Automated decision support for bone scintigraphy

Author

Ohlsson, Mattias ; Kaboteh, Reza ; Sadik, May ; Suurkula, Madis ; Lomsky, Milan ; Gjertsson, Peter ; Sjöstrand, Karl ; Richter, Jens ; Edenbrandt, Lars

Author_Institution

Dept. of Theor. Phys., Lund Univ., Lund, Sweden

fYear

2009

fDate

2-5 Aug. 2009

Firstpage

1

Lastpage

6

Abstract

A quantitative analysis of metastatic bone involvement can be an important prognostic indicator of survival or a tool in monitoring treatment response in patients with cancer. The purpose of this study was to develop a completely automated decision support system for whole-body bone scans using image analysis and artificial neural networks. The study population consisted of 795 whole-body bone scans. The decision support system first detects and classifies individual hotspots as being metastatic or not. A second prediction model then classifies the scan regarding metastatic disease on a patient level. The test set sensitivity and specificity was 95% and 64% respectively, corresponding to 95% area under the receiver operating characteristics curve.

Keywords

bone; cancer; decision support systems; medical computing; neural nets; orthopaedics; radioisotope imaging; sensitivity analysis; tumours; artificial neural networks; automated decision support system; bone scintigraphy; cancer treatment monitoring; metastatic bone involvement; receiver operating characteristics; whole-body bone scans; Artificial neural networks; Bones; Cancer; Decision support systems; Image analysis; Medical treatment; Metastasis; Patient monitoring; Predictive models; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems, 2009. CBMS 2009. 22nd IEEE International Symposium on

Conference_Location

Albuquerque, NM

ISSN

1063-7125

Print_ISBN

978-1-4244-4879-1

Electronic_ISBN

1063-7125

Type

conf

DOI

10.1109/CBMS.2009.5255270

Filename

5255270