Skip to main content

Main menu

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Journal of Nuclear Medicine
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Journal of Nuclear Medicine

Advanced Search

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • View or Listen to JNM Podcast
  • Visit JNM on Facebook
  • Join JNM on LinkedIn
  • Follow JNM on Twitter
  • Subscribe to our RSS feeds
Research ArticleCardiovascular

Imaging Inflammation in Atherosclerosis with CXCR4-Directed 68Ga-Pentixafor PET/CT: Correlation with 18F-FDG PET/CT

Malte Kircher, Johannes Tran-Gia, Luisa Kemmer, Xiaoli Zhang, Andreas Schirbel, Rudolf A. Werner, Andreas K. Buck, Hans-Jürgen Wester, Marcus Hacker, Constantin Lapa and Xiang Li
Journal of Nuclear Medicine May 2020, 61 (5) 751-756; DOI: https://doi.org/10.2967/jnumed.119.234484
Malte Kircher
1Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Johannes Tran-Gia
1Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Luisa Kemmer
1Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiaoli Zhang
2Department of Nuclear Medicine, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andreas Schirbel
1Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rudolf A. Werner
1Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andreas K. Buck
1Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hans-Jürgen Wester
3Pharmaceutical Radiochemistry, Technische Universität München, Munich, Germany; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marcus Hacker
4Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Constantin Lapa
1Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiang Li
2Department of Nuclear Medicine, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
4Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF
Loading

Abstract

C-X-C motif chemokine receptor 4 (CXCR4) is expressed on the surface of various cell types involved in atherosclerosis, with a particularly rich receptor expression on macrophages and T cells. First pilot studies with 68Ga-pentixafor, a novel CXCR4-directed PET tracer, have shown promise to noninvasively image inflammation within atherosclerotic plaques. The aim of this retrospective study was to investigate the performance of 68Ga-pentixafor PET/CT for imaging atherosclerosis in comparison to 18F-FDG PET/CT. Methods: Ninety-two patients (37 women and 55 men; mean age, 62 ± 10 y) underwent 68Ga-pentixafor and 18F-FDG PET/CT for staging of oncologic diseases. In these subjects, lesions in the walls of large arteries were identified using morphologic and PET criteria for atherosclerosis (n = 652). Tracer uptake was measured and adjusted for vascular lumen (background) signal by calculation of target-to-background ratios (TBRs) by 2 investigators masked to the other PET scan. On a lesion-to-lesion and patient basis, the TBRs of both PET tracers were compared and additionally correlated to the degree of arterial calcification as quantified in CT. Results: On a lesion-to-lesion basis, 68Ga-pentixafor and 18F-FDG uptake showed a weak correlation (r = 0.28; P < 0.01). 68Ga-pentixafor PET identified more lesions (n = 290; TBR ≥ 1.6, P < 0.01) and demonstrated higher uptake than 18F-FDG PET (1.8 ± 0.5 vs. 1.4 ± 0.4; P < 0.01). The degree of plaque calcification correlated negatively with both 68Ga-pentixafor and 18F-FDG uptake (r = −0.38 vs. −0.31, both P < 0.00001). Conclusion: CXCR4-directed imaging of the arterial wall with 68Ga-pentixafor PET/CT identified more lesions than 18F-FDG PET/CT, with only a weak correlation between tracers. Further studies to elucidate the underlying biologic mechanisms and sources of CXCR4 positivity, and to investigate the clinical utility of chemokine receptor–directed imaging of atherosclerosis, are highly warranted.

  • atherosclerotic lesions
  • plaque
  • molecular imaging
  • CXCR4
  • FDG

Despite significant improvement in the management of cardiovascular diseases, coronary artery disease and stroke are still the leading causes of mortality in developed societies (1,2). Atherosclerosis, the common underlying pathogenesis, is characterized by the gradual formation of focal, asymmetric arterial wall lesions that progressively narrow the affected vascular lumen (3). Formation of an atherosclerotic lesion is initiated by endothelial dysfunction, followed by chronic accumulation of lipids, triggering a chemotaxis-orchestrated migration of atherogenic, proinflammatory immune cells to the lesion (3–5). Structurally unstable plaques are prone to rupture, leading to thrombosis and possibly severe complications such as myocardial infarction or stroke (6). Though many of the exact mechanisms of plaque formation and rupture are yet to be elucidated, inflammation is considered one of the most important predictive factors for stroke or myocardial infarction due to atherosclerotic plaque ruptures (7). This hypothesis was recently validated by a trial in which antiinflammatory therapy with the interleukin-1β inhibitor canakinumab significantly lowered rates of cardiovascular events (8).

Functional imaging of arterial inflammation can help to identify patients at risk of plaque rupture (9). PET has been used to visualize different aspects of the atherosclerotic plaque and its associated inflammation, with most PET tracers targeting activated macrophages within the atherosclerotic lesion (10,11), and with 18F-FDG being the most-studied tracer of nuclear inflammation imaging (12–14). Other approaches include the use of 18F-NaF, which can detect calcifications and microcalcifications (15–17). Imaging atherosclerosis with PET/CT not only characterizes atherosclerotic plaques on a molecular level but also enables the quantification of arterial calcification (11), combining the strengths of both modalities.

