研究生: |
蔡忠宏 Chung-Hung Tsai |
---|---|
論文名稱: |
改良式軟片劑量驗證應用於強度調控放射線治療之研究 An Improved Method of Film Dosimetry for IMRT |
指導教授: |
莊克士
Keh-Shih Chuang |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
原子科學院 - 生醫工程與環境科學系 Department of Biomedical Engineering and Environmental Sciences |
論文出版年: | 2002 |
畢業學年度: | 90 |
語文別: | 中文 |
論文頁數: | 57 |
中文關鍵詞: | 強度調控放射治療 、劑量驗證 、類神經網路 、光密度值 |
外文關鍵詞: | dose verification, over-response, neural net, energy spectra |
相關次數: | 點閱:4 下載:0 |
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強度調控放射治療 (intensity modulated radiation therapy; IMRT) 的劑量驗證有三個主要特點:空間解析度要高,測量是要在整個平面,能夠測量數個射束的整體劑量。用軟片作劑量測量大致可以滿足這些條件,但是由於(1)軟片對低能量光子較靈敏,吸收係數較強。(2)受散射光子的影響在不同深度的能譜分佈也不同,使得軟片的劑量驗證需要對深度與照野大小作校正,且僅能用於單一射束。為此我們發展出一套改良系統,利用數種材質的濾片與軟片之組合接受X光的照射,再以類神經網路將不同能譜與劑量之間的關係找出來,可以得到實際的劑量。
先前的研究對於軟片應用在動態性照野,導致照射至軟片的能譜變化皆無法適當地加以修正,本研究針對軟片光密度值轉換劑量所需面對的能量依持性加以探討。利用X光能譜對各種不同材質衰減係數的差異,分析到達各測量點的能譜組成資訊,再藉由適當的轉換函數對應各能譜,並轉換為劑量值。實驗結果顯示,經本系統轉換的劑量值,在深度及照野變化的情況下,仍能有效轉換劑量至最大誤差小於±4%,平均誤差2%左右,此為臨床上可接受之誤差範圍。
X-ray film emulsion contains high-Z elements that preferentially respond to photons with energies below 400 keV. This over-response significantly overestimates the dose at deep parts of a phantom where the low-energy photons are abundant due to scattering. Previous method used a high Z foil placed next to film to improve the dose response. However, this method cannot be used for off-axis dose measurement. It’s inappropriate for multiple fields dose verification.
We propose an improved film system by using the combination of film with various filters (None, Pb, Cu, and Al) so that each film is irradiated to different energy spectrum and the readings of these four films are input to a neural net that relates the actual dose with energy spectra.
Percentage depth dose (PDD) measured by the film system in the polystyrene phantom for a 10cm×10cm field size of a 6MV linear accelerator together with measurement in a water phantom using an ionization chamber detector were served as a training data set to the neural net. To validate this method, the PDD of a 20×20 field size and the dose distribution of an off-axis location at 5cm are estimated using this trained neural network. The maximum differences between the measurements of film system and ionization chamber were less than ±4%, and less than 2% for the mean error in our investigation.
Further study of this film system will focus on the performance of multi-fields and its clinical application.
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