3D Printing, Computational Modeling, and Artificial Intelligence for Structural Heart Disease

The Emerging and Important Role of Artificial Intelligence in Cardiac Surgery

Artificial Intelligence (AI) has greatly affected our everyday lives and holds great promise to change the landscape of medicine. AI is particularly positioned to improve care for the increasingly complex patients undergoing cardiac surgery using immense amount of data generated in the course of their care. When deployed, AI can be used to analyze this information at the patient's bedside more expediently and accurately, all while providing new insights. This review summarizes the current applications of AI in cardiac surgery from the vantage point of a patient's journey. Applications of AI include preoperative risk assessment, intraoperative planning, postoperative patient care, and outpatient telemonitoring, encompassing the spectrum of cardiac surgical care. Offloading of administrative processes and enhanced experience with information gathering also represent a unique and under-represented avenue for future use of AI. As clinicians, understanding the nomenclature and applications of AI is important to contextualize problems, to ensure problem-driven solutions, and for clinical benefit. Precision medicine, and thus clinically relevant AI, remains dependent on data curation and warehousing to gather insights from large multicentre repositories while treating privacy with the utmost importance. AI tasks should not be siloed but rather holistically integrated into clinical workflow to retain context and relevance. As cardiac surgeons, AI allows us to look forward to a bright future of more efficient use of our clinical expertise toward high-level decision making and technical prowess.

Preliminary Study of a Degenerated Tricuspid Bioprosthetic Valve Implanted via Transcatheter Valve-in-Valve Implantation Guided by 3-Dimensional Printing

Background

The procedures of transcatheter tricuspid valve-in-valve (TTViV) replacement are challenging, and the clinical outcomes are still unclear. Our goal was to report the short- and mid-term clinical outcomes of patients who underwent a TTViV implantation guided by 3-dimensional (3D) printing.

Methods

A retrospective analysis was performed on 6 patients who had TTViV implantation from May 2021 to March 2022. The median age was 51 years (range: 18-71 years), and 50.0% of the patients were male. Imaging assessments and 3D printing were performed on all 6 patients before the procedures. The perioperative data were evaluated, and the patients were followed up.

Results

Among the 6 patients, the etiologies of conditions affecting the tricuspid valves at baseline varied widely, including 1 case of Ebstein anomaly, 2 cases of infective endocarditis, 1 case of ventricular septal defect, and 2 cases of rheumatic heart disease. TTViV implantation was successfully performed in all 6 patients via the femoral vein approach; postoperative tricuspid regurgitation disappeared immediately, and the hemodynamic results were satisfactory. During the follow-up, all patients had significant improvement in symptoms and functional status.

Conclusions

TTViV implantation for the treatment of degenerated tricuspid bioprostheses should be considered safe and effective. Multimodal imaging and 3D printing may provide effective guidance for conducting the procedure.

Clinical Trial Registration

ClinicalTrials.gov Protocol Registration System (NCT02917980).

A comprehensive review on heart disease prognostication using different artificial intelligence algorithms

Prediction of heart diseases on time is significant in order to preserve life. Many conventional methods have taken efforts on earlier prediction but faced with challenges of higher prediction cost, extended time for computation and complexities with larger volume of data which reduced prediction accuracy. In order to overcome such pitfalls, AI (Artificial Intelligence) technology has been evolved in diagnosing heart diseases through deployment of several ML (Machine Learning) and DL (Deep Learning) algorithms. It improves detection by influencing with its capacity of learning from the massive data containing age, obesity, hypertension and other risk factors of patients and extract it accordingly to differentiate on the circumstances. Moreover, storage of larger data with AI greatly assists in analysing the occurrence of the disease from past historical data. Hence, this paper intends to provide a review on different AI based algorithms used in the heart disease prognostication and delivers its benefits through researching on various existing works. It performs comparative analysis and critical assessment as encompassing accuracies and maximum utilization of algorithms focussed by traditional studies in this area. The major findings of the paper emphasized on the evolution and continuous explorations of AI techniques for heart disease prediction and the future researchers aims in determining the dimensions that have attained high and low prediction accuracies on which appropriate research works can be performed. Finally, future research is included to offer new stimulus for further investigation of AI in cardiac disease diagnosis.

Computer-aided design and 3D printing for a stable construction of segmental bone defect model in Beagles: a short term observation

OBJECTIVE

Segmental bone defect animal studies require stable fixation which is a continuous experimental challenge. Large animal models are comparable to the human bone, but with obvious drawbacks of housing and costs. Our study aims to utilize CAD and 3D printing in the construction of a stable and reproducible segmental bone defect animal mode.

METHODS

CAD-aided 3D printed surgical instruments were incorporated into the construction of the animal model through preoperative surgical emulation. 20 3D printed femurs were divided into either experimental group using 3D surgical instruments or control group. In Vitro surgical time and accuracy of fixation were analysed and compared between the two groups. A mature surgical plan using the surgical instruments was then utilized in the construction of 3 segmental bone defect Beagle models in vivo. The Beagles were postoperatively assessed through limb function and imaging at 1, 2 and 3 months postoperatively.

RESULTS

In vitro experiments showed a significant reduction in surgical time from 40.6 ± 14.1 (23-68 min) to 26 ± 4.6 (19-36 min) (n = 10, p < 0.05) and the accuracy of intramedullary fixation placement increased from 71.6 ± 23.6 (33.3-100) % to 98.3 ± 5.37 (83-100) %, (n = 30, p < 0.05) with the use of CAD and 3D printed instruments. All Beagles were load-bearing within 1 week, and postoperative radiographs showed no evidence of implant failure.

CONCLUSION

Incorporation of CAD and 3D printing significantly increases stability, while reducing the surgical time in the construction of the animal model, significantly affecting the success of the segmental bone defect model in Beagles.

Treatment of complex limb fractures with 3D printing technology combined with personalized plates: a retrospective study of case series and literature review

Background

In recent years, 3D printing technology has made significant strides in the medical field. With the advancement of orthopedics, there is an increasing pursuit of high surgical quality and optimal functional recovery. 3D printing enables the creation of precise physical models of fractures, and customized personalized steel plates can better realign and more comprehensively and securely fix fractures. These technologies improve preoperative diagnosis, simulation, and planning for complex limb fractures, providing patients with better treatment options.

Patients and methods

Five typical cases were selected from a pool of numerous patients treated with 3D printing technology combined with personalized custom steel plates at our hospital. These cases were chosen to demonstrate the entire process of printing 3D models and customizing individualized steel plates, including details of the patients' surgeries and treatment procedures. Literature reviews were conducted, with a focus on highlighting the application of 3D printing technology combined with personalized custom steel plates in the treatment of complex limb fractures.

