脑转移瘤调强放疗最佳子野数目

目的:研究子野数目对脑转移瘤患者调强放射治疗(IMRT)计划质量、治疗时间、机器磨损等影响,获得最佳子野数目。方法:重新优化30例患者的IMRT计划,保持其它参数一致,仅改变子野数制定放疗计划P0、P1、P2…。原始计划P0优化获得子野数的90%作为P1给定的子野数,优化P1获得子野数的90%作为P2给定的子野数,以此类推直到IMRT计划质量不能满足临床要求。统计靶区最小剂量、最大剂量、平均剂量、靶区适形指数、靶区均匀性指数、危及器官受量等参数,用于对计划质量进行分析比较,得到计划质量满足临床要求的同时子野数最少的最佳放疗计划Pm。结果:最优子野计划相对于原计划的子野数由81减少到34,总MU减少205.00,每个射野MU减少34.00,子野MU增加10.72,子野面积增加9.35 cm2,治疗时间减少228.96 s,3 mm/3%标准通过率变化不大。结论:对于较简单的靶区,每个射野的子野数给定为3~6;较复杂的靶区,每个射野的子野数给定为4~8,既不影响计划质量又能减少治疗时间,降低分次内的不确定度和减少机器磨损。     

子野小数机器跳数取整对鼻咽癌静态调强放射治疗计划剂量学的影响

目的:探讨Prowess5.1计划系统在鼻咽癌静态调强放疗（IMRT）计划设计时子野小数机器跳数（MU）的四舍五入取整对计划剂量学的影响。 方法:选择33例病理诊断明确的鼻咽癌患者的IMRT计划纳入研究,分为两组计划:计划系统优化完成的原始计划组为Porig;对原始计划组的子野小数机器跳数四舍五入取整,做最终剂量计算后生成新计划组Pnew。两组计划所有子野形状未改变,比较两组计划的MU变化及剂量学差异。 结果:两组计划所有靶区的CI和HI相近,差异均无统计学意义;Pnew组靶区覆盖率、PGTVnd的D98、D95、D2、Dmean及PTV2的D98、D95,Pnew组均低于Porig组（P<0.05）,PGTVnd、PTVnx和PTV1的V100%分别降低了1.807%、0.655%和1.258%;危及器官仅左颞叶的Dmean差异具有统计学意义（P<0.05）;对于P1计划,单次Pnew比Porig跳数增加了1.600,差异具有统计学意义（519.758±46.410 vs 518.158±46.693, P<0.05)。 结论:Prowess5.1计划系统在制定鼻咽癌静态调强IMRT计划时,子野小数MU的微小变化会引起剂量学的变化,临床实践中应引起重视。     

胸段食管癌不同调强放疗技术的剂量学差异分析

目的:比较不同调强放疗技术在胸段食管癌的剂量学差异,探讨适用于胸段食管癌的调强放射治疗手段。方法:选取2016~2017年间收治的10例病理确诊的局部晚期胸段食管癌,用Monaco 5.11 TPS进行计划设计,分别制定固定角度5野和7野静态调强(sIMRT)和动态调强(dIMRT),360°单弧VMAT共5种放疗计划,比较不同计划靶区的剂量分布以及危及器官(OAR)受量,并比较加速器的总机器跳数(MU)和治疗执行时间,以评估不同技术的执行效率。结果:5种调强计划的靶区剂量均能满足临床处方要求,固定角度7野IMRT技术在靶区覆盖率、适形度和剂量分布均匀性方面均优于5野IMRT,但差异无统计学意义(P0.05)。5种调强计划在双肺的高量区V_(20)、V_(30)的差异不明显。与sIMRT相比,dIMRT降低了双肺低剂量区V_5、V_(10)的受照体积。而对于VMAT计划来说,双肺低剂量区V_5、V_(10)的受照体积均高于固定野的IMRT计划,但仅V_5的剂量差异有统计学意义(P0.05)。5种调强计划中心脏、脊髓的受照剂量无明显差异(P0.05)。固定角度IMRT计划,随着野数增加,MU数显著增加,计划治疗执行时间也随着增加;dIMRT的MU数比sIMRT明显增多(P0.05),但计划治疗时间明显减少(P0.05)。VMAT计划的MU数比静态调强计划和5野动态调强明显增多(P0.05),但VMAT计划的治疗时间最短,执行效率最高。结论:对胸段食管癌治疗,5野dIMRT可以在满足靶区剂量学要求和保护正常组织的同时,显著缩短治疗时间,并提高治疗效率。而VMAT计划虽能显著减少治疗时间,但同时提高了双肺低剂量区受照体积,对于胸段食管癌来说,VMAT并无明显剂量优势。     

