Saige-Q is a software workflow device that processes Digital Breast Tomosynthesis (DBT) and Full-Field Digital Mammography (FFDM) screening mammograms using artificial intelligence to act as a prioritization tool for interpreting radiologists. By automatically indicating whether a given mammogram is suspicious for malignancy, Saige-Q can help the user prioritize or triage cases in their worklist (or queue) that may benefit from prioritized review.Saige-Q takes as input a set of x-ray mammogram DICOM files from a single screening mammography study (FFDM or DBT). The software first checks that the study is appropriate for Saige-Q analysis and then extracts, processes and analyses the DICOM images using an artificial intelligence algorithm. As a result of the analysis, the software generates a Saige-Q code indicating the software’s suspicion of the presence of findings suggestive of breast cancer. For mammograms given a Saige-Q code of “Suspicious,” the software also generates a compressed preview image, which is for informational purposes only and is not intended for diagnostic use.The Saige-Q code can be viewed by radiologists on a picture archiving and communication system (PACS), Electronic Patient Record (EPR), and/or Radiology Information System (RIS) worklist and can be used to reorder the worklist. As a software-only device, Saige-Q can be hosted on a compatible host server connected to the necessary clinical IT systems such that DICOM studies can be received and the resulting outputs returned where they can be incorporated into the radiology worklist.The Saige-Q codes can be used for triage or prioritization. For example, “Suspicious” studies could be given prioritized review. With a worklist that supports sorting, batches of mammograms could also be sorted based on the Saige-Q code.

Saige-Dx is a software device that processes screening mammograms using artificial intelligence to aid interpreting radiologists. By automatically detecting the presence or absence of soft tissue lesions and calcifications in mammography images, Saige-Dx can help improve reader performance, while also reducing reading time. The software takes as input a set of x-ray mammogram DICOM files from a single digital breast tomosynthesis (DBT) study and generates finding-level outputs for each image analyzed, as well as an aggregate case- level assessment. Saige-Dx processes both the DBT image stacks and the associated 2D images (full-field digital mammography (FFDM) and/or synthetic 2D images) in a DBT study. For each image, Saige-Dx outputs bounding boxes circumscribing any detected findings and assigns a Finding Suspicion Level to each finding, indicating the degree of suspicion that the finding is malignant. Saige-Dx uses the results of the finding-level analysis to generate a Case Suspicion Level, indicating the degree of suspicion for malignancy across the case. Saige-Dx encapsulates the finding and case-level results into a DICOM Structured Report (SR) object containing markings that can be overlaid on the original mammogram images using a viewing workstation and a DICOM Secondary Capture (SC) object containing a summary report of the Saige-Dx results.