ArticleLa Radiologia medica2022
FLORA software: semi-automatic LGE-CMR analysis tool for cardiac lesions identification and characterization.
Article in La Radiologia medica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 8 citations in OpenAlex.
- Myocardial Fibrosis in Hypertrophic Cardiomyopathy: Leveraging Quantitative Imaging and Artificial Intelligence for Precision Management.Reviews in cardiovascular medicine · 2026Review
- Evaluation of deep learning-based reconstruction late gadolinium enhancement images for identifying patients with clinically unrecognized myocardial infarction.BMC medical imaging · 2024Article
- The Role of T2 Mapping in Cardiac Amyloidosis.Diagnostics (Basel, Switzerland) · 2024Article
- Practical Guide to Interpreting Cardiac Magnetic Resonance in Patients with Cardiac Masses.Journal of cardiovascular development and disease · 2023Review
- Gender Medicine in Clinical Radiology Practice.Journal of personalized medicine · 2023Review
- Quantitative late gadolinium enhancement cardiac magnetic resonance analysis of the relationship between ablation parameter and left atrial tissue lesion following pulmonary vein isolation.Frontiers in cardiovascular medicine · 2022Article
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeToday there is a growing interest in the quantification of late gadolinium enhancement (LGE) in ischemic and non-ischemic cardiac pathologies. We build an automatic self-made free software FLORA (For Late gadOlinium enhanced aReas clAssification) for the recognition, classification and quantification of LGE areas that allows to improve the observer's performances and that homogenizes the evaluations between different operators. MATERIAL AND
methodsWe have retrospectively selected 120 CMR exams: 40-ischemic with evident scar tissue on LGE sequences; 40-non-ischemic cardiomyopathy; 40-any myocardial alteration on CMR, especially on LGE sequences. FLORA's performance was compared to the radiologist's evaluation.
resultsFLORA identified both ischemic and non-ischemic myocardial lesions in almost all cases (80/80 and 79/80 for the double-Gaussian fit method and fixed-shift method, respectively, with sensitivity and specificity of 100%/98.8% and 55%/50%, respectively). The best results were obtained from the classification of ischemic myocardial damage, which was correctly identified in 85%-95% of cases. FLORA also increases the agreement between observers and allows a quantitative evaluation of transmurality.
conclusionsFLORA has proven to be an applicable tool that improves and facilitates the classification of LGE areas allowing their quantification.
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