Results

3D printing technology can produce accurate physical models of fractures, and personalized custom plates can achieve better fracture realignment and more comprehensive and robust fixation. These technologies provide patients with better treatment options.

Conclusion

The use of 3D printing models and personalized custom steel plates can improve preoperative diagnosis, simulation, and planning for complex limb fractures, realizing personalized medicine. This approach helps reduce surgical time, minimize trauma, enhance treatment outcomes, and improve patient functional recovery.

Is AI 3D-printed PSI an accurate option for patients with developmental dysplasia of the hip undergoing THA?

BACKGROUND

In traditional surgical procedures, significant discrepancies are often observed between the pre-planned templated implant sizes and the actual sizes used, particularly in patients with congenital hip dysplasia. These discrepancies arise not only in preoperative planning but also in the precision of implant placement, especially concerning the acetabular component. Our study aims to enhance the accuracy of implant placement during Total Hip Arthroplasty (THA) by integrating AI-enhanced preoperative planning with Patient-Specific Instrumentation (PSI). We also seek to assess the accuracy and clinical outcomes of the AI-PSI (AIPSI) group in comparison to a manual control group.

METHODS

This study included 60 patients diagnosed with congenital hip dysplasia, randomly assigned to either the AIPSI or manual group, with 30 patients in each. No significant demographic differences between were noted the two groups. A direct anterior surgical approach was employed. Postoperative assessments included X-rays and CT scans to measure parameters such as the acetabular cup anteversion angle, acetabular cup inclination angle, femoral stem anteversion angle, femoral offset, and leg length discrepancy. Functional scores were recorded at 3 days, 1 week, 4 weeks, and 12 weeks post-surgery. Data analysis was conducted using SPSS version 22.0, with the significance level was set at α = 0.05.

RESULTS AND CONCLUSION

The AIPSI group demonstrated greater prosthesis placement accuracy. With the aid of PSI, AI-planned THA surgery provides surgeons with enhanced precision in prosthesis positioning. This approach potentially offers greater insights and guidelines for managing more complex anatomical variations or cases.

Advances in cardiac tissue engineering and heart-on-a-chip

Recent advances in both cardiac tissue engineering and hearts-on-a-chip are grounded in new biomaterial development as well as the employment of innovative fabrication techniques that enable precise control of the mechanical, electrical, and structural properties of the cardiac tissues being modelled. The elongated structure of cardiomyocytes requires tuning of substrate properties and application of biophysical stimuli to drive its mature phenotype. Landmark advances have already been achieved with induced pluripotent stem cell-derived cardiac patches that advanced to human testing. Heart-on-a-chip platforms are now commonly used by a number of pharmaceutical and biotechnology companies. Here, we provide an overview of cardiac physiology in order to better define the requirements for functional tissue recapitulation. We then discuss the biomaterials most commonly used in both cardiac tissue engineering and heart-on-a-chip, followed by the discussion of recent representative studies in both fields. We outline significant challenges common to both fields, specifically: scalable tissue fabrication and platform standardization, improving cellular fidelity through effective tissue vascularization, achieving adult tissue maturation, and ultimately developing cryopreservation protocols so that the tissues are available off the shelf.

Physical and Computational Modeling for Transcatheter Structural Heart Interventions

Structural heart disease interventions rely heavily on preprocedural planning and simulation to improve procedural outcomes and predict and prevent potential procedural complications. Modeling technologies, namely 3-dimensional (3D) printing and computational modeling, are nowadays increasingly used to predict the interaction between cardiac anatomy and implantable devices. Such models play a role in patient education, operator training, procedural simulation, and appropriate device selection. However, current modeling is often limited by the replication of a single static configuration within a dynamic cardiac cycle. Recognizing that health systems may face technical and economic limitations to the creation of "in-house" 3D-printed models, structural heart teams are pivoting to the use of computational software for modeling purposes.

The Application of Precision Medicine in Structural Heart Diseases: A Step towards the Future

The personalized applications of 3D printing in interventional cardiology and cardiac surgery represent a transformative paradigm in the management of structural heart diseases. This review underscores the pivotal role of 3D printing in enhancing procedural precision, from preoperative planning to procedural simulation, particularly in valvular heart diseases, such as aortic stenosis and mitral regurgitation. The ability to create patient-specific models contributes significantly to predicting and preventing complications like paravalvular leakage, ensuring optimal device selection, and improving outcomes. Additionally, 3D printing extends its impact beyond valvular diseases to tricuspid regurgitation and non-valvular structural heart conditions. The comprehensive synthesis of the existing literature presented here emphasizes the promising trajectory of individualized approaches facilitated by 3D printing, promising a future where tailored interventions based on precise anatomical considerations become standard practice in cardiovascular care.

Preprocedural Planning of Left Atrial Appendage Occlusion: A Review of the Use of Additive Manufacturing

Stroke is a significant public health problem, with non-valvular atrial fibrillation (NVAF) being one of its main causes. This cardiovascular arrhythmia predisposes to the production of intracardiac thrombi, mostly formed in the left atrial appendage (LAA). When there are contraindications to treatment with oral anticoagulants, another therapeutic option to reduce the possibility of thrombus formation in the LAA is the implantation of an occlusion device by cardiac catheterization. The effectiveness of LAA occlusion is dependent on accurate preprocedural device sizing and proper device positioning at the LAA ostium, to ensure sufficient device anchoring and avoid peri-device leaks. Additive manufacturing, commonly known as three-dimensional printing (3DP), of LAA models is beginning to emerge in the scientific literature to address these challenges through procedural simulation. This review aims at clarifying the impact of 3DP on preprocedural planning of LAA occlusion, specifically in the training of cardiac surgeons and in the assessment of the perfect adjustment between the LAA and the biomedical implant.

Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment

Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor-patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed.

Three-dimensional printing of mitral valve models using echocardiographic data improves the knowledge of cardiology fellow physicians in training

Background

High fidelity three-dimensional Mitral valve models (3D MVM) printed from echocardiography are currently being used in preparation for surgical repair.

Aim

We hypothesize that printed 3DMVM could have relevance to cardiologists in training by improving their understanding of normal anatomy and pathology.

Methods

Sixteen fellow physicians in pediatric and adult cardiology training were recruited. 3D echocardiography (3DE) video clips of six mitral valves (one normal and five pathological) were displayed and the fellows were asked to name the prolapsing segments in each. Following that, three still images of 3D MVMs in different projections: enface, profile and tilted corresponding to the same MVs seen in the clip were presented on a screen. Participating physicians were presented with a comprehensive questionnaire aimed at assessing whether the 3D MVM has improved their understanding of valvular anatomy. Finally, a printed 3D MVM of each of the valves was handed out, and the same questionnaire was re-administered to identify any further improvement in the participants' perception of the anatomy.

