PET imaging of vulnerable coronary artery plaques

Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group

The detection and characterization of coronary artery stenosis and atherosclerosis using imaging tools are key for clinical decision-making in patients with known or suspected coronary artery disease. In this regard, imaging-based quantification can be improved by choosing the most appropriate imaging modality for diagnosis, treatment and procedural planning. In this Consensus Statement, we provide clinical consensus recommendations on the optimal use of different imaging techniques in various patient populations and describe the advances in imaging technology. Clinical consensus recommendations on the appropriateness of each imaging technique for direct coronary artery visualization were derived through a three-step, real-time Delphi process that took place before, during and after the Second International Quantitative Cardiovascular Imaging Meeting in September 2022. According to the Delphi survey answers, CT is the method of choice to rule out obstructive stenosis in patients with an intermediate pre-test probability of coronary artery disease and enables quantitative assessment of coronary plaque with respect to dimensions, composition, location and related risk of future cardiovascular events, whereas MRI facilitates the visualization of coronary plaque and can be used in experienced centres as a radiation-free, second-line option for non-invasive coronary angiography. PET has the greatest potential for quantifying inflammation in coronary plaque but SPECT currently has a limited role in clinical coronary artery stenosis and atherosclerosis imaging. Invasive coronary angiography is the reference standard for stenosis assessment but cannot characterize coronary plaques. Finally, intravascular ultrasonography and optical coherence tomography are the most important invasive imaging modalities for the identification of plaques at high risk of rupture. The recommendations made in this Consensus Statement will help clinicians to choose the most appropriate imaging modality on the basis of the specific clinical scenario, individual patient characteristics and the availability of each imaging modality.

Autoradiographical assessment of inflammation-targeting radioligands for atherosclerosis imaging: potential for plaque phenotype identification

PURPOSE

Many radioligands have been developed for the visualization of atherosclerosis by targeting inflammation. However, interpretation of in vivo signals is often limited to plaque identification. We evaluated binding of some promising radioligands in an in vitro approach in atherosclerotic plaques with different phenotypes.

METHODS

Tissue sections of carotid endarterectomy tissue were characterized as early plaque, fibro-calcific plaque, or phenotypically vulnerable plaque. In vitro binding assays for the radioligands [111In]In-DOTATATE; [111In]In-DOTA-JR11; [67Ga]Ga-Pentixafor; [111In]In-DANBIRT; and [111In]In-EC0800 were conducted, the expression of the radioligand targets was assessed via immunohistochemistry. Radioligand binding and expression of radioligand targets was investigated and compared.

RESULTS

In sections characterized as vulnerable plaque, binding was highest for [111In]In-EC0800; followed by [111In]In-DANBIRT; [67Ga]Ga-Pentixafor; [111In]In-DOTA-JR11; and [111In]In-DOTATATE (0.064 ± 0.036; 0.052 ± 0.029; 0.011 ± 0.003; 0.0066 ± 0.0021; 0.00064 ± 0.00014 %Added activity/mm2, respectively). Binding of [111In]In-DANBIRT and [111In]In-EC0800 was highest across plaque phenotypes, binding of [111In]In-DOTA-JR11 and [67Ga]Ga-Pentixafor differed most between plaque phenotypes. Binding of [111In]In-DOTATATE was the lowest across plaque phenotypes. The areas positive for cells expressing the radioligand's target differed between plaque phenotypes for all targets, with lowest percentage area of expression in early plaque sections and highest in phenotypically vulnerable plaque sections.

CONCLUSIONS

Radioligands targeting inflammatory cell markers showed different levels of binding in atherosclerotic plaques and among plaque phenotypes. Different radioligands might be used for plaque detection and discerning early from vulnerable plaque. [111In]In-EC0800 and [111In]In-DANBIRT appear most suitable for plaque detection, while [67Ga]Ga-Pentixafor and [111In]In-DOTA-JR11 might be best suited for differentiation between plaque phenotypes.