头颈部肿瘤静态调强中强度分级数的研究

目的:研究在头颈部肿瘤静态调强放疗中强度分级数对计划结果的影响,确定在临床调强放疗中最佳的强度分级参数。方法:利用商用的放疗计划系统,分别对5个临床头颈部肿瘤病例作静态调强放疗计划。在强度矩阵离散化时,设置离散化等级分别为3、4、5、6、7、8、10、15和20。比较和分析强度分级数对放疗计划结果的影响。结果:从总的趋势来看,随着强度分级数的提高,PTV的最小剂量增大,最大剂量减小,剂量标准差减小;危及器官受到的剂量照射降低;总的子野数目增加;总的机器跳数降低。结论:提高强度分级数,意味着可能提高IMRT计划的质量。综合强度分级数对PTV、OAR和治疗时间的影响,建议在计划设计时,将强度分级数控制在5~10级范围内。     

脑胶质瘤术后VMAT与IMRT放疗技术间比较

目的:比较脑胶质瘤术后容积旋转调强(Volumetric Modulated Arc Therapy,VMAT)计划与静态调强(IntensityModulated Radiation Therapy,IMRT)计划,讨论VMAT的剂量学特性,分析VMAT在脑胶质瘤术后放射治疗中的应用。材料与方法:选取10例颅内肿瘤患者,采用Monaco治疗计划系统,分别制作VMAT计划与IMRT计划,处方剂量全部为PTV:60 Gy/30f。比较两组计划的剂量分布图、DVH图、适形度指数(CI)、均匀指数(HI)、治疗时间、治疗跳数(MU)、危及器官受量。结果:两组计划靶区剂量分布及适形度均较好,CI、HI数相近(P>0.05),但VMAT组的治疗时间和MU均优于IMRT组(P<0.05)。在危及器官受量方面,两组计划的脑干与视交叉的平均剂量相近(P>0.05),而视神经、视网膜、晶体和周围正常脑组织的平均剂量,VMAT组明显低于IMRT组(P<0.05)。结论:在脑胶质瘤术后的放射治疗中,VMAT与IMRT的靶区剂量分布相近。VMAT的优势在于大大缩小缩短治疗时间、减少MU,同时减少了部分危及器官受量。     

子野权重优化对CMS XiO宫颈癌调强计划的影响

目的:本文分析了CMS治疗计划系统XiO在制定调强放射治疗(IMRT)计划时,子野权重优化对治疗计划结果的影响。方法:本文选取10例宫颈癌全程放射治疗病例,制定影像引导下(IGRT)的调强放射治疗计划,首先直接用静态调强(Step&Shoot)方式进行优化一步生成调强放射治疗计划(S-IMRT),之后继续进行子野权重优化(Segment weight op-timization,SWO)并生成新的治疗计划(SWO-IMRT),比较子野权重优化前后总子野数、总跳数,同时分析比较正常组织受照剂量的变化。结果:结果显示,经过子野权重优化后,总的子野数显著减少,减少约26%~31%(p<0.0001);总的机器跳数有所降低,减少约5.1%~9.7%(p<0.0001),同时,直肠、膀胱和小肠的剂量也有所降低。结论:在使用CMS治疗计划系统XiO进行宫颈癌全程调强放射治疗计划设计过程中,充分利用子野权重优化方式,可以减少总的机器跳数,降低正常组织剂量,缩短治疗时间,这既降低正常组织的毒性反应,也为肿瘤剂量的提高提供了可能。在其他病种的调强放射治疗计划设计中,子野权重优化也可以发挥重要的作用。     

