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TH‐CD‐207A‐10: Using the Gamma Index to Flag Changes in Anatomy During Radiation Therapy of Head and Neck Cancer

机译:TH-CD-207A-10:使用伽玛指数在头部和颈部癌症的放射治疗过程中造针造旗的变化

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Purpose: This article presents a fast algorithm for comparing 3‐D anatomy from Cone‐Beam CT (CBCT) imaging using the gamma comparison index and to demonstrate how this can be used to flag patients for possible re‐planning of treatment. Methods: CBCT scans acquired on a Varian linear accelerator during treatment were used as input to the gamma comparator using thresholds of 5 mm distance to agreement and 30 Hounsfield Unit CT number difference. The fraction 1 CBCT study was initially used as the reference. Should there be a re‐plan during treatment, the reference resets to the CBCT study acquired on the day 1 of the re‐plan. Histograms of failing pixels (γ 1) were generated from each 3‐D gamma map. An indicator of anatomy congruence, the match quality parameter (MQP), was derived from failed pixel histograms using the 90th percentile gamma value. The MQP was plotted versus fraction number and related to actual repeat computed tomography (re‐CT) order dates as decided by a radiation oncologist. From this, decision criteria were derived for the algorithm to “trigger” re‐CT consideration and predictive power was scored using receiver‐operator characteristic (ROC) analysis. Results: The MQP plot generally showed that the on‐line match from CBCT image guidance deteriorated as the treatment progressed due to weight loss and tumor regression. The optimized MQP criteria for triggering re‐CT consideration demonstrated high sensitivity and specificity, consistent with actual re‐CT order dates within ± 3 fractions. Out of 20 patients that were actually re‐planned, the algorithm failed to trigger a re‐CT recommendation only twice and this was caused by CBCT ring artifacts. Conclusion: We have demonstrated that gamma comparisons can be used to evaluate CBCT‐acquired anatomy pairs and, from this, an algorithm can be “trained” to flag patients for possible re‐planning in a manner consistent with local radiation oncology practice.
机译:目的:本文介绍了一种快速算法,用于使用伽马比较指标从锥形光束CT(CBCT)成像比较3-D解剖学,并证明如何用于标记患者进行治疗的可能重新规划。方法:使用5mm距离与协议的阈值和30 Hounsfield单元CT数差,使用在处理期间在处理过程中获得的CBCT扫描作为伽马比较器的输入。最初使用级分1 CBCT研究作为参考。如果在治疗期间有重新计划,则参考将重置为在重新计划第1天获得的CBCT研究。从每个3-D伽马图产生失败像素(γ& 1)的直方图。解剖学一致性的指标,匹配质量参数(MQP),从使用第90百分位数伽马值导出从失败的像素直方图导出。 MQP与分数数相绘制,与实际重复计算断层扫描(RE-CT)订单日期相关,如放射肿瘤科医生决定。由此,导出判断标准为算法“触发”重新CT考虑,使用接收器 - 操作员特征(ROC)分析得分预测功率。结果:MQP图通常表明,由于减肥和肿瘤回归由于治疗进展而导致CBCT图像引导的在线匹配。用于触发RE-CT考虑的优化MQP标准表现出高灵敏度和特异性,与±3分数内的实际RE-CT订单日期一致。在20名实际重新计划的患者中,该算法未能仅触发两次RE-CT推荐,这是由CBCT环形伪影引起的。结论:我们已经证明,伽玛比较可用于评估CBCT获取的解剖成对,并且从此可以“训练”以以与局部辐射肿瘤学实践一致的方式进行标记患者。

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