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Mattias Ohlsson

Mattias Ohlsson

Professor

Mattias Ohlsson

Clinical data do not improve artificial neural network interpretation of myocardial perfusion scintigraphy.

Author

  • Peter Gjertsson
  • Lena Johansson
  • Milan Lomsky
  • Mattias Ohlsson
  • Stephen Richard Underwood
  • Lars Edenbrandt

Summary, in English

Artificial neural networks interpretation of myocardial perfusion scintigraphy (MPS) has so far been based on image data alone. Physicians reporting MPS often combine image and clinical data. The aim was to evaluate whether neural network interpretation would be improved by adding clinical data to image data. Four hundred and eighteen patients were used for training and 532 patients for testing the neural networks. First, the network was trained with image data alone and thereafter with image data in combination with clinical parameters (age, gender, previous infarction, percutaneous coronary intervention, coronary artery bypass grafting, typical chest pain, present smoker, hypertension, hyperlipidaemia, diabetes, peripheral vascular disease and positive family history). Expert interpretation was used as gold standard. Receiver operating characteristic (ROC) curves were calculated, and the ROC areas for the networks trained with and without clinical data were compared for the diagnosis of myocardial infarction and ischaemia. There was no statistically significant difference in ROC area for the diagnosis of myocardial infarction between the neural network trained with the combination of clinical and image data (95·8%) and with image data alone (95·2%). For the diagnosis of ischaemia, there was no statistically significant difference in ROC area between the neural network trained with the combination of clinical and image data (87·9%) and with image data alone (88·0%). Neural network interpretation of MPS is not improved when clinical data are added to perfusion and functional data. One reason for this could be that experts base their interpretations of MPS mainly on the images and to a lesser degree on clinical data.

Department/s

  • Computational Biology and Biological Physics
  • Nuclear medicine, Malmö

Publishing year

2011

Language

English

Pages

240-245

Publication/Series

Clinical Physiology and Functional Imaging

Volume

31

Issue

3

Document type

Journal article

Publisher

John Wiley and Sons

Topic

  • Physiology

Status

Published

Research group

  • Nuclear medicine, Malmö

ISBN/ISSN/Other

  • ISSN: 1475-0961