调强放射治疗计划中子野跳数输出误差分析

目的:探讨三维静态调强放射治疗计划的子野机器跳数(MU)与加速器实际输出的MU存在的误差,为计划设计时最小跳数的设置提供参考。方法:选择50例调强放射治疗计划,子野数共4 842个。对治疗计划每个子野输出的MU(PDM)与实际加速器出束时每个子野的MU(ADM)进行统计学分析,判断两者的误差情况。结果:计划PDM与ADM的平均值存在显著差异(P0.05);当PDM值较小时,PDM与ADM的相对误差概率大大增加,最高达16.33%。结论:PDM与ADM之间存在的误差临床上不可忽视。在不影响计划剂量分布的前提下,当误差可接受在5%内时,建议PDM应该大于8.49 MU;当可接受误差在3%内时,建议PDM应大于14.46 MU。     

SmartSequence与SlidingWnd两种子野分割算法的比较

目的:本研究试图比较Elekta Xio TPS(版本:4.62)计划设计中使用SmartSequence和SlidingWnd两种子野分割算法的特点。方法:对9例宫颈癌患者优化计划设计后的射野通量分布,分别用两种子野分割算法分别分割子野,将剂量归一到95%ptv=5000 cGy。然后利用剂量体积直方图(DVH)、靶区和危及器官的剂量分布、子野数、机器跳数(MU)以及治疗时间,对两组计划进行比较。结果:两种子野分割算法得到的计划均满足临床要求,剂量分布基本一致,DVH接近。相对于SlidingWnd子野分割算法,SmartSequence分割算法得到的子野数数目平均减少了28%,总MU数减少了20%,但是在治疗时间上没有明显优势。结论:在维持治疗计划方案质量相同的条件下,与SlidingWnd子野分割算法相比,SmartSequence分割算法可以显著减少子野数和总MU数。     

两种不同优化算法在胸部肿瘤调强放射治疗计划中的对比研究

目的:研究直接子野优化(DMPO)算法与多目标优化(MCO)算法在胸部肿瘤放射治疗计划设计优化过程中的差异。方法:选取20例食管癌患者,将患者在Pinnacle3计划系统的CT图像、勾画的靶区、设计参数和剂量信息等资料,通过DicomRT协议从Pinnacle3计划系统传输到Ray Station计划系统中。保持照射野设置、处方剂量不变,改用MCO算法重新优化治疗计划,比较两种优化算法在剂量分布、靶区适形指数(CI)与靶区均匀指数(HI)、危及器官(OAR)剂量、计划设计与执行效率的差异性。结果:两种算法优化的计划结果均能基本满足临床剂量要求,与DMPO相比,MCO计划靶区PGTV适形指数CIpgtv和均匀指数HIpgtv以及靶区PTV的适形指数CIptv均差别不大,但危及器官的受量明显小于前者,其中肺的V10、V20、V30、平均剂量Dmean-l,心脏的V30、V40和平均剂量Dmean-h以及脊髓最大剂量D1cm3-s和平均剂量Dmean-s,均存在显著性差异;从计划的设计时间上来看,MCO计划组明显短于DMPO计划组,而从执行效率上来看,两者差异不大。结论:对于食管癌同期加量三维调强放疗计划,与DMPO算法相比,MCO算法可得到更低的OAR剂量,并且在临床应用上明显提高工作效率。     

