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The EK Delivery Device is to be used by ophthalmic surgeons trained in Endothelial Keratoplasty (EK) procedures and trained in the use of the EK Delivery Device as:

• An aid facilitating the insertion of donor corneal posterior lamellar endothelial graft of 100 – 220 µm of thickness into the anterior chamber of the eye during endothelial keratoplasty.
• For use in a 5.1 mm or larger incision and a maximum donor tissue diameter of ≤ 8.5 mm)
• For loading and storage of donor tissue during transport to the surgeon by trained eye bank technicians, and for storage of donor tissue for up to a maximum of 72 hours.

The Endothelial Keratoplasty Injector is a single-use, disposable device that allows an ophthalmic surgeon to insert a previously prepared disc of posterior donor cornea into the eye of a recipient patient through a small incision during a posterior comeal transplant surgical procedure. The function of the device is to insert the flat disc of donor comeal tissue within a cylindrical tube that is sized to fit into 5.1 mm or larger corneal or scleral incision, and to pull or push this donor corneal tissue into the anterior chamber of the eye as part of a Endothelial Keratoplasty procedure. This device was designed to insert donor posterior corneal tissue ≤ 8.5 mm in diameter, 100um to 220um in thickness, through a 5.1 mm or larger corneal incision.

The EK Delivery device consists of four components: (1) the Trocar which is used to hold the graft material and introduce it into the anterior chamber of the recipient eye, (2) the Trocar Holder, which is used to close the proximal end of the Trocar and as an ergonomic handle to aid the surgeon handling the device, (3) the Injector Assembly, which is a plunger to push the endothelial keratoplasty tissue out of the Trocar and into the anterior chamber of the recipient eye, and (4) End Plug used during shipping. Delivers a circular endothelial tissue button in a rolled configuration.

Here's an analysis of the provided 510(k) summary for the TDAK Medical, Inc. EK Delivery Device, focusing on acceptance criteria and study details:

Device: TDAK Medical, Inc. EK Delivery Device

1. Acceptance Criteria and Reported Device Performance

The provided 510(k) summary is for a Class I (reserved) medical device, specifically an Endothelial Keratoplasty (EK) Injector. For such devices, the "acceptance criteria" are primarily related to meeting performance specifications and demonstrating substantial equivalence to a predicate device, rather than statistical performance metrics (like sensitivity/specificity) typically seen in diagnostic AI/ML devices.

The acceptance criteria are inferred from the comparison table and the description of testing performed to demonstrate equivalence and safety.

Study Information

The document describes pre-market testing to demonstrate substantial equivalence to a predicate device (EndoSerter™ K090626), rather than a clinical efficacy study with human subjects. The studies are primarily engineering and bench-top tests.

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not explicitly stated for each test (e.g., how many devices were tested for mechanical strength, or how many tissue samples for tissue handling). These would typically be detailed in the full test reports, which are not part of this summary document.
   • Data Provenance: The studies were conducted by TDAK Medical, Inc. The nature of the device (a delivery tool) means the "data" is primarily performance data from pre-clinical, bench-top testing, not clinical data from patients or tissue banks in a specific country. The studies are retrospective in the sense that they are validations conducted before market entry.

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

   • This question is not applicable in the context of this device. The "ground truth" for a mechanical device like this is whether it performs its intended function (e.g., inserts tissue without damage, maintains sterility, has adequate mechanical strength). This is established through engineering specifications, material science, and performance testing, not through expert human interpretation or diagnosis. No "test set" in the diagnostic sense is described that would require expert ground truth.

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

   • Not applicable. Adjudication methods are used in studies involving human interpretation or clinical endpoints (e.g., a panel of radiologists reviewing images). This is a device for physical delivery of tissue.

4. 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 not an AI/ML device, nor is it a diagnostic device that involves human readers interpreting cases. It is a surgical delivery tool.

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

   • Not applicable. This is a physical medical device, not an algorithm.

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

   • The "ground truth" for this device's performance is based on established engineering principles, material standards, and functional testing against design specifications. For example:
     • Mechanical Strength: Demonstrated by testing to failure or against defined load limits.
     • Tissue Handling: Demonstrated by successful insertion of donor tissue surrogates or actual tissue samples without damage, and maintenance of tissue viability (implied by "Tissue Handling and Stability" testing and 72-hour storage claim).
     • Biocompatibility: Established through standardized in vitro and/or in vivo tests to ensure the device materials do not cause adverse biological reactions.
     • Sterilization: Validated using methods like "Sterilization Validation" to ensure a certain sterility assurance level (SAL).

7. The sample size for the training set:

   • Not applicable. This is not an AI/ML device, so there is no concept of a "training set" for an algorithm.

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

   • Not applicable.

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