2021
DOI: 10.1186/s12968-021-00800-w
|View full text |Cite
|
Sign up to set email alerts
|

Mitral valve prolapse morphofunctional features by cardiovascular magnetic resonance: more than just a valvular disease

Abstract: Introduction Mitral valve (MV) prolapse (MVP) is a primary valvular abnormality. We hypothesized that additionally there are concomitant abnormalities of the left ventricle (LV) and MV apparatus in this entity even in the absence of significant mitral regurgitation (MR). Objective To characterize MV and LV anatomic and functional features in MVP with preserved LV ejection fraction, with and without significant MR, using cardiovascular magnetic reso… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
18
0
1

Year Published

2022
2022
2024
2024

Publication Types

Select...
9

Relationship

0
9

Authors

Journals

citations
Cited by 20 publications
(21 citation statements)
references
References 39 publications
0
18
0
1
Order By: Relevance
“…The flattening of the mitral annulus increases mechanical stretch on the mitral leaflets [37] and PM causing PM elongation and resulting in leaflet degeneration, regional hypertrophy and subsequent fibrosis [4,38]. This hypothesis is further supported by CMR findings where LGE enhancement is confirmed in the areas prone to mechanical stretch [3,15] (Fig. 2).…”
Section: Ventricular Arrhythmias In Mad: Origin Triggers and Anatomic...mentioning
confidence: 81%
“…The flattening of the mitral annulus increases mechanical stretch on the mitral leaflets [37] and PM causing PM elongation and resulting in leaflet degeneration, regional hypertrophy and subsequent fibrosis [4,38]. This hypothesis is further supported by CMR findings where LGE enhancement is confirmed in the areas prone to mechanical stretch [3,15] (Fig. 2).…”
Section: Ventricular Arrhythmias In Mad: Origin Triggers and Anatomic...mentioning
confidence: 81%
“…However, no correlation between these findings and VA was reported [29]. Finally, in another study evaluating MVP patients using CMR, Daza et al [42] found that, compared to controls, MVP patients had LV enlargement, basal inferolateral hypertrophy, increased basal longitudinal strain, particularly in the anterior, anterolateral, and inferolateral segments, and more frequently MAD, regardless of the presence of significant MR and also in the presence of borderline MVP, concluding that MVP is a complex disease that involves not only the valve, but also the LV and should be seen as a "ventriculo-mitral unit". CMR can help in stratifying MVP patients at risk for malignant arrhythmias as it allows the detection of either focal or diffuse fibrosis that may be responsible for reentry circuits, providing also evidence of early structural and functional remodeling that may evolve to fibrosis, although these findings need wider clinical investigation.…”
Section: Cardiac Magnetic Resonancementioning
confidence: 96%
“…CMR is the gold standard for LV and right ventricular volumetric assessment. CMR can also provide additional and more precise information on mitral valve characteristics, is more sensitive in MAD and curling identification [31], localized hypertrophy [14,42], and LV myocardial strain [42], although it has a poorer performance than TTE. Tissue characterization is another piece of the MVP puzzle that CMR adds.…”
Section: Cardiac Magnetic Resonancementioning
confidence: 99%
“…The Gerald M. Prohost award for the best scientific manuscript for 2021 went to Dr. Theo Pezel and colleagues for their study on the prognostic value of vasodilator stress perfusion CMRafter inconclusive stress testing [ 32 ]. Dr Angelica Romero Daza and colleagues were the Pohost runner’s up for their article on assessment of morpho-functional features of mitral valve prolapse on CMR [ 33 ]. The Dudley Pennell award for the manuscript contributing the most to the June 2021 JCMR impact factor (currently 5.364) was presented to Dr Wnjia Bai and colleagues for their article on automated CMR image analysis by fully convolutional neural networks [ 34 ].…”
Section: Other Activitiesmentioning
confidence: 99%