Effect of variability of mechanical properties on the predictive capabilities of vulnerable coronary plaques.

BACKGROUND AND OBJECTIVE: Coronary plaque rupture is a precipitating event responsible for two thirds of myocardial infarctions. Currently, the risk of plaque rupture is computed based on demographic, clinical, and image-based adverse features. However, using these features the absolute event rate per single higher-risk lesion remains low. This work studies the power of a novel framework based on biomechanical markers accounting for material uncertainty to stratify vulnerable and non-vulnerable coronary plaques. METHODS: Virtual histology intravascular ultrasounds from 55 patients, 29 affected by acute coronary syndrome and 26 affected by stable angina pectoris, were included in this study. Two-dimensional vessel cross-sections for finite element modeling (10 sections per plaque) incorporating plaque structure (medial tissue, loose matrix, lipid core and calcification) were reconstructed. A Montecarlo finite element analysis was performed on each section to account for material variability on three biomechanical markers: peak plaque structural stress at diastolic and systolic pressure, and peak plaque stress difference between systolic and diastolic pressures, together with the luminal pressure. Machine learning decision tree classifiers were trained on 75% of the dataset and tested on the remaining 25% with a combination of feature selection techniques. Performance against classification trees based on geometric markers (i.e., luminal, external elastic membrane and plaque areas) was also performed. RESULTS: Our results indicate that the plaque structural stress outperforms the classification capacity of the combined geometric markers only (0.82 vs 0.51 area under curve) when accounting for uncertainty in material parameters. Furthermore, the results suggest that the combination of the peak plaque structural stress at diastolic and systolic pressures with the maximum plaque structural stress difference between systolic and diastolic pressures together with the systolic pressure and the diastolic to systolic pressure gradient is a robust classifier for coronary plaques when the intrinsic variability in material parameters is considered (area under curve equal to [0.91-0.93]). CONCLUSION: In summary, our results emphasize that peak plaque structural stress in combination with the patient's luminal pressure is a potential classifier of plaque vulnerability as it independently considers stress in all directions and incorporates total geometric and compositional features of atherosclerotic plaques.

Impact of Tissue Damage and Hemodynamics on Restenosis Following Percutaneous Transluminal Angioplasty: A Patient-Specific Multiscale Model.

Multiscale agent-based modeling frameworks have recently emerged as promising mechanobiological models to capture the interplay between biomechanical forces, cellular behavior, and molecular pathways underlying restenosis following percutaneous transluminal angioplasty (PTA). However, their applications are mainly limited to idealized scenarios. Herein, a multiscale agent-based modeling framework for investigating restenosis following PTA in a patient-specific superficial femoral artery (SFA) is proposed. The framework replicates the 2-month arterial wall remodeling in response to the PTA-induced injury and altered hemodynamics, by combining three modules: (i) the PTA module, consisting in a finite element structural mechanics simulation of PTA, featuring anisotropic hyperelastic material models coupled with a damage formulation for fibrous soft tissue and the element deletion strategy, providing the arterial wall damage and post-intervention configuration, (ii) the hemodynamics module, quantifying the post-intervention hemodynamics through computational fluid dynamics simulations, and (iii) the tissue remodeling module, based on an agent-based model of cellular dynamics. Two scenarios were explored, considering balloon expansion diameters of 5.2 and 6.2 mm. The framework captured PTA-induced arterial tissue lacerations and the post-PTA arterial wall remodeling. This remodeling process involved rapid cellular migration to the PTA-damaged regions, exacerbated cell proliferation and extracellular matrix production, resulting in lumen area reduction up to 1-month follow-up. After this initial reduction, the growth stabilized, due to the resolution of the inflammatory state and changes in hemodynamics. The similarity of the obtained results to clinical observations in treated SFAs suggests the potential of the framework for capturing patient-specific mechanobiological events occurring after PTA intervention.

A Secure Dual-Layer Fault Protection Strategy for Distribution Network with DERs: Enhancing Security in the Face of Communication Challenges.

