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510(k) Data Aggregation
(168 days)
MED-TAB, is a computer hardware/software device intended for viewing of images acquired from CT, MR, CR, DR, US and other DICOM compliant medical imaging systems. Images and data can be stored, communicated, processed, and displayed within the system and or across computer networks at distributed locations. Mammographic images and digitized film screen images must not be reviewed for primary diagnosis or image interpretation. Mammographic images may only be interpreted using a monitor that meets technical specifications identified by FDA. It is the User's responsibility to ensure monitor quality, ambient light conditions, and image compression ratios are consistent with clinical application.
MED-TAB is a 13.3" color LCD monitor including a built-in tablet computer for viewing and analyzing of medical images (except those of mammography) from a picture archiving and communication system (PACS). The color panel employs in-plane switching (IPS) technology allowing wide viewing angles. MED-TAB has one regular display mode to visualize non-medical images, and one DICOM factory calibrated display mode to display medical images according to DICOM requlations. The MED-TAB has been calibrated to comply with DICOM Part 14 at the factory. With built-in brightness stabilization circuit. USB adiustment tool and ambient light sensor. stable brightness and persistent calibration can be guaranteed. The MED-TAB can support both landscape and portrait mode. The anti-reflection coated protective screen can prevent display damage under heavy operating conditions. The tablet-PC is designed in conformity with IEC60601-1, and IEC60601-1-2 standards. Off-the-shelf (OTS) software is used for the mobile viewer application. It supports DICOM image files as well as other common image formats and PDF files.
The provided document, a 510(k) Summary of Safety and Effectiveness for the MED-TAB device, describes the device's intended use and compares its technological characteristics to a predicate device, but it does not contain a detailed study with acceptance criteria and device performance results in the format requested.
The document states:
- "The complete system configuration has been tested at the factory and the device has passed all in-house pre-determined testing criteria without significant failures."
- "The data presented in the submission demonstrates that MED-TAB performs as required according to the functional requirements specified in the Software Requirements Specification and the User Manual with no errors that had an impact on safety or efficacy."
However, it does not provide the specific acceptance criteria, the reported device performance against those criteria, or the details of a formal study as outlined in your request (sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types, or training set details).
Based on the provided text, I can only extract limited information related to the device and its testing:
Key Information from the Document:
- Device Name: MED-TAB
- Intended Use: Viewing of images acquired from CT, MR, CR, DR, US, and other DICOM compliant medical imaging systems. It can store, communicate, process, and display images and data.
- Restriction: Mammographic images and digitized film screen images must not be reviewed for primary diagnosis or image interpretation.
- DICOM Compliance: The device has been calibrated to comply with DICOM Part 14 at the factory.
- Standards Compliance: Designed in conformity with IEC60601-1 and IEC60601-1-2 standards.
- Hazard Analysis: "Level of Concern for potential hazards has been classified as 'Moderate'."
- Predicate Device: IQ-SYSTEM PACS SYSTEM (K062488)
Since the document is a 510(k) summary focused on demonstrating substantial equivalence to a predicate device, it emphasizes functional similarity rather than detailed clinical performance studies for novel AI algorithms. The "testing" mentioned appears to be internal validation against functional requirements, not a separate clinical efficacy study.
Therefore, I cannot populate the requested table and answer many of the questions because the document does not contain that specific level of detail regarding acceptance criteria and study data.
Here is what I can infer or explicitly state based only on the provided text, acknowledging that much of your request cannot be fulfilled:
1. Table of acceptance criteria and the reported device performance
| Acceptance Criteria (Implied from text) | Reported Device Performance (Implied from text) |
|---|---|
| Compliance with DICOM Part 14 | "The MED-TAB has been calibrated to comply with DICOM Part 14 at the factory." |
| Stable brightness and persistent calibration | "With built-in brightness stabilization circuit. USB adjustment tool and ambient light sensor, stable brightness and persistent calibration can be guaranteed." |
| Conformity with IEC60601-1, and IEC60601-1-2 standards | "The tablet-PC is designed in conformity with IEC60601-1, and IEC60601-1-2 standards." |
| Performance according to functional requirements and user manual | "The data presented in the submission demonstrates that MED-TAB performs as required according to the functional requirements specified in the Software Requirements Specification and the User Manual with no errors that had an impact on safety or efficacy." |
| No significant failures in pre-determined testing criteria | "The complete system configuration has been tested at the factory and the device has passed all in-house pre-determined testing criteria without significant failures." |
| No diagnostic assistance to the physician | "The software does not provide any diagnostic assistance to the physician." (This is a functional characteristic, not a performance metric per se, but stated as part of its operation) |
| No control of life-sustaining devices | "MED-TAB does not contact the patient, nor does it control any life sustaining devices." (Functional characteristic) |
| Support for specified image viewing functions and tools (e.g., level window, panning, zooming, MPR, MIP, measurements, annotations) | The device description lists these as "major image viewing functions" and states they are "well-established" and "standard tools." (Implies successful implementation and function) |
| No primary diagnosis or image interpretation of mammographic images | "Mammographic images and digitized film screen images must not be reviewed for primary diagnosis or image interpretation." (This is a limitation of use, not a performance claim, but implies the device does not meet higher standards for specific mammography viewing). |
2. Sample size used for the test set and the data provenance: Not provided in the document. The text refers to "in-house pre-determined testing criteria," which suggests internal validation rather than a clinical study with a defined test set of patient data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not provided in the document.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not provided in the document.
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. The MED-TAB is a viewing device, not an AI-powered diagnostic aid meant to improve human reader performance. The document explicitly states: "The software does not provide any diagnostic assistance to the physician."
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. MED-TAB is a display and viewing system, not an algorithm performing a standalone diagnostic task. Its performance is related to accurate display and functionality.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not provided in the document. Given the device's nature as a viewing system, "ground truth" would likely refer to the accuracy of DICOM rendering, display calibration, and software functionality, rather than diagnostic outcomes.
8. The sample size for the training set: Not applicable. The MED-TAB is a hardware/software viewing system; it is not described as involving a machine learning model that requires a "training set" in the conventional sense of AI.
9. How the ground truth for the training set was established: Not applicable for the same reason as point 8.
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