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Optimizing Preclinical Imaging. If you want to ensure that you get some good imaging for a preclinical space, then you would need to get data across all the states, relevant data that would be used together with the tools for study to identify certain diseases and help design drugs that would counteract with the diseases very well. Prior to engaging in a study, connect preclinical imaging specialists if possible with specialists from elsewhere within the field (preclinical translation and clinical development) to evaluate the translatability of all the components of the model. 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.
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It is also not very accurate to utilize data from rodent tests and compare it with human tests due to their difference, but certain parameters – such as the results of the MRS – must be discussed and analyzed.
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More often than not imaging constitutes a single aspect of the modeling paradigm together with function, behavior, electrophysiological and histopathological aspects, well, the paradigm ought to be examined with respect to the timing and outcome of the assays relative to imaging endpoints. Always seek for data from imaging groups to determine whether there is a gap within the modeling paradigm and see if the parameters used in the study can be examined by the imaging group or those doing the study. The next step is to validate newly established paradigms to discover new methodologies and designs which are more cost-effective than those currently used for the subject, well, it is important to remember that data from one scanner and the representative data coming from the team is crucial for a study and utilizing data from a different scanner may present conflicting results. 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 be quite confusing, but they can work hand-in-hand in studies, however, it is important to use the opportunity provided by imaging time per subject to get all the right information and retain high throughput. Of course, do not forget to discuss with experts the methodologies possible for the study to retain the expectations for the study and make it easier to interpret the data coming from imaging studies.