Evidence map›Paper›PMID 41474051›Full record

ArticleMedical physics2026

Dose optimization with fully flexible vertex positioning for LATTICE radiotherapy.

Xin Tong, Weijie Zhang, Ya-Nan Zhu, Xue Hong, Chao Wang, Jufri Setianegara, Yuting Lin, Hao Gao

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In one paragraph

Article in Medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xin TongDepartment of Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Weijie ZhangDepartment of Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Ya-Nan ZhuSchool of Mathematics, Harbin Institute of Technology, Harbin, China.
Xue HongDepartment of Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Chao WangCollege of Science, China Agricultural University, Beijing, China.
Jufri SetianegaraDepartment of Radiation Oncology, Hospital of the University of Pennsylvania, Pennsylvania, USA.
Yuting LinDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Hao GaoDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.

Funding

Novel Optimization Methods and Treatment Planning System for Clinically-Deliverable Truly-Hybrid Proton-Photon RadiotherapyR37CA250921 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI Hao Gao · 2021 to 2026
$2.2M
Simultaneous dose and dose rate optimization for clinical FLASH proton radiotherapyR01CA261964 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GAO, HAO · 2022 to 2025
$2.0M
KUCCNational Science Foundation R01CA261964National Science Foundation R37CA250921NCI NIH HHS R01 CA261964NCI NIH HHS R37 CA250921
6 · The paper itself

Abstract

backgroundLattice radiotherapy (LATTICE) is a technique of spatially fractionated radiation therapy (SFRT) that delivers high radiation doses to specific regions (vertices) within a large tumor, forming a spatially modulated "lattice" pattern, while surrounding areas receive lower doses to minimize damage to healthy tissues. Although the original conception of LATTICE did not prescribe any rigorous symmetry, and early clinical implementations relied on manual vertex placement tailored to tumor shape and anatomical constraints, more recent automated approaches have introduced regular patterns such as simple cubic or hexagonal arrangements. These rigid configurations, while convenient, may reduce the flexibility needed to accommodate irregular tumor geometries and nearby critical structures, potentially resulting in unintended hotspots or under-treatment. Optimizing the placement of vertices in LATTICE is beneficial for precisely targeting high-dose regions within the tumor while minimizing radiation exposure to adjacent healthy tissue, but there is still no optimization method available for solving the positions of fully flexible placed vertices. The great challenge in such optimization lies in handling the constraints on the relative positions between different vertices. PURPOSE: This work aims to develop a new treatment planning method for LATTICE with fully flexible placement of vertices and simultaneous optimization of the position of each lattice vertex and dose, to improve overall plan quality compared with conventional LATTICE planning methods relying on manual regular placements of lattice vertices.

methodsThe proposed method simultaneously optimizes each lattice vertex position and other plan optimization variables (proton spot weights or photon fluences) during the dose optimization process. This is formulated as a new constrained optimization problem by adding each lattice vertex position to optimization variables with appropriate constraints to meet the requirements of the LATTICE vertices placement guideline on the 1) center-to-center distance between lattice vertices and 2) distance of lattice vertices to the target boundaries. The optimization problem is solved by the alternating direction method of multipliers and iterative convex relaxation methods.

resultsPlans generated using our proposed method (NEW) were compared with conventional LATTICE plans for two representative patient cases presented in the main manuscript: one abdominal and one lung tumor. To maintain brevity, two additional patient cases are included in the Supporting Information to further demonstrate the performance and generalizability of the proposed method. For each case, we generated 100 LATTICE plans with varying vertex positions. From these, three plans-termed BEST, MID, and WORST-were selected based on the largest, median, and smallest total optimization objective value

conclusionA new LATTICE treatment planning approach is introduced, in which lattice positions are fully flexible and optimized simultaneously with dose distribution, leading to improved target PVDR and OAR sparing compared to conventional LATTICE methods with regularly spaced vertices.

Indexed as

Dose Fractionation, RadiationRadiation DosageRadiotherapy Planning, Computer-AssistedHumansRadiotherapy Dosageinverse optimizationLATTICEPVDRSFRTtreatment planning

Identifiers

PMID41474051
PMCPMC13584643

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.