A new genetic algorithm technique in optimization of permanent 125I prostate implants

Real time optimized treatment planning at the time of the implant is desirable for ultrasound-guided transperineal 125I permanent prostate implants. Currently available optimization algorithms are too slow to be used in the operating room. The goal of this work is to develop a robust optimization algorithm, which is suitable for such application. Three different genetic algorithms (sGA, sureGA and securGA) were developed and compared in terms of the number of function evaluations and the corresponding fitness. The optimized dose distribution was achieved by searching the best seed distribution through the minimization of a cost function. The cost function included constraints on the periphery dose of the planned target volume, the dose uniformity within the target volume, and the dose to the critical structure. Adjustment between the peripheral dose, the dose uniformity and critical structure dose can be achieved by varying the weighting factors in the cost function. All plans were evaluated in terms of the dose nonuniformity ratio, the conformation number and the dose volume histograms. Among these three GA algorithms, the securGA provided the best performance. Within 2500 function evaluations, the near optimum results were obtained. For a large target volume (5 cm x 4 cm x 4.5 cm) including urethra with 20 needles, the computer time needed for the optimization was less than 5 min on a HP735 workstation. The results showed that once the best set of parameters was found, they were applicable for all sizes of prostate volume. For a fixed needle geometry, the optimized plan showed much better dose distribution than that of nonoptimized plan. If the critical structure was considered in the optimization, the dose to the critical structure could be minimized. In the cases of irregular and skewed needle geometry, the optimized treatment plans were almost as good as ideal needle geometry. It is concluded that this new genetic algorithm (securGA) allows for an efficient and rapid optimization of dose distribution, which is suitable for real time treatment planning optimization for ultrasound-guided prostate implant.     

The simple excision

A method for the fully computerized determination and optimization of positions of target points and collimator sizes in convergent beam irradiation is presented. In conventional interactive trial and error methods, which are very time consuming, the treatment parameters are chosen according to the operator's experience and improved successively. This time is reduced significantly by the use of a computerized procedure. After the definition of target volume and organs at risk in the CT or MR scans, an initial configuration is created automatically. In the next step the target point positions and collimator diameters are optimized by the program. The aim of the optimization is to find a configuration for which a prescribed dose at the target surface is approximated as close as possible. At the same time dose peaks inside the target volume are minimized and organs at risk and tissue surrounding the target are spared. To enhance the speed of the optimization a fast method for approximate dose calculation in convergent beam irradiation is used. A possible application of the method for calculating the leaf positions when irradiating with a micromultileaf collimator is briefly discussed. The success of the procedure has been demonstrated for several clinical cases with up to six target points.     

Paleolithic and Neolithic lineages in the European mitochondrial gene pool

PURPOSE: This article presents a new optimization method for stereotactic radiosurgery treatment planning for gamma unit treatment system. METHODS AND MATERIALS: The gamma unit has been utilized in stereotactic radiosurgery for about 30 years, but the usual procedure for a physician-physicist team to design a treatment plan is a trial-and-error approach. Isodose curves are viewed on two-dimensional computed tomography (CT) or magnetic resonance (MR) image planes, which is not only time consuming but also seldom achieves the optimal treatment plan, especially when the isocenter weights are regarded. We developed a treatment-planning system on a computer workstation in which Powell's optimization method is realized. The optimization process starts with the initial parameters (the number of isocenters as well as corresponding 3D isocenters' coordinates, collimator sizes, and weight factors) roughly determined by the physician-physicist team. The objective function can be changed to consider protection of sensitive tissues. RESULTS: We use the plan parameters given by a well-trained physician-physicist team, or ones that the author give roughly as the initial parameters for the optimization procedure. Dosimetric results of optimization show a better high dose-volume conformation to the target volume compared to the doctor's plan. CONCLUSION: This method converges quickly and is not sensitive to the initial parameters. It achieves an excellent conformation of the estimated isodose curves with the contours of the target volume. If the initial parameters are varied, there will be a little difference in parameters' configuration, but the dosimetric results proved almost to be the same.     

