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 (223)RaCl2-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.