Collier Natalie, Kneebone Andrew, Hruby George, McCloud Philip, Booth Jeremy, Eade Thomas
Northern Sydney Cancer Centre, Radiation Oncology, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Northern Clinical School, University of Sydney, Camperdown, New South Wales, Australia.
J Med Imaging Radiat Oncol. 2019 Aug;63(4):546-551. doi: 10.1111/1754-9485.12902. Epub 2019 May 28.
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.
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.
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.
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.
前列腺切除术后放疗(PPRT)的最佳调强放疗(IMRT)/容积调强弧形放疗(VMAT)计划何时达成并不总是显而易见的。患者解剖结构的个体差异是一个关键因素。本研究旨在创建一个模型,根据计划前的个体患者解剖结构来确定直肠和/或膀胱剂量超过计划目标的概率。
将200名男性的IMRT/VMAT PPRT计划随机且平均地分配到训练队列和验证队列中。对训练队列进行单因素和多因素分析,以确定影响膀胱和直肠剂量的变量。将显著变量纳入分类与回归树(CART)分析。然后将所得算法应用于验证队列。
多因素分析显示,处方剂量、膀胱和直肠体积、淋巴结治疗以及膀胱和直肠与计划靶体积(PTV)的重叠百分比是显著变量。经过CART分析,直肠(直肠重叠>20%)和膀胱(膀胱重叠>20%)的重叠体积(OV)是达到计划目标的关键驱动因素。盆腔淋巴结治疗被列为膀胱(而非直肠)剂量的次要驱动因素。将CART分析应用于验证队列时,其分别预测了95%和87%能达到膀胱和直肠计划目标的患者。
开发了一种简单算法,通过使用膀胱和直肠与PTV的OV来预测计划质量。该算法可在解剖结构多变的情况下,事先用于评估计划过程,并优化计划质量和效率。