Results

The correct diagnosis using the echocardiography video clip of the Mitral valve was attained by 45% of the study participants. Both pediatric and adult trainees, regardless of the year of training demonstrated improved understanding of the anatomy of MV after observing the corresponding model image. Significant improvement in their understanding was noted after participants had seen and physically examined the printed model.

Conclusion

Printed 3D MVM has a beneficial impact on the cardiology trainees' understanding of MV anatomy and pathology compared to 3DE images.

Application of artificial intelligence in 3D printing physical organ models

Artificial intelligence (AI) and 3D printing will become technologies that profoundly impact humanity. 3D printing of patient-specific organ models is expected to replace animal carcasses, providing scenarios that simulate the surgical environment for preoperative training and educating patients to propose effective solutions. Due to the complexity of 3D printing manufacturing, it is still used on a small scale in clinical practice, and there are problems such as the low resolution of obtaining MRI/CT images, long consumption time, and insufficient realism. AI has been effectively used in 3D printing as a powerful problem-solving tool. This paper introduces 3D printed organ models, focusing on the idea of AI application in 3D printed manufacturing of organ models. Finally, the potential application of AI to 3D-printed organ models is discussed. Based on the synergy between AI and 3D printing that will benefit organ model manufacturing and facilitate clinical preoperative training in the medical field, the use of AI in 3D-printed organ model making is expected to become a reality.

The Lifelong Impact of Artificial Intelligence and Clinical Prediction Models on Patients With Tetralogy of Fallot

Medical advancements in the diagnosis, surgical techniques, perioperative care, and continued care throughout childhood have transformed the outlook for individuals with tetralogy of Fallot (TOF), improving survival and shifting the perspective towards lifelong care. However, with a growing population of survivors, longstanding challenges have been accentuated, and new challenges have surfaced, necessitating a re-evaluation of TOF care. Availability of prenatal diagnostics, insufficient information from traditional imaging techniques, previously unforeseen medical complications, and debates surrounding optimal timing and indications for reintervention are among the emerging issues. To address these challenges, the integration of artificial intelligence and machine learning holds great promise as they have the potential to revolutionize patient management and positively impact lifelong outcomes for individuals with TOF. Innovative applications of artificial intelligence and machine learning have spanned across multiple domains of TOF care, including screening and diagnosis, automated image processing and interpretation, clinical risk stratification, and planning and performing cardiac interventions. By embracing these advancements and incorporating them into routine clinical practice, personalized medicine could be delivered, leading to the best possible outcomes for patients. In this review, we provide an overview of these evolving applications and emphasize the challenges, limitations, and future potential for integrating them into clinical care.

Fluid-structure interaction and structural simulation of high acceleration effects on surgical repaired human mitral valve biomechanics

Mitral valve dynamics depend on force stability in the mitral leaflets, the mitral annulus, the chordae tendineae, and the papillary muscles. In chordal rupture conditions, the proper function of the valve disrupts, causing mitral regurgitation, the most prevalent valvular disease. In this study, Structural and FSI frameworks were employed to study valve dynamics in healthy, pathologic, and repaired states. Anisotropic, non-linear, hyper-elastic material properties applied to tissues of the valve while the first-order Ogden model reflected the best compatibility with the empirical data. Hemodynamic blood pressure of the cardiovascular system is applied on the leaflets as uniform loads varying by time, and exposure to high acceleration loads imposed on models. Immersed boundary method used for simulation of fluid in a cardiac cycle. In comparison between healthy and pathologic models, stress values and chordal tensions are increased, by nearly threefold and twofold, respectively. Stress concentration on leaflets is reduced by 75% after performing a successful surgical repair on the pathological model. Crash acceleration loads led to more significant stress and chordae tension on models, by 27% and 23%, respectively. It is concluded that a more sophisticated model could lead to a better understanding of human heart valve biomechanics in various conditions. If a preoperative plan is developed based on these modeling methods, the requirement for multiple successive repairs would be eliminated, operative times are shortened, and patient outcomes are improved.

A Systematic Review of Individualized Heart Surgery with a Personalized Prosthesis

Personalized surgery is not just a new trend but rather a patient-specific approach to therapy that makes it possible to adopt a targeted approach for a specific patient and closely mirrors the approach of personalized medicine. However, the application of tailored surgery in the context of cardiovascular replacement surgery has not been systematically reviewed. The ability to customize a device is highly dependent on the collection of radiological image data for precise prosthesis modeling. These facts are essential to "tailor-made" device design for precise prosthesis implantation. According to this study, computed tomography (CT) was the most prominent imaging modality; however, transesophageal echocardiography and echocardiography were also found to be helpful. Additionally, a dynamic finite element simulation was also found to be an attractive alternative to the finite element analysis for an in-silico experiment. Nonetheless, there is a paucity of relevant publications and only sporadic evidence. More clinical studies have been warranted, notwithstanding that the derived data and results from this insight into the use of therapeutic interventions may be evidence of multiple directives in clinical practices and beyond. This study may help the integration of personalized devices for better comprehension of predicted clinical outcomes, thus leading towards enhanced performance gains.

Assessment of laparoscopic intracorporeal intestinal anastomosis training using simulation-based 3D printed models: exploring surgical performance and learning curves

BACKGROUND AND AIMS

Intestinal anastomosis is a clinical procedure widely used to reconstruct the digestive tract, but authentic laparoscopic intracorporeal intestinal anastomosis (LIIA) models are lacking. However, three-dimensional (3D) printing can enable authentic and reusable models. In this paper, a novel cost-effective 3D-printing training model of LIIA is designed and the authenticity and validity of the model are tested.

METHODS

A fused deposition modeling 3D printing and an assembled lab model were built to test LIIA. Fifteen surgeons were required to perform LIIA, and their operation score and time were recorded and analyzed. Five experts were invited to assess the face and content validity of the models. A study was also performed to further evaluate and validate the learning curve of surgeons.

RESULTS

The difference in modified anastomosis objective structured assessment of technical skills (MAOSATS) scores between the expert, intermediate, and novice groups were significant (64.1±1.8: 48.5±1.7: 29.5±3.1, P <0.001). In addition, the operation time of the procedure was statistically different for all three groups (21.5±1.9: 30.6±2.8:70.7±4.0, P<0.001 ). The five experts rated the face and content validity of the model very highly, with the median being four out of five. Surgeons who underwent repeated training programs showed improved surgical performance. After eight training sessions, the novices' performance was similar to that of the average level of untrained intermediates, while the operation scores of the intermediates were close to that of the average level of experts.

