Academic Journal
Machine Model-Specific Delivery Sequence Optimization for Spot-scanning Proton Arc Therapy Using a Compact Superconducting Synchrocyclotron.
| Τίτλος: | Machine Model-Specific Delivery Sequence Optimization for Spot-scanning Proton Arc Therapy Using a Compact Superconducting Synchrocyclotron. |
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| Συγγραφείς: | Liu P; Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA.; Department of Medical Physics, School of Medicine, Wayne State University, Detroit, Michigan, USA., Zhao L; Department of Radiation Oncology, Medstar Georgetown University Hospital, Washington, District of Columbia, USA., Cong X; Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA., Liu G; Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA., Li X; Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA., Ding X; Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA. |
| Πηγή: | Medical physics [Med Phys] 2026 Sep; Vol. 53 (9), pp. e70658. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: John Wiley and Sons, Inc Country of Publication: United States NLM ID: 0425746 Publication Model: Print Cited Medium: Internet ISSN: 2473-4209 (Electronic) Linking ISSN: 00942405 NLM ISO Abbreviation: Med Phys Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2017- : Hoboken, NJ : John Wiley and Sons, Inc. Original Publication: Lancaster, Pa., Published for the American Assn. of Physicists in Medicine by the American Institute of Physics. |
| Ιατρικοί όροι (MeSH): | Proton Therapy*/instrumentation , Proton Therapy*/methods, Radiotherapy Planning, Computer-Assisted/methods ; Brain Neoplasms/radiotherapy ; Radiotherapy Dosage ; Humans |
| Περίληψη: | Background: Spot scanning proton arc therapy (SPArc) combines the dosimetric advantages of proton therapy with the beam-angle freedom of arc delivery. However, current planning algorithms rely on static delivery assumptions that do not account for the temporal characteristics of pulsed-beam synchrocyclotron systems during continuous gantry rotation. This mismatch between nominal plans and actual treatment delivery may lead to clinically meaningful dose deviations. Purpose: To develop and evaluate a dynamic arc delivery sequencing optimization framework that incorporates machine-specific delivery characteristics to minimize deviations between planned and delivered dose in SPArc. Methods: A five-step dynamic arc delivery sequencing optimization framework was developed. The framework includes: (1) static and dynamic delivery time calculation, (2) spot and energy-layer disassembling, (3) incorporation of dynamic delivery timing into control points, (4) spot-weight fine-tuning, and (5) reconstruction of energy-layer sequences. Five multi-metastatic brain stereotactic radiosurgery cases were retrospectively evaluated. Delivery accuracy, efficiency and plan quality were assessed using virtual machine logfiles. Results: The sequencing optimization framework substantially improved delivery accuracy while preserving plan quality and efficiency. For the total gross tumor volume, the mean absolute D98 deviation between planned and virtual logfile reconstructed doses decreased from 77.4 ± 81.0 cGyE (4.2 ± 4.5%) with static SPArc plans to 9.6 ± 4.0 cGyE (0.5 ± 0.2%) after sequencing optimization. For the worst metastasis in each case, D98 deviation decreased from 184.4 ± 145.2 cGyE (9.8 ± 7.9%) to 19.0 ± 16.4 cGyE (1.0 ± 0.8%), and D2 deviation decreased from 148.4 ± 114.4 cGyE (6.8 ± 5.6%) to 13.2 ± 8.6 cGyE (0.6 ± 0.4%). Target coverage and normal brain sparing remained statistically unchanged (p > 0.05), and total delivery times differed by < 1 s. Conclusions: The proposed sequencing optimization framework addresses the temporal mismatch between static SPArc planning and dynamic delivery in synchrocyclotron-based systems. By improving delivery accuracy without compromising plan quality or delivery efficiency, the framework demonstrates the feasibility of incorporating machine-specific delivery timing into dynamic proton arc therapy. (© 2026 American Association of Physicists in Medicine.) |
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| Grant Information: | R01 CA301448 United States CA NCI NIH HHS; R01CA301448 United States CA NCI NIH HHS |
| Contributed Indexing: | Keywords: delivery accuracy; proton arc therapy; synchrocyclotron |
| Entry Date(s): | Date Created: 20260831 Date Completed: 20260831 Latest Revision: 20260926 |
| Update Code: | 20260926 |
| PubMed Central ID: | PMC13527260 |
| DOI: | 10.1002/mp.70658 |
| PMID: | 42670024 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 2473-4209 |
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| DOI: | 10.1002/mp.70658 |