颈段及胸上段食管癌调强放射治疗计划的比较

目的：射野数目的多少在调强放射计划中直接影响着靶区的适形性（conformity）,均匀度（uniformity）以及对周围危及器官（organs at risk,OAR）的保护。本文就颈段及胸上段食管癌,对不同射野数目进行调强放射治疗计划的比较。方法：回顾继往颈段及胸上段食管癌病例,从中挑选5位患者,运用5,7,9个射野的调强放射治疗计划,同时对IMRT的靶区运用200 cGy/fx,30fx总共60 Gy剂量,比较在这个给定相同的剂量的条件下,通过剂量体积直方图（dose volumehistograms,DVH）,等剂量曲线分布（iso-dose distributions）以及靶区的适形指数（conformity index,CI）等来比较各个计划中计划靶区（planning target volume,PTV）,以及危及器官（OARs）的剂量学差异。结果：随着射野数目的增加靶区适形度以及等剂量线分布越来越好。7、9个射野对肺的损伤也不像想象中那么大。甚至7、9野的IMRT在肺的V20更低。结论：相比5个射野的IMRT计划,7个射野能提供更好的适形度和均匀性,以及对肺组织的保护;而相比9野计划,7个射野能运用更短的治疗时间和更少的加速器跳数（monitor unite,MU）,减少器官运动对靶区剂量的影响。     

Beam orientation optimization in intensity-modulated radiation treatment planning

Beam direction optimization is an important problem in radiation therapy. In intensity modulated radiation therapy (IMRT), the difficulty for computer optimization of the beam directions arises from the fact that they are coupled with the intensity profiles of the incident beams. In order to obtain the optimal incident beam directions using iterative or stochastic methods, the beam profiles ought to be optimized after every change of beam configuration. In this paper we report an effective algorithm to optimize gantry angles for IMRT. In our calculation the gantry angles and the beam profiles (beamlet weights) were treated as two separate groups of variables. The gantry angles were sampled according to a simulated annealing algorithm. For each sampled beam configuration, beam profile calculation was done using a fast filtered backprojection (FBP) method. Simulated annealing was also used for beam profile optimization to examine the performance of the FBP for beam orientation optimization. Relative importance factors were incorporated into the objective function to control the relative importance of the target and the sensitive structures. Minimization of the objective function resulted in the best possible beam orientations and beam profiles judged by the given objective function. The algorithm was applied to several model problems and the results showed that the approach has potential for IMRT applications.     

Determining optimal two-beam axial orientations for heart sparing in left-sided breast cancer patients

BACKGROUND AND PURPOSE: The optimal intensity fluence profile of a beam depends on the profiles of other beams but most optimizations assume fixed beam orientations, a priori. Breast cancer radiotherapy attempts to cover the target and to spare critical structures such as the heart and lungs. The study aims are (1) to determine and document the optimal two-beam orientation that best spares the heart for left-sided breast cancer patients and (2) to investigate the influence of the treatment technique (i.e., conformal versus intensity modulation) on the optimal objective cost function. MATERIAL AND METHODS: Ten left-sided breast cancer patients were planned using a conformal (3DCRT) and a simplified intensity modulated (sIMRT) technique using predefined segments and different two-beam orientations. Optimal segment weights were determined exhaustively for all axial two-beam combinations, in 5 degree increments, by minimizing a quadratic objective cost function. The resulting objective cost function was analyzed with respect to target geometry and treatment technique. RESULTS: The sIMRT plans are generally less sensitive to beam orientation compared to 3DCRT plans. Optimal two-beam orientations for 3DCRT and sIMRT plans exist and they correspond to a hinge angle of approximately 188 degrees and 160 degrees or 210 degrees (the latter is bimodal), respectively. CONCLUSIONS: The optimization software is a useful tool that can test many different beam combinations and estimate their associated objective cost values. Afterwards, the most promising beam orientations could be re-optimized under the TPS to fine-tune and verify the dose distributions. Optimal uniform two-beam orientations for the breast consist of opposing tangential medial and lateral beams. Optimal nonuniform two-beam orientations for left-sided breast cancers are bimodal, containing hinge angles around 160 degrees and 210 degrees. Nonuniform beam techniques are less sensitive to beam orientation compared to uniform beam techniques and result in significantly improved heart sparing but at a cost of slightly compromised planning target volume coverage.     

