使用小波进行强度调制治疗计划的子野剂量分布压缩与重建。

Zakarian Constantine, Deasy Joseph O

Department of Radiation Oncology, Alvin J. Siteman Cancer Center, Mallinckrodt Institute of Radiology, Washington University Medical Center, St. Louis, Missouri 63110, USA.

Med Phys. 2004 Feb;31(2):368-75. doi: 10.1118/1.1636560.

Intensity modulated radiation therapy (IMRT) treatment planning is often formulated as the optimization of weights of fixed-geometry subfields (beamlets). Efficient optimization techniques can be based on direct storage of the influence matrix relating beamlet weights to dose values. However, direct storage of beamlet dose distributions for IMRT treatment planning can easily exceed several gigabytes, and is therefore often not feasible. We present a method for rapidly calculating full three-dimensional IMRT dose distributions, based on a vector of beamlet weights. The method is based on compressed beamlet dose distributions using fast digital wavelet transforms and so-called hard thresholding. We studied the method with a rectangular beamlet of 0.5 cm x 0.5 cm cross section from a monoenergetic 6 MeV photon point source simulated in homogeneous (water) and heterogeneous (CT-data) phantoms. Dose was calculated using the accurate VMC+ + Monte Carlo engine. The beamlet dose distributions were wavelet transformed and compressed by dropping wavelet coefficients below a given threshold value. Dose is then computed using the remaining wavelets. Selection of the wavelet basis function, decomposition level, and threshold values, for different slice orientations (transverse or parallel to the beam) and varying angles of beamlet incidence are studied. A typical in-slice compression ratio for a plane containing a beamlet was 32:1 using the sym2 wavelet and a threshold of 0.01, with a typical root-mean-square error, for voxels above 50% of the maximum dose, of about 0.04%. The overall compression performance, which includes many planes with little information content, is on the order of 100:1 or greater compared to full matrix storage. Although other methods are available to make the use of stored influence matrix values more feasible in IMRT treatment planning (such as using coarse grids or restricting values to defined volumes of interest) we conclude that wavelet compression facilitates the storage and use of full pencil dose deposition (influence matrix) data in IMRT treatment planning.

调强放射治疗（IMRT）治疗计划通常被制定为对固定几何形状子野（射束单元）权重的优化。高效的优化技术可基于直接存储将射束单元权重与剂量值相关联的影响矩阵。然而，用于IMRT治疗计划的射束单元剂量分布的直接存储很容易超过数GB，因此通常不可行。我们提出了一种基于射束单元权重向量快速计算完整三维IMRT剂量分布的方法。该方法基于使用快速数字小波变换和所谓的硬阈值处理的压缩射束单元剂量分布。我们用一个来自单能6 MeV光子点源的0.5 cm×0.5 cm横截面的矩形射束单元在均匀（水）和非均匀（CT数据）体模中进行了模拟研究。使用精确的VMC++蒙特卡罗引擎计算剂量。对射束单元剂量分布进行小波变换，并通过舍弃低于给定阈值的小波系数进行压缩。然后使用剩余的小波计算剂量。研究了不同切片方向（横向或与射束平行）以及射束单元入射角度变化时小波基函数、分解级别和阈值的选择。使用sym2小波和0.01的阈值时，包含射束单元的平面的典型切片内压缩比为32:1，对于高于最大剂量50%的体素，典型均方根误差约为0.04%。与完整矩阵存储相比，包括许多信息含量少的平面的整体压缩性能约为100:1或更高。尽管有其他方法可使在IMRT治疗计划中使用存储的影响矩阵值更可行（例如使用粗网格或将值限制在定义的感兴趣体积内），但我们得出结论，小波压缩有助于在IMRT治疗计划中存储和使用完整的笔形剂量沉积（影响矩阵）数据。