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510(k) Data Aggregation
(174 days)
The device is general purpose diagnostic ultrasound system for use by qualified healthcare professionals. It is applicable for adults, pregnant women, pediatric patients and neonates.
The device is intended for ultrasound imaging, measurement and analysis of human body and fluid for multiple clinical applications including: abdominal (GYN and Urology), Thoracic/Pleural, Fetal/Ob, small organ (including breast, thyroid, testes), peripheral vessel, neonatal cephalic, pediatric, musculo-skeletal (conventional, superficial), transrectal, trans-vaginal, cardiac pediatric, magnetic Needle guidance and imaging guidance of interventional procedures (e.g. biopsy).
This device is intended to use by, or by the order of, and under the supervision of a licensed physician qualified to direct the use of the device.
The device is used in hospital, clinical point-of-care for diagnosis of patients. The operating modes supported by the device are B, M,PWD CWD, Tissue Doppler, Color M Doppler, Power Doppler, Tissue Velocity Imaging, Harmonic Imaging, 3D/4D, CBI, EI, Combine modes.
The VINNO 6EXP, VINNO 6PRO, VINNO 5EXP, VINNO 5PRO, VINNO 3, VINNO 3EXP, VINNO 3PRO ultrasound devices are laptop digital color ultrasonic diagnostic devices which transmit ultrasound waves into the body tissues and display the echo images of the tissues and blood flow accordingly. The devices are capable of digital acquisition, processing and display and operate from an integrated battery or separate power supply/charger.
The provided 510(k) summary does not contain performance criteria or a study proving that the device meets specific acceptance criteria in the manner typically requested for AI/ML devices. This submission focuses on establishing substantial equivalence to a predicate ultrasound device through technical comparisons and compliance with general safety and performance standards, rather than evaluating a specific AI algorithm's diagnostic performance against established criteria.
However, based on the information provided, here's what can be extracted and inferred:
1. Table of Acceptance Criteria and Reported Device Performance
Since this is not an AI/ML device with specific diagnostic performance metrics (like sensitivity, specificity, AUC) for a particular medical condition, the "acceptance criteria" revolve around demonstrating comparable safety and effectiveness to the predicate device.
| Acceptance Criteria Category | Specific Criteria (Implicitly Met by Predicate Equivalence) | Reported Device Performance (as demonstrated by non-clinical testing) |
|---|---|---|
| Biocompatibility | Meet ISO 10993-1:2009 standards for probes. | All evaluation acceptance criteria were met. |
| Electrical Safety | Comply with IEC 60601-1 standards. | The system complies with IEC 60601-1. |
| EMC (Electromagnetic Compatibility) | Comply with IEC 60601-1-2 standards. | The system complies with IEC 60601-1-2. |
| Software Verification & Validation | Follow FDA's "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" for "moderate" level of concern software. | Software verification and validation testing were conducted, and documentation was provided as recommended. |
| Acoustic Output | Comply with Track 3 limits (Ispta.3 ≤ 720mW/cm², MI ≤ 1.9) according to NEMA UD2 and IEC 60601-2-37. | Acoustic output testing was performed according to NEMA UD2 and IEC60601-2-37, and the device complies with Track 3 limits (explicitly stated). |
| General Performance | Perform as safely and effectively as the predicate device for its intended uses and technological characteristics. | Non-clinical testing demonstrates that the device is as safe, as effective, and performs as well as the legally marketed device (predicate). |
2. Sample Size Used for the Test Set and Data Provenance
This information is not applicable in the context of this 510(k) summary. This submission is for an ultrasound system, not an AI diagnostic algorithm. There is no "test set" of patient data used for diagnostic performance evaluation of an AI algorithm in this document. The performance data discussed are related to engineering and safety standards (biocompatibility, electrical safety, etc.), not a clinical performance study using patient data.
3. Number of Experts Used to Establish Ground Truth and Qualifications
This information is not applicable. There is no "ground truth" to be established by experts for a test set in this kind of submission, as it doesn't involve the evaluation of an AI algorithm's diagnostic accuracy.
4. Adjudication Method
This information is not applicable for the same reasons as above.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
This information is not applicable as this is not an AI-assisted diagnostic device being evaluated for its impact on human reader performance.
6. Standalone Performance Study
This information is not applicable as this is not an AI algorithm requiring standalone performance evaluation. The device itself is a standalone ultrasound system.
7. Type of Ground Truth Used
This information is not applicable as there is no diagnostic AI algorithm being evaluated. The "ground truth" for the device's claims are the established engineering standards and specifications (e.g., IEC 60601-1) and the performance characteristics of the predicate device.
8. Sample Size for the Training Set
This information is not applicable. There is no AI algorithm being trained.
9. How the Ground Truth for the Training Set Was Established
This information is not applicable. There is no AI algorithm being trained.
In summary: The provided document is a 510(k) summary for a general-purpose diagnostic ultrasound system. Its "acceptance criteria" and "proof" primarily revolve around demonstrating substantial equivalence to a legally marketed predicate device by showing that it meets relevant safety, electromagnetic compatibility, software validation, and acoustic output standards, and that its technical characteristics and indications for use are the same. It does not involve the type of AI/ML performance study described in the prompt.
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