Optimizing 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 models 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.
You should take into account the particular disease model and the aspects of the different diseases that are being discussed, it may help in examining different aspects of the disease hence translating into a reliable imaging aspect.
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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.
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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.
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.
When studying data, parties must use “test-retest” measures to create the study’s estimates and determine possible variations to the subject, also, the selected animal model and imaging methodologies applied in the study and the type of data analysis selected may influence the overall results of the study thus the necessity of doing multiple retests to get accurate results. Such measures would work wonders for those studying the changes in drug treatments.
Discuss openly any exclusion of criteria and when/where/if to replace the subjects in the study within the same context.
Looking for high quality throughout, then do not be worries, because these terms can co-exist, but you have to do it in a careful manner where you only extract relevant information while understanding the capability of retention of the imaging.
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.