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HMD3C21S : The 3MP Color LCD Monitor HMD3C21S is indicated for use in displaying radiological images for review, and diagnosis by trained medical practitioners. The display is not intended for mammography.
HMD5G21S : The 5MP Monochrome LCD Monitor HMD5G21S is intended to be used in displaying and viewing medical images for diagnosis by trained medical practified personnel. It is intended to be used in digital mammography PACS, digital breast tomosynthesis and modalities including FFDM.

The LCD monitor employs high-luminance LCD panel, and is designed for medical image display.

This document describes the performance assessment of medical LCD monitors (HMD3C21S and HMD5G21S) for displaying radiological images. It is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than proving clinical effectiveness of an AI algorithm. Therefore, many of the requested elements typically found in AI/ML medical device evaluations (like sample sizes for training/test sets, expert adjudication, MRMC studies, or specific performance metrics using AI) are not applicable or available in this submission.

The "acceptance criteria" here refers to the performance benchmarks for a medical display, ensuring it meets standards for diagnostic imaging. The "study that proves the device meets the acceptance criteria" refers to the bench testing performed on the monitors.

Here's the breakdown based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document lists various physical laboratory measurements performed on the monitors to ensure they meet the display requirements. The acceptance criteria are implicit in the tests performed, aiming for performance comparable to existing medical displays. The reported performance is generally "By reporting [method]" or "Measure the [property]", indicating that these measurements were taken rather than providing specific numerical results for each one. This type of submission focuses on demonstrating that the testing was done according to recognized standards.

Implicit Acceptance Criteria (based on tests performed): The monitors must demonstrate adequate performance across these parameters consistent with established medical display standards (e.g., AAPM-TG18, IEC).

2. Sample size used for the test set and the data provenance

• Test Set Sample Size: Not explicitly stated as a "sample size" in the context of diagnostic performance testing with cases. This submission is for a medical monitor, not an AI diagnostic algorithm. The "testing" refers to the physical bench testing of the device itself.
• Data Provenance: No patient data or clinical images are referenced for the performance testing of the monitor. The testing relates to the physical characteristics and display capabilities of the monitor hardware.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not Applicable. This document is for a medical display device, not an AI algorithm that requires setting ground truth for image interpretation. The "ground truth" for a monitor's performance is established by objective physical measurements against industry standards (e.g., AAPM-TG18).

4. Adjudication method for the test set

• Not Applicable. As no diagnostic performance with images and human readers is being evaluated, no adjudication method is relevant.

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. This is a medical monitor, not an AI-powered diagnostic device. No MRMC studies were conducted as part of this submission.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Not Applicable. This is a monitor, not an algorithm. Therefore, standalone performance (in the context of an algorithm's diagnostic output) is irrelevant.

7. The type of ground truth used

• Objective Physical Measurements against Industry Standards. The "ground truth" for a display device is its adherence to performance specifications and established industry standards (e.g., DICOM GSDF, AAPM-TG18), verified through physical and optical measurements using specialized equipment.

8. The sample size for the training set

• Not Applicable. This device is a medical monitor, not an AI/ML algorithm that requires a training set.

9. How the ground truth for the training set was established

• Not Applicable. As there is no training set for an AI algorithm, no ground truth needed to be established in that context.

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The 2MP/3MP LCD Monitor (HMD2C21) is intended to be used in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The 2MP/3MP LCD Monitor (HMD2C21/HMD3C21) is a display system for medical viewing, with high resolution 1600x1200(HMD2C21)/2048 x 1536(HMD3C21), built-in brightness stabilization circuit, front sensor and ambient light sensor, stable brightness and persistent calibration can be guaranteed. The display can support both landscape and portrait mode. The antiglare screen can prevent display from reflection under highlight conditions, make the image and display clearer.

