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3 Reasons Why You Should Perform Quality Control in Centralized Imaging

Today, more and more clinical trials are being conducted internationally, generating a vast amount of imaging data that can be used and analyzed for various purposes. For any research team centralizing medical images in clinical trials, performing real-time quality control is a valuable asset for many reasons. By centralizing medical imaging, sponsors standardize imaging quality, control the integrity of the imaging data, and ensure that investigator sites have followed the provided imaging acquisition guidelines. Such guidelines are in place to ensure readers have access to high-quality medical imaging as well as clear and bias-free datasets. For centralized medical imaging, quality control measures exist to facilitate accuracy and consistency of image quality, maintain compliance with regulatory standards, and optimize the workflow and overall efficiency of the trial.

This blog will explore three reasons why sponsors should prioritize quality control of their medical imaging data as early as possible in the clinical trial timeline.

#1. Accuracy and Consistency 

In clinical trials, real time quality control is implemented to reduce imaging errors and enhance imaging data quality. Typically, the individual responsible for quality control will open the images using a viewing software to ensure that the datasets received contain all the data relevant to the clinical trial. This oversight ensures central readers produce optimal reading results. Then, the individual will perform visual and data checks to guarantee that every image submitted was acquired according to the imaging acquisition guidelines.  

Quality control is vital for the improvement of imaging data analysis long term and for generating valuable imaging endpoints. In oncology trials, for example, images are reviewed against a variety of parameters; anatomical coverage, contrast enhancement, scan parameters, and field of view. The quality controller will review images using a “checklist” of items designed for the study by an imaging specialist or quality control expert. Quality control also involves regular checks on equipment calibration, image resolution, and processing protocols. Furthermore, regular monitoring of data entry processes serves to identify and rectify any discrepancies or missing information in a timely manner.   

Meanwhile, real time quality control enables the detection of deviation from study protocol and facilitates corrective actions to maintain the trial’s scientific and ethical integrity. For example, when a study requires multiphasic contrasted imaging but sites follow monophasic local routine protocol, or when the wrong modality is used for patient assessment, or even when a study requires specific acquisition parameters and the site did not apply them—these kinds of issues can be spotted during site qualification steps. Continuous monitoring ensures that all trial sites follow the established protocols consistently and that high quality datasets are provided for every site involved.  

#2 Compliance and Regulatory Requirements 

Every clinical trial is submitted to various regulations such as HIPAA (Health Insurance Portability & Accountability Act) in the United States or the European Union’s GDPR (General Data Protection Regulation). By reviewing each transmitted image before the reading process, the quality controller is therefore key in the Patient Health Information (PHI) identifiers detection process.  

De-identification in quality control is a careful process; when sites upload images onto a platform there’s always the risk of uploading unwanted data. In turn, our medical imaging platform contains an automatic de-identification and manual quality control process. With real time quality control, users can delete all irrelevant imaging data (or data containing patient identifiers) to ensure a flawless dataset is stored and can be analyzed during the reading process.  

#3 Optimizing Workflow and Efficiency 

Quality control also provides insights into process improvements, revealing opportunities for adjustments that can enhance the overall efficiency of the imaging process. Furthermore, many biotech companies are collecting images to read at a later time. But without implementing real time quality control and monitoring activities, research sites run the risk of spending large amounts of money on image collection that will not lead to the production of a quality image dataset. There is also the risk of sites producing deviant acquisitions and therefore potentially losing patient images entirely, which adversely affects site expenditure and patient enrollment in the long run.  

Quality Control Means Quality Imaging Data 

By implementing quality control, sponsors can ensure both high-quality and quality-equivalent datasets among all involved sites, generate necessary datasets that facilitate the central assessment of the images, and guarantee that all analyzed data sets are PHI-free. Quality control is essential towards producing valid and reliable results by maintaining the quality and integrity of clinical trial data.   

To learn more about the Keosys imaging platform, contact one of our sales representatives today.