Evidence map›Paper›PMID 34315136›Full record

ArticlePhysics in medicine and biology2021

Proof-of-concept for x-ray based real-time image guidance during cardiac radioablation.

Nicholas Hindley, Suzanne Lydiard, Chun-Chien Shieh, Paul Keall

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

4 authors.

Nicholas HindleyACRF Image X Institute, University of Sydney, Sydney, Australia.
Suzanne LydiardACRF Image X Institute, University of Sydney, Sydney, Australia.
Chun-Chien ShiehACRF Image X Institute, University of Sydney, Sydney, Australia.ORCID 0000-0001-8245-8936
Paul KeallACRF Image X Institute, University of Sydney, Sydney, Australia.

Funding

TR&D Project 3: Virtual ReadersP41EB028744 · NIBIB · DUKE UNIVERSITY · PI Ehsan Samei · 2021 to 2026
$7.8M
Simulation Tools for Dynamic CTR01EB001838 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI SAMEI, EHSAN, SEGARS, WILLIAM P · 2005 to 2023
$6.9M
NIBIB NIH HHS P41 EB028744NIBIB NIH HHS R01 EB001838
6 · The paper itself

Abstract

Cardiac radioablation offers non-invasive treatments for refractory arrhythmias. However, treatment delivery for this technique remains challenging. In this paper, we introduce the first method for real-time image guidance during cardiac radioablation for refractory atrial fibrillation on a standard linear accelerator. Our proposed method utilizes direct diaphragm tracking on intrafraction images to estimate the respiratory component of cardiac substructure motion. We compare this method to treatment scenarios without real-time image guidance using the 4D-XCAT digital phantom. Pre-treatment and intrafraction imaging was simulated for 8 phantoms with unique anatomies programmed using cardiorespiratory motion from healthy volunteers. As every voxel in the 4D-XCAT phantom is labelled precisely according to the corresponding anatomical structure, this provided ground-truth for quantitative evaluation. Tracking performance was compared to the ground-truth for simulations with and without real-time image guidance using the left atrium as an exemplar target. Differences in target volume size, mean volumetric coverage, minimum volumetric coverage and geometric error were recorded for each simulation. We observed that differences in target volume size were statistically significant (

Indexed as

HeartFour-Dimensional Computed TomographyHumansMotionPhantoms, ImagingX-Rayscardiacguidanceradioablationreal-time

Identifiers

PMID34315136
PMCPMC8815757

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.