Combined Metabolic and Functional Tumor Volumes on [18F]FDG-PET/MRI in Neuroblastoma Using Voxel-Wise Analysis

Abstract

Purpose: The purpose of our study was to evaluate the association between the [¹⁸F]FDG standard uptake value (SUV) and the apparent diffusion coefficient (ADC) in neuroblastoma (NB) by voxel-wise analysis.

Methods: From our prospective observational PET/MRI study, a subcohort of patients diagnosed with NB with both baseline imaging and post-chemotherapy imaging was further investigated. After registration and tumor segmentation, metabolic and functional tumor volumes were calculated from the ADC and SUV values using dedicated software allowing for voxel-wise analysis. Under the mean of thresholds, each voxel was assigned to one of three virtual tissue groups: highly vital (v) (low ADC and high SUV), possibly low vital (lv) (high ADC and low SUV), and equivocal (e) with high ADC and high SUV or low ADC and low SUV. Moreover, three clusters were generated from the total tumor volumes using the method of multiple Gaussian distributions. The Pearson's correlation coefficient between the ADC and the SUV was calculated for each group.

Results: Out of 43 PET/MRIs in 21 patients with NB, 16 MRIs in 8 patients met the inclusion criteria (PET/MRIs before and after chemotherapy). The proportion of tumor volumes were 26%, 36%, and 38% (v, lv, e) at baseline, 0.03%, 66%, and 34% after treatment in patients with response, and 42%, 25%, and 33% with progressive disease, respectively. In all clusters, the ADC and the SUV correlated negatively. In the cluster that corresponded to highly vital tissue, the ADC and the SUV showed a moderate negative correlation before treatment (R = -0.18; p < 0.0001) and the strongest negative correlation after treatment (R = -0.45; p < 0.0001). Interestingly, only patients with progression (n = 2) under therapy had a relevant part in this cluster post-treatment.

Conclusion: Our results indicate that voxel-wise analysis of the ADC and the SUV is feasible and can quantify the different quality of tissue in neuroblastic tumors. Monitoring ADCs as well as SUV levels can quantify tumor dynamics during therapy.

Keywords: PET/MRI; high-risk neuroblastoma; voxel-wise analysis.

Figure 1

Example of tumor segmentation and clustering in a 3-year-old patient (Nr. 1) with retroperitoneal manifestation of neuroblastoma. (A) Axial T2-weighted image. (B) Axial fused image of the corrected PET dataset and the T2-weighted image. (C) After clustering, the voxels were assigned to one of three clusters: cluster 1  =  red, cluster 2  =  blue, cluster 3  =  green. (D) The volume of interest included total tumor volume.

Figure 2

Proportion and distribution of the three clusters in total and separately for each patient before and after chemotherapy: (A) in total before therapy, (B) therapy response, (C) progressive disease. Red—“vital” cluster, blue—“equivocal”, green—“low vital”.

Figure 3

Proportion of voxels in three tissue groups (left) and clusters (right). Cluster 1 “malignant”, cluster 2 “low vital”, cluster 3 “equivocal”. There is a similar distribution between the respective clusters and tissue groups before and after chemotherapy: there was a significantly increase in the proportion of the “vital tissue” group in patients with progressive disease and a decrease in the “low vital tissue” group and in the “equivocal tissue” group. For patients responding to chemotherapy, the “low vital tissue” increased and the “vital tissue” decreased significantly. Interestingly, the “equivocal tissue” group also decreased significantly (p < 0.05).