Chemokine-mediated recruitment of proinflammatory leukocytes to the dysfunctional endothelium and subsequent plaque formation are important steps in atheroprogression (3). C-X-C motif chemokine receptor 4 (CXCR4) and its endogenous ligands, C-X-C motif chemokine 12 (CXCL12; stromal cell–derived factor 1) and migration inhibitory factor, play important roles in progenitor and immune cell trafficking (18). The precise role of the CXCR4/CXCL12 axis in atherosclerosis progression is yet to be fully elucidated, with conflicting reports about atherogenic and atheroprotective effects, respectively (18). This conflict is partly due to the recent identification of migration inhibitory factor as an alternate ligand for CXCR4 (19). Evidence shows that CXCR4 activation by CXCL12 exerts stabilizing effects on atherosclerotic lesions, whereas migration inhibitory factor acts as a major proinflammatory player (20).

Recently, CXCR4-directed PET imaging with 68Ga-pentixafor introduced the possibility for noninvasive, in vivo visualization of human CXCR4 expression (21–25). First pilot studies examining its ability to characterize atherosclerotic inflammation and myocardial injury have shown promising results and have suggested that major parts of the PET signal originate from intralesional macrophages (26–31). In this study, we investigated the performance of 68Ga-pentixafor for detection of arterial wall inflammation in comparison to 18F-FDG and correlated the respective tracer uptake to the degree of calcification in the corresponding lesions.

MATERIALS AND METHODS

Patients

One hundred forty-four oncologic patients underwent PET/CT imaging with 68Ga-pentixafor and 18F-FDG (with a maximum interval of 3 d between the 2 scans) for staging purposes or for evaluation of CXCR4-directed endoradiotherapy (32,33). Subjects with a history of inflammatory diseases (including vasculitis), chemotherapy in the preceding 4 wk, or cardiovascular events (myocardial infarction, stroke) in the last 6 mo, and patients taking cholesterol-lowering drugs such as statins or ezetimibe, were excluded from the study (n = 52). The remaining 92 subjects (37 women and 55 men; mean age, 62 ± 10 y; 33 with multiple myeloma, 25 with adrenocortical carcinoma, 13 with neuroendocrine neoplasia, 6 with non–small cell lung cancer, and 15 with miscellaneous other conditions) were included in this retrospective analysis. A flowchart of the study design is shown in Supplemental Figure 1 (supplemental materials are available at http://jnm.snmjournals.org).

68Ga-pentixafor was administered in compliance with the German Medicinal Products Act, AMG §13 2b, and in accordance with the responsible regulatory body (Government of Upper Franconia, “Regierung von Oberfranken”). The data analysis was disclosed to the local ethics committee of Würzburg University Hospital, and the need for a formal review was waived. All patients gave written informed consent before imaging. The patient characteristics are shown in Table 1.

View this table:
  • View inline
  • View popup
TABLE 1

Patient Characteristics

PET/CT Acquisition

All 68Ga-pentixafor and 18F-FDG PET/CT scans were performed on a dedicated PET/CT scanner (Biograph mCT 64; Siemens Medical Solutions). 18F-FDG PET/CT imaging was performed after a 6-h fasting period to ensure serum glucose levels below 130 mg/dL. Injected activities ranged from 108 to 178 MBq (mean, 143 ± 26 MBq) for 68Ga-pentixafor and from 235 to 363 MBq (mean, 299 ± 18 MBq) for 18F-FDG.

Low-dose CT scans for attenuation correction were acquired (35 mAs, 120 keV, a 512 × 512 matrix, 5-mm slice thickness, increment of 30 mm/s, rotation time of 0.5 s, and pitch index of 0.8). Whole-body (top of the skull to knees) scans were performed 1 h after administration of the radiopharmaceutical. All PET images were reconstructed using standard parameters (HD-PET [Siemens]; 3 iterations, 24 subsets, 2-mm gaussian filtering, 5-mm axial resolution, 4 × 4 mm2 in-plane resolution) with corrections for attenuation (CT-based), dead time, random events, and scatter. The PET scanner is periodically checked for calibration accuracy as part of quality control according to published guidelines (34).

Data Analysis

Images were analyzed by 2 investigators masked to the other PET scan. 68Ga-pentixafor and 18F-FDG uptake was visually and semiquantitatively assessed with commercially available software (Hybrid 3D; Hermes Medical Solutions) on transaxial PET, CT, and PET/CT slices. The following segments of large arteries were analyzed for signs of atherosclerosis in each patient: the left and right carotid arteries; the ascending thoracic aorta; the aortic arch; the descending thoracic aorta; the abdominal aorta; and the left and right iliac arteries. Signs of atherosclerosis were defined as either arterial wall calcification with a minimum density of 130 Hounsfield units (HU) on unenhanced CT images or high focal tracer uptake on either 18F-FDG or 68Ga-pentixafor PET images, defined as a minimum arterial target-to-background ratio (TBR) of 1.6, as described for 18F-FDG PET in the literature (35).

Volumes of interest were manually drawn at the selected sites, particularly at regions of arterial bifurcations, known to be susceptible to atherosclerotic formation, and at calcified arterial wall lesions. For analysis of calcification extent, lesions were categorized according to the modified Agatston score (36), with measurements of HU on unenhanced CT images. Group 1 (noncalcified lesions) had a calcium density of less than 130 HU. Group 2 (mildly calcified lesions) had a calcium density of 130–399 HU. Group 3 (severely calcified lesions) had a calcium density of at least 400 HU.

