Evidence map›Paper›PMID 39235683›Full record

ArticleJournal of applied clinical medical physics2024

AFI manual planning versus HyperArc auto-planning: A head-to-head comparison of SRS plan quality.

Dharmin D Desai, Ivan L Cordrey, E Lee Johnson, Thomas A Oldland

Abstract readComparative Study
In one paragraph

Article in Journal of applied clinical medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

4 authors.

Dharmin D DesaiVarian Medical Systems Inc., Advanced Oncology Solutions, Hixson, Tennessee, USA.
Ivan L CordreyThompson Cancer Survival Center, Cumberland Medical Center, Crossville, Tennessee, USA.
E Lee JohnsonDepartment of Radiation Medicine, University of Kentucky Chandler Medical Center, Lexington, Kentucky, USA.
Thomas A OldlandDepartment of Radiation Medicine, University of Kentucky Chandler Medical Center, Lexington, Kentucky, USA.

Funding

University of Kentucky Markey Cancer Center Support Grant ECIA SupplementP30CA177558 · NCI · UNIVERSITY OF KENTUCKY · PI KATHLEEN L. O'CONNOR · 2013 to 2026
$38.3M
NCI NIH HHS P30 CA177558
6 · The paper itself

Abstract

introductionHyperArc (HA) auto-planning offers simplicity for the end user and consistently high-quality SRS plans. The "Ask For It" (AFI) optimization strategy offers a manual planning technique that, when coupled with R50%

methodsUsing a CT data set available from the Radiosurgery Society, 54 PTVs were created and used to generate 19 individual SRS/SRT cases. Case complexity ranged from single PTV plans to multiple PTV plans with a single isocenter. PTV locations ranged from relative isolation from critical structures to lesions within 1.5 mm of the optic apparatus and abutting the brainstem. All cases were planned using both the AFI and HA optimization strategies as implemented in the Varian Medical Systems Eclipse Treatment Planning System. A range of treatment plan quality metrics were obtained including Intermediate Dose Spill (R50%), Conformity Indices CI

resultsStatistically significant improvements were found for the AFI strategy for metrics R50%, CI

conclusionThis study provides evidence that the AFI manual planning strategy can produce high-quality planning metrics similar to the HA auto-planning method.

Indexed as

Organs at RiskRadiosurgeryRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedAlgorithmsBrain NeoplasmsHumansNeoplasmsQuality Assurance, Health CareAFIHyperArcplan qualityR50%SIMTSRS

Identifiers

PMID39235683
PMCPMC11540047

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Registered trials

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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.