蒙古铁矿块矿直接入炉基础冶金性能

摘要：高炉装料制度是复杂高炉炼铁中调节炉况运行状态的重要上部调剂手段,炉料在布料矩阵操作参数下在炉喉处所形成的空间分布是影响炉内煤气流分布和高炉炉况波动的重要因素之一。合理的调控与优化高炉装料所产生的料面形状,给出布料矩阵优化计算的理论依据,是保证高炉稳定顺行,提高资源利用率和减少污染物排放的有效途径。结合无钟炉顶的设备结构与布料工艺,针对期望料层厚度分布研究布料矩阵的优化计算方法,进行完善与改进;同时以期望料面输出形状为设定目标,建立了期望料面输出形状优化模型并通过遗传算法实现对布料矩阵的优化计算。最后,通过工业过程的实测数据对PSO优化方法和遗传算法优化方法进行对比验证,结果表明,使用基于遗传算法的优化模型能够有效地制定布料矩阵,符合期望目标。     

基于遗传算法的高炉布料矩阵的优化计算

摘要：高炉装料制度是复杂高炉炼铁中调节炉况运行状态的重要上部调剂手段,炉料在布料矩阵操作参数下在炉喉处所形成的空间分布是影响炉内煤气流分布和高炉炉况波动的重要因素之一。合理的调控与优化高炉装料所产生的料面形状,给出布料矩阵优化计算的理论依据,是保证高炉稳定顺行,提高资源利用率和减少污染物排放的有效途径。结合无钟炉顶的设备结构与布料工艺,针对期望料层厚度分布研究布料矩阵的优化计算方法,进行完善与改进;同时以期望料面输出形状为设定目标,建立了期望料面输出形状优化模型并通过遗传算法实现对布料矩阵的优化计算。最后,通过工业过程的实测数据对PSO优化方法和遗传算法优化方法进行对比验证,结果表明,使用基于遗传算法的优化模型能够有效地制定布料矩阵,符合期望目标。     

An efficient method for small field treatment dose calculation for stereotactic radiosurgery using a LINAC

The normal procedure for a physician-physicist team designing a treatment plan for multiarc stereotactic radiosurgery is the trial-and-error approach of changing the collimator size and the location of the isocenter of radiation and viewing the isodose curves on two-dimensional computed tomography (CT) or magnetic resonance imaging (MRI) image planes. Automatic optimization procedures have also been used to optimize beam weight or beam size. However, either process is very time consuming. To improve the speed of the dose calculation, a random sampling method has been proposed. Unfortunately, the sampled values of an objective function are different from one sample to another. Such a sampling method cannot be used in automatic optimization because the next move in an optimization process is based on the current and past objective function values. To this end, an adaptive method based on the size of the collimators is proposed and used to determine a small volume in the shape of a hollow sphere for which the dose is calculated. With an appropriate choice of an adaptive hollow sphere, the objective function calculated based on such a hollow sphere is the same as that calculated with the traditional three-dimensional (3-D) cube matrix. However, with the new adaptive method, the speed of calculating a dose can be improved by a factor of 4 to a factor of 100. Because of the improvement in the speed of calculating a treatment dose, the new adaptive hollow sphere method for calculating a treatment dose can be used routinely in designing a treatment plan.     

