The use and benefit of stereology in choosing a CT scanning protocol for the lung

Zvi Markowitz; Murray H. Loew; Joseph M. Reinhardt

doi:10.1117/12.595657

29 April 2005 The use and benefit of stereology in choosing a CT scanning protocol for the lung

Zvi Markowitz, Murray H. Loew, Joseph M. Reinhardt

Proceedings Volume 5747, Medical Imaging 2005: Image Processing; (2005) https://doi.org/10.1117/12.595657
Event: Medical Imaging, 2005, San Diego, California, United States

Abstract

When a patient is examined at different times using different protocols, how can we know whether the observed differences in the area or volume estimate are due to the patient, the protocol, or both? Specifically, we ask what is the smallest difference in lung volume that can be computed reliably when two sets of CT data are acquired by varying the number and thickness of the slices, but while holding constant the in-plane resolution. The accuracy and precision of the total lung volume estimates are calculated based on the principles of stereology using uniform design sampling. Comparisons of the lung volume estimate based on fewer slices using stereological principles are employed. A formal test made of the hypothesis that the use of fewer slices can yield satisfactory precision of the lung estimate. It is known that estimation of lung volume based on CT images is sensitive to the acquisition parameters used during scanning: dose, scan time, number of cross-sectional slices, and slice collimation. Those parameters are very different depending on the lung examination required: routine studies or high-resolution detailed studies. Thus, if different protocols are to be used confidently for volume estimation, it is important to understand the factors that influence volume estimate accuracy and to provide the associated confidence intervals for the measurements.

Citation Download Citation

Zvi Markowitz, Murray H. Loew, and Joseph M. Reinhardt "The use and benefit of stereology in choosing a CT scanning protocol for the lung", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.595657

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