3D Ultrasound: seeing is understanding—from imaging to pathophysiology to developing therapies in secondary MR
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".