(184 days)
UROSTATION - 3D PROSTATE SUITE is a computer-based software application intended to process, visualize and record 3D digital ultrasound images of the prostate.
UROSTATION - 3D PROSTATE SUITE is intended to be used by physicians in the clinic or hospital for 2D and 3D visualization of ultrasound images of the prostate gland. Additional software features include patient data management, multi-planar reconstruction and 3D image registration.
UROSTATION - 3D PROSTATE SUITE is a computer-based software application designed to process, visualize and record 3D digital ultrasound images of the prostate, and to manage patient and clinical data in the context of transrectal prostate biopsy.
This 510(k) summary does not contain the acceptance criteria or a study proving that the device meets acceptance criteria in the traditional sense of a clinical performance study with statistical endpoints.
Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (3-D Imaging Workstation, K081093) based on shared intended use, technological characteristics, and functions. The "study" here is a comparison of features and capabilities.
Here's a breakdown of the requested information based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance:
| Feature/Characteristic | Acceptance Criteria (Implied by Predicate) | Reported Device Performance (UROSTATION - 3D PROSTATE SUITE) |
|---|---|---|
| Intended Use | Process, visualize and record 3D digital ultrasound images of the prostate | Process, visualize and record 3D digital ultrasound images of the prostate |
| Function - Image Acquisition | 2D/3D image acquisition | 2D/3D image acquisition |
| Function - Image Viewing/Reviewing | 2D/3D image viewing/reviewing | 2D/3D image viewing/reviewing |
| Function - Image Processing | 2D/3D image processing | 2D/3D image processing |
| Function - Image Storage | 2D/3D image storage | 2D/3D image storage |
| Function - Multi-Planar Reformatting (MPR) | Multi-Planar Reformatting (MPR) (implied by predicate's "Volume rendering", "Segmentation") | Multi-Planar Reformatting (MPR) |
| Function - Patient and Clinical Data Management | Patient and clinical data management | Patient and clinical data management |
| Data Source | 3D TRUS scanners | 3D TRUS scanners |
| Physical Characterization | Software package, operates on off-the-shelf hardware, Windows OS | Software package, operates on off-the-shelf hardware, Windows OS |
| Differences from Predicate | Not applicable; differences are noted as not raising safety/effectiveness concerns. | • Linear workflow adapted to physician's practice. |
| • Dedicated algorithm to visualize biopsies w.r.t. a single reference image. | ||
| • No measurement features. |
Note on Acceptance Criteria: The acceptance criteria are implied by the features of the predicate device. The goal of this 510(k) is to show UROSTATION performs similarly or introduces no new risks despite differences. There are no explicit quantitative performance metrics or thresholds mentioned as "acceptance criteria" for a study to meet.
2. Sample size used for the test set and the data provenance:
- Sample Size: Not applicable. The document describes a comparison to a predicate device's functionalities, not a clinical test set for performance evaluation.
- Data Provenance: Not applicable. No specific data or images were used for performance evaluation in a clinical study context.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of Experts: Not applicable. No ground truth was established by experts for a test set in this submission.
- Qualifications of Experts: Not applicable.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Adjudication Method: Not applicable. No test set requiring expert adjudication was conducted.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- MRMC Study: No. This submission does not include an MRMC comparative effectiveness study. The device is image processing software, not an AI diagnostic tool requiring evaluation of human reader performance.
- Effect Size: Not applicable.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Standalone Study: No. This submission does not describe a standalone performance study. The device's function is to process and visualize images for physician use, not to make independent diagnoses.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Type of Ground Truth: Not applicable. No ground truth data (e.g., pathology, outcomes) was used for performance validation in this context. The "ground truth" for substantial equivalence is the predicate device's established safety and effectiveness.
8. The sample size for the training set:
- Sample Size: Not applicable. The document does not mention any machine learning or AI components that would require a "training set" in the context of performance evaluation. It describes software with image processing and display algorithms.
9. How the ground truth for the training set was established:
- How Ground Truth Was Established: Not applicable, as there is no mention of a training set.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).