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Context: The current data analysis tools in nuclear medicine have not been used to evaluate intra organ regional deposition patterns of pharmaceutical aerosols in preclinical species. Objective: This study evaluates aerosol deposition patterns as a function of particle size in rats and mice using novel image analysis techniques. Materials and Method: Mice and rats were exposed to radiolabeled polydisperse aerosols at 0.5, 1.0, 3.0, and 5.0 µm MMAD followed by SPECT/CT imaging for deposition analysis. Images were quantified for both macro deposition patterns and regional deposition analysis using the LRRI-developed Onion Model. Results: The deposition fraction in both rats and mice was shown to increase as the particle size decreased, with greater lung deposition in rats at all particle sizes. The Onion Model indicated that the smaller particle sizes resulted in increased peripheral deposition. Discussion: These data contrast the commonly used 10% deposition fraction for all aerosols between 1.0 and 5.0 µm and indicate that lung deposition fraction in this range does change with particle size. When compared to historical data, the 1.0, 3.0, and 5.0 µm particles result in similar lung deposition fractions; however, the 0.5 µm lung deposition fraction is markedly different. This is probably caused by the current aerosols that were polydisperse to reflect current pharmaceutical aerosols, while the historical data were generated with monodisperse aerosols. Conclusion: The deposition patterns of aerosols between 0.5 and 5.0 µm showed an increase in both overall and peripheral deposition as the particle size decreased. The Onion Model allows a more complex analysis of regional deposition in preclinical models. [ABSTRACT FROM AUTHOR]

Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed. [ABSTRACT FROM AUTHOR]