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.
|Title of host publication||2009 22nd IEEE International Symposium on Computer-Based Medical Systems|
|Publisher||IEEE--Institute of Electrical and Electronics Engineers Inc.|
|State||Published - 2009|
|Event||22nd IEEE International Symposium on Computer-Based Medical Systems - Albuquerque, NM|
Duration: 2009 Aug 3 → 2009 Aug 4
|Conference||22nd IEEE International Symposium on Computer-Based Medical Systems|
|Period||2009/08/03 → 2009/08/04|