ArticleCurrent cardiovascular imaging reports2018
Cardiac CT: Technological Advances in Hardware, Software, and Machine Learning Applications.
Article in Current cardiovascular imaging reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled 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.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Pooled it
- Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.Journal of imaging informatics in medicine · 2025Article
- A wearable cardiac ultrasound imager.Nature · 2023Article
- Heart Rate-Dependent Degree of Motion Artifacts in Coronary CT Angiography Acquired by a Novel Purpose-Built Cardiac CT Scanner.Journal of clinical medicine · 2022Article
- Clinical applications of cardiac computed tomography: a consensus paper of the European Association of Cardiovascular Imaging-part I.European heart journal. Cardiovascular Imaging · 2022Article
- Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications.Diagnostics (Basel, Switzerland) · 2021Review
- Carotid Artery Plaque Identification and Display System (MRI-CAPIDS) Using Opensource Tools.Diagnostics (Basel, Switzerland) · 2020Article
- Technical development in cardiac CT: current standards and future improvements-a narrative review.Cardiovascular diagnosis and therapy · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 2 countries.
Funding
Abstract
purpose of reviewMultidetector row computed tomography (CT) allows noninvasive imaging of the heart and coronary arteries. The purpose of this review is to briefly summarize recent advances in CT hardware and software technology, and machine learning applications for cardiovascular imaging. RECENT
findingsIn the last decades, there have been significant improvements in CT hardware focusing on faster gantry rotation resulting in improved temporal resolution. Concurrent hardware improvements include improved spatial resolution and higher coverage of the patient, enabling faster acquisition. Advances in cardiac CT software include methods for measurement of noninvasive FFR, coronary plaque characterization, and adipose tissue characteristics around the heart. Machine learning approaches using cardiac CT have been shown to improve both risk of prognosis and lesion-specific ischemia. SUMMARY: Recent advances in CT hardware and software have expanded the clinical utility of CT for cardiovascular imaging. In the next decades, continued advances can be anticipated in these areas, and in machine learning applications in cardiac CT, as they are incorporated into clinical routine for image acquisition, image analysis, and prediction of patient outcomes.
Indexed as
Identifiers
What OpenQuestion holds
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.