Search Results

The Medstrat echoeSYSTEM™ is intended to enable the communication, storage, viewing and manipulation of diagnostic medical images and data. The echoeSYSTEM™ can show images on workstations locally and/or across computer networks at widely distributed locations. The echoeSYSTEM™ software is intended for assisting healthcare professionals in preoperative planning and postoperative evaluation of orthopedic surgery. The device allows for overlaying of prosthesis templates on radiological images, and includes tools for performing measurements on the image and positioning the templates. The typical echoeSYSTEM™ users are trained professionals such as orthopedic surgeons, referring and collaborating physicians, and other authorized medical professionals.

It is the user's responsibility to bear in mind the display monitor's quality, ambient light conditions and the tradeoff between image compression ratio and clinical effectiveness for specific image study indications.

ECHOES™ is a client-server software system designed to allow viewing access to medical images on a personal computer by authorized medical professionals. This product is designed to function with off-the-shelf hardware and software products including standard communications products. It does not require specialized, or nonstandard, devices of any type.

Image acquisition is via the industry standard DICOM 3.0 protocol allowing the images to be produced from the digital data originated by the imaging modality.

The software will run on standard off-the-shelf hardware and system configurations,

The provided text is a 510(k) Summary for the Medstrat echoeSYSTEM™, a Picture Archiving and Communication System (PACS). This document focuses on demonstrating substantial equivalence to predicate devices rather than proving a device meets specific acceptance criteria through a performance study with quantitative results.

Therefore, many of the requested sections (e.g., specific acceptance criteria, sample sizes for test/training sets, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth establishment) are not present in the provided text.

The summary describes the device's intended use and compares its features to two predicate devices to establish substantial equivalence. It does not contain information about a study designed to evaluate the statistical performance of the device against predefined acceptance criteria for clinical accuracy or efficacy.

Here's an analysis of what can be extracted based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

There are no explicit acceptance criteria or quantitative performance metrics reported in the provided document. The analysis focuses on substantial equivalence to predicate devices based on shared features and intended use.

2. Sample size used for the test set and the data provenance:

• Not provided. The document describes a comparison to predicate devices' features and intended use, not a clinical performance study with a test set.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not provided. No test set or ground truth establishment process is described.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

• Not provided. No test set or adjudication method is described.

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:

• No, an MRMC study was not done/reported. The device is a PACS system for viewing and manipulation; it's not described as an AI-powered diagnostic aid that would typically undergo such a study for "human reader improvement."

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Not applicable/Not provided. The echoeSYSTEM™ is described as a client-server software system and PACS for viewing and manipulation, not a standalone AI algorithm with independent diagnostic performance. Its primary function is displaying and managing images and providing tools for human professionals.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

• Not provided. No clinical ground truth is mentioned as a basis for validating the device's performance, as the submission focuses on substantial equivalence of functionality.

8. The sample size for the training set:

• Not provided. There is no mention of a training set, as the device is not an AI/machine learning system in the sense of requiring a "training set."

9. How the ground truth for the training set was established:

• Not provided/Not applicable. As no training set is mentioned, the method for establishing its ground truth is also not applicable.

Ask a specific question about this device