Abstract

The purpose of this paper is to identify several important issues in the statistical analysis of serial images of active brain tumors and to offer some approaches and methods to help resolve them. Current serial brain tumor imaging is very strong on data acquisition and display yet appears weak on data analysis and inference. To help bridge the gap between certain theoretical mathematical methods for medical imaging developed over the past several decades and actual clinical practice, we describe a new physical phantom that we have designed and built for our research. We also offer some extensions of several relevant tools and principles from statistical science to the analysis of our serial medical images. Among the tools we discuss are the physical phantom itself, a simple experimental design, methods that help to separate image registration and object deformation effects, and some simple paired t-test ideas for comparison of differences in spatial point processes generated from pixelwise events in serial images. We identify several sources of extraneous variation between paired images and propose a few simple methods to control or eliminate them. Replicated experiments with our physical phantom can be used to study the properties of these methods under controlled and known conditions. Several actual patient and simulated serial SPECT images help to motivate and illustrate our techniques.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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