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Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software

机译:基于Eclipse脚本的特定于患者的自动防撞软件的开发和临床实施

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Purpose Increased use of Linac‐based stereotactic radiosurgery (SRS), which requires highly noncoplanar gantry trajectories, necessitates the development of efficient and accurate methods of collision detection during the treatment planning process. This work outlines the development and clinical implementation of a patient‐specific computed tomography (CT) contour‐based solution that utilizes Eclipse Scripting to ensure maximum integration with clinical workflow. Methods The collision detection application uses triangle mesh structures of the gantry and couch, in addition to the body contour of the patient taken during CT simulation, to virtually simulate patient treatments. Collision detection is performed using Binary Tree Hierarchy detection methods. Algorithm accuracy was first validated for simple cuboidal geometry using a calibration phantom and then extended to an anthropomorphic phantom simulation by comparing the measured minimum distance between structures to the predicted minimum distance for all allowable orientations. The collision space was tested at couch angles every 15° from 90 to 270 with the gantry incremented by 5° through the maximum trajectory. Receiver operating characteristic curve analysis was used to assess algorithm sensitivity and accuracy for predicting collision events. Following extensive validation, the application was implemented clinically for all SRS patients. Results The application was able to predict minimum distances between structures to within 3?cm. A safety margin of 1.5?cm was sufficient to achieve 100% sensitivity for all test cases. Accuracy obtained was 94.2% with the 5?cm clinical safety margin with 100% true positive collision detection. A total of 88 noncoplanar SRS patients have been currently tested using the application with one collision detected and no undetected collisions occurring. The average time for collision testing per patient was 2?min 58?s. Conclusions A collision detection application utilizing patient CT contours was developed and successfully clinically implemented. This application allows collisions to be detected early during the planning process, avoiding patient delays and unnecessary resource utilization if detected during delivery.
机译:目的越来越多地使用基于Linac的立体定向放射外科(SRS),这需要高度非共面的龙门轨迹,因此有必要在治疗计划过程中开发有效而准确的碰撞检测方法。这项工作概述了基于患者的计算机断层扫描(CT)基于轮廓的解决方案的开发和临床实施,该解决方案利用Eclipse脚本来确保与临床工作流程的最大集成。方法碰撞检测应用程序除了在CT模拟过程中获取患者的身体轮廓外,还使用龙门架和沙发床的三角形网格结构来虚拟模拟患者的治疗。使用二叉树层次结构检测方法执行冲突检测。首先使用校准体模对简单的立方体几何体验证算法的准确性,然后通过将结构之间的实测最小距离与所有允许方向的预测最小距离进行比较,将算法的精度扩展到拟人体模仿真。在从90到270的每15°躺椅角度测试碰撞空间,并通过最大轨迹将门架增加5°。接收器工作特性曲线分析用于评估算法灵敏度和预测碰撞事件的准确性。经过广泛的验证,该应用程序已在临床上适用于所有SRS患者。结果该应用程序能够预测结构之间的最小距离在3?cm以内。 1.5?cm的安全裕度足以使所有测试用例达到100%的灵敏度。准确度为94.2%,临床安全裕度为5?cm,真正的碰撞检测为100%。目前,使用该应用程序对总共88位非共面SRS患者进行了测试,发现一个碰撞,没有发生未检测到的碰撞。每位患者进行碰撞测试的平均时间为2?min 58?s。结论开发了利用患者CT轮廓的碰撞检测应用程序,并成功地在临床上实现了该应用程序。该应用程序允许在计划过程中及早发现冲突,从而避免了患者延误以及在分娩过程中被发现时不必要的资源利用。

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