Automated Definition of Skeletal Disease Burden in Metastatic Prostate Carcinoma: A 3D Analysis of SPECT/CT Images

To meet the current need for skeletal tumor-load estimation in castration-resistant prostate cancer (CRPC), we developed a novel approach based on adaptive bone segmentation. In this study, we compared the program output with existing estimates and with the radiological outcome. Seventy-six whole-body single-photon emission computed tomographies/x-ray computed tomography with 3,3-diphosphono-1,2-propanedicarboxylic acid from mCRPC patients were analyzed. The software identified the whole skeletal volume (S_Vol) and classified the voxels metastases (M_Vol) or normal bone (B_Vol). S_Vol was compared with the estimation of a commercial software. M_Vol was compared with manual assessment and with prostate specific antigen (PSA) levels. Counts/voxel were extracted from M_Vol and B_Vol. After six cycles of ²²³RaCl2-therapy every patient was re-evaluated as having progressive disease (PD), stable disease (SD), or a partial response (PR). S_Vol correlated with that of the commercial software (R = 0.99, p < 0.001). M_Vol correlated with the manually-counted lesions (R = 0.61, p < 0.001) and PSA (R = 0.46, p < 0.01). PD had a lower counts/voxel in M_Vol than PR/SD (715 ± 190 vs. 975 ± 215 and 1058 ± 255, p < 0.05 and p < 0.01) and B_Vol (PD 275 ± 60, PR 515 ± 188 and SD 528 ± 162 counts/voxel, p < 0.001). Segmentation-based tumor load correlated with radiological/laboratory indices. Uptake was linked with the clinical outcome, suggesting that metastases in PD patients have a lower affinity for bone-seeking radionuclides and might benefit less from bone-targeted radioisotope therapies.