Rhee Dong Joo, Perni Subha, Perrin Kelly J, Casey Kevin E, Leone Alexandra O, Nguyen Callistus M, Court Laurence E, Wang He, Wang Xin, Han Eun Young
Department of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.
Department of Central Nervous System Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
J Appl Clin Med Phys. 2025 Jul;26(7):e70076. doi: 10.1002/acm2.70076. Epub 2025 Mar 18.
Hippocampal avoidance whole-brain radiotherapy (HA-WBRT) is designed to spare cognitive function by reducing radiation dose to the hippocampus during the treatment of brain metastases. Current manual planning methods can be time-consuming and may vary in quality, necessitating the development of automated approaches to streamline the process and ensure consistency.
To automate hippocampal avoidance whole-brain radiotherapy (HA-WBRT) planning.
Our algorithm automatically contours organs-at-risk (OARs) and the hippocampal-avoidance brain target. The algorithm generates planning structures from given contours, utilizing preset beam parameters and dose constraints for optimization. If the dose constraints are unmet, "hotspot" contours will be created to improve dosimetry. The algorithm was written with RayStation's scripting feature and was compared with clinically approved manual HA-WBRT plans for 20 retrospective patients using target and OAR dose metrics, with statistical analysis performed using the Student's t-test. In the qualitative review, an experienced radiation oncologist blindly scored both the manual plans and autoplans for qualitative review. Lastly, IMRT QA was performed to determine the plans' deliverability.
The autoplans demonstrated a better target coverage with a more uniform dose. With a prescription dose of 3000 cGy, autoplans achieved higher D (3026 cGy vs. 2998 cGy, p = 0.02) and lower D (3337 cGy vs. 3533 cGy, p < 0.01) for the target. The maximum OAR doses were substantially lower in the eyes of autoplans (1727 cGy vs. 2176 cGy, p < 0.01), while the other OARs had similar maximum doses to those of the manual plans. The autoplans met all of the in-house dose constraints, and the minimum dose to the hippocampus was reduced by 5% compared to the manual plans; the average MU was 1376 ± 329 MU for the manual plans and 1141 ± 64 MU for the autoplans. Autoplan generation took an average of 100.2 ± 16.3 minutes (range 62.9-127.9 min). In the qualitative review, the average scores were 4.9 ± 0.4 for the autoplans and 3.4 ± 1.0 for the manual plans. The gamma criteria results for IMRT QA were 96.4 ± 2.1% for the autoplans and 91.6 ± 5.3% for the manual plans.
Our rule-based autoplanning algorithm produces high-quality plans that are comparable to those of manual planning, demonstrating autoplanning's potential to reduce HA-WBRT planning time while ensuring consistent plan quality.
海马回避全脑放疗（HA-WBRT）旨在通过在脑转移瘤治疗期间降低海马体的辐射剂量来保留认知功能。当前的手动规划方法可能耗时且质量参差不齐，因此需要开发自动化方法来简化流程并确保一致性。
实现海马回避全脑放疗（HA-WBRT）规划的自动化。
我们的算法自动勾勒出危及器官（OARs）和海马回避脑靶区。该算法根据给定轮廓生成规划结构，利用预设的射束参数和剂量约束进行优化。如果未满足剂量约束，将创建“热点”轮廓以改善剂量测定。该算法使用RayStation的脚本功能编写，并与20例回顾性患者的临床批准的手动HA-WBRT计划进行比较，使用靶区和OAR剂量指标，采用学生t检验进行统计分析。在定性评估中，一位经验丰富的放射肿瘤学家对手动计划和自动计划进行盲法评分以进行定性审查。最后，进行调强放疗质量保证（IMRT QA）以确定计划的可交付性。
自动计划显示出更好的靶区覆盖和更均匀的剂量。处方剂量为3000 cGy时，自动计划在靶区实现了更高的D（3026 cGy对2998 cGy，p = 0.02）和更低的D（3337 cGy对3533 cGy，p < 0.01）。自动计划眼中的最大OAR剂量显著更低（1727 cGy对2176 cGy，p < 0.01），而其他OARs的最大剂量与手动计划相似。自动计划满足了所有内部剂量约束，与手动计划相比，海马体的最小剂量降低了5%；手动计划的平均机器跳数（MU）为1376 ± 329 MU，自动计划为1141 ± 64 MU。自动计划生成平均耗时100.2 ± 16.3分钟（范围62.9 - 127.9分钟）。在定性评估中，自动计划的平均得分为4.9 ± 0.4，手动计划为3.4 ± 1.0。IMRT QA的伽马标准结果自动计划为96.4 ± 2.1%，手动计划为91.6 ± 5.3%。
我们基于规则的自动规划算法生成的高质量计划与手动规划相当，证明了自动规划在减少HA-WBRT规划时间同时确保一致计划质量方面的潜力。
