Optical Coherence Tomography in Cardiac Allograft Vasculopathy: State-of-the-Art Review

Transplant Vasculopathy Versus Native Atherosclerosis: Similarities and Differences

Cardiac allograft vasculopathy (CAV) is one of the leading causes of graft failure and death after heart transplantation. Alloimmune-dependent and -independent factors trigger the pathogenesis of CAV through activation of the recipients' (and to a lesser extent donor-derived) immune system. Early diagnosis of CAV is complicated by the lack of clinical symptoms for ischemia in the denervated heart, by the impact of early functional coronary alterations, by the insensitivity of coronary angiography, and by the involvement of small intramyocardial vessels. CAV in general is a panarterial disease confined to the allograft and characterized by diffuse concentric longitudinal intimal hyperplasia in the epicardial coronary arteries and concentric medial disease in the microvasculature. Plaque composition in CAV may include early fibrous and fibrofatty tissue and late atheromatous calcification. In contrast, native coronary atherosclerosis usually develops over decades, is focal, noncircumferential, and typically diminishes proximal parts of the epicardial vessels. The rapid and early development of CAV has an adverse prognostic impact, and current prevention and treatment strategies are of limited efficacy compared with established strategies in native atherosclerosis. Following acute coronary syndromes, patients after heart transplantation were more likely to have accompanying cardiogenic shock and higher mortality compared with acute coronary syndromes patients with native hearts.

Quantitative flow ratio computed from invasive coronary angiography as a predictor for cardiac allograft vasculopathy after cardiac transplant

Cardiac allograft vasculopathy (CAV) is a significant determinant of long-term survival in heart transplant recipients. Standard CAV screening typically utilizes invasive coronary angiography (ICA). Quantitative flow ratio (QFR) is a computational method for functional testing of coronary stenosis, and may add diagnostic value to ICA in assessing CAV. Consecutive subjects who received heart transplantation and underwent two separate routine coronary angiograms between January 2013 and April 2016 were enrolled. Coronary angiograms and IVUS were performed per local protocol at 1, 2, 3 and 5 years post-transplant. QFR was calculated offline. CAV was assessed semi-quantitively based on coronary angiogram results. Twenty-two patients were enrolled. Mean time from transplant to first included ICA was 2.1 years. QFR in at least 1 coronary vessel was interpretable in 19/22 (86%) of initial ICA (QFR1). QFR1 correlated well with the CAV score derived from the second ICA (CAV2) with a clustering of CAV at lower QFR values. In a receiver-operating characteristic (ROC) analysis, an optimal QFR threshold of 0.88 yielded 0.94 sensitivity and 0.67 specificity (AUC of 0.79) for at least non-obstructive subsequent CAV. Initial angiographically and intravascular ultrasound derived CAV severity poorly predicted subsequent CAV severity. QFR derived from invasive coronary angiography predicts subsequent development of CAV more accurately than angiography and intravascular ultrasound. This novel method of coronary flow assessment in recipients of heart transplantation may be useful to diagnose and predict subsequent CAV development.

Deep-learning visualization enhancement method for optical coherence tomography angiography in dermatology

Optical coherence tomography angiography (OCTA) in dermatology usually suffers from low image quality due to the highly scattering property of the skin, the complexity of cutaneous vasculature, and limited acquisition time. Deep-learning methods have achieved great success in many applications. However, the deep learning approach to improve dermatological OCTA images has not been investigated due to the requirement of high-performance OCTA systems and difficulty of obtaining high-quality images as ground truth. This study aims to generate proper datasets and develop a robust deep learning method to enhance the skin OCTA images. A swept-source skin OCTA system was employed to create low-quality and high-quality OCTA images with different scanning protocols. We propose a model named vascular visualization enhancement generative adversarial network and adopt an optimized data augmentation strategy and perceptual content loss function to achieve better image enhancement effect with small amount of training data. We demonstrate the superiority of the proposed method in skin OCTA image enhancement by quantitative and qualitative comparisons.

