The UCI has responded to reports that it failed to detect riders using motors in their bikes at in early season Italian races by insisting that its method of testing for mechanical doping is “by far the most cost effective, reliable and accurate method”.
A joint investigation by French TV station Stade 2 and Italian newspaper Corriere della Sera used thermal imaging cameras which, they claimed, showed seven riders using motors in Strade Bianche and Coppi e Bartali. Five of the motors were allegedly in the seat tube of bikes, with the other two were located within the rear hubs.
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This is in contrast to the UCI’s method of detecting motors in bikes, which involves magnetic resonance testing using an iPad, the method used to find the motor in Femke Van den Driessche’s bike at the cyclocross World Championships in January.
In a statement issue in response to the report, the UCI says that after testing numerous methods for detecting so-called mechanical doping, it is confident its magnetic resonance method is the best solution currently available.
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“The UCI has been testing for technological fraud for many years and with the objective of increasing the efficiency of these tests, we have been trialling new methods of detection over the last year.
“We have looked at thermal imaging, x-ray and ultrasonic testing but by far the most cost effective, reliable and accurate method has proved to be magnetic resonance testing using software we have created in partnership with a company of specialist developers. The scanning is done with a tablet and enables an operator to test the frame and wheels of a bike in less than a minute.”
The UCI also took the opportunity to emphasise the extent of its current testing, although made no mention of any testing that it carried out at either Strade Bianche or Coppi e Bartali.
“We have tested bikes at many races this year (for example 216 at Tour of Flanders, 224 at Paris-Roubaix) and will continue to test heavily in all disciplines throughout the year. Co-operation from teams and riders as we have deployed these extensive tests has been excellent. We are confident that we now have a method of detection that is extremely efficient and easy to deploy.”