Automatic beam angle selection in IMRT planning using genetic algorithm

The selection of suitable beam angles in external beam radiotherapy is at present generally based upon the experience of the human planner. The requirement to automatically select beam angles is particularly highlighted in intensity-modulated radiation therapy (IMRT), in which a smaller number of modulated beams is hoped to be used, in comparison with conformal radiotherapy. It has been proved by many researchers that the selection of suitable beam angles is most valuable for a plan with a small number of beams (< or = 5). In this paper an efficient method is presented to investigate how to improve the dose distributions by selecting suitable coplanar beam angles. In our automatic beam angle selection (ABAS) algorithm, the optimal coplanar beam angles correspond to the lowest objective function value of the dose distributions calculated using the intensity-modulated maps of this group of candidate beams. Due to the complexity of the problem and the large search space involved, the selection of beam angles and the optimization of intensity maps are treated as two separate processes and implemented iteratively. A genetic algorithm (GA) incorporated with an immunity operation is used to select suitable beam angles, and a conjugate gradient (CG) method is used to quickly optimize intensity maps for each selected beam combination based on a dose-based objective function. A pencil-beam-based three-dimensional (3D) full scatter convolution (FSC) algorithm is employed for the dose calculation. Two simulated cases with obvious optimal beam angles are used to verify the validity of the presented technique, and a more complicated case simulating a prostate tumour and two clinical cases are employed to test the efficiency of ABAS. The results show that ABAS is valid and efficient and can improve the dose distributions within a clinically acceptable computation time.     

Sensitivity of megavoltage photon beam Monte Carlo simulations to electron beam and other parameters

The BEAM code is used to simulate nine photon beams from three major manufacturers of medical linear accelerators (Varian, Elekta, and Siemens), to derive and evaluate estimates for the parameters of the electron beam incident on the target, and to study the effects of some mechanical parameters like target width, primary collimator opening, flattening filter material and density. The mean energy and the FWHM of the incident electron beam intensity distributions (assumed Gaussian and cylindrically symmetric) are derived by matching calculated percentage depth-dose curves past the depth of maximum dose (within 1% of maximum dose) and off-axis factors (within 2sigma at 1% statistics or less) with measured data from the AAPM RTC TG-46 compilation. The off-axis factors are found to be very sensitive to the mean energy of the electron beam, the FWHM of its intensity distribution, its angle of incidence, the dimensions of the upper opening of the primary collimator, the material of the flattening filter and its density. The off-axis factors are relatively insensitive to the FWHM of the electron beam energy distribution, its divergence and the lateral dimensions of the target. The depth-dose curves are sensitive to the electron beam energy, and to its energy distribution, but they show no sensitivity to the FWHM of the electron beam intensity distribution. The electron beam incident energy can be estimated within 0.2 MeV when matching either the measured off-axis factors or the central-axis depth-dose curves when the calculated uncertainties are about 0.7% at the 1 sigma level. The derived FWHM (+/-0.1 mm) of the electron beam intensity distributions all fall within 1 mm of the manufacturer specifications except in one case where the difference is 1.2 mm.     

Determination of beam intensity in a single step for IMRT inverse planning

In intensity modulated radiotherapy (IMRT), targets are treated by multiple beams at different orientations each with spatially-modulated beam intensities. This approach spreads the normal tissue dose to a greater volume and produces a higher dose conformation to the target. In general, inverse planning is used for IMRT treatment planning. The inverse planning requires iterative calculation of dose distribution in order to optimize the intensity profile for each beam and is very computation intensive. In this paper, we propose a single-step method utilizing a figure of merit (FoM) to estimate the beam intensities for IMRT treatment planning. The FoM of a ray is defined as the ratio between the delivered tumour dose and normal tissue dose and is a good index for the dose efficacy of the ray. To maximize the beam utility, it is natural to irradiate the tumour with intensity of each ray proportional to the value of the FoM. The nonuniform beam intensity profiles are then fixed and the weights of the beam are determined iteratively in order to yield a uniform tumour dose. In this study, beams are employed at equispaced angles around the patient. Each beam with its field size that just covers the tumour is divided into a fixed number of beamlets. The FoM is calculated for each beamlet and this value is assigned to be the beam intensity. Various weighting factors are incorporated in the FoM computation to accommodate different clinical considerations. Two clinical datasets are used to test the feasibility of the algorithm. The resultant dose-volume histograms of this method are presented and compared to that of conformal therapy. Preliminary results indicate that this method reduces the critical organ doses at a small expense of uniformity in tumour dose distribution. This method estimates the beam intensity in one single step and the computation time is extremely fast and can be finished in less than one minute using a regular PC.     

