Evidence map›Paper›PMID 40653628›Full record

ArticleJournal of applied clinical medical physics2025

Semi-automated hippocampal avoidance whole-brain radiotherapy planning.

Dong Joo Rhee, Subha Perni, Kelly J Perrin, Kevin E Casey, Alexandra O Leone, Callistus M Nguyen, Laurence E Court, He Wang, Xin Wang, Eun Young Han

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Semi-automated hippocampal avoidance whole-brain radiotherapy planning.Journal of applied clinical medical physics · 2025
    Article
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

10 authors.

Dong Joo RheeDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.
Subha PerniDepartment of Central Nervous System Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Kelly J PerrinDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.
Kevin E CaseyDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0001-7345-7130
Alexandra O LeoneDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.
Callistus M NguyenDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.
Laurence E CourtDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.
He WangDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0002-4904-531X
Xin WangDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.
Eun Young HanDepartment of Radiation Physics, The University of Texas MD Anderson, Cancer Center, Houston, Texas, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHippocampal avoidance whole-brain radiotherapy (HA-WBRT) is designed to spare cognitive function by reducing radiation dose to the hippocampus during the treatment of brain metastases. Current manual planning methods can be time-consuming and may vary in quality, necessitating the development of automated approaches to streamline the process and ensure consistency. PURPOSE: To automate hippocampal avoidance whole-brain radiotherapy (HA-WBRT) planning.

methodsOur algorithm automatically contours organs-at-risk (OARs) and the hippocampal-avoidance brain target. The algorithm generates planning structures from given contours, utilizing preset beam parameters and dose constraints for optimization. If the dose constraints are unmet, "hotspot" contours will be created to improve dosimetry. The algorithm was written with RayStation's scripting feature and was compared with clinically approved manual HA-WBRT plans for 20 retrospective patients using target and OAR dose metrics, with statistical analysis performed using the Student's t-test. In the qualitative review, an experienced radiation oncologist blindly scored both the manual plans and autoplans for qualitative review. Lastly, IMRT QA was performed to determine the plans' deliverability.

resultsThe autoplans demonstrated a better target coverage with a more uniform dose. With a prescription dose of 3000 cGy, autoplans achieved higher D

conclusionsOur rule-based autoplanning algorithm produces high-quality plans that are comparable to those of manual planning, demonstrating autoplanning's potential to reduce HA-WBRT planning time while ensuring consistent plan quality.

Indexed as

AlgorithmsBrain NeoplasmsCranial IrradiationHippocampusOrgans at RiskOrgan Sparing TreatmentsRadiotherapy Planning, Computer-AssistedHumansRadiotherapy DosageRadiotherapy, Intensity-ModulatedRetrospective Studiesautocontouringautoplanninghippocampal avoidance WBRTwhole brain radiotherapy

Identifiers

PMID40653628
PMCPMC12256275

What OpenQuestion holds

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LicenceCC BY
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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.