Evidence map›Paper›PMID 39092893›Full record

ArticleJournal of applied clinical medical physics2024

Geometric and dosimetric evaluation for breast and regional nodal auto-segmentation structures.

Tiffany Tsui, Alexander Podgorsak, John C Roeske, William Small, Tamer Refaat, Hyejoo Kang

Abstract read
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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. 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

6 authors.

Tiffany TsuiDepartment of Radiation Oncology, Loyola University Chicago, Stritch School of Medicine, Maywood, Illinois, USA.
Alexander PodgorsakDepartment of Radiation Oncology, University of Rochester Medical Center, Rochester, New York, USA.ORCID https://orcid.org/0000-0001-6351-703X
John C RoeskeDepartment of Radiation Oncology, Loyola University Chicago, Stritch School of Medicine, Maywood, Illinois, USA.
William SmallDepartment of Radiation Oncology, Loyola University Chicago, Stritch School of Medicine, Maywood, Illinois, USA.
Tamer RefaatDepartment of Radiation Oncology, Loyola University Chicago, Stritch School of Medicine, Maywood, Illinois, USA.
Hyejoo KangDepartment of Radiation Oncology, Loyola University Chicago, Stritch School of Medicine, Maywood, Illinois, USA.ORCID https://orcid.org/0000-0002-4433-0939

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accuracy of artificial intelligence (AI) generated contours for intact-breast and post-mastectomy radiotherapy plans was evaluated. Geometric and dosimetric comparisons were performed between auto-contours (ACs) and manual-contours (MCs) produced by physicians for target structures. Breast and regional nodal structures were manually delineated on 66 breast cancer patients. ACs were retrospectively generated. The characteristics of the breast/post-mastectomy chestwall (CW) and regional nodal structures (axillary [AxN], supraclavicular [SC], internal mammary [IM]) were geometrically evaluated by Dice similarity coefficient (DSC), mean surface distance, and Hausdorff Distance. The structures were also evaluated dosimetrically by superimposing the MC clinically delivered plans onto the ACs to assess the impact of utilizing ACs with target dose (Vx%) evaluation. Positive geometric correlations between volume and DSC for intact-breast, AxN, and CW were observed. Little or anti correlations between volume and DSC for IM and SC were shown. For intact-breast plans, insignificant dosimetric differences between ACs and MCs were observed for AxN

Indexed as

Breast NeoplasmsMastectomyOrgans at RiskRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedArtificial IntelligenceFemaleHumansLymph NodesPrognosisRetrospective StudiesAI‐algorithmAuto‐contourauto‐segmentationbreast radiation treatment

Identifiers

PMID39092893
PMCPMC11466470

What OpenQuestion holds

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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.