TBRs were calculated as previously described (35). First, SUVmax was measured by placing a circular 10-mm volume of interest around a site of focal uptake. Then, the SUVmean of the background was derived by calculating the mean of 3 regions of interest placed in the superior vena cava (the SUV of the blood pool). TBRs were then calculated as SUVmax (focal uptake) divided by the SUV of the blood pool.

Statistics

All statistical testing was performed in SPSS statistics 25 (IBM Corp.). Kolmogorov–Smirnov testing was used to verify a normal distribution of the data. Continuous parametric variables are expressed as mean ± SD. For group statistics, comparisons within the 3 groups of lesions were performed using 1-way ANOVA. The significance of observed differences between groups was confirmed with a Games–Howell post hoc test. Unpaired t tests were used to compare uptake (ratios) of both tracers in corresponding lesions. Pearson correlation coefficients (r) were calculated to assess the association between the TBRs of both tracers. P values of at least 0.05 were considered statistically significant.

RESULTS

Comparison of 68Ga-Pentixafor and 18F-FDG Uptake: Patient-Based Analysis

In the patient-based analysis, 88 of 92 subjects (95.7%) had at least 1 68Ga-pentixafor–positive lesion and 58 patients (63.0%) had at least 1 18F-FDG–positive lesion. Two patients (2.2%) had both negative 68Ga-pentixafor and negative 18F-FDG scans, and 2 patients (2.2%) had exclusively 18F-FDG–positive lesions. In the remaining 32 subjects (34.8%), all lesions were 68Ga-pentixafor–positive, 18F-FDG–negative.

The median number of 68Ga-pentixafor–positive lesions (per patient) was 4 (range, 0–13), as compared with 1 for 18F-FDG (range, 0–10). The number of 68Ga-pentixafor–positive lesions moderately correlated with the number of 18F-FDG–positive lesions (r = 0.46, P < 0.0001). On a patient level, individual mean TBRs for 68Ga-pentixafor were significantly higher than those for 18F-FDG (1.8 ± 0.3 vs. 1.4 ± 0.3; P < 0.001; Fig. 1) and were only moderately correlated (r = 0.36, P < 0.001; Fig. 1).

FIGURE 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
FIGURE 1.

Comparison of 68Ga-pentixafor and 18F-FDG uptake on per-patient basis. Box plot (A) and scatterplot (B) showing correlation of mean 18F-FDG and 68Ga-pentixafor (PEN) uptake as measured by TBR on per-patient basis.

Comparison of 68Ga-Pentixafor and 18F-FDG Uptake: Lesion-Based Analysis

In total, 652 sites of arterial wall calcification or elevated tracer uptake (TBR ≥ 1.6) were identified and selected for further analysis. At these sites, mean SUVmax was significantly higher for 68Ga-pentixafor than for 18F-FDG (3.3 ± 1.0 vs. 2.6 ± 0.7; P < 0.01). Both tracers’ SUVmax showed a moderate positive correlation (r = 0.43; P < 0.01). With the mean blood-pool SUV of 68Ga-pentixafor and 18F-FDG being comparable (1.87 ± 0.37 vs. 1.81 ± 0.29, P = 0.18), the mean TBR was significantly higher for 68Ga-pentixafor than for 18F-FDG (1.8 ± 0.5 vs. 1.4 ± 0.4; P < 0.01). The TBR of 68Ga-pentixafor and 18F-FDG showed a weak positive correlation (r = 0.28, P < 0.01; Fig. 2). When a TBR threshold of 1.6 was applied, 290 of the potential lesions were exclusively identified on 68Ga-pentixafor PET (18F-FDG < 1.6 and 68Ga-pentixafor ≥ 1.6, P < 0.01). An example of the different tracer uptake patterns is given in Figure 3.

FIGURE 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
FIGURE 2.

Comparison of 68Ga-pentixafor and 18F-FDG uptake on lesion-to-lesion basis. Box plot (A) and scatterplot (B) showing correlation of 18F-FDG and 68Ga-pentixafor (PEN) uptake as measured by TBR.

FIGURE 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
FIGURE 3.

Example of concordant and discordant 68Ga-pentixafor and 18F-FDG uptake. Representative transversal and coronal CT (A and D), 68Ga-pentixafor PET/CT (B), and 18F-FDG PET/CT (C), as well as respective PET-only (E and F), images of patient with multiple myeloma. Dashed arrows indicate concordant foci of 68Ga-pentixafor and 18F-FDG arterial uptake; solid arrows show lesions exclusively seen in 68Ga-pentixafor but not in 18F-FDG PET.

Relationship Between Plaque Calcification and Tracer Uptake

Most of the 652 analyzed sites demonstrated no signs of calcification (<130 HU; n = 467), whereas 99 lesions showed mild calcification (130–399 HU) and 86 showed severe calcification (≥400 HU).

There was an inverse relationship between the extent of calcification and the intensity of tracer uptake as measured by TBR for both 68Ga-pentixafor and 18F-FDG. Severely calcified lesions (n = 86) showed the lowest TBRs for both PET tracers (1.4 ± 0.6 and 1.1 ± 0.4 for 68Ga-pentixafor and 18F-FDG, respectively). Mildly calcified lesions (n = 99) showed higher TBRs than severely calcified lesions (1.7 ± 0.4 and 1.3 ± 0.3, respectively; P < 0.01). The highest TBRs were concordantly observed in noncalcified lesions (n = 467; 1.9 ± 0.4 and 1.5 ± 0.4, respectively). Higher TBRs for 68Ga-pentixafor than for 18F-FDG were also observed when the different calcification subgroups were analyzed. Results are shown in Figure 4.

