Tips for Improving Preclinical Imaging
In order to study the nature or diseases, such as those affecting the central nervous system, medical practitioners and scientists often use preclinical models and modalities to assist in their diagnosis, frankly, medical practitioners follow certain guidelines to ensure that the imaging recorded from preclinical molecular imaging can provide a clear and interpretable data across all fields and assist drug manufacturers a better framework to work on how they can conduct their clinical trials and develop their drugs for a certain disease.
When it is possible and prior to the beginning of every study, preclinical imaging specialists from all areas of development come together to analyze the data and determine whether the models components are accurate for review.
Things to take into account during the process include the pertinence of the particular disease model and the aspects of the disease under scrutiny, well, it may be futile to examine attributes of the disease that lack translatable imaging aspect.
Once you factor in several things, then scaling from rodents to humans may not be as easy as it seems but there has to be a very straightforward translational aspects that rely on certain parameters.
Modeling paradigms must be examined in junction with the timing and the results of the relevant studies that is related to the imaging endpoints.
Whenever possible, it is critical that prior data is availed by the imaging group that shows either a discernible deficit within the modeling paradigm or that the parameters under study can actually be examined by the body conducting the study. To understand more about preclinical imaging, visit https://en.wikipedia.org/wiki/Preclinical_imaging.
So, ensure that you get all the data from the analysis team who are employing any scanner at hand because this will help you understand the methodologies in a very cost effective way, additionally, doing the same experiment with a different scanner will help you know the accurate results of the study.
The particular animal model and the specific imaging techniques applied and the data analysis selected may all have an effect on the eventual results, this becomes of utmost importance when possibly subtle changes upon drug treatment are under scrutiny.
Take the disease model and look at all the limitations and possibilities of the model which will help you find the best exclusion criteria in the study for the subject animal at hand.
These terms can definitely coexist, but it is critical to optimize time used for imaging per subject to obtain only the relevant information required with subsequent capability to retain high throughput.
Imaging studies can be difficult, however, if you are working hand in hand with experts then you have a higher and better chance to understand it through some easier and quicker interpretation.