A prototype beam delivery system for the proton medical accelerator at Loma Linda.

A variable energy proton accelerator was commissioned at Fermi National Accelerator Laboratory for use in cancer treatment at the Loma Linda University Medical Center. The advantages of precise dose localization by proton therapy, while sparing nearby healthy tissue, are well documented [R. R. Wilson, Radiology 47, 487 (1946); M. Wagner, Med. Phys. 9, 749 (1982); M. Goitein and F. Chen, Med. Phys. 10, 831 (1983)]. One of the components of the proton therapy facility is a beam delivery system capable of delivering precise dose distributions to the target volume in the patient. To this end, a prototype beam delivery system was tested during the accelerator's commissioning period. The beam delivery system consisted of a beam spreading device to produce a large, uniform field, a range modulator to generate a spread out Bragg peak (SOBP), and various beam detectors to measure intensity, beam centering, and dose distributions. The beam delivery system provided a uniform proton dose distribution in a cylindrical volume of 20-cm-diam area and 9-cm depth. The dose variations throughout the target volume were found to be less than +/- 5%. Modifications in the range modulator should reduce this considerably. The central axis dose rate in the region of the SOBP was found to be 0.4 cGy/spill with an incident beam intensity of 6.7 x 10(9) protons/spill. With an accelerator repetition rate of 30 spills/min and expected intensity of 2.5 x 10(10) protons/spill for patient treatment, this system can provide 50 cGy/min for a 20-cm-diam field and 9-cm range modulation.(ABSTRACT TRUNCATED AT 250 WORDS)     

Leaf-sequencing for intensity-modulated arc therapy using graph algorithms

Intensity-modulated arc therapy (IMAT) is a rotational IMRT technique. It uses a set of overlapping or nonoverlapping arcs to create a prescribed dose distribution. Despite its numerous advantages, IMAT has not gained widespread clinical applications. This is mainly due to the lack of an effective IMAT leaf-sequencing algorithm that can convert the optimized intensity patterns for all beam directions into IMAT treatment arcs. To address this problem, we have developed an IMAT leaf-sequencing algorithm and software using graph algorithms in computer science. The input to our leaf-sequencing software includes (1) a set of (continuous) intensity patterns optimized by a treatment planning system at a sequence of equally spaced beam angles (typically 10 degrees apart), (2) a maximum leaf motion constraint, and (3) the number of desired arcs, k. The output is a set of treatment arcs that best approximates the set of optimized intensity patterns at all beam angles with guaranteed smooth delivery without violating the maximum leaf motion constraint. The new algorithm consists of the following key steps. First, the optimized intensity patterns are segmented into intensity profiles that are aligned with individual MLC leaf pairs. Then each intensity profile is segmented into k MLC leaf openings using a k-link shortest path algorithm. The leaf openings for all beam angles are subsequently connected together to form 1D IMAT arcs under the maximum leaf motion constraint using a shortest path algorithm. Finally, the 1D IMAT arcs are combined to form IMAT treatment arcs of MLC apertures. The performance of the implemented leaf-sequencing software has been tested for four treatment sites (prostate, breast, head and neck, and lung). In all cases, our leaf-sequencing algorithm produces efficient and highly conformal IMAT plans that rival their counterpart, the tomotherapy plans, and significantly improve the IMRT plans. Algorithm execution times ranging from a few seconds to 2 min are observed on a laptop computer equipped with a 2.0 GHz Pentium M processor.     

