scholarly journals Bone scan index on bone scintigraphy and radiation therapy for bone metastases from cancers other than prostate and breast cancers: a retrospective observational study

2020 ◽  
Author(s):  
Naoya Ishibashi ◽  
Toshiya Maebayashi ◽  
Yuki Kimura ◽  
Masahiro Okada
Keyword(s):  
Prostate Cancer ◽  
Overall Survival ◽  
Radiation Therapy ◽  
Bone Metastases ◽  
Bone Scintigraphy ◽  
Bone Scan ◽  
Whole Body ◽  
Study Cohort ◽  
Breast Cancers ◽  
Bone Scan Index

Abstract Background A low bone scan index that is associated with a better prognosis in patients with bone metastases from prostate or breast cancer, the former often being osteolytic, has been established. In this study we aimed to use new automatic analysis software (VSBONE BSI; Nihon Medi-Physics, Tokyo, Japan) to investigate whether the pre-radiation therapy bone scan index, derived from bone scintigraphy images, is a prognostic indicator in patients undergoing radiation therapy for bone metastases from cancers other than breast or prostate cancer. Methods In this retrospective single institution study, we analyzed data of 51 patients who had undergone whole-body scintigraphy before receiving radiation therapy for bone metastases from cancers other than breast and prostate cancer between 2013 and 2019. Their bone metastases were classified as osteoblastic, osteolytic, or mixed and their pre-radiation bone scan indexes were automatically calculated using newly developed software (VSBONE BSI; Nihon Medi-Physics, Tokyo, Japan). Univariate and multivariate analyses were performed to identify associations between selected clinical variables and overall survival. Results We did not find a significant association between BSI and overall survival, possibly because osteolytic lesions may be underestimated by bone scan indexes. However, we did find that younger patients (aged less than the median of 66 years at the time of bone scintigraphy or of diagnosis of bone metastases) had significantly better overall survivals than older patients (P = 0.016 and P = 0.036, respectively). Additionally, bone scan indexes were significantly lower in patient with solitary or osteolytic bone metastases than in those with osteoblastic or mixed bone metastases (P = 0.035 and P = <0.001, respectively), and significantly higher in those with lung cancer than in those with other types of cancer (mean BSI 3.26% vs. 1.97%; P = 0.009). Conclusions The only significant association with survival identified in this study was for age at the time of bone scintigraphy and at time of diagnosis of bone metastases. In particular, we found no association between bone scan index and survival in the whole study cohort.

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 Kezdeti tapasztalatok a 99mTc-PSMA-SPECT/CT-vel prosztatarákos betegekben

2018 ◽  
Vol 159 (35) ◽  
pp. 1433-1440
Author(s):  
István Farkas ◽  
Zsuzsanna Besenyi ◽  
Anikó Maráz ◽  
Zoltán Bajory ◽  
András Palkó ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastases ◽  
Bone Scintigraphy ◽  
Transmembrane Protein ◽  
Tracer Uptake ◽  
Whole Body ◽  
Primary Prostate Cancer ◽  
Cancer Tumor ◽  
Visceral Metastases ◽  
Male Patients

Abstract: Introduction: The prostate-specific membrane antigen (PSMA) is a transmembrane protein, that is highly expressed on the surface of prostate cancer cells. In the last few years, several PSMA-specific ligands have been developed, that can be successfully used to detect primary prostate cancer, tumor recurrences and metastases as well. Aim: The goal of our work was to examine the clinical application of a 99mtechnetium-labeled PSMA-radiopharmaceutical as part of the routine diagnostics of prostate cancer. Method: We examined 15 male patients with verified prostate adenocarcinoma with suspicion of progression or recurrence of the disease. We performed whole-body PSMA-SPECT/CTs and multiparametric MRIs of the prostate and the pelvic regions within a week. We used 99mTc-mas3-y-nal-k(Sub-KuE) for the PSMA-SPECT scans. The images were visually evaluated by independent observers. The results were compared with the follow-up bone scintigraphies as well. Results: Twenty-two PSMA-positive lesions were found. Nine of them were localized outside, 13 were within the MRI’s field of view. From these 13 lesions, 7 matched with the SPECT/CT results and in 5 cases the MRI images showed no abnormalities. In one case, bone metastasis was suspected on the MRI scan but there was no corresponding pathological tracer uptake on the SPECT images. In two patients, none of the examinations showed signs of prostate malignancy. Four patients had PSMA-positive bone metastases. One of them had a matching PSMA/SPECT and bone scintigraphy result and in one case the PSMA examination showed metastasis in contrast to the negative bone scintigraphy. Conclusion: PSMA-SPECT/CT with 99mTc-mas3-y-nal-k(Sub-KuE) is a promising diagnostic tool. This technique is capable of visualizing bone metastases and it can detect local recurrences and visceral metastases as well. Orv Hetil. 2018; 159(35): 1433–1440.

