ReviewJournal of biomedical research2013
Multimodality image fusion for diagnosing coronary artery disease.
Review in Journal of biomedical research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Simulation Study of a Frame-Based Motion Correction Algorithm for Positron Emission Imaging.Sensors (Basel, Switzerland) · 2021Article
- Diagnostic performance of the quantification of myocardium at risk from MPI SPECT/CTA 2G fusion for detecting obstructive coronary disease: A multicenter trial.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2018Article
- Multimodality Image Fusion for Coronary Artery Disease Detection: Concepts and Latest Developments.Annals of nuclear cardiology · 2018Article
- Survey of Non-Rigid Registration Tools in Medicine.Journal of digital imaging · 2017Review
- Multimodality Imaging in Ischemic Cardiomyopathy.Current cardiovascular imaging reports · 2014Review
- The frontiers of nuclear cardiology research.Journal of biomedical research · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coronary artery disease (CAD) is one of the leading causes of death in the US and a substantial health-care burden in all industrialized societies. In recent years we have witnessed a constant strive towards the development and the clinical application of novel or improved detection methods as well as therapies. Particularly, noninvasive imaging is a decisive component in the cardiovascular field. Image fusion is the ability of combining into a single integrated display the anatomical as well as the physiological data retrieved by separated modalities. Clinical evidence suggests that it represents a promising strategy in CAD assessment and risk stratification by significantly improving the diagnostic power of each modality independently considered and of the traditional side-by-side interpretation. Numerous techniques and approaches taken from the image registration field have been implemented and validated in the context of CAD assessment and management. Although its diagnostic power is widely accepted, additional technical developments are still needed to become a routinely used clinical tool.
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Registered trials
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.