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Mattias Ohlsson

Mattias Ohlsson

Professor

Mattias Ohlsson

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

Author

  • Reza Kaboteh
  • Peter Gjertsson
  • Håkan Leek
  • Milan Lomsky
  • Mattias Ohlsson
  • Karl Sjöstrand
  • Lars Edenbrandt

Summary, in English

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.

Department/s

  • Department of Clinical Sciences, Malmö
  • Computational Biology and Biological Physics
  • Department of Astronomy and Theoretical Physics
  • Artificial Intelligence in CardioThoracic Sciences (AICTS)
  • Nuclear medicine, Malmö

Publishing year

2013-08-16

Language

English

Publication/Series

EJNMMI Research

Volume

3

Issue

1

Document type

Journal article

Publisher

BioMed Central (BMC)

Topic

  • Medical and Health Sciences
  • Cancer and Oncology

Keywords

  • Journal Article

Status

Published

Research group

  • Artificial Intelligence in CardioThoracic Sciences (AICTS)
  • Nuclear medicine, Malmö

ISBN/ISSN/Other

  • ISSN: 2191-219X