Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer
Background and purpose: Adaptive radiotherapy (ART) decision-making benefits from dosimetric information to supplement image inspection when assessing the significance of anatomical changes. This study evaluated a dosimetry-based clinical decision workflow for ART utilizing deformable registration o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-07-01
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| Series: | Physics and Imaging in Radiation Oncology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405631623000696 |
| _version_ | 1797691963877621760 |
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| author | Caitlin Allen Adam U. Yeo Nicholas Hardcastle Rick D. Franich |
| author_facet | Caitlin Allen Adam U. Yeo Nicholas Hardcastle Rick D. Franich |
| author_sort | Caitlin Allen |
| collection | DOAJ |
| description | Background and purpose: Adaptive radiotherapy (ART) decision-making benefits from dosimetric information to supplement image inspection when assessing the significance of anatomical changes. This study evaluated a dosimetry-based clinical decision workflow for ART utilizing deformable registration of the original planning computed tomography (CT) image to the daily Cone Beam CT (CBCT) to replace the need for a replan CT for dose estimation. Materials and methods: We used 12 retrospective Head & Neck patient cases having a ground truth – a replan CT (rCT) in response to anatomical changes apparent in the daily CBCT – to evaluate the accuracy of dosimetric assessment conducted on synthetic CTs (sCT) generated by deforming the original planning CT Hounsfield Units to the daily CBCT anatomy.The original plan was applied to the sCT and dosimetric accuracy of the sCT was assessed by analyzing plan objectives for targets and organs-at-risk compared to calculations on the ground-truth rCT. Three commercial DIR algorithms were compared. Results: For the best-performing algorithms, the majority of dose metrics calculated on the sCTs differed by less than 4 Gy (5.7% of 70 Gy prescription dose). An uncertainty of ±2.5 Gy (3.6% of 70 Gy prescription) is recommended as a conservative tolerance when evaluating dose metrics on sCTs for head and neck. Conclusions: Synthetic CTs present a valuable addition to the adaptive radiotherapy workflow, and synthetic CT dose estimates can be effectively used in addition to the current practice of visually inspecting the overlay of the planning CT and CBCT to assess the significance of anatomical change. |
| first_indexed | 2024-03-12T02:21:28Z |
| format | Article |
| id | doaj.art-b2b2b64443a846778bc00507a58b1fba |
| institution | Directory Open Access Journal |
| issn | 2405-6316 |
| language | English |
| last_indexed | 2024-03-12T02:21:28Z |
| publishDate | 2023-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Physics and Imaging in Radiation Oncology |
| spelling | doaj.art-b2b2b64443a846778bc00507a58b1fba2023-09-06T04:52:30ZengElsevierPhysics and Imaging in Radiation Oncology2405-63162023-07-0127100478Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancerCaitlin Allen0Adam U. Yeo1Nicholas Hardcastle2Rick D. Franich3Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; School of Science, RMIT University, Melbourne, Victoria, AustraliaPhysical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; School of Science, RMIT University, Melbourne, Victoria, AustraliaPhysical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; Centre for Medical Radiation Physics, University of Wollongong, NSW, AustraliaPhysical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; School of Science, RMIT University, Melbourne, Victoria, Australia; Corresponding author at: School of Science, RMIT University, Melbourne, Victoria, Australia.Background and purpose: Adaptive radiotherapy (ART) decision-making benefits from dosimetric information to supplement image inspection when assessing the significance of anatomical changes. This study evaluated a dosimetry-based clinical decision workflow for ART utilizing deformable registration of the original planning computed tomography (CT) image to the daily Cone Beam CT (CBCT) to replace the need for a replan CT for dose estimation. Materials and methods: We used 12 retrospective Head & Neck patient cases having a ground truth – a replan CT (rCT) in response to anatomical changes apparent in the daily CBCT – to evaluate the accuracy of dosimetric assessment conducted on synthetic CTs (sCT) generated by deforming the original planning CT Hounsfield Units to the daily CBCT anatomy.The original plan was applied to the sCT and dosimetric accuracy of the sCT was assessed by analyzing plan objectives for targets and organs-at-risk compared to calculations on the ground-truth rCT. Three commercial DIR algorithms were compared. Results: For the best-performing algorithms, the majority of dose metrics calculated on the sCTs differed by less than 4 Gy (5.7% of 70 Gy prescription dose). An uncertainty of ±2.5 Gy (3.6% of 70 Gy prescription) is recommended as a conservative tolerance when evaluating dose metrics on sCTs for head and neck. Conclusions: Synthetic CTs present a valuable addition to the adaptive radiotherapy workflow, and synthetic CT dose estimates can be effectively used in addition to the current practice of visually inspecting the overlay of the planning CT and CBCT to assess the significance of anatomical change.http://www.sciencedirect.com/science/article/pii/S2405631623000696Adaptive radiotherapySynthetic CTDeformable image registrationDIRCBCT |
| spellingShingle | Caitlin Allen Adam U. Yeo Nicholas Hardcastle Rick D. Franich Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer Physics and Imaging in Radiation Oncology Adaptive radiotherapy Synthetic CT Deformable image registration DIR CBCT |
| title | Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer |
| title_full | Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer |
| title_fullStr | Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer |
| title_full_unstemmed | Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer |
| title_short | Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer |
| title_sort | evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer |
| topic | Adaptive radiotherapy Synthetic CT Deformable image registration DIR CBCT |
| url | http://www.sciencedirect.com/science/article/pii/S2405631623000696 |
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