Failure in radiosurgery treatment of cerebral arteriovenous malformations

OBJECTIVE: The aim of this study was to retrospectively analyze the reasons for the failure of radiosurgical treatment of cerebral arteriovenous malformations (AVMs). METHODS: Seventeen cases of noncured AVMs were reviewed 3 years after radiosurgical treatment. Follow-up ranged from 33 to 54 months (mean, 44.3 mo). Lesion dimensions varied from 9 to 55 mm (mean, 29.2 mm). The lesions were located in critical or near-critical brain regions. Angiography was performed under Talairach's stereotactic conditions. Two large AVMs bled 36 and 39 months after receiving irradiation, respectively. These two AVMs had been incompletely irradiated. RESULTS: Retrospectively, in four cases (23.5%) we observed errors in determining AVM target shape and size because of inaccurate definition of the nidus and/or because of stereoangiographic incompleteness (absence of external carotid artery injections). In five large and/or irregularly shaped AVMs (29.4%), a strategy of partial volume irradiation had been used. In one patient (5.8%), we observed the recanalization of previously embolized AVMs. In another case (5.8%), the target had been partially missed. The AVMs in one case (5.8%) had been treated with an ineffective peripheral dose. In one (5.8%), the failure occurred because of the lesion angio-architecture. In four cases (23.5%), no evident reasons for failure were determined. CONCLUSION: The results of this study suggest the necessity of complete irradiation of the nidus. The strategy of partial volume irradiation might be avoided, even if it necessitates lowering the doses to treat large AVMs. Accuracy in the target determination is required, and complete stereoangiography is necessary.     

Optimization of permanent 125I prostate implants using fast simulated annealing

PURPOSE: Treatment planning of ultrasound-guided transperineal 125I permanent prostatic implants is a time-consuming task, due to the large number of seeds used and the very large number of possible source arrangements within the target volume. The goal of this work is to develop an algorithm based on fast simulated annealing allowing consistent and automatic dose distribution optimization in permanent 125I prostatic implants. METHODS AND MATERIALS: Fast simulated annealing is used to optimize the dose distribution by finding the best seed distribution through the minimization of a cost function. The cost function includes constraints on the dose at the periphery of the planned target volume and on the dose uniformity within this volume. Adjustment between peripheral dose and the dose uniformity can be achieved by varying the weight factor in the cost function. RESULTS: Fast simulated annealing algorithm finds very good seed distributions within 20,000 iterations. The computer time needed for the optimization of a typical permanent implant involving 60 seeds and 14 needles is approximately 15 min. An additional 5 min are necessary for isodose distribution computations and miscellaneous outputs. CONCLUSION: The use of fast simulated annealing allows for an efficient and rapid optimization of dose distribution. This algorithm is now routinely used at our institution in the clinical planning of 125I permanent transperineal prostate implants for early stage prostatic carcinoma.     

基于神经网络和模拟退火算法的配煤智能优化方法

炼焦配煤过程是存在诸多不确定性的复杂工业过程,传统控制方法难以实施控制。在炼焦配煤中,配煤比是影响焦炭质量的主要因素。本文通过建立智能优化系统,提出一种确定配煤比的优化策略。首先根据焦化反应机理,分别建立配合煤和焦炭质量预测模型,然后通过配比智能优化模型,运用模拟退火算法对配煤比进行优化计算。实际效果证明了这种控制策略的有效性。     

基于UWB的地下定位算法和拓扑优化

地下定位面对环境恶劣、干扰、多径等影响,常规算法难以获得高精度的定位结果,同时井下环境多为狭长的巷道,不利于布置定位所需的锚节点,而井下锚节点的布置通常对定位结果有较大影响,因而使用普通的定位方法不足以满足智能采矿所需的高精度定位需求.本文对传统的三边定位算法进行分析,总结了传统三边定位结果产生误差的原因,并提出了改进的算法,通过仿真实验验证了改进算法的有效性.同时通过理论分析误差带,使用最大绝对定位误差用于仿真分析拓扑结构对定位结果精度的影响,提出了对拓扑结构的优化原则,能够根据环境特点以实现定位区域内平均最大绝对定位误差最小为原则得出最优拓扑结构.文中设置了仿真实验和实地实验对改进的算法和拓扑结构优化方法进行了验证,实验结果中,改进的算法能够在相同拓扑结构下减小15%~43%的误差,而在相同算法下优化的拓扑结构能够减小17%~65%,二者结合能够减小误差达74%.结果表明,在相同的定位条件下,改进的定位算法能够明显提高定位结果的精度,同时定位结果与拓扑结构之间也有着密切的联系,根据实际环境灵活布置拓扑结构能够使定位结果的精度进一步提高,将改进的算法与拓扑结构优化方法结合可以实现更高的定位精度.      

