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Patient-oriented simulation based on Monte Carlo algorithm by using MRI data.

ABSTRACT: BACKGROUND: Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with in vivo MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement with Monte Carlo simulation. METHODS: In this study, an individualized brain is modeled based on in vivo MRI 3D image as five layers structure. The behavior of photon migration was studied for this individualized brain detections based on three-dimensional time-resolved Monte Carlo algorithm. During the Monte Carlo iteration, all photon paths were traced with various source-detector separations for characterization of brain structure to provide helpful information for individualized design of NIRS system. RESULTS: Our results indicate that the patient-oriented simulation can provide significant characteristics on the optimal choice of source-detector separation within 3.3 cm of individualized design in this case. Significant distortions were observed around the cerebral cortex folding. The spatial sensitivity profile penetrated deeper to the brain in the case of expanded CSF. This finding suggests that the optical method may provide not only functional signal from brain activation but also structural information of brain atrophy with the expanded CSF layer. The proposed modeling method also provides multi-wavelength for NIRS simulation to approach the practical NIRS measurement. CONCLUSIONS: In this study, the three-dimensional time-resolved brain modeling method approaches the realistic human brain that provides useful information for NIRS systematic design and calibration for individualized case with prior MRI data.

SUBMITTER: Chuang CC

PROVIDER: S-EPMC3355000 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Patient-oriented simulation based on Monte Carlo algorithm by using MRI data.

Chuang Ching-Cheng CC Lee Yu-Tzu YT Chen Chung-Ming CM Hsieh Yao-Sheng YS Liu Tsan-Chi TC Sun Chia-Wei CW

Biomedical engineering online 20120417

<h4>Background</h4>Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with in vivo MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement wit ...[more]

PMID: 22510474

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Project description:BackgroundPlotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies.ResultsAn estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake.ConclusionPlotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

Project description:ObjectiveTo estimate the association between centre volume and patient outcomes in peritoneal dialysis, explore robustness to residual confounding and predict the impact of policies to increase centre volumes.DesignRegistry-based cohort study with probabilistic sensitivity analysis and Monte Carlo simulation of (hypothetical) intervention effects.Setting112 secondary-care centres in France.Participants9602 adult patients initiating peritoneal dialysis.Main outcome measuresTechnique failure (ie, permanent transfer to haemodialysis), renal transplantation and death while on peritoneal dialysis within 5 years of initiating treatment. Associations with underlying risk measured by cause-specific HRs (cs-HRs) and with cumulative incidence by subdistribution HRs (sd-HRs). Intervention effects measured by predicted mean change in cumulative incidences.ResultsHigher volume centres had more patients with diabetes and were more frequently academic centres or associative groupings of private physicians. Patients in higher volume centres had a reduced risk of technique failure (>60 patients vs 0-10 patients: adjusted cs-HR 0.46; 95% CI 0.43 to 0.69), with no changed risk of death or transplantation. Sensitivity analyses mitigated the cs-HRs without changing the findings. In higher volume centres, the cumulative incidence was reduced for technique failure (>60 patients vs 0-10 patients: adjusted sd-HR 0.49; 95% CI 0.29 to 0.85) but was increased for transplantation and death (>60 patients vs 0-10 patients: transplantation-adjusted sd-HR 1.53; 95% CI 1.04 to 2.24; death-adjusted sd-HR 1.28; 95% CI 1.00 to 1.63). The predicted reduction in cumulative incidence of technique failure was largest under a scenario of shifting all patients to the two highest volume centre groups (0.091 reduction) but lower for three more realistic interventions (around 0.06 reduction).ConclusionsPatients initiating peritoneal dialysis in high-volume centres had a considerably reduced risk of technique failure but simulations of interventions to increase exposure to high-volume centres yielded only modest improvements.

Project description:A recently introduced brachytherapy system for partial breast irradiation, MammoSite, consists of a balloon applicator filled with contrast solution and a catheter for insertion of an 192Ir high-dose-rate (HDR) source. In using this system, the treatment dose is typically prescribed to be delivered 1 cm from the balloon's surface. Most treatment-planning systems currently in use for brachytherapy procedures use water-based dosimetry with no correction for heterogeneity. Therefore, these systems assume that full scatter exists regardless of the amount of tissue beyond the prescription line. This assumption might not be a reasonable one, especially when the tissue beyond the prescription line is thin. In such a case, the resulting limited scatter could cause an underdose to be delivered along the prescription line. We used Monte Carlo simulations to investigate how the thickness of the tissue between the surface of the balloon and the skin or lung affected the treatment dose delivery. Calculations were based on a spherical water phantom with a diameter of 30 cm and balloons with diameters of 4 cm, 5 cm, and 6 cm. The dose modification factor is defined as the ratio of the dose rate at the typical prescription distance of 1 cm from the balloon's surface with full scatter obtained using the water phantom to the dose rate with a finite tissue thickness (from 0 cm to 10 cm) beyond the prescription line. The dose modification factor was found to be dependent on the balloon diameter and was 1.098 for the 4-cm balloon and 1.132 for the 6-cm balloon with no tissue beyond the prescription distance at the breast-skin interface. The dose modification factor at the breast-lung interface was 1.067 for the 4-cm balloon and 1.096 for the 6-cm balloon. Even 5 cm of tissue beyond the prescription distance could not result in full scatter. Thus, we found that considering the effect of diminished scatter is important to accurate dosimetry. Not accounting for the dose modification factor may result in delivering a lower dose than is prescribed.

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Patient-oriented simulation based on Monte Carlo algorithm by using MRI data.

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Patient-oriented simulation based on Monte Carlo algorithm by using MRI data.

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