FIGURE 4.
  • Download figure
  • Open in new tab
  • Download powerpoint
FIGURE 4.

68Ga-pentixafor and 18F-FDG uptake in correlation to degree of calcification on lesion-to-lesion basis. Correlation of 68Ga-pentixafor (A and B) and 18F-FDG (C and D) uptake with degree of calcification. Lesions were categorized by calcification degree as noncalcified (˂130 HU), mildly calcified (130–399 HU), or severely calcified (≥400 HU), respectively. TBR of 68Ga-pentixafor and 18F-FDG are lowest in severely calcified lesions and highest in noncalcified lesions.

DISCUSSION

18F-FDG is the best-studied PET tracer for inflammation imaging and is routinely used for nuclear imaging of atherosclerosis (10). More recently, several small-animal and human pilot studies have established the feasibility of the CXCR4-directed PET tracer 68Ga-pentixafor for cardiovascular imaging (26–30,37).

68Ga-Pentixafor and 18F-FDG Uptake Show Only a Weak Correlation

Overall, accumulation of 68Ga-pentixafor and 18F-FDG showed only a weak correlation. This was primarily observed in noncalcified lesions, in which many sites with focal 68Ga-pentixafor uptake were inconspicuous on 18F-FDG PET. Most of the 18F-FDG signal can be attributed to activated, proinflammatory macrophages (10). Likewise, at least part of the 68Ga-pentixafor signal is traceable to areas rich in CD68-positive macrophages (28,38), which may account for the lesions identified by both tracers. However, the dynamics of CXCR4 regulation in atherosclerosis are complex, and various involved cell types (including thrombocytes) have been described as contributing to the 68Ga-pentixafor signal (18,31,39,40), making its interpretation more challenging than 18F-FDG.

The 68Ga-Pentixafor Signal Appears to Originate Not Merely from Inflammation

Although there has been extensive research into the CXCR4-CXCL12 axis and its role in atherosclerosis, the basis of its involvement is still incompletely understood, given the contribution of multiple cell types and a rather complex and highly dynamic receptor expression profile (20). Because 68Ga-pentixafor PET/CT detects sites that are inconspicuous on 18F-FDG PET/CT, the source of the PET signal probably originates in additional cell types beyond mere inflammation (41). In the setting of atherosclerosis, CXCR4-expressing cells include T cells, thrombocytes, and smooth muscle cells; thus, some of the exclusively 68Ga-pentixafor–positive sites might represent very early stage lesions without markedly elevated inflammation.

It is the prevailing scientific consensus that the effects of CXCR4 through activation by its cognate ligand CXCL12 are largely atheroprotective, particularly by maintaining the arterial wall integrity, which prevents vascular remodeling. Maintenance of wall integrity is achieved by protecting the endothelial barrier function and smooth muscle cell elasticity, which is associated with retarding adhesion and penetration of leukocytes into the arterial intima (39). Collagen produced by smooth muscle cells strengthens the fibrous plaque cap, implying that dysfunctional smooth muscle cells lead to reduced plaque stability, which in turn increases the risk of subsequent plaque rupture and thrombosis (42). On the other hand, observations suggest that CXCR4 activation through its noncognate-ligand migration inhibitory factor leads to recruitment of highly inflammatory immune cells, including monocytes, macrophages, and T cells, and has a detrimental effect on atheroprogression and plaque stability (19).

One study of carotid plaques in humans showed that compared with unaffected vessels, CXCR4 expression is likewise elevated in both stable and unstable atherosclerotic plaques, with the highest receptor expression found on macrophages and macrophage-derived foam cells (31). This observation was also made in another study that showed an abundant accumulation of 68Ga-pentixafor, especially in inflamed plaques, verified histologically in human carotid plaques and in a rabbit model (28). Taken together, preclinical and clinical findings suggest a sophisticated system of CXCR4-expressing cell types within the atherosclerotic lesion that, depending on their activating ligand, may have atherogenic or antiatherosclerotic effects.

Tracer Uptake and Plaque Calcification

Our data show an inverse relationship between both 68Ga-pentixafor and 18F-FDG uptake and the degree of calcification. Noncalcified sites demonstrated the highest, severely calcified plaques the lowest TBRs for both tracers, respectively. Severely calcified plaques are generally considered to be more stable and less susceptible to rupture. In the case of 18F-FDG, this observation is consistent with previously published studies (13,43). Regarding 68Ga-pentixafor, Weiberg et al. recently documented similar results using 68Ga-pentixafor PET/CT for atherosclerosis imaging, with increased tracer uptake in only a few of the calcified lesions (30).