Optimization of intensity-modulated very high energy (50-250 MeV) electron therapy

This work evaluates the potential of very high energy (50-250 MeV) electron beams for dose conformation and identifies those variables that influence optimized dose distributions for this modality. Intensity-modulated plans for a prostate cancer model were optimized as a function of the importance factors, beam energy and number of energy bins, number of beams, and the beam orientations. A trial-and-error-derived constellation of importance factors for target and sensitive structures to achieve good conformal dose distributions was 500, 50, 10 and I for the target, rectum, bladder and normal tissues respectively. Electron energies greater than 100 MeV were found to be desirable for intensity-modulated very high energy electron therapy (VHEET) of prostate cancer. Plans generated for lower energy beams had relatively poor conformal dose distributions about the target region and delivered high doses to sensitive structures. Fixed angle beam treatments utilizing a large number of fields in the range 9-21 provided acceptable plans. Using more than 21 beams at fixed gantry angles had an insignificant effect on target coverage, but resulted in an increased dose to sensitive structures and an increased normal tissue integral dose. Minor improvements in VHEET plans utilizing a 'small' number (< or =9) of beams may be achieved if, in addition to intensity modulation, energy modulation is implemented using a small number (< or =3) of beam energies separated by 50 to 100 MeV. Rotation therapy provided better target dose homogeneity but unfortunately resulted in increased rectal dose, bladder dose and normal tissue integral dose relative to the 21-field fixed angle treatment plan. Modulation of the beam energy for rotation therapy had no beneficial consequences on the optimized dose distributions. Lastly, selection of beam orientations influenced the optimized treatment plan even when a large number of beams (approximately 15) were employed.     

Beam orientation optimization for intensity modulated radiation therapy using adaptive l(2,1)-minimization

Beam orientation optimization (BOO) is a key component in the process of intensity modulated radiation therapy treatment planning. It determines to what degree one can achieve a good treatment plan in the subsequent plan optimization process. In this paper, we have developed a BOO algorithm via adaptive l(2, 1)-minimization. Specifically, we introduce a sparsity objective function term into our model which contains weighting factors for each beam angle adaptively adjusted during the optimization process. Such an objective function favors a small number of beam angles. By optimizing a total objective function consisting of a dosimetric term and the sparsity term, we are able to identify unimportant beam angles and gradually remove them without largely sacrificing the dosimetric objective. In one typical prostate case, the convergence property of our algorithm, as well as how beam angles are selected during the optimization process, is demonstrated. Fluence map optimization (FMO) is then performed based on the optimized beam angles. The resulting plan quality is presented and is found to be better than that of equiangular beam orientations. We have further systematically validated our algorithm in the contexts of 5-9 coplanar beams for five prostate cases and one head and neck case. For each case, the final FMO objective function value is used to compare the optimized beam orientations with the equiangular ones. It is found that, in the majority of cases tested, our BOO algorithm leads to beam configurations which attain lower FMO objective function values than those of corresponding equiangular cases, indicating the effectiveness of our BOO algorithm. Superior plan qualities are also demonstrated by comparing DVH curves between BOO plans and equiangular plans.     

A graph-searching method for MLC leaf sequencing under constraints

A new leaf-sequencing algorithm for step-and-shoot IMRT that is based on a graph-searching technique is described. An iterative process guided by a quantitative measure for the complexity of the initial or residual intensity pattern is used to identify the field segments shaped by a multileaf collimator (MLC). Given a user selected number of intensity levels, the algorithm searches deliverable segment candidates considering all intensity levels and two collimator positions separated by 90 degrees. The candidates for each intensity level are obtained as the least number of segments to cover the areas with equal or higher intensity. The shape of a deliverable segment is adjusted by leaving out certain beam elements for later delivery if this results in a simpler residual intensity pattern and the segment is still deliverable. For a MLC design that does not allow leaf interdigitation, it is initially assumed that a single segment cannot cover two disjoined areas. Among all candidates the segment with the greatest reduction of the complexity of the residual intensity distribution is chosen for the current step of iteration. The iterative process generates a set of deliverable segments of simply connected areas. These segments are combined later under specific MLC constraints. Different orders of segment combination are considered for minimizing the beam-on time. The final segments are sequenced to minimize the leaf travel. This algorithm has been tested using randomly generated intensity distributions and clinical cases for the Varian, Siemens, and Elekta MLC systems. The results show that as the number of intensity levels is increased, the numbers of segments and MUs increase only modestly. Using two collimator angles results in decreases in the required number of segments and the number of monitor units that can be as much as 20%.