Diagnostic and prognostic value of baseline FDG PET/CT skeletal textural features in diffuse large B cell lymphoma

Our purpose was to evaluate the diagnostic and prognostic value of skeletal textural features (TFs) on baseline FDG PET in diffuse large B cell lymphoma (DLBCL) patients.

Eighty-two patients with DLBCL who underwent a bone marrow biopsy (BMB) and a PET scan between December 2008 and December 2015 were included. Two readers blinded to the BMB results visually assessed PET images for bone marrow involvement (BMI) in consensus, and a third observer drew a volume of interest (VOI) encompassing the axial skeleton and the pelvis, which was used to assess skeletal TFs. ROC analysis was used to determine the best TF able to diagnose BMI among four first-order, six second-order and 11 third-order metrics, which was then compared for diagnosis and prognosis in disease-free patients (BMB-/PET-) versus patients considered to have BMI (BMB+/PET-, BMB-/PET+, and BMB+/PET+).

Twenty-two out of 82 patients (26.8%) had BMI: 13 BMB-/PET+, eight BMB+/PET+ and one BMB+/PET-. Among the nine BMB+ patients, one had discordant BMI identified by both visual and TF PET assessment. ROC analysis showed that SkewnessH, a first-order metric, was the best parameter for identifying BMI with sensitivity and specificity of 81.8% and 81.7%, respectively. SkewnessH demonstrated better discriminative power over BMB and PET visual analysis for patient stratification: hazard ratios (HR), 3.78 (P = 0.02) versus 2.81 (P = 0.06) for overall survival (OS) and HR, 3.17 (P = 0.03) versus 1.26 (P = 0.70) for progression-free survival (PFS). In multivariate analysis accounting for IPI score, bulky status, haemoglobin and SkewnessH, the only independent predictor of OS was the IPI score, while the only independent predictor of PFS was SkewnessH.

The better discriminative power of skeletal heterogeneity for risk stratification compared to BMB and PET visual analysis in the overall population, and more specifically in BMB-/PET- patients, suggests that it can be useful to identify diagnostically overlooked BMI.