When evaluating preclinical X-ray imaging systems, it can be helpful to understand the factors that make for a quality system. We've broken it down into three categories that we'll introduce here and explore further in future emails.
First, the power and sensitivity of the instrument components (i.e., source kV and detector focus) are key. X-ray components must be capable of capturing and generating high-resolution images, otherwise no amount of image optimization can compensate when detailed information is lacking from the start.

Capturing fine details enables accurate visual examination and analysis of meaningful biology, including:
There should be no compromise on a system's ability to generate images where the level of clarity needed to corroborate findings from other imaging modalities is provided.

Second, intuitive imaging tools and innovative software that complement imaging capability make for a complete imaging system, capable of generating more robust, quantitative datasets.
For example, next-generation DXA software that can simulate CCA (Carcass Composition Analysis) and NMR (Nuclear Magnetic Resonance) brings a multitude of advantages to the lab:
Finally, effective pre- and post-image processing can ensure images are automatically optimized based on the characteristic density of the sample.
Users may wish to further optimize an image based on their own specific imaging goals. A quality system offers a balance of:
System performance, software intelligence, and optimization flexibility are the three pillars of effective X-ray imaging.