Novel Method to Track Soft Tissue Deformation by Micro-Computed Tomography: Application to the Mitral Valve

Pierce, Eric T.; Bloodworth, Charles H.; Naran, Ajay; Easley, Thomas F.; Jensen, Morten Ø.; Yoganathan, Ajit P.

doi:10.1007/s10439-015-1499-9

Cited by 13 publications

(10 citation statements)

References 29 publications

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“…20 Strain in the belly region was found to be 47.1±21.5% (n = 61 markers). This agrees well with previous in vitro studies by Jimenez et al (36±14%) 15 , He et al (42±20%) 12 , and Sacks et al (47±10%) 24 .…”

Section: Resultsmentioning

confidence: 92%

“…Following the finite element simulation of MV closure, the accuracy of the systolic MV geometry can be directly compared to the experimental results using discrete marker positions from the microCT scans. Additionally, the fiducial markers can be used to measure directional strain in response to both levels of loading 20 , and fine-tune the material properties of the FE model.…”

Section: Discussionmentioning

confidence: 99%

“…Described in previously published work by our group, these markers enable the tracking of discrete features, and the calculation of strain between different microCT scans under different loading conditions ( Figure 4B ). 20 In a modeling setting, this allows the mapping of additional microstructural data to discrete locations on the leaflet surface, as well as precise geometric manipulation of the model. Following marker application, the CLHS was then loaded into a Siemens Inveon microCT scanner (Siemens Corp, Malvern, PA, USA) and scanned with parameters optimized for soft tissue (80 keV, 500 uA, ~40 micron isotropic voxel size).…”

Section: Methodsmentioning

confidence: 99%

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Ex Vivo Methods for Informing Computational Models of the Mitral Valve

et al. 2016

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Computational modeling of the mitral valve (MV) has potential applications for determining optimal MV repair techniques and risk of recurrent mitral regurgitation. Two key concerns for informing these models are (1) sensitivity of model performance to the accuracy of the input geometry, and, (2) acquisition of comprehensive data sets against which the simulation can be validated across clinically relevant geometries. Addressing the first concern, ex vivo micro-computed tomography (microCT) was used to image MVs at high resolution (~40 micron voxel size). Because MVs distorted substantially during static imaging, glutaraldehyde fixation was used prior to microCT. After fixation, MV leaflet distortions were significantly smaller (p<0.005), and detail of the chordal tree was appreciably greater. Addressing the second concern, a left heart simulator was designed to reproduce MV geometric perturbations seen in vivo in functional mitral regurgitation and after subsequent repair, and maintain compatibility with microCT. By permuting individual excised ovine MVs (n=5) through each state (healthy, diseased and repaired), and imaging with microCT in each state, a comprehensive data set was produced. Using this data set, work is ongoing to construct and validate high-fidelity MV biomechanical models. These models will seek to link MV function across clinically relevant states.

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Section: Resultsmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Ex Vivo Methods for Informing Computational Models of the Mitral Valve

et al. 2016

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“…Methodologies for in vitro MV imaging, image processing, and FE mesh generation have been described previously in detail . Briefly, three freshly excised ovine MV specimens were sutured to an adjustable annulus holder by a ford interlocking stitch and mounted into an extensively validated cylindrical left heart simulator . Prior to imaging, the leaflets were instrumented with approximately 100 high‐contrast fiducial markers uniformly distributed over the entire leaflet surface (Figure ), and the papillary muscles were attached to adjustable rods.…”

Section: Methodsmentioning

confidence: 99%

“…[55][56][57][58][59][60] Briefly, three freshly excised ovine MV specimens were sutured to an adjustable annulus holder by a ford interlocking stitch and mounted into an extensively validated cylindrical left heart simulator. 41,[61][62][63] Prior to imaging, the leaflets were instrumented with approximately 100 high-contrast fiducial markers uniformly distributed over the entire leaflet surface ( Figure 2), and the papillary muscles were attached to adjustable rods. The system was then installed into a pulsatile flow loop for hemodynamic tuning to match the parameters of healthy left ventricular function, and the positions of the papillary muscles were adjusted to achieve normal coaptation behavior.…”

Section: Data Collection and Processing 221 In Vitromentioning

confidence: 99%

A noninvasive method for the determination of in vivo mitral valve leaflet strains

Rego

Khalighi

Drach

et al. 2018

Numer Methods Biomed Eng

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Assessment of mitral valve (MV) function is important in many diagnostic, prognostic, and surgical planning applications for treatment of MV disease. Yet, to date, there are no accepted noninvasive methods for determination of MV leaflet deformation, which is a critical metric of MV function. In this study, we present a novel, completely noninvasive computational method to estimate MV leaflet in-plane strains from clinical-quality real-time three-dimensional echocardiography (rt-3DE) images. The images were first segmented to produce meshed medial-surface leaflet geometries of the open and closed states. To establish material point correspondence between the two states, an image-based morphing pipeline was implemented within a finite element (FE) modeling framework in which MV closure was simulated by pressurizing the open-state geometry, and local corrective loads were applied to enforce the actual MV closed shape. This resulted in a complete map of local systolic leaflet membrane strains, obtained from the final FE mesh configuration. To validate the method, we utilized an extant in vitro database of fiducially labeled MVs, imaged in conditions mimicking both the healthy and diseased states. Our method estimated local anisotropic in vivo strains with less than 10% error and proved to be robust to changes in boundary conditions similar to those observed in ischemic MV disease. Next, we applied our methodology to ovine MVs imaged in vivo with rt-3DE and compared our results to previously published findings of in vivo MV strains in the same type of animal as measured using surgically sutured fiducial marker arrays. In regions encompassed by fiducial markers, we found no significant differences in circumferential(P = 0.240) or radial (P = 0.808) strain estimates between the marker-based measurements and our novel noninvasive method. This method can thus be used for model validation as well as for studies of MV disease and repair.

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