Earlier protection methods mainly focused on using communication channels to transmit trip signals between the protective devices (PDs), with no solutions provided in the case of communication failure. Therefore, this paper introduces a dual-layer protection system to ensure secure protection against fault events in the Distribution Systems (DSs), particularly in light of communication failures. The initial layer uses the Total Harmonic Distortion (THD), the estimates of the amplitude voltages, and the zero-sequence grid voltage components, functioning as a fault sensor, to formulate an adaptive algorithm based on a Finite State Machine (FSM) for the detection and isolation of faults within the grid. This layer primarily relies on communication protocols for effective coordination. A Second-Order Generalized Integrator (SOGI) expedites the derivation of the estimated variables, ensuring fast detection with minimal computational overhead. The second layer uses the behavior of the positive- and negative-sequence components of the grid voltages during fault events to locate and isolate these faults. In the event that the first layer exposes a communication failure, the second layer will automatically be activated to ensure secure protection as it operates, using the local information of the Protective devices (PDs), without the need for communication channels to transmit trip signals between the PDs. The proposed protection system has been assessed using simulations with MATLAB/Simulink and providing experimental results considering an IEEE 9-bus standard radial system. The obtained results confirm the capability of the system for identifying and isolating different types of faults, varying conditions, and modifications to the grid configuration. The results show good behavior of the initial THD-based layer, with fast time responses ranging from 6 to 8.5 ms in all the examined scenarios. In contrast, the sequence-based layer exhibits a protection time response of approximately 150 ms, making it a viable backup option in the event of a communication failure.

A Phase I Dose-Escalation Clinical Trial to Assess the Safety and Efficacy of Umbilical Cord-Derived Mesenchymal Stromal Cells in Knee Osteoarthritis.

Osteoarthritis (OA) is the most common degenerative joint disease. Mesenchymal stromal cells (MSC) are promising cell-based therapy for OA. However, there is still a need for additional randomized, dose-dependent studies to determine the optimal dose and tissue source of MSC for improved clinical outcomes. Here, we performed a dose-dependant evaluation of umbilical cord (UC)-derived MSC (Celllistem) in a murine model and in knee OA patients. For the preclinical study, a classical dose (200.000 cells) and a lower dose (50.000 cells) of Cellistem were intra-articularly injected into the mice knee joints. The results showed a dose efficacy response effect of Cellistem associated with a decreased inflammatory and degenerative response according to the Pritzker OARSI score. Following the same approach, the dose-escalation phase I clinical trial design included 3 sequential cohorts: low-dose group (2 × 106 cells), medium-dose group (20 × 106), and high-dose group (80 × 106). All the doses were safe, and no serious adverse events were reported. Nonetheless, 100% of the patients injected with the high-dose experienced injection-related swelling in the knee joint. According to WOMAC total outcomes, patients treated with all doses reported significant improvements in pain and function compared with baseline after 3 and 6 months. However, the improvements were higher in patients treated with both medium and low dose as compared to high dose. Therefore, our data demonstrate that the intra-articular injection of different doses of Cellistem is both safe and efficient, making it an interesting therapeutic alternative to treat mild and symptomatic knee OA patients. Trial registration ClinicalTrials.gov NCT03810521.

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.

Serial RV wall stress measurements: association with right ventricular function in repaired Tetralogy of Fallot patients.

