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Updated: Oct 1, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
Published on: August 16, 2020
Predicting the Prognosis of Prostate Cancer Bone Metastasis Using the Bone Scan Index and Hot Spots Calculated Using
Shigeaki Higashiyama1, Atsushi Yoshida1, Joji Kawabe1
1Department of Nuclear Medicine, Graduate School of Medicine, Osaka City University, Osaka, Japan.
Introduction:
The bone scan index (BSI) is widely used as a quantitative indicator of bone metastasis, therapeutic effect assessment, and prognosis prediction in prostate cancer. However, the BONE NAVI, which calculates BSI, only supports bone scintigraphy using Tc-99m-methylene diphosphonate. We developed the VSBONEⓇ BSI, which calculates BSI from bone scintigraphy using Tc-99m-hydroxymethylene diphosphonate (HMDP). The purpose of this study was to demonstrate that the BSI calculated using VSBONEⓇ BSI and hot spots (HS), which indicates the number of abnormal accumulations, are useful prognostic factors for patients with prostate cancer bone metastasis, similar to BONE NAVI.
Methods:
We analyzed 322 patients who underwent bone scintigraphy for prostate cancer bone metastasis at our hospital. Initial bone scintigraphy was performed using Tc-99m-HMDP. All cases were retrospectively examined for their outcome and time to the final outcome. The results obtained were compared with the BSI and HS calculated using VSBONEⓇ BSI.
Results:
When the patients were divided into two groups, HS >2 and HS ≤2, the HS ≤2 group had a significantly longer survival time (p < 0.001). In addition, when divided into two groups, BSI >0.46 and BSI ≤0.46, the survival time of the BSI ≦0.46 group was significantly longer (p < 0.001).
Conclusion:
BSI and HS obtained using VSBONEⓇ BSI may be useful as prognostic predictors, similar to those obtained using BONE NAVI.
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