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Prognostic value of 68Ga-DOTATATE PET/CT in assessing cardiac involvement in autoimmune diseases: a prospective study
1Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Background:
This prospective study aimed to evaluate the prognostic value of 68Ga-DOTATATE PET/CT imaging in assessing myocardial macrophage infiltration in patients with autoimmune diseases and its relationship with clinical outcomes, specifically all-cause mortality and cardiovascular rehospitalization.
Methods:
A total of 36 patients with cardiac involvement due to autoimmune diseases were enrolled. All underwent 68Ga-DOTATATE PET/CT imaging to assess left ventricular mononuclear macrophage infiltration. Clinical data, including myocardial biopsy results and left ventricular SUV values (LVmax and LVmean), were recorded. Prognostic thresholds were identified using ROC curve analysis, while Kaplan-Meier survival were used to analyze the relationship between myocardial macrophage activity and clinical outcomes.
Results:
Of the 36 patients, 9 died and 9 were rehospitalized for cardiovascular reasons. ROC analysis demonstrated that LVmax ≥ 2.405 predicted all-cause mortality with an AUC of 0.96 (95% CI: 0.92-1.00, P < 0.0001), while LVmean ≥ 1.36 predicted cardiovascular rehospitalization with an AUC of 0.87 (95% CI: 0.79-0.96, P < 0.0001). High 68Ga-DOTATATE uptake thus significantly correlated with adverse clinical outcomes, surpassing traditional markers such as ejection fraction and inflammatory biomarkers. Moreover, 68Ga-DOTATATE imaging results were more consistent with the patients' clinical conditions compared to myocardial biopsy, highlighting its superior diagnostic utility in assessing diffuse myocardial inflammation.
Conclusion:
68Ga-DOTATATE PET/CT imaging offers a valuable, non-invasive, and quantitative method for assessing myocardial inflammation in autoimmune diseases. This technique shows potential for improving personalized treatment and prognosis by identifying patients at higher risk for adverse outcomes in autoimmune diseases.
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