Diagnostic Accuracy of Cardiovascular Magnetic Resonance for Cardiac Transplant Rejection: A Meta-analysis

Cardiac magnetic resonance assessment of acute rejection and cardiac allograft vasculopathy in pediatric heart transplant

BACKGROUND

In pediatric heart transplant (PHT), cardiac catheterization with endomyocardial biopsy (EMB) is standard for diagnosing acute rejection (AR) and cardiac allograft vasculopathy (CAV) but is costly and invasive.

OBJECTIVES

To evaluate the ability of cardiac magnetic resonance (CMR) to noninvasively identify differences in PHT patients with AR and CAV.

METHODS

Patients were enrolled at three children's hospitals. Data were collected from surveillance EMB or EMB for-cause AR. Patients were excluded if they had concurrent diagnoses of AR and CAV, CMR obtained >7days from AR diagnosis, they had EMB negative AR, or could not undergo contrasted, unsedated CMR. Kruskal-Wallis test was used to compare groups: (1) No AR or CAV (Healthy), (2) AR, (3) CAV. Wilcoxon rank-sum test was used for pairwise comparisons.

RESULTS

Fifty-nine patients met inclusion criteria (median age 17years [IQR 15-19]) 10 (17%) with AR, and 11 (19%) with CAV. AR subjects had worse left ventricular ejection fraction compared to Healthy patients (p = 0.001). Global circumferential strain (GCS) was worse in AR (p = 0.054) and CAV (p = 0.019), compared to Healthy patients. ECV, native T1, and T2 z-scores were elevated in patients with AR.

CONCLUSIONS

CMR was able to identify differences between CAV and AR. CAV subjects had normal global function but abnormal GCS which may suggest subclinical dysfunction. AR patients have abnormal function and tissue characteristics consistent with edema (elevated ECV, native T1 and T2 z-scores). Characterization of CMR patterns is critical for the development of noninvasive biomarkers for PHT and may decrease dependence on EMB.

Cardiac transplant rejection assessment with 18F-FDG PET-CT: initial single-centre experience for diagnosis and management

BACKGROUND

Rejection is a major cause of mortality and morbidity in heart transplant (HTx) recipients. Current methods for diagnosing rejection have limitations. Imaging methods to map the entire left ventricle and reliably identify potential sites of rejection is lacking. Animal studies suggest FDG PET-CT (FDG PET) could have potential application in human HTx recipients.

METHODS

Between December 2020 and February 2022, all HTx recipients at Harefield Hospital, London, with definite or suspected rejection underwent FDG PET in addition to routine work-up.

RESULTS

Thirty HTx recipients (12 with definite and 18 with suspected rejection) underwent FDG PET scans. Overall, 12 of the 30 patients had FDG PET with increased myocardial avidity, of whom 2 died (17%). Eighteen patients of the 30 patients had FDG PET with no myocardial avidity and all are alive (100%, p = 0.15). All patients with definite rejection, scanned within 2 weeks of starting anti-rejection treatment, showed increased myocardial avidity. In 5 cases, FDG PET showed myocardial avidity beyond 6 weeks despite pulsed steroid treatment, suggesting unresolved myocardial rejection.

CONCLUSION

Preliminary findings suggest FDG PET may have a role in diagnosing cardiac transplant rejection. Future blinded studies are needed to help further validate this.

Advancements in Heart Transplantation: Donor-Derived Cell-Free DNA as Next-Generation Biomarker

Heart failure, particularly in its advanced stages, significantly impacts quality of life. Despite progress in Guideline-Directed Medical Therapy (GDMT) and invasive treatments, heart transplantation (HT) remains the primary option for severe cases. However, complications such as graft rejection present significant challenges that necessitate effective monitoring. Endomyocardial biopsy (EMB) is the gold standard for detecting rejection, but its invasive nature, associated risks, and healthcare costs have shifted interest in non-invasive techniques. Donor-derived cell-free DNA (dd-cfDNA) has gained attention as a promising non-invasive biomarker for monitoring graft rejection. Compared to EMB, dd-cfDNA detects graft rejection early and enables clinicians to adjust immunosuppression promptly. Despite its advantages, dd-cfDNA testing faces challenges, such as the need for specialized technology and potential inaccuracies due to other clinical conditions. Additionally, dd-cfDNA cannot yet differentiate between types of graft rejection, and its effectiveness in chronic rejection remains unclear. Research is ongoing to set precise standards for dd-cfDNA levels, which would enhance its diagnostic accuracy and help in clinical decisions. The article also points to the future of HT monitoring, which may involve combining dd-cfDNA with other biomarkers and integrating artificial intelligence to improve diagnostic capabilities and personalize patient care. Furthermore, it emphasizes both global and racial inequalities in dd-cfDNA testing and the ethical issues related to its use in transplant medicine.

Cardiac magnetic resonance imaging in detection of progressive graft dysfunction in pediatric heart transplantation

BACKGROUND

Chronic graft failure (CGF) in pediatric heart transplant (PHT) is multifactorial and may present with findings of fibrosis and microvessel disease (MVD) on endomyocardial biopsy (EMB). There is no optimal CGF surveillance method. We evaluated associations between cardiac magnetic resonance imaging (CMR) and historical/EMB correlates of CGF to assess CMR's utility as a surveillance method.

