18F-FDG PET/CT metabolic parameters are correlated with clinical features and valuable in clinical stratification management in patients of castleman disease.

Abstract

Background: Castleman disease (CD) is a rare lymphoproliferative disorder. This study is to evaluate the correlation between ¹⁸F-flurodeoxyglucose (¹⁸F-FDG) positron emission tomography-computed tomography (PET/CT) and clinical features in CD patients, and exploring its value in distinguishing disease severity and assisting in risk stratification.

Methods: We retrospectively enrolled 93 patients with newly diagnosed CD. Traditional semi-quantitative ¹⁸F-FDG PET/CT parameters including the maximum standardized uptake value (SUV_max), total metabolic lesion volume (MLV), total lesion glycolysis (TLG) were measured, and the lymph node to liver ratio of SUV_max (LLR), lymph node to mediastinal blood pool of SUV_max (LMR), spleen to liver ratio of SUV_max (SLR) and No. of involved lymph node stations (LNS) were calculated. The correlation between these metabolic parameters and clinical features were studied using a univariate analysis. The influencing factors of CD severity were determined by univariate and multivariate analysis. The optimal cut-off values for metabolic parameters were obtained by receiver operating characteristic (ROC) curve.

Results: A total of 20 unicentric CD (UCD) and 73 multicentric CD (MCD) cases were included, with the highest SUV_max of Lymph nodes ranged 1.40 ~ 28.18 (median, 4.86). The metabolic parameters (SUV_max, MLV, TLG, LLR, LMR, SLR) in MCD were significantly higher than those in UCD (p < 0.05). There were significant differences in MLV, TLG, LLR and SLR among different histological subtypes (p < 0.05). The No. of involved lymph node stations (LNS) and spleen-to-liver ratio (SLR) were significantly correlated with laboratory findings. In univariate and multivariate analyses, SLR (p = 0.011; OR value = 14.806) and HGB (p = 0.004; OR value = 0.044) exhibited an independent correlation with disease severity. The ROC curve revealed that SLR had a sensitivity of 77.4%, specificity of 69.4% and AUC of 0.761 (cut-off value = 1.04; p < 0.001) in discriminating severity of CD. SLR also showed significant statistical differences between severe and non-severe idiopathic MCD (iMCD) (p = 0.016).

Conclusions: SLR is closely related to clinical features of CD, and can relatively effectively differentiate the severity of CD and assist in the clinical risk stratification of iMCD.