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Dose convolution filter: Incorporating spatial dose information into tissue response modeling
Author(s) -
Huang Yimei,
Joiner Michael,
Zhao Bo,
Liao Yixiang,
Burmeister Jay
Publication year - 2010
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3309440
Subject(s) - collimated light , convolution (computer science) , dosimetry , spatial filter , filter (signal processing) , pencil (optics) , grid , computer science , physics , nuclear medicine , optics , mathematics , medicine , artificial intelligence , laser , artificial neural network , computer vision , geometry
Purpose: A model is introduced to integrate biological factors such as cell migration and bystander effects into physical dose distributions, and to incorporate spatial dose information in plan analysis and optimization. Methods: The model consists of a dose convolution filter (DCF) with single parameter σ . Tissue response is calculated by an existing NTCP model with DCF‐applied dose distribution as input. The authors determined σ of rat spinal cord from published data. The authors also simulated the GRID technique, in which an open field is collimated into many pencil beams. Results: After applying the DCF, the NTCP model successfully fits the rat spinal cord data with a predicted value of σ = 2.6 ± 0.5 mm , consistent with 2 mm migration distances of remyelinating cells. Moreover, it enables the appropriate prediction of a high relative seriality for spinal cord. The model also predicts the sparing of normal tissues by the GRID technique when the size of each pencil beam becomes comparable to σ . Conclusions: The DCF model incorporates spatial dose information and offers an improved way to estimate tissue response from complex radiotherapy dose distributions. It does not alter the prediction of tissue response in large homogenous fields, but successfully predicts increased tissue tolerance in small or highly nonuniform fields.