首页> 外文期刊>Journal of neurosurgical sciences >A simple algorithm to predict non-compliance with organ at risk dose-volume constraints when planning intensity modulated post-prostatectomy radiation treatment: 'Why we should put the CART before the horse'
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A simple algorithm to predict non-compliance with organ at risk dose-volume constraints when planning intensity modulated post-prostatectomy radiation treatment: 'Why we should put the CART before the horse'

机译:一种简单的算法,在规划强度调制后前列腺切除术辐射治疗时预测风险剂量约束的风险剂量约束的算法:“为什么我们应该将推车放在马之前”

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Introduction It is not always apparent when the optimal IMRT/VMAT plan for post-prostatectomy radiotherapy (PPRT) has been achieved. Individual variation in patient anatomy is a key contributor. This study aimed to create a model to determine the probability of rectum and/or bladder doses exceeding planning goals based on individual patient anatomy prior to planning. Methods The IMRT/VMAT PPRT plans from 200 men were randomly and evenly allocated into the Training Cohort and the Validation Cohort. Univariate and multivariate analysis of the Training Cohort identified variables which impacted bladder and rectal doses. Significant variables were included in a Classification and Regression Tree (CART) analysis. The resultant algorithm was then applied to the Validation Cohort. Results On multivariate analysis, prescription dose; bladder and rectal volume; lymph node treatment; and percentage of bladder and rectal overlap with the PTV were significant variables. Following CART analysis, the overlap volume (OV) for both rectum (rectum overlap > 20%) and bladder (bladder overlap > 20%) were the key drivers of meeting planning goals. Treatment of pelvic lymph nodes was included as the secondary driving factor for bladder (but not rectal) dose. On application to the Validation Cohort, CART analysis predicted 95% and 87% of patients who would meet bladder and rectal planning goals respectively. Conclusions A simple algorithm was developed to predict plan quality by using the OV of the bladder and rectum with the PTV. This algorithm may be used a priori to assess the planning process in the context of variable anatomy, and to optimise planning quality and efficiency.
机译:当达到前列腺切除术放射疗法(PPRT)的最佳IMRT / VMAT计划时,并不总是显而易见的。患者解剖学的个体变异是一个关键的贡献者。本研究旨在创建一种模型,以确定直肠和/或膀胱剂量超出规划目标的规划,基于规划前的个体患者解剖学。方法采用200名男性的IMRT / VMAT PPRT计划随机均匀地分配到培训队列和验证队列中。训练队的单变量和多变量分析鉴定了影响膀胱和直肠剂量的变量。分类和回归树(推车)分析中包括显着变量。然后将得到的算法应用于验证队列。结果对多变量分析,处方剂量;膀胱和直肠体积;淋巴结治疗;与PTV的膀胱和直肠重叠的百分比是显着的变量。购物车分析后,直肠(RECTUM重叠> 20%)和膀胱(膀胱重叠> 20%)的重叠体积(OV)是会议计划目标的关键驱动因素。将盆腔淋巴结的处理作为膀胱(但不是直肠直肠)剂量的二次驱动因子。在验证队列的应用中,购物车分析预测95%和87%的患者分别符合膀胱和直肠计划目标。结论开发了一种简单的算法,通过使用PTV使用膀胱和直肠的OV来预测计划质量。该算法可以使用先验以在可变解剖结构的上下文中评估规划过程,并优化规划质量和效率。

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