Evidence map›Paper›PMID 31213732›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2018

Technical Note: On Cardiac Ablation Lesion Visualization for Image-guided Therapy Monitoring.

Cristian A Linte, Jon J Camp, Maryam E Rettmann, Dieter Haemmerich, Mehmet K Aktas, David T Huang, Douglas L Packer, David R Holmes

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2018. 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

8 authors.

Cristian A LinteBiomedical Engineering and Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester NY USA.
Jon J CampBiomedical Imaging Resource, Mayo Clinic, Rochester MN USA.
Maryam E RettmannDivision of Cardiology, Mayo Clinic, Rochester MN USA.
Dieter HaemmerichDepartment of Pediatrics, Medical University of South Carolina, Charleston SC USA.
Mehmet K AktasDivision of Cardiology, University of Rochester Medical Center, Rochester NY USA.
David T HuangDivision of Cardiology, University of Rochester Medical Center, Rochester NY USA.
Douglas L PackerDivision of Cardiology, Mayo Clinic, Rochester MN USA.
David R HolmesBiomedical Imaging Resource, Mayo Clinic, Rochester MN USA.

Funding

5-D Image Guided Cardiac Ablation TherapyR01EB002834 · NIBIB · MAYO CLINIC ROCHESTER · PI ROBB, RICHARD A · 2003 to 2012
$3.9M
NIBIB NIH HHS R01 EB002834
6 · The paper itself

Abstract

The delivery of insufficient thermal dose is a significant contributor to incomplete tissue ablation and leads to arrhythmia recurrence and a large number of patients requiring repeat procedures. In concert with ongoing research efforts aimed at better characterizing the RF energy delivery, here we propose a method that entails modeling and visualization of the lesions in real time. The described image-based ablation model relies on classical heat transfer principles to estimate tissue temperature in response to the ablation parameters, tissue properties, and duration. The ablation lesion quality, geometry, and overall progression is quantified on a voxel-by-voxel basis according to each voxel's cumulative temperature and time exposure. The model was evaluated both numerically under different parameter conditions, as well as experimentally, using

Indexed as

ablation lesion modeling and monitoringimage-guided cardiac catheter ablationlesion visualizationmodel evaluation and validationradiofrequency ablation

Identifiers

PMID31213732
PMCPMC6581517

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.