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

Research output: Contribution to journalArticle

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.

Details

Authors
  • Reza Kaboteh
  • Peter Gjertsson
  • Håkan Leek
  • Milan Lomsky
  • Mattias Ohlsson
  • Karl Sjöstrand
  • Lars Edenbrandt
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Medical and Health Sciences
  • Cancer and Oncology

Keywords

  • Journal Article
Original languageEnglish
JournalEJNMMI Research
Volume3
Issue number1
Publication statusPublished - 2013 Aug 16
Publication categoryResearch
Peer-reviewedYes