How modelling and simulation can deliver new medical insight into cardiovascular systems
Rafiq Somani, area vice president, India and South Asia Pacific, Ansys explains how cardiac device engineering helps understand the behaviour of new devices and providing insight into how cardiovascular devices behave within human bodies despite their variability
Cardiovascular diseases or CVDs are a group of ailments of the heart and blood vessels that include coronary heart disease, cerebrovascular disease, rheumatic heart disease and other conditions. CVDs are the leading cause of death in the world and it takes an estimated 17.9 million lives annually. India is no exception.
Some aspects of the CVD epidemic in India are particular causes of concern, including its accelerated build-up, the early age of disease onset in the population, and the high case fatality rate. In India, the epidemiological transition from predominantly infectious disease conditions to non-communicable diseases has occurred over a rather brief period of time and premature mortality in terms of years of life lost because of CVD is on the rise.
In 2016, the estimated prevalence of CVDs in India was 54.5 million and one in four deaths in India are now because of CVDs with ischemic heart disease and stroke responsible for more than 80 per cent of this burden. The economic impact of this is staggering as well.
To provide safe, reliable and cost-effective medical solutions, consumers and the medical field are turning to treatments that are personalised, participative, predictive and preventive. When healthcare providers optimise treatments for an average person, they are effectively optimising it for no one in particular. As a result, the medical industry is starting to embrace the idea of personalised medicine and in silico testing. Personalised medicine is the idea of tailoring a medical treatment for the individual not the masses.
To achieve this level of optimisation, medical practitioners use simulations, models and digital twins of their patients to perform in silico tests. Medical and pharma worlds have already entered an era in which a growing number of experiments will be done on the computer.
Engineering simulation to the rescue
While providing medical facilities to those in need, there is one sector that stands out: engineering simulation. With the convergence of engineering and medicine, researchers are making new advances in understanding and treating the causes of cardiovascular disease.
Simulation plays an integral role in research in the design of medical devices for cardiovascular applications. Properly validated engineering tools can help to accurately simulate cardiovascular problems of interest. State-of-the-art simulations of the cardiovascular system are based on the integration of clinical observations, theories and predictions across a range of temporal and spatial scales. Interactions can be investigated through computers, also called in silico, to bring new insight about phenomena observed in vitro (in an artificial environment, such as a test tube) and in vivo (via medical testing of a living organism) and to assist in the formulation and validation of new hypothesis.
The nature of such research is highly multidisciplinary, combining aspects of physics, chemistry, mathematics, engineering, computer science, biology and medicine.
Airflow in human nasal passage and sinuses of chronic rhinosinusitis subjects
Several studies have reported that chronic rhinosinusitis (CRS) increases the risk of stroke regardless of age and gender. Chronic sinus congestion can lead to snoring and sleep apnea, which is associated with an increased risk of cardiovascular disease.
Endoscopic surgery is performed on patients with chronic inflammatory disease of the paranasal sinuses to improve sinus ventilation. Little is known about how sinus surgery affects sinonasal airflow. The current understanding of the relationship between nasal geometry (pre- and post-operative) and sinus ventilation is poor. Simulating nasal airflow in this complex patient group will improve the understanding of how surgical strategies affect post-surgical sinus ventilation, as well as providing new understanding for how drug delivery treatments and devices can be designed to target delivery to the sinuses.
Computed tomographic (CT) imaging of human head in a normal, pre- and post-operative subject helps in the patient specific simulation modelling. With simulation, researchers can study the conditioning of the nasal passage airflow and particle transport to better understand the post-operative environment when compared with a healthy passage. Using omputational fluid dynamics (CFD) researchers can simulate, airflow, temperature, humidity and particle transport that can provide a qualitative and quantitative assessment of surgery.
The nasal passage geometry can be reconstructed from computed tomographic imaging from healthy normal, pre-operative, and post-operative subjects giving the surgery the luxury to test various approaches at no risk for the patient and select the best possible one. Transient air flow through the nasal passage during calm breathing or various activities including exercising can be simulated. Subject-specific differences in ventilation of the nasal passage are then visible. When this is done, it can be observed that the velocity magnitude at ostium was different between left and right airway.
In functional endoscopic sinus surgery (FESS), airflow in post-surgical subjects, airflow at the maxillary sinus ostium is up to ten times higher during inspiration. In a Lothrop procedure, airflow at the frontal sinus ostium can be up to four times higher during inspiration. In both post-operative subjects, airflow at ostium was not quasi-steady. The subject-specific effect of the surgery on sinonasal interaction evaluated through airflow simulations may have important consequences for pre- and post-surgical assessment and surgical planning, and design for improvement of the delivery efficiency of nasal therapeutics.