This document is a 510(k) summary for the Hisense 2MP/3MP LCD Monitors (HMD2C21/HMD3C21). A 510(k) submission aims to demonstrate that a new device is "substantially equivalent" to a legally marketed predicate device, meaning it is as safe and effective. This type of submission focuses on comparing the new device's characteristics to a predicate, rather than an independent study to define acceptance criteria and then demonstrate performance against those specific criteria using a test set and ground truth.

Therefore, the requested information cannot be fully provided in the typical format of an AI/ML device study. Instead, I will describe the comparisons made to establish substantial equivalence.

Here's an analysis of the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

Instead of formal acceptance criteria and device performance as typically seen in a diagnostic AI study, this document compares the technical specifications and intended use of the proposed devices (Hisense HMD2C21 and HMD3C21) against their predicate devices (BARCO Nio 2MP and Nio 3MP). The "acceptance criteria" here is effectively meeting comparable specifications to the predicate device, thereby demonstrating substantial equivalence.

Table 1: Comparison of Proposed Devices (Hisense HMD3C21/HMD2C21) to Predicate Devices (BARCO Nio 3MP/2MP)

2. Sample Size Used for the Test Set and the Data Provenance

This is an LCD monitor, not an AI/ML diagnostic algorithm that processes medical data. Therefore, there is no "test set" of medical images or patient data, nor is there "data provenance" in the sense of country of origin of patient data or retrospective/prospective studies. The "testing" involves verifying the monitor's physical, electrical, and performance specifications against industry standards and the predicate device's specifications.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

Not applicable. As this is a medical display device, not an AI/ML diagnostic device interpreting images, there is no "ground truth" based on expert consensus on diagnoses. The "truth" lies in the adherence to technical specifications and safety standards.

4. Adjudication Method for the Test Set

Not applicable. There is no test set of patient data requiring adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

Not applicable. This is a medical display device, not an AI diagnostic tool. MRMC studies are used to assess diagnostic performance of algorithms (with or without human readers).

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Not applicable. There is no algorithm in this product for standalone performance evaluation.

7. The Type of Ground Truth Used

Not applicable. The "ground truth" for this device revolves around objective engineering and performance metrics (e.g., brightness levels, resolution, contrast ratio, compliance with electrical safety standards, etc.), not clinical diagnoses or outcomes.

8. The Sample Size for the Training Set

Not applicable. This is a medical display device; there is no AI/ML algorithm requiring a training set.

9. How the Ground Truth for the Training Set Was Established

Not applicable. There is no training set for this device.

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This diagnostic ultrasound system (Hi-Light) and its transducers are intended for use in clinical examinations to evaluate differences in the echogenicity of soft tissue of small parts in adult patients (thyroid, breast, and testicles) and for superficial muscular skeletal diagnosis.

The system is for prescription use only by a trained sonographer under the direction of a qualified physician or directly by a qualified physician.

The Hi-Light is a portable Diagnostic Ultrasound System, which applies the latest technologies to produce optimal images. The system facilitates a workflow from image acquisition through to archival in a standard DICOM interface to the clinics PACs system. Various image parameter adjustments, a 15 inch high resolution display and custom probes are configured to provide clear and stable images. The modes of operation include B mode.

The provided document is a 510(k) premarket notification for the Hi-Light Diagnostic Ultrasound System. This type of FDA submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than providing extensive clinical study data to prove the device meets specific acceptance criteria in the same way a novel device might.

