Gordon J J, Siebers J V
Department of Radiation Oncology, Virginia Commonwealth University, PO Box 980058, Richmond, VA 23298, USA.
Phys Med Biol. 2007 Apr 7;52(7):1967-90. doi: 10.1088/0031-9155/52/7/013. Epub 2007 Mar 20.
The van Herk margin formula (VHMF) relies on the accuracy of the convolution method (CM) to determine clinical target volume (CTV) to planning target volume (PTV) margins. This work (1) evaluates the accuracy of the CM and VHMF as a function of the number of fractions N and other parameters, and (2) proposes an alternative margin algorithm which ensures target coverage for a wider range of parameter values. Dose coverage was evaluated for a spherical target with uniform margin, using the same simplified dose model and CTV coverage criterion as were used in development of the VHMF. Systematic and random setup errors were assumed to be normally distributed with standard deviations Sigma and sigma. For clinically relevant combinations of sigma, Sigma and N, margins were determined by requiring that 90% of treatment course simulations have a CTV minimum dose greater than or equal to the static PTV minimum dose. Simulation results were compared with the VHMF and the alternative margin algorithm. The CM and VHMF were found to be accurate for parameter values satisfying the approximate criterion: sigma[1 - gammaN/25] < 0.2, where gamma = Sigma/sigma. They were found to be inaccurate for sigma[1 - gammaN/25] > 0.2, because they failed to account for the non-negligible dose variability associated with random setup errors. These criteria are applicable when sigma greater than or approximately egual sigma(P), where sigma(P) = 0.32 cm is the standard deviation of the normal dose penumbra. (Qualitative behaviour of the CM and VHMF will remain the same, though the criteria might vary if sigma(P) takes values other than 0.32 cm.) When sigma << sigma(P), dose variability due to random setup errors becomes negligible, and the CM and VHMF are valid regardless of the values of Sigma and N. When sigma greater than or approximately egual sigma(P), consistent with the above criteria, it was found that the VHMF can underestimate margins for large sigma, small Sigma and small N. A potential consequence of this underestimate is that the CTV minimum dose can fall below its planned value in more than the prescribed 10% of treatments. The proposed alternative margin algorithm provides better margin estimates and CTV coverage over the parameter ranges examined here. This algorithm is not amenable to expression as a simple formula (e.g., as a linear combination of Sigma and sigma). However, it can be easily calculated. For 0.1 cm < or = sigma < or = 0.75 cm, 0 < or = gamma < or = 1 and 5 < or = N < or = 30, the VHMF underestimates margins by as much as 33%. With the alternative margin algorithm, the maximum underestimate is 7%. These results suggest that the VHMF should be used with caution for hypofractionated treatment and in adaptive therapy.
范·赫尔克边界公式(VHMF)依赖于卷积法(CM)的准确性来确定临床靶区(CTV)到计划靶区(PTV)的边界。本研究(1)评估了CM和VHMF作为分次照射次数N及其他参数的函数时的准确性,(2)提出了一种替代边界算法,该算法能确保在更广泛的参数值范围内实现靶区覆盖。使用与VHMF开发过程中相同的简化剂量模型和CTV覆盖标准,对具有均匀边界的球形靶区的剂量覆盖情况进行了评估。假设系统和随机摆位误差呈正态分布,标准差分别为Sigma和sigma。对于sigma、Sigma和N的临床相关组合,通过要求90%的治疗过程模拟中CTV的最小剂量大于或等于静态PTV的最小剂量来确定边界。将模拟结果与VHMF和替代边界算法进行了比较。发现CM和VHMF对于满足近似标准sigma[1 - gammaN/25] < 0.2的参数值是准确的,其中gamma = Sigma/sigma。当sigma[1 - gammaN/25] > 0.2时,发现它们不准确,因为它们没有考虑与随机摆位误差相关的不可忽略的剂量变异性。当sigma大于或近似等于sigma(P)时,这些标准适用,其中sigma(P) = 0.32 cm是正常剂量半影的标准差。(尽管如果sigma(P)取0.32 cm以外的值标准可能会有所不同,但CM和VHMF的定性行为将保持不变。)当sigma << sigma(P)时,随机摆位误差引起的剂量变异性可忽略不计,CM和VHMF无论Sigma和N的值如何都是有效的。当sigma大于或近似等于sigma(P)时,与上述标准一致,发现对于大sigma、小Sigma和小N,VHMF可能会低估边界。这种低估的一个潜在后果是,在超过规定的10%的治疗中,CTV的最小剂量可能会低于其计划值。在此处研究的参数范围内,提出的替代边界算法提供了更好的边界估计和CTV覆盖。该算法不适合表示为简单公式(例如,作为Sigma和sigma的线性组合)。然而,它可以很容易地计算出来。对于0.1 cm ≤ sigma ≤ 0.75 cm,0 ≤ gamma ≤ 1且5 ≤ N ≤ 30,VHMF低估边界多达33%。使用替代边界算法时,最大低估为7%。这些结果表明,在低分割治疗和自适应治疗中应谨慎使用VHMF。