強度調控與直接機器參數最佳化演算法在攝護腺癌治療計畫之比較

A Comparison of Intensity Modulation and Direct Machine Parameters Optimizations in Treatment Planning for Prostate Cancer

黃家政(Chia-cheng Huang)

指導教授 ： 陳信雄

中臺科技大學/健康科學院/醫學影像暨放射科學系暨研究所/碩士(2012年)

摘要

直接機器參數最佳化演算法 ( Direct Machine Parameters Optimization, DMPO ) 運用反向治療計畫運算模式，將子照野 ( segments ) 的葉片位置及葉片相對比重都含括在最佳化的過程之中，並排除了葉片序列化的步驟。本研究之目的藉由臨床攝護腺癌病例，比較強度調控 ( Intensity Modulation, IM ) 與直接機器參數最佳化演算法的靜態強度調控放射治療計畫，結果經由成對樣本T檢定 ( paired-sample t-test ) 比較方法分析差異，可得知直接機器參數最佳化演算方式的治療計畫有較佳執行效率。本研究進一步將二種演算法中三個設定參數加以調整，可得知改變強度調控最佳化演算方式的強度階層數，與直接機器參數最佳化演算方式的最大子照野數時，子照野的最小面積與最小 MU 值，對於執行效率與計畫品質具有明顯的影響，利用系統化的方法評估治療計畫總體品質，提出最佳化參數建議設定值，進而使治療計劃更加理想，並可提供本單位製作治療計畫時的重要參考依據。

關鍵字

強度調控最佳化演算法 ； 直接機器參數最佳化演算法 ； 葉片序列化

並列摘要

The principle of Direct Machine Parameters Optimization (DMPO) is to compose the leaf position and dose weight from a number of segments in inverse treatment planning algorithm, eliminating the leaf sequencing steps in optimization process. The purpose of this study was to compare the two optimization methods, Intensity Modulation (IM) and Direct Machine Parameters Optimization, in static IMRT planning for prostate cancer. Paired samples t-test statistical method was used in calculated results. We found DMPO had the better deliver efficiency for treatment planning. And further, we adjusted the parameters of the both algorithms to evaluate and modify the intensity level in IM and max number segments in DMPO, the results indicated the significant correlation between the minimum area and minimum MU of segment to the plan deliver efficiency and quality. The optimized parameters setting will approach the ideal treatment plan, and provide the important information in planning implementation for our institution.

並列關鍵字

leaf Sequencing ； Direct Machine Parameters Optimization (DMPO) ； Intensity Modulation (IM)

參考文獻

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