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1. Automated Segmentation and 4-D reconstruction of the Heart Left Ventricle from CINE MRI

   Molina, Giovanni ; Velazco-Garcia, Jose D. ; Shah, Dipan ; Becker, Aaron T. ; Tsekos, Nikolaos V. ( October 2019 , IEEE International Conference on Bioinformatics and Bioengineering (BIBE))

   Heart disease is highly prevalent in developed countries, causing 1 in 4 deaths. In this work we propose a method for a fully automated 4D reconstruction of the left ventricle of the heart. This can provide accurate information regarding the heart wall motion and in particular the hemodynamics of the ventricles. Such metrics are crucial for detecting heart function anomalies that can be an indication of heart disease. Our approach is fast, modular and extensible. In our testing, we found that generating the 4D reconstruction from a set of 250 MRI images takes less than a minute. The amount of time saved as a result of our work could greatly benefit physicians and cardiologist as they diagnose and treat patients. Index Terms—Magnetic Resonance Imaging, segmentation, reconstruction, cardiac, machine learning, ventricle 

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2. DeepOrganNet: On-the-Fly Reconstruction and Visualization of 3D / 4D Lung Models from Single-View Projections by Deep Deformation Network

   Wang, Yifan ; Zhong, Zichun ; Hua, Jing ( January 2020 , IEEE transactions on visualization and computer graphics)

   This paper introduces a deep neural network based method, i.e., DeepOrganNet, to generate and visualize fully high-fidelity 3D / 4D organ geometric models from single-view medical images with complicated background in real time. Traditional 3D / 4D medical image reconstruction requires near hundreds of projections, which cost insufferable computational time and deliver undesirable high imaging / radiation dose to human subjects. Moreover, it always needs further notorious processes to segment or extract the accurate 3D organ models subsequently. The computational time and imaging dose can be reduced by decreasing the number of projections, but the reconstructed image quality is degraded accordingly. To our knowledge, there is no method directly and explicitly reconstructing multiple 3D organ meshes from a single 2D medical grayscale image on the fly. Given single-view 2D medical images, e.g., 3D / 4D-CT projections or X-ray images, our end-to-end DeepOrganNet framework can efficiently and effectively reconstruct 3D / 4D lung models with a variety of geometric shapes by learning the smooth deformation fields from multiple templates based on a trivariate tensor-product deformation technique, leveraging an informative latent descriptor extracted from input 2D images. The proposed method can guarantee to generate high-quality and high-fidelity manifold meshes for 3D / 4D lung models; while, all current deep learning based approaches on the shape reconstruction from a single image cannot. The major contributions of this work are to accurately reconstruct the 3D organ shapes from 2D single-view projection, significantly improve the procedure time to allow on-the-fly visualization, and dramatically reduce the imaging dose for human subjects. Experimental results are evaluated and compared with the traditional reconstruction method and the state-of-the-art in deep learning, by using extensive 3D and 4D examples, including both synthetic phantom and real patient datasets. The efficiency of the proposed method shows that it only needs several milliseconds to generate organ meshes with 10K vertices, which has great potential to be used in real-time image guided radiation therapy (IGRT). 

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3. Novel Image Processing to Restore Scattered Light-sheet Microscopic Imaging Technique and its Application for Quantifying Biomechanics

   C Dominguez, T Teranikar ( February 2024 , River Publishers)

   Research of cellular and molecular processes by way of histological methods allows for some insight but comes with a fundamental set of constraints that are challenging to overcome. Traditional histological methods are laborious, as well as severely limiting for in-depth study of developmental processes or disease processes in vivo. In traditional histology, fixing and sectioning tissue necessarily eliminates its dynamic function, while tissue section thickness limits the scope of investigation with conventional imaging tools. Noninvasive in vivo study of tissues and biomarkers is therefore paramount in gaining a fuller understanding of the pathophysiology surrounding conditions like congenital heart disorders. Light-sheet fluorescence microscopy (LSFM) is a powerful and noninvasive optical microscopy tool that can image in vivo tissue function in 4D (3D + time). LSFM boasts benefits such as short pixel dwell time (and therefore minimal photobleaching) while maintaining the ability to image a high dynamic range, as well as deep-tissue optical sectioning. Researchers have been seeking to overcome this problem by developing tissue-clearing techniques to attempt to homogenize the refractive index across the tissue via the removal of light-scattering pigments and lipids. 

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4. 4D physiologically adaptable cardiac patch: A 4-month in vivo study for the treatment of myocardial infarction

   https://doi.org/10.1126/sciadv.abb5067  

   Cui, Haitao ; Liu, Chengyu ; Esworthy, Timothy ; Huang, Yimin ; Yu, Zu-xi ; Zhou, Xuan ; San, Hong ; Lee, Se-jun ; Hann, Sung Yun ; Boehm, Manfred ; et al ( June 2020 , Science Advances)

   There has been considerable progress in engineering cardiac scaffolds for the treatment of myocardial infarction (MI). However, it is still challenging to replicate the structural specificity and variability of cardiac tissues using traditional bioengineering approaches. In this study, a four-dimensional (4D) cardiac patch with physiological adaptability has been printed by beam-scanning stereolithography. By combining a unique 4D self-morphing capacity with expandable microstructure, the specific design has been shown to improve both the biomechanical properties of the patches themselves and the dynamic integration of the patch with the beating heart. Our results demonstrate improved vascularization and cardiomyocyte maturation in vitro under physiologically relevant mechanical stimulation, as well as increased cell engraftment and vascular supply in a murine chronic MI model. This work not only potentially provides an effective treatment method for MI but also contributes a cutting-edge methodology to enhance the structural design of complex tissues for organ regeneration. 

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5. A Study of Gene Expression, Structure, and Contractility of iPSC-Derived Cardiac Myocytes from a Family with Heart Disease due to LMNA Mutation

   https://doi.org/10.1007/s10439-021-02850-8  

   Mehrabi, Mehrsa ; Morris, Tessa A. ; Cang, Zixuan ; Nguyen, Cecilia H. H. ; Sha, Yutong ; Asad, Mira N. ; Khachikyan, Nyree ; Greene, Taylor L. ; Becker, Danielle M. ; Nie, Qing ; et al ( September 2021 , Annals of Biomedical Engineering)

   Genetic mutations to the Lamin A/C gene (LMNA) can cause heart disease, but the mechanisms making cardiac tissues uniquely vulnerable to the mutations remain largely unknown. Further, patients withLMNAmutations have highly variable presentation of heart disease progression and type.In vitropatient-specific experiments could provide a powerful platform for studying this phenomenon, but the use of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) introduces heterogeneity in maturity and function thus complicating the interpretation of the results of any single experiment. We hypothesized that integrating single cell RNA sequencing (scRNA-seq) with analysis of the tissue architecture and contractile function would elucidate some of the probable mechanisms. To test this, we investigated five iPSC-CM lines, three controls and two patients with a (c.357-2A>G) mutation. The patient iPSC-CM tissues had significantly weaker stress generation potential than control iPSC-CM tissues demonstrating the viability of ourin vitroapproach. Through scRNA-seq, differentially expressed genes between control and patient lines were identified. Some of these genes, linked to quantitative structural and functional changes, were cardiac specific, explaining the targeted nature of the disease progression seen in patients. The results of this work demonstrate the utility of combiningin vitrotools in exploring heart disease mechanics.

    

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