Limitations

There are several limitations to this retrospective study. The first concerns the cohort of oncologic, non–cardiovascular-disease patients and the PET acquisition protocol used. The impact of previous anticancer therapies on vascular inflammation cannot be excluded (although chemotherapy within 4 wk before imaging was an exclusion criterion). In addition, metabolic (inflammatory) changes induced by malignancy itself cannot be measured and therefore confound the results of this pilot study. Given the fact that imaging was performed on oncology patients, scans were started as early as 1 h after tracer injection, limiting the diagnostic accuracy, as tracer circulation time is a critical variable affecting quantification of plaque uptake (35). This limitation is particularly true for 68Ga-pentixafor, for which experience with inflammation imaging is limited. Comparability between tracers might furthermore be influenced by differences in biodistribution. Studies to optimize the imaging protocol are needed. The use of an unestablished, nonvalidated TBR threshold to define 68Ga-pentixafor–positive lesions is another limitation. In the limited literature available, the mean TBR of atherosclerotic lesions in the carotid arteries were 1.6 (38), 1.7 (30), and 1.6 (28, supplemental data), suggesting that the chosen threshold might be a reasonable first estimate, but further studies are needed to define the correct threshold for the detection of CXCR4-positive plaques visualized by receptor-directed PET imaging.

The second major limitation concerns the lack of a gold standard, namely the lack of histopathologic confirmation of an atherosclerotic plaque and associated cell types. Although the colocalization of CD68 (macrophages) and CXCR4 within atherosclerotic plaques observed in prior studies suggests that at least part of the PET signal originates from macrophages (28,31,38), no definitive conclusions can be drawn about its exact cellular source, as it is the sum of all CXCR4-expressing cells localized within or near a particular lesion and may include a combination of various cell types, including T-cells, thrombocytes, and smooth muscle cells (18,31,39,41).

The third major limitation concerns the radiopharmaceutical itself. The use of 68Ga-labeled tracers for vascular PET imaging poses several physical and technical challenges, as the high positron energy and high positron range of 68Ga lead to noisier images and worse spatial resolution, which are amplified by the lower injected activity of 68Ga compared with 18F-FDG. Therefore, it cannot be ruled out that the increased number of foci observed with 68Ga-pentixafor PET is (at least partially) attributable to noise (44). These limitations are partly compensated by the predominantly high specificity of most 68Ga-labeled radiopharmaceuticals in comparison to the nonspecific tissue uptake of 18F-labeled FDG (45). In addition, 68Ga-labeled tracers have already been successfully used to image atherosclerotic plaques in vessels as small as the coronary arteries (46), and the general feasibility of plaque imaging with 68Ga-pentixafor PET in particular has been demonstrated in recent studies (30,38). The reproducibility of the data was not tested in this retrospective study.

CONCLUSION

CXCR4-directed imaging of the arterial wall with 68Ga-pentixafor PET/CT identified more lesions than 18F-FDG PET/CT, with only a weak correlation between tracers. Further studies to elucidate the underlying biologic mechanisms and sources of CXCR4 positivity and to investigate the clinical utility of chemokine receptor–directed imaging of atherosclerosis are highly warranted.

DISCLOSURE

Hans-Jürgen Wester is founder and shareholder of Scintomics. No other potential conflict of interest relevant to this article was reported.

KEY POINTS

  • QUESTION: Is CXCR4-directed 68Ga-pentixafor PET/CT able to image inflammation in atherosclerosis, and how does it compare with 18F-FDG PET/CT?

  • PERTINENT FINDINGS: In a cohort of 92 oncologic patients, 68Ga-pentixafor PET/CT identified more lesions with higher target-to-background contrast than 18F-FDG PET/CT.

  • IMPLICATIONS FOR PATIENT CARE: Imaging of CXCR4 expression might contribute to a better understanding of the dynamics of atheroprogression and plaque destabilization and, in the future, might help identify patients at risk of cardiovascular events.

Footnotes

  • Published online Oct. 25, 2019.

  • © 2020 by the Society of Nuclear Medicine and Molecular Imaging.

