Julie Fitzpatrick has been working as a diagnostic radiographer for 24 years and engages in the qualification of imaging centers globally through training of personnel and analysis of imaging datasets. We have formulated four questions for a quick interview to take advantage of her tremendous work experience.
Christoph Bamet (CB): You have been involved in staff training for a long time. It is a difficult task, as amongst radiographers one finds a big variation in capabilities and training. Yet all their images need to be useful for the studies. What are the measures you take on the training side?
Julie Fitzpatrick (JF): I have been a radiographer for nearly 24 years, working in both clinical and most recently research environments. I have been fortunate to work with some amazing people who have taught, guided and mentored me and I am forever grateful to them. I have unfortunately also worked with some difficult individuals, but I have learned much from these experiences too.
Part of my job at the moment is to train staff and ensure standardization in the imaging component of clinical drugs trials. As you have already highlighted there are huge differences in training and ability of my fellow imaging professionals and this is a challenge. So, firstly I will always try to engage them in a ‘getting to know you’ conversation. Introducing myself and talking about my background, asking about theirs and just generally ‘breaking the ice’.
Then I move onto how much information has been shared with them so far. It is surprising how often that little has been conveyed. Many people tell me they have just been told to turn up ‘for training’. This can lead to feelings of frustration and resentment so I try to dissipate this and start with an overview of the study. Giving an understanding of where they fit into any study/project often helps get people on board.
And what can technology do to bridge the disparities? There are many options available but is dependent on the facilities at ones disposal. For example, is there an internet connection and what options are there to display presentations? I often perform remote trainings using conferencing websites, i.e. WebEx. This means that I can display a presentation while getting immediate reaction, feedback and take questions. Thus, I can concentrate and emphasize the points that need more in-depth explanation.
CB: For its use in studies, MR image quality is often an issue. How do you decide what data is discarded and what can be used for the analysis?
JF: This would very much depend on the study and whether one is collecting quantitative or qualitative data. What is the objective of including imaging in the study and this will guide where the threshold for the data to be included or discarded is set.
It is essential that this be established at the very beginning of any study. It is the same for clinical imaging, what is the question that needs to be answered? With this in mind a range of quality may be acceptable or a very narrow one.
CB: In MR data analysis, more and more often different contrasts need to be brought together to be analyzed (e.g. anatomical images and functional ones). Is the lack of geometrical incongruence between them an issue?
JF: Once again, it depends on the study. But, if we are referring to localizing signal from BOLD images then this is an issue and can have consequences for the accuracy of a study and also planning surgical interventions on patients.
Here is where standardizing the acquisition parameters is imperative. A robust protocol needs to be initiated and adhered too. A system of quality control will also need to be founded in order to ratify that data sets are acceptable.
CB: At what step in the image acquisition process would you like to see advances in MR image quality assurance most?
JF: For me, it starts before any images are even acquired with robust preventative mainte-nance/quality assurance program. Regular checks on performance along with a service contract and good record keeping will insure optimum and consistent image output and hopefully identify any issues before they become problems. I cannot emphasize this strongly enough.
My next choice would be coil construction. I would like to see advances in how coils adapt to individual body habitus. A good example would be the GE adaptive imaging receive (AIR) technology. Although I do not have any experience of this very new technology I hope that this will improve quality by enabling increased signal to noise ratio (SNR) and contrast to noise ratio (CNR) as the coil can be positioned in close proximity to the area under investigation.
Another benefit of improved coil design will be more people being able to take part in MRI studies. A more flexible design will improve comfort for participants and hopefully they will be able to undergo imaging and remain motionless for longer periods.