Evaluating ΔMTV%, ΔDmax%, and %ΔSUVmax of 18F-FDG PET/CT for mid-treatment efficacy and prognosis in diffuse large B-cell lymphoma
Yali Cui, Yao Li, Wenhao Hu, Zhifang Wu, Sijin Li, Hongliang Wang
Abstract
To investigate the value of 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) imaging in interim therapeutic and prognostic evaluation of patients with diffuse large B-cell lymphoma (DLBCL). Data of 86 patients with pathologically confirmed DLBCL who underwent 18 F-FDG PET/CT imaging before chemotherapy, radiotherapy, and after interim chemotherapy, were retrospectively analyzed. Receive operating characteristic (ROC) curve analysis was performed to assess the predictive capacity of changes and change rates in PET/CT imaging parameters [maximum standardized uptake value (SUV max ), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum tumor dissemination (D max )] for progression-free survival (PFS) and to identify optimal cutoff values. Kaplan–Meier survival curves were constructed, and the log-rank test was used to assess intergroup differences. Cox regression analysis was used to explore potential factors influencing PFS. Among 86 patients [(45 men, 41 women, age: 57.8 ± 12.2 years)], the median PFS was 22.5 (14.5, 46) months. Until the last follow-up date, progression or recurrence occurred in 14 patients, while 9 patients died. The ROC curves indicated that the optimal cutoff values for predicting PFS were 99.10%, 99.72%, and 96.47% for ΔMTV%, ΔTLG%, and ΔD max %, respectively (area under the curve = 0.786–0.849, all P < 0.05). Cox univariate analysis demonstrated that the alteration rates in metabolic and diffusion parameters before and after treatment, including SUV max %, MTV%, TLG%, and D max %, were predictive of PFS (hazard ratio [HR] = 6.213–13.430, all P < 0.05). The Cox multivariate analysis demonstrated that ΔMTV% and ΔD max % independently predicted PFS, with HRs of 10.727 (95% confidence interval [CI] = 1.928–56.672, P = 0.007) and 7.178 (95%CI = 1.514–34.041, P = 0.013), respectively. We established a new prediction model by combining the ΔMTV% and ΔD max % parameters, and the results of the model showed statistically significant differences in PFS between the high, intermediate, and low-risk groups. The model predicted higher effects than individual indicators. The rate of change in metabolic and diffusion parameters on interim PET/CT can predict the prognosis of patients with DLBCL.