Molecular Imaging Visualizes Recruitment of Inflammatory Monocytes and Macrophages to the Injured Heart

Abstract

Rationale: Paradigm shifting studies have revealed that the heart contains functionally diverse populations of macrophages derived from distinct embryonic and adult hematopoietic progenitors. Under steady-state conditions, the heart is largely populated by CCR2- (C-C chemokine receptor type 2) macrophages of embryonic descent. After tissue injury, a dramatic shift in macrophage composition occurs whereby CCR2+ monocytes are recruited to the heart and differentiate into inflammatory CCR2+ macrophages that contribute to heart failure progression. Currently, there are no techniques to noninvasively detect CCR2+ monocyte recruitment into the heart and thus identify patients who may be candidates for immunomodulatory therapy.

Objective: To develop a noninvasive molecular imaging strategy with high sensitivity and specificity to visualize inflammatory monocyte and macrophage accumulation in the heart.

Methods and results: We synthesized and tested the performance of a positron emission tomography radiotracer (⁶⁸Ga-DOTA [1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid]-ECL1i [extracellular loop 1 inverso]) that allosterically binds to CCR2. In naive mice, the radiotracer was quickly cleared from the blood and displayed minimal retention in major organs. In contrast, biodistribution and positron emission tomography demonstrated strong myocardial tracer uptake in 2 models of cardiac injury (diphtheria toxin induced cardiomyocyte ablation and reperfused myocardial infarction). ⁶⁸Ga-DOTA-ECL1i signal localized to sites of tissue injury and was independent of blood pool activity as assessed by quantitative positron emission tomography and ex vivo autoradiography. ⁶⁸Ga-DOTA-ECL1i uptake was associated with CCR2+ monocyte and CCR2+ macrophage infiltration into the heart and was abrogated in CCR2^-/- mice, demonstrating target specificity. Autoradiography demonstrated that ⁶⁸Ga-DOTA-ECL1i specifically binds human heart failure specimens and with signal intensity associated with CCR2+ macrophage abundance.

Conclusions: These findings demonstrate the sensitivity and specificity of ⁶⁸Ga-DOTA-ECL1i in the mouse heart and highlight the translational potential of this agent to noninvasively visualize CCR2+ monocyte recruitment and inflammatory macrophage accumulation in patients.

Keywords: macrophages; molecular imaging; monocytes; myocardial infarction; positron emission tomography.

Figure 1.. Generation of a CCR2-targeted ⁶⁸Gallium PET tracer.

(A) Synthetic scheme utilized to generate ⁶⁸Ga-DOTA-ECL1i. (B) Serum stability of ⁶⁸Ga-DOTA-ECL1i administered to mice via tail vein injection. (C) Flow cytometry showing that CCR2+ monocytes (CCR2+MHC-II^low) and CCR2+ macrophages (CCR2+MHC-II^high) accumulate in the hearts of Tnnt2-DTR mice 4 days after the administration of diphtheria toxin (DT, 25 ng IP). In contrast, the hearts of littermate control mice contain predominately CCR2- macrophages following DT injection. (D) Biodistribution of ⁶⁸Ga activity in DT treated wild type (WT) and Tnnt2-DTR mice 1 h post intravenous injection (tail vein) of ⁶⁸Ga-DOTA-ECL1i. n=5 per experimental group. (E) Tracer uptake ratios (heart/blood and heart/muscle) in WT and Tnnt2-DTR mice demonstrating enrichment of ⁶⁸Ga activity in the hearts of Tnnt2-DTR mice administered DT over the blood pool. n=5 per experimental group. * p< 0.05, ** p< 0.01, *** p< 0.005, **** p<0.001.

Figure 2.. PET of ⁶⁸Ga-DOTA-ECL1i in a mouse model of cardiomyocyte ablation.

(A) Representative PET/CT images of ⁶⁸Ga-DOTA-ECL1i in wild-type (WT) and Tnnt2-DTR mice 4 days following either vehicle (PBS) or diphtheria toxin (DT) administration. Arrow denotes robust tracer accumulation in the hearts of Tnnt2-DTR+DT mice compared to all other groups. PET images are overlaid on CT images. (B) Quantitative analysis of ⁶⁸Ga-DOTA-ECL1i signal in the hearts of WT and Tnnt2-DTR mice treated with either vehicle or DT. n=5 per experimental group. (C) Ratio of ⁶⁸Ga-DOTA-ECL1i signal between the heart and aorta of WT and Tnnt2-DTR mice demonstrating that increased ⁶⁸Ga-DOTA-ECL1i signal in Tnnt2-DTR+DT hearts is not a result of increased blood pool signal, n=5 per experimental group. (D) Autoradiography of heart slices collected from WT and Tnnt2-DTR mice immediately after PET showing myocardial uptake of ⁶⁸Ga-DOTA-ECL1i. Mice were flushed with saline prior to heart collection and autoradiography to remove intravascular cells. (E) Quantitative comparison of radioactivity measured from autoradiography images of WT and Tnnt2-DTR hearts expressed as fold increase over WT control. (F) Linear regression of ⁶⁸Ga-DOTA-ECL1i heart uptake and chemokine/cytokine mRNA expression. n=5 per experimental group. * p< 0.05, ** p< 0.01, *** p< 0.005, **** p<0.001.

