Thoracic Stent Graft Numerical Models To Virtually Simulate Thoracic Endovascular Aortic Repair: A Scoping Review.

OBJECTIVE: Pre-procedural planning of thoracic endovascular aortic repair (TEVAR) may implement computational adjuncts to predict technical and clinical outcomes. The aim of this scoping review was to explore the currently available TEVAR procedure and stent graft modelling options. DATA SOURCES: PubMed (MEDLINE), Scopus, and Web of Science were systematically searched (English language, up to 9 December 2022) for studies presenting a virtual thoracic stent graft model or TEVAR simulation. REVIEW METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) was followed. Qualitative and quantitative data were extracted, compared, grouped, and described. Quality assessment was performed using a 16 item rating rubric. RESULTS: Fourteen studies were included. Among the currently available in silico simulations of TEVAR, severe heterogeneity exists in study characteristics, methodological details, and evaluated outcomes. Ten studies (71.4%) were published during the last five years. Eleven studies (78.6%) included heterogeneous clinical data to reconstruct patient specific aortic anatomy and disease (e.g., type B aortic dissection, thoracic aortic aneurysm) from computed tomography angiography imaging. Three studies (21.4%) constructed idealised aortic models with literature input. The applied numerical methods consisted of computational fluid dynamics analysing aortic haemodynamics in three studies (21.4%) and finite element analysis analysing structural mechanics in the others (78.6%), including or excluding aortic wall mechanical properties. The thoracic stent graft was modelled as two separate components (e.g., graft, nitinol) in 10 studies (71.4%), as a one component homogenised approximation (n = 3, 21.4%), or including nitinol rings only (n = 1, 7.1%). Other simulation components included the catheter for virtual TEVAR deployment and numerous outcomes (e.g., Von Mises stresses, stent graft apposition, drag forces) were evaluated. CONCLUSION: This scoping review identified 14 severely heterogeneous TEVAR simulation models, mostly of intermediate quality. The review concludes there is a need for continuous collaborative efforts to improve the homogeneity, credibility, and reliability of TEVAR simulations.

A numerical investigation to evaluate the washout of blood compartments in a total artificial heart.

Total artificial heart (TAH) represents the only valid alternative to heart transplantation, whose number is continuously increasing in recent years. The TAH used in this work, is a biventricular pulsatile, electrically powered, hydraulically actuated flow pump with all components embodied in a single device. One of the major issues for TAHs is the washout capability of the device, strictly correlated with the presence of blood stagnation sites. The aim of this work was to develop a numerical methodology to study the washout coupled with the fluid dynamics evaluation of a total artificial heart under nominal working conditions. The first part of this study focussed on the CT scan analysis of the hybrid membrane kinematics during TAH operation, which was replicated with a fluid-structure interaction simulation in the second part. The difference in percentage between the in vitro and in silico flow rates and stroke volume is 9.7% and 6.3%, respectively. An injection of contrast blood was simulated, and a good washout performance was observed and quantified with the volume fraction of the contrast blood still in the ventricle. The left chamber of the device showed a superior washout performance, with a contrast volume still inside the device after four washout cycles of 6.2%, with the right chamber showing 15%.

Numerical Approach to Study the Behavior of an Artificial Ventricle: Fluid-Structure Interaction Followed By Fluid Dynamics With Moving Boundaries.

Heart failure is a progressive and often fatal pathology among the main causes of death in the world. An implantable total artificial heart (TAH) is an alternative to heart transplantation. Blood damage quantification is imperative to assess the behavior of an artificial ventricle and is strictly related to the hemodynamics, which can be investigated through numerical simulations. The aim of this study is to develop a computational model that can accurately reproduce the hemodynamics inside the left pumping chamber of an existing TAH (Carmat-TAH) together with the displacement of the leaflets of the biological aortic and mitral valves and the displacement of the pericardium-made membrane. The proposed modeling workflow combines fluid-structure interaction (FSI) simulations based on a fixed grid method with computational fluid dynamics (CFD). In particular, the kinematics of the valves is accounted for by means of a dynamic mesh technique in the CFD. The comparison between FSI- and CFD-calculated velocity fields confirmed that the presence of the valves in the CFD model is essential for realistically mimicking blood dynamics, with a percentage difference of 2% during systole phase and 13% during the diastole. The percentage of blood volume in the CFD simulation with a shear stress above the threshold of 50 Pa is less than 0.001%. In conclusion, the application of this workflow to the Carmat-TAH provided consistent results with previous clinical studies demonstrating its utility in calculating local hemodynamic quantities in the presence of complex moving boundaries.

