To meet the current need for skeletal tumor-load estimation in prostate cancer, we developed a novel approach, based on adaptive bone segmentation. Seventy-six whole-body tumors from mCRPC patients were analyzed. Segmentation-based tumor load correlated with radiological/laboratory metrics.
To meet the current need for skeletal tumor-load estimation in prostate
cancer (mCRPC), 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
99mTc-DPD-SPECT/CT from mCRPC patients were analyzed. The software identified
the whole skeletal volume (SVol) and classified it voxels metastases (MVol) or
normal bone (BVol). SVol was compared with the estimation of a commercial
software. MVol was compared with manual assessment and with PSA-level.
Counts/voxel were extracted from MVol and BVol. After six cycles of
223RaCl2-therapy every patient was re-evaluated as progressing (PD), stabilized
(SD) or responsive (PR). SVol correlated with the one of the commercial
software (R=0,99, p<0,001). MVol correlated with manually-counted lesions
(R=0,61, p<0,001) and PSA (R=0,46, p<0.01). PD had a lower counts/voxel in MVol
than PR/SD (715 \pm 190 Vs. 975 \pm 215 and 1058 \pm 255, p<0,05 and p<0,01)
and in BVol (PD 275 \pm 60, PR 515 \pm 188 and SD 528 \pm 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.