Novel Monte Carlo dose calculation algorithm for robotic radiosurgery with multi leaf collimator: Dosimetric evaluation

PurposeAt introduction in 2014, dose calculation for the first MLC on a robotic SRS/SBRT platform was limited to a correction-based Finite-Size Pencil Beam (FSPB) algorithm. We report on the dosimetric accuracy of a novel Monte Carlo (MC) dose calculation algorithm for this MLC, included in the Precision™ treatment planning system.MethodsA phantom was built of one slab (5.0 cm) of lung-equivalent material (0.09…0.29 g/cc) enclosed by 3.5 cm (above) and 5 cm (below) slabs of solid water (1.045 g/cc). This was irradiated using rectangular (15.4 × 15.4 mm² to 53.8 × 53.7 mm²) and two irregular MLC-fields. Radiochromic film (EBT3) was positioned perpendicular to the slabs and parallel to the beam. Calculated dose distributions were compared to film measurements using line scans and 2D gamma analysis.ResultsMeasured and MC calculated percent depth dose curves showed a characteristic dose drop within the low-density region, which was not correctly reproduced by FSPB. Superior average gamma pass rates (2%/1 mm) were found for MC (91.2 ± 1.5%) compared to FSPB (55.4 ± 2.7%). However, MC calculations exhibited localized anomalies at mass density transitions around 0.15 g/cc, which were traced to a simplification in electron transport. Absence of these anomalies was confirmed in a modified build of the MC engine, which increased gamma pass rates to 96.6 ± 1.2%.ConclusionsThe novel MC algorithm greatly improves dosimetric accuracy in heterogeneous tissue, potentially expanding the clinical use of robotic radiosurgery with MLC. In-depth, independent validation is paramount to identify and reduce the residual uncertainties in any software solution.     

Does biocatalysis involve inhomogeneous kinetics?

Biocatalytic reactions can occur according to two very different mechanisms: homogeneous, which is described by standard transition state theory (TST) and its modifications, and inhomogeneous (polychromatic), which is characteristic for some of the charge-transfer reactions in liquids and amorphous solids. While most data published on enzyme reactions are interpreted on the basis of homogeneous kinetics, the important recent findings suggest the involvement of inhomogeneous kinetics mechanism.     

A quasispecies on a moving oasis

A population evolving in an inhomogeneous environment will adapt differently to different areas. We study the conditions under which such a population can maintain adaptations to a particular region when that region is not stationary, but can move. In particular, we consider a haploid population living near a moving favorable patch ("oasis") in the middle of a large "desert." At one genetic locus, individuals may have one of a few gene sequences that convey an advantage while in the oasis at the cost of a disadvantage in the desert. The distribution of genetic states in the population, possibly localized in genome space around the oasis-adapted genotypes, is known as a quasispecies. We find that the ratio of oasis-adapted individuals to desert-adapted ones exhibits sharp transitions at particular oasis velocities. We calculate an extinction velocity, and a switching velocity above which the dominance switches from the oasis-adapted genotype to the desert-adapted one. This switching velocity is analogous to the quasispecies mutational error threshold. Above this velocity, the population cannot maintain adaptations to the properties of the oasis.     

人体躯干模型中肺的存在对体表电位分布的影响

在所建三维人体躯干模型的基础上,给出了如何应用边界元方法对非均匀人体场域进行求解。在设定心外膜电位分别呈现为单偶极子和双偶极子时,求出相应非均匀场域中的体表电位分布,并将它们与相同情况下均匀场域的体表电位分布进行分析比较。结果表明：躯干模型中肺的存在虽然对体表电位中极值的大小和位置没有太大影响,但却较大程序地改变了整个体表电位的分布状况,具体地说,就是由于肺的存在使得体表电位值较均匀时的相对误差高     

Variance estimation for statistics computed from single recurrent event processes

This article is concerned with variance estimation for statistics that are computed from single recurrent event processes. Such statistics are important in diagnosis for each individual recurrent event process. The proposed method only assumes a semiparametric form for the first-order structure of the processes but not for the second-order (i.e., dependence) structure. The new variance estimator is shown to be consistent for the target parameter under very mild conditions. The estimator can be used in many applications in semiparametric rate regression analysis of recurrent event data such as outlier detection, residual diagnosis, as well as robust regression. A simulation study and application to two real data examples are used to demonstrate the use of the proposed method.     