Quantitative bone scan lesion area as an early surrogate outcome measure indicative of overall survival in metastatic castration-resistant prostate cancer.

2015 ◽  
Vol 33 (7_suppl) ◽  
pp. 179-179
Author(s):  
Matthew S. Brown ◽  
Hyun J. Kim ◽  
Gregory H. Chu ◽  
Martin Allen-Auerbach ◽  
Cheryce Fischer ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Overall Survival ◽  
Bone Scan ◽  
Post Treatment ◽  
Whole Body ◽  
Treatment Trial ◽  
Castration Resistant Prostate Cancer ◽  
Lesion Area ◽  
Surrogate Outcome ◽  
Castration Resistant

179 Background: Bone Scan Lesion Area (BSLA) is a biomarker that can be computed semi-automatically from whole-body scintigraphic imaging as a measure of overall bone tumor burden. Initial development and validation, including correlation with outcomes, was performed in trial cohorts from a single drug treatment with controls in subjects with metastatic castrate-resistant prostate cancer (CRPC). A 30% increase/decrease in BSLA was defined as progression/response on bone scan. We hypothesize that, when applied to an independent treatment trial cohort with a different mechanism of drug action, baseline BSLA and Week 12 change post-treatment are predictive of a subject's overall survival. Methods: From an anonymized imaging research database a cohort of 198 CRPC subjects was identified who enrolled in a treatment trial (127 treated, 71 placebo). This cohort was independent of those used for biomarker development and initial validation, and involved a different mechanism of drug action. Subjects underwent standard of care whole-body bone scintigraphy with 99mTc-Methyl diphosphonate (99mTc-MDP). BSLA was calculated at baseline and response at Week 12. Multivariate Cox regression was used to test whether (1) baseline BSLA, and (2) early changes in BSLA (12 weeks post treatment) were predictive of overall survival. Results: BSLA < 2000 mm2 at baseline was a prognostic factor (HR=0.6; p=0.003) and predictive of longer survival (HR=0.4; p<0.001). Subjects without PD by BSLA at Week 12 had significantly longer survival than subjects with PD: median 170 days vs. 186 days in the placebo group and 260 days vs. 392 days in the treatment group. The overall survival rates between non-PD and PD subjects were statistically different (HR=0.64, p=0.007). Conclusions: BSLA is calculated semi-automatically from bone scans and provides a quantitative and objective treatment response assessment. Baseline BSLA and early changes post treatment were found to be predictive of overall survival in patients with metastatic castration-resistant prostate cancer. BSLA has now been demonstrated to be an early surrogate outcome for overall survival in different drug treatments.

Diagnosis and semiquantification of osteonecrosis of the jaw by bone scan index on bone scintigraphy.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. e639-e639
Author(s):  
Hiroshi Yaegashi ◽  
Atsushi Mizokami ◽  
Satoru Watanabe ◽  
Kenichi Nakajima ◽  
Natsuyo Noguchi ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Early Detection ◽  
Bone Scintigraphy ◽  
Renal Cancer ◽  
Bone Scan ◽  
Osteonecrosis Of The Jaw ◽  
Bone Scan Index ◽  
Reactive Protein ◽  
Skeletal Related Event

