(124 days)
QUATERA System (QUATERA 700) is intended for the emulsification and removal of cataracts and anterior segment vitrectomy. In combination with various required components and accessories, the device is designed for use in anterior segment surgery. It provides capabilities for phacoemulsification, coaxial and bimanual irrigation/aspiration, bipolar coagulation and anterior vitrectomy.
This device is for Prescription Use (Rx) only.
QUATERA 700 is a mobile phacoemulsification system designed for use in the ophthalmic surgical operating rooms during surgery of the anterior eye segment. When QUATERA 700 is used with compatible components and accessories, the system will perform the following surgical procedures: irrigation and/or aspiration, phacoemulsification of crystalline lens, anterior vitrectomy, and bipolar coagulation.
QUATERA 700 has fluidic, ultrasound and pneumatic modules for emulsification and aspiration of the cataractous lens from eye and maintain the pressure and volume of the eye intraoperatively. The required values are pre-set via a Graphical User Interface and controlled directly by the surgeon using the Foot Control Panel of the device and delivered in the eye via a range of accessories. The systems control mechanism verifies the output values and the pre-set values.
QUATERA 700 has the following functions:
- · Irrigation and Aspiration
- · Ultrasound Capability
- · Diathermy
- · Anterior Vitrectomy
- Reflux
QUATERA 700 is intended to be used within a clinic(s)/hospital(s)/surgical practice network.
The provided text is an FDA 510(k) clearance letter for a medical device called QUATERA 700. It asserts the device's substantial equivalence to a predicate device (also a QUATERA 700, but with older software) rather than presenting a performance study against specific acceptance criteria for a novel AI/software component.
Therefore, many of the requested details, such as sample size for test sets, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for AI models, are not applicable or not present in this document.
The document focuses on non-clinical performance testing and substantial equivalence to an existing device, primarily due to minor software changes and component updates. There is no mention of an AI/machine learning component that would require the rigorous performance evaluation typically outlined by the questions.
However, I can extract and infer information relevant to the types of "acceptance criteria" and "study" that were performed to demonstrate substantial equivalence, based on the provided text, even if not in the AI-specific format you requested.
Here's the breakdown based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
The document doesn't present a table of quantitative performance metrics against specific predefined acceptance criteria in the way one would for an AI algorithm's diagnostic accuracy. Instead, the "acceptance criteria" for this 510(k) are essentially the demonstration of compliance with established medical device standards and the maintenance of equivalence to the predicate device. The "performance" is a statement of compliance or "passed."
| Acceptance Criteria Category/Standard | Reported Device Performance |
|---|---|
| Biocompatibility (for accessories/components coming into patient contact) | "Standards have been followed for the accessories/components, specifically regarding cytotoxicity, kligman maximization, and intracutaneous irritation and acute systemic toxicity testing." (Implies compliance/acceptance) |
| Sterilization and Shelf Life (for reprocessed accessories) | "Testing was performed on the appropriate components of the subject device. The testing aligns with current recognized standards and meets or exceeds testing performed for the predicate device." (Implies compliance/acceptance) |
| Software Verification and Validation (Software Version 1.1.4) | "Testing passed." (According to FDA Guidance May 2005, IEC 62304:2008 + AC:2015, IEC 62366) |
| Electromagnetic Compatibility (EMC) and Electrical Safety | "Testing passed." (In accordance with IEC 60601-1, IEC 60601-1-2, IEC 60601-1-6, IEC 60601-2-2 standards) |
| Bench Performance Testing (Efficacy, Safety, Substantial Equivalence) | "Additional laboratory (bench) performance tests have been conducted... to demonstrate efficacy, safety and substantial equivalence to predicate devices." (Specifically: IEC 80601-2-58, IEC 60601-2-2). [Implies compliance/acceptance, but no specific metrics are given.] |
| Functionality Equivalence to Predicate (e.g., Irrigation/Aspiration, Ultrasound, etc.) | "Identical" for all listed functional attributes (see comparison tables on page 5-6). |
| Intended Use/Indications for Use Equivalence to Predicate | "The indications for use are equivalent as basis of the medical context." (See table on page 5). |
| Technological Characteristics and Risk Profile Equivalence to Predicate | "The technological characteristics and risk profile of the subject device are equivalent to the predicate device." |
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size for Test Set: Not applicable in the context of an AI model's performance on a dataset. The "tests" performed here are primarily engineering verification and validation (e.g., software testing, electrical safety, bench testing for performance against standards). The document does not specify "sample sizes" for these types of tests (e.g., how many times an electrical test was run, or how many components were tested for sterility).
- Data Provenance: Not applicable in the context of clinical data for AI model evaluation. The "data" here refers to test results from engineering and lab assessments.
3. Number of Experts Used to Establish Ground Truth and Qualifications:
Not applicable. The "ground truth" for this filing is compliance with engineering standards, functional equivalence to a predicate device, and successful verification/validation testing. This is typically established through documented test procedures and adherence to regulatory guidelines, not clinical expert consensus on medical images.
4. Adjudication Method for the Test Set:
Not applicable, as this refers to adjudication of discrepancies in expert readings for clinical test sets.
5. MRMC Comparative Effectiveness Study:
No. The document explicitly states: "Animal and Clinical testing was not conducted." Therefore, no MRMC study comparing human readers with and without AI assistance was performed.
6. Standalone Performance:
Not applicable in the context of an AI algorithm's standalone performance. The device itself (QUATERA 700) performs specific surgical functions. Its "performance" is demonstrated through engineering tests and comparison to a predicate device, not as a standalone diagnostic algorithm.
7. Type of Ground Truth Used:
The "ground truth" for this submission is based on:
- Compliance with recognized international and national standards (e.g., ISO, IEC, FDA guidance documents).
- Successful completion of verification and validation testing protocols.
- Functional equivalence to the legally marketed predicate device, demonstrated through comparative tables of specifications.
8. Sample Size for the Training Set:
Not applicable. This device is a phacofragmentation system, not an AI/machine learning model that undergoes a "training" phase on a dataset of clinical cases.
9. How the Ground Truth for the Training Set Was Established:
Not applicable, as there is no training set for an AI model.
In summary: The K230858 clearance for QUATERA 700 is for a surgical device that has undergone minor software and component changes. The "acceptance criteria" and "study" described in the document are primarily focused on demonstrating continued safety, efficacy, and substantial equivalence to an existing predicate device through engineering verification and validation, rather than a clinical performance study of a novel AI component.
§ 886.4670 Phacofragmentation system.
(a)
Identification. A phacofragmentation system is an AC-powered device with a fragmenting needle intended for use in cataract surgery to disrupt a cataract with ultrasound and extract the cataract.(b)
Classification. Class II.