Patient-specific model of aortic valves to identify and understand role of influential parameters
The aortic valve is a valve in the human heart between the left ventricle and the aorta. It is one of the two semilunar valves of the heart, the other being the pulmonary valve. The heart has four valves; the other two are the mitral and the tricuspid valves. The most common congenital cardiac malformation in adults is Bicuspid aortic valve is or the BAV. It is strongly associated with vascular complications such as aortic root dilatation, thoracic aortic aneurysm and aortic dissection. Accurately estimating changes in basic hemodynamic parameters and reducing the risk of aortopathy and valve dysfunction can improve long-term BAV patient outcomes.
Defining parameters in clinical conditions is very difficult and at times not even possible to measure. Extensively validated computer modelling based on patient-specific CT images can be used to define parameters. The opening and closing of the aortic valve is the result of complex interactions between valve leaflets, the aortic root and blood driven by the electrophysiological behaviour of the heart regulating the contractions of this organ. Therefore, to study the events that take place as the blood flows through the aortic valve, computer-based fluid-structure interaction simulation is used with a flexible aortic wall and flexible aortic valve leaflets.
Multiphysics simulation can be used to determine the flow pattern, turbulence, stagnation area, shear stress, wall deformation and turbulence eddy dissipation based on a numerical solution of the Navier-Stokes and continuity equations. Fluid Structure Interaction (FSI) evaluated the degree to which geometric changes of a dilated aorta influence the flow distribution and basic hemodynamic parameters in patients with BAV.
Patient specific blood flows
One complicating factor in aortic flow modelling is the application of accurate outflow boundary conditions. Specialised conditions are required because the flow split at a bifurcation is controlled by downstream organ demand, not the bifurcation geometry. Without a specialised condition, an analyst will not have a proper understanding of the baseline flow patterns and how an implanted device affects those patterns. Simulation can create a detailed geometric model of the entire cardiovascular system, extending from the heart to the capillaries giving the medical device designers or the clinicians more insight before making life or death decision.
Babies with heart defects
When a baby is born with a single-ventricle heart defect, the prognosis is grim. The child will need multiple surgeries to rewire its cardiovascular system to work with one ventricle. Clinical studies show that the long-term survival rate of these procedures varies wildly. This exists because surgeons have a few options when rewiring the cardiovascular system. However, they have no way to know which the best option for each patient is. Using accurate simulation in conjunction with skilled surgery will increase the effectiveness of these procedures and provide the young patients with better quality of life.
Surgeons at the Shanghai Children’s Medical Center use Ansys CFD to determine the optimal way to perform these surgeries for each patient. This example of personalised medicine results in improved surgical effectiveness and a better quality of life for each child.
Conclusion
With more than 30 per cent of all deaths due to cardiovascular or cardiac problems, the healthcare industry invests massively to prevent diseases, treat patients and maximise recovery. However, innovative implantable cardiovascular devices like are slow to reach the patients because of extensive (pre) clinical testing and necessary compliance with the regulatory authorities.
Clinically validated, non-invasive modelling of the pressure drop across a lesion or a blockage gives clinical cardiologists a quantitative metric to help them decide whether to perform invasive procedures like insertion of stents or cardiac bypass surgery or to simply medicate those patients with less severe conditions. Reducing discomfort, invasiveness and risk, as well as increasing successful treatment outcomes, is of obvious value to patients. The potential monetary savings involved in simplifying the procedure, performing fewer stent procedures, and avoiding costly bypass surgeries are enormous to a world increasingly overwhelmed by healthcare costs.
In cardiac device engineering, understanding the behaviour of a new device is important and it can benefit greatly from medical engineering simulation or in silico medicine. Reliable computer modelling helps researchers to confidently invent and improve implantable materials that co-exist without complications with organs, tissues and blood. Simulation software uniquely integrates patient specific fluid, structural, thermal and electrophysiologics analysis for extended cohort of virtual patients into a single environment, providing insight into how cardiovascular devices behave within human bodies despite their variability. It provides flexible and open solutions that can be adapted to solve even the most challenging problems facing the biomedical engineers of today.
The decision about how to treat a cardiovascular lesion can be a determining factor in the lifespan and also the quality of life of a patient. The choice to opt for cardiac bypass surgery, perform stent insertion or simply treat with medication can make a big difference in the end result but the decision might be tricky, and the doctor may welcome more insight about his/her specific patient.
If you are the person lying on the table in the cardiac catheterisation laboratory, you would definitely want your doctor to have all the best data possible about yourself, not a generic patient, to make his or her treatment decision for you. This is where technology and simulation can be of assistance…to provide you with the best possible option that is available.