REFERENCES

  1. 1.↵
    1. Pant S,
    2. Deshmukh A,
    3. Gurumurthy GS,
    4. et al
    . Inflammation and atherosclerosis: revisited. J Cardiovasc Pharmacol Ther. 2014;19:170–178.
    OpenUrlCrossRefPubMed
  2. 2.↵
    1. Benjamin EJ,
    2. Virani SS,
    3. Callaway CW,
    4. et al
    . Heart disease and stroke statistics: 2018 update—a report from the American Heart Association. Circulation. 2018;137:e67–e492.
    OpenUrlFREE Full Text
  3. 3.↵
    1. Weber C,
    2. Noels H
    . Atherosclerosis: current pathogenesis and therapeutic options. Nat Med. 2011;17:1410–1422.
    OpenUrlCrossRefPubMed
  4. 4.
    1. Hansson GK,
    2. Hermansson A
    . The immune system in atherosclerosis. Nat Immunol. 2011;12:204–212.
    OpenUrlCrossRefPubMed
  5. 5.↵
    1. Moore KJ,
    2. Tabas I
    . Macrophages in the pathogenesis of atherosclerosis. Cell. 2011;145:341–355.
    OpenUrlCrossRefPubMed
  6. 6.↵
    1. Finn AV,
    2. Nakano M,
    3. Narula J,
    4. Kolodgie FD,
    5. Virmani R
    . Concept of vulnerable/unstable plaque. Arterioscler Thromb Vasc Biol. 2010;30:1282–1292.
    OpenUrlAbstract/FREE Full Text
  7. 7.↵
    1. Libby P,
    2. Ridker PM,
    3. Hansson GK
    . Progress and challenges in translating the biology of atherosclerosis. Nature. 2011;473:317–325.
    OpenUrlCrossRefPubMed
  8. 8.↵
    1. Ridker PM,
    2. Everett BM,
    3. Thuren T,
    4. et al
    . Antiinflammatory therapy with canakinumab for atherosclerotic disease. N Engl J Med. 2017;377:1119–1131.
    OpenUrlCrossRefPubMed
  9. 9.↵
    1. Rudd JH,
    2. Hyafil F,
    3. Fayad ZA
    . Inflammation imaging in atherosclerosis. Arterioscler Thromb Vasc Biol. 2009;29:1009–1016.
    OpenUrlAbstract/FREE Full Text
  10. 10.↵
    1. Joseph P,
    2. Tawakol A
    . Imaging atherosclerosis with positron emission tomography. Eur Heart J. 2016;37:2974–2980.
    OpenUrlCrossRefPubMed
  11. 11.↵
    1. Tarkin JM,
    2. Dweck MR,
    3. Evans NR,
    4. et al
    . Imaging atherosclerosis. Circ Res. 2016;118:750–769.
    OpenUrlAbstract/FREE Full Text
  12. 12.↵
    1. Tawakol A,
    2. Migrino RQ,
    3. Bashian GG,
    4. et al
    . In vivo 18F-fluorodeoxyglucose positron emission tomography imaging provides a noninvasive measure of carotid plaque inflammation in patients. J Am Coll Cardiol. 2006;48:1818–1824.
    OpenUrlFREE Full Text
  13. 13.↵
    1. Li X,
    2. Heber D,
    3. Cal-Gonzalez J,
    4. et al
    . Association between osteogenesis and inflammation during the progression of calcified plaque evaluated by 18F-fluoride and 18F-FDG. J Nucl Med. 2017;58:968–974.
    OpenUrlAbstract/FREE Full Text
  14. 14.↵
    1. Li X,
    2. Heber D,
    3. Rausch I,
    4. et al
    . Quantitative assessment of atherosclerotic plaques on 18F-FDG PET/MRI: comparison with a PET/CT hybrid system. Eur J Nucl Med Mol Imaging. 2016;43:1503–1512.
    OpenUrl
  15. 15.↵
    1. Moghbel M,
    2. Al-Zaghal A,
    3. Werner TJ,
    4. Constantinescu CM,
    5. Hoilund-Carlsen PF,
    6. Alavi A
    . The role of PET in evaluating atherosclerosis: a critical review. Semin Nucl Med. 2018;48:488–497.
    OpenUrl
  16. 16.
    1. Oliveira-Santos M,
    2. Castelo-Branco M,
    3. Silva R,
    4. et al
    . Atherosclerotic plaque metabolism in high cardiovascular risk subjects: a subclinical atherosclerosis imaging study with 18F-NaF PET-CT. Atherosclerosis. 2017;260:41–46.
    OpenUrl
  17. 17.↵
    1. Irkle A,
    2. Vesey AT,
    3. Lewis DY,
    4. et al
    . Identifying active vascular microcalcification by 18F-sodium fluoride positron emission tomography. Nat Commun. 2015;6:7495.
    OpenUrlCrossRefPubMed
  18. 18.↵
    1. Döring Y,
    2. Pawig L,
    3. Weber C,
    4. Noels H
    . The CXCL12/CXCR4 chemokine ligand/receptor axis in cardiovascular disease. Front Physiol. 2014;5:212.
    OpenUrlPubMed
  19. 19.↵
    1. Bernhagen J,
    2. Krohn R,
    3. Lue H,
    4. et al
    . MIF is a noncognate ligand of CXC chemokine receptors in inflammatory and atherogenic cell recruitment. Nat Med. 2007;13:587–596.
    OpenUrlCrossRefPubMed
  20. 20.↵
    1. Schmitt MM,
    2. Megens RT,
    3. Zernecke A,
    4. et al
    . Endothelial junctional adhesion molecule-A guides monocytes into flow-dependent predilection sites of atherosclerosis. Circulation. 2014;129:66–76.
    OpenUrlAbstract/FREE Full Text
  21. 21.↵
    1. Lapa C,
    2. Schreder M,
    3. Schirbel A,
    4. et al
    . [68Ga]pentixafor-PET/CT for imaging of chemokine receptor CXCR4 expression in multiple myeloma: comparison to [18F]FDG and laboratory values. Theranostics. 2017;7:205–212.
    OpenUrl
  22. 22.
    1. Lapa C,
    2. Luckerath K,
    3. Rudelius M,
    4. et al
    . [68Ga]pentixafor-PET/CT for imaging of chemokine receptor 4 expression in small cell lung cancer: initial experience. Oncotarget. 2016;7:9288–9295.
    OpenUrl
  23. 23.
    1. Vag T,
    2. Gerngross C,
    3. Herhaus P,
    4. et al
    . First experience with chemokine receptor CXCR4-targeted PET imaging of patients with solid cancers. J Nucl Med. 2016;57:741–746.
    OpenUrlAbstract/FREE Full Text
  24. 24.
    1. Wester HJ,
    2. Keller U,
    3. Schottelius M,
    4. et al
    . Disclosing the CXCR4 expression in lymphoproliferative diseases by targeted molecular imaging. Theranostics. 2015;5:618–630.
    OpenUrlCrossRefPubMed
  25. 25.↵
    1. Philipp-Abbrederis K,
    2. Herrmann K,
    3. Knop S,
    4. et al
    . In vivo molecular imaging of chemokine receptor CXCR4 expression in patients with advanced multiple myeloma. EMBO Mol Med. 2015;7:477–487.
    OpenUrlAbstract/FREE Full Text
  26. 26.↵
    1. Lapa C,
    2. Reiter T,
    3. Werner RA,
    4. et al
    . [68Ga]pentixafor-PET/CT for imaging of chemokine receptor 4 expression after myocardial infarction. JACC Cardiovasc Imaging. 2015;8:1466–1468.
    OpenUrlFREE Full Text
  27. 27.
    1. Thackeray JT,
    2. Derlin T,
    3. Haghikia A,
    4. et al
    . Molecular imaging of the chemokine receptor CXCR4 after acute myocardial infarction. JACC Cardiovasc Imaging. 2015;8:1417–1426.