Background: Optimal timing of pulmonary valve replacement (PVR) in Tetralogy of Fallot (TOF) patients remains challenging. Ventricular wall stress is considered to be an early marker of right ventricular (RV) dysfunction. Objectives: To investigate the association of RV wall stresses and their change over time with functional parameters in TOF patients. Methods: Ten TOF patients after surgical repair with moderate/severe pulmonary regurgitation were included. At two timepoints (median follow-up time 7.2 years), patient-specific computational biventricular models for wall stress assessment were created using CMR short-axis cine images and echocardiography-based RV pressures. RV ejection fraction (RVEF), NT-proBNP and cardiopulmonary exercise tests were used as outcome measures reflecting RV function. Associations between regional RV diastolic wall stress and RV function were investigated using linear mixed models. Results: Increased wall stress correlated with lower RV mass (rrm = -0.70, p = 0.017) and lower RV mass-to-volume (rrm = -0.80, p = 0.003) using repeated measures. Wall stress decreased significantly over time, especially in patients with a stable RVEF (p < 0.001). Higher wall stress was independently associated with lower RVEF, adjusted for left ventricular ejection fraction, RV end-diastolic volume and time since initial surgery (decrease of 1.27% RVEF per kPa increase in wall stress, p = 0.029) using repeated measurements. No association was found between wall stress, NT-proBNP, and exercise capacity. Conclusions: Using a computational method to calculate wall stress locally in geometrically complex ventricles, we demonstrated that lower wall stress might be important to maintain ventricular function. RV wall stress assessment can be used in serial follow-up, and is potentially an early marker of impending RV dysfunction.

An In Vitro Study to Assess the Best Strategy for the Chemical Debridement of Periprosthetic Joint Infection.

Irrigation and debridement using an irrigation solution is a fundamental step during the surgical treatment of both acute and chronic periprosthetic joint infection (PJI). However, there is no consensus on the optimal solution, nor is there sufficient evidence on the optimal irrigation time and combination of solutions. Therefore, it is necessary to determine which solution or combination of solutions is most efficacious against biofilm, as well as the optimal irrigation time. We conducted an experimental in vitro model by inoculating stainless steel discs with ATCC strains of methicillin-susceptible Staphylococcus aureus, methicillin-resistant S. aureus, Pseudomonas aeruginosa, and a clinical strain of Staphylococcus epidermidis. The discs were all irrigated with commonly used antiseptic solutions (10% and 3% povidone iodine, hydrogen peroxide, 3% acetic acid, and Bactisure™) for 1 min, 3 min, and 5 min and their combinations for 9 min (3 min each) vs. sterile saline as a positive control. We evaluated the reduction in biofilm based on colony-forming unit (cfu) counts and in combination assays, also based on cell viability and scanning electron microscopy. All antiseptics alone reduced more than 90% of cfu counts after 1 min of irrigation; the worst results were for hydrogen peroxide and 3% acetic acid. When solutions were sequentially combined, the best results were observed for all those starting with acetic acid, in terms of both reduction of log cfu/mL counts and viable cells. We consider that a combination of antiseptic solutions, particularly that comprising the sequence acetic acid + povidone iodine + hydrogen peroxide, would be the best option for chemical debridement during PJI surgery.

In Vitro Efficacy of Dalbavancin as a Long-Acting Anti-Biofilm Agent Loaded in Bone Cement.

Based on previous studies by our group in which we demonstrated that dalbavancin loaded in bone cement had good elution capacity for the treatment of biofilm-related periprosthetic infections, we now assess the anti-biofilm activity of dalbavancin and compare it with that of vancomycin over a 3-month period. We designed an in vitro model in which we calculated the percentage reduction in log cfu/mL counts of sonicated steel discs contaminated with staphylococci and further exposed to bone cement discs loaded with 2.5% or 5% vancomycin and dalbavancin at various timepoints (24 h, 48 h, 1 week, 2 weeks, 6 weeks, and 3 months). In addition, we tested the anti-biofilm activity of eluted vancomycin and dalbavancin at each timepoint based on a 96-well plate model in which we assessed the percentage reduction in metabolic activity. We observed a significant decrease in the dalbavancin concentration from 2 weeks of incubation, with sustained anti-biofilm activity up to 3 months. In the case of vancomycin, we observed a significant decrease at 1 week. The concentration gradually increased, leading to significantly lower anti-biofilm activity. The percentage reduction in cfu/mL counts was higher for dalbavancin than for vancomycin at both the 2.5% and the 5% concentrations. The reduction in log cfu/mL counts was higher for S. epidermidis than for S. aureus and was particularly more notable for 5% dalbavancin at 3 months. In addition, the percentage reduction in metabolic activity also decreased at 3 months in 5% dalbavancin and 5% vancomycin, with more notable values recorded for the latter.