CONCLUSIONS

In this study, it is found that the LIIA model exhibits excellent face, content, and construct validity. Repeated simulation training of the LIIA training program improved the surgeon's operative performance, so the model is considered one of the most effective methods for LIIA training and assessment of surgical quality in the future and for reducing healthcare costs.

Artificially Intelligent Three-Dimensionally-Printed Patient-Specific Instrument Improves Total Hip Arthroplasty Accuracy

BACKGROUND

Patient-specific instrumentation (PSI) has the potential to improve the accuracy of implant positioning in total hip arthroplasty (THA). This prospective clinical study aimed to develop artificial intelligence to increase PSI production efficiency and assess accuracy, clinical outcomes, and learning curves.

METHODS

A convolutional neural network was applied to automatically process computer tomography images. PSI size and position were designed to guide the acetabular preparation and femoral neck resection. Thirty patients who underwent PSI-assisted THAs were matched to thirty patients who underwent free-hand THAs, and the component positions, as well as radiographic and clinical outcomes were analyzed.

RESULTS

PSI-assisted THA was significantly more accurate than free-hand THA at achieving the target component position. The mean absolute errors of cup inclination (P = .004) and anteversion (P < .001) were significantly smaller in the PSI group with fewer outliers. Calcar length (P = .002) and neck length (P = .026) were also more accurate in the PSI group. The leg length discrepancy was significantly lower in the PSI group (P = .002). There were no significant differences in operation time, blood loss, leg length discrepancy, or cup position among the first, second, and last 10 cases.

CONCLUSION

PSI-assisted THA offered more accurate component positions and better radiographic outcomes than free-hand THA. There was no evidence of a learning curve. Our findings suggest that PSI is a convenient and practical option to help surgeons achieve accurate surgical outcomes.

Multimodality imaging for patient selection, procedural guidance, and follow-up of transcatheter interventions for structural heart disease: a consensus document of the EACVI Task Force on Interventional Cardiovascular Imaging: part 1: access routes, transcatheter aortic valve implantation, and transcatheter mitral valve interventions

Transcatheter therapies for the treatment of structural heart diseases (SHD) have expanded dramatically over the last years, thanks to the developments and improvements of devices and imaging techniques, along with the increasing expertise of operators. Imaging, in particular echocardiography, is pivotal during patient selection, procedural monitoring, and follow-up. The imaging assessment of patients undergoing transcatheter interventions places demands on imagers that differ from those of the routine evaluation of patients with SHD, and there is a need for specific expertise for those working in the cath lab. In the context of the current rapid developments and growing use of SHD therapies, this document intends to update the previous consensus document and address new advancements in interventional imaging for access routes and treatment of patients with aortic stenosis and regurgitation, and mitral stenosis and regurgitation.

Transapical Mitral Valve-in-Ring Replacement Using the Innovative System under 3-Dimensional Printing Guidance

BACKGROUND

Transcatheter mitral valve-in-ring replacement (TMViR) is an emerging alternative for patients with recurrent mitral regurgitation (MR) after a prior failed annuloplasty ring. However, intraoperative common issues and complications remain to be addressed.

CASE SUMMARY

We describe the case of a 67-year-old male patient who underwent surgical mitral concomitant tricuspid annuloplasty repair 7 years ago who developed recurrent severe MR (New York Heart Association functional class IV). To avoid a high-risk surgical reoperation, we chose to perform a TMViR using an innovative dedicated device-the Mi-thos system-via a transapical approach. A patient-specific, 3-dimensional printed model was used to guide the procedure to avoid potential challenges. The procedure was performed successfully, and the patient exhibited symptomatic improvement.

CONCLUSIONS

This case report highlights the first use of the innovative Mi-thos system in a TMViR procedure. The findings demonstrate the feasibility and safety of utilizing the Mi-thos system, guided by 3-dimensional printing technology, for patients who have experienced recurrent mitral regurgitation MR following a failed annuloplasty ring.

Trends and Challenges in the Development of 3D-Printed Heart Valves and Other Cardiac Implants: A Review of Current Advances

This article provides a comprehensive review of the current trends and challenges in the development of 3D-printed heart valves and other cardiac implants. By providing personalized solutions and pushing the limits of regenerative medicine, 3D printing technology has revolutionized the field of cardiac healthcare. The use of several organic and synthetic polymers in 3D printing heart valves is explored in this article, with emphasis on both their benefits and drawbacks. In cardiac tissue engineering, stem cells are essential, and their potential to lessen immunological rejection and thrombogenic consequences is highlighted. In the clinical applications section, the article emphasizes the importance of 3D printing in preoperative planning. Surgery results are enhanced when surgeons can visualize and assess the size and placement of implants using patient-specific anatomical models. Customized implants that are designed to match the anatomy of a particular patient reduce the likelihood of complications and enhance postoperative results. The development of physiologically active cardiac implants, made possible by 3D bioprinting, shows promise by eliminating the need for artificial valves. In conclusion, this paper highlights cutting-edge research and the promise of 3D-printed cardiac implants to improve patient outcomes and revolutionize cardiac treatment.

A benchmark study of convolutional neural networks in fully automatic segmentation of aortic root

Recent clinical studies have suggested that introducing 3D patient-specific aortic root models into the pre-operative assessment procedure of transcatheter aortic valve replacement (TAVR) would reduce the incident rate of peri-operative complications. Tradition manual segmentation is labor-intensive and low-efficient, which cannot meet the clinical demands of processing large data volumes. Recent developments in machine learning provided a viable way for accurate and efficient medical image segmentation for 3D patient-specific models automatically. This study quantitively evaluated the auto segmentation quality and efficiency of the four popular segmentation-dedicated three-dimensional (3D) convolutional neural network (CNN) architectures, including 3D UNet, VNet, 3D Res-UNet and SegResNet. All the CNNs were implemented in PyTorch platform, and low-dose CTA image sets of 98 anonymized patients were retrospectively selected from the database for training and testing of the CNNs. The results showed that despite all four 3D CNNs having similar recall, Dice similarity coefficient (DSC), and Jaccard index on the segmentation of the aortic root, the Hausdorff distance (HD) of the segmentation results from 3D Res-UNet is 8.56 ± 2.28, which is only 9.8% higher than that of VNet, but 25.5% and 86.4% lower than that of 3D UNet and SegResNet, respectively. In addition, 3D Res-UNet and VNet also performed better in the 3D deviation location of interest analysis focusing on the aortic valve and the bottom of the aortic root. Although 3D Res-UNet and VNet are evenly matched in the aspect of classical segmentation quality evaluation metrics and 3D deviation location of interest analysis, 3D Res-UNet is the most efficient CNN architecture with an average segmentation time of 0.10 ± 0.04 s, which is 91.2%, 95.3% and 64.3% faster than 3D UNet, VNet and SegResNet, respectively. The results from this study suggested that 3D Res-UNet is a suitable candidate for accurate and fast automatic aortic root segmentation for pre-operative assessment of TAVR.

