optimization results were fairly independent of beam energy and radius of curvature, but improved as the number of beams increased, particularly for small PTV-NT separations or strict dose constraints. CONCLUSION: Optimized dose distributions are strongly affected by both the constraint parameters and target-normal tissue geometry. Standard site-specific constraint templates can serve as a starting point for optimization, but the final constraints must be determined iteratively for individual patients. A strategy whereby NT constraints and penalties are modified until the highest acceptable PTV uniformity index is achieved is discussed. This strategy can be used, in simple patient geometries, to ensure the lowest possible normal tissue dose. Strategies for setting the optimum dose constraints and penalties may vary for different optimization algorithms and objective functions. Increasing the number of beams can significantly improve normal tissue dose and target uniformity in situations where the PTV-NT separation is small or the normal tissue dose limits are severe. Setting unrealistically severe constraints in such situations often results in dose distributions that are inferior to plans achieved with more lenient constraints.
PURPOSE: To evaluate and develop optimum inverse treatment planning strategies for the treatment of concave targets adjacent to normal tissue structures. METHODS AND MATERIALS: Optimized dose distributions were designed using an idealized geometry consisting of a cylindrical phantom with a concave kidney-shaped target (PTV) and cylindrical normal tissues (NT) placed 5-13 mm from the target. Targets with radii of curvature from 1 to 2.75 cm were paired with normal tissues with radii between 0.5 and 2.25 cm. The target was constrained to a prescription dose of 100% and minimum and maximum doses of 95% and 105% with relative penalties of 25. Maximum dose constraint parameters for the NT varied from 10% to 70% with penalties from 10 to 1000. Plans were evaluated using the PTV uniformity index (PTV D(max)/PTV D(95)) and maximum normal tissue doses (NT D(max)/PTV D(95)). RESULTS: In nearly all situations, the achievable PTV uniformity index and the maximum NT dose exceeded the corresponding constraints. This was particularly true for small PTV-NT separations (5-8 mm) or strict NT dose constraints (10%-30%), where the achievable doses differed from the requested by 30% or more. The same constraint parameters applied to different PTV-NT separations yielded different dose distributions. For most geometries, a range of constraints could be identified that would lead to acceptable plans. The optimization results were fairly independent of beam energy and radius of curvature, but improved as the number of beams increased, particularly for small PTV-NT separations or strict dose constraints. CONCLUSION: Optimized dose distributions are strongly affected by both the constraint parameters and target-normal tissue geometry. Standard site-specific constraint templates can serve as a starting point for optimization, but the final constraints must be determined iteratively for individual patients. A strategy whereby NT constraints and penalties are modified until the highest acceptable PTV uniformity index is achieved is discussed. This strategy can be used, in simple patient geometries, to ensure the lowest possible normal tissue dose. Strategies for setting the optimum dose constraints and penalties may vary for different optimization algorithms and objective functions. Increasing the number of beams can significantly improve normal tissue dose and target uniformity in situations where the PTV-NT separation is small or the normal tissue dose limits are severe. Setting unrealistically severe constraints in such situations often results in dose distributions that are inferior to plans achieved with more lenient constraints.