Fully automated tracking of cardiac structures using radiopaque markers and high-frequency videofluoroscopy in an in vivo ovine model: from three-dimensional marker coordinates to quantitative analyses

Intrinsically radiopaque biomaterial assortments: a short review on the physical principles, X-ray imageability, and state-of-the-art developments

X-ray attenuation ability, otherwise known as radiopacity of a material, could be indisputably tagged as the central and decisive parameter that produces contrast in an X-ray image. Radiopaque biomaterials are vital in the healthcare sector that helps clinicians to track them unambiguously during pre and post interventional radiological procedures. Medical imaging is one of the most powerful resources in the diagnostic sector that aids improved treatment outcomes for patients. Intrinsically radiopaque biomaterials enable themselves for visual targeting/positioning as well as to monitor their fate and further provide the radiologists with critical insights about the surgical site. Moreover, the emergence of advanced real-time imaging modalities is a boon to the contemporary healthcare systems that allow to perform minimally invasive surgical procedures and thereby reduce the healthcare costs and minimize patient trauma. X-ray based imaging is one such technologically upgraded diagnostic tool with many variants like digital X-ray, computed tomography, digital subtraction angiography, and fluoroscopy. In light of these facts, this review is aimed to briefly consolidate the physical principles of X-ray attenuation by a radiopaque material, measurement of radiopacity, classification of radiopaque biomaterials, and their recent advanced applications.

In Vivo Image-Based 4D Modeling of Competent and Regurgitant Mitral Valve Dynamics

BACKGROUND

In vivo characterization of mitral valve dynamics relies on image analysis algorithms that accurately reconstruct valve morphology and motion from clinical images. The goal of such algorithms is to provide patient-specific descriptions of both competent and regurgitant mitral valves, which can be used as input to biomechanical analyses and provide insights into the pathophysiology of diseases like ischemic mitral regurgitation (IMR).

OBJECTIVE

The goal is to generate accurate image-based representations of valve dynamics that visually and quantitatively capture normal and pathological valve function.

METHODS

We present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE), an imaging modality used for pre-operative surgical planning of mitral interventions. The framework integrates groupwise multi-atlas label fusion and template-based medial modeling with Kalman filtering to generate quantitatively descriptive and temporally consistent models of valve dynamics.

RESULTS

The algorithm is evaluated on rt-3DE data series from 28 patients: 14 with normal mitral valve morphology and 14 with severe IMR. In these 28 data series that total 613 individual 3DE images, each 3D mitral valve segmentation is validated against manual tracing, and temporal consistency between segmentations is demonstrated.

CONCLUSIONS

Automated 4D image analysis allows for reliable non-invasive modeling of the mitral valve over the cardiac cycle for comparison of annular and leaflet dynamics in pathological and normal mitral valves. Future studies can apply this algorithm to cardiovascular mechanics applications, including patient-specific strain estimation, fluid dynamics simulation, inverse finite element analysis, and risk stratification for surgical treatment.

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

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.