Left Atrial Thrombus-Are All Atria and Appendages Equal?

Although the left atrial appendage (LAA) seems useless, it has several critical functions that are not fully known yet, such as the causes for being the main origin of cardioembolic stroke. Difficulties arise due to the extreme range of LAA morphologic variability, making the definition of normality challenging and hampering the stratification of thrombotic risk. Furthermore, obtaining quantitative metrics of its anatomy and function from patient data is not straightforward. A multimodality imaging approach, using advanced computational tools for their analysis, allows a complete characterization of the LAA to individualize medical decisions related to left atrial thrombosis patients.

Pre-cath Laboratory Planning for Left Atrial Appendage Occlusion - Optional or Essential?

In the wake of rapid advancement in cardiovascular procedural technologies, physician-led preprocedural planning utilizing multi-modality imaging training is increasingly recognized as invaluable for procedural accuracy. Left atrial appendage occlusion (LAAO) is one such procedure in which complications such as device leak, cardiac injury, and device embolization can be decreased substantially with incorporation of physician driven imaging and digital tools. We discuss the benefits of cardiac CT and 3D printing in preprocedural planning for the Heart Team, as well as novel applications by physicians of intraprocedural 3D angiography and dynamic fusion imaging. Furthermore, incorporation of computational modeling and artificial intelligence (AI) may yield promise. For optimal patient-centric procedural success, we advocate for standardized preprocedural imaging planning by physicians within the Heart Team as an essential part of LAAO.

Development and evaluation of a portable and soft 3D-printed cast for laparoscopic choledochojejunostomy model in surgical training

BACKGROUND

Laparoscopic choledochojejunostomy (LCJ) is an essential basic skill for biliary surgeons. Therefore, we established a convenient and effective LCJ 3D printing model to evaluate whether the model could simulate the actual operation situation and determine its effectiveness and validity in surgical training.

METHODS

A 3D printing dry laboratory model was established to simulate LCJ. The face and content validity of the model were evaluated by six experienced biliary surgeons based on 5-point Likert scale questionnaires. A total of 15 surgeons with different levels of experience performed LCJ on the model and evaluated the structural validity of the model using the objective structured assessment of technical skills (OSATS). Simultaneously, the operation time of each surgery was also recorded. A study was also performed to further evaluate the learning curve of residents.

RESULTS

The operating space score of the model was 4.83 ± 0.41 points. The impression score of bile duct and intestinal canal was 4.33 ± 0.52 and 4.17 ± 0.41 points, respectively. The tactile sensation score of bile duct suture and intestinal canal suture was 4.00 ± 0.63 and 3.83 ± 0.41points, respectively. The OSATS score for model operation in the attending group was 29.20 ± 0.45 points, which was significantly higher than that in the fellow group (26.80 ± 1.10, P = 0.007) and the resident group (19.80 ± 1.30, P < 0.001). In addition, there was a statistical difference in operation time among surgeons of different experience levels (P < 0.05). Residents could significantly improve the surgical score and shorten the time of LCJ through repeated training.

CONCLUSIONS

The 3D printing LCJ model can simulate the real operation scenes and distinguish surgeons with different levels of experience. The model is expected to be one of the training methods for biliary tract surgery in the future.

The role of artificial intelligence in surgical simulation

Artificial Intelligence (AI) plays an integral role in enhancing the quality of surgical simulation, which is increasingly becoming a popular tool for enriching the training experience of a surgeon. This spans the spectrum from facilitating preoperative planning, to intraoperative visualisation and guidance, ultimately with the aim of improving patient safety. Although arguably still in its early stages of widespread clinical application, AI technology enables personal evaluation and provides personalised feedback in surgical training simulations. Several forms of surgical visualisation technologies currently in use for anatomical education and presurgical assessment rely on different AI algorithms. However, while it is promising to see clinical examples and technological reports attesting to the efficacy of AI-supported surgical simulators, barriers to wide-spread commercialisation of such devices and software remain complex and multifactorial. High implementation and production costs, scarcity of reports evidencing the superiority of such technology, and intrinsic technological limitations remain at the forefront. As AI technology is key to driving the future of surgical simulation, this paper will review the literature delineating its current state, challenges, and prospects. In addition, a consolidated list of FDA/CE approved AI-powered medical devices for surgical simulation is presented, in order to shed light on the existing gap between academic achievements and the universal commercialisation of AI-enabled simulators. We call for further clinical assessment of AI-supported surgical simulators to support novel regulatory body approved devices and usher surgery into a new era of surgical education.

Case report: Three-dimensional printing as an educational tool for optimal lead positioning to left bundle branch pacing

Left bundle branch pacing (LBBP) has been widely adopted as a physiological pacing approach. However, LBBP fails to achieve in some cases because it is difficult to maintain the orientation of the lead tip perpendicular to the interventricular septum (IVS). Three-dimensional (3D) printing technology has emerged as a promising tool for modeling and teaching cardiovascular interventions. Seeking confirmation of optimal lead placement relative to the IVS, we used 3D printing technology to generate a 3D printed heart from a selected patient with successful and proven LBBP. Our model successfully illustrated that the lead tip was perpendicular to the IVS. Application of the 3D technology has potential to help the early-operator understand the optimal lead placement relative to IVS and diminish the learning-curve.

