Advances in Quantitative Analysis of 18F-Sodium Fluoride Coronary Imaging

Role of 18F-sodium fluoride positron emission tomography in imaging atherosclerosis

Atherosclerosis involving vascular beds across the human body remains the leading cause of death worldwide. Coronary and peripheral artery disease, which are almost universally a result of atherosclerotic plaque, can manifest clinically as myocardial infarctions, ischemic stroke, or acute lower-limb ischemia. Beyond imaging myocardial perfusion and blood-flow, nuclear imaging has the potential to depict the activity of the processes that are directly implicated in the atherosclerotic plaque progression and rupture. Out of several tested tracers to date, the literature is most advanced for 18F-sodium fluoride positron emission tomography. In this review, we present the latest data in the field of atherosclerotic 18F-sodium fluoride positron emission tomography imaging, discuss the advantages and limitation of the techniques, and highlight the aspects that require further research in the future.

AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging

Epicardial adipose tissue (EAT) volume and attenuation are associated with cardiovascular risk, but manual annotation is time-consuming. We evaluated whether automated deep learning-based EAT measurements from ungated computed tomography (CT) are associated with death or myocardial infarction (MI). We included 8781 patients from 4 sites without known coronary artery disease who underwent hybrid myocardial perfusion imaging. Of those, 500 patients from one site were used for model training and validation, with the remaining patients held out for testing (n = 3511 internal testing, n = 4770 external testing). We modified an existing deep learning model to first identify the cardiac silhouette, then automatically segment EAT based on attenuation thresholds. Deep learning EAT measurements were obtained in <2 s compared to 15 min for expert annotations. There was excellent agreement between EAT attenuation (Spearman correlation 0.90 internal, 0.82 external) and volume (Spearman correlation 0.90 internal, 0.91 external) by deep learning and expert segmentation in all 3 sites (Spearman correlation 0.90-0.98). During median follow-up of 2.7 years (IQR 1.6-4.9), 565 patients experienced death or MI. Elevated EAT volume and attenuation were independently associated with an increased risk of death or MI after adjustment for relevant confounders. Deep learning can automatically measure EAT volume and attenuation from low-dose, ungated CT with excellent correlation with expert annotations, but in a fraction of the time. EAT measurements offer additional prognostic insights within the context of hybrid perfusion imaging.

Automated nonlinear registration of coronary PET to CT angiography using pseudo-CT generated from PET with generative adversarial networks

BACKGROUND

Coronary 18F-sodium-fluoride (18F-NaF) positron emission tomography (PET) showed promise in imaging coronary artery disease activity. Currently image processing remains subjective due to the need for manual registration of PET and computed tomography (CT) angiography data. We aimed to develop a novel fully automated method to register coronary 18F-NaF PET to CT angiography using pseudo-CT generated by generative adversarial networks (GAN).

METHODS

A total of 169 patients, 139 in the training and 30 in the testing sets were considered for generation of pseudo-CT from non-attenuation corrected (NAC) PET using GAN. Non-rigid registration was used to register pseudo-CT to CT angiography and the resulting transformation was used to align PET with CT angiography. We compared translations, maximal standard uptake value (SUVmax) and target to background ratio (TBRmax) at the location of plaques, obtained after observer and automated alignment.

RESULTS

Automatic end-to-end registration was performed for 30 patients with 88 coronary vessels and took 27.5 seconds per patient. Difference in displacement motion vectors between GAN-based and observer-based registration in the x-, y-, and z-directions was 0.8 ± 3.0, 0.7 ± 3.0, and 1.7 ± 3.9 mm, respectively. TBRmax had a coefficient of repeatability (CR) of 0.31, mean bias of 0.03 and narrow limits of agreement (LOA) (95% LOA: - 0.29 to 0.33). SUVmax had CR of 0.26, mean bias of 0 and narrow LOA (95% LOA: - 0.26 to 0.26).

CONCLUSION

Pseudo-CT generated by GAN are perfectly registered to PET can be used to facilitate quick and fully automated registration of PET and CT angiography.

