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Enregistrement W2299589870 · doi:10.1093/ehjci/jew029

3D Ultrasound: seeing is understanding—from imaging to pathophysiology to developing therapies in secondary MR

2016· letter· en· W2299589870 sur OpenAlexaff
Jacob P. Dal‐Bianco, Philipp E. Bartko, Jonathan Beaudoin, Elena Aïkawa, Joyce Bischoff, Robert A. Levine

Notice bibliographique

RevueEuropean Heart Journal - Cardiovascular Imaging · 2016
Typeletter
Langueen
DomaineMedicine
ThématiqueCardiac Valve Diseases and Treatments
Établissements canadiensUniversité Laval
Organismes subventionnairesNational Heart, Lung, and Blood InstituteNational Institutes of HealthAustrian Science FundFondation Leducq
Mots-clésMedicineChordae tendineaeMitral regurgitationCardiologyPathophysiologyUltrasoundHypertrophic cardiomyopathyMitral valveInternal medicineMitral valve repairRadiology

Résumé

récupéré en direct d'OpenAlex

There is a wide variability in chordal anatomy, which makes consistent non-invasive anatomic labelling and quantification difficult,1 but in the current issue of the European Heart Journal - Cardiovascular Imaging a group of very experienced investigators led by Dr Roberto Lang present an intriguing use of 3D transesophageal echocardiography (3D-TEE) to assess chordae non-invasively.2 Similar to mitral valve (MV) leaflets, chordae adapt to altered loading conditions,3,4 and now Obase et al. report that chordal remodelling appears to contribute to secondary mitral regurgitation (MR) depending on whether primary chords elongate (=less MR) or shorten (=more MR)2: with a validated and reproducible 3D-TEE method that identifies and measures primary chordae,5 the authors compared chordal lengths in normal subjects (n = 20) with those in patients with secondary MR (n = 38) in the setting of ischaemic (n = 16) and non-ischaemic cardiomyopathy (CMP; n = 22). By subdividing secondary MR patients by MR severity, they found that shorter chordae to the anterior MV leaflet were associated with more MR. Longer chordae to the posterior MV leaflet, on the other hand, were associated with less MR. No difference in primary chordal lengths was found comparing ischaemic vs. non-ischaemic CMP patients in the setting of similar MR severity.2 It is worth pointing out that such a detailed study of chordal anatomy and quantification has been restricted historically mostly to anatomic and pathological specimens1,6; the innovative use of 3D-TEE by Lang's group now brings this field into the non-invasive, in vivo arena with important implications. The findings of Obase et al. come at a time of growing recognition that the MV apparatus is a dynamic structure responding to pathological triggers, with adaptation of its components the chordae,3–5 the MV leaflets,3,4,7,8 and the MV annulus.9,10 These triggers can be mechanical tissue stretch (tethering) due to left ventricular (LV) enlargement and dysfunction,11 MR jet turbulence and inflammation in the setting of, for example, ischaemic cytokine release.12,13 Chordae tendineae are fibrous tissue strings that connect the MV leaflets to the papillary muscles (PM) and LV. Rudimentary chordae develop by Week 11, and they subsequently grow to match the needs of the growing heart to an average length and thickness of, respectively, ∼20 and 1–2 mm (anterior secondary chordae).1,3 The chordal core is made of collagen (∼80%) and elastin fibres, and the surface is covered by endothelial cells. The tensor modulus and the point of lock-up are influenced by the amount of collagen crimping and elastin interaction.14,15 There are two types of chordae, primary and secondary, and in concert they ensure a stable anterior and posterior MV leaflet coaptation and thus a tight leaflet seal, and they dampen physical leaflet stress.14,16 Primary chordae are thin and collagen dense, and they attach to the leaflet edges, preventing leaflet tip flail; secondary chordae are thick with tightly crimped collagen, which makes them more flexible,17 and they insert into a system of continuous collagen fibres in the leaflet body that distributes chordal force to the MV annulus.18 Experimental animal data have demonstrated that chordal adaptation occurs over time in tethered MVs with and without LV ischemia.3,4 In both scenarios chordae were found to be significantly thicker and there was evidence for chordal endothelial-mesenchymal transformation,19 a process in which normally quiescent endothelial cells become activated, express α-smooth muscle actin, enter the chordal interstitium and start to produce extracellular matrix (ECM) such as collagen.3,4 Tethered chordae were found to be longer, although the measured chords were secondary (strut) chordae.3 Experimental and human data support the concept that chordae adapt to stretch and ischaemia but we are only beginning to understand the triggers, regulatory pathways and resulting cell and tissue changes including the associated altered biomechanics.15 Adaptive changes are also likely different in primary vs. secondary chordae: crimped collagen makes secondary chordae flexible, but a remodelled chordal ECM with newly deposited collagen may negatively alter the tissue architecture, favouring early systolic lock-up. The echo correlate is the tethered ‘hockey-stick’ configuration of the anterior MV leaflet observed in patients with functional MR,20 and indeed such chordae can be cut to reduce MR.21 How adaptation affects the primary chordae and what drives them to shorten or elongate is unknown.2 Without doubt further investigations are needed to understand the natural history and mechanisms of chordal adaptation and why, for example, it is effective in physiological cardiac growth, but likely counterproductive in secondary MR. Obase et al.'s 3D-TEE work2,5 is important as it may provide an immediate clinical tool to further optimize MV repair strategies.22,23 It also provides an imaging tool to follow chordal adaptation non-invasively over time; when combined with cellular, histological and biomechanical analyses, this will allow to explore the mechanisms of chordal adaptation. The aim is to identify modifiable regulatory chordal adaptation pathways, similar to the TGF-β targeting in Marfan syndrome. The goal is to find therapies that modulate chordal adaptation towards maintaining durable tissue architecture and fibre composition that provide optimal MV leaflet coaptation with minimal MV leaflet stress. This work is supported in part by grant 07CVD04 of the Leducq Foundation, Paris, France, for the Leducq Transatlantic MITRAL Network, and by National Institutes of Health grants K24 HL67434, R01 HL72265, and HL109506. Additional support was from an American Society of Echocardiography Career Development Award and an Erwin-Schrödinger Stipend (FWF Austrian Science Fund). Conflict of interest: none declared.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,011
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,014

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,011
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,002
Communication savante0,0020,004
Science ouverte0,0010,001
Intégrité de la recherche0,0110,016
Charge utile insuffisante (le modèle a refusé de juger)0,0040,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,030
Tête enseignante GPT0,301
Écart entre enseignants0,271 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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