Literature DB >> 34777616

Multiscale simulations of left ventricular growth and remodeling.

Hossein Sharifi1, Charles K Mann1, Alexus L Rockward1, Mohammad Mehri1, Joy Mojumder2, Lik-Chuan Lee2, Kenneth S Campbell3, Jonathan F Wenk1,4.   

Abstract

Cardiomyocytes can adapt their size, shape, and orientation in response to altered biomechanical or biochemical stimuli. The process by which the heart undergoes structural changes-affecting both geometry and material properties-in response to altered ventricular loading, altered hormonal levels, or mutant sarcomeric proteins is broadly known as cardiac growth and remodeling (G&R). Although it is likely that cardiac G&R initially occurs as an adaptive response of the heart to the underlying stimuli, prolonged pathological changes can lead to increased risk of atrial fibrillation, heart failure, and sudden death. During the past few decades, computational models have been extensively used to investigate the mechanisms of cardiac G&R, as a complement to experimental measurements. These models have provided an opportunity to quantitatively study the relationships between the underlying stimuli (primarily mechanical) and the adverse outcomes of cardiac G&R, i.e., alterations in ventricular size and function. State-of-the-art computational models have shown promise in predicting the progression of cardiac G&R. However, there are still limitations that need to be addressed in future works to advance the field. In this review, we first outline the current state of computational models of cardiac growth and myofiber remodeling. Then, we discuss the potential limitations of current models of cardiac G&R that need to be addressed before they can be utilized in clinical care. Finally, we briefly discuss the next feasible steps and future directions that could advance the field of cardiac G&R. © International Union for Pure and Applied Biophysics (IUPAB) and Springer-Verlag GmbH Germany, part of Springer Nature 2021.

Entities:  

Keywords:  Cardiac growth; Cardiomyopathy; Machine learning; Multiscale modeling; Myofiber remodeling; Sarcomeres

Year:  2021        PMID: 34777616      PMCID: PMC8555068          DOI: 10.1007/s12551-021-00826-5

Source DB:  PubMed          Journal:  Biophys Rev        ISSN: 1867-2450


  148 in total

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Review 8.  Computational models of cardiac hypertrophy.

Authors:  Kyoko Yoshida; Jeffrey W Holmes
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9.  Identification of Myocardial Disarray in Patients With Hypertrophic Cardiomyopathy and Ventricular Arrhythmias.

Authors:  Rina Ariga; Elizabeth M Tunnicliffe; Sanjay G Manohar; Masliza Mahmod; Betty Raman; Stefan K Piechnik; Jane M Francis; Matthew D Robson; Stefan Neubauer; Hugh Watkins
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Review 10.  Hypertension in Thyroid Disorders.

Authors:  Eszter Berta; Inez Lengyel; Sándor Halmi; Miklós Zrínyi; Annamária Erdei; Mariann Harangi; Dénes Páll; Endre V Nagy; Miklós Bodor
Journal:  Front Endocrinol (Lausanne)       Date:  2019-07-17       Impact factor: 5.555

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Review 1.  Computational models of ventricular mechanics and adaptation in response to right-ventricular pressure overload.

Authors:  Oscar O Odeigah; Daniela Valdez-Jasso; Samuel T Wall; Joakim Sundnes
Journal:  Front Physiol       Date:  2022-08-24       Impact factor: 4.755

  1 in total

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