Shear Stress Quantification in Tissue Engineering Bioreactor Heart Valves: A Computational Approach.

Tissue-engineered heart valves can grow, repair, and remodel after implantation, presenting a more favorable long-term solution compared to mechanical and porcine valves. Achieving functional engineered valve tissue requires the maturation of human cells seeded onto valve scaffolds under favorable growth conditions in bioreactors. The mechanical stress and strain on developing valve tissue caused by different pressure and flow conditions in bioreactors are currently unknown. The aim of this study is to quantify the wall shear stress (WSS) magnitude in heart valve prostheses under different valve geometries and bioreactor flow rates. To achieve this, this study used fluid-structure interaction simulations to obtain the valve's opening geometries during the systolic phase. These geometries were then used in computational fluid dynamics simulations with refined near-wall mesh elements and ranges of prescribed inlet flow rates. The data obtained included histograms and regression curves that characterized the distribution, peak, and median WSS for various flow rates and valve opening configurations. This study also found that the upper region of the valve near the commissures experienced higher WSS magnitudes than the rest of the valve.

Improving early detection of keratoconus by Non Contact Tonometry. A computational study and new biomarkers proposal.

Keratoconus is a progressive ocular disorder affecting the corneal tissue, leading to irregular astigmatism and decreased visual acuity. The architectural organization of corneal tissue is altered in keratoconus, however, data from ex vivo testing of biomechanical properties of keratoconic corneas are limited and it is unclear how their results relate to true mechanical properties in vivo. This study explores the mechanical properties of keratoconic corneas through numerical simulations of non-contact tonometry (NCT) reproducing the clinical test of the Corvis ST device. Three sensitivity analyses were conducted to assess the impact of corneal material properties, size, and location of the pathological area on NCT results. Additionally, novel asymmetry-based indices were proposed to better characterize corneal deformations and improve the diagnosis of keratoconus. Our results show that the weakening of corneal material properties leads to increased deformation amplitude and altered biomechanical response. Furthermore, asymmetry indices offer valuable information for locating the pathological tissue. These findings suggest that adjusting the Corvis ST operation, such as a camera rotation, could enhance keratoconus detection and provide insights into the relative position of the affected area. Future research could explore the application of these indices in detecting early-stage keratoconus and assessing the fellow eye's risk for developing the pathology.

On the necessity to include arterial pre-stress in patient-specific simulations of minimally invasive procedures.

Transcatheter aortic valve implantation (TAVI) and thoracic endovascular aortic repair (TEVAR) are minimally invasive procedures for treating aortic valves and diseases. Finite element simulations have proven to be valuable tools in predicting device-related complications. In the literature, the inclusion of aortic pre-stress has not been widely investigated. It plays a crucial role in determining the biomechanical response of the vessel and the device-tissue interaction. This study aims at demonstrating how and when to include the aortic pre-stress in patient-specific TAVI and TEVAR simulations. A percutaneous aortic valve and a stent-graft were implanted in aortic models reconstructed from patient-specific CT scans. Two scenarios for each patient were compared, i.e., including and neglecting the wall pre-stress. The neglection of pre-stress underestimates the contact pressure of 48% and 55%, the aorta stresses of 162% and 157%, the aorta strains of 77% and 21% for TAVI and TEVAR models, respectively. The stent stresses are higher than 48% with the pre-stressed aorta in TAVI simulations; while, similar results are obtained in TEVAR cases. The distance between the device and the aorta is similar with and without pre-stress. The inclusion of the aortic wall pre-stress has the capability to give a better representation of the biomechanical behavior of the arterial tissues and the implanted device. It is suggested to include this effect in patient-specific simulations replicating the procedures.

A finite element model of the embryonic zebrafish heart electrophysiology.

