Prognostic parameters on baseline and interim [ 18 F]FDG-PET/computed tomography in diffuse large B-cell lymphoma...

Area of Science:

• Oncology
• Nuclear Medicine
• Radiomics

Background:

• 2-[ 18 F]fluoro-2-deoxy- d -glucose PET/computed tomography (FDG-PET/CT) is integral to managing diffuse large B-cell lymphomas (DLBCL).
• Prognostic performance of various FDG-PET/CT biomarkers requires further investigation in multicenter settings.

Purpose of the Study:

• To evaluate the prognostic accuracy of different baseline and interim FDG-PET/CT biomarkers for predicting progression-free survival (PFS) in DLBCL patients.
• To compare the performance of volumetric PET parameters (MTV, TLG) and interim PET parameters (Deauville score, ΔSUVmax, mqPET, rPET) using various segmentation methods.

Main Methods:

• 107 DLBCL patients underwent baseline and interim FDG-PET/CT.
• Baseline volumetric parameters (metabolic tumor volume [MTV], total lesion glycolysis [TLG]) were segmented using three methods (glob4, 41pc, grad).
• Interim parameters included Deauville score, ΔSUVmax, modified qPET (mqPET), and ratio PET (rPET). Progression-free survival (PFS) at 24 months was the endpoint. Receiver operating characteristic (ROC) analyses determined optimal cutoff points.

Main Results:

• Baseline MTV and TLG, despite good correlation across segmentation methods, showed different optimal cutoffs and limited prognostic impact.
• Interim PET parameters (Deauville score, ΔSUVmax, mqPET, rPET) and baseline body weight-adjusted MTV and TLG significantly differentiated between low- and high-risk groups.
• Multivariate analysis identified ratio PET (rPET) as an independent predictor of PFS (HR=9.15, P=0.041).
• Combination of ΔSUVmax positivity and high MTV indicated distinctly poor PFS (35.3%).

Conclusions:

• Interim FDG-PET/CT parameters demonstrate superior prognostic performance over baseline volumetric parameters in DLBCL.
• Semiquantitative 'Deauville-like' interim parameters offer the most accurate prognostic information.
• Baseline MTV and TLG segmentation methods yield variable optimal cutoffs, limiting their prognostic utility.