Analytic Validation of the Automated Bone Scan Index as an Imaging Biomarker to Standardize Quantitative Changes in Bone Scans of Patients with Metastatic Prostate Cancer - Aseem Anand; Michael J. Morris; Reza Kaboteh; Lena Båth; May Sadik; Peter Gjertsson; Milan Lomsky; Lars Edenbrandt; David Minarik; Anders Bjartell (2015)
A reproducible and quantitative imaging biomarker is needed to standardize the evaluation of changes in bone scans of prostate cancer patients with skeletal metastasis. We performed a series of analytic validation studies to evaluate the performance of the automated bone scan index (BSI) as an imaging biomarker in patients with metastatic prostate cancer. Methods: Three separate analytic studies were performed to evaluate the accuracy, precision, and reproducibility of the automated BSI. Simulation study: bone scan simulations with predefined 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 (0.10–13.0 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 a routine clinical setting, 2 repeat bone scans were obtained from metastatic prostate cancer patients after a single 600-MBq 99mTc-methylene diphosphonate injection. Follow-up bone scan study: 2 follow-up bone scans of metastatic prostate cancer patients were analyzed to determine the interobserver variability between the automated BSIs and the visual interpretations in assessing changes. The automated BSI was generated using the upgraded EXINI boneBSI software (version 2). The results were evaluated using linear regression, Pearson correlation, Cohen κ measurement, coefficient of variation, and SD. Results: Linearity of the automated BSI interpretations in the range of 0.10–13.0 was confirmed, and Pearson correlation was observed at 0.995 (n = 50; 95% confidence interval, 0.99–0.99; P < 0.0001). The mean coefficient of variation was less than 20%. The mean BSI difference between the 2 repeat bone scans of 35 patients was 0.05 (SD = 0.15), with an upper confidence limit of 0.30. The interobserver agreement in the automated BSI interpretations was more consistent (κ = 0.96, P < 0.0001) than the qualitative visual assessment of the changes (κ = 0.70, P < 0.0001) was in the bone scans of 173 patients. Conclusion: The automated BSI provides a consistent imaging biomarker capable of standardizing quantitative changes in the bone scans of patients with metastatic prostate cancer.