Trial reportEuropean radiology2025
Automated vs manual cardiac MRI planning: a single-center prospective evaluation of reliability and scan times.
Trial report in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- [The digital patient journey : Performing radiological examinations].Radiologie (Heidelberg, Germany) · 2026Review
- Best fast MRI protocols for the knee: advantages and limitations.Skeletal radiology · 2026Review
- Reproducibility of cardiac volumetric parameters derived from fully automatically prescribed image planes: a direct comparison to manual planning at 1.5-T and 3-T MRI.European radiology · 2026Article
- Fully automated free-breathing cardiac magnetic resonance imaging at 3T: A prospective randomized study of image quality, efficiency, and workflow burden.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2026Article
- Artificial Intelligence-Assisted CMR Scanning vs Standard-of-Care: Comparative Analysis of Clinical Benefits From 6,545 Consecutive Studies.JACC. Advances · 2026Article
- Artificial Intelligence in Cardiovascular Imaging: From Automated Acquisition to Precision Diagnostics and Clinical Decision Support.Medical sciences (Basel, Switzerland) · 2026Review
- Fully Automated Plane Prescription in Cardiac MRI: A Prospective Cohort Study.Journal of magnetic resonance imaging : JMRI · 2026Article
- Artificial intelligence in cardiology: a narrative review with focus on patient outcomes.Cardiovascular diagnosis and therapy · 2026Review
- Applying artificial intelligence to cardiac MRI to diagnose congenital heart disease in low-resource settings such as Sub-Saharan Africa.Communications medicine · 2025Review
- Democratizing cardiac imaging with an automated magnetic resonance exam.Research square · 2025Article
- Artificial intelligence for diagnostics in radiology practice: a rapid systematic scoping review.EClinicalMedicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesEvaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on procedure errors and scan times compared to manual planning alone. MATERIAL AND
methodsConsecutive patients undergoing non-stress CMR were prospectively enrolled at a single center (August 2023-February 2024) and randomized into manual, or automated scan execution using prototype software. Patients with pacemakers, targeted indications, or inability to consent were excluded. All patients underwent the same CMR protocol with contrast, in breath-hold (BH) or free breathing (FB). Supervising radiologists recorded procedure errors (plane prescription, forgotten views, incorrect propagation of cardiac planes, and field-of-view mismanagement). Scan times and idle phase (non-acquisition portion) were computed from scanner logs. Most data were non-normally distributed and compared using non-parametric tests.
resultsEighty-two patients (mean age, 51.6 years ± 17.5; 56 men) were included. Forty-four patients underwent automated and 38 manual CMRs. The mean rate of procedure errors was significantly (p = 0.01) lower in the automated (0.45) than in the manual group (1.13). The rate of error-free examinations was higher (p = 0.03) in the automated (31/44; 70.5%) than in the manual group (17/38; 44.7%). Automated studies were shorter than manual studies in FB (30.3 vs 36.5 min, p < 0.001) but had similar durations in BH (42.0 vs 43.5 min, p = 0.42). The idle phase was lower in automated studies for FB and BH strategies (both p < 0.001).
conclusionAn AI-based automated software performed CMR at a clinical level with fewer planning errors and improved efficiency compared to manual planning. KEY POINTS: Question What is the impact of an AI-based automated CMR planning software on procedure errors and scan times compared to manual planning alone? Findings Software-driven examinations were more reliable (71% error-free) than human-planned ones (45% error-free) and showed improved efficiency with reduced idle time. Clinical relevance CMR examinations require extensive technologist training, and continuous attention, and involve many planning steps. A fully automated software reliably acquired non-stress CMR potentially reducing mistake risk and increasing data homogeneity.
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.