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Biomedical subjects

R A Siochi

Publications and source records attributed to R A Siochi.

2 recordsLinked to original sources

Minimizing static intensity modulation delivery time using an intensity solid paradigm.

PURPOSE: A leaf sequencing optimization algorithm that minimizes the delivery time for a static intensity modulated field is presented. METHODS AND MATERIALS: Sets of segments are created by intensity map operations subject to leaf collision constraints and tongue and groove effects. Each set's delivery time is evaluated as a function of leaf travel, beam on time, and the verify and record (V&R) overhead. The configuration with the minimum delivery time is chosen. As a test, optimization was done on three clinical cases of varying complexity. RESULTS: Assuming 10 x 10-cm fields with an average of 17 intensity levels, the optimization technique reduced delivery times by 27% and 45%, when compared to rod pushing and power of two extraction, respectively. The treatment time for the optimal case with a V&R overhead of 4 s would be 11.5 min for 9 coplanar ports. Tongue-and-groove underdosages are removed, and the worst case leakage is 2% of the peak dose. CONCLUSION: Compared to previously reported leaf sequencing methods, the new optimization algorithm described here reduces treatment times for complex static intensity modulated fields. Additionally, leakage is minimal and no tongue-and-groove underdosage occurs.

Algorithms↗

A self-collimating convolution backprojection algorithm for optimizing dose distributions of I-125 prostate implants.

The algorithm presented here for optimizing brachytherapy dose distributions is based on the idea that the seed distribution can be modeled as an activity distribution determined analogously to gamma camera imaging. The peripheral dose to the tumor is converted to a set of uncollimated projection data that are then filtered and backprojected to produce an initial seed distribution. The actual doses resulting from the seed placement are used to correct the initial projection data for attenuation, scatter, and lack of collimation. The corrected projection data are backprojected a second time to yield the optimized but unconstrained seed distribution. Clinical constraints such as the number of different seed activities, the maximum seed activity, the minimum peripheral tumor dose, and the minimum percentage of the volume which receives less than a specified dose are then applied to the unconstrained solution. Through the entire process, the dose calculations are functions of source anisotropy, scatter, and attenuation. When applied to a set of elliptical contours, the algorithm produces elliptical peripheral dose isodose contours and reasonable dose volume histograms for a constrained solution. The results for actual patient prostate contours were not as good, primarily because of the difficulties encountered in dealing with the irregular geometry of the prostate. However, the algorithm shows promise for further research.

Algorithms↗