(99 days)
JUSHA-M32 Medical Display is intended to be used in displaying and viewing digital images for diagnosis of X-ray or MRI, etc. by trained medical practitioners. The device is not specified for digital mammography system.
JUSHA-M32 Medical Display is the display system with the high resolution(2048 x 1536), high luminance(700 cd/m²), and 256 simultaneous shades of gray out of a palette of 4096, 8 DICOM look up table inside, the product is consisted of the following components:
- 21.3 inch, mono-TFT Liquid Crystal Display
- Motherboard HDVI-3M V1.0
- JUSHA-M32 Medical Display software
- Power Adapter
- Data Cable.
The Medical Display is designed, tested, and will be manufactured in accordance with both mandatory and voluntary standards:
- IEC 60601-1 Medical equipment medical electrical equipment - Part 1: General requirements for basic safety and essential performance 1988+A1: 1991 + A2:1995
- IEC 60601-1-2 Edition 3:2007, Medical electrical equipment - Part 1-2: General requirements for basic safety and essential performance - Collateral standard: Electromagnetic compatibility - Requirements and tests.
The provided text is a 510(k) Premarket Notification Submission for the JUSHA-M32 Medical Display. This document focuses on demonstrating substantial equivalence to a predicate device and does not contain information about clinical studies with acceptance criteria and device performance as typically expected for algorithms or AI-driven diagnostic devices.
The submission explicitly states:
"Summary of Clinical Tests: The subject of this premarket submission, Medical Display, did not require clinical studies to support substantial equivalence."
Therefore, it is not possible to provide the requested information regarding acceptance criteria and device performance based on the provided text, as this device (a medical display monitor) did not undergo clinical studies for performance evaluation in the same way an AI diagnostic device would.
The document describes the device's technical specifications and compliance with voluntary standards for safety and performance (e.g., IEC 60601-1 for basic safety and essential performance, and IEC 60601-1-2 for electromagnetic compatibility). The substantial equivalence is determined based on these technical characteristics and non-clinical tests.
If this were an AI or diagnostic algorithm, the expected information would be:
- A table of acceptance criteria and the reported device performance: This would list metrics like sensitivity, specificity, AUC, etc., and the performance achieved by the device.
- Sample size used for the test set and the data provenance: Details about the number of cases/patients in the test set and whether the data was retrospective/prospective, and its origin.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Information about the clinicians who provided truth labels.
- Adjudication method for the test set: How disagreements among experts were resolved (e.g., majority vote, senior expert decision).
- If a multi-reader multi-case (MRMC) comparative effectiveness study was done: If so, the effect size of human readers' improvement with AI assistance.
- If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Yes/No.
- The type of ground truth used: For example, expert consensus, pathology, or outcomes data.
- The sample size for the training set: Number of cases/patients used to train the algorithm.
- How the ground truth for the training set was established: Similar to the test set, but for the training data.
Since the JUSHA-M32 Medical Display is a display system and not a diagnostic algorithm requiring clinical performance evaluation, this information is not present in the 510(k) summary.
§ 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).