A Comparative Study of Smart THD-Based Fault Protection Techniques for Distribution Networks.

The integration of Distributed Generators (DGs) into distribution systems (DSs) leads to more reliable and efficient power delivery for customers. However, the possibility of bi-directional power flow creates new technical problems for protection schemes. This poses a threat to conventional strategies because the relay settings have to be adjusted depending on the network topology and operational mode. As a solution, it is important to develop novel fault protection techniques to ensure reliable protection and avoid unnecessary tripping. In this regard, Total Harmonic Distortion (THD) can be used as a key parameter for evaluating the grid's waveform quality during fault events. This paper presents a comparison between two DS protection strategies that employ THD levels, estimated amplitude voltages, and zero-sequence components as instantaneous indicators during the faults that function as a kind of fault sensor to detect, identify, and isolate faults. The first method uses a Multiple Second Order Generalized Integrator (MSOGI) to obtain the estimated variables, whereas the second method uses a single SOGI for the same purpose (SOGI-THD). Both methods rely on communication lines between protective devices (PDs) to facilitate coordinated protection. The effectiveness of these methods is assessed by using simulations in MATLAB/Simulink considering various factors such as different types of faults and DG penetrations, different fault resistances and fault locations in the proposed network. Moreover, the performance of these methods is compared with conventional overcurrent and differential protections. The results show that the SOGI-THD method is highly effective in detecting and isolating faults with a time interval of 6-8.5 ms using only three SOGIs while requiring only 447 processor cycles for execution. In comparison to other protection methods, the SOGI-THD method exhibits a faster response time and a lower computational burden. Furthermore, the SOGI-THD method is robust to harmonic distortion, as it considers pre-existing harmonic content before the fault and avoids interference with the fault detection process.

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.

The mechanisms of potassium loss in acute myocardial ischemia: New insights from computational simulations.

Acute myocardial ischemia induces hyperkalemia (accumulation of extracellular potassium), a major perpetrator of lethal reentrant ventricular arrhythmias. Despite considerable experimental efforts to explain this pathology in the last decades, the intimate mechanisms behind hyperkalemia remain partially unknown. In order to investigate these mechanisms, we developed a novel computational model of acute myocardial ischemia which couples a) an electrophysiologically detailed human cardiomyocyte model that incorporates modifications to account for ischemia-induced changes in transmembrane currents, with b) a model of cardiac tissue and extracellular K + transport. The resulting model is able to reproduce and explain the triphasic time course of extracellular K + concentration within the ischemic zone, with values of [ K + ] o close to 14 mmol/L in the central ischemic zone after 30 min. In addition, the formation of a [ K + ] o border zone of approximately 1.2 cm 15 min after the onset of ischemia is predicted by the model. Our results indicate that the primary rising phase of [ K + ] o is mainly due to the imbalance between K + efflux, that increases slightly, and K + influx, that follows a reduction of the NaK pump activity by more than 50%. The onset of the plateau phase is caused by the appearance of electrical alternans (a novel mechanism identified by the model), which cause an abrupt reduction in the K + efflux. After the plateau, the secondary rising phase of [ K + ] o is caused by a subsequent imbalance between the K + influx, which continues to decrease slowly, and the K + efflux, which remains almost constant. Further, the study shows that the modulation of these mechanisms by the electrotonic coupling is the main responsible for the formation of the ischemic border zone in tissue, with K + transport playing only a minor role. Finally, the results of the model indicate that the injury current established between the healthy and the altered tissue is not sufficient to depolarize non-ischemic cells within the healthy tissue.

