ArticleJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance2022
Infarct quantification with cardiovascular magnetic resonance using "standard deviation from remote" is unreliable: validation in multi-centre multi-vendor data.
Article in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Native T1-mapping using cardiovascular magnetic resonance detects myocardium at risk during the first week following myocardial infarction in a swine model and in patients - comparison to contrast-enhanced cine steady-state free precession.BMC cardiovascular disorders · 2026Article
- Non-invasive pressure-volume loops by cardiovascular magnetic resonance and outcome in ST-elevation myocardial infarction.European heart journal. Imaging methods and practice · 2026Article
- Lumos: Software for Multi-level Multi-reader Comparison of Cardiovascular Magnetic Resonance Late Gadolinium Enhancement Scar Quantification.Journal of imaging informatics in medicine · 2025Article
- Myocardial Entropy and Risk Predictors in Hypertrophic Cardiomyopathy: An Analysis From the NHLBI HCM Registry.Circulation. Cardiovascular imaging · 2025Observational
- Deep learning pipeline for fully automated myocardial infarct segmentation from clinical cardiac MR scans.Radiology advances · 2025Article
- Automated fibrosis segmentation from wideband post-contrastMagnetic resonance in medicine · 2025Article
- Reproducibility of late gadolinium enhancement quantification techniques in ischemic and non-ischemic heart diseases (ReLate study).Frontiers in cardiovascular medicine · 2025Article
- Non-invasive pressure-volume loops provide incremental value to age, sex, and infarct size for predicting adverse cardiac remodelling after ST-elevation myocardial infarction.European heart journal. Imaging methods and practice · 2025Article
- Noninvasive Pressure-Volume Loops Predict Major Adverse Cardiac Events in Heart Failure With Reduced Ejection Fraction.JACC. Advances · 2024Article
- Feasibility of relaxation along a fictitious field in the 2nd rotating frame (TFrontiers in cardiovascular medicine · 2024Article
- Late-gadolinium enhancement is common in older pediatric heart transplant recipients and is associated with lower ejection fraction.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2023Article
- Myocardial Tissue Characterization to Predict Ventricular Arrhythmic Risk: Road Well-Traveled But So Far to Go.JACC. Cardiovascular imaging · 2023Article
- Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images.Frontiers in cardiovascular medicine · 2023Article
- Ex-vivo validation of nine algorithms for quantifying infarcts with late gadolinium enhancement cardiovascular magnetic resonance.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic ResonanceArticle
- Interactive deep learning for myocardial scar segmentation using cardiovascular magnetic resonance.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic ResonanceArticle
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7 authors.
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Abstract
backgroundThe objective of the study was to investigate variability and agreement of the commonly used image processing method "n-SD from remote" and in particular for quantifying myocardial infarction by late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR). LGE-CMR in tandem with the analysis method "n-SD from remote" represents the current reference standard for infarct quantification. This analytic method utilizes regions of interest (ROIs) and defines infarct as the tissue with a set number of standard deviations (SD) above the signal intensity of remote nulled myocardium. There is no consensus on what the set number of SD is supposed to be. Little is known about how size and location of ROIs and underlying signal properties in the LGE images affect results. Furthermore, the method is frequently used elsewhere in medical imaging often without careful validation. Therefore, the usage of the "n-SD" method warrants a thorough validation.
methodsData from 214 patients from two multi-center cardioprotection trials were included. Infarct size from different remote ROI positions, ROI size, and number of standard deviations ("n-SD") were compared with reference core lab delineations.
resultsVariability in infarct size caused by varying ROI position, ROI size, and "n-SD" was 47%, 48%, and 40%, respectively. The agreement between the "n-SD from remote" method and the reference infarct size by core lab delineations was low. Optimal "n-SD" threshold computed on a slice-by-slice basis showed high variability, n = 5.3 ± 2.2.
conclusionThe "n-SD from remote" method is unreliable for infarct quantification due to high variability which depends on different placement and size of remote ROI, number "n-SD", and image signal properties related to the CMR-scanner and sequence used. Therefore, the "n-SD from remote" method should not be used, instead methods validated against an independent standard are recommended.
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