| 1. |
- Reza, Mariana, et al.
(författare)
-
Bone Scan Index as a prognostic imaging biomarker during androgen deprivation therapy.
- 2014
-
Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 4
-
Tidskriftsartikel (refereegranskat)abstract
- Bone Scan Index (BSI) is a quantitative measurement of tumour burden in the skeleton calculated from bone scan images. When analysed at the time of diagnosis, it has been shown to provide prognostic information on survival in men with metastatic prostate cancer (PCa). In this study, we evaluated the prognostic value of BSI during androgen deprivation therapy (ADT).
|
|
| 2. |
- Armstrong, Andrew J, et al.
(författare)
-
Assessment of the bone scan index in a randomized placebo-controlled trial of tasquinimod in men with metastatic castration-resistant prostate cancer (mCRPC).
- 2014
-
Ingår i: Urologic oncology. - : Elsevier BV. - 1873-2496. ; 32:8, s. 1308-1316
-
Tidskriftsartikel (refereegranskat)abstract
- Drug development and clinical decision making for patients with metastatic prostate cancer (PC) have been hindered by a lack of quantitative methods of assessing changes in bony disease burden that are associated with overall survival (OS). Bone scan index (BSI), a quantitative imaging biomarker of bone tumor burden, is prognostic in men with metastatic PC. We evaluated an automated method for BSI calculation for the association between BSI over time with clinical outcomes in a randomized double-blind trial of tasquinimod (TASQ) in men with metastatic castration-resistant PC (mCRPC).
|
|
| 3. |
- Kaboteh, Reza, et al.
(författare)
-
Bone Scan Index: a prognostic imaging biomarker for high-risk prostate cancer patients receiving primary hormonal therapy.
- 2013
-
Ingår i: EJNMMI research. - 2191-219X. ; 3:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: The objective of this study was to explore the prognostic value of the Bone Scan Index (BSI) obtained at the time of diagnosis in a group of high-risk prostate cancer patients receiving primary hormonal therapy. Methods: This was a retrospective study based on 130 consecutive prostate cancer patients at high risk, based on clinical stage (T2c/T3/T4), Gleason score (8 to 10) and prostate-specific antigen (PSA) (> 20 ng/mL), who had undergone whole-body bone scans < 3 months after diagnosis and who received primary hormonal therapy. BSI was calculated using an automated method. Cox proportional-hazards regression models were used to investigate the association between clinical stage, Gleason score, PSA, BSI and survival. Discrimination between prognostic models was assessed using the concordance index (C-index). Results: In a multivariate analysis, Gleason score (p = 0.01) and BSI (p < 0.001) were associated with survival, but clinical stage (p = 0.29) and PSA (p = 0.57) were not prognostic. The C-index increased from 0.66 to 0.71 when adding BSI to a model including clinical stage, Gleason score and PSA. The 5-year probability of survival was 55% for patients without metastases, 42% for patients with BSI < 1, 31% for patients with BSI = 1 to 5, and 0% for patients with BSI > 5. Conclusions: BSI can be used as a complement to PSA to risk-stratify high-risk prostate cancer patients at the time of diagnosis. This imaging biomarker, reflecting the extent of metastatic disease, can be of value both in clinical trials and in patient management when deciding on treatment.
|
|
| 4. |
- Kaboteh, Reza, et al.
(författare)
-
Progression of bone metastases in patients with prostate cancer - automated detection of new lesions and calculation of bone scan index
- 2013
-
Ingår i: EJNMMI Research. - 2191-219X. ; 3:1
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The objective of this study was firstly to develop and evaluate an automated method for the detection of new lesions and changes in bone scan index (BSI) in serial bone scans and secondly to evaluate the prognostic value of the method in a group of patients receiving chemotherapy.METHODS: The automated method for detection of new lesions was evaluated in a group of 266 patients using the classifications by three experienced bone scan readers as a gold standard. The prognostic value of the method was assessed in a group of 31 metastatic hormone-refractory prostate cancer patients who were receiving docetaxel. Cox proportional hazards were used to investigate the association between percentage change in BSI, number of new lesions and overall survival. Kaplan-Meier estimates of the survival function were used to indicate a significant difference between patients with an increase/decrease in BSI or those with two or more new lesions or less than two new lesions.RESULTS: The automated method detected progression defined as two or more new lesions with a sensitivity of 93% and a specificity of 87%. In the treatment group, both BSI changes and the number of new metastases were significantly associated with survival. Two-year survival for patients with increasing and decreasing BSI from baseline to follow-up scans were 18% and 57% (p = 0.03), respectively. Two-year survival for patients fulfilling and not fulfilling the criterion of two or more new lesions was 35% and 38% (n.s.), respectively.CONCLUSIONS: An automated method can be used to calculate the number of new lesions and changes in BSI in serial bone scans. These imaging biomarkers contained prognostic information in a small group of patients with prostate cancer receiving chemotherapy.
|
|
| 5. |
- Ulmert, David, et al.
(författare)
-
A novel automated platform for quantifying the extent of skeletal tumour involvement in prostate cancer patients using the bone scan index
- 2012
-
Ingår i: European Urology. - : Elsevier BV. - 0302-2838 .- 1873-7560. ; 62:1, s. 78-84
-
Tidskriftsartikel (refereegranskat)abstract
- Background: There is little consensus on a standard approach to analysing bone scan images. The Bone Scan Index (BSI) is predictive of survival in patients with progressive prostate cancer (PCa), but the popularity of this metric is hampered by the tedium of the manual calculation. Objective: Develop a fully automated method of quantifying the BSI and determining the clinical value of automated BSI measurements beyond conventional clinical and pathologic features. Design, setting, and participants: We conditioned a computer-assisted diagnosis system identifying metastatic lesions on a bone scan to automatically compute BSI measurements. A training group of 795 bone scans was used in the conditioning process. Independent validation of the method used bone scans obtained ≤3 mo from diagnosis of 384 PCa cases in two large population-based cohorts. An experienced analyser (blinded to case identity, prior BSI, and outcome) scored the BSI measurements twice. We measured prediction of outcome using pretreatment Gleason score, clinical stage, and prostate-specific antigen with models that also incorporated either manual or automated BSI measurements. Measurements: The agreement between methods was evaluated using Pearson's correlation coefficient. Discrimination between prognostic models was assessed using the concordance index (C-index). Results and limitations: Manual and automated BSI measurements were strongly correlated (ρ = 0.80), correlated more closely (ρ = 0.93) when excluding cases with BSI scores ≥10 (1.8%), and were independently associated with PCa death (p < 0.0001 for each) when added to the prediction model. Predictive accuracy of the base model (C-index: 0.768; 95% confidence interval [CI], 0.702-0.837) increased to 0.794 (95% CI, 0.727-0.860) by adding manual BSI scoring, and increased to 0.825 (95% CI, 0.754-0.881) by adding automated BSI scoring to the base model. Conclusions: Automated BSI scoring, with its 100% reproducibility, reduces turnaround time, eliminates operator-dependent subjectivity, and provides important clinical information comparable to that of manual BSI scoring. © 2012 European Association of Urology.
|
|