    OpenUrlAbstract/FREE Full Text
  28. 28.↵
    1. Hyafil F,
    2. Pelisek J,
    3. Laitinen I,
    4. et al
    . Imaging the cytokine receptor CXCR4 in atherosclerotic plaques with the radiotracer 68Ga-pentixafor for PET. J Nucl Med. 2017;58:499–506.
    OpenUrlAbstract/FREE Full Text
  29. 29.
    1. Reiter T,
    2. Kircher M,
    3. Schirbel A,
    4. et al
    . Imaging of C-X-C motif chemokine receptor CXCR4 expression after myocardial infarction with [68Ga]pentixafor-PET/CT in correlation with cardiac MRI. JACC Cardiovasc Imaging. 2018;11:1541–1543.
    OpenUrlFREE Full Text
  30. 30.↵
    1. Weiberg D,
    2. Thackeray JT,
    3. Daum G,
    4. et al
    . Clinical molecular imaging of chemokine receptor CXCR4 expression in atherosclerotic plaque using 68Ga-pentixafor PET: correlation with cardiovascular risk factors and calcified plaque burden. J Nucl Med. 2018;59:266–272.
    OpenUrlAbstract/FREE Full Text
  31. 31.↵
    1. Merckelbach S,
    2. van der Vorst EPC,
    3. Kallmayer M,
    4. et al
    . Expression and cellular localization of CXCR4 and CXCL12 in human carotid atherosclerotic plaques. Thromb Haemost. 2018;118:195–206.
    OpenUrl
  32. 32.↵
    1. Lapa C,
    2. Herrmann K,
    3. Schirbel A,
    4. et al
    . CXCR4-directed endoradiotherapy induces high response rates in extramedullary relapsed multiple myeloma. Theranostics. 2017;7:1589–1597.
    OpenUrl
  33. 33.↵
    1. Lapa C,
    2. Hanscheid H,
    3. Kircher M,
    4. et al
    . Feasibility of CXCR4-directed radioligand therapy in advanced diffuse large B-cell lymphoma. J Nucl Med. 2019;60:60–64.
    OpenUrlAbstract/FREE Full Text
  34. 34.↵
    1. Aide N,
    2. Lasnon C,
    3. Veit-Haibach P,
    4. Sera T,
    5. Sattler B,
    6. Boellaard R
    . EANM/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies. Eur J Nucl Med Mol Imaging. 2017;44:17–31.
    OpenUrl
  35. 35.↵
    1. Bucerius J,
    2. Hyafil F,
    3. Verberne HJ,
    4. et al
    . Position paper of the Cardiovascular Committee of the European Association of Nuclear Medicine (EANM) on PET imaging of atherosclerosis. Eur J Nucl Med Mol Imaging. 2016;43:780–792.
    OpenUrlCrossRefPubMed
  36. 36.↵
    1. Agatston AS,
    2. Janowitz WR,
    3. Hildner FJ,
    4. Zusmer NR,
    5. Viamonte M Jr.,
    6. Detrano R
    . Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15:827–832.
    OpenUrlFREE Full Text
  37. 37.↵
    1. Greenland P,
    2. LaBree L,
    3. Azen SP,
    4. Doherty TM,
    5. Detrano RC
    . Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA. 2004;291:210–215.
    OpenUrlCrossRefPubMed
  38. 38.↵
    1. Li X,
    2. Yu W,
    3. Wollenweber T,
    4. et al
    . [68Ga]pentixafor PET/MR imaging of chemokine receptor 4 expression in the human carotid artery. Eur J Nucl Med Mol Imaging. 2019;46:1616–1625.
    OpenUrl
  39. 39.↵
    1. Döring Y,
    2. Noels H,
    3. van der Vorst EPC,
    4. et al
    . Vascular CXCR4 limits atherosclerosis by maintaining arterial integrity: evidence from mouse and human studies. Circulation. 2017;136:388–403.
    OpenUrlAbstract/FREE Full Text
  40. 40.↵
    1. Grosse GM,
    2. Bascunana P,
    3. Schulz-Schaeffer WJ,
    4. et al
    . Targeting chemokine receptor CXCR4 and translocator protein for characterization of high-risk plaque in carotid stenosis ex vivo. Stroke. 2018;49:1988–1991.
    OpenUrl
  41. 41.↵
    1. Zernecke A,
    2. Weber C
    . Chemokines in atherosclerosis: proceedings resumed. Arterioscler Thromb Vasc Biol. 2014;34:742–750.
    OpenUrlAbstract/FREE Full Text
  42. 42.↵
    1. O’Connor SD,
    2. Graffy PM,
    3. Zea R,
    4. Pickhardt PJ
    . Does nonenhanced CT-based quantification of abdominal aortic calcification outperform the Framingham risk score in predicting cardiovascular events in asymptomatic adults? Radiology. 2019;290:108–115.
    OpenUrl
  43. 43.↵
    1. Derlin T,
    2. Toth Z,
    3. Papp L,
    4. et al
    . Correlation of inflammation assessed by 18F-FDG PET, active mineral deposition assessed by 18F-fluoride PET, and vascular calcification in atherosclerotic plaque: a dual-tracer PET/CT study. J Nucl Med. 2011;52:1020–1027.
    OpenUrlAbstract/FREE Full Text
  44. 44.↵
    1. Derlin T,
    2. Thiele J,
    3. Weiberg D,
    4. et al
    . Evaluation of 68Ga-glutamate carboxypeptidase II ligand positron emission tomography for clinical molecular imaging of atherosclerotic plaque neovascularization. Arterioscler Thromb Vasc Biol. 2016;36:2213–2219.
    OpenUrlAbstract/FREE Full Text
  45. 45.↵
    1. Sanchez-Crespo A
    . Comparison of gallium-68 and fluorine-18 imaging characteristics in positron emission tomography. Appl Radiat Isot. 2013;76:55–62.
    OpenUrlCrossRef
  46. 46.↵
    1. Derlin T,
    2. Sedding DG,
    3. Dutzmann J,
    4. et al
    . Imaging of chemokine receptor CXCR4 expression in culprit and nonculprit coronary atherosclerotic plaque using motion-corrected [68Ga]pentixafor PET/CT. Eur J Nucl Med Mol Imaging. 2018;45:1934–1944.
    OpenUrl
  • Received for publication July 25, 2019.
  • Accepted for publication September 27, 2019.
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine: 61 (5)
Journal of Nuclear Medicine
Vol. 61, Issue 5
May 1, 2020
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Journal of Nuclear Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Imaging Inflammation in Atherosclerosis with CXCR4-Directed 68Ga-Pentixafor PET/CT: Correlation with 18F-FDG PET/CT
(Your Name) has sent you a message from Journal of Nuclear Medicine
(Your Name) thought you would like to see the Journal of Nuclear Medicine web site.
Citation Tools
Imaging Inflammation in Atherosclerosis with CXCR4-Directed 68Ga-Pentixafor PET/CT: Correlation with 18F-FDG PET/CT
Malte Kircher, Johannes Tran-Gia, Luisa Kemmer, Xiaoli Zhang, Andreas Schirbel, Rudolf A. Werner, Andreas K. Buck, Hans-Jürgen Wester, Marcus Hacker, Constantin Lapa, Xiang Li
Journal of Nuclear Medicine May 2020, 61 (5) 751-756; DOI: 10.2967/jnumed.119.234484