On the need of a scale-dependent material characterization to describe the mechanical behavior of 3D printed Ti6Al4V custom prostheses using finite element models.

Additive manufacturing is widely used in the orthopaedic industry for the high freedom and flexibility in the design and production of personalized custom implants made of Ti6Al4V. Within this context, finite element modeling of 3D printed prostheses is a robust tool both to guide the design phase and to support clinical evaluations, possibly virtually describing the in-vivo behavior of the implant. Given realistic scenarios, a suitable description of the overall implant's mechanical behavior is unavoidable. Considering typical custom prostheses' designs (i.e. acetabular and hemipelvis implants), complex designs involving solid and/or trabeculated parts, and material distribution at different scales hinder a high-fidelity modeling of the prostheses. Moreover, uncertainties in the production and in the material characterization of small parts approaching the accuracy limit of the additive manufacturing technology still exist. While recent works suggest that the mechanical properties of thin 3D-printed parts may be peculiarly affected by specific processing parameters (i.e. powder grain size, printing orientation, samples' thickness) as compared to conventional Ti6Al4V alloy, the current numerical models make gross simplifications in describing the complex material behavior of each part at different scales. The present study focuses on two patient-specific acetabular and hemipelvis prostheses, with the aim of experimentally characterizing and numerically describing the dependency of the mechanical behavior of 3D printed parts on their peculiar scale, therefore, overcoming one major limitation of current numerical models. Coupling experimental activities with finite element analyses, the authors initially characterized 3D printed Ti6Al4V dog-bone samples at different scales, representative of the main material components of the investigated prostheses. Afterwards, the authors implemented the characterized material behaviors into finite element models to compare the implications of adopting scale-dependent vs. conventional scaleindependent approaches in predicting the experimental mechanical behavior of the prostheses in terms of their overall stiffness and the local strain distribution. The material characterization results highlighted the need for a scale-dependent reduction of the elastic modulus for thin samples compared to the conventional Ti6Al4V, which is fundamental to properly describe the overall stiffness and local strain distribution on the prostheses. The presented works demonstrate how an appropriate material characterization and a scale-dependent material description is needed to develop reliable FE models of 3D printed implants characterized by a complex material distribution at different scales.

A THD-Based Fault Protection Method Using MSOGI-FLL Grid Voltage Estimator.

The rapid growth of the distributed generators (DGs) integration into the distribution systems (DSs) creates new technical issues; conventional relay settings need to be updated depending on the network topology and operational mode as fault protection a major challenge. This emphasizes the need for new fault protection methods to ensure secure protection and prevent undesirable tripping. Total harmonic distortion (THD) is an important indicator for assessing the quality of the grid. Here, a new protection system based on the THD of the grid voltages is proposed to address fault events in the electrical distribution network. The proposed protection system combines the THD with the estimates of the amplitude voltages and the zero-sequence component for defining an algorithm based on a finite state machine (FSM) for the detection, identification, and isolation of faults in the grid. The algorithm employs communication lines between all the protective devices (PDs) of the system to transmit tripping signals, allowing PDs to be coordinated. A second order generalized integrator (SOGI) and multiple SOGI (MSOGI) are used to obtain the THDs, estimated amplitude voltages, and zero-sequence component, which allows for fast detection with a low computational burden. The protection algorithm performance is evaluated through simulations in MATLAB/Simulink and a comparative study is developed between the proposed protection method and a differential relay (DR) protection system. The proposed method shows its capability to detect and isolate faults during different fault types with different fault resistances in different locations in the proposed network. In all the tested scenarios, the detection time of the faults has been between 7-10 ms. Moreover, this method gave the best solution as it has a higher accuracy and faster response than the conventional DR protection system.

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.

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.

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.

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.

Predicting the response to methylprednisolone pulses in patients with SARS-COV-2 infection.

