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Träfflista för sökning "WFRF:(Evans David M.) ;srt2:(2010-2014);srt2:(2012)"

Sökning: WFRF:(Evans David M.) > (2010-2014) > (2012)

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11.
  • 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.
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12.
  • Ulmert, David, et al. (författare)
  • Imaging androgen receptor signaling with a radiotracer targeting free prostate-specific antigen.
  • 2012
  • Ingår i: Cancer Discovery. - 2159-8274. ; 2:4, s. 320-327
  • Tidskriftsartikel (refereegranskat)abstract
    • Despite intense efforts to develop radiotracers to detect cancers or monitor treatment response, few are widely used as a result of challenges with demonstrating clear clinical use. We reasoned that a radiotracer targeting a validated clinical biomarker could more clearly assess the advantages of imaging cancer. The virtues and shortcomings of measuring secreted prostate-specific antigen (PSA), an androgen receptor (AR) target gene, in patients with prostate cancer are well documented, making it a logical candidate for assessing whether a radiotracer can reveal new (and useful) information beyond that conferred by serum PSA. Therefore, we developed (89)Zr-labeled 5A10, a novel radiotracer that targets "free" PSA. (89)Zr-5A10 localizes in an AR-dependent manner in vivo to models of castration-resistant prostate cancer, a disease state in which serum PSA may not reflect clinical outcomes. Finally, we demonstrate that (89)Zr-5A10 can detect osseous prostate cancer lesions, a context where bone scans fail to discriminate malignant and nonmalignant signals.
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  • Resultat 11-12 av 12
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