RT Journal Article
SR Electronic
T1 Comparison of quantitative metabolic parameters of measurable tumors for the prediction of treatment response in patients with lymphoma using FDG PET
JF Journal of Nuclear Medicine
JO J Nucl Med
FD Society of Nuclear Medicine
SP 482P
OP 482P
VO 47
IS suppl 1
A1 Byun, Byung Hyun
A1 Cheon, Gi Jeong
A1 Park, Yeon Hee
A1 Lee, Sang Woo
A1 Choi, Chang Woon
YR 2006
UL http://jnm.snmjournals.org/content/47/suppl_1/482P.2.abstract
AB 1776 Objectives: The treatment response of lymphoma has usually been documented in measurable tumors using morphological cross-sectional imaging. However, it has been frequently reported that FDG PET yielded a more accurate assessment of therapeutic response than morphological imaging only. The aim of this study was to evaluate the adequate quantitative metabolic parameters for the prediction of therapeutic response. Methods: FDG PET was performed in 35 patients with lymphoma (5 HD, 30 NHL) at pre-treatment and after 1 week of 1st cycle of chemotherapy. Therapeutic response was evaluated by CT scans as the recommendation of IWC after the completion of chemotherapy (4 to 8 cycle). On each FDG PET scan, maximum SUV (maxSUV) was measured at the measurable tumors. We also acquired volume of interest (VOI) by the automatic edge detection software at the cut-off value of 50% maximal voxel activity in the measurable tumors. According to the VOI, we measured the metabolic volume and mean SUV, and then, calculated volume-activity indexes (SUV*Vol) as mean SUV times metabolic volume. Then, we acquired the decrements (%) of each metabolic parameter on FDG PET after 1 week of 1st-cycle of chemotherapy. Diagnostic performance of each metabolic parameter decrement was evaluated by receiver-operating characteristics (ROC) curves for prediction of therapeutic response (CR or not). Results: Of 35 patients, one patient with skin involvement was excluded because of the difficulty in locating measurable tumors. Initial stages of 34 lymphoma patients were stage I in 6, II in 11, III in 11, and IV in 6 by Ann Arbor system. Clinical responses after the completion of chemotherapy were CR/CRu in 30, PR in 1, PD in 3 by IWC. By the ROC curve analysis, area under the curve (AUC) and optimal criterion of each metabolic parameter decrement (%) according to the therapeutic response were as the table. There was no stastically significant difference between the metabolic parameters. Among the metabolic parameters, however, SUV*vol had the largest AUC (0.875) and optimal criterion of approximately 50% decrease for the prediction of treatment response. Conclusions: By ROC curve analysis, metabolic parameters of measurable tumors on FDG PET could be applicable to predict treatment response in patients with lymphoma. Among the metabolic parameters, SUV*Vol showed the largest AUC by ROC curve analysis to predict treatment response at the optimal criterion of approximately 50% decrement.