BACKGROUND AND OBJECTIVE: In the last 30 years, a growing interest has involved the study of zebrafish thanks to its physiological characteristics similar to those of humans. The aim of the following work is to create an electrophysiological computational model of the zebrafish heart and lay the foundation for the development of an in-silico model of the zebrafish heart that will allow to study the correlation between pathologies and drug administration with the main electrophysiological parameters as the ECG signal. METHODS: The model considers a whole body and the two chambers of three days post fertilization (3 dpf) zebrafish. A four-variable phenomenological action potential model describes the action potential of different heart regions. Tissue conductivity was calibrated to reproduce the experimentally described activation sequence. RESULTS: The model is able to correctly reproduce the activation sequence and times found in literature, with activation of the atrium and ventricle that correspond to 36 and 59 ms, respectively, and a delay of 14 ms caused by the presence of the atrioventricular band (AV band). Moreover, the obtained in-silico ECG reflects the main characteristics of the zebrafish ECG in good agreement with experimental records, a P-wave with a duration of approximately the total atrial activation, followed by a QRS complex of approximately 109 ms corresponding to ventricle activation. CONCLUSIONS: The model allows the assessment of the main electrophysiological parameters in terms of activation sequence and timing, reproducing monopolar and bipolar ECG signals in line with experimental data. Coupling the proposed model with an electrophysiological detailed action potential model of zebrafish will represent a significant breakthrough toward the development of an in-silico zebrafish heart.

A low dimensional surrogate model for a fast estimation of strain in the thrombus during a thrombectomy procedure.

BACKGROUND: Intra-arterial thrombectomy is the main treatment for acute ischemic stroke due to large vessel occlusions and can consist in mechanically removing the thrombus with a stent-retriever. A cause of failure of the procedure is the fragmentation of the thrombus and formation of micro-emboli, difficult to remove. This work proposes a methodology for the creation of a low-dimensional surrogate model of the mechanical thrombectomy procedure, trained on realizations from high-fidelity simulations, able to estimate the evolution of the maximum first principal strain in the thrombus. METHOD: A parametric finite-element model was created, composed of a tapered vessel, a thrombus, a stent-retriever and a catheter. A design of experiments was conducted to sample 100 combinations of the model parameters and the corresponding thrombectomy simulations were run and post-processed to extract the maximum first principal strain in the thrombus during the procedure. Then, a surrogate model was built with a combination of principal component analysis and Kriging. RESULTS: The surrogate model was chosen after a sensitivity analysis on the number of principal components and was tested with 10 additional cases. The model provided predictions of the strain curves with correlation above 0.9 and a maximum error of 28%, with an error below 20% in 60% of the test cases. CONCLUSIONS: The surrogate model provides nearly instantaneous estimates and constitutes a valuable tool for evaluating the risk of thrombus rupture during pre-operative planning for the treatment of acute ischemic stroke.

Utilizing numerical simulations to prevent stent graft kinking during thoracic endovascular aortic repair.

Numerical simulations of thoracic endovascular aortic repair (TEVAR) may be implemented in the preoperative workflow if credible and reliable. We present the application of a TEVAR simulation methodology to an 82-year-old woman with a penetrating atherosclerotic ulcer in the left hemiarch, that underwent a left common carotid artery to left subclavian artery bypass and consequent TEVAR in zone 2. During the intervention, kinking of the distal thoracic stent graft occurred and the simulation was able to reproduce this event. This report highlights the potential and reliability of TEVAR simulations to predict perioperative adverse events and short-term postoperative technical results.

Applicability assessment for in-silico patient-specific TEVAR procedures.

Thoracic Endovascular Aortic Repair (TEVAR) is a minimally invasive technique to treat thoracic aorta pathologies and consists of placing a self-expandable stent-graft into the pathological region to restore the vessel lumen and recreate a more physiological condition. Exhaustive computational models, namely the finite element analysis, can be implemented to reproduce the clinical procedure. In this context, numerical models, if used for clinical applications, must be reliable and the simulation credibility should be proved to predict clinical procedure outcomes or to build in-silico clinical trials. This work aims first at applying a previously validated TEVAR methodology to a patient-specific case. Then, defining the TEVAR procedure performed on a patient population as the context of use, the overall applicability of the TEVAR modeling is assessed to demonstrate the reliability of the model itself following a step-by-step method based on the ASME V&V40 protocol. Validation evidence sources are identified for the specific context of use and adopted to demonstrate the applicability of the numerical procedure, thereby answering a question of interest that evaluates the deployed stent-graft configuration in the vessel.