e639 Background: Bone management is extremely important for maintaining QOL of prostate or renal cancer patients with bone metastasis. Physicians often administrate bone modifying agents (BMA), zoledronic acid or denosumab, to prevent skeletal-related event and bone pain for such patients. However, osteonecrosis of the jaw (ONJ) is one of sever adverse events of BMA (Medication-related ONJ; MRONJ). The early detection and follow-up of ONJ is extremely important issue. In order to achieve this issue, we utilized bone scintigraphy and a computer-aided diagnosis using a bone scan index (BSI). Methods: A total of 22 patients with either prostate cancer or renal cancer (27 lesions) diagnosed with MRONJ after treatment with BMA were investigated. Median age was 72.5 years (range 52-82 years). The primary disease was prostate cancer (81.8%), renal cancer (18.2%). Regarding the treatment, 86.4% of the patients were treated with bisphosphonate drugs, none in denosumab, and both in 13.6%, respectively. The median duration of medication was 33 months (range 7-70 months) by the time of MRONJ diagnosis. All patients underwent Tc-99m methylene diphosphonate bone scintigraphy. Bone uptake in the jaw was analyzed using BSI, which was calculated by BONENAVI (FUJIFILM RI Pharma, Japan; EXINIbone, EXINI Diagnostics, Sweden). Significant hot spots were manually selected according to both serial scintigraphic images and dental records, and the fraction of them to the entire skeleton was referred as BSI of the jaw (BSIJ). The level of BSIJ was evaluated in comparison with stage of ONJ and inflammation marker, C-reactive protein (CRP). Results: The median BSIJ of lesions was 0.14 (range 0.00-0.43) at the time of MRONJ diagnosis. If MRONJ is not treated appropriately, BSIJ tended to increase during treatment with BMA. When patients were classified according to their clinical stages of MRONJ, higher stage MRONJ lesions had significantly higher BSIJ (p < 0.01). In addition, BSIJ was correlated with CRP. Conclusions: Evaluation of BSIJ using BONENAVI on bone scintigraphy was helpful for early detection and follow-up of MRONJ. Furthermore, increased BSIJ on bone scintigraphy were related to CRP and stage of ONJ.

A novel artificial intelligence biomarker: Validation of the automated bone scan index (aBSI) in veterans with metastatic prostate cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e17507-e17507
Author(s):  
Vipal P. Durkal ◽  
Nicholas George Nickols ◽  
Matthew Rettig
Keyword(s):  
Prostate Cancer ◽  
Artificial Intelligence ◽  
Overall Survival ◽  
Bone Scan ◽  
Metastatic Prostate Cancer ◽  
Unmet Need ◽  
Bone Scan Index ◽  
Cancer Specific Survival ◽  
Cancer Specific Mortality ◽  
Bone Scans

e17507 Background: Prostate cancer commonly metastasizes to the bone and is associated with reduced survival, pathologic fractures and bone pain. The assessment of bone lesions is made with the technetium Tc99m(99mTc) bone scan, which relies on the subjective interpretation of radiologists and has a wide interobserver variability. There is an unmet need for a more objective and quantifiable measurement tool. Progenics Pharmaceuticals has introduced an automated bone scan index (aBSI), which employs artificial intelligence to quantify skeletal tumor burden. The automated bone scan index has been prospectively validated and is reproducible in large Phase III studies. The aBSI was validated by our study in the Veteran population at the West LA VA Medical Center. Methods: The first positive technetium 99 Tc99m bone scans of veterans diagnosed with metastatic, castration-sensitive prostate cancer were evaluated. Since 2011, a total of 107 evaluable patient bone scans were studied (n = 107). Patients with visceral metastases were excluded to evaluate only those with skeletal metastases. An automated bone scan index (aBSI) was generated for each scan using the Progenics Pharmaceuticals’ artificial intelligence platform. Multivariate analysis of aBSI with overall survival, prostate cancer specific survival, time from diagnosis to first positive bone scan, age at diagnosis, ethnicity, and Gleason score was assessed. Results: The study demonstrated a wide range of aBSI values (Range 0-16.84). Values calculated above the Median aBSI value (1.0) were prognostic for Overall Survival (p = 0.0009) and Prostate Cancer-Specific Survival (p = 0.0011). Patients in the highest quartile of aBSI values (range 5.2-16.84) showed a statistically significant Prostate Cancer-Specific Mortality (p = 0.0300) when compared to the lowest two quartiles (Range 0-1.07). The time from diagnosis to the first positive Tc99m bone scan statistically correlated with aBSI values (p = 0.0016). Multivariate analysis using Cox regression was utilized in the final statistical analysis of prostate cancer-specific mortality and overall survival. Conclusions: The automated Bone Scan Index provides a quantifiable and validated artificial intelligence biomarker to address an unmet need among metastatic prostate cancer patients. This tool was validated among Veterans, a pertinent population that is commonly affected by metastatic prostate cancer.

scholarly journals Progression of bone metastases in patients with prostate cancer - automated detection of new lesions and calculation of bone scan index

2013 ◽  
Vol 3 (1) ◽  
pp. 64 ◽  
Author(s):  
Reza Kaboteh ◽  
Peter Gjertsson ◽  
Håkan Leek ◽  
Milan Lomsky ◽  
Mattias Ohlsson ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastases ◽  
Bone Scan ◽  
Automated Detection ◽  
Bone Scan Index
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