Visualization of Disease Progress

In nuclear medicine, several kinds of organ function can be measured simultaneously with various radiopharmaceuticals under different conditions. This gives us useful information about the stage of disease progress if the relationship between various parameters such as metabolism, blood flow, and hemodynamics can be elucidated. Toyama et al. [116] investigated the use of agglomera-tive hierarchical and K-means clustering methods to study regional vasodila-tive and vascoconstrictive reactivity and oxygen metabolism before and after revascularization surgery in chronic occlusive cerebrovascular disease. By clustering a four-variable correlation map, whose pixel values on the X, Y, Z, and T axes represent, respectively, the resting cerebral blood flow, the hyperventila-tory response, the acetazolamide response, and regional oxygen metabolic rate, anatomically and pathophysiologically different areas can be identified showing the involvement of certain areas with varying degrees of progression between pre- and postsurgical treatment, while functional changes in the revascularized region can be depicted on the clustered brain images. It appears that clustering technique maybe useful for multivariate staging of hemodynamic deficiency in obstructive cerebrovascular disease and it also be suitable for objective representation of multiple PET physiological parameters obtained from 15O-labeled compound studies and also in brain activation studies.

The Lean, Mean Body Machine

The Lean, Mean Body Machine

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