Towards automatic analysis of dynamic radionuclide studies using principal-components factor analysis.

A method is proposed for automatic analysis of dynamic radionuclide studies using the mathematical technique of principal-components factor analysis. This method is considered as a possible alternative to the conventional manual regions-of-interest method widely used. The method emphasises the importance of introducing a priori information into the analysis about the physiology of at least one of the functional structures in a study. Information is added by using suitable mathematical models to describe the underlying physiological processes. A single physiological factor is extracted representing the particular dynamic structure of interest. Two spaces "study space, S' and "theory space, T' are defined in the formation of the concept of intersection of spaces. A one-dimensional intersection space is computed. An example from a dynamic 99Tcm DTPA kidney study is used to demonstrate the principle inherent in the method proposed. The method requires no correction for the blood background activity, necessary when processing by the manual method. The careful isolation of the kidney by means of region of interest is not required. The method is therefore less prone to operator influence and can be automated.

[1]  J. Truijens,et al.  A quantitative theory of radioisotope renography with hippuran-131-I. , 1966, Physics in medicine and biology.

[2]  H. I. Glass,et al.  Gamma-camera renography using 123I-hippuran. , 1973, The British journal of radiology.

[3]  T. Lindmo,et al.  An examination of different mathematical models for renal function as measured by 131I-hippuran renography. , 1974, Medical physics.

[4]  W. Fair,et al.  Clinical applications of a kinetic model of hippurate distribution and renal clearance. , 1974, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[5]  J S Fleming,et al.  Deconvolution analysis of the scintillation camera renogram. , 1975, British Journal of Radiology.

[6]  D C Barber,et al.  Digital computer processing of brain scans using principal components. , 1976, Physics in medicine and biology.

[7]  P Schmidlin,et al.  Quantitative evaluation and imaging of functions using pattern recognition methods. , 1979, Physics in medicine and biology.

[8]  D. Barber The use of principal components in the quantitative analysis of gamma camera dynamic studies. , 1980, Physics in medicine and biology.