(44 days)
MD301C4 is intended to be used for displaying and viewing of digital images for diagnosis by trained physicians. Caution: MD301C4 cannot be used for a life-support system. This unit is designed as component of a final system which is compliance to IEC60601-1-1 requirements. MD301C4 must not be used in digital mammography.
Medical Display, MD301C4 is a 29.8" Color LCD monitor that displays image for medical use. It provides 4 mega pixel (2560*1600) resolution with adjustable gamma gray scale for more precise diagnose use in CT, MRI, HIS, and PACS. MD301C4 conforms with DICOM.
The provided text is a 510(k) summary for a medical display (MD301C4). It does not contain information about acceptance criteria or a study that proves the device meets specific performance criteria related to an AI algorithm.
This document describes a medical display device and demonstrates its substantial equivalence to a predicate display device. It focuses on physical and technical specifications of the monitor itself, rather than the performance of an AI algorithm or software. Therefore, most of the requested information cannot be extracted from the provided text.
Here is an explanation of why the requested information is not available:
- This is a 510(k) for a display monitor, not an AI diagnostic device. The device (MD301C4) is a "Color LCD Monitor, Color Diagnostic Display," intended for "displaying and viewing of digital images for diagnosis." It does not contain or utilize an AI algorithm for diagnostic purposes.
- The "study" mentioned is a comparison of the new monitor to a predicate monitor to establish substantial equivalence. It's not a clinical performance study involving AI and human readers. The conclusion states: "Device with trade name MD301C4 (model name is L309TY) and predicate device with trade name MD304MC (model name is L307TD) have the same target population... it shares the same design, same performance and is the same in radiation safety (EN60601-1-2), mechanical safety, electrical safety (UL60601-1) and human factors." This is the "study" proving it meets acceptance criteria, which is essentially demonstrating equivalence to an already approved device.
Therefore, I cannot populate the table or answer most of the questions as the information is not present in the provided text.
Here's what can be inferred or stated as "not applicable" based on the document:
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Table of acceptance criteria and reported device performance:
- Acceptance Criteria: The primary acceptance criterion for this 510(k) is "substantial equivalence" to the predicate device (MD304MC, K083916) in terms of design, performance (implied regulatory compliance like DICOM conformance), safety (radiation, mechanical, electrical), human factors, and intended use. Specific quantitative performance metrics for diagnostic accuracy of an AI are not applicable.
- Reported Device Performance: The document states the device "conforms with DICOM" and has "4 mega pixel (2560*1600) resolution with adjustable gamma gray scale." The "performance" in the context of this device refers to its display capabilities and regulatory compliance, not diagnostic accuracy.
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Sample size used for the test set and the data provenance: Not applicable. There is no diagnostic AI test set. This is a display device.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. There is no AI test set requiring expert ground truth.
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Adjudication method for the test set: Not applicable.
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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 for AI performance. The equivalence study compares properties of the display monitors themselves.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI algorithm.
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The type of ground truth used: Not applicable.
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The sample size for the training set: Not applicable. This is not an AI algorithm.
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How the ground truth for the training set was established: Not applicable. This is not an AI algorithm.
§ 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).