Objectives: Bone scan index (BSI) is a reproducible, quantitative expression of tumor burden seen on bone scintigraphy. The objective of this study was to compare changes between serial scans of prostate cancer patients with bone metastasis, as assessed by visual analysis, lesion number, and automated BSI software.

Methods: We retrospectively reviewed 283 bone scans from 29 prostate cancer patients. Visual analysis for response assessment was done on a 4-point scale: 1 progression, 2 indeterminate (new uptake for which metastasis cannot be excluded nor confirmed), 3 stable disease, 4 regression. BSI and lesion number were calculated using EXINI Bone ^BSI. ΔBSI and Δlesion number were taken as the difference between two consecutive scans. The difference in ΔBSI and Δlesion number was evaluated by the Mann Whitney U-test. Survival differences according to response as assessed by the three methods were estimated by the Kaplan-Meier method. Regression analysis was done for survival with ΔBSI and Δlesion number.

Results: The mean BSI and lesion number at initial diagnosis of bone metastasis with a previously negative scan was 0.33 and 4, respectively. Four of the 17 cases with indeterminate visual response were true positive on follow-up, and had a significantly higher mean ΔBSI (p=0.030) and Δlesion number (p=0.004) than the false positive. For patients progressing by visual analysis, the mean ΔBSI for was significantly higher than for stable disease (see table). In all three methods of response assessment, Kaplan-Meier curves showed shorter survival for progression than stable disease, with the greatest difference being by ΔBSI (p=0.022). Regression modeling with ΔBSI for survival was also statistically significant (p=0.029).

Conclusion: BSI is a promising biomarker for disease progression or treatment response in prostate cancer patients with bone metastasis.

Objectives: Bone scan index (BSI), a method of expressing the tumor burden in bone as a percent of the total skeletal mass, was developed as a quantitative tool to improve the interpretability and clinical relevance of bone scintigraphy. Baseline BSI has already been shown to be an independent prognostic factor for overall survival. The objective of this study was to evaluate whether BSI from scans throughout management are also predictive for survival and to compare BSI to prostate-specific antigen (PSA) as an outcome measure in prostate cancer patients with bone metastasis.

Methods: We retrospectively reviewed 283 bone scans from 29 prostate cancer patients. BSI and the lesion number were calculated using EXINI Bone ^BSI, and correlated with PSA and survival. Predictive modeling with these biomarkers was performed by Cox regression, with survival defined from time of each bone scan to death, or censored to the date of last follow-up. BSI values were dichotomized at the median, and survival distribution was estimated by the Kaplan-Meier method.

Results: BSI correlated inversely with survival in the subset of pretreatment baseline scans (ρ=-.404, p=0.030) and the overall series including subsequent in-treatment and posttreatment scans (ρ=-.362, p<0.001). BSI moderately correlated with PSA (ρ=0.592, p<0.001), while lesion number did not (p=0.374). The only statistically significant predictive variable on forward conditional Cox regression was BSI, with a relative risk of 1.089 (p<0.001). Kaplan-Meier curves for BSI dichotomized at the median 0.38 showed a significant difference between the two groups (p<0.001), with higher BSI showing shorter survival (mean survival 67.84 months vs 49.65 months for BSI<0.38 and >=0.38, respectively).

Conclusion: As with BSI from pretreatment scans, scans throughout management can be used to predict survival in prostate cancer patients with bone metastasis, and may have higher prognostic value than PSA.

Background: mCRPC is a bone dominant lethal disease. A validated endpoint in mCRPC trials is bone scan progression, which is semi-quantitative and rely on the appearance of new lesions as proposed by the PCWG. The validated automated bone scan index (BSI) quantifies the bone tumor burden as the fraction of total skeletal weight. To build on the current definition of disease progression, we sought to compare the association of time to progression with overall survival (OS) using PCWG criteria and BSI increase. Methods: mCRPC patients (pts) enrolled on trials of agents targeting androgen-receptor (AR) were assessed. Pts were required to have a raw bone scan image for BSI analysis concurrent with disease assessments. The EXINI automated computing platform generated the BSI values. Thresholds for the absolute and relative increase in BSI from 1st follow-up (≤12 weeks) were explored for the time to BSI progression. The association with survival time was computed for each threshold defined time to BSI progression. Kendall’s Tau, derived from the Clayton copula, was used to associate time to BSI progression with survival time, where both endpoints may be censored. Results: A total of 257 pts were assessed, of whom 169 had raw bone scans images needed for the BSI analysis. 90 pts (53%) met progression by PCWG criteria, the association between the time to PCWG progression and OS was 0.52. The association between time to BSI progression and OS was comparable to the PCWG progression when the absolute increase in BSI was 0.6 or more (table below). Conclusions: Progression in bone can be expressed as a single quantitative metric that describes the increase in total disease burden while retaining the same association that PCWG has with OS. These data represent the first steps to a quantitative expression of bone disease progression as a clinical trials endpoint.

