K Number
K152172
Device Name
Econsole1
Manufacturer
Date Cleared
2015-12-14

(132 days)

Product Code
Regulation Number
892.2050
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Econsole1 software is indicated for use in general radiographic images of human anatomy (excluding fluoroscopic, angiographic, and mammographic applications).

Device Description

Econsole1 is digital radiography operating console software. Econsole1 provides an integrated solution for X-ray projection. It integrates with the digital detector. Furthermore, Econsole1 acquires and processes images. In addition, it complies with DICOM standards and is able to transmit and receive data with the PACS system, and print images through the DICOM printer.

AI/ML Overview

The provided text is a 510(k) Summary for the Econsole1 device. It contains some information about the device's characteristics and comparison to a predicate device, but it does not contain acceptance criteria for performance, nor does it describe a study that proves the device meets such criteria.

The document explicitly states: "10. Summary of Clinical Data. This section is not applicable." This strongly indicates that no clinical study was performed for this 510(k) submission to demonstrate performance against specific criteria in a real-world or simulated clinical setting.

The "Summary of Non-Clinical Data" mentions compliance with a "FDA guidance document entitled 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices,' May 11, 2005". This guidance focuses on software development and validation processes, not on demonstrating device performance against clinical or technical acceptance criteria.

The information provided confirms that this device is a "Picture archiving and communications system" and "Radiological Image Processing System" which acquires and processes images. The comparison table focuses on technological equivalence to the predicate device, not on quantitative performance metrics.

Therefore,Based on the provided text, I cannot provide the requested information.

Here's why:

  • No Acceptance Criteria or Performance Data: The document does not list any specific performance acceptance criteria for the Econsole1 device (e.g., image quality metrics, processing speed metrics, accuracy scores for any automated features). Consequently, there is no reported device performance against such criteria.
  • No Study Described: The document explicitly states "10. Summary of Clinical Data. This section is not applicable." This means no clinical study (or any study to demonstrate performance against acceptance criteria) was conducted and detailed in this submission. The submission relies on demonstrating substantial equivalence to a predicate device based on intended use and technological characteristics, not on a new performance study.
  • No Clinical Ground Truth: Since no performance study was conducted, there's no mention of ground truth establishment, expert adjudication, or human reader performance.
  • No Training Set Information: As no new algorithm performance study is described, there is no information about a training set.

In summary, the provided 510(k) summary focuses on demonstrating substantial equivalence based on intended use and technological characteristics compared to a predicate device, rather than on presenting performance data against specific acceptance criteria from a new study.

§ 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).