Evidence map›Paper›PMID 42488742›Full record

ArticleJournal of contemporary brachytherapy2026

Development of a patient-specific adaptive ring for organ at risk contours in high-dose-rate brachytherapy gynecologic cancers.

Sruthi Sivabhaskar, Yesenia Gonzalez, Paul Medin, Brian Hrycushko, Kevin Albuquerque, Zohaib Iqbal

Abstract read
In one paragraph

Article in Journal of contemporary brachytherapy, 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

6 authors.

Sruthi SivabhaskarDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA.
Yesenia GonzalezDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA.
Paul MedinDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA.
Brian HrycushkoDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA.
Kevin AlbuquerqueDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA.
Zohaib IqbalDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: High-dose-rate (HDR) brachytherapy for gynecologic cancers requires repeated organ at risk (OAR) contouring for each fraction, which is a time-consuming task susceptible to variability. This study evaluated the use of patient-specific adaptive rings to streamline OAR contouring without compromising dosimetric accuracy and patient safety. Material and methods: Fifty HDR brachytherapy tandem and ovoid (T&O) fractions from twenty-five previously treated patients were analyzed. Two adaptive rings were investigated: one generated based on margins from clinical target volume (CTV) to 50% isodose line (IDL), and the other based on margins from CTV to 75% IDL, referred to as the 50% IDL and 75% IDL adaptive rings, respectively. Bladder, rectum, small bowel, and sigmoid were contoured within these two rings, and D Results: Errors in D Conclusions: Adaptive IDL-based rings provide an efficient strategy for OAR contouring in HDR gynecologic brachytherapy. Using adaptive rings to limit OAR contouring allows for fraction-specific adaptation, reduces contouring workload, and maintains dosimetric accuracy.

Indexed as

adaptive ringsgynecologic cancerHDR brachytherapyOAR contouringtandem and ovoidworkflow efficiency

Identifiers

PMID42488742
PMCPMC13389763

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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.