In silico thrombectomy trials for acute ischemic stroke.

BACKGROUND AND OBJECTIVE: In silico trials aim to speed up the introduction of new devices in clinical practice by testing device design and performance in different patient scenarios and improving patient stratification for optimizing clinical trials. In this paper, we demonstrate an in silico trial framework for thrombectomy treatment of acute ischemic stroke and apply this framework to compare treatment outcomes in different subpopulations and with different thrombectomy stent-retriever devices. We employ a novel surrogate thrombectomy model to evaluate the thrombectomy success in the in silico trial. METHODS: The surrogate thrombectomy model, built using data from a fine-grained finite-element model, is a device-specific binary classifier (logistic regression), to estimate the probability of successful recanalization, the outcome of interest. We incorporate this surrogate model within our previously developed in silico trial framework and demonstrate its use with three examples of in silico clinical trials. The first trial is a validation trial for the surrogate thrombectomy model. We then present two exploratory trials: one evaluating the performance of a commercially available device based on the fibrin composition in the occluding thrombus and one comparing the performance of two commercially available stent retrievers. RESULTS: The Validation Trial showed the surrogate thrombectomy model was able to reproduce a similar recanalization rate as the real-life MR CLEAN trial (p=0.6). Results from the first exploratory trial showed that the chance of successful thrombectomy increases with higher blood cell concentrations in the thrombi, which is in line with observations from clinical data. The second exploratory trial showed improved recanalization success with a newer stent retriever device; however, these results require further investigation as the surrogate model for the newer stent retriever device has not yet been validated. CONCLUSIONS: In this novel study, we have shown that in silico trials have the potential to help inform medical device developers on the performance of a new device and may also be used to select populations of interest for a clinical trial. This would reduce the time and costs involved in device development and traditional clinical trials.

Microcatheter tracking in thrombectomy procedures: A finite-element simulation study.

BACKGROUND AND OBJECTIVE: Mechanical thrombectomy is a minimally invasive procedure that aims at removing the occluding thrombus from the vasculature of acute ischemic stroke patients. Thrombectomy success and failure can be studied using in-silico thrombectomy models. Such models require realistic modeling steps to be effective. We here present a new approach to model microcatheter tracking during thrombectomy. METHODS: For 3 patient-specific vessel geometries, we performed finite-element simulations of the microcatheter tracking (1) following the vessel centerline (centerline method) and (2) as a one-step insertion simulation, where the microcatheter tip was advanced along the vessel centerline while its body was free to interact with the vessel wall (tip-dragging method). Qualitative validation of the two tracking methods was performed with the patient's digital subtraction angiography (DSA) images. In addition, we compared simulated thrombectomy outcomes (successful vs unsuccessful thrombus retrieval) and maximum principal stresses on the thrombus between the centerline and tip-dragging method. RESULTS: Qualitative comparison with the DSA images showed that the tip-dragging method more realistically resembles the patient-specific microcatheter-tracking scenario, where the microcatheter approaches the vessel walls. Although the simulated thrombectomy outcomes were similar in terms of thrombus retrieval, the thrombus stress fields (and the associated fragmentation of the thrombus) were strongly different between the two methods, with local differences in the maximum principal stress curves up to 84%. CONCLUSIONS: Microcatheter positioning with respect to the vessel affects the stress fields of the thrombus during retrieval, and therefore, may influence thrombus fragmentation and retrieval in-silico thrombectomy.

Self-expandable stent for thrombus removal modeling: Solid or beam finite elements?

BACKGROUND: The performance of self-expandable stents is being increasingly studied by means of finite-element analysis. As for peripheral stents, transcatheter valves and stent-grafts, there are numerous computational studies for setting up a proper model, this information is missing for stent-retrievers used in the procedure of thrombus removal in cerebral arteries. It is well known that the selection of the appropriate finite-element dimensions (topology) and formulations (typology) is a fundamental step to set up accurate and reliable computational simulations. In this context, a thorough verification analysis is here proposed, aimed at investigating how the different element typologies and topologies - available to model a stent-retriever - affect simulation results. METHOD: Hexahedral and beam element formulations were analyzed first individually by virtually replicating a crimping test on the device, and then by replicating the thrombectomy procedure aiming at removing a thrombus from a cerebral vessel. In particular, three discretization refinements for each element type and different element formulations including both full and reduced integration were investigated and compared in terms of the resultant radial force of the stent and the stress field generated in the thrombus. RESULTS: The sensitivity analysis on the element formulation performed with the crimping simulations allowed the identification of the optimal setting for each element family. Both setting lead to similar results in terms of stent performance in the virtual thrombectomy and should be used in future studies simulating the mechanical thrombectomy with stent-retrievers. CONCLUSIONS: The carried out virtual thrombectomy procedures confirmed that the beam element formulation results were sufficiently accurate to model the radial force and the performance of the stent-retriever during the procedure. For different self-expandable stents, hexahedral formulation could be essential in stress analysis.

