Evidence map›Paper›PMID 41912983›Full record

ReviewCardiovascular engineering and technology2026

Image-Based Medical Navigation Systems for Cardiac Interventions: Recent Technological Advances.

Luís C N Barbosa, João L Vilaça, Siobhán Moane, Pedro Morais

Abstract readReview
In one paragraph

Review in Cardiovascular engineering and technology, 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

4 authors.

Luís C N Barbosa2AI-Applied Artificial Intelligence Laboratory, School of Technology, IPCA, Barcelos, Portugal. lbarbosa@ipca.pt.ORCID 0000-0002-7818-1994
João L Vilaça2AI-Applied Artificial Intelligence Laboratory, School of Technology, IPCA, Barcelos, Portugal.ORCID 0000-0002-4196-5357
Siobhán MoaneLIFE Biosciences Research Institute, TUS- Technological University of the Shannon: Midlands Midwest, Limerick, Ireland.ORCID 0000-0001-9651-9162
Pedro Morais2AI-Applied Artificial Intelligence Laboratory, School of Technology, IPCA, Barcelos, Portugal.ORCID 0000-0002-1995-7879

Funding

UIDB/05549:2Ai DOI: 10.54499/UIDB/05549UIDP/05549:2Ai DOI: 10.54499/UIDP/05549
6 · The paper itself

Abstract

backgroundThe application of catheter-based treatments for a growing range of structural heart diseases (SHD) has significantly increased over the past five years, driven by technological advances in medical navigation systems, particularly those based on medical imaging. Multimodal cardiac imaging plays a crucial role in these systems by combining complementary anatomical, morphological, and functional information, thereby increasing diagnostic accuracy and improving the effectiveness of cardiovascular interventions and clinical outcomes. However, multimodal imaging poses challenges, including intermodality misalignment and the need to determine optimal integration methods for data from different imaging modalities.

methodsThis article reviews the state-of-the-art image-based medical navigation systems used in catheter-based cardiac procedures. The review covers the period from 2019 to 2023 and includes a total of 44 articles. The methodologies in these studies are grouped into six main categories: Image Enhancement and Tracking, Image Fusion and Reconstruction, 3D Modeling/Printing, Extended Reality, and Artificial Intelligence (AI).

resultsMost studies involve multimodality imaging, combining or transferring information across different modalities. The review emphasizes that current multimodal imaging techniques enhance the accuracy of procedures such as left atrial appendage closure (LAAC), transcatheter aortic valve implantation (TAVI), and catheter ablation therapy. These techniques rely on combinations of imaging modalities such as fluoroscopy, ultrasound, and computed tomography (CT) to enable real-time guidance and precise navigation during minimally invasive interventions.

conclusionBy integrating data from multiple sources, these systems improve diagnostic reliability and procedural success, meeting the complex demands of SHD treatment. Despite advances, real-time surgical guidance remains a major challenge, underscoring the need for continued research in this area.

Indexed as

Cardiac CatheterizationCatheter AblationHeart DiseasesMultimodal ImagingSurgery, Computer-AssistedArtificial IntelligenceDiffusion of InnovationHumansIntelligent SystemsLeft Atrial Appendage ClosurePredictive Value of TestsTreatment OutcomeArtificial intelligenceCardiac catheterization proceduresImage trackingMedical navigation systemsMulti-modality imagingReview

Identifiers

PMID41912983
PMCPMC13102890

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.