宫颈癌术后骨髓保护调强放疗研究

Objective: The aim of this study was to compare bone marrow-sparing intensity-modulated radiotherapy (IMRT)with IMRT without entering pelvic bone marrow as a planning constraint in the treatment of cervical cancer after hysterectomy. Methods: For a cohort of 10 patients, bone marrow-sparing IMRT and routine IMRT planning were designed. Theproscribed dose was 45 Gy/1.8 Gy/25f, 95% of the planning target volume received this dose. Doses were computed with a commercially available treatment planning system (TPS) using convolution/superimposition (CS) algorithm. Plans were compared according to dose-volume histogram (DVH) analysis in terms of planning target volume (PTV) homogeneity and conformity indices (HI and CI) as well as organs at risk (OARs) dose and volume parameters. Results: Bone marrow-sparing IMRT had an vantages over routine IMRT in terms of CI, but inferior to the latter for HI. Compared with routine IMRT, V5,V10, V20, V30, V40 of pelvic bone marrow of bone marrow-sparing IMRT reduced by 1.81%, 8.61%, 31.81%, 29.50%, 28.29%,respectively. No statistically significant differences were observed between bone marrow-sparing IMRT and routine IMRT in terms of small bowel, bladder and rectum. Conclusion: For patients with cervical cancer after hysterectomy, bone marrowsparing IMRT reduced the pelvic bone marrow volume irradiated at all dose levels and might be conducive to preventing the occurrence of acute bone marrow toxicity.     

Protein folding: optimized sequences obtained by simulated breeding in a minimalist model

For a minimalist model of protein folding, which we introduced recently, we investigate various methods to obtain folding sequences. A detailed study of random sequences shows that, for this model, such sequences usually do not fold to their ground states during simulations. Straight-forward techniques for the construction of folding sequences, based solely on the target structure, fail. We describe in detail an optimization algorithm, based on genetic algorithms, for the "simulated breeding" of folding sequences in this model. We find that, for any target structure studied, there is not only a single folding sequence but a patch of sequences in sequence space that fold to this structure. In addition, we show that, much as in real proteins, nonhomologous sequences may fold to the same target structure.     

Application of Improved PSO Algorithm in Hydraulic Pressing System Identification

 In view of characteristics of particle swarm optimization (PSO) algorithm of fast convergence but easily falling into local optimum value, a novel improved particle swarm optimization algorithm is put forward, and it is applicable to identify parameters of hydraulic pressure system model in strip rolling process. In order to maintain population diversity and enhance global optimization capability, the algorithm is firstly improved by means of decreasing its inertia weight linearly from the maximum to the minimum and then combined with chaotic characteristics of ergodicity, randomness and sensitivity to initial value. When the improved algorithm is used to identify parameters of hydraulic pressure system, the comparison of simulation curves and measured curves indicates that the identification results are reliable and close to actual situation. A new method was provided for hydraulic AGC system model identification.     

Conformal treatment planning for interstitial brachytherapy

PURPOSE: Quality of a brachytherapy application depends on the choice of the target volume, on the dose distribution homogeneity and radiation injury on critical tissue, which should be postulated by advanced brachytherapy treatment planning systems. MATERIAL AND METHODS: Basic imaging method for conformal treatment planning is the cross-sectional imaging. The clinical applicability of a new type 3D planning system using CT and/or MRT-simulation or US-simulation for planning purposes was studied. The planning system developed at Kiel University differs from usual brachytherapy planning systems because of the obligatory use of cross-sectional imaging as basic imaging method for reconstruction of structures of interest. Dose distribution and normal anatomy can be visualized on each CT/MRT/US slice as well as coronal, sagittal, axial and free chosen reconstruction (3D), as well as dose-volume histogram curves and special colour-coded visualization of dose homogeneity in the target can be analyzed. RESULTS: Because of the experience in the clinical routine, as well as on the base of 30 simultaneous planning procedures on both 2D (semi-3D) and 3D planning systems we observed similar time consumption. Advantages of 3D planning were the better interpretation of target delineation, delineation of critical structures as well as dose distribution, causing more accurate volume optimisation of dose distribution. CONCLUSION: Conformal brachytherapy treatment planning for interstitial brachytherapy means significant advantages for the clinical routine compared to 2D or semi-3D methods.     