Patient-specific multi-scale design optimization of transcatheter aortic valve stents.

BACKGROUND AND OBJECTIVE: Transcatheter aortic valve implantation (TAVI) has become the standard treatment for a wide range of patients with aortic stenosis. Although some of the TAVI post-operative complications are addressed in newer designs, other complications and lack of long-term and durability data on the performance of these prostheses are limiting this procedure from becoming the standard for heart valve replacements. The design optimization of these devices with the finite element and optimization techniques can help increase their performance quality and reduce the risk of malfunctioning. Most performance metrics of these prostheses are morphology-dependent, and the design and the selection of the device before implantation should be planned for each individual patient. METHODS: In this study, a patient-specific aortic root geometry was utilized for the crimping and implantation simulation of 50 stent samples. The results of simulations were then evaluated and used for developing regression models. The strut width and thickness, the number of cells and patterns, the size of stent cells, and the diameter profile of the stent were optimized with two sets of optimization processes. The objective functions included the maximum crimping strain, radial strength, anchorage area, and the eccentricity of the stent. RESULTS: The optimization process was successful in finding optimal models with up to 40% decrease in the maximum crimping strain, 261% increase in the radial strength, 67% reduction in the eccentricity, and about an eightfold increase in the anchorage area compared to the reference device. CONCLUSIONS: The stents with larger distal diameters perform better in the selected objective functions. They provide better anchorage in the aortic root resulting in a smaller gap between the device and the surrounding tissue and smaller contact pressure. This framework can be used in designing patient-specific stents and improving the performance of these devices and the outcome of the implantation process.

Reliable Numerical Models of Nickel-Titanium Stents: How to Deduce the Specific Material Properties from Testing Real Devices.

The current interest of those dealing with medical research is the preparation of digital twins. In this frame, the first step to accomplish is the preparation of reliable numerical models. This is a challenging task since it is not common to know the exact device geometry and material properties unless in studies performed in collaboration with the manufacturer. The particular case of modeling Ni-Ti stents can be highlighted as a worst-case scenario due to both the complex geometrical features and non-linear material response. Indeed, if the limitations in the description of the geometry can be overcome, many difficulties still exist in the assessment of the material, which can vary according to the manufacturing process and requires many parameters for its description. The purpose of this work is to propose a coupled experimental and computational workflow to identify the set of material properties in the case of commercially-resembling Ni-Ti stents. This has been achieved from non-destructive tensile tests on the devices compared with results from Finite Element Analysis (FEA). A surrogate modeling approach is proposed for the identification of the material parameters, based on a minimization problem on the database of responses of Ni-Ti materials obtained with FEA with a series of different parameters. The reliability of the final result was validated through the comparison with the output of additional experiments.

A detailed methodology to model the Non Contact Tonometry: a Fluid Structure Interaction study.

