Analytical Validation of the Automated Bone Scan Index as an Imaging Biomarker to Standardize the Quantitative Changes in Bone Scans of Patients with Metastatic Prostate Cancer

Abstract

Rationale: A reproducible and quantitative imaging biomarker to standardize the evaluation of changes in bone scans is an unmet need for prostate cancer patients with skeletal metastasis. Here we have performed a series of analytical validation studies to evaluate the performance of the automated Bone Scan Index (BSI) as an imaging biomarker in patients with metastatic prostate cancer (mPCa). Methods: Three separate analytical studies were performed to evaluate accuracy, precision, and reproducibility of automated BSI. Simulation Study: Bone scan simulations with pre-defined tumor burdens were created to assess accuracy and precision. Fifty bone scans were simulated with a tumor burden ranging from low to high disease confluence (0.10 to 13.0 BSI). A second group of 50 scans was divided into 5 subgroups, each containing 10 simulated bone scans, corresponding to BSI values of 0.5, 1.0, 3.0, 5.0 and 10.0. Repeat Bone Scan Study: To assess the reproducibility in routine clinical setting, two repeat bone scans were obtained from mPCa patients after a single 600 MBq ^99mTc MDP injection. Follow-up Bone Scan Study: Two follow-up bone scans of mPCa patients were analyzed to compare the inter-observer variability of the automated BSI with that of the qualitative visual reads in assessing changes between the bone scans. The automated BSI was calculated using the software EXINI boneBSI. The results were evaluated using linear regression, Pearson’s correlation, Cohen’s kappa (κ) measurement, coefficient of variation and standard deviation (SD). Results: Linearity of the automated BSI in the range of 0.10 to 13.0 was confirmed, and Pearson’s correlation was observed at 0.995 (N = 50, 95% CI 0.99–0.99, P < 0.0001). The mean coefficient of variation was less than 20%. The mean BSI difference between the two repeat bone scans of 35 patients was 0.05 (SD=0.15), with an upper confidence limits at 0.30. The inter-observer agreement in the automated BSI was more consistent (κ=0.96, P < 0.0001) than the qualitative visual assessment of the changes (κ=0.70, P < 0.0001) in bone scans of 173 patients. Conclusion: The automated BSI is a consistent imaging biomarker with performance characteristics that can standardize the quantitative changes in bone scans of patients with mPCa.