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ProKnow DS is a patient data archive, information management, and analytics software system with a focus on the data and images specific to radiation oncology patients. Users may upload digital patient data created by other devices to ProKnow DS to securely archive, display, and analyze the data. Users can view and navigate patient images, drawn anatomy, calculated dose, and plan details derived from the source files. Users can create or edit anatomy structures to be used either prospectively (e.g., as an input to treatment planning) or retrospectively (e.g., for data analysis, research, and outcomes studies). Users can extract metrics for any single patient, or across a collection of patients, then view results as tables or graphically. ProKnow DS is to be used as an accessory system to perform data archive, review, and analysis, and is not to be used for diagnosis, treatment, or as the sole form of plan approval.

ProKnow DS is a Radiation Therapy Picture/Patient Archiving and Communication System (RT-PACS). It allows users to archive, inspect, analyze, and interact with radiation therapy patient data for both retrospective and prospective studies. Its features are centered on two primary areas of interaction: (1) single patient datasets and (2) collections of patient datasets, i.e., patient cohorts. Users are able to import patient data from existing imaging, contouring, and treatment planning systems (via DICOM formats). Once imported, patient data is archived for long-term storage and is also available for inspection and analysis (examples of supported inspection and analysis tasks include: visualizing images, structures, and dose distributions; inspecting plan information; inspecting dose volume histograms; and extracting metrics). ProKnow DS also allows users to edit anatomical contour data associated with a patient for use in retrospective studies or to be exported to commercially available radiation treatment planning systems. Once a set of patients have been established in ProKnow DS, users may create collections of related patients allowing them to analyze and correlate dosimetric values of interest and clinical endpoints across large treatment populations.