Everything You Need to Know About Imaging Analytics For Clinical Trials

November 10, 2014
Marylyn Donahue

Applied Clinical Trials

The image acquisition and analysis components of R&D and clinical trials can be quite complex...

Editor’s Note: This article is part of a series examining popular peer-reviewed articles from years past called “Peer-Reviews Revisited: Why You Should Read Today.” You can read the other articles in this series here.


The image acquisition and analysis components of R&D and clinical trials can be quite complex, so complex that it can leave even the savviest sponsors and CROs facing the I-don’t-even-know-where–to-begin dilemma. 

And yet, a critical part of the trial protocol is the "power" variable, or the number of patients required to reach 90% to 95% confidence such that statistical significance can be reliably concluded at the end of a trial. Inevitably, in order to reach such significance in a highly variable human population the recommended number of patients in these studies can be quite large. Unfortunately, with large patients cohorts, the effort, time, and cost required to analyze and score all of the medical image data acquired during the trial can increase exponentially and pose a significant barrier in getting a new medical device or therapeutic to market. Harnessing the power of imaging analytics and incorporating them into a clinical study is not a simple task, but the benefits gained can make it a worthwhile investment.

The good news is rapid advances in image acquisition technology and continued developments in image analysis software are changing the depth and breadth of clinical research. Imaging permeates clinical and basic research across many scientific disciplines including oncology, orthopedics, ophthalmology, cardiology, and neurology, and across entities focusing on pharmaceuticals, medical device development, cell and molecular biology, tissue engineering and beyond.

The challenge for the investigator then is to stay current on the state-of-the-art in imaging and image analysis, let alone the imaging-related requirements for preclinical and clinical trials. He or she must also know how to figure in availability and, of course, cost along with other factors particular to the trial.

In this peer-reviewed article “Art & Science of Imaging Analytics” that appeared in Applied Clinical Trials in March 2013, authors Amit Vasanji and Brett A. Hoover tell you everything you need to know about the state of Imaging and guide you through the acquisition process.

Once integrated, these new approaches to imaging and analysis provide a number of other benefits as well:

  • Increased precision, throughput and objectivity of outcome metrics with automation of traditionally manual image scoring processes

  • Reduced likelihood of unexpected delays due to personnel turnover and expertise unavailability

  • Reduced cost and guesswork associated with clinical trials with more comprehensive and quantitative data and potentially smaller patient cohorts

  • Improved ability to communicate and leverage study results through quantitative data renderings and visualizations (2D or 3D)—collateral for market adoption

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