Based on the document, here's what can be extracted and inferred regarding the acceptance criteria and supporting studies:

1. A table of acceptance criteria and the reported device performance:

   Acceptance Criteria Type	Criteria/Standard	Reported Device Performance
   Clinical Performance (Imaging)	Not explicitly defined in quantitative metrics for this type of submission. The overarching criterion is "substantially equivalent" to predicate for intended clinical use (evaluating differences in echogenicity of soft tissue of small parts in adult patients (thyroid, breast, and testicles) and superficial musculoskeletal diagnosis).	"applies the latest technologies to produce optimal images." "configured to provide clear and stable images." "same fundamental scientific technologies as the predicate device." "supports the same operating mode (B) and the same measurement functions for anatomic structures."
   Safety Standards	IEC 60601-1 (Safety Requirements for Medical Equipment, 2012)	In conformance
   	IEC 60601-1-2 (EMC Requirements for Medical Equipment, 2007)	In conformance
   	IEC 60601-2-37 (Diagnostic Ultrasound Safety Standards, 2007)	In conformance
   Acoustic Output	FDA guidance "Information for Manufacturers Seeking Marketing Clearance of Diagnostic Ultrasound Systems and Transducers", dated September 9, 2008	Testing conducted as per guidance
   Biocompatibility	ISO 10993-1 (Evaluation and testing, 2003)	Acceptable for specified usage of the system
   	ISO 10993-5 (Tests for in vitro cytotoxicity, 1999)	(Implied acceptable through conformance to ISO 10993)
   	ISO 10993-10 (Tests for irritation and delayed-type hypersensitivity, 2002)	(Implied acceptable through conformance to ISO 10993)
   	ISO 10993-11 (Tests for systemic toxicity, 2006)	(Implied acceptable through conformance to ISO 10993)
   Technological Equivalence	Same intended use and operational characteristics as predicate OR same intended use and different operational characteristics where substantial equivalency can be demonstrated without raising new questions of safety and effectiveness.	"same fundamental scientific technologies as the predicate device" "narrowed, but still in the scope of the predicate device" "does not raise any questions regarding its safety and effectiveness"

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • No clinical test set or data provenance is mentioned because the submission explicitly states: "Clinical Test: Clinical testing not required" for this device. The assessment is based on non-clinical testing and comparison to a predicate device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   • Not applicable, as no clinical testing was performed and therefore no ground truth was established by experts for a test set.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable, as no clinical testing was performed.

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. This is a diagnostic ultrasound system, not an AI-powered diagnostic algorithm. No MRMC study was mentioned or performed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Not applicable. This is a hardware diagnostic ultrasound system, not a standalone algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

   • Not applicable for clinical performance. The "ground truth" for the submission is the established safety and effectiveness of the predicate device (Siemens Acuson S2000, K081148) and adherence to recognized non-clinical safety standards.

8. The sample size for the training set:

   • Not applicable. This is not an AI/ML device that requires a training set.

9. How the ground truth for the training set was established:

   • Not applicable. This is not an AI/ML device.

Summary of the Study:

The "study" referenced in this 510(k) submission is primarily a non-clinical comparative study demonstrating compliance with recognized safety and performance standards for medical devices and establishing substantial equivalence to a previously cleared predicate device.

• Objective: To demonstrate that the Hi-Light Diagnostic Ultrasound System is substantially equivalent to the Siemens Acuson S2000 Ultrasound System (K081148).
• Methodology:
  • Non-clinical Testing: The device underwent testing to established international and FDA-recognized safety standards, including IEC 60601-1, IEC 60601-1-2, IEC 60601-2-37, acoustic output testing per FDA guidance, and biocompatibility testing per ISO 10993 series.
  • Comparative Analysis: A detailed comparison was made between the Hi-Light system and the predicate device (Siemens Acuson S2000) regarding:
    • Indications for Use
    • Intended Use
    • Principles of Operation
    • Device characteristics (e.g., size, weight, transducer specifications like type, frequency, applications, number of elements, modes of operation, array footprint).
  • Basis for Equivalence: The submission argues that the Hi-Light uses the "same fundamental scientific technologies" and has "narrowed, but still in the scope" clinical applications compared to the predicate. The differences (primarily size and some modes of operation) do not raise new questions of safety or effectiveness.
• Outcome: The FDA determined that the device is substantially equivalent to the predicate device based on the non-clinical testing and comparative analysis, and thus did not require clinical testing.

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