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随后基于千伏成像的基准三角测量用于分次内前列腺运动监测与校正。

Subsequent kilovoltage imaging-based fiducial triangulation for intra-fractional prostate motion monitoring and correction.

作者信息

Gevorkyan Gevork S, Chen Quan, Tegtmeier Riley C, Toesca Diego Santos, Laughlin Brady S, Bashir Sara, Welchel Zachary J, Holmes Jason M, Vargas Carlos E, Rwigema Jean-Claude M, James Sarah E, Yu Nathan Y, Rong Yi

机构信息

Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.

Department of Radiation Oncology, University of South Florida Morsani College of Medicine, Tampa, Florida, USA.

出版信息

Med Phys. 2025 Jun;52(6):4008-4022. doi: 10.1002/mp.17703. Epub 2025 Feb 22.

Abstract

BACKGROUND

Inter-fractional and intra-fractional positioning and motion monitoring based on implanted fiducials through kilovoltage (kV) imaging is a cost-effective approach to enhance intact prostate radiotherapy treatment accuracy. However, comprehensive studies for three-dimensional (3D) position extraction and the corrective action threshold are lacking.

PURPOSE

To develop and verify a fiducial motion monitoring system with 3D position information based on triggered kV images taken during treatment delivery, and to comprehensively evaluate the recommended thresholds for corrective action during treatment.

METHODS

An in-house fiducial triangulation algorithm was developed to monitor fiducial positions using subsequent kV triggered images. The precision of fiducial triangulation and motion detection was validated on a pelvis phantom with four fiducial inserts. A retrospective study was conducted on prostate cancer patients who received either moderately hypofractionated radiotherapy (MHRT, n = 16) or stereotactic body radiotherapy (SBRT, n = 12), categorized by endo-rectal balloon (ERB) use. Intra-fractional positions relative to isocenter were computed, and these positions were analyzed in comparison to the original marker locations of the patient's treatment plan. A linear regression fit was used per fraction to determine correlation coefficients between motions in the left-right (LR), superior-inferior (SI), and anterior-posterior (AP) directions. Average fraction time (AFT) of treatment was reported based on the observed average time spent on steps in the workflow and the percentage of fiducials caught outside of the current two-dimensional (2D) tolerance threshold of 5 mm. The observed 3D offsets were used to estimate AFT for various 3D tolerance thresholds.

RESULTS

Overall, our triangulation method proved to be very precise for static cases, where phantom measurements revealed a fiducial position triangulation precision of mm for stationary targets, but had a spread of mm for targets with 1 mm of motion. Employing triangulation, true motion exceeding 5 mm was detected above 4.0 mm in magnitude 90.9% of the time, a noticeable improvement in comparison to the 28%-65% successful detection rate reported by 2D projection methods. Most detection errors were attributed to depth disparity. Similar to other reports, correlation coefficients for intra-fractional motion generally indicated no LR/SI, no LR/AP, and weak positive SI/AP correlations for MHRT and SBRT patients. Offsets beyond a 3D tolerance threshold of 5 mm were observed at a rate of 4.25%-5.25%, while the 5 mm 2D out-of-tolerance catch-rate was 1.6%. The AFT was 8.1-8.2 min using the 2D tolerance threshold of 5 mm. In comparison, the estimated AFT for the proposed 3D tolerance monitoring of offsets beyond 2-5 mm was slightly higher at 8.2-10.9 min due to the higher amount of out-of-tolerance instances for the higher precision intra-fractional motion management.

CONCLUSIONS

Our study showcases a promising subsequent kV-based triangulation method for intra-fractional prostate motion monitoring. Acquiring 3D motion information results in higher out-of-tolerance catch-rates particularly in the depth dimension of the kV images, which is perpendicular to the treatment beam. Failure to properly observe and catch these offsets would result in sub-optimal conformality and accuracy of the dose delivery.

摘要

背景

基于千伏(kV)成像通过植入基准标记进行分次间和分次内定位及运动监测,是提高前列腺癌放疗治疗准确性的一种经济有效的方法。然而,缺乏关于三维(3D)位置提取和校正动作阈值的综合研究。

目的

开发并验证一种基于治疗过程中触发的kV图像获取3D位置信息的基准标记运动监测系统,并全面评估治疗期间校正动作的推荐阈值。

方法

开发了一种内部基准三角测量算法,使用后续触发的kV图像监测基准标记位置。在带有四个基准标记插入物的骨盆模型上验证了基准三角测量和运动检测的精度。对接受中度低分割放疗(MHRT,n = 16)或立体定向体部放疗(SBRT,n = 12)的前列腺癌患者进行回顾性研究,根据是否使用直肠内气囊(ERB)进行分类。计算相对于等中心的分次内位置,并将这些位置与患者治疗计划的原始标记位置进行比较分析。每分次使用线性回归拟合来确定左右(LR)、上下(SI)和前后(AP)方向运动之间的相关系数。根据观察到的工作流程中各步骤所花费的平均时间以及在当前5mm二维(2D)公差阈值之外捕获的基准标记百分比,报告治疗的平均分次时间(AFT)。使用观察到的3D偏移量来估计各种3D公差阈值下的AFT。

结果

总体而言,我们的三角测量方法在静态情况下证明非常精确,模型测量显示静止目标的基准位置三角测量精度为 mm,但对于运动1mm的目标,其精度范围为 mm。采用三角测量法,在90.9%的时间内,能检测到幅度超过4.0mm、真实运动超过5mm的情况,与二维投影方法报告的28%-65%的成功检测率相比有显著提高。大多数检测误差归因于深度差异。与其他报告类似,MHRT和SBRT患者分次内运动的相关系数通常表明LR/SI方向无相关性、LR/AP方向无相关性以及SI/AP方向呈弱正相关。观察到超出5mm的3D公差阈值的偏移率为4.25%-5.25%,而5mm二维公差外捕获率为1.6%。使用5mm的二维公差阈值时,AFT为8.1-8.2分钟。相比之下,对于提议的超出2-5mm的3D公差监测偏移量,估计的AFT略高,为8.2-10.9分钟,这是由于更高精度的分次内运动管理导致公差外情况数量增加。

结论

我们的研究展示了一种有前景的基于后续kV图像的三角测量方法,用于前列腺癌分次内运动监测。获取3D运动信息可提高公差外捕获率,特别是在与治疗束垂直的kV图像深度维度上。未能正确观察和捕获这些偏移将导致剂量传递的适形性和准确性欠佳。

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