8 TECH OUTLOOKJune - 2019IN MY OPINIONBest Practices for Implementing Image Analysis Software in Clinical TrialsBy Amit Vasanji, Ph.D Chief Technology Officer, Imaging, ERT, Brett A. Hoover, Product Management, Imaging, ERTPharmaceutical developers are increasingly asked by regulators to include quantitative image analysis as part of the study Imaging Charter for evaluating clinical trial data. In fact, imaging in clinical trials has grown by an astonishing 700% since 2001. This phenomenal growth adds a whole new level of risk and complexity to clinical trials. From compliance challenges, site image acquisition inconsistencies, reader measurement variability, and image transfer issues to incomplete data and timeline delays, study teams need to manage and evolve their imaging strategies to position trials for success.That said, clinical trial sponsors need not fret about the inclusion of imaging in their clinical development programs. As with many of today's clinical research activities, technological advancements are often leveraged by trial sponsors to overcome these challenges and accelerate their research. Here, we present the rationale behind the utility of image analysis software and suggest best practices for sponsors looking to leverage this technology to ensure successful extraction of clinical trial quantitative imaging endpoint data.Each clinical study with a primary, secondary, and/or exploratory imaging endpoint will have many qualitative observations and quantitative measurements to sift through. The larger the study, and the more complex the therapeutic area and indication, the more sponsors and contract research organizations (CROs) risk acquiring a potentially overwhelming number of imaging data points, which can lead to problems if the study team is not well prepared.Key to preparedness is comprehensive, purposeful and well-documented validation of the image analysis software (method) to be implemented in the study. While the original vendor or developer may have previously validated the software, that doesn't necessarily mean it's the most effective tool for a particular study and associated workflows. Validating the image processing and analysis software method specifically for the study's protocol, site acquisition equipment, and imaging endpoints is necessary for two key reasons: 1) to ensure the software method is optimal for your study and will produce accurate, objective, quantitative data, and 2) to avoid regulatory and compliance hang-ups.These challenges can be addressed by following a few simple ­ yet essential ­ steps: 1. Get on the Same Page. If multiple clinical experts (e.g., readers) are providing image evaluation for a study, demand and ensure that all expert readers are utilizing the same software and methods tailored to the study's image interpretation standards (IIS). 2. Ensure Consistent Measurements. Make sure all of the expert readers are performing their image measurements and observations in the same manner. A well-written IISis a great start and will harmonize image analysis quality across all readers. Tailoring the image analysis software (and method/workflow) to the study's therapeutic area, indication and imaging endpoints will provide confidence in the image evaluation process and generate accurate, objective, complete data. Ideally, both reader and software consistency and competence should be tested periodically using a library of
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