Search Results

The Color Nio 2MP is intended to be used in displaying and viewing digital images for review by trained medical practitioners. These devices must not be used in primary image diagnosis in mammography.
The E-2320 C is intended to be used in displaying and viewing digital images for review by trained medical practitioners. These devices must not be used in primary image diagnosis in mammography.

Color Nio 2MP is a display system for medical viewing. It consists of 3 components: E-2320 C is a 20.1" color LCD display. BarcoMed 2MP2CFe is a fast high-resolution display controller board that plugs into a PACS workstation computer. NioWatch is user-friendly software that allows to optimize the display for DICOM-compliant viewing. The display system can be a single-head system or multi-head system. In the last case it contains multiple displays and display controller boards.
E-2320 C is a 20.1" color LCD display for medical viewing. It is combined with NioWatch, a userfriendly software that allows to optimize the display for DICOM-compliant viewing.

This document is a 510(k) premarket notification for the "Color Nio 2MP" and "E-2320 C" display systems, seeking to demonstrate substantial equivalence to predicate devices. It does not contain information about a study proving device performance against acceptance criteria in the typical sense of a clinical trial or algorithm performance study.

These are display devices, and the "acceptance criteria" here relate to their technical specifications aligning with those of legally marketed predicate devices, rather than clinical performance metrics like sensitivity or specificity for a diagnostic task.

Therefore, many of the requested categories (e.g., sample size for test set, number of experts, adjudication method, MRMC study, standalone performance, ground truth types for test/training sets, training set sample size, ground truth establishment for training set) are not applicable to this type of submission.

Here's a breakdown of the available information interpreted in the context of a display device submission:

1. Table of Acceptance Criteria and Reported Device Performance

Study Proving Device Meets Acceptance Criteria:

The document describes a substantial equivalence determination rather than a traditional study with acceptance criteria and performance metrics. The "study" is, in essence, the technical comparison presented in the 510(k) summary.

The core of the "proof" is the comparison of technological characteristics between the new devices (Color Nio 2MP and E-2320 C) and their respective predicate devices (Nio 2MP Medical flat panel display system K042660 and MFCD 2320 K040158). The manufacturer asserts, and the FDA concurs, that "Any difference between both devices does not affect safety or efficacy."

Specifics from your numbered list:

2. Sample size used for the test set and the data provenance: Not applicable. This is a technical comparison for display devices, not a study involving patient data or a test set in the clinical sense.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for clinical interpretation is not relevant for this type of device.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable for the reasons above.
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: Not applicable. These are display devices, not AI algorithms, and no MRMC study is mentioned or relevant to their substantial equivalence.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. These are display hardware and associated software, not algorithms.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. The "ground truth" for this submission revolves around the technical specifications and performance of the display panel and controller, relative to a legally marketed predicate device, to ensure it continues to adequately display medical images without compromising safety or efficacy.
8. The sample size for the training set: Not applicable. No algorithms were "trained" in this submission.
9. How the ground truth for the training set was established: Not applicable. No algorithms were "trained" in this submission.

Ask a specific question about this device