Quest for cardiovascular interventions: precise modeling and 3D printing of heart valves.
Rajat VashisthaPrasoon KumarArun Kumar DangiNaveen SharmaDeepak ChhabraPratyoosh ShuklaPublished in: Journal of biological engineering (2019)
Digitalization of health care practices is substantially manifesting itself as an effective tool to diagnose and rectify complex cardiovascular abnormalities. For cardiovascular abnormalities, precise non-invasive imaging interventions are being used to develop patient specific diagnosis and surgical planning. Concurrently, pre surgical 3D simulation and computational modeling are aiding in the effective surgery and understanding of valve biomechanics, respectively. Consequently, 3D printing of patient specific valves that can mimic the original one will become an effective outbreak for valvular problems. Printing of these patient-specific tissues or organ components is becoming a viable option owing to the advances in biomaterials and additive manufacturing techniques. These additive manufacturing techniques are receiving a full-fledged support from burgeoning field of computational fluid dynamics, digital image processing, artificial intelligence, and continuum mechanics during their optimization and implementation. Further, studies at cellular and molecular biomechanics have enriched our understanding of biomechanical factors resulting in valvular heart diseases. Hence, the knowledge generated can guide us during the design and synthesis of biomaterials to develop superior extra cellular matrix, mimicking materials that can be used as a bioink for 3D printing of organs and tissues. With this notion, we have reviewed current opportunities and challenges in the diagnosis and treatment of heart valve abnormalities through patient-specific valve design via tissue engineering and 3D bioprinting. These valves can replace diseased valves by preserving homogeneity and individuality of the patients.
Keyphrases
- aortic valve
- tissue engineering
- healthcare
- artificial intelligence
- aortic valve replacement
- transcatheter aortic valve replacement
- aortic stenosis
- transcatheter aortic valve implantation
- deep learning
- atrial fibrillation
- heart failure
- primary care
- end stage renal disease
- ejection fraction
- machine learning
- gene expression
- big data
- physical activity
- minimally invasive
- newly diagnosed
- chronic kidney disease
- mitral valve
- high resolution
- finite element analysis
- prognostic factors
- coronary artery bypass
- quality improvement
- left ventricular
- health information
- case control