Aseem Anand1, Michael J Morris2, Reza Kaboteh3, Lena Båth3, May Sadik3, Peter Gjertsson3, Milan Lomsky3, Lars Edenbrandt4, David Minarik5, Anders Bjartell6. 1. Department of Translational Medicine, Division of Urological Cancer, Lund University, Malmö, Sweden Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York aseem.anand@med.lu.se. 2. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York. 3. Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden. 4. Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden Department of Clinical Physiology, Skåne University Hospital, Lund University, Malmö, Sweden. 5. Department of Radiation Physics, Skåne University Hospital, Lund University, Malmö, Sweden; and. 6. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York Department of Urology, Skåne University Hospital, Lund University, Malmö, Sweden.
Abstract
UNLABELLED: 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 (99m)Tc-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 bone(BSI) 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.
UNLABELLED: A reproducible and quantitative imaging biomarker is needed to standardize the evaluation of changes in bone scans of prostate cancerpatients 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 cancerpatients after a single 600-MBq (99m)Tc-methylene diphosphonate injection. Follow-up bone scan study: 2 follow-up bone scans of metastatic prostate cancerpatients 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 bone(BSI) 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.
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