Evidence map›Paper›PMID 39169048›Full record

ArticleScientific reports2024

Enhancing boundary detection of radiofrequency ablation lesions through photoacoustic mapping.

Shang Gao, Haotian Liu, Allison Post, Lukas Jaworski, Drew Bernard, Mathews John, Elizabeth Cosgriff-Hernandez, Mehdi Razavi, Haichong K Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. 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

9 authors.

Shang GaoDepartment of Robotics Engineering, Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA, 01609, USA. sgao@wpi.edu.
Haotian LiuDepartment of Robotics Engineering, Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA, 01609, USA.
Allison PostElectrophysiology Clinical Research and Innovations, The Texas Heart Institute, 6770 Bertner Ave, Houston, TX, 77030, USA.
Lukas JaworskiElectrophysiology Clinical Research and Innovations, The Texas Heart Institute, 6770 Bertner Ave, Houston, TX, 77030, USA.
Drew BernardElectrophysiology Clinical Research and Innovations, The Texas Heart Institute, 6770 Bertner Ave, Houston, TX, 77030, USA.
Mathews JohnElectrophysiology Clinical Research and Innovations, The Texas Heart Institute, 6770 Bertner Ave, Houston, TX, 77030, USA.
Elizabeth Cosgriff-HernandezDepartment of Biomedical Engineering, The University of Texas at Austin, 2515 Speedway, Austin, TX, 78712, USA.
Mehdi RazaviElectrophysiology Clinical Research and Innovations, The Texas Heart Institute, 6770 Bertner Ave, Houston, TX, 77030, USA.
Haichong K ZhangDepartment of Robotics Engineering, Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA, 01609, USA. hzhang10@wpi.edu.

Funding

Physician Assistance Technology in Image-guided Robotic Intervention of ProstateR01EB030539 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI HATA, NOBUHIKO, ZHANG, HAICHONG · 2021 to 2024
$2.7M
Automatic Wide-Field Optical Coherence Tomography for Assessment of Transplant Kidney ViabilityR01DK133717 · NIDDK · UNIVERSITY OF MASSACHUSETTS AMHERST · PI POTTER, STEVEN, TANG, QINGGONG · 2022 to 2025
$2.5M
Injectable Hydrogel Electrodes to Prevent Ventricular ArrhythmiasR01HL162741 · NHLBI · UNIVERSITY OF TEXAS AT AUSTIN · PI Elizabeth Marie Cosgriff-Hernandez, Mehdi Razavi · 2023 to 2026
$2.4M
Robotic Lung Ultrasound for Triage of COVID-19 Patients in a Resource-Limited EnvironmentDP5OD028162 · OD · WORCESTER POLYTECHNIC INSTITUTE · PI ZHANG, HAICHONG · 2019 to 2023
$2.3M
NHLBI NIH HHS R01 HL162741NIBIB NIH HHS R01 EB030539NIDDK NIH HHS R01 DK133717NIH HHS DP5 OD028162NIH HHS R01 DK133717NIH HHS R01 HL162741
6 · The paper itself

Abstract

Atrial fibrillation (A-fib) is the most common type of heart arrhythmia, typically treated with radiofrequency catheter ablation to isolate the heart from abnormal electrical signals. Monitoring the formation of ablation-induced lesions is crucial for preventing recurrences and complications arising from excessive or insufficient ablation. Existing imaging modalities lack real-time feedback, and their intraoperative usage is in its early stages. A critical need exists for an imaging-based lesion indexing (LSI) method that directly reflects tissue necrosis formation. Previous studies have indicated that spectroscopic photoacoustic (sPA) imaging can differentiate ablated tissues from their non-ablated counterparts based on PA spectrum variation. In this paper, we introduce a method for detecting ablation lesion boundaries using sPA imaging. This approach utilizes ablation LSI, which quantifies the ratio between the signal from ablated tissue and the total tissue signal. We enhance boundary detection accuracy by adapting a regression model-based compensation. Additionally, the method was cross-validated with clinically used intraoperative monitoring parameters. The proposed method was validated with ex vivo porcine cardiac tissues with necrotic lesions created by different ablation durations. The PA-measured lesion size was compared with gross pathology. Statistical analysis demonstrates a strong correlation (R > 0.90) between the PA-detected lesion size and gross pathology. The PA-detected lesion size also exhibits a moderate to strong correlation (R > 0.75) with local impedance changes recorded during procedures. These results suggest that the introduced PA imaging-based LSI has great potential to be incorporated into the clinical workflow, guiding ablation procedures intraoperatively.

Indexed as

Catheter AblationPhotoacoustic TechniquesAnimalsAtrial FibrillationNecrosisRadiofrequency AblationSwineAblation lesion indexingAtrial fibrillationCatheterImage-guided interventionPhotoacoustic imagingRadiofrequency ablation

Identifiers

PMID39169048
PMCPMC11339419

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.