A case report of cardiac allograft vasculopathy complicated with coronary vasospasm: insights from near-infrared spectroscopy, intravascular ultrasound, and optical coherence tomography

Background

Cardiac allograft vasculopathy (CAV) remains a major complication after heart transplantation. Although coronary vasospasm after heart transplantation has occasionally been reported, the association between CAV and coronary vasospasm remains unclear.

Case summary

A 68-year-old male with a history of heart transplantation 21 years ago presented with atypical angina. Coronary angiography demonstrated intermediate stenoses in the proximal and mid left anterior descending artery (LAD) and right posterolateral artery. Intracoronary acetylcholine provocation testing resulted in subtotal occlusion of the coronary arteries bilaterally, which was resolved by nitroglycerine administration, but the intermediate stenoses remained. The stenosis in the proximal LAD was physiologically significant based on fractional flow reserve. The patient was diagnosed with a developed CAV and concomitant coronary vasospasm and treated with percutaneous coronary intervention and nifedipine. Near-infrared spectroscopy and intravascular ultrasound showed a large isoechoic plaque with a low lipidic burden, suggesting a non-atherosclerotic plaque. Optical coherence tomography revealed a layered homogenous plaque, an intravascular imaging finding common in both CAV and coronary vasospasm. A drug-eluting stent dilated the stenosis, and follow-up angiography at 4 months showed no CAV progression.

Discussion

This case highlights the potential association between CAV and coronary vasospasm. Intravascular imaging detected similarities in plaque morphology between CAV and coronary vasospasm, suggesting that coronary vasospasm might contribute to the development of CAV. Although coronary vasospasm may be underdiagnosed in heart transplant recipients due to the lack of symptoms involving the denervated heart, this case showed that appropriate provocation testing may be beneficial for evaluating the cause of CAV.

Invasive Intracoronary Imaging of Cardiac Allograft Vasculopathy: Established Modalities and Emerging Technologies

Despite advances in the care of heart transplant recipients during the past 5 decades, cardiac allograft vasculopathy (CAV) continues to be a major barrier to long-term survival. The early diagnosis and treatment of CAV is crucial for improving long-term outcomes. Coronary angiography, the current gold standard for CAV screening, has low sensitivity for detecting early CAV. Increasingly, invasive intracoronary imaging modalities that provide a more detailed analysis of vessel anatomy and allow for plaque characterization are being used to detect CAV earlier after transplant and uncover mechanistic insights. Studies validating these emerging imaging platforms are needed before their widespread adoption.

Validation of a semi-automatic software for optical coherence tomography - analysis in heart transplanted patients

Optical Coherence Tomography (OCT) is an intravascular imaging modality enabling detailed evaluation of cardiac allograft vasculopathy (CAV) after heart transplantation (HTx). However, its clinical application remains hampered by time-consuming manual quantitative analysis. We aimed to validate a semi-automated quantitative OCT analysis software (Iowa Coronary Wall Analyzer, ICWA-OCT) to improve OCT-analysis in HTx patients. 23 patients underwent OCT evaluation of all three major coronary arteries at 3 months (3M) and 12 months (12M) after HTx. We analyzed OCT recordings using the semiautomatic software and compared results with measurements from a validated manual software. For semi-automated analysis, 31,228 frames from 114 vessels were available. The validation was based on a subset of 4287 matched frames. We applied mixed model statistics to accommodate the multilevel data structure with method as a fixed effect. Lumen (minimum, mean, maximum) and media (mean, maximum) metrics showed no significant differences. Mean and maximum intima area were underestimated by the semi-automated method (β-methodmean = - 0.289 mm2, p < 0.01; β-methodmax = - 0.695 mm2, p < 0.01). Bland-Altman analyses showed increasing semi-automatic underestimation of intima measurements with increasing intimal extent. Comparing 3M to 12M progression between methods, mean intimal area showed minor underestimation (β-methodmean = - 1.03 mm2, p = 0.04). Lumen and media metrics showed excellent agreement between the manual and semi-automated method. Intima metrics and progressions from 3M to 12M were slightly underestimated by the semi-automated OCT software with unknown clinical relevance. The semi-automated software has the future potential to provide robust and time-saving evaluation of CAV progression.