Figure 3.. PET of ⁶⁸Ga-DOTA-ECL1i in a mouse model of closed-chest ischemia reperfusion injury.

(A) Representative ¹⁸F-FDG PET/CT images obtained 5 days following 90 minutes of ischemia reperfusion injury identifying the infarct region in mice that underwent ischemia reperfusion injury (MI) compared to sham controls. Transverse, coronal, and maximal intensity projected (MIP) views are shown and white arrows denote the infarct area. (B) Representative ⁶⁸Ga-DOTA-ECL1i PET/CT images showing regional accumulation of ⁶⁸Ga-DOTA-ECL1i signal in the infarct and border zone 4 days following ischemia reperfusion injury. Transverse, coronal and maximal intensity projected (MIP) views are shown. Yellow arrow identifies tracer uptake in hearts that underwent ischemia reperfusion injury compared to sham controls. White arrows denote the infarct area as determined by ¹⁸F-FDG imaging. (C) Quantitative analysis of ⁶⁸Ga-DOTA-ECL1i accumulation in the hearts of naïve, sham, MI, and CCR2 KO mice that underwent ischemia reperfusion injury at the indicated time points. n=4–5 per experimental group. (D) Regional accumulation of ⁶⁸Ga-DOTA-ECL1i uptake in the infarct and remote areas of sham and MI mice over the indicated time points. (E) Biodistribution of ⁶⁸Ga activity 4 days following ischemia rerpefusion injury measured 1 h post intravenous injection (tail vein) of ⁶⁸Ga-DOTA-ECL1i. n=5 per experimental group. (F) Trichrome and H&E staining show the evolution of fibrosis (trichrome-blue, 40X magnification) and cell infiltration (H&E, 200X magnification) over time in the closed-chest ischemia reperfusion injury model. Note the dense accumulation of cells within the infarct 4 days following ischemia reperfusion injury. Representative images from 6 independent experiments. (G) Flow cytometry analysis showing accumulation of CCR2+ monocytes (CCR2+MHC-II^low) and CCR2+ macrophages (CCR2+MHC-II^high) 4 days following ischemia reperfusion injury and persistence of CCR2+ macrophages 7 days following ischemia reperfusion injury compared to sham controls. (H) Immunostaining showing accumulation of CCR2+ cells (brown) in the infarct region peaking at day 4 following ischemia reperfusion injury. (I) Linear regression analyses showing the relationship between ⁶⁸Ga-DOTA-ECL1i heart uptake measured on day 4 following ischemia reperfusion injury and echocardiographic assessment of LV ejection fraction and akinetic area measured on day 28 following ischemia reperfusion injury. * p< 0.05, ** p< 0.01, *** p< 0.005, **** p<0.001.

Figure 4.. ⁶⁸Ga-DOTA-ECL1i identifies CCR2+ monocytes and macrophages in the human heart.

(A) Autoradiography images of human acute myocardial infarction and chronic ICM specimens incubated with ⁶⁸Ga-DOTA-ECL1i revealing heterogeneous distribution or tracer binding. Competitive blocking assaying using excess non-radioactive DOTA-ECL1i showing decreased tracer binding. (B) Quantification of ⁶⁸Ga-DOTA-ECL1i binding (displayed as relative counts ratio) demonstrated significantly decreased tracer binding following co-incubation with DOTA-ECL1i blocking agent (n=11). (C) Immunohistochemical staining for CD68 (white), CCR2 (red), and DAPI (blue) highlighting the distribution of CCR2-CD68+ and CCR2+CD68+ macrophages in human ICM samples. Representative images (200X magnification) from acute ICM (n=5) and chronic ICM (n=11) samples. (D) Linear regression analysis demonstrating that the intensity of ⁶⁸Ga-DOTA-ECL1i binding is associated with the number of total CD68+ macrophages (left) and abundance of CCR2+ macrophages (right). No association was detected between ⁶⁸Ga-DOTA-ECL1i binding and the number of CCR2- macrophages (center). * p< 0.05, ** p< 0.01, *** p< 0.005, **** p<0.001.