Background: Quantitative measures of metastatic bone disease are needed in men with mCRPC. We recently demonstrated the validity/reproducibility of a computational approach to bone scan imaging that employs artificial intelligence called the automated BSI (aBSI), which quantifies the percent of skeletal mass involved by cancer. We aimed to extend the prognostic validation of aBSI in a multinational prospective phase 3 clinical study of men with bone-metastatic CRPC. Methods: Whole-body bone scans were acquired at screening in a placebo-controlled phase 3 trial of men with mCRPC and bone metastases and treated with tasquinimod/placebo (n = 1,245). The prospective aBSI biomarker analysis plan was locked in Sept 2014 prior to treatment unblinding. All scans generated at 241 trial sites in 37 countries were assessed for image quality and analyzed using the EXINI Bone ^BSI v.2 software and were blindly associated with outcomes. Baseline aBSI was evaluated for its independent prognostic association with overall survival (OS), radiographic progression-free survival (rPFS), and symptomatic skeletal related events (SSEs). Results: The aBSI-population (721 pts) was representative of the entire trial population based on patient characteristics at screening and OS outcomes. Median aBSI was 1.07 (SE 0.05). The aBSI-population was divided into quartiles (n = 180-181) with aBSI-levels of 0 - 0.3 (Q1); > 0.3 - 1.1 (Q2); > 1.1 - 4.0 (Q3); and > 4.0 (Q4) and median OS ranging from 35 months (Q1) to 13 mo (Q4) (p < 0.0001). Baseline aBSI was significantly associated with OS (HR 1.2 per doubling of BSI; p < 0.0001) and remained independently associated with OS after adjustment for treatment, PSA, CRP, LDH and albumin. Baseline aBSI was also strongly associated with rPFS (p = 0.0005), time to symptomatic progression (p < 0.0001), and time to SSE (p = 0.001). Conclusions: This analysis represents the first phase 3 evaluation of aBSI as a clinically validated prognostic biomarker for OS, rPFS, and SSEs in men with bone-metastatic CRPC, providing independent prognostic information over commonly measured clinical characteristics. 

Background: The Zeus/SPCG11 study is a randomized controlled clinical trial with the aim to assess the efficacy of zoledronic acid (ZA) in preventing bone metastases in high-risk prostate cancer (PCa) patients. Bone Scan Index (BSI) reflects the tumour burden in bone calculated from bone scintigraphy, and has recently been validated as an imaging biomarker in metastatic PCa patients. The purpose of this study was to investigate if change in BSI during treatment may serve as a useful imaging biomarker to predict clinical outcome in the Zeus/SPCG11 study population. Methods: We retrospectively selected as our BSI-study cohort all patients with bone scan image data of sufficient quality to allow for both baseline and 48-months follow-up BSI-assessments. BSI data was obtained by using the automated quantification software EXINI Bone ^BSI, in a blind fashion, without knowledge of any clinical data or treatment randomization. Clinical data on age, overall survival (OS) and prostate-specific antigen (PSA) concentration in blood at baseline and upon follow-up was collected separately. Association between clinical data and BSI change during treatment was evaluated using Cox proportional-hazards regression models, Kaplan-Meier estimates of the survival function and Log rank test. Discrimination between prognostic variables was assessed using the concordance index (C-index). Results: The 176 patients who fulfilled the inclusion criteria presented showed baseline characteristics similar to those of the final total Zeus/SPCG11 study population (N = 1,433)(p= 0.83). In our BSI-study cohort (N = 176), patients with a BSI change < 0.3 had a significantly longer median survival time compared to patients with BSI increase of > 0.3 (32.3 months and 18.2 months respectively) (p < 0.001). In the Cox analysis BSI change from baseline to follow-up was significantly associated with OS (p < 0.01 and C-index = 0.6) while age and PSA change were not significantly associated with OS. Conclusions: BSI change during treatment was associated with OS in high-risk PCa patients from the Zeus/SPCG11 study. BSI may be a useful imaging biomarker in future clinical trials involving PCa patients with bone metastases.

Aim: Evaluation of progression and therapy response is needed to improve and optimize individualized therapy management of patients suffering from metastatic castration resistant prostate cancer (mCRPC). However, there is a lack of consistent data for therapy response assessment to optimize treatment. Treatment decisions based on PSA-value alone are inadequate, therefore other clinical and radiologic criteria indicating disease progression should be taken into account. Therefore we evaluated the utility of an automatic bone scan index (aBSI) to assess response to Ra-223-therapy in patients with mCRPS with bone metastases, in comparison to established response markers, e.g. number of lesions or PSA. Materials and Methods: Nine patients with clinical progress of bone metastases from mCRPC, who underwent 6 cycles of Ra-223-therapy were retrospectively included in this pilot study. Whole-body bone scans with Tc-99m-DPD were performed and blood samples were taken approximately four weeks before and after 6 cylces of Ra-223-therapy. The aBSI was calculated using EXINIboneBSI (EXINI Diagnostics AB, Sweden). Changes of aBSI, number of lesions, levels of PSA and alkaline phosphatase (AP) were compared pre- and post-therapy. Correlation between aBSI and PSA as well as AP was evaluated by calculation of Pearson?s correlation coefficient. Results: Therapy response / progress was defined as decreasing / increasing aBSI, less / more than two new lesions in whole-body bone scan and lower / higher PSA level compared to baseline. Response was found in 2/9 (22 %), stable disease in 1/9 (11%) and progress in 6/9 (67%) of the patients. The median aBSI was 2,67?2,62 at baseline scan and 2,71?2,73 at control scan after 6 cycles of therapy. The median number of lesions was 18?40 and 22?42, respectively. The median PSA level was 38,5?339,19 and 46,7?364,63, respectively. Median alkaline phosphatase level was 1,28?1,87 and 1,23?2,18, respectively. The ∆aBSI (mean 0,04?0,86) showed a statistically significant correlation with ∆PSA (mean 60,79?117,2; r = 0,76, p = 0,014) and weaker one with ∆AP (mean -0,28?1,86; r=0,59, p = 0,093). Limitations are the small patient sample-size, the retrospective analysis and high inter-individual variability. Conclusions: The aBSI might be a useful and promising data analysis tool for the assessment of therapy response to Ra-223. Studies in larger cohorts are needed.

