Jiahua Zhu1, Scott N Penfold2. 1. Department of Physics, University of Adelaide, Adelaide, SA 5005, Australia. 2. Department of Physics, University of Adelaide, Adelaide, SA 5005, Australia and Department of Medical Physics, Royal Adelaide Hospital, Adelaide, SA 5000, Australia.
Abstract
PURPOSE: The accuracy of proton dose calculation is dependent on the ability to correctly characterize patient tissues with medical imaging. The most common method is to correlate computed tomography (CT) numbers obtained via single-energy CT (SECT) with proton stopping power ratio (SPR). CT numbers, however, cannot discriminate between a change in mass density and change in chemical composition of patient tissues. This limitation can have consequences on SPR calibration accuracy. Dual-energy CT (DECT) is receiving increasing interest as an alternative imaging modality for proton therapy treatment planning due to its ability to discriminate between changes in patient density and chemical composition. In the current work we use a phantom of known composition to demonstrate the dosimetric advantages of proton therapy treatment planning with DECT over SECT. METHODS: A phantom of known composition was scanned with a clinical SECT radiotherapy CT-simulator. The phantom was rescanned at a lower X-ray tube potential to generate a complimentary DECT image set. A set of reference materials similar in composition to the phantom was used to perform a stoichiometric calibration of SECT CT number to proton SPRs. The same set of reference materials was used to perform a DECT stoichiometric calibration based on effective atomic number. The known composition of the phantom was used to assess the accuracy of SPR calibration with SECT and DECT. Intensity modulated proton therapy (IMPT) treatment plans were generated with the SECT and DECT image sets to assess the dosimetric effect of the imaging modality. Isodose difference maps and root mean square (RMS) error calculations were used to assess dose calculation accuracy. RESULTS: SPR calculation accuracy was found to be superior, on average, with DECT relative to SECT. Maximum errors of 12.8% and 2.2% were found for SECT and DECT, respectively. Qualitative examination of dose difference maps clearly showed the dosimetric advantages of DECT imaging, compared to SECT imaging for IMPT dose calculation for the case investigated. Quantitatively, the maximum dose calculation error in the SECT plan was 7.8%, compared to a value of 1.4% in the DECT plan. When considering the high dose target region, the root mean square (RMS) error in dose calculation was 2.1% and 0.4% for SECT and DECT, respectively. CONCLUSIONS: DECT-based proton treatment planning in a commercial treatment planning system was successfully demonstrated for the first time. DECT is an attractive imaging modality for proton therapy treatment planning owing to its ability to characterize density and chemical composition of patient tissues. SECT and DECT scans of a phantom of known composition have been used to demonstrate the dosimetric advantages obtainable in proton therapy treatment planning with DECT over the current approach based on SECT.
PURPOSE: The accuracy of proton dose calculation is dependent on the ability to correctly characterize patient tissues with medical imaging. The most common method is to correlate computed tomography (CT) numbers obtained via single-energy CT (SECT) with proton stopping power ratio (SPR). CT numbers, however, cannot discriminate between a change in mass density and change in chemical composition of patient tissues. This limitation can have consequences on SPR calibration accuracy. Dual-energy CT (DECT) is receiving increasing interest as an alternative imaging modality for proton therapy treatment planning due to its ability to discriminate between changes in patient density and chemical composition. In the current work we use a phantom of known composition to demonstrate the dosimetric advantages of proton therapy treatment planning with DECT over SECT. METHODS: A phantom of known composition was scanned with a clinical SECT radiotherapy CT-simulator. The phantom was rescanned at a lower X-ray tube potential to generate a complimentary DECT image set. A set of reference materials similar in composition to the phantom was used to perform a stoichiometric calibration of SECT CT number to proton SPRs. The same set of reference materials was used to perform a DECT stoichiometric calibration based on effective atomic number. The known composition of the phantom was used to assess the accuracy of SPR calibration with SECT and DECT. Intensity modulated proton therapy (IMPT) treatment plans were generated with the SECT and DECT image sets to assess the dosimetric effect of the imaging modality. Isodose difference maps and root mean square (RMS) error calculations were used to assess dose calculation accuracy. RESULTS: SPR calculation accuracy was found to be superior, on average, with DECT relative to SECT. Maximum errors of 12.8% and 2.2% were found for SECT and DECT, respectively. Qualitative examination of dose difference maps clearly showed the dosimetric advantages of DECT imaging, compared to SECT imaging for IMPT dose calculation for the case investigated. Quantitatively, the maximum dose calculation error in the SECT plan was 7.8%, compared to a value of 1.4% in the DECT plan. When considering the high dose target region, the root mean square (RMS) error in dose calculation was 2.1% and 0.4% for SECT and DECT, respectively. CONCLUSIONS: DECT-based proton treatment planning in a commercial treatment planning system was successfully demonstrated for the first time. DECT is an attractive imaging modality for proton therapy treatment planning owing to its ability to characterize density and chemical composition of patient tissues. SECT and DECT scans of a phantom of known composition have been used to demonstrate the dosimetric advantages obtainable in proton therapy treatment planning with DECT over the current approach based on SECT.
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