ArticleJournal of magnetic resonance imaging : JMRI2025
Improved and Automated Detection of Papillary Muscle Infarction Using Joint Bright- and Black-Blood Late Gadolinium Enhancement MRI.
Article in Journal of magnetic resonance imaging : JMRI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Wideband black- and bright-blood late gadolinium enhancement imaging in patients with implantable cardiac devices at 1.5 T for improved visualization and localization of myocardial injury.European heart journal. Imaging methods and practice · 2026Article
- Clinical applications of co-registered myocardial T2 mapping and dual bright- and black-blood late gadolinium enhancement magnetic resonance imaging.European heart journal. Imaging methods and practice · 2026Article
- SPOT-Cardio: Integrated Application for AI-Powered Automated Myocardial Scar Quantification on Joint Bright- and Black-Blood Late Gadolinium Enhancement MRI Images.Journal of clinical medicine · 2025Article
- Improved and Automated Detection of Papillary Muscle Infarction Using Joint Bright- and Black-Blood Late Gadolinium Enhancement MRI.Journal of magnetic resonance imaging : JMRI · 2025Article
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Authors and funding
20 authors.
Funding
Abstract
backgroundPapillary muscle infarction (PMI) has been linked to significantly increased mortality and is associated with ventricular arrhythmias and mitral regurgitation. Reference bright-blood late gadolinium enhancement (LGE) imaging provides poor scar-to-blood contrast, making PMI visualization challenging. Black-blood LGE imaging overcomes this limitation by improving the blood-scar contrast. PURPOSE: To evaluate a recent co-registered bright- (papillary muscle localization) and black-blood (PMI visualization) sequence (Scar-specific imaging with Preserved myOcardial visualizaTion: SPOT) to improve PMI visualization compared to a reference standard phase-sensitive inversion recovery (PSIR) sequence, and to enable automated PMI detection (auto-PMI). STUDY TYPE: Retrospective. POPULATION: 198 patients with ischemic heart disease were divided into an optimization dataset (N = 127) and a testing dataset (N = 71). FIELD STRENGTH/SEQUENCE: 2D SPOT and PSIR balanced steady-state free precession sequences at 1.5 T. ASSESSMENT: Auto-PMI included: image acquisition, slice selection, endocardial segmentation, blood pool preprocessing, and PMI detection. Three radiologists (8, 5 and 2 years of MRI experience) assessed PMI in SPOT and PSIR images independently. A consensus reading regarding all assessments of both sequences was established. The number of patients with PMI in SPOT and PSIR acquisitions was compared. The diagnostic performances of visual (SPOT and PSIR) and auto-PMI (SPOT) detection were evaluated. Inter- and intra-observer reproducibility of the visual PMI detection was assessed. STATISTICAL TESTS: McNemar test, p-value < 0.05 was considered statistically significant.
resultsIn the testing dataset, significantly more patients with PMI were detected using SPOT compared to PSIR in each session (37 vs. 27, 36 vs. 29, 41 vs. 31, 42 vs. 25). Sensitivity ranges for visual PMI detection were significantly higher using SPOT (89%-100% vs. 61%-82%). SPOT vs. PSIR inter- and intra-observer reproducibility ranges were 77%-80% vs. 71%-77%, and 97% vs. 88%, respectively. Auto-PMI sensitivity was 87%. DATA
conclusionCo-registered bright- and black-blood SPOT imaging improved visual PMI detection and facilitated automated PMI assessment. EVIDENCE LEVEL: 3. Technical Efficacy: Stage 2.
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