In the world of clinic treatments, 3D-printed tissue constructs have emerged as a less invasive treatment method for various ailments. Printing processes, scaffold and scaffold free materials, cells used, and imaging for analysis are all factors that must be observed in order to develop successful 3D tissue constructs for clinical applications. However, current research in 3D bioprinting model development lacks diverse methods of successful vascularization as a result of issues with scaling, size, and variations in printing method. This study analyzes the methods of printing, bioinks used, and analysis techniques in 3D bioprinting for vascularization. These methods are discussed and evaluated to determine the most optimal strategies of 3D bioprinting for successful vascularization. Integrating stem and endothelial cells in prints, selecting the type of bioink according to its physical properties, and choosing a printing method according to physical properties of the desired printed tissue are steps that will aid in the successful development of a bioprinted tissue and its vascularization.

Computational fluid dynamics (CFD) is a tool that allows for the analysis of otherwise unobservable blood flow patterns. In the context of medicine, CFD enables researchers to better understand acute and chronic pathophysiology as well as utilize modeling tools to predict blood flow patterns in response to surgical intervention. Such a tool is particularly useful in the field of congenital heart disease (CHD), where complex geometries and patient-specific pathology are common. Research applying CFD to study CHDs has significantly grown in the last twenty years, with new methodologies and recommendations being published at an even faster pace in the last decade. Many currently available reviews are focused on a particular area of progress or on the technical approaches to CFD geared toward the clinician. This review focuses on CFD application within the major domains of CHD research, specifically single ventricle defects and aortic coarctation, reviewing consensus seminal work while highlighting more recent avenues of study. Balancing discussion of CFD parameters with potential clinical implications of study results, this review not only aims to provide cardiovascular professionals context for the technical advancements being made in the field but also a sense of contemporary CFD’s utility in clinical practice.

The growing number of wearable electrocardiogram (ECG) users today, combined with the surge of artificial intelligence (AI) and machine learning (ML) in medical signal-processing, has led to a new age of wearable-enabled monitoring for cardiac conditions. With the development of advanced processing methods, wearables offer the opportunity to monitor and predict the probability of various cardiac conditions, from cardiac ischemia to arrhythmias, by collecting personalized data from the comfort of a user’s home. Although such technology has not yet entered the market, AI and ML research training specifically on wearable-based ECG data has grown significantly in the last decade. Despite this growing niche, there are few current articles reviewing the applications of these techniques in wearable ECG technology. To fill this gap, this article first primes the reader to the practical tools required to build models from ambulatory ECG, synthesizes the state of the field across major cardiac condition use-cases, and finally highlights recurring limitations in the current literature and outlines the need to improve reliability if this technology were to be widely utilized. As a result, we aim to help readers who otherwise may be unfamiliar with the specifics of these tools and their applications to form an interpretation of the current capabilities of AI/ML in wearable ECGs and identify key steps required for improvement based on the most current research.

Surgical resection is the main curative option for non-small-cell lung cancer. Pulmonary resections have historically been performed through a highly morbid open thoracotomy. Minimally invasive approaches to pulmonary resection have revolutionized the field with reduced perioperative morbidity, including less postoperative pain, length-of-stay, and complications, while potentially enhancing oncologic outcomes. In its current generation, robotically performed video-assisted thoracoscopic surgery (R-VATS) offers numerous advantages over traditional VATS and is increasingly becoming the standard of care. In this review, we highlight the technical and clinical advantages of R-VATS compared to VATS and traditional thoracotomy. We reflect on emerging advancements in the utilization of the minimally invasive platform for single-anesthetic marking and resection of pulmonary nodules, the integration of artificial intelligence and radiomics to augment preoperative planning, and the expanding role of single-incision robotic surgery. Lastly, we discuss the financial considerations of implementing a robotic thoracic platform and identify opportunities to optimize costs.

Fontan patients experience anatomical remodeling over time, yet the mechanisms driving these changes remain unclear. This study aimed to characterize full-route Fontan remodeling and evaluate whether observed morphological changes arise from somatic growth alone or from the combined influence of conduit properties, surgical design, thoracic anatomy, and mechanical forces. Five Fontan patients (four extracardiac, one lateral tunnel) underwent analysis using two MRI-derived 3D models obtained between 1 and 4 years apart. Directional displacement was assessed using 3D shape overlays, surface geometry was quantified using the Koenderink Shape Index (KSI), and patient-specific growth mapping estimated localized tissue dynamics. Statistical analyses included a one-sample t-test for mean anterior displacement, the Grubbs’ test for outlier detection, and the Wilcoxon signed-rank test for KSI comparisons across time points. All patients exhibited anterior displacement of the Fontan route, with a mean shift of 0.29″ ± 0.33″ and one significant outlier (lateral tunnel, 0.87″). Four of five patients showed increased convexity over time. Growth mapping revealed minimal, heterogeneous native-tissue expansion, with localized growth up to 0.2 mm/year. Individual remodeling trajectories varied and did not consistently align with localized anterior growth, indicating that Fontan route remodeling is highly individualized and cannot be explained by somatic growth alone. This retrospective longitudinal case series study highlights the value of quantitative 3D geometric tools for assessing subtle Fontan route remodeling and supports the feasibility of growth-aware, patient-specific modeling frameworks in single-ventricle physiology.