Evidence map›Paper›PMID 42410888›Full record

ArticleJournal of applied clinical medical physics2026

An integrated toolkit for structure generation, optimization, and evaluation in spatially fractionated radiation therapy.

Japan K Patel, Anthony Magliari, Gregory Gill, Todd A Wareing, Tenzin Kunkyab, Caleb Raman, Ilias Sachpazidis, Peter Szentivanyi, Ryan Clark, Pierre Lansonneur and 6 more

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Japan K PatelGateway Scripts, Saint Louis, Missouri, USA.
Anthony MagliariMedical Affairs, Varian Medical Systems, Palo Alto, California, USA.
Gregory GillDepartment of Radiation Oncology, Intermountain Health, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0002-3487-9987
Todd A WareingMedical Affairs, Varian Medical Systems, Palo Alto, California, USA.
Tenzin KunkyabDepartment of Radiation Oncology, Icahn School of Medicine at Mt. Sinai, New York City, New York, USA.ORCID https://orcid.org/0000-0003-0467-0784
Caleb RamanBiological Sciences Division, University of Chicago, Chicago, Illinois, USA.
Ilias SachpazidisDepartment of Radiation Oncology, University of Freiburg, Freiburg, Baden-Württemberg, Germany.ORCID https://orcid.org/0000-0001-5701-8947
Peter SzentivanyiMedical Affairs, Varian Medical Systems, Palo Alto, California, USA.
Ryan ClarkMedical Affairs, Varian Medical Systems, Palo Alto, California, USA.
Pierre LansonneurMedical Affairs, Varian Medical Systems, Palo Alto, California, USA.
Arjun KarnwalDepartment of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.
Michael KudlaRadiation Therapy Program, BC Cancer, Vancouver, British Columbia, Canada.
Sergejs UnterkirhersClinic Hirslanden, Zurich, Zurich, Switzerland.
Junqi SongFoshan Fosun Chancheng Hospital, Foshan City, Guangdong, China.
Jun YangFoshan Fosun Chancheng Hospital, Foshan City, Guangdong, China.ORCID https://orcid.org/0000-0002-2861-0885
Matthew C SchmidtGateway Scripts, Saint Louis, Missouri, USA.

Funding

Varian Medical Affairs
6 · The paper itself

Abstract

purposeSpatially fractionated radiation therapy (SFRT) planning requires three coordinated tasks: generation of high-dose sphere structures, position-aware optimization, and peak-valley dose ratio evaluation. In practice, clinicians and researchers address these tasks with a combination of closed-source scripts, research codes, and manual calculation. The absence of a unified, commercially deployable toolkit remains a barrier to multi-institutional SFRT trials. We present MAAS-SFRThelper, a shared-source plugin that integrates structure generation, geometric-aware optimization, and peak-valley dose ratio evaluation for SFRT into a single workflow inside Varian's Eclipse treatment planning system. ACQUISITION AND VALIDATION

methodsMAAS-SFRThelper is a Windows Presentation Foundation (WPF) application built on the Model-View-ViewModel (MVVM) pattern, implemented in C# against ESAPI for Eclipse 15.6 and later. The plugin currently contains five task-oriented tabs that share common services for sphere extraction and objective creation. The SphereLattice tab generates sphere lattices using five placement patterns: hexagonal close-packed, simple cubic, alternating cubic, centroidal Voronoi tessellation, and a constraint-based Monte Carlo method. The SCART tab creates contracted spindle-like boost volumes for stereotactic central ablative radiation therapy. The Optimization tab auto-populates structure list, searches over candidate lattice positions using a four-metric geometric surrogate score, and triggers Eclipse VMAT optimization along with dose calculation on the best candidate. The Evaluation tab implements four analysis modes including 1D, 2D, and 3D PVDR analysis. We validated all functionality on digital phantoms against analytic ground truth. In phantom testing, the optimized lattice achieved 22.5% higher PVDR. DATA FORMAT AND USAGE: The plugin is distributed as source code that compiles to a single dynamic-link library (DLL); all third-party dependencies are bundled at build time. At first launch, users review the Varian Limited Use Software License Agreement (LUSLA) and enter an access code that is emailed upon request. The plugin accepts the patient structure set and, where applicable, a plan with calculated dose; outputs include new structures written directly to the structure set through ESAPI and summary statistics exported as comma-separated value (CSV) files. Source code and documentation are publicly available on GitHub under the LUSLA. POTENTIAL APPLICATIONS: MAAS-SFRThelper supports clinical lattice SFRT planning with consistent workflows across institutions and standardized peak-valley dose ratio reporting for multi-institutional trials. The shared-services architecture enables community contributions of new placement patterns, evaluation metrics, and validation datasets. These features represent a practical step toward the dosimetric consistency called for in the 2024 NRG Oncology/AAPM consensus on SFRT. The plugin also serves as a platform for research extensions to GRID therapy, minibeam radiation therapy, and other heterogeneous dose-delivery modalities.

Indexed as

AlgorithmsNeoplasmsPhantoms, ImagingRadiotherapy Planning, Computer-AssistedSoftwareDose Fractionation, RadiationHumansOrgans at RiskRadiotherapy DosageRadiotherapy, Intensity-ModulatedEclipseESAPIlattice therapypeak‐valley dose ratiospatially fractionated radiation therapytreatment planning

Identifiers

PMID42410888
PMCPMC13338100

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.