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Imaging Inflammation in Atherosclerosis with CXCR4-Directed 68Ga-Pentixafor PET/CT: Correlation with 18F-FDG PET/CT
Malte Kircher, Johannes Tran-Gia, Luisa Kemmer, Xiaoli Zhang, Andreas Schirbel, Rudolf A. Werner, Andreas K. Buck, Hans-Jürgen Wester, Marcus Hacker, Constantin Lapa, Xiang Li
Journal of Nuclear Medicine May 2020, 61 (5) 751-756; DOI: 10.2967/jnumed.119.234484
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Abstract
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSION
    • DISCLOSURE
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF

Related Articles

  • This Month in JNM
  • PubMed
  • Google Scholar

Cited By...

  • Radiotracers to Address Unmet Clinical Needs in Cardiovascular Imaging, Part 2: Inflammation, Fibrosis, Thrombosis, Calcification, and Amyloidosis Imaging
  • Improved Primary Staging of Marginal-Zone Lymphoma by Addition of CXCR4-Directed PET/CT
  • Google Scholar

More in this TOC Section

Cardiovascular

  • Cardiac β-Adrenergic Receptor Downregulation, Evaluated by Cardiac PET, in Chronotropic Incompetence
  • Diagnostic Performance of PET Versus SPECT Myocardial Perfusion Imaging in Patients with Smaller Left Ventricles: A Substudy of the 18F-Flurpiridaz Phase III Clinical Trial
  • Quantification of Macrophage-Driven Inflammation During Myocardial Infarction with 18F-LW223, a Novel TSPO Radiotracer with Binding Independent of the rs6971 Human Polymorphism
Show more Cardiovascular

Clinical

  • Dual PET Imaging in Bronchial Neuroendocrine Neoplasms: The NETPET Score as a Prognostic Biomarker
  • Addition of 131I-MIBG to PRRT (90Y-DOTATOC) for Personalized Treatment of Selected Patients with Neuroendocrine Tumors
  • SUVs Are Adequate Measures of Lesional 18F-DCFPyL Uptake in Patients with Low Prostate Cancer Disease Burden
Show more Clinical

Similar Articles

Keywords

  • atherosclerotic lesions
  • Plaque
  • Molecular imaging
  • CXCR4
  • FDG
SNMMI

© 2025 SNMMI

Powered by HighWire