Oral Presentation 24th International Conference of Racing Analysts and Veterinarians 2026

Key considerations for measurements of elements by ICP-MS in equine doping control (130476)

George Ho Man Chan 1 , April Sum Yee Wong 1 , Emmie Ngai Man Ho 1
  1. Racing Laboratory, The Hong Kong Jockey Club, Hong Kong, China

Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is widely used for the reliable detection and quantification of trace elements in equine urine and plasma. While regulatory thresholds have been established for arsenic and cobalt to control their misuses, other elements, such as lithium, nickel, and bromide, are emerging as potential performance-related substances that may require similar regulatory measures in future.  Accurate quantification is therefore vital not only for confirming analytical adverse findings when their concentrations exceed the corresponding thresholds, but also for analysing population data and establishing realistic thresholds for regulatory purposes.

Nevertheless, several analytical factors can compromise the accuracy of ICP-MS measurements. For instance, matrix effects caused by carbon content and matrix components can impact ionisation efficiency, leading to signal suppression or enhancement.  Additionally, protein binding may affect recovery if samples are deproteinised before analysis, while interferences from doubly charged ions, isobaric species and polyatomic ions can produce false signals.  Since these interferences vary by element, selecting an appropriate internal standard with a comparable signal enhancement/suppression response becomes essential to compensate for bias.

Furthermore, the choice of calibration strategy for screening and quantifying samples significantly associated with result reliability. While external calibration curves offer a straightforward approach, they may not account for unique sample matrix effects. In contrast, the standard addition method can effectively compensate for these effects, although it typically requires larger sample volumes and reduces throughput.

A comprehensive understanding of matrix effects, interference mitigation, internal standard selection, and calibration methodologies is crucial for generating robust and reliable ICP-MS data. Reliable quantification supports the establishment of future thresholds for performance-related elements in equine sports.