Modeling the transport of photons from source to detector as a means of improving radiation therapy by enhanced utilization of kV and MV x-ray imaging

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Introduction: This research program seeks to develop new algorithms to remove contaminating x-ray scatter from diagnostic and therapeutic medical images obtained in modern radiation therapy. Current radiation treatment units use kilovoltage (KV) x-rays for anatomical imaging (ie. cone-beam computed tomography, CBCT) just prior to therapy delivery using a megavoltage (MV) x-ray beam. Therapy and diagnostic imaging applications on these units are currently at a rudimentary level.***Hypothesis: A hybrid scatter estimation algorithm for both MV and KV energy x-rays will improve the accuracy of image reconstruction and density conversion (CBCT) and also improve the accuracy of dose reconstruction (MV) providing increased sensitivity for error detection. ***Objectives: 1. Develop a hybrid scatter estimation algorithm combining a deterministic approach with a novel, fast Monte Carlo method. 2. Validate and optimize this algorithm using both MV and KV x-ray beams. 3. Combine interleaved KV and MV imaging allowing diagnostic imaging during therapy delivery.***Methods: Building on our previous experience, a hybrid algorithm will be developed to estimate x-ray scatter from patients for both KV and MV energy x-ray beams. A fast analytical solution will estimate singly-scattered x-rays, while a novel Monte Carlo approach treating each voxel as a scatter source will estimate multiply-scattered x-rays. The method will be validated on both MV therapeutic beams and KV (CBCT) diagnostic imaging beams and quantitatively evaluated in terms of reconstruction accuracy and improved contrast (CBCT), and patient reconstructed dose accuracy (MV) on a variety of geometric and anthropomorphic phantoms. Furthermore, an interleaved acquisition approach will be developed to concurrently obtain KV and MV image data during radiation treatment delivery through the use of XML control software, minimizing the impact of patient motion. Performance will be assessed through quantitative comparison of image quality results to standard sequential image acquisition.***Significance: This research program will provide significantly improved quality CBCT data on radiation treatment units (i.e. improved tumour visibility, accurate density conversions). For MV imaging, more accurate patient dose reconstructions will be provided, improving sensitivity in detecting delivery errors. Interleaved image acquisition will provide a more accurate representation of patient anatomy during treatment. Future research opportunities for real-time tumour tracking and adaptive radiation therapy will be created.***Conclusion: This research program builds on our experience developing scatter estimation algorithms and their applications to improve the accuracy of radiation treatments. Eventually these advances may be used throughout Canada and the world to improve quality of life for all patients treated with radiation.**