基于遗传算法的无钟高炉布料工艺优化

 面对现代炼铁生产节能减排的迫切需求,优化无钟高炉布料是保证高炉稳产顺行、提高资源利用率和减少污染排放的有效途径。结合无钟炉顶的设备结构与布料工艺特点,提出了使用料面形状误差评价布料操作的准确性,设计了针对多环布料操作优化的遗传算法,并应用该优化算法分析了溜槽倾角档位数量以及布料总周数等参数对无钟布料工艺的影响。结果表明：基于遗传算法的组合优化模型能够有效制定布料矩阵,溜槽倾角档位数量和布料总周数的增多以及单次布料体积的减少有利于实现高炉精准布料,溜槽倾角档位数量无穷大时与螺旋布料的料面构造能力相当,布料总周数和单次布料体积受设备和工艺多方面限制,需合理设定。     

基于双维度搜索的地下自主铲运机最优转弯轨迹规划

提出了一种基于双维度搜索的实时轨迹规划方法,用来解决自主地下铲运机转弯轨迹规划问题。该方法是一种结合采样思想和最优化算法的复合轨迹规划方法,包含三个主要步骤:基于双维度搜索策略的优化模型参数生成,基于二次规划的轨迹计算,以及基于约束检查的最优轨迹确定。该方法新颖之处在于提出的基于转弯区域行驶时间和里程的双维度搜索策略,以及基于平稳目标的轨迹最优化模型,可根据弯道区域入口速度和位置,快速生成纵横向都有最优性保证的最优轨迹。该方法结构简单、易于实施,可通过关键参数的调整满足控制器对轨迹生成速度的实时性要求。基于该轨迹规划方法的特点,使其不仅适用于实时轨迹规划,还可为未来智慧矿山的智能管控与优化调度提供底层约束。多组算例验证了该方法的有效性和优越性。      

Computer-assisted irradiation planning by means of computed tomography (author's transl)

Operation of the computer tomograph combined with a computer for irradiation planning leads to an optimization of radiotherapeutic efforts. By means of a careful carrying-over of computed tomographic data into the computing system the demanded homogeneous dose distribution with a deviation rate of +/- 10% may be accomplished to a large extent for any given target volume. At the same time this method achieves an optimal sparing of the sound or else critical organs. An evaluation unit independent of the diagnostics ought to be available, as this renders possible the adaptation of the CT cross-sections of interest under individual aspects.     

An adaptive control algorithm for optimization of intensity modulated radiotherapy considering uncertainties in beam profiles, patient set-up and internal organ motion

A new general beam optimization algorithm for inverse treatment planning is presented. It utilizes a new formulation of the probability to achieve complication-free tumour control. The new formulation explicitly describes the dependence of the treatment outcome on the incident fluence distribution, the patient geometry, the radiobiological properties of the patient and the fractionation schedule. In order to account for both measured and non-measured positioning uncertainties, the algorithm is based on a combination of dynamic and stochastic optimization techniques. Because of the difficulty in measuring all aspects of the intra- and interfractional variations in the patient geometry, such as internal organ displacements and deformations, these uncertainties are primarily accounted for in the treatment planning process by intensity modulation using stochastic optimization. The information about the deviations from the nominal fluence profiles and the nominal position of the patient relative to the beam that is obtained by portal imaging during treatment delivery, is used in a feedback loop to automatically adjust the profiles and the location of the patient for all subsequent treatments. Based on the treatment delivered in previous fractions, the algorithm furnishes optimal corrections for the remaining dose delivery both with regard to the fluence profile and its position relative to the patient. By dynamically refining the beam configuration from fraction to fraction, the algorithm generates an optimal sequence of treatments that very effectively reduces the influence of systematic and random set-up uncertainties to minimize and almost eliminate their overall effect on the treatment. Computer simulations have shown that the present algorithm leads to a significant increase in the probability of uncomplicated tumour control compared with the simple classical approach of adding fixed set-up margins to the internal target volume.     

