title: Patient gender and radiopharmaceutical tracer is of minor importance for the interpretation of myocardial perfusion images using an artificial neural network.
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.
authors.affiliation: Department of Clinical Sciences, Malmö University Hospital, Malmö, Sweden. kristina.tagil@med.lu.se
authors.forename: Kristina
authors.initials: K
authors.lastname: Tägil
authors.forename: S
authors.initials: S
authors.lastname: Richard Underwood
authors.forename: Glyn
authors.initials: G
authors.lastname: Davies
authors.forename: Katherine A
authors.initials: KA
authors.lastname: Latus
authors.forename: Mattias
authors.initials: M
authors.lastname: Ohlsson
authors.forename: Cecilia Wallin
authors.initials: CW
authors.lastname: Götborg
authors.forename: Lars
authors.initials: L
authors.lastname: Edenbrandt
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006331:Heart Diseases / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D009943:Organophosphorus Compounds; D015609:Organotechnetium Compounds; D012372:ROC Curve; D011877:Radionuclide Imaging; D019275:Radiopharmaceuticals; D012737:Sex Factors; D017256:Technetium Tc 99m Sestamibi; D013794:Thallium Radioisotopes
chemical_list: D009943:Organophosphorus Compounds; D015609:Organotechnetium Compounds; D019275:Radiopharmaceuticals; D013794:Thallium Radioisotopes; C078700:technetium tc-99m tetrofosmin; D017256:Technetium Tc 99m Sestamibi