Left Atrial Appendage Occlusion: Current Stroke Prevention Strategies and a Shift Toward Data-Driven, Patient-Specific Approaches

The left atrial appendage (LAA) is a complex structure with unknown physiologic function protruding from the main body of the left atrium. In patients with atrial fibrillation, the left atrium does not contract effectively. Insufficient atrial and LAA contractility predisposes the LAA morphology to hemostasis and thrombus formation, leading to an increased risk of cardioembolic events. Oral anticoagulation therapies are the mainstay of stroke prevention options for patients; however, not all patients are candidates for long-term oral anticoagulation. Percutaneous occlusion devices are an attractive alternative to long-term anticoagulation therapy, although they are not without limitations, such as peri-implant leakage and device-related thrombosis. Although efforts have been made to reduce these risks, significant interpatient heterogeneity inevitably yields some degree of device-anatomy mismatch that is difficult to resolve using current devices and can ultimately lead to insufficient occlusion and poor patient outcomes. In this state-of-the-art review, we evaluated the anatomy of the LAA as well as the current pathophysiologic understanding and stroke prevention strategies used in the management of the risk of stroke associated with atrial fibrillation. We highlighted recent advances in computed tomography imaging, preprocedural planning, computational modeling, and novel additive manufacturing techniques, which represent the tools needed for a paradigm shift toward patient-centric LAA occlusion. Together, we envisage that these techniques will facilitate a pipeline from the imaging of patient anatomy to patient-specific computational and bench-top models that enable customized, data-driven approaches for LAA occlusion that are engineered specifically to meet each patient's unique needs.

3D-Printing to Plan Complex Transcatheter Paravalvular Leaks Closure

Background: Percutaneous closure of paravalvular leak (PVL) has emerged as an alternative to surgical management in selected cases. Achieving complete PVL occlusion, while respecting prosthesis function remains challenging. A multimodal imaging analysis of PVL morphology before and during the procedure is mandatory to select an appropriate device. We aim to explore the additional value of 3D printing in predicting device related adverse events including mechanical valve leaflet blockade, risk of device embolization and residual shunting. Methods: From the FFPP registries (NCT05089136 and NCT05117359), we included 11 transcatheter PVL closure procedures from three centers for which 3D printed models were produced. Cardiac CT was used for segmentation for 3D printed models (3D-heartmodeling, Caissargues, France). Technology used a laser to fuse very fine powders (TPU Thermoplastic polyurethane) into a final part-laser sintering technology (SLS) with an adapted elasticity. A simulation on 3D printed model was performed using a set of occluders. Results: PVLs were located around aortic prostheses in six cases, mitral prostheses in four cases and tricuspid ring in one case. The device chosen during the simulation on the 3D printed model matched the one implanted in eight cases. In the three other cases, a similar device type was chosen during the procedures but with a different size. A risk of prosthesis leaflet blockade was identified on 3D printed models in four cases. During the procedure, the occluder was removed before release in one case. In another case the device was successfully repositioned and released. In two patients, leaflet impingement was observed post-operatively and surgical device removal had to be performed. Conclusion: In a case-series of complex transcatheter PVL closure procedures, hands-on simulation testing on 3D printed models proved its usefulness to plan and facilitate these challenging procedures.

Complex transcatheter left atrial appendage closure using a tailored trans-jugular approach simulated by 3D printing: a case report

Background

Transcatheter left atrial appendage (LAA) closure (LAAc) is less feasible in patients with unusual LAA anatomy.

Case summary

A 65-year-old woman with persistent atrial fibrillation was referred for LAAc. Transesophageal echocardiography (TEE) revealed spontaneous contrast in the LAA without formation of a thrombus; the LAA shape was tortuous and difficult to assess. A first LAAc procedure was unsuccessful given the unsuitable sheath position. Therefore, a soft three-dimensional (3D) model printing was performed by laser sintering and revealed excessive sheath kinking with an inferior approach, but successful deployment would be feasible using a superior approach. Successful trans-jugular implantation of a Watchman FLX 31 device in stable position without residual leakage was achieved during the subsequent procedure. At 3-month follow-up, and after cessation of oral anticoagulation, the patient’s symptoms improved. Imaging demonstrated complete LAA occlusion and correct placement of the device along the LAA superior axis.

Discussion

This is the first-reported clinical case of a complex transcatheter LAAc through a trans-jugular approach. Simulating the patient’s anatomy with a laser sintering 3D-printed model showed why the transfemoral approach failed, validated the trans-jugular procedure, enabled selection of the simple curve access sheath that had the most direct trajectory towards the LAA, confirmed that transseptal puncture was possible, allowed determination of the angle of puncture, enabled selection of the most appropriate LAA device and had a very low cost compared with planning software or other printing methods.

Mitral Valve-in-Valve Implant of a Balloon-Expandable Valve Guided by 3-Dimensional Printing

Background

Our goal was to explore the role of 3-dimensional (3D) printing in facilitating the outcome of a mitral valve-in-valve (V-in-V) implant of a balloon-expandable valve.

Methods

From November 2020 to April 2021, 6 patients with degenerated mitral valves were treated by a transcatheter mitral V-in-V implant of a balloon-expandable valve. 3D printed mitral valve pre- and post-procedure models were prepared to facilitate the process by making individualized plans and evaluating the outcomes.

Results

Each of the 6 patients was successfully implanted with a balloon-expandable valve. From post-procedural images and the 3D printed models, we could clearly observe the valve at the ideal position, with the proper shape and no regurgitation. 3D printed mitral valve models contributed to precise decisions, the avoidance of complications, and the valuation of outcomes.

Conclusions

3D printing plays an important role in guiding the transcatheter mitral V-in-V implant of a balloon-expandable valve.

Clinical Trial Registration

ClinicalTrials.gov Protocol Registration System (NCT02917980).

Engineering Efforts to Refine Compatibility and Duration of Aortic Valve Replacements: An Overview of Previous Expectations and New Promises

The absence of pharmacological treatments to reduce or retard the progression of cardiac valve diseases makes replacement with artificial prostheses (mechanical or bio-prosthetic) essential. Given the increasing incidence of cardiac valve pathologies, there is always a more stringent need for valve replacements that offer enhanced performance and durability. Unfortunately, surgical valve replacement with mechanical or biological substitutes still leads to disadvantages over time. In fact, mechanical valves require a lifetime anticoagulation therapy that leads to a rise in thromboembolic complications, while biological valves are still manufactured with non-living tissue, consisting of aldehyde-treated xenograft material (e.g., bovine pericardium) whose integration into the host fails in the mid- to long-term due to unresolved issues regarding immune-compatibility. While various solutions to these shortcomings are currently under scrutiny, the possibility to implant fully biologically compatible valve replacements remains elusive, at least for large-scale deployment. In this regard, the failure in translation of most of the designed tissue engineered heart valves (TEHVs) to a viable clinical solution has played a major role. In this review, we present a comprehensive overview of the TEHVs developed until now, and critically analyze their strengths and limitations emerging from basic research and clinical trials. Starting from these aspects, we will also discuss strategies currently under investigation to produce valve replacements endowed with a true ability to self-repair, remodel and regenerate. We will discuss these new developments not only considering the scientific/technical framework inherent to the design of novel valve prostheses, but also economical and regulatory aspects, which may be crucial for the success of these novel designs.

Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities

Hepatocellular carcinoma (HCC) constitutes the fifth most frequent malignancy worldwide and the third most frequent cause of cancer-related deaths. Currently, treatment selection is based on the stage of the disease. Emerging fields such as three-dimensional (3D) printing, 3D bioprinting, artificial intelligence (AI), and machine learning (ML) could lead to evidence-based, individualized management of HCC. In this review, we comprehensively report the current applications of 3D printing, 3D bioprinting, and AI/ML-based models in HCC management; we outline the significant challenges to the broad use of these novel technologies in the clinical setting with the goal of identifying means to overcome them, and finally, we discuss the opportunities that arise from these applications. Notably, regarding 3D printing and bioprinting-related challenges, we elaborate on cost and cost-effectiveness, cell sourcing, cell viability, safety, accessibility, regulation, and legal and ethical concerns. Similarly, regarding AI/ML-related challenges, we elaborate on intellectual property, liability, intrinsic biases, data protection, cybersecurity, ethical challenges, and transparency. Our findings show that AI and 3D printing applications in HCC management and healthcare, in general, are steadily expanding; thus, these technologies will be integrated into the clinical setting sooner or later. Therefore, we believe that physicians need to become familiar with these technologies and prepare to engage with them constructively.

Left Atrial Thrombus-Are All Atria and Appendages Equal?

Although the left atrial appendage (LAA) seems useless, it has several critical functions that are not fully known yet, such as the causes for being the main origin of cardioembolic stroke. Difficulties arise due to the extreme range of LAA morphologic variability, making the definition of normality challenging and hampering the stratification of thrombotic risk. Furthermore, obtaining quantitative metrics of its anatomy and function from patient data is not straightforward. A multimodality imaging approach, using advanced computational tools for their analysis, allows a complete characterization of the LAA to individualize medical decisions related to left atrial thrombosis patients.

Pre-cath Laboratory Planning for Left Atrial Appendage Occlusion - Optional or Essential?

In the wake of rapid advancement in cardiovascular procedural technologies, physician-led preprocedural planning utilizing multi-modality imaging training is increasingly recognized as invaluable for procedural accuracy. Left atrial appendage occlusion (LAAO) is one such procedure in which complications such as device leak, cardiac injury, and device embolization can be decreased substantially with incorporation of physician driven imaging and digital tools. We discuss the benefits of cardiac CT and 3D printing in preprocedural planning for the Heart Team, as well as novel applications by physicians of intraprocedural 3D angiography and dynamic fusion imaging. Furthermore, incorporation of computational modeling and artificial intelligence (AI) may yield promise. For optimal patient-centric procedural success, we advocate for standardized preprocedural imaging planning by physicians within the Heart Team as an essential part of LAAO.

Case Report: Three-Dimensional Printing Model for Surgical Planning of Left Ventricular Aneurysm: Evolution Toward Tailoring Surgery

A 59-year-old woman was admitted to the emergency department for heart failure (HF), New York Heart Association (NYHA) IV, showing an anterior, evolved myocardial infarction (MI) with a wide apical left ventricular aneurysm (LVA), ejection fraction (EF) 24%, and global longitudinal strain (GLS) −5. 5% by echo. Cardiac magnetic resonance imaging (MRI) confirmed an apical LVA without thrombus, EF 20%, and a transmural delayed enhancement in the myocardium wall. Coronarography showed a three-vessel disease with occluded proximal left anterior descending (LAD) and proximal right coronary artery (RCA). Based on the cardiac CT scan, we decided to generate a three-dimensional (3D) print model of the heart, for better prediction of residual LV volumes. After LVA surgery plus complete functional revascularization, an optimal agreement was found between predicted and surgical residual LV end-diastolic (24.7 vs. 31.8 ml/m2) and end-systolic (54.1 vs. 69.4 ml/m2) volumes, with an improvement of NYHA class, from IV to I. The patient was discharged uneventfully and at 6- and 12-month follow-up, the NYHA class, and LV volumes were found unchanged. This is a second report describing the use of the 3D print model for the preoperative planning of surgical management of LVA; the first report was described by Jacobs et al. among three patients, one with a malignant tumor and the remaining two patients with LVA. This article focused on the use of the 3D print model to optimize surgical planning and individualize treatment of LVA associated with complete functional revascularization, leading to complete recovery of LV function with a favorable outcome.

Integrative lymph node-mimicking models created with biomaterials and computational tools to study the immune system

The lymph node (LN) is a vital organ of the lymphatic and immune system that enables timely detection, response, and clearance of harmful substances from the body. Each LN comprises of distinct substructures, which host a plethora of immune cell types working in tandem to coordinate complex innate and adaptive immune responses. An improved understanding of LN biology could facilitate treatment in LN-associated pathologies and immunotherapeutic interventions, yet at present, animal models, which often have poor physiological relevance, are the most popular experimental platforms. Emerging biomaterial engineering offers powerful alternatives, with the potential to circumvent limitations of animal models, for in-depth characterization and engineering of the lymphatic and adaptive immune system. In addition, mathematical and computational approaches, particularly in the current age of big data research, are reliable tools to verify and complement biomaterial works. In this review, we first discuss the importance of lymph node in immunity protection followed by recent advances using biomaterials to create in vitro/vivo LN-mimicking models to recreate the lymphoid tissue microstructure and microenvironment, as well as to describe the related immuno-functionality for biological investigation. We also explore the great potential of mathematical and computational models to serve as in silico supports. Furthermore, we suggest how both in vitro/vivo and in silico approaches can be integrated to strengthen basic patho-biological research, translational drug screening and clinical personalized therapies. We hope that this review will promote synergistic collaborations to accelerate progress of LN-mimicking systems to enhance understanding of immuno-complexity.

Renaissance of Cardiac Imaging to Assist Percutaneous Interventions in Congenital Heart Diseases:The Role of Three-Dimensional Echocardiography and Multimodality Imaging

Percutaneous interventions have completely refashioned the management of children with congenital heart diseases (CHD) and the use of non-invasive imaging has become the gold standard to plan and guide these procedures in the modern era. We are now facing a dual challenge to improve the standard of care in low-risk patients, and to shift our strategies from the classic open chest surgery to imaging-guided percutaneous interventions in high-risk patients. Such rapid evolution of ultrasound technologies over the last 20 years have permitted the integration of transthoracic, transesophageal and intracardiac echocardiography into the interventional workflow to improve image guidance and reduce radiation burden from fluoroscopy and angiography. Specifically, miniaturization of transesophageal probe and advances in three-dimensional (3D) imaging techniques have enabled real-time 3D image guidance during complex interventional procedure, In addition, multimodality and fusion imaging techniques harness the strengths of different modalities to enhance understanding of anatomical and spatial relationship between different structures, improving communication and coordination between interventionalists and imaging specialists. In this review, we aim to provide an overview of 3D imaging modalities and multimodal fusion in procedural planning and live guidance of percutaneous interventions. At the present times, 3D imaging can no longer be considered a luxury but a routine clinical tool to improve procedural success and patient outcomes.

