The analytic and functional accuracy of a video densitometry system.
Applications using radiotracers and quantitative film autoradiography are increasing dramatically in the neurosciences. Microcomputer-based image analyzing systems with video input have been developed to provide rapid quantification of autoradiographic images on relatively inexpensive systems. However, there has been some question as to whether such systems can reliably produce high levels of densitometric accuracy, especially when compared to mechanical scanners which are standard in research requiring extreme fidelity of measurement. We report methods and results from tests done to determine the analytical and functional accuracy of the Drexel Unix-based Microcomputer image Analysis System (DUMAS), which is a video densitometric system designed to provide quantitative data from autoradiograms. Analytical accuracy was determined by measuring photometric uniformity, the optical density transfer function, temporal stability, geometric uniformity, and flare. In addition, data are provided on the resolution of the system at several magnifications. Functional accuracy, the accuracy of the estimates of mean isotope concentrations in diverse neural structures, was determined by comparing the results obtained on the DUMAS system with the results from analyzing the same [14C]2-deoxyglucose images with two different Optronics P1000 systems. Our results show that, provided care is taken in the choice of a camera and a light source, the analytic accuracy of videodensitometry is high. Its functional accuracy is also high in that measurements of radioisotope concentrations in diverse neural structures made on the DUMAS system agree closely with the measurements from a properly adjusted Optronics P1000 system. The rapidity and economy of videodensitometry is not, therefore, obtained at the sacrifice of densitometric accuracy. Given adequately tested hardware and provided that suitable checks on instrument calibration and adjustment are made, the errors in autoradiographic quantification due to the image analyzing system itself are minor in comparison to other sources of error, including, as we show, variations in the user's delineation of the boundaries of neural structures.
McEachron
D L
DL
Department of Bioscience, Drexel University, Philadelphia, PA 19104.
Gallistel
C R
CR
Eilbert
J L
JL
Tretiak
O J
OJ
D001345:Autoradiography; D003720:Densitometry / Q000379:methods; D005069:Evaluation Studies as Topic; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D009488:Neurosciences / Q000295:instrumentation / Q000379:methods*; D014741:Video Recording / Q000295:instrumentation / Q000379:methods*