RESUMO
This article addresses the question posed in the title by examining the effects of parameters traditionally associated with improved absolute quantitation, on the analysis of 12 acquired immune deficiency syndrome dementia complex (ADC) patients compared to a normal control group. Results are discussed within the framework of the subprofile scaling model (SSM) for analyzing patterns of regional covariation. It is demonstrated that the ability to extract measures of group discrimination and disease progression are unaffected by (1) limited improvements in image resolution, (2) the use of transmission scan smoothing, (3) the application of a scatter deconvolution correction, and (4) converting region-of-interest measurements of counts per voxel to measurements of regional CMRglc. This "robustness" of the SSM approach is partly due to the extraction of disease-related subject weights, independent of any subject's global scaling effects. It is argued that other analysis techniques that initially reduce intersubject variation (e.g., using regional ratios or normalizing by global metabolic rates before applying traditional multivariate procedures) lack analytic features that may be important to identify multidimensional, disease-related image patterns. Based on the ADC patient data, it is concluded that measures of group discrimination and disease progression will not necessarily benefit from the organization of parameters traditionally associated with improved absolute quantitation.