K Number
K102388
Date Cleared
2010-11-04

(73 days)

Product Code
Regulation Number
892.1550
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

Ultrasound imaging, measurement and analysis of the human body as follows: Abdominal/GYN; Urology; Fetal/OB; Small Organ (breast, testes, thyroid); Pediatric; Neonatal & Adult Cephalic; Cardiac (adult & pediatric); Peripheral Vascular; Musculo-skeletal (conventional & superficial); Transesophageal; Intraoperative (abdominal, thoracic and PV); Transvaginal and Transrectal, Intra-cardiac and intra-luminal applications.

Device Description

The Vivid-i and Vivid-q are compact and portable diagnostic ultrasound systems with integrated keyboard, fold-up LCD type display and interchangeable electronic-array transducers. They have an overall size approximately 36 cm wide, 31.5 cm deep and 6 cm high in transport configuration and provide digital acquisition, processing and display capability. The user interface includes a computer keyboard, an intuitive layout of specialized controls, color GUI display and Doppler audio.

AI/ML Overview

The provided text is a 510(k) Summary for the GE Healthcare Vivid i/q Diagnostic Ultrasound System. It is primarily focused on demonstrating substantial equivalence to predicate devices rather than presenting detailed performance criteria and a study to prove those criteria.

Therefore, the requested information regarding "acceptance criteria and the study that proves the device meets the acceptance criteria" is largely not present in the provided document. The 510(k) summary explicitly states:

"The subject of this premarket submission, the modified Vivid i/q, did not require clinical studies to support substantial equivalence." (Page 3)

However, I can extract the following relevant details from the document:

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

Since no clinical studies were performed to establish new acceptance criteria and performance metrics for the modified Vivid i/q, a table of specific clinical performance acceptance criteria and reported device performance cannot be generated from this document. The document instead relies on substantial equivalence to predicate devices, implying that their performance characteristics are maintained.

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

No clinical test sets were used for this 510(k) submission, as explicitly stated above. Therefore, details regarding sample size and data provenance are not applicable.

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 test sets requiring expert-established ground truth were used.

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

Not applicable, as no clinical test sets requiring adjudication were used.

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 submission is for an ultrasound system, not an AI-assisted diagnostic tool. No MRMC studies were conducted.

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

Not applicable. This submission is for an ultrasound system, which inherently involves human operation and interpretation.

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

Not applicable, as no clinical studies requiring new ground truth establishment were performed for this submission. The ground truth for the predicate devices would have been established through clinical validation relevant to diagnostic ultrasound.

8. The sample size for the training set:

Not applicable, as this submission is for a medical device (ultrasound system), not a machine learning algorithm that requires a training set.

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

Not applicable, as this submission is for a medical device (ultrasound system), not a machine learning algorithm.

Summary of Non-Clinical Tests (from Page 3 of the document for completeness, as this is the closest to "performance"):

The document highlights the following non-clinical evaluations to ensure safety and effectiveness:

  • Acoustic output
  • Biocompatibility
  • Cleaning and disinfection effectiveness
  • Thermal, electrical, electromagnetic, and mechanical safety

These tests comply with applicable medical device safety standards and voluntary standards. The following quality assurance measures were applied to the development of the system:

  • Risk Analysis
  • Requirements Reviews
  • Design Reviews
  • Testing on unit level (Module verification)
  • Integration testing (System verification)
  • Final Acceptance Testing (Validation)
  • Performance testing (Verification)
  • Safety testing (Verification)

The biocompatibility of transducer materials and other patient contact materials was also confirmed.

§ 892.1550 Ultrasonic pulsed doppler imaging system.

(a)
Identification. An ultrasonic pulsed doppler imaging system is a device that combines the features of continuous wave doppler-effect technology with pulsed-echo effect technology and is intended to determine stationary body tissue characteristics, such as depth or location of tissue interfaces or dynamic tissue characteristics such as velocity of blood or tissue motion. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.