Mathematical modelling can predict adequacy rates and needle passes for fine needle aspiration cytology with rapid on-site evaluation

ObjectiveFine needle aspiration is widely used to obtain tissue samples. There are two types of sampling processes: fixed and variable. In fixed sampling, the samples are not observed for adequacy during the sampling process. In variable sampling, samples are evaluated for adequacy as they are received, and sampling is stopped as soon as an adequate sample is obtained. Each sample involves a risk of harm to the patient, and so limits are often imposed on the number of samples. The impact of such limits has not been investigated. The objective of this study was to determine the impact of sampling limits on the adequacy rate. MethodsA mathematical model of the sampling process was developed. The model describes the per-case adequacy rate in terms of the per-pass probability of success, the number of needle passes, the accuracy of the assessor and an upper limit on the number of needle passes. ResultsPer-case adequacy was positively correlated with the per-pass adequacy and the accuracy of the assessor. Sampling limits reduced the per-case adequacy rate. The impact of sampling limits decreased as the sampling limit increased. The model provides good approximations of the adequacy rate even when the constant yield assumption is violated. ConclusionMathematical modelling provides a useful approach to study sampling processes that would be difficult to evaluate with clinical studies.