Evidence map›Paper›PMID 32212374›Full record

ArticleJournal of applied clinical medical physics2020

Clinical impact of the VOLO optimizer on treatment plan quality and clinical treatment efficiency for CyberKnife.

Emil Schüler, Anthony Lo, Cynthia F Chuang, Scott G Soltys, Erqi L Pollom, Lei Wang

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.6field-weighted citation impact, top 5% of its field
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

22 citing papers in PubMed, 42 citations in OpenAlex.

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  11. Comparison of two optimization algorithms (VOLOJournal of applied clinical medical physics · 2023
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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

6 authors at 1 institution in 1 country.

Emil SchülerDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA.
Anthony LoDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA.
Cynthia F ChuangDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA.
Scott G SoltysDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA.
Erqi L PollomDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA.
Lei WangDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA.
Stanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the recent CyberKnife treatment planning system (TPS) upgrade from Precision 1.0 to Precision 2.0, the new VOLO optimizer was released for plan optimization. The VOLO optimizer sought to overcome some of the limitations seen with the Sequential optimizer from previous TPS versions. The purpose of this study was to investigate the clinical impact of the VOLO optimizer on treatment plan quality and clinical treatment efficiency as compared to the Sequential optimizer. Treatment plan quality was evaluated in four categories of patients: Brain Simple (BS), Brain Complex (BC), Spine Complex (SC), and Prostate (PC). A total of 60 treatment plans were compared using both the Sequential and VOLO optimizers with Iris and MLC collimation with the same clinical constraints. Metrics evaluated included estimated treatment time, monitor units (MUs) delivered, conformity index (CI), and gradient index (GI). Furthermore, the clinical impact of the VOLO optimizer was evaluated through statistical analysis of the patient population treated during the 4 months before (n = 297) and 4 months after (n = 285) VOLO introduction. Significant MU and time reductions were observed for all four categories planned. MU reduction ranged from -14% (BS Iris) to -52% (BC MLC), and time reduction ranged from -11% (BS Iris) to -22% (BC MLC). The statistical analysis of patient population before and after VOLO introduction for patients using 6D Skull tracking with fixed cone, 6D Skull tracking with Iris, and Xsight Spine tracking with Iris were -4.6%, -22.2%, and -17.8% for treatment time reduction, -1.1%, -22.0%, and -28.4% for beam reduction and -3.2%, -21.8%, and -28.1% for MU reduction, respectively. The VOLO optimizer maintains or improves the plan quality while decreases the plan complexity and improves treatment efficiency. We anticipate an increase in patient throughput with the introduction of the VOLO optimizer.

Indexed as

Radiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedHumansMaleProstateRadiotherapy DosageCyberKnifeoptimizer algorithmsequential optimizationtreatment Planning

Identifiers

PMID32212374
PMCPMC7286021
OpenAlexW3013557964

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.