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Updated: Feb 6, 2026

Determining 3D Flow Fields via Multi-camera Light Field Imaging
Published on: March 6, 2013
Pencil beam scanning proton lattice radiotherapy: single-field versus multi-field optimization
Shouyi Wei1, Lee Xu1, Hang Qi1
1New York Proton Center, New York, NY, United States.
Objective:
To evaluate the advantages and disadvantages of single-field versus multi-field optimization in the clinical implementation of pencil beam scanning (PBS) proton lattice radiotherapy (LRT).
Methods:
LRT proton plans were created retrospectively for 12 patients with head-and-neck, thoracic, or abdominal bulky tumors, averaging a gross tumor volume (GTV) of 1011.1 cc (between 333 cc and 3546 cc). The plans were developed in the RayStation treatment planning system (version 2023B), adhering to established consensus guidelines for prescription dose and planning goals. For each plan, 6-8 vertices with an average diameter of 1.4 cm were positioned approximately 3.5 cm apart. The prescription was 18 Gy to each vertex and 3 Gy to the GTV. Single-field optimization (SFO) and multi-field optimization (MFO) techniques were employed. The dosimetric parameters of GTV Dmean, D95%, generalized equivalent uniform dose (gEUD a=-10), vertex D90%, peak-to-valley dose ratio (PVDR), and skin D1% were used for plan quality assessment. Plan robustness was also investigated by comparing dose metrics between the nominal and second worst-case scenarios in the robust analysis.
Results:
For all 12 patients, both SFO and MFO plans achieved a PVDR close to 4 across the three treatment sites. No significant differences in primary dose metrics were observed between SFO and MFO plans, except for skin D1%, which was reduced by an average of 25% in the MFO plans (p<0.05). Robustness evaluation indicated larger deviations in PVDR, GTV Dmean, and skin D1% between nominal and second worst-case scenarios for MFO plans compared to SFO (p<0.05).
Conclusion:
Both SFO and MFO techniques can be reliably implemented with current proton beam quality standards and advanced treatment planning algorithms. While SFO offers better plan robustness in maintaining the originally optimized metrics under various treatment-related uncertainties, MFO enhances the ability to spare critical organs.
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