Perioperative Right Ventricular Dysfunction: Analysis of Outcomes

Artificial intelligence-analyzed computed tomography in patients undergoing transcatheter tricuspid valve repair

BACKGROUND

Baseline right ventricular (RV) function derived from 3-dimensional analyses has been demonstrated to be predictive in patients undergoing transcatheter tricuspid valve repair (TTVR). The complex nature of these cumbersome analyses makes patient selection based on established imaging methods challenging. Artificial intelligence (AI)-driven computed tomography (CT) segmentation of the RV might serve as a fast and predictive tool for evaluating patients prior to TTVR.

METHODS

Patients suffering from severe tricuspid regurgitation underwent full cycle cardiac CT. AI-driven analyses were compared to conventional CT analyses. Outcome measures were correlated with survival free of rehospitalization for heart-failure or death after TTVR as the primary endpoint.

RESULTS

Automated AI-based image CT-analysis from 100 patients (mean age 77 ± 8 years, 63% female) showed excellent correlation for chamber quantification compared to conventional, core-lab evaluated CT analysis (R 0.963-0.966; p < 0.001). At 1 year (mean follow-up 229 ± 134 days) the primary endpoint occurred significantly more frequently in patients with reduced RV ejection fraction (EF) <50% (36.6% vs. 13.7%; HR 2.864, CI 1.212-6.763; p = 0.016). Furthermore, patients with dysfunctional RVs defined as end-diastolic RV volume > 210 ml and RV EF <50% demonstrated worse outcome than patients with functional RVs (43.7% vs. 12.2%; HR 3.753, CI 1.621-8.693; p = 0.002).

CONCLUSIONS

Derived RVEF and dysfunctional RV were predictors for death and hospitalization after TTVR. AI-facilitated CT analysis serves as an inter- and intra-observer independent and time-effective tool which may thus aid in optimizing patient selection prior to TTVR in clinical routine and in trials.

Arrhythmias in Patients with Pulmonary Hypertension and Right Ventricular Failure: Importance of Rhythm Control Strategies

Arrhythmias frequently complicate the course of advanced pulmonary hypertension, often leading to hemodynamic compromise, functional impairment, and mortality. Given the importance of right atrial function in this physiology, the restoration and maintenance of sinus rhythm are of critical importance. In this review, we outline the pathophysiology of arrhythmias and their impact on right heart performance; describe considerations for antiarrhythmic drug selection, anesthetic and periprocedural management; and discuss the results of catheter ablation techniques in this complex and challenging patient population.

The Role of Artificial Intelligence and Machine Learning in the Prediction of Right Heart Failure after Left Ventricular Assist Device Implantation: A Comprehensive Review

One of the most challenging and prevalent side effects of LVAD implantation is that of right heart failure (RHF) that may develop afterwards. The purpose of this study is to review and highlight recent advances in the uses of AI in evaluating RHF after LVAD implantation. The available literature was scanned using certain key words (artificial intelligence, machine learning, left ventricular assist device, prediction of right heart failure after LVAD) was scanned within Pubmed, Web of Science, and Google Scholar databases. Conventional risk scoring systems were also summarized, with their pros and cons being included in the results section of this study in order to provide a useful contrast with AI-based models. There are certain interesting and innovative ML approaches towards RHF prediction among the studies reviewed as well as more straightforward approaches that identified certain important predictive clinical parameters. Despite their accomplishments, the resulting AUC scores were far from ideal for these methods to be considered fully sufficient. The reasons for this include the low number of studies, standardized data availability, and lack of prospective studies. Another topic briefly discussed in this study is that relating to the ethical and legal considerations of using AI-based systems in healthcare. In the end, we believe that it would be beneficial for clinicians to not ignore these developments despite the current research indicating more time is needed for AI-based prediction models to achieve a better performance.

Role of Echocardiography for the Perioperative Assessment of the Right Ventricle

Purpose of Review

This review aims to highlight the perioperative echocardiographic evaluation of right ventricular (RV) function with strengths and limitations of commonly used and evolving techniques. It explains the value of transthoracic echocardiography (TTE) and transesophageal echocardiography (TEE) and describes the perioperative changes of RV function echocardiographers should be aware of.

Recent Findings

RV dysfunction is an entity with strong influence on outcome. However, its definition and assessment in the perioperative interval are not well-defined. Moreover, values assessed by TTE and TEE are not interchangeable; while some parameters seem to correlate well, others do not. Myocardial strain analysis and three-dimensional echocardiography may overcome the limitations of conventional echocardiographic measures and provide further insight into perioperative cardiac mechanics.

Summary

Echocardiography has become an essential part of modern anesthesiology in patients with RV dysfunction. It offers the opportunity to evaluate not only global but also regional RV function and distinguish alterations of RV contraction.