Making a difference, an integrated PACS workflow for evaluating longitudinal changes across serial imaging

Improvements in resolution, pulse sequences, and access to scanners allow for increasingly subtle changes to be detected in magnetic resonance images, while increasing the volume of data to be interpreted by radiologists. The burden of reviewing this vast amount of information is further exacerbated by a lack of spatial alignment between images as well as the potential presence of multifocal pathologies. In this work, we describe an informatics approach for incorporating difference images into clinical workflows for highlighting 1) changes in anatomy over time, or 2) contrast enhanced regions following administration of gadolinium. These difference images enhance features of interest while suppressing stable features, providing efficient detection of changes over time, whether due to treatment, age, medical intervention, or progression of disease. Our pipeline is initiated by the physician sending images to a DICOM receiver, which then applies spatial transformation, bias-field correction, and intensity normalization before returning the newly generated difference images to the clinical PACS for review. This pipeline has been used to process 2683 neuroimaging data sets for evaluating disease progression and contrast enhancement in patients with brain lesions. We demonstrate that difference images quantitatively improve contrast-To-noise ratio (CNR) of new lesions while reducing clutter, which should translate to improved accuracy and efficiency in radiological interpretations.