A Stochastic Interpretation of Thallium Myocardial Perfusion Scintigraphy

Abstract

A method is presented for the quantitative interpretation of Thallium-201 myocardial perfusion studies. The data are planar images collected immediately following the stress injection, and four to six hours later. Data analysis consists of preprocessing, including thresholding of the original data, and data reduction using a variant of the circumferential profile methods.

The profiles are subdivided into segments, and for each segment the difference between the norm and the actual data is computed. This difference is a quantitative symptom, whose size is assumed to be related to the probability of having the disease.

The relationship between the size of the symptom in each of nine segments (three segments/view in three views) and the probability of disease is expressed in a table in which for 30 diseases (combinations of vascular lesions), the sensitivity is described as a Gaussian function whose average and standard deviation is computed from previous validated cases.

Using an arbitrary prevalence, the post testing probability can then be computed using Bayes’ formula sequentially. The sensitivities, however, are not expressed as a binary function of the presence or absence of a symptom, but as a distribution function defined by experience.

The method assumes independence of symptoms, which cannot be disproven on the basis of the data available, and relies on the central limit theorem to assume a Gaussian distribution function.

The results are close to the reported results in other methods, but tend to be clustered around extreme probability values, suggesting some symptom interdependence.