Tedgren Åsa Carlsson, Plamondon Mathieu, Beaulieu Luc
Department of Medical and Health Sciences (IMH) and Center for Medical Image Science and Visualization, Radiation Physics, Linköping University, SE-581 85 Linköping, Sweden and Department of Medical Physics, Karolinska University Hospital, SE 171 76 Stockholm, Sweden.
Phys Med Biol. 2015 Jul 7;60(13):5313-23. doi: 10.1088/0031-9155/60/13/5313. Epub 2015 Jun 25.
The aim of this work was to investigate how dose distributions calculated with the collapsed cone (CC) algorithm depend on the size of the water phantom used in deriving the point kernel for multiple scatter. A research version of the CC algorithm equipped with a set of selectable point kernels for multiple-scatter dose that had initially been derived in water phantoms of various dimensions was used. The new point kernels were generated using EGSnrc in spherical water phantoms of radii 5 cm, 7.5 cm, 10 cm, 15 cm, 20 cm, 30 cm and 50 cm. Dose distributions derived with CC in water phantoms of different dimensions and in a CT-based clinical breast geometry were compared to Monte Carlo (MC) simulations using the Geant4-based brachytherapy specific MC code Algebra. Agreement with MC within 1% was obtained when the dimensions of the phantom used to derive the multiple-scatter kernel were similar to those of the calculation phantom. Doses are overestimated at phantom edges when kernels are derived in larger phantoms and underestimated when derived in smaller phantoms (by around 2% to 7% depending on distance from source and phantom dimensions). CC agrees well with MC in the high dose region of a breast implant and is superior to TG43 in determining skin doses for all multiple-scatter point kernel sizes. Increased agreement between CC and MC is achieved when the point kernel is comparable to breast dimensions. The investigated approximation in multiple scatter dose depends on the choice of point kernel in relation to phantom size and yields a significant fraction of the total dose only at distances of several centimeters from a source/implant which correspond to volumes of low doses. The current implementation of the CC algorithm utilizes a point kernel derived in a comparatively large (radius 20 cm) water phantom. A fixed point kernel leads to predictable behaviour of the algorithm with the worst case being a source/implant located well within a patient/phantom for which low doses at phantom edges can be overestimated by 2-5 %. It would be possible to improve the situation by using a point kernel for multiple-scatter dose adapted to the patient/phantom dimensions at hand.
本研究的目的是探讨使用坍缩圆锥（CC）算法计算的剂量分布如何取决于用于推导多次散射点核的水模体大小。使用了CC算法的一个研究版本，该版本配备了一组可选择的多次散射剂量点核，这些点核最初是在不同尺寸的水模体中推导出来的。新的点核是使用EGSnrc在半径为5厘米、7.5厘米、10厘米、15厘米、20厘米、30厘米和50厘米的球形水模体中生成的。将在不同尺寸的水模体以及基于CT的临床乳腺几何模型中用CC算法得出的剂量分布与使用基于Geant4的近距离治疗专用蒙特卡罗（MC）代码Algebra进行的蒙特卡罗模拟进行比较。当用于推导多次散射核的模体尺寸与计算模体的尺寸相似时，与MC的一致性在1%以内。当在较大模体中推导核时，模体边缘的剂量被高估，而在较小模体中推导时则被低估（根据距源的距离和模体尺寸，低估约2%至7%）。在乳房植入物的高剂量区域，CC与MC吻合良好，并且在确定所有多次散射点核大小的皮肤剂量方面优于TG43。当点核与乳房尺寸可比时，CC与MC之间的一致性会提高。多次散射剂量中所研究的近似值取决于与模体大小相关的点核选择，并且仅在距源/植入物几厘米的距离处产生总剂量的很大一部分，这些距离对应于低剂量区域。CC算法的当前实现使用在相对较大（半径20厘米）的水模体中推导的点核。固定的点核会导致算法具有可预测的行为，最坏的情况是源/植入物位于患者/模体内部，此时模体边缘的低剂量可能被高估2 - 5%。通过使用适合手头患者/模体尺寸的多次散射剂量点核，有可能改善这种情况。
