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The Konan Kerato Analyzer ("EKA") is a specular microscope used to make cell counts of preserved corneas in eye banks and to measure the thicknesses of the corneas without removing the corneas from their storage vials.

The Konan Kerato Analyzer ("EKA") is a specular microscope used to make cell counts of prescrved corneas in eye banks and to measure the thicknesses of the corneas without removing the corneas from their storage vials. The basic structure of the EKA is similar to that of an inverted laboratory microscope. With the EKA, all focusing is done manually by the operator. For the EKA, vials containing the corneas are placed in a receptacle in the unit.

The Konan Kerato Analyzer (EKA) is a specular microscope intended to make cell counts of preserved corneas in eye banks without removing the corneas from their storage vials.

1. Acceptance Criteria and Reported Device Performance:

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

The document explicitly states "Cell counts on eye bank samples were done with the Noncon Robo and the EKA." However, it does not specify the sample size of eye bank samples used for this comparison.

The data provenance is not explicitly stated as retrospective or prospective, nor is the country of origin of the data mentioned.

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

The document does not detail the use of experts to establish ground truth for a test set. The comparison was made directly between the EKA and a predicate device (Noncon Robo). It's implied that the predicate device's measurements serve as the reference or "ground truth" for comparison.

4. Adjudication Method for the Test Set:

No adjudication method is mentioned, as the comparison was direct between the two devices.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done:

No, an MRMC comparative effectiveness study was not done. The study focused on the agreement between the EKA and a predicate device, not on human reader performance with or without AI assistance.

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

Yes, a standalone performance assessment was done. The EKA, as a device for automated cell counting, was evaluated on its own ability to perform these counts and was compared directly to a predicate device, without a human operator's interpretation as part of the core performance metric. While an operator manually focuses the EKA, the cell counting itself is an automated function of the device being assessed.

7. The Type of Ground Truth Used:

The ground truth for the comparison was established by the measurements obtained from a legally marketed predicate device, the Konan Noncon Robo. The assumption is that the Noncon Robo provides accurate cell counts.

8. The Sample Size for the Training Set:

The submission document does not specify a separate training set or its sample size. The focus is on the performance comparison of the new device (EKA) against a predicate device. This suggests a direct validation approach rather than a machine learning model that would require a distinct training set.

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

Not applicable, as a separate training set with its own ground truth establishment is not described in this 510(k) summary. The study is a comparative performance assessment against an existing device rather than the development and validation of a new algorithm requiring a training phase.

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