Advances in the Assessment of Coronary Artery Disease Activity with PET/CT and CTA

Non-invasive testing plays a pivotal role in the diagnosis, assessment of progression, response to therapy, and risk stratification of coronary artery disease. Although anatomical plaque imaging by computed tomography angiography (CTA) and ischemia detection with myocardial perfusion imaging studies are current standards of care, there is a growing body of evidence that imaging of the processes which drive atherosclerotic plaque progression and rupture has the potential to further enhance risk stratification. In particular, non-invasive imaging of coronary plaque inflammation and active calcification has shown promise in this regard. Positron emission tomography (PET) with newly-adopted radiotracers provides unique insights into atheroma activity acting as a powerful independent predictor of myocardial infarctions. Similarly, by providing a quantitative measure of coronary inflammation, the pericoronary adipose tissue density (PCAT) derived from standard coronary CTA enhances cardiac risk prediction and allows re-stratification over and above current state-of-the-art assessments. In this review, we shall discuss the recent advances in the non-invasive methods of assessment of disease activity by PET and CTA, highlighting how these methods could improve risk stratification and ultimately benefit patients with coronary artery disease.

Novel PET Applications and Radiotracers for Imaging Cardiovascular Pathophysiology

PET allows the assessment of cardiovascular pathophysiology across a wide range of cardiovascular conditions. By imaging processes directly involved in disease progression and adverse events, such as inflammation and developing calcifications (microcalcifications), PET can not only enhance our understanding of cardiovascular disease, but also, as shown for 18F-sodium fluoride, has the potential to predict hard endpoints. In this review, the recent advances in disease activity assessment with cardiovascular PET, which provide hope that this promising technology could be leveraged in the clinical setting, shall be discussed.

NaF-PET Imaging of Atherosclerosis Burden

The method of 18F-sodium fluoride (NaF) positron emission tomography/computed tomography (PET/CT) of atherosclerosis was introduced 12 years ago. This approach is particularly interesting because it demonstrates microcalcification as an incipient sign of atherosclerosis before the development of arterial wall macrocalcification detectable by CT. However, this method has not yet found its place in the clinical routine. The more exact association between NaF uptake and future arterial calcification is not fully understood, and it remains unclear to what extent NaF-PET may replace or significantly improve clinical cardiovascular risk scoring. The first 10 years of publications in the field were characterized by heterogeneity at multiple levels, and it is not clear how the method may contribute to triage and management of patients with atherosclerosis, including monitoring effects of anti-atherosclerosis intervention. The present review summarizes findings from the recent 2¾ years including the ability of NaF-PET imaging to assess disease progress and evaluate response to treatment. Despite valuable new information, pertinent questions remain unanswered, not least due to a pronounced lack of standardization within the field and of well-designed long-term studies illuminating the natural history of atherosclerosis and effects of intervention.

Advanced targeted nanomedicines for vulnerable atherosclerosis plaque imaging and their potential clinical implications

Atherosclerosis plaques caused by cerebrovascular and coronary artery disease have been the leading cause of death and morbidity worldwide. Precise assessment of the degree of atherosclerotic plaque is critical for predicting the risk of atherosclerosis plaques and monitoring postinterventional outcomes. However, traditional imaging techniques to predict cardiocerebrovascular events mainly depend on quantifying the percentage reduction in luminal diameter, which would immensely underestimate non-stenotic high-risk plaque. Identifying the degree of atherosclerosis plaques still remains highly limited. vNanomedicine-based imaging techniques present unique advantages over conventional techniques due to the superior properties intrinsic to nanoscope, which possess enormous potential for characterization and detection of the features of atherosclerosis plaque vulnerability. Here, we review recent advancements in the development of targeted nanomedicine-based approaches and their applications to atherosclerosis plaque imaging and risk stratification. Finally, the challenges and opportunities regarding the future development and clinical translation of the targeted nanomedicine in related fields are discussed.