The Current State of Clinical Trial Imaging


by Amit Vasanji, Ph.D., and Brett A. Hoover

The addition of imaging to a clinical trial, regardless of the therapeutic area, indication or treatment, creates a layer of complexity and produces new regulatory and workflow compliance challenges. A given trial can have any number of images from a variety of modalities that require review by clinical expert readers (e.g., radiologists, pathologists, dermatologists, cardiologists), typically at multiple sites. The more variables present, the more opportunities exist for error(s), compliance mis-steps and subjective ― often biased ― data.

Fortunately, technology exists to help guide the imaging evaluation process. For example, image analysis software can be implemented to direct and guide a reader through the analysis of each imaging time point and even pre-process and segment anatomical structures of interest in lock-step with the study’s imaging charter and Independent Review Manual (IRM). This minimizes protocol deviations and ensures that each reader’s unique bias does not creep into the trial’s imaging analysis process by focusing the reader on targeted endpoints whose workflows are outlined in the trial-specific IRM. Software-guided reads are becoming an important part of trial design and the development of the trial’s IRM to help ensure all images are read uniformly and consistently, minimizing inter-/intra-reader variability and the potential for imaging-related queries. Simply stated, image analysis software brings myriad benefits to clinical studies, including accuracy, consistency, adaptability and compliance.

Imaging Analysis Software Has Tangible Benefits

Accuracy & Consistency

By designing an IRM that includes software-guided reads tailored to the trial’s imaging charter, trial leaders help enable and protect the accuracy and reproducibility (i.e., quality) of imaging endpoint data. Image readers are prompted by the software when exams are ready to be read – each reader interfacing with the software, imaging exams, and measurement and viewing tools within a unified imaging management system. And, the software requires the reader to comply with the IRM’s workflow – minimizing the introduction of reader-specific bias and unintended protocol deviations. As image observations and measurements are completed, the software captures each read (i.e., automated eCRF field population and corresponding image measurement overlays), providing a clear audit trail, eliminating eCRF transcription errors, and reducing data queries to accelerate database lock at study completion.


Very few trials run entirely smoothly. Unexpected challenges always seem to arise, such as the introduction of new or replacement readers. Utilizing image analysis software also facilitates the transition to or introduction of new clinical expert readers into the imaging evaluation process, while minimizing any potentially negative impact this might have on final data quality and consistency. And, if the new reader makes an error, the software helps identify, document and correct the anomaly ― and signal if additional IRM training and/or image evaluation workflow adjustments may be required. Software that tracks reader assessments can provide real-time rates of discordance and can be particularly helpful for studies with batched reads.


While urging trial sponsors to incorporate more rigorous, controlled imaging methods and objectives into their studies, the FDA and other regulators want to see consistency and objectivity in every facets of every clinical trial. Consistent image acquisition, processing and evaluation processes are not only important for ensuring imaging endpoint data quality, objectivity and reproducibility, they’re  also crucial for meeting regulatory standards for obtaining marketing approval. Surprisingly, many trials conducted today often have little or no traceability for imaging-related measurements. For example, reader delineation of a tumor on a lung CT is often not saved and documented. This prevents a sponsor or monitor from auditing the read consistency. More importantly, not being able to visually recall prior measurements in a longitudinal study prohibits accurate assessment of therapeutic efficacy.

Clinical trial sponsors need not worry about meeting regulators’ increasing requests for imaging data in their clinical development programs. By leveraging today’s advanced image analysis software solutions, sponsors can overcome the challenges of traditional clinical trial imaging approaches, position their trials for success and accelerate new product development.


Amit Vasanji, Ph.D. is Chief Technology Officer, Imaging at ERT

Brett A. Hoover is Product Management, Imaging at ERT