Introduction: Treating systemic inflammation caused by SARS-COV 2 (COVID-19) has become a challenge for the clinician. Corticosteroids have been the turning point in the treatment of this disease. Preliminary data from Recovery clinical trial raises hope by showing that treatment with dexamethasone at doses of 6 mg/day shows a reduction on morbidity in patients requiring added oxygen therapy. However, both the start day or what kind of corticosteroid, are still questions to be clarified. Since the pandemic beginning, we have observed large differences in the type of corticosteroid, dose and initiation of treatment.Our objective is to assess the predictive capacity of the characteristics of patients treated with methylprednisolone pulses to predict hospital discharge. Materials and methods: We presented a one-center observational study of a retrospective cohort. We included all patients admitted between 03/06/2020 and 05/15/2020 because of COVID-19. We have a total number of 1469 patients, of whom 322 received pulses of methylprednisolone. Previous analytical, radiographic, previous disease data were analyzed on these patients. The univariant analysis was performed using Chi-squared and the T test of Student according to the qualitative or quantitative nature of the variables respectively. For multivariate analysis, we have used binary logistic regression and ROC curves. Results: The analysis resulted statistically significant in dyspnea, high blood pressure, dyslipidemia, stroke, ischemic heart disease, cognitive impairment, solid tumor, C-reactive protein (CRP), lymphopenia and d-dimer within 5 days of admission. Radiological progression and FIO2 input are factors that are associated with a worst prognosis in COVID-19 that receive pulses of methylprednisolone. Multivariate analysis shows that age, dyspnea and C-reactive protein are markers of hospital discharge with an area below the curve of 0.816. Conclusions: In patients with methylprednisolone pulses, the capacity of the predictive model for hospital discharge including variables collected at 5 days was (area under the curve) 0.816.

Introducción: Tratar la inflamación sistémica producida por el SARS-COV 2 (COVID-19) se ha convertido en un reto para el clínico. Los corticoides han sido el punto de inflexión en el tratamiento de esta enfermedad. Los datos preliminares del ensayo clínico Recovery alentan esperanza mostrando que con el tratamiento con dexametasona a dosis de 6 mg/día hay una disminución de la morbimortalidad en pacientes que requieren oxigenoterapia añadida. Sin embargo, tanto el día de inicio, o qué tipo de corticosteroide, son todavía preguntas por aclarar. Desde el inicio de la pandemia hemos observado grandes diferencias en cuanto al tipo de corticoide, dosis e inicio de tratamiento.Nuestro objetivo es valorar la capacidad predictiva de las características de los pacientes tratados con bolos de metilprednisolona para predecir el alta hospitalaria. Materiales y métodos: Presentamos un estudio unicéntrico observacional de cohorte retrospectiva. Incluimos a todos los pacientes ingresados entre el 06/03/2020 y el 15/05/2020 por COVID-19. Contamos con un número total de 1469 pacientes, de los cuales 322 recibieron pulsos de metilprednisolona. De estos pacientes se analizaron los datos clínicos, analíticos, radiográficos, enfermedades previas. El análisis univariante se realizó mediante Chi cuadrado y el test t de Student según la naturaleza cualitativa o cuantitativa de las variables respectivamente. Para el análisis multivariante hemos empleado la regresión logística binaria y las curvas ROC. Resultados: En el análisis resultó estadísticamente significativo la disnea, hipertensión arterial, dislipemia, accidente cerebrovascular, cardiopatía isquémica, deterioro cognitivo, tumor sólido, la proteína C reactiva (PCR), linfopenia y d-dímero a los 5 días de ingreso. La progresión radiológica y de aporte de FIO2 son factores que se asocian a peor pronóstico en la COVID-19 que reciben pulsos de metilprednisolona. En el análisis multivariante se observa que la edad, disnea y la proteína C reactiva son marcadores de alta hospitalaria con un área bajo la curva de 0,816. Conclusión: En pacientes con bolos de metilprednisolona, la capacidad del modelo predictivo del alta hospitalaria incluyendo variables recogidas a los 5 días ha sido (Área Bajo la Curva) de 0.816.