METHODS

Retrospective analysis of PHT undergoing comprehensive CMR between September 2015 and January 2022 was performed. EMB within 6 months was graded for fibrosis (scale 0-5) and MVD (number of capillaries with stenotic wall thickening per field of view). Correlation analysis and logistic regression were performed.

RESULTS

Forty-seven PHT with median age at CMR of 15.7 years (11.6, 19.3) and time from transplant of 6.4 years (4.1, 11.0) were studied. Cardiac allograft vasculopathy (CAV) was present in 11/44 (22.0%) and historical rejection in 14/41 (34.2%). CAV was associated with higher global T2 (49.0 vs. 47.0 ms; p = 0.038) and peak T2 (57.0 vs. 53.0 ms; p = 0.013) on CMR. Historical rejection was associated with higher global T2 (49.0 vs. 47.0 ms; p = 0.007) and peak T2 (57.0 vs. 53.0 ms; p = 0.03) as well as global extracellular volume (31.0 vs. 26.3%; p = 0.03). Higher fibrosis score on EMB correlated with smaller indexed left ventricular mass (rho = -0.34; p = 0.019) and greater degree of MVD with lower indexed left ventricular end-diastolic volume (rho = -0.35; p = 0.017).

CONCLUSION

Adverse ventricular remodeling and abnormal myocardial characteristics on CMR are present in PHT with CAV, historical rejection, as well as greater fibrosis and MVD on EMB. CMR has the potential use for screening of CGF.

Serial electrocardiograms at follow-up for early detection of transplanted heart rejection: A viewpoint

This viewpoint proposed that serial electrocardiograms (ECG) could be used to monitor for heart transplantation (HT) rejection, based on the expected attenuation of the amplitude of ECG QRS complexes (attQRS) engendered by the rejection-induced decrease in electrical resistance due to the underlying myocardial edema (ME). Previous work in humans has shown attQRS in the setting of a diverse array of edematous states, affecting the myocardium (i.e, ME) and the body volume conductor "enveloping" the heart. Also, animal and human experience has revealed low electrical resistance during mild/moderate HT rejection. Studies with serial correlations of endomyocardial biopsy (EMB), echocardiography, cardiac magnetic resonance imaging, and ECG are recommended, which will merely require recording of an ECG, when EMB and imaging studies are carried out for monitoring of post-HT rejection.

2022 Artificial intelligence primer for the nuclear cardiologist

Driven by advances in computing power, the past decade has seen rapid developments in artificial intelligence (AI) which now offers potential enhancements to every aspect of nuclear cardiology workflow including acquisition, reconstruction, segmentation, direct image analysis, and interpretation; as well as facilitating clinical and imaging big-data integration for superior personalized risk stratification. To understand the relevance and potential of AI in their field, this review provides a primer for nuclear cardiologists in 2022. The aim is to explain terminology and provide a summary of key current implementations, challenges, and future aspirations of AI-based enhancements to nuclear cardiology.

Artificial intelligence for disease diagnosis and risk prediction in nuclear cardiology

Artificial intelligence (AI) techniques have emerged as a highly efficient approach to accurately and rapidly interpret diagnostic imaging and may play a vital role in nuclear cardiology. In nuclear cardiology, there are many clinical, stress, and imaging variables potentially available, which need to be optimally integrated to predict the presence of obstructive coronary artery disease (CAD) or predict the risk of cardiovascular events. In spite of clinical awareness of a large number of potential variables, it is difficult for physicians to integrate multiple features consistently and objectively. Machine learning (ML) is particularly well suited to integrating this vast array of information to provide patient-specific predictions. Deep learning (DL), a branch of ML characterized by a multi-layered convolutional model architecture, can extract information directly from images and identify latent image features associated with a specific prediction. This review will discuss the latest AI applications to disease diagnosis and risk prediction in nuclear cardiology with a focus on potential clinical applications.

Cardiac Allograft Injuries: A Review of Approaches to a Common Dilemma, With Emphasis on Emerging Techniques

Clinical features of allograft injury are often unreliable, and context within the transplant journey is key. In the setting of post-transplant allograft dysfunction, the choice of initial investigation depends on clinical assessment and history. One of the major considerations is the time post transplantation in helping to decide a likely cause for allograft injury. Immediately post transplantation, it is important to consider donor factors (including donor demographics as well as immunological match), ischaemic times, surgical issues as well as early rejection. Clinical suspicion needs to remain high with variable presentations, including haemodynamic instability, arrhythmia, as well as left ventricular dysfunction. Symptoms of allograft dysfunction may include dyspnoea, exertional intolerance, dizziness / lightheadedness, palpitations, as well as right or left heart failure. In the coming weeks and months, endomyocardial biopsy and blood-based biomarkers may be helpful including high sensitivity troponin and donor-derived cell-free DNA. Molecular markers for rejection are hopeful, and may also be useful in non-ischaemic causes of allograft dysfunction. Screening remains important late post heart transplant due to variety of signs associated with rejection (early) and lack of typical anginal symptoms (later). New imaging modalities - especially cardiac magnetic resonance imaging, have been shown to be useful for assessing cause of allograft dysfunction including ischemia, infarction and rejection.