Automated localization of the prostate at the time of treatment using implanted radiopaque markers: technical feasibility

PURPOSE: Prostate movement is a major consideration in the formation of target volumes for conformal radiation therapy of prostate cancer. The goal of this study was to determine the technical feasibility of using implanted radiopaque markers and digital imaging to localize the prostate at the time of treatment, thus allowing for reduction of the margin required for uncertainty in target position. METHODS AND MATERIALS: Radiopaque markers implanted around the prostate prior to treatment are visible on electronic radiographs generated with a portal imager or diagnostic imaging device. The locations of the images of these markers on the digital radiographs were automatically determined by a template-matching algorithm. The coordinates of the markers were found by projecting rays through the marker locations on orthogonal radiographs using a three-dimensional (3D) point-matching algorithm. Prostate and/or patient movement was inferred from the marker displacements. Images generated from known movements of a phantom with implanted markers were tested with this algorithm. Locations of markers from daily images of patients with implanted markers were determined by both manual and automatic techniques to determine the efficacy of automated localization on typical clinical images. RESULTS: Prostate movements can be automatically detected in a phantom using low-energy photons within 30 s after image acquisition and with a precision of better than 1 mm in translation and 1 degree in rotation (indistinguishable from the uncertainty in measuring precision). CONCLUSION: The studies show that on-line repositioning of the patient based on localization of the markers at the time of treatment is feasible, and may reduce the uncertainty in prostate location when combined with practical on-line repositioning techniques.     

MR image-guided portal verification for brain treatment field

PURPOSE: To investigate a method for the generation of digitally reconstructed radiographs directly from MR images (DRR-MRI) to guide a computerized portal verification procedure. METHODS AND MATERIALS: Several major steps were developed to perform an MR image-guided portal verification procedure. Initially, a wavelet-based multiresolution adaptive thresholding method was used to segment the skin slice-by-slice in MR brain axial images. Some selected anatomical structures, such as target volume and critical organs, were then manually identified and were reassigned to relatively higher intensities. Interslice information was interpolated with a directional method to achieve comparable display resolution in three dimensions. Next, a ray-tracing method was used to generate a DRR-MRI image at the planned treatment position, and the ray tracing was simply performed on summation of voxels along the ray. The skin and its relative positions were also projected to the DRR-MRI and were used to guide the search of similar features in the portal image. A Canny edge detector was used to enhance the brain contour in both portal and simulation images. The skin in the brain portal image was then extracted using a knowledge-based searching technique. Finally, a Chamfer matching technique was used to correlate features between DRR-MRI and portal image. RESULTS: The MR image-guided portal verification method was evaluated using a brain phantom case and a clinical patient case. Both DRR-CT and DRR-MRI were generated using CT and MR phantom images with the same beam orientation and then compared. The matching result indicated that the maximum deviation of internal structures was less than 1 mm. The segmented results for brain MR slice images indicated that a wavelet-based image segmentation technique provided a reasonable estimation for the brain skin. For the clinical patient case with a given portal field, the MR image-guided verification method provided an excellent match between features in both DRR-MRI and portal image. Moreover, target volume could be accurately visualized in the DRR-MRI and mapped over to the corresponding portal image for treatment verification. The accuracy of DRR-MRI was also examined by comparing it to the corresponding simulation image. The matching results indicated that the maximum deviation of anatomical features was less than 2.5 mm. CONCLUSION: A method for MR image-guided portal verification of brain treatment field was developed. Although the radiographic appearance in the DRR-MRI is different from that in the portal image, DRR-MRI provides essential anatomical features (landmarks and target volume) as well as their relative locations to be used as references for computerized portal verification.