title: Spot-Scanning Proton Arc (SPArc) Therapy: The First Robust and Delivery-Efficient Spot-Scanning Proton Arc Therapy.
abstract: To present a novel robust and delivery-efficient spot-scanning proton arc (SPArc) therapy technique.
  
  
  
  A SPArc optimization algorithm was developed that integrates control point resampling, energy layer redistribution, energy layer filtration, and energy layer resampling. The feasibility of such a technique was evaluated using sample patients: 1 patient with locally advanced head and neck oropharyngeal cancer with bilateral lymph node coverage, and 1 with a nonmobile lung cancer. Plan quality, robustness, and total estimated delivery time were compared with the robust optimized multifield step-and-shoot arc plan without SPArc optimization (Arcmulti-field) and the standard robust optimized intensity modulated proton therapy (IMPT) plan. Dose-volume histograms of target and organs at risk were analyzed, taking into account the setup and range uncertainties. Total delivery time was calculated on the basis of a 360° gantry room with 1 revolutions per minute gantry rotation speed, 2-millisecond spot switching time, 1-nA beam current, 0.01 minimum spot monitor unit, and energy layer switching time of 0.5 to 4 seconds.
  
  
  
  The SPArc plan showed potential dosimetric advantages for both clinical sample cases. Compared with IMPT, SPArc delivered 8% and 14% less integral dose for oropharyngeal and lung cancer cases, respectively. Furthermore, evaluating the lung cancer plan compared with IMPT, it was evident that the maximum skin dose, the mean lung dose, and the maximum dose to ribs were reduced by 60%, 15%, and 35%, respectively, whereas the conformity index was improved from 7.6 (IMPT) to 4.0 (SPArc). The total treatment delivery time for lung and oropharyngeal cancer patients was reduced by 55% to 60% and 56% to 67%, respectively, when compared with Arcmulti-fieldplans.
  
  
  
  The SPArc plan is the first robust and delivery-efficient proton spot-scanning arc therapy technique, which could potentially be implemented into routine clinical practice.
authors.affiliation: Department of Radiation Oncology, Beaumont Health System, Rose Cancer Center, Royal Oak, Michigan. Electronic address: Xuanfeng.ding@beaumont.org.
authors.forename: Xuanfeng
authors.initials: X
authors.lastname: Ding
authors.affiliation: Department of Radiation Oncology, Beaumont Health System, Rose Cancer Center, Royal Oak, Michigan.
authors.forename: Xiaoqiang
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Radiation Oncology, Beaumont Health System, Rose Cancer Center, Royal Oak, Michigan.
authors.forename: J Michele
authors.initials: JM
authors.lastname: Zhang
authors.affiliation: Department of Radiation Oncology, Beaumont Health System, Rose Cancer Center, Royal Oak, Michigan.
authors.forename: Peyman
authors.initials: P
authors.lastname: Kabolizadeh
authors.affiliation: Department of Radiation Oncology, Beaumont Health System, Rose Cancer Center, Royal Oak, Michigan.
authors.forename: Craig
authors.initials: C
authors.lastname: Stevens
authors.affiliation: Department of Radiation Oncology, Beaumont Health System, Rose Cancer Center, Royal Oak, Michigan.
authors.forename: Di
authors.initials: D
authors.lastname: Yan
mesh_terms: D000465:Algorithms; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D005240:Feasibility Studies; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D058958:Organs at Risk / Q000000981:diagnostic imaging; D009959:Oropharyngeal Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D061766:Proton Therapy / Q000379:methods*; D058996:Quality Improvement; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D013997:Time Factors