The digital heart-lung unit: applications of exponential technology

Exponential technologies such as virtual reality (VR), computational modelling, and additive manufacturing have emerged in the field of cardiology and cardiothoracic surgery. An increasing number of publications that evaluate the clinical role of these technologies are becoming available. Moreover, there is an increase in the number of hospitals and departments that have implemented digital and exponential solutions in clinical workflow. In our centre, we have adopted various exponential technologies in order to improve clinical pre-procedural workflow, patient care, and training and education. In order to provide our view and approach on the implementation of these technologies, in this article, we provide an overview of the currently applied modalities including immersive VR, three-dimensional (3D) computational modelling, VR-based simulations, and additive manufacturing (3D printing). Moreover, we present the potential of these applications in cardiovascular and cardiothoracic medicine, and additionally, we will provide key facilitators, challenges, and recommendations to adopting these technologies in clinical practice.

Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology

Artificial intelligence (AI) is an umbrella term used to describe a cluster of interrelated fields. Machine learning (ML) refers to a model that learns from past data to predict future data. Medicine and particularly gastroenterology and hepatology, are data-rich fields with extensive data repositories, and therefore fruitful ground for AI/ML-based software applications. In this study, we comprehensively review the current applications of AI/ML-based models in these fields and the opportunities that arise from their application. Specifically, we refer to the applications of AI/ML-based models in prevention, diagnosis, management, and prognosis of gastrointestinal bleeding, inflammatory bowel diseases, gastrointestinal premalignant and malignant lesions, other nonmalignant gastrointestinal lesions and diseases, hepatitis B and C infection, chronic liver diseases, hepatocellular carcinoma, cholangiocarcinoma, and primary sclerosing cholangitis. At the same time, we identify the major challenges that restrain the widespread use of these models in healthcare in an effort to explore ways to overcome them. Notably, we elaborate on the concerns regarding intrinsic biases, data protection, cybersecurity, intellectual property, liability, ethical challenges, and transparency. Even at a slower pace than anticipated, AI is infiltrating the healthcare industry. AI in healthcare will become a reality, and every physician will have to engage with it by necessity.

Patient-specific preprocedural planning for tricuspid valve repair and replacement procedures

PURPOSE OF REVIEW

Despite the prevalence of tricuspid valve regurgitation disorders, isolated interventions on tricuspid valves were previously infrequent due to high mortality rates and lack of advanced clinical imaging technology. Due to advancements in cardiovascular imaging and interventional technologies tricuspid valve repairs and replacement interventions became increasingly more attainable.

RECENT FINDINGS

Noninvasive clinical imaging of the tricuspid valve can be challenging, providing anincomplete assessment of unique tricuspid anatomy. 3D printing technology represents an additional tool for more comprehensive preprocedural planning of tricuspid interventions and observation of tricuspid valve geometry. Patient-specific 3D printed replicas of tricuspid valve apparatus are especially useful in highly complicated cases, where physiological tricuspid replicas allow benchtop observation of individual patient's anatomy, device implantation in physiological tricuspid valves and interactions of devices with native tricuspid tissue, frequently leading to optimization or change in operational strategy.

SUMMARY

Comprehensive use of clinical imaging including echocardiography, computed tomography, and cardiac magnetic resonance along with 3D printed modeling is key to successful tricuspid repair and replacements. Patient-specific 3D printed models of tricuspid anatomy can facilitate preprocedural planning, educate patients and clinicians, and improve device design, leading to the overall improvement of patients' outcomes and care.

Anatomic Approach to Transseptal Puncture for Structural Heart Interventions

The use of transseptal puncture continues to rise given the increase in left atrial cardiac interventions. The authors review an anatomic approach to transseptal puncture incorporating multimodality imaging both pre- and intraprocedurally with stepwise escalation algorithms to ensure safe and efficacious large-bore transseptal puncture.

Lifespan Perspective on Congenital Heart Disease Research: JACC State-of-the-Art Review

More than 90% of patients with congenital heart disease (CHD) are nowadays surviving to adulthood and adults account for over two-thirds of the contemporary CHD population in Western countries. Although outcomes are improved, surgery does not cure CHD. Decades of longitudinal observational data are currently motivating a paradigm shift toward a lifespan perspective and proactive approach to CHD care. The aim of this review is to operationalize these emerging concepts by presenting new constructs in CHD research. These concepts include long-term trajectories and a life course epidemiology framework. Focusing on a precision health, we propose to integrate our current knowledge on the genome, phenome, and environome across the CHD lifespan. We also summarize the potential of technology, especially machine learning, to facilitate longitudinal research by embracing big data and multicenter lifelong data collection.

Transverse isotropic modelling of left-ventricle passive filling: Mechanical characterization for epicardial biomaterial manufacturing

Biomaterials applied to the epicardium have been studied intensively in recent years for different therapeutic purposes. Their mechanical influence on the heart, however, has not been clearly identified. Most biomaterials for epicardial applications are manufactured as membranes or cardiac patches that have isotropic geometry, which is not well suited to myocardial wall motion. Myocardial wall motion during systole and diastole produces a complex force in different directions. Membrane or cardiac patches that cannot adapt to these specific directions will exert an inappropriate force on the heart, at the risk of overly restricting or dilating it. Accurately characterizing the mechanical properties of the myocardial wall is thus essential, through analysis of muscle orientation and elasticity. In this study, we investigated the Hertz contact theory for characterizing cardiac tissue, using nanoindentation measurements to distinguish different patterns in the local myocardium. We then evaluated the predictive accuracy of this model using Finite Element Analysis (FEA) to mimic the diastolic phase of the heart. Our results, extracted from instrumented nanoindentation experiments in a liquid environment using five pig hearts, revealed variations in elasticity according to the local orientation of the myocardial tissue. In addition, applying the Finite Element Method (FEM) in our model based on transverse isotropy and local tissue orientation proved able to accurately simulate the passive filling of a left ventricle (LV) in a representative 3D geometry. Our model enables improved understanding of the underlying mechanical properties of the LV wall and can serve as a guide for designing and manufacturing biomedical material better adapted to the local epicardial tissue.