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Biomedical subjects

D M Shepard

Publications and source records attributed to D M Shepard.

10 recordsLinked to original sources

Iterative approaches to dose optimization in tomotherapy.

This paper will present the results of an investigation into three iterative approaches to inverse treatment planning. These techniques have been examined in the hope of developing an optimization algorithm suitable for the large-scale problems that are encountered in tomotherapy. The three iterative techniques are referred to as the ratio method, iterative least-squares minimization and the maximum-likelihood estimator. Our results indicate that each of these techniques can serve as a useful tool in tomotherapy optimization. As compared with other mathematical programming techniques, the iterative approaches can reduce both memory demands and time requirements. In this paper, the results from small- and large-scale optimizations will be analysed. It will also be demonstrated that the flexibility of the iterative techniques can be greatly enhanced through the use of dose-volume histogram based penalty functions and/or through the use of weighting factors assigned to each region of the patient. Finally, results will be presented from an investigation into the stability of the iterative techniques.

Algorithms↗

Inverse treatment planning for Gamma Knife radiosurgery.

An inverse treatment planning system for Gamma Knife radiosurgery has been developed using nonlinear programming techniques. The system optimizes the shot sizes, locations, and weights for Gamma Knife treatments. In the patient's prescription, the user can specify both the maximum number of shots of radiation and a minimum isodose line that must surround the entire treatment volume. After satisfying all of the constraints included in the prescription, the system maximizes the conformity of the dose distribution. This automated approach to treatment planning has been applied retrospectively to a series of patient cases, and each optimized plan has been compared to the corresponding manual plan produced by an experienced user. The results demonstrate that this tool can often improve the tumor dose homogeneity while using fewer shots than were included in the original plan. Therefore, inverse treatment planning should improve both the quality and the efficiency of Gamma Knife treatments.

Algorithms↗

A simple model for examining issues in radiotherapy optimization.

Convolution/superposition software has been used to produce a library of photon pencil beam dose matrices. This library of pencil beams is designed to serve as a tool for both education and investigation in the field of radiotherapy optimization. The elegance of this pencil beam model stems from its cylindrical symmetry. Because of the symmetry, the dose distribution for a pencil beam from any arbitrary angle can be determined through a simple rotation of a pre-computed dose matrix. Rapid dose calculations can thus be performed while maintaining the accuracy of a convolution/superposition based dose computation. The pencil beam data sets have been made publicly available. It is hoped that the data sets will facilitate a comparison of a variety of optimization and delivery approaches. This paper will present a number of studies designed to demonstrate the usefulness of the pencil beam data sets. These studies include an examination of the extent to which a treatment plan can be improved through either an increase in the number of beam angles and/or a decrease in the collimator size. A few insights into the significance of heterogeneity corrections for treatment planning for intensity modulated radiotherapy will also be presented.

Computer Simulation↗

Application of constrained optimization to radiotherapy planning.

Essential for the calculation of photon fluence distributions for intensity modulated radiotherapy (IMRT) is the use of a suitable objective function. The objective function should reflect the clinical aims of tumor control and low side effect probability. Individual radiobiological parameters for patient organs are not yet available with sufficient accuracy. Some of the major drawbacks of some current optimization methods include an inability to converge to a solution for arbitrary input parameters, and/or a need for intensive user input in order to guide the optimization. In this work, a constrained optimization method was implemented and tested. It is closely related to the demanded clinical aims, avoiding the drawbacks mentioned above. In a prototype treatment planning system for IMRT, tumor control was guaranteed by setting a lower boundary for target dose. The aim of low complication is fulfilled by minimizing the dose to organs at risk. If only one type of tissue is involved, there is no absolute need for radiobiological parameters. For different organs, threshold dose, relative seriality of the organs or an upper dose limit could be set. All parameters, however, were optional, and could be omitted. Dose-volume constraints were not used, avoiding the possibility of local minima in the objective function. The approach was benchmarked through the simulation of both a head and neck and a lung case. A cylinder phantom with precalculated dose distributions of individual pencil beams was used. The dose to regions at risk could be significantly reduced using at least seven ports of beam incidence. Increasing the number of ports beyond seven produced only minor further gain. The relative seriality of organs was modeled through the use of an added exponent to the dose. This approach however increased calculation time significantly. The alternative of setting an upper limit is much faster and allows direct control of the maximum dose. Constrained optimization guarantees high tumor control probability, it is computationally more efficient than adding penalty terms to the objective function, and the input parameters are dose limits known in clinical practice.

Algorithms↗

Maximum likelihood as a common computational framework in tomotherapy.

Tomotherapy is a dose delivery technique using helical or axial intensity modulated beams. One of the strengths of the tomotherapy concept is that it can incorporate a number of processes into a single piece of equipment. These processes include treatment optimization planning, dose reconstruction and kilovoltage/megavoltage image reconstruction. A common computational technique that could be used for all of these processes would be very appealing. The maximum likelihood estimator, originally developed for emission tomography, can serve as a useful tool in imaging and radiotherapy. We believe that this approach can play an important role in the processes of optimization planning, dose reconstruction and kilovoltage and/or megavoltage image reconstruction. These processes involve computations that require comparable physical methods. They are also based on equivalent assumptions, and they have similar mathematical solutions. As a result, the maximum likelihood approach is able to provide a common framework for all three of these computational problems. We will demonstrate how maximum likelihood methods can be applied to optimization planning, dose reconstruction and megavoltage image reconstruction in tomotherapy. Results for planning optimization, dose reconstruction and megavoltage image reconstruction will be presented. Strengths and weaknesses of the methodology are analysed. Future directions for this work are also suggested.

Algorithms↗

Sodium in drinking water in South Carolina.

The potential contribution of drinking water sodium to total consumption and to blood pressure levels is explored in a South Carolina survey. Most (96 per cent) of the population was served by drinking water containing less than 100 mg/l Na (median 14.8 mg/l). For households with water sources containing greater than or equal to 100 mg/l Na, drinking water accounted for approximately 8.5 per cent of total estimated consumption. After adjustment for age, sex, race, body mass index, education, and dietary sodium, a negative association between diastolic blood pressure and drinking water sodium levels was found.

Adolescent↗