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. 2020 Sep;13(9):e010628.
doi: 10.1161/CIRCIMAGING.120.010628. Epub 2020 Sep 11.

Relationship Between Cardiac Fibroblast Activation Protein Activity by Positron Emission Tomography and Cardiovascular Disease

Affiliations

Relationship Between Cardiac Fibroblast Activation Protein Activity by Positron Emission Tomography and Cardiovascular Disease

Markus B Heckmann et al. Circ Cardiovasc Imaging. 2020 Sep.

Abstract

Background: FAP (fibroblast activation protein) plays an important role in cardiac wound healing and remodeling. Although initially developed as a theranostic ligand for metastasized cancer, FAPI (FAP inhibitor) tracers have recently been used to study cardiac remodeling following myocardial infarction in small-animal models. The aim of the study was to evaluate the activity of FAP via FAPI-positron emission tomography-computed tomography scans in human hearts.

Methods: FAPI-positron emission tomography-computed tomography scans of 229 patients of 2 consecutive cohorts (modeling cohort: n=185; confirmatory cohort: n=44) suffering from metastasized cancer were analyzed applying the American Heart Association 17-segment model of the left ventricle. Logistic regression models were created using data from the modeling cohort. Multivariate regression models were established using Akaike information criterion in a step-down approach.

Results: Fourteen percent of patients had preexisting coronary artery disease (n=31), 33% arterial hypertension (n=75), and 12% diabetes mellitus type II (n=28). Forty-three percent had been treated with platin derivatives (n=100), 14% with anthracyclines (n=32), and 10% had a history of prior radiation to the chest (n=23). High left ventricular FAPI signals correlated with the presence of cardiovascular risk factors (odds ratio [OR], 4.3, P=0.0029), a focal myocardial signal pattern (OR, 3.9, P=0.0068), diabetes mellitus type II (OR, 4.1, P=0.046), and beta-blocker use (OR, 3.8, P=0.049) in univariate regression models. In a multivariate analysis, increased signal intensity was significantly higher in patients with cardiovascular risk factors (overweight [OR, 2.6, P=0.023], diabetes mellitus type II [OR, 2.9, P=0.041], certain chemotherapies [platinum derivatives; OR, 3.0, P=0.034], and a history of radiation to the chest [OR, 3.5, P=0.024]). A focal enrichment pattern was more frequently observed in patients with known cardiovascular risk factors (P<0.0001).

Conclusions: FAPI-positron emission tomography-computed tomography scans represent a new imaging modality to investigate cardiac FAP. High signal intensities correlate with cardiovascular risk factors and metabolic disease.

Keywords: diabetes mellitus; fibroblast; myocardial infarction; risk factors; tomography.

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Conflict of interest statement

U. Haberkorn has a patent application for quinoline based FAP (fibroblast activation protein)-targeting agents for imaging and therapy in nuclear medicine and has shares of a consultancy-group for iTheranostics. The authors filed a patent application for quinoline based FAP-targeting agents for the diagnosis of cardiovascular disease.

Figures

Figure 1.
Figure 1.
Logistic regression and linear prediction model for FAPI (fibroblast activation protein inhibitor) signal in the myocardium. A, Multivariate logistic regression models for signal intensity and focal enrichment. Odds ratios (OR) are depicted as a dot. Lines mark the 95% CI. Although metabolic variables, such as increased thyroid-stimulating hormone (TSH), radiation, diabetes mellitus, overweight, and different chemotherapies, are associated with an increased FAPI signal, focal FAPI enrichment patterns are mainly associated with cardiovascular risk. N=185 for both analyses. B, Linear regression model for FAPI signal intensity prediction and outlier analysis based on significant variables of the multivariate logistic regression analysis. The model was established with the initial cohort (N=185) and tested for accuracy with a confirmatory cohort (N=44). Outliers (N=11) are marked in red in both plots. Outliers were defined as patients with residuals (actual–predicted FAPI signal) above the 95% mark of the initial cohort. Patient characteristics of the outlier cohort are reported in Table. BMI indicates body mass index; CTx, chemotherapy; CvRF, cardiovascular risk factors; and GFR, glomerular filtration rate.
Figure 2.
Figure 2.
Bullseye 17-segment analysis of different subgroups with representative FAPI (fibroblast activation protein inhibitor) images. The median signal intensity of the corresponding segment is displayed for each group. The number of patients in a group is seen in the right lower corner of each bullseye above the color scale. The color coding was taken from a spectral color scale ranging from 0.7 (blue) to 1.3 (red) with 1.0 (yellow) being the center. Representative FAPI images are displayed below. Signal intensity was generally increased in the septal basal segments. The apex exhibited the lowest signal intensity. This effect was most pronounced in arterial hypertension. Diabetes mellitus, arterial hypertension, and obesity—all risk factors associated with metabolic stress and cardiac remodeling—show the highest increase in FAPI signals. BMI indicates body mass index; and CvRF, cardiovascular risk factors.

Comment in

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