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Patient gender and radiopharmaceutical tracer is of minor importance for the interpretation of myocardial perfusion images using an artificial neural network.

Tägil, Kristina LU ; Underwood, S Richard ; Davies, Glyn ; Latus, Katherine A ; Ohlsson, Mattias LU orcid ; Gotborg, Cecilia Wallin and Edenbrandt, Lars LU (2006) In Clinical Physiology and Functional Imaging 26(3). p.146-150
Abstract
The purpose of this study was to assess the influence of patient gender and choice of perfusion tracer on computer-based interpretation of myocardial perfusion images. For the image interpretation, an automated method was used based on image processing and artificial neural network techniques. A total of 1000 patients were studied, all referred to the Royal Brompton Hospital in London for myocardial perfusion scintigraphy over a period of 1 year. The patients were randomized to receive either thallium or one of the two technetium tracers, methoxyisobutylisonitrile or tetrofosmin. Artificial neural networks were trained with either mixed gender or gender-specific and mixed tracer or tracer-specific training sets of different sizes. The... (More)
The purpose of this study was to assess the influence of patient gender and choice of perfusion tracer on computer-based interpretation of myocardial perfusion images. For the image interpretation, an automated method was used based on image processing and artificial neural network techniques. A total of 1000 patients were studied, all referred to the Royal Brompton Hospital in London for myocardial perfusion scintigraphy over a period of 1 year. The patients were randomized to receive either thallium or one of the two technetium tracers, methoxyisobutylisonitrile or tetrofosmin. Artificial neural networks were trained with either mixed gender or gender-specific and mixed tracer or tracer-specific training sets of different sizes. The performance of the networks was assessed in separate test sets, with the interpretation of experienced physicians regarding the presence or absence of fixed or reversible defects in the images as the gold standard. The neural networks trained with large mixed gender training sets were as good as the networks trained with gender-specific data sets. In addition, the neural networks trained with large mixed tracer training sets were as good as or better than the networks trained with tracer-specific data sets. Our results indicate that the influence of patient gender and perfusion tracer are of minor importance for the computer-based interpretation of the myocardial perfusion images. The differences that occur can be compensated for by larger training sets. (Less)
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author
; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Clinical Physiology and Functional Imaging
volume
26
issue
3
pages
146 - 150
publisher
John Wiley and Sons
external identifiers
  • wos:000237093900002
  • pmid:16640508
  • scopus:33646045301
  • pmid:16640508
ISSN
1475-0961
DOI
10.1111/j.1475-097X.2006.00668.x
language
English
LU publication?
yes
id
eeb7c22c-3106-49f0-b242-0ee83b3be371 (old id 155716)
date added to LUP
2016-04-01 11:52:33
date last changed
2021-06-23 01:06:40
@article{eeb7c22c-3106-49f0-b242-0ee83b3be371,
  abstract     = {The purpose of this study was to assess the influence of patient gender and choice of perfusion tracer on computer-based interpretation of myocardial perfusion images. For the image interpretation, an automated method was used based on image processing and artificial neural network techniques. A total of 1000 patients were studied, all referred to the Royal Brompton Hospital in London for myocardial perfusion scintigraphy over a period of 1 year. The patients were randomized to receive either thallium or one of the two technetium tracers, methoxyisobutylisonitrile or tetrofosmin. Artificial neural networks were trained with either mixed gender or gender-specific and mixed tracer or tracer-specific training sets of different sizes. The performance of the networks was assessed in separate test sets, with the interpretation of experienced physicians regarding the presence or absence of fixed or reversible defects in the images as the gold standard. The neural networks trained with large mixed gender training sets were as good as the networks trained with gender-specific data sets. In addition, the neural networks trained with large mixed tracer training sets were as good as or better than the networks trained with tracer-specific data sets. Our results indicate that the influence of patient gender and perfusion tracer are of minor importance for the computer-based interpretation of the myocardial perfusion images. The differences that occur can be compensated for by larger training sets.},
  author       = {Tägil, Kristina and Underwood, S Richard and Davies, Glyn and Latus, Katherine A and Ohlsson, Mattias and Gotborg, Cecilia Wallin and Edenbrandt, Lars},
  issn         = {1475-0961},
  language     = {eng},
  number       = {3},
  pages        = {146--150},
  publisher    = {John Wiley and Sons},
  series       = {Clinical Physiology and Functional Imaging},
  title        = {Patient gender and radiopharmaceutical tracer is of minor importance for the interpretation of myocardial perfusion images using an artificial neural network.},
  url          = {http://dx.doi.org/10.1111/j.1475-097X.2006.00668.x},
  doi          = {10.1111/j.1475-097X.2006.00668.x},
  volume       = {26},
  year         = {2006},
}