AIM: We purchased a CAD software, commercially available, in order to help to detect metastases in bone scans. This retrospective study investigates lesion detection performance of such CAD tool as compared to nuclear physician diagnosis. MATERIAL & METHODS: In 2013, 245 patients (112 F/133 M) with different types of cancer underwent one to several whole-body (WB) bone scans (388). 14832 lesions were detected by the CAD system on anterior and posterior views using an intermediate sensitivity among 3 levels (low, intermediate, high). Trained physicians were able to alter CAD decision (confirmed by SPECT/CT) for each lesion from high to low (HL) and low to high (LH) metastatic probability. XML files stored by CAD software were analyzed to extract relevant informations such as skeletal localization, number of lesions, maximum counts per lesion. RESULTS: The number of examinations was 179 (151 resp.) for prostate (breast resp.). The 58 remaining examinations were performed for other types of cancer. Number of metastases was 3903 for prostate cancer and 2082 for breast cancer. Prostate cancer metastases were mostly located in ribs, thoracic spine (TS) and pelvis (21.7, 10.9 and 9.7 % resp.) whereas in TS, pelvis, skull and lumbar spine (LS) for breast cancer (21.0, 18.1, 12.9 and 11.3% resp.). Whatever the pathology, HL and LH changes were 11.8% of detected lesions and the most frequent modifications appeared in TS, pelvis, skull and LS (17, 15, 13 and 9% resp.). For the most frequent examinations i.e. breast (prostate resp.) cancer, overall changes were 5.5% (3.7% resp.) of detected lesions. In breast cancer, the most frequent lesion alterations were respectively 8.7, 7.8, 7.2 and 6.6% for skull, pelvis, TS and ribs. The same analysis performed for prostate cancer lead to 8.2, 7.2, 3.8 and 3.1% for ribs, TS, skull and pelvis respectively. The mean of maximum counts in lesions manually changed by physicians was 25% lower than the respective value in lesions automatically labeled by CAD system as highly metastatic (Wilcoxon-test p < 10e-6). CONCLUSION: This study showed that CAD system is an effective tool for physicians in their daily work as less than 12% of lesions were falsely identified. Some improvements would be helpful e.g. labeling unlabeled foci, as some ribs lesions, in breast cancer especially, were not identified at all, making any changes impossible. Maybe, a learning phase based on breast cancer WB scans would have helped the CAD system to perform better.

Background: A computer-aided diagnosis system for bone scintigraphy using semiquantitative index [Bone Scan Index (BSI)] has been used to measure the tumor burden of bone metastases. We examined relationships of BSI, bone turnover marker, and prostate-specific antigen (PSA)-progression free survival (PFS) after docetaxel-treatment for castration resistant prostate cancer (CRPC) with bone metastasis.Methods: Sixteen CRPC patients with bone metastases (median age 72, range 52 to 82) were treated with docetaxel. We evaluated bone metastasis by bone scintigraphy before or around six months after docetaxel-treatment retrospectively. BSI was automatically calculated by BONENAVI software version 1 (FUJIFILM RI Pharma, Co. Ltd., Tokyo, Japan; Exini Bone, Exini Diagnostics, Sweden). Serum PSA, bone alkaline phosphatase (BAP), carboxyterminal telopeptide of type I collagen (I-CTP) were examined every months. PSA-PFS was evaluated after docetaxel-treatment and compared with baseline of BSI, BAP, I-CTP, and change of these value after treatment. Overall survival (OS) was also evaluated by these markers. The rate of patients with PFS and OS was estimated by the Kaplan-Meier method.Results: Baseline of BSI, the serum BAP, and I-CTP before docetaxel-treatment did not affect PFS. The change of BAP and I-CTP by the docetaxel-treatment also did not affect PFS. Only the change of BSI affected PFS and the median PFS of CRPC patients with increased BSI and decreased BSI was 5.5 months and 10 months, respectively (p=0.026). Although OS showed a longer tendency in CRPC patients with decreased BSI than with increased BSI, there was not the significant difference (p=0.12).Conclusions: The change of BSI affected PFS in CRPC patients with bone metastases. Bone scan and its evaluation with BONENAVI was effective to monitor the clinical course during chemotherapy.