Evidence map›Paper›PMID 40940285›Full record

ArticleMedical physics2025

A motion analysis of cardiac substructures for guiding stereotactic arrhythmia radiotherapy motion management.

Yuhao Wang, Trevor McKeown, Yao Hao, Hongyu An, H Michael Gach, Clifford G Robinson, Phillip S Cuculich, Deshan Yang

Abstract read
In one paragraph

Article in Medical physics, 2025. 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
  3. 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

8 authors.

Yuhao WangDepartment of Radiation Oncology, School of Medicine, Duke University, Durham, North Carolina, USA.
Trevor McKeownDepartment of Radiation Oncology, School of Medicine, Duke University, Durham, North Carolina, USA.
Yao HaoDepartment of Radiation Oncology, School of Medicine, Washington University in Saint Louis, St. Louis, Missouri, USA.
Hongyu AnDepartment of Radiology, School of Medicine, Washington University in Saint Louis, St. Louis, Missouri, USA.
H Michael GachDepartment of Radiation Oncology, School of Medicine, Washington University in Saint Louis, St. Louis, Missouri, USA.
Clifford G RobinsonDepartment of Radiation Oncology, School of Medicine, Washington University in Saint Louis, St. Louis, Missouri, USA.
Phillip S CuculichDepartment of Radiation Oncology, School of Medicine, Washington University in Saint Louis, St. Louis, Missouri, USA.
Deshan YangDepartment of Radiation Oncology, School of Medicine, Duke University, Durham, North Carolina, USA.

Funding

Novel imaging and treatment technologies for image-guided noninvasive stereotactic cardiac radiosurgeryR01HL148210 · NHLBI · WASHINGTON UNIVERSITY · PI GACH, H MICHAEL, YANG, DESHAN · 2019 to 2022
$1.7M
Develop a large-scale library of comprehensive deformable image registration (DIR) benchmark datasets and an integrated framework for quantifying accuracy of patient-specific DIR resultsR01EB029431 · NIBIB · WASHINGTON UNIVERSITY · PI YANG, DESHAN · 2021 to 2021
$1.6M
NHLBI NIH HHS R01 HL148210NIBIB NIH HHS R01 EB029431the National Heart, Lung, and Blood Institute (NHLBI) R01-HL148210the National Institute of Biomedical Imaging and Bioengineering (NIBIB) R01-EB029431
6 · The paper itself

Abstract

backgroundStereotactic arrhythmia radiotherapy (STAR) has recently emerged as a novel noninvasive treatment option for critically ill and drug-refractory VT patients who cannot be treated or re-treated by catheter ablation. However, STAR requires precise management of cardiorespiratory motion to minimize radiation toxicity to the healthy heart and nearby organs-at-risk (OARs) and to ensure the radiation precision to deliver the prescribed dose to the VT target. PURPOSE: To investigate the characteristics of cardiac motion of VT patients to facilitate cardiac motion management for STAR treatments.

methodsBreath-hold cardiac 4DCTs (c4DCT) of 18 patients previously treated with STAR were analyzed retrospectively. Each c4DCT contained ten 3DCTs corresponding to 10 phases of an entire cardiac motion cycle. For each c4DCT, a group-wise deformable image registration (DIR) method was used to register all ten 3DCTs, resulting in ten 3D deformation vector fields (DVFs) and an average position 3DCT. The DVFs were computed from each phase to the average position 3DCT instead of between pairs of phases. Metal artifacts caused by the Implantable Cardioverter-Defibrillator (ICD) leads were reduced using a diffusion procedure before DIR. The heart chambers were segmented on the average position 3DCT using an AI segmentation tool, followed by manual evaluation and correction. Cardiac motion characteristics (magnitude and direction) were investigated temporally over the 10 cardiac phases and spatially for the outer myocardium walls of the heart and per chamber, AV (atrium-ventricle) valves, septa (the muscular walls dividing the chambers), and STAR targets.

resultsThe motion magnitude maximum over cardiac phases was computed by taking each voxel's maximum motion magnitude in 10 phases, referring to the average position. The cardiac motion magnitudes were found to be strongly patient-specific. The maximum, 99

conclusionsThe cardiac motion characteristics (magnitude, direction, and spatial distribution) of STAR patients provided in this study would further facilitate cardiac motion management.

Indexed as

Arrhythmias, CardiacHeartRadiosurgeryRadiotherapy, Image-GuidedFemaleFour-Dimensional Computed TomographyHumansMaleMovementRetrospective Studies4DCTmedical image analysismotion managementstereotactic arrhythmia radiotherapy

Identifiers

PMID40940285
PMCPMC12980959

What OpenQuestion holds

Textmetadata
LicenceTDM
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.