scholarly journals Prognosis of patients with prostate cancer and bone metastasis from the Japanese Prostatic Cancer Registry of Standard Hormonal and Chemotherapy Using Bone Scan Index cohort study

2021 ◽  
Author(s):  
Kenichi Nakajima ◽  
Atsushi Mizokami ◽  
Hideyasu Matsuyama ◽  
Tomohiko Ichikawa ◽  
Go Kaneko ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cohort Study ◽  
Bone Metastasis ◽  
Cancer Registry ◽  
Prostatic Cancer ◽  
Bone Scan ◽  
Bone Scan Index

Evaluation of bone metastasis of castration-resistant prostate cancer after enzalutamide and abiraterone using Bone Scan Index on bone scintigraphy.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. e596-e596
Author(s):  
Suguru Kadomoto ◽  
Kouji Izumi ◽  
Takahiro Nohara ◽  
Konaka Hiroyuki ◽  
Yoshifumi Kadono ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Bone Metastases ◽  
Bone Scintigraphy ◽  
Bone Scan ◽  
Average Rate ◽  
Castration Resistant Prostate Cancer ◽  
Bone Scan Index ◽  
Castration Resistant ◽  
Better Than

e596 Background: It was ambiguous till now to evaluate the change of bone metastasis by various treatments. To quantify the change of bone metastases by enzalutamide, abiraterone, and docetaxel for the castration-resistant prostate cancer (CRPC) with bone metastases (bmCRPC), we employed Bone Scan Index (BSI) on bone scintigraphy. Methods: We retrospectively evaluated the change of PSA and bone metastases of CRPC patients who were treated with enzalutamide (Enz), abiraterone (Abi) and/or docetaxel (DOC) in our hospital. All patients underwent Tc-99m MDP bone scintigraphy. The degree of bone metastases was analyzed using BSI, which was calculated by BONENAVI (FUJIFILM RI Pharma, Japan; EXINIbone, EXINI Diagnostics, Sweden). 19 patients were treated with enzalutamide (8 cases: pre-docetaxel, 11 cases: post-docetaxel). The median PSA of patients treated with Enz was 12.64 ng/ml (1.63-199 ng/ml). And 11 patients were treated with abiraterone (5 cases: pre-docetaxel, 6 cases: post-docetaxel). The median PSA of patients treated with Abi was 26.37 ng/ml (2.29-199 ng/ml). Results: We observed decline of PSA in 18/30 cases (9 cases: pre-DOC, 9 cases: post-DOC). Decline of PSA to 50% or more was observed in 14 cases. In contrast, decline of BSI was observed in 53.3% (16/30) cases and decline of PSA to 25% or more was observed in only 6 cases. BSI decreased in 84.6% (11/13) of pre-DOC setting and in 29.4% (5/17) of post-DOC setting indicating that change of BSI was poor in post-DOC setting. However, DOC had already decreased BSI in 91.7% (11/12) before Abi or Enz treatment. Moreover, the average rate of BSI decline in the patients that BSI decreased by DOC was better than the patients that BSI decreased by Abi/Enz (-48.46% vs -28.56%). Finally, although the rate of BSI change by Enz was weakly correlated with the rate of PSA decline (y = 0.3906x + 25.35, R2 = 0.3423), BSI continued to increase in four cases in spite of PSA decline. Conclusions: BSI using BONENAVI on bone scintigraphy was helpful for evaluating the effectiveness of treatment and following-up of bmCRPC.

