Computational biomechanics: a potential new tool for the vascular surgeon in personalized management

Since their inception, computer models have dramatically impacted practically all aspects of life. In the biomedical arena, they have enabled research both in vivo and in vitro, additionally creating the field of “in silico” (computational) research. Applications of in silico research now extend to models of human respiratory, orthopaedic and cardiovascular systems, with the blue-sky vision of creating a virtual physiological human to expand our knowledge and develop novel innovations to meet clinical needs. In the cardiovascular space, computer modelling, specifically computational fluid dynamics (CFD, calculates shear stress and flow-based metrics) and finite element analysis (FEA, calculates displacements, structural stresses and strains), has allowed better understanding of the structure and function of vascular networks on every scale. In the last decade, significant progress has been made in diagnostic and prognostic tools, as well as planning of intervention for congenital heart disease (CHD), coronary artery disease, aneurysms and other vascular diseases. However, there is a clear pathway to develop these methods for other diseases where quantitative information from CFD or FEA would provide deeper insights into patient-specific prognosis and optimisation of treatment methods. CFD and FEA have been used as research tools to understand aneurysms since the 1990s. This arose from the need for better predictive metrics of aneurysm growth and rupture, to complement geometry-based metrics such as diameter. FEA methods have since evolved, circumventing the issue of major variation in tissue properties across patients. Recently, the FEA-based aneurysm biomechanical ratio (ratio of wall stress to strength) was found to be a strong independent predictor of both abdominal aortic aneurysm rupture and repair. Furthermore, CFD modelling of intraluminal conditions, particularly shear stress, have shown promise in predicting aneurysmal growth and outcome in abdominal aortic, common iliac artery and cerebral aneurysms with their use suggested as an adjunct in clinical guidelines. Presurgical planning of CHD is an established area where CFD and FEA, have shown great potential. Modelling provides pre-surgical assessment of complex CHD cases and prediction of Fontan procedure outcomes. This process involves image acquisition, 3D extraction of cardiac structures, customized design of surgical options and numerical simulations revealing functional performance, to determine the best approach. This pipeline has been integrated into clinical decision-making processes in multiple centres to provide additional patient-specific insights to the clinician. In patients with coronary heart disease, standard non-invasive diagnostic tests such as image-based geometric measurements of coronary stenosis often fail to differentiate patients with intermediate levels of stenosis who require further testing or intervention. Recently, computed-tomography (CT) based blood flow simulations have provided a non-invasive alternative to flow-wire measurements of fractional flow reserve. These computer-based methods provide a new physiological gold standard for assessing the clinical significance of coronary stenosis without the need for invasive imaging and measurement. Furthermore, when shear stress data obtained from CFD simulations is combined with measurements of coronary plaque morphology from imaging, the positive predictive value of clinical outcomes is practically doubled compared to imaging alone. The integration of these tools in platforms that allow clinicians to perform virtual stenting enables optimal intervention strategies to be identified ahead of time and treatments to be bespoke. Despite progress in many areas of clinical medicine and evidence-based management, the consensus for treatment of many vascular pathologies remains unclear. This is particularly true for type B aortic dissections (TBAD), where decision-making remains complex. Classification (Stanford and DeBakey) methods have helped guide treatment, however the effectiveness of endovascular aortic repair in acute TBAD is variable. Risk prediction in TBAD has recently been reviewed with the need for computational frameworks to assist clinical decision-making highlighted. CFD modelling has shown that both high and low shear stresses and the pressure difference between lumens may provide prognostic value in aortic dissection in addition to other CT-based morphological predictors. Decision-making algorithms for TBAD that utilize CFD have been proposed and need to be tested in large cohort studies. Beyond prognosis and treatment planning, new functional indicators to quantify hemodynamic improvements from the intervention and prediction of aortic remodelling have been suggested. Therefore, for TBAD, using computer modelling to better understand the immediate risk, plan timely interventions, design the optimal device and simulate long-term aortic remodelling posttreatment may soon be possible. To realize this vision, management strategies involving engineers, clinicians and scientists must be formulated. Embedding engineers with computer modelling and biomechanics expertise into the clinical team, to work alongside the radiologists, surgeons and wider multidisciplinary line-up, will provide supplementary quantifiable data to aid in clinical decision-making (Fig. 1).