A Changing Paradigm in Heart Transplantation: An Integrative Approach for Invasive and Non-Invasive Allograft Rejection Monitoring

Heart Transplantation

Heart transplantation (HTx) remains the last therapeutic resort for patients with advanced heart failure. The present work is a clinically focused review discussing current issues in heart transplantation. Several factors have been associated with the outcome of HTx, such as ABO and HLA compatibility, graft size, ischemic time, age, infections, and the cause of death, as well as imaging and laboratory tests. In 2018, UNOS changed the organ allocation policy for HTx. The aim of this change was to prioritize patients with a more severe clinical condition resulting in a reduction in mortality of people on the waiting list. Advanced heart failure and resistant angina are among the main indications of HTx, whereas active infection, peripheral vascular disease, malignancies, and increased body mass index (BMI) are important contraindications. The main complications of HTx include graft rejection, graft angiopathy, primary graft failure, infection, neoplasms, and retransplantation. Recent advances in the field of HTx include the first two porcine-to-human xenotransplantations, the inclusion of hepatitis C donors, donation after circulatory death, novel monitoring for acute cellular rejection and antibody-mediated rejection, and advances in donor heart preservation and transportation. Lastly, novel immunosuppression therapies such as daratumumab, belatacept, IL 6 directed therapy, and IgG endopeptidase have shown promising results.

Digital pathology in cardiac transplant diagnostics: from biopsies to algorithms

In the field of heart transplantation, the ability to accurately and promptly diagnose cardiac allograft rejection is crucial. This comprehensive review explores the transformative role of digital pathology and computational pathology, especially through machine learning, in this critical domain. These methodologies harness large datasets to extract subtle patterns and valuable information that extend beyond human perceptual capabilities, potentially enhancing diagnostic outcomes. Current research indicates that these computer-based systems could offer accuracy and performance matching, or even exceeding, that of expert pathologists, thereby introducing more objectivity and reducing observer variability. Despite promising results, several challenges such as limited sample sizes, diverse data sources, and the absence of standardized protocols pose significant barriers to the widespread adoption of these techniques. The future of digital pathology in heart transplantation diagnostics depends on utilizing larger, more diverse patient cohorts, standardizing data collection, processing, and evaluation protocols, and fostering collaborative research efforts. The integration of various data types, including clinical, demographic, and imaging information, could further refine diagnostic precision. As researchers address these challenges and promote collaborative efforts, digital pathology has the potential to become an integral part of clinical practice, ultimately improving patient care in heart transplantation.

Amplification of Plasma MicroRNAs for Non-invasive Early Detection of Acute Rejection after Heart Transplantation With Ultrasound-Targeted Microbubble Destruction

OBJECTIVE

Acute rejection (AR) screening has always been the focus of patient management in the first several years after heart transplantation (HT). As potential biomarkers for the non-invasive diagnosis of AR, microRNAs (miRNAs) are limited by their low abundance and complex origin. Ultrasound-targeted microbubble destruction (UTMD) technique could temporarily alter vascular permeability through cavitation. We hypothesized that increasing the permeability of myocardial vessels might enhance the abundance of circulating AR-related miRNAs, thus enabling the non-invasive monitoring of AR.

METHODS

The Evans blue assay was applied to determine efficient UTMD parameters. Blood biochemistry and echocardiographic indicators were used to ensure the safety of the UTMD. AR of the HT model was constructed using Brown-Norway and Lewis rats. Grafted hearts were sonicated with UTMD on postoperative day (POD) 3. The polymerase chain reaction was used to identify upregulated miRNA biomarkers in graft tissues and their relative amounts in the blood.

RESULTS

Amounts of six kinds of plasma miRNA, including miR-142-3p, miR-181a-5p, miR-326-3p, miR-182, miR-155-5p and miR-223-3p, were 10.89 ± 1.36, 13.54 ± 2.15, 9.84 ± 0.70, 8.55 ± 2.00, 12.50 ± 3.96 and 11.02 ± 3.47 times higher in the UTMD group than those in the control group on POD 3. Plasma miRNA abundance in the allograft group without UTMD did not differ from that in the isograft group on POD 3. After FK506 treatment, no miRNAs increased in the plasma after UTMD.

CONCLUSION

UTMD can promote the transfer of AR-related miRNAs from grafted heart tissue to the blood, allowing non-invasive early detection of AR.

Clonal hematopoiesis confers an increased mortality risk in orthotopic heart transplant recipients

Novel risk stratification and non-invasive surveillance methods are needed in orthotopic heart transplant (OHT) to reduce morbidity and mortality post-transplant. Clonal hematopoiesis (CH) refers to the acquisition of specific gene mutations in hematopoietic stem cells linked to enhanced inflammation and worse cardiovascular outcomes. The purpose of this study was to investigate the association between CH and OHT. Blood samples were collected from 127 OHT recipients. Error-corrected sequencing was used to detect CH-associated mutations. We evaluated the association between CH and acute cellular rejection, CMV infection, cardiac allograft vasculopathy (CAV), malignancies, and survival. CH mutations were detected in 26 (20.5%) patients, mostly in DNMT3A, ASXL1, and TET2. Patients with CH showed a higher frequency of CAV grade 2 or 3 (0% vs. 18%, p < .001). Moreover, a higher mortality rate was observed in patients with CH (11 [42%] vs. 15 [15%], p = .008) with an adjusted hazard ratio of 2.9 (95% CI, 1.4-6.3; p = .003). CH was not associated with acute cellular rejection, CMV infection or malignancies. The prevalence of CH in OHT recipients is higher than previously reported for the general population of the same age group, with an associated higher prevalence of CAV and mortality.

Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies

Endomyocardial biopsy (EMB) screening represents the standard of care for detecting allograft rejections after heart transplant. Manual interpretation of EMBs is affected by substantial interobserver and intraobserver variability, which often leads to inappropriate treatment with immunosuppressive drugs, unnecessary follow-up biopsies and poor transplant outcomes. Here we present a deep learning-based artificial intelligence (AI) system for automated assessment of gigapixel whole-slide images obtained from EMBs, which simultaneously addresses detection, subtyping and grading of allograft rejection. To assess model performance, we curated a large dataset from the United States, as well as independent test cohorts from Turkey and Switzerland, which includes large-scale variability across populations, sample preparations and slide scanning instrumentation. The model detects allograft rejection with an area under the receiver operating characteristic curve (AUC) of 0.962; assesses the cellular and antibody-mediated rejection type with AUCs of 0.958 and 0.874, respectively; detects Quilty B lesions, benign mimics of rejection, with an AUC of 0.939; and differentiates between low-grade and high-grade rejections with an AUC of 0.833. In a human reader study, the AI system showed non-inferior performance to conventional assessment and reduced interobserver variability and assessment time. This robust evaluation of cardiac allograft rejection paves the way for clinical trials to establish the efficacy of AI-assisted EMB assessment and its potential for improving heart transplant outcomes.

Noninvasive methods to reduce cardiac complications postheart transplant

PURPOSE OF REVIEW

Long-term success of heart transplantation is limited by allograft rejection and cardiac allograft vasculopathy (CAV). Classic management has relied on frequent invasive testing to screen for early features of rejection and CAV to allow for early treatment. In this review, we discuss new developments in the screening and prevention of allograft rejection and CAV.

RECENT FINDINGS

Newer noninvasive screening techniques show excellent sensitivity and specificity for the detection of clinically significant rejection. New biomarkers and treatment targets continue to be identified and await further studies regarding their utility in preventing allograft vasculopathy.

SUMMARY

Noninvasive imaging and biomarker testing continue to show promise as alternatives to invasive testing for allograft rejection. Continued validation of their effectiveness may lead to new surveillance protocols with reduced frequency of invasive testing. Furthermore, these noninvasive methods will allow for more personalized strategies to reduce the complications of long-term immunosuppression whereas continuing the decline in the overall rate of allograft rejection.

The Role of Machine Learning in Cardiovascular Pathology

Machine learning has seen slow but steady uptake in diagnostic pathology over the past decade to assess digital whole-slide images. Machine learning tools have incredible potential to standardise, and likely even improve, histopathologic diagnoses, but they are not yet widely used in clinical practice. We describe the principles of these tools and technologies and some successful preclinical and pretranslational efforts in cardiovascular pathology, as well as a roadmap for moving forward. In nonhuman animal models, one proof-of-principle application is in rodent progressive cardiomyopathy, which is of particular significance to drug toxicity studies. Basic science successes include screening the quality of differentiated stem cells and characterising cardiomyocyte developmental stages, with potential applications for research and toxicology/drug safety screening using derived or native human pluripotent stem cells differentiated into cardiomyocytes. Translational studies of particular note include those with success in diagnosing the various forms of heart allograft rejection. For fully realising the value of these tools in clinical cardiovascular pathology, we identify 3 essential challenges. First is image quality standardisation to ensure that algorithms can be developed and implemented on robust, consistent data. The second is consensus diagnosis; experts don't always agree, and thus "truth" may be difficult to establish, but the algorithms themselves may provide a solution. The third is the need for large-enough data sets to facilitate robust algorithm development, necessitating large cross-institutional shared image databases. The power of histopathology-based machine learning technologies is tremendous, and we outline the next steps needed to capitalise on this power.

Molecular Diagnosis of Rejection in Heart Transplantation

Despite the overall success of heart transplantation as a definitive treatment for endstage heart failure, cardiac allograft rejection remains an important cause of morbidity and mortality. Endomyocardial biopsy has been the standard of care for rejection monitoring, but is associated with several diagnostic limitations and serious procedural complications. The use of molecular diagnostics has emerged over the past decade as a tool to potentially circumvent some of these limitations. We present an update on novel molecular approaches to detecting transplant rejection, focusing on 4 categories: microarray technology, gene expression profiling, cell-free DNA and microRNA.

Novel biomarkers useful in surveillance of graft rejection after heart transplantation

Heart transplantation (HTx) is considered the gold-standard therapy for the treatment of advanced heart failure (HF). The long-term survival in HTx is hindered by graft failure which represents one of the major limitations of the long-term efficacy of HTx. Endomyocardial biopsy (EMB) and the evaluation of donor-specific antibodies (DSA) are currently considered the essential diagnostic tools for surveillance of graft rejection. Recently, new molecular biomarkers (including cell-free DeoxyriboNucleic Acid, exosomes, gene profiling microarray, nanostring, reverse transcriptase multiplex ligation-dependent probe amplification, proteomics and immune profiling by quantitative multiplex immunofluorescence) provide useful information on mechanisms of graft rejection. The ambitious role of a similar change of perspective is aimed at a better and longer graft preservation.