Artificial intelligence and telemedicine promise to reshape patient care to an unprecedented extent, leading to a safer and more sustainable work environment and improved patient care. In this article, we summarize how these emerging technologies can be used in the care of cardiovascular patients in such ways as fall detection and prevention, virtual nursing, remote case support, automation of instrument counts in the operating room, and efficiency optimization in the cardiovascular suite.

The past decade has seen significant advances in dynamic imaging of the aorta. Today’s vascular surgeons have the opportunity to choose from a wide array of imaging modalities to evaluate different aortic pathologies. While vascular ultrasound and aortography are considered to be the bread and butter imaging modalities, newer dynamic imaging techniques provide time-resolved information in various aortic pathologies. However, despite growing evidence of their advantages in the literature, they have not been routinely adopted. In order to understand the role of these emerging modalities, one must understand their principles, advantages, and limitations in the context of various clinical scenarios. In this review, we provide an overview of dynamic imaging techniques for aortic pathologies and describe various dynamic computed tomography and magnetic resonance imaging protocols, clinical applications, and potential future directions.

Ruptured abdominal aortic aneurysm (RAAA) is an acute aortic condition that requires emergent intervention and appropriate continuity of care to optimize patient outcomes. We describe the standardized RAAA protocol at the Houston Methodist Hospital Acute Aortic Treatment Center, developed to navigate critical patient transfer periods safely and efficiently, make crucial decisions about surgical intervention, and clearly communicate these plans with other care team providers. Our workflow is organized into five phases: prehospital, preoperative, intraoperative, postoperative, and post-discharge. We identify the transfer center, anesthesia, operating room nursing staff, surgeons, and intensive care unit as key entities of our acute aortic pathology care team. This systematic protocol for the management of acute aortic emergencies such as RAAA identifies critical decision points, potential complications at each stage, and recommendations for best practice.

Objective: Three-dimensional models are increasingly used to facilitate the positioning of fenestrations on a physician-modified endograft (PMEG) during the fenestrated endovascular aortic repair (FEVAR) of complex abdominal aortic aneurysms (CAAA). The punch card technique was developed to eliminate the 3D printing workflow while preserving the benefits of having a 3D model. The objective of the current study is to evaluate the performance of the purpose-built software EndoDraft compared to manual punch card design. Methods: An experimental study was performed to compare software-assisted and manual punch card creation. Fenestration data of readily available procedural plans were used for patients who underwent elective FEVAR for CAAA from May 2023 to September 2024. Time needed to complete punch card planning was recorded as well as inaccuracies of the manual technique were evaluated by measuring the vertical and circumferential position of the fenestrations on the punch card. Results: A total of 76 punch cards and 288 fenestrations were made based on 38 patients’ fenestration data. Preparation time was 233.0 ± 40.3 seconds for the manual group, whereas 63.2 ± 21.5 seconds for the software-aided group (p<0.001). Longitudinal imprecision of the manual punch card was 0.8 ± 0.6 mm for the celiac axis (CA), 1.0 ± 0.6 mm for the superior mesenteric artery (SMA), 0.8 ± 0.5 mm for the right renal artery (RRen), whereas 1.0 ± 0.6 mm for the left renal artery (LRen). Circumferential errors of the same fenestrations were 0.4 ± 0.4 mm for the CA, 0.4 ± 0.4 mm for the SMA, 0.6 ± 0.5 mm for the RRen, and 0.5 ± 0.4 mm for the LRen. No significant difference between the completion time recorded at the beginning and at the end of the software’s learning curve was detected (77.8 ± 29.4 s vs 55.8 ± 18.5 s, p=0.15). Conclusions: The software-assisted design of the punch card is associated with higher precision and a vast improvement in speed compared to the manual technique during PMEG planning for the endovascular treatment of CAAAs. The purpose-built EndoDraft tool was made freely available in an online repository offering a more streamlined workflow. Clinical Impact: EndoDraft® could meaningfully streamline the PMEG-FEVAR workflow by replacing manual punch-card drafting with rapid, software-generated, proportionally scaled templates that are produced in about one minute rather than several minutes, while reducing the small but measurable positioning errors inherent to hand drawing. For clinicians, this means a more reproducible planning step, less cognitive load and “ruler time” during preparation, and a workflow that is easier to standardize across operators with a short learning curve. The key innovation is purpose-built automation with integrated 2D/virtual 3D visualization and direct PDF output, made freely available to support wider adoption.

The recent decline in RAAA incidence and the fast paced scenario with associated challenges regarding training calls for initiative for a better training environment to maximize learning. This led us to the creation of a pulsatile human cadaveric RAAA model. Fresh frozen cadaver was used to create RAAA with BioTissue in hybrid suite with ability to perform CBCTA for sizing. As a proof of concept, the model was used to perform REVAR with proximal CODA balloon control. The model proved to be feasible and we believe it is a better environment to train and gain adequate proficiency in RAAA management.