Spatial distribution of active muscle fibre characteristics in the upper trapezius muscle and its dependency on contraction level and duration

The aim of this study was to provide direct in vivo information of the physiological and structural characteristics of active muscle fibres from a large part of the upper trapezius muscle. Two-dimensional (2-D) multi-channel surface electromyography recordings were used, with 13 × 10 electrodes covering 6 × 4.5 cm of the skin’s surface. A previously developed method was applied to detect individual propagating motor unit action potentials and to estimate their corresponding muscle fibre conduction velocity (MFCV) and muscle fibre orientation (MFO). Using these estimates, spatial distributions of MFCV and MFO were examined for five male subjects performing isometric shoulder elevation at different force levels. The main results were: (1) the general relationship between MFCV and force generation was non-systematic, with a positive relationship at the inferior part of the muscle, (2) the spatial distribution of MFCV at different force levels and fatigue was inhomogeneous and (3) the MFO was slightly different (6°) of the muscle fibres with origin superior compared to inferior to the C7 vertebra. These findings provide new information of the MFO of contracting muscle fibres and knowledge of the physiological characteristics of a large part of the upper trapezius muscle that previously was based on observations from human cadavers only.     

Bayesian Inference for a Random Tessellation Process

This article describes an inhomogeneous Poisson point process in the plane with an intensity function based on a Dirichlet tessellation process and a method for using observations on the point process to make fully Bayesian inferences about the underlying tessellation. The method is implemented using a Markov chain Monte Carlo approach. An application to modeling the territories of clans of badgers, Meles meles, is described.     

Determining the location of a deceased mother tree and estimating forest regeneration variables by use of microsatellites and spatial genetic models

In this paper we first mathematically formulate spatial genetic models that rely on dispersal kernels, using the genetic inhomogeneous Poisson process. On the basis of mapped and genotyped data pertaining to adult and juvenile trees we are able to estimate three fundamental variables of population dynamics: individual female reproductive success, seed dispersal, and pollen flow. The model was applied to a secondary Fagus crenata stand in northern Japan, regenerated after shelterwood harvesting. Highly polymorphic microsatellite data revealed that most of the juveniles around one adult tree were not that tree’s progeny and that some minor alleles were clustered there. These data suggested that another mother tree had formerly been present in the vicinity, produced offspring there and died. Inferring its genotype and location, we applied the genetic inhomogeneous Poisson process. Results confirmed that we would have wrongly assessed the regeneration if we had been unaware of the existence of the dead mother. The average distances for seed dispersal and pollen flow were 18 and 193 m, respectively. The contribution of outside mothers, simultaneously assessed using the dispersal variables in the models, ranged from 10 to 50% depending on their positions relative to preserved adults. Individual female reproductive success varied as much as fiftyfold among the eight preserved adults. Our comprehensive approach, utilizing currently available genetic information, mathematical models, and previous forestry records, helped elucidation of the past forest-regeneration processes.     

Inference for clustered inhomogeneous spatial point processes

Summary .  We propose a method to test for significant differences in the levels of clustering between two spatial point processes (cases and controls) while taking into account differences in their first-order intensities. The key advance on earlier methods is that the controls are not assumed to be a Poisson process. Inference and diagnostics are based around the inhomogeneous K -function with confidence envelopes obtained from either resampling events in a nonparametric bootstrap approach, or simulating new events as in a parametric bootstrap. Methods developed are demonstrated using the locations of adult and juvenile trees in a tropical forest. A simulation study briefly examines the accuracy and power of the inferential procedures.     

Estimating functions for inhomogeneous spatial point processes with incomplete covariate data

The R package spatstat provides a very flexible and useful frameworkfor analysing spatial point patterns. A fundamental featureis a procedure for fitting spatial point process models dependingon covariates. However, in practice one often faces incompleteobservation of the covariates and this leads to parameter estimationerror which is difficult to quantify. In this paper, we introducea Monte Carlo version of the estimating function used in spatstatfor fitting inhomogeneous Poisson processes and certain inhomogeneouscluster processes. For this modified estimating function, itis feasible to obtain the asymptotic distribution of the parameterestimators in the case of incomplete covariate information.This allows a study of the loss of efficiency due to the missingcovariate data.