Clinical Trials
Advantages & Benefits
Quantification increases reproducibility
The clinical endpoints used in a drug trial may be defined as the characteristics or variables that reflect how a patient feels, functions or survives. The standard endpoints used (such as pain or functionality scoring) are largely subjective and difficult to reproduce. In contrast, imaging allows the replacement of subjective evaluations such as pain scoring of the knee with an objective quantification such as knee joint space width (a measure of cartilage thickness) in millimeters measured from an x-ray image. Using quantitative imaging in this way removes subjectivity from the clinical trial process, thereby reducing the random variation in the measurement of each result.
Automation enables new measurements
Bringing automation to the image analysis task process allows a computer algorithm to measure an anatomical or pathological feature from a digital image rather than having a clinician do this with a ruler or graduated lens, usually on hardcopy film. This automation provides a degree of accuracy and reproducibility that cannot be duplicated by manual techniques, and allows multiple, laborious measurements to be made that would be uneconomic or impossible by the manual method.
New imaging measurement technologies benefit the trial process
Highly reproducible (precise) measurement of disease is of huge benefit to the pharmaceutical industry, allowing clinical trials to be carried out with a fraction of the subjects and in significantly less time. This is recognised as the key to the successful development of new image-based biomarkers. The need for reproducibility has been one of the major factors in driving the growth of Core Imaging Labs (CIL). By centralising the QA and reading of images, the reproducibility of manual image analysis can be improved significantly.
New imaging measurement technologies enable new therapies to be tested
Precise, automated measurement brings another critical benefit: it enables the development of drugs in disease areas that might otherwise be thought “too difficult”. Clinical trials in chronic diseases, such as the musculoskeletal diseases, that evolve through phases of inflammation and degeneration over many decades are often difficult and expensive. The detection of small changes in structure and function over time can change the feasibility of trials in a whole area, for example in the evaluation of osteoarthritis for which there are currently no treatments, other than surgical joint replacement, that significantly change the course of this joint disease.