Understanding the corneal mechanical properties has great importance in the study of corneal pathologies and the prediction of refractive surgery outcomes. Non-Contact Tonometry (NCT) is a non-invasive diagnostic tool intended to characterize the corneal tissue response in vivo by applying a defined air-pulse. The biomarkers inferred from this test can only be considered as indicators of the global biomechanical behaviour rather than the intrinsic biomechanical properties of the corneal tissue. A possibility to isolate the mechanical response of the corneal tissue is the use of an inverse finite element method, which is based on accurate and reliable modelling. Since a detailed methodology is still missing in the literature, this paper aims to construct a high-fidelity finite-element model of an idealized 3D eye for in silico NCT. A fluid-structure interaction (FSI) simulation is developed to virtually apply a defined air-pulse to a 3D idealized eye model comprising cornea, limbus, sclera, lens and humors. Then, a sensitivity analysis is performed to examine the influence of the intraocular pressure (IOP) and the structural material parameters on three biomarkers associated with corneal deformation. The analysis reveals the requirements for the in silico study linked to the correct reproduction of three main aspects: the air pressure over the cornea, the biomechanical properties of the tissues, and the IOP. The adoption of an FSI simulation is crucial to capture the correct air pressure profile over the cornea as a consequence of the air-jet. Regarding the parts of the eye, an anisotropic material should be used for the cornea. An important component is the sclera: the stiffer the sclera, the lower the corneal deformation due to the air-puff. Finally, the fluid-like behavior of the humors should be considered in order to account for the correct variation of the IOP during the test which will, otherwise, remain constant. The development of a strong FSI tool amenable to model coupled structures and fluids provides the basis to find the biomechanical properties of the corneal tissue in vivo.

Development of a patient-specific cerebral vasculature fluid-structure-interaction model.

Development of in-silico models of patient-specific cerebral artery networks presents several significant technical challenges: (i) The resolution and smoothness of medical CT images are much lower than the required element/cell length for FEA/CFD/FSI models; (ii) contact between vessels, and indeed self contact of high tortuosity vessel segments are not clearly identifiable from medical CT images. Commercial model construction software does not provide customised solutions for such technical challenges, with the result that accurate, efficient and automated development of patient-specific models of the cerebral vessels is not facilitated. This paper presents the development of a customised and highly automated platform for the generation of high resolution patient-specific FEA/CFD/FSI models from clinical images. This platform is used to perform the first fluid-structure-interaction patient-specific analysis of blood flow and artery deformation of an occluded cerebral vessel. Results demonstrate that in addition to flow disruption, clot occlusion significantly alters the geometry and strain distribution in the vessel network, with the blocked M2 segment undergoing axial elongation. The new computational approach presented in this study can be further developed as a clinical diagnostic tool and as a platform for thrombectomy device design.

Combined stent-retriever and aspiration intra-arterial thrombectomy performance for fragmentable blood clots: A proof-of-concept computational study.

Mechanical thrombectomy (MT) treatment of acute ischemic stroke (AIS) patients typically involves use of stent retrievers or aspiration catheters alone or in combination. For in silico trials of AIS patients, it is crucial to incorporate the possibility of thrombus fragmentation during the intervention. This study focuses on two aspects of the thrombectomy simulation: i) Thrombus fragmentation on the basis of a failure model calibrated with experimental tests on clot analogs; ii) the combined stent-retriever and aspiration catheter MT procedure is modeled by adding both the proximal balloon guide catheter and the distal access catheter. The adopted failure criterion is based on maximum principal stress threshold value. If elements of the thrombus exceed this criterion during the retrieval simulation, then they are deleted from the calculation. Comparison with in-vitro tests indicates that the simulation correctly reproduces the procedures predicting thrombus fragmentation in the case of red blood cells rich thrombi, whereas non-fragmentation is predicted for fibrin-rich thrombi. Modeling of balloon guide catheter prevents clot fragments' embolization to further distal territories during MT procedure.

Validation and Verification of High-Fidelity Simulations of Thoracic Stent-Graft Implantation.

Thoracic Endovascular Aortic Repair (TEVAR) is the preferred treatment option for thoracic aortic pathologies and consists of inserting a self-expandable stent-graft into the pathological region to restore the lumen. Computational models play a significant role in procedural planning and must be reliable. For this reason, in this work, high-fidelity Finite Element (FE) simulations are developed to model thoracic stent-grafts. Experimental crimp/release tests are performed to calibrate stent-grafts material parameters. Stent pre-stress is included in the stent-graft model. A new methodology for replicating device insertion and deployment with explicit FE simulations is proposed. To validate this simulation, the stent-graft is experimentally released into a 3D rigid aortic phantom with physiological anatomy and inspected in a computed tomography (CT) scan at different time points during deployment with an ad-hoc set-up. A verification analysis of the adopted modeling features compared to the literature is performed. With the proposed methodology the error with respect to the CT is on average 0.92 ± 0.64%, while it is higher when literature models are adopted (on average 4.77 ± 1.83%). The presented FE tool is versatile and customizable for different commercial devices and applicable to patient-specific analyses.