Study of the Usefulness of Bone Scan Index Calculated From 99m-Technetium-Hydroxymethylene Diphosphonate (99mtc-HMDP) Bone Scintigraphy for Bone Metastases from Prostate Cancer Using Deep Learning Algorithms

2020 ◽  
Vol 16 ◽  
Author(s):  
Shigeaki Higashiyama ◽  
Atsushi Yoshida ◽  
Joji Kawabe
Keyword(s):  
Prostate Cancer ◽  
Deep Learning ◽  
Bone Metastasis ◽  
Bone Metastases ◽  
Bone Scintigraphy ◽  
Bone Scan ◽  
Learning Algorithms ◽  
Bone Imaging ◽  
Bone Scan Index ◽  
Metabolic Biomarkers

Background: BSI calculated from bone scintigraphy using 99mtechnetium-methylene diphosphonate (99mTc-MDP) is used as a quantitative indicator of metastatic bone involvement in bone metastasis diagnosis, therapeutic effect assessment, and prognosis prediction. However, the BONE NAVI, which calculates BSI, only supports bone scintigraphy using 99mTc-MDP. Aims: We developed a method in collaboration with the Tokyo University of Agriculture and Technology to calculate bone scan index (BSI) employing deep learning algorithms with bone scintigraphy images using 99mtechnetiumhydroxymethylene diphosphonate (99mTc-HMDP). We used a convolutional neural network (CNN) enabling the simultaneous processing of anterior and posterior bone scintigraphy images named CNNapis. Objectives: The purpose of this study is to investigate the usefulness of the BSI calculated by CNNapis as bone imaging and bone metabolic biomarkers in patients with bone metastases from prostate cancer. Methods: At our hospital, 121 bone scintigraphy scans using 99mTc-HMDP were performed and analyzed to examine bone metastases from prostate cancer, revealing the abnormal accumulation of radioisotope (RI) at bone metastasis sites. Blood tests for serum prostate-specific antigen (PSA) and alkaline phosphatase (ALP) were performed concurrently. BSI values calculated by CNNapis were used to quantify the metastatic bone tumor involvement. Correlations between BSI and PSA and between BSI and ALP were calculated. Subjects were divided into four groups by BSI values (Group 1, 0 to <1; Group 2, 1 to <3; Group 3, 3 to <10; Group 4, >10), and the PSA and ALP values in each group were statistically compared. Results: Patients diagnosed with bone metastases after bone scintigraphy were also diagnosed with bone metastases using CNNapis. BSI corresponding to the range of abnormal RI accumulation was calculated. PSA and BSI (r = 0.2791) and ALP and BSI (r = 0.6814) correlated positively. Significant intergroup differences in PSA between Groups 1 and 2, Groups 1 and 4, Groups 2 and 3, and Groups 3 and 4 and in ALP between Groups 1 and 4, Groups 2 and 4, and Groups 3 and 4 were found. Conclusion : BSI calculated using CNNapis correlated with ALP and PSA values and is useful as bone imaging and bone metabolic biomarkers, indicative of the activity and spread of bone metastases from prostate cancer.

scholarly journals Bone scan index: A new biomarker of bone metastasis in patients with prostate cancer

2017 ◽  
Vol 24 (9) ◽  
pp. 668-673 ◽  
Author(s):  
Kenichi Nakajima ◽  
Lars Edenbrandt ◽  
Atsushi Mizokami
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Bone Scan ◽  
Bone Scan Index

Comparison of 18F-Fluciclovine PET/CT and 99mTc-MDP bone scan in detection of bone metastasis in prostate cancer

2019 ◽  
Vol 40 (9) ◽  
pp. 940-946 ◽  
Author(s):  
Bo Chen ◽  
Peng Wei ◽  
Homer A. Macapinlac ◽  
Yang Lu
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Bone Scan ◽  
Pet Ct

scholarly journals Total-Body 68Ga-PSMA-11 PET/CT for Bone Metastasis Detection in Prostate Cancer Patients: Potential Impact on Bone Scan Guidelines

2019 ◽  
Vol 61 (3) ◽  
pp. 405-411 ◽  
Author(s):  
Kelsey L. Pomykala ◽  
Johannes Czernin ◽  
Tristan R. Grogan ◽  
Wesley R. Armstrong ◽  
John Williams ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Cancer Patients ◽  
Bone Scan ◽  
Pet Ct ◽  
Potential Impact ◽  
Total Body
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