Intended Use

Used by radiation oncology to segment non-contrast CT images to generate information for treatment planning, evaluation, and adaptation.

Technology

A standalone software that uses deep learning for automatic segmentation of organs-at-risk on non-contrast CT images. It supports desktop and web-based automatic contouring and manual adjustments, compatible with DICOM 3.0 CT images from any scanner, targeting adults undergoing radiation therapy.

Performance

Segmentation performance was validated using datasets from US healthcare institutions scanned on major vendors' CT scanners (GE, Siemens, Philips). Performance measured by Dice Similarity Coefficients (DSC) showed non-inferiority compared to the predicate device. Additional organs segmented by RT-Mind-AI also showed comparable accuracy.

Predicate Devices

No predicate devices specified

Device Timeline

  • 1

    Submission

    9/28/2021

    2 months
  • 2

    FDA Approval

    12/15/2021

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