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Patient Specific Cranial implants are intended for the replacement of bony voids in the cranial skeleton.

The Kelyniam Custom Skull Implant (CSI) is designed individually for each patient to correct defects in cranial bone. The Kelyniam Custom Skull Implant (CSI) is individually sized and shaped implantable prosthetic cranioplasty plates intended to fill defects in a specific patient's cranial skeleton. The implants are composed of PEEK-OPTIMA, and are fabricated using the patient's CT imaging data. The implants are provided with .125" diameter pressure relief holes, equally spaced over the contour of the implant with .625″ centerline spacing and a minimum of .500″ edge margin. The devices are provided non-sterile for sterilization prior to implantation and are attached to the native bone with commercially available cranioplasty fasteners. This product is a single use device.

The provided text is a 510(k) summary for the Kelyniam Custom Skull Implant (CSI) and discusses substantial equivalence to predicate devices, but it does not describe acceptance criteria or a study that specifically proves the device meets acceptance criteria in the manner typically expected for AI/software-based medical devices (e.g., performance metrics against a clinical ground truth).

Instead, the submission appears to be focused on demonstrating substantial equivalence to existing legally marketed devices based on intended use, material, technical specifications, and sterilization. The "study" mentioned directly relates to a biocompatibility test (Toxicity), not a performance study in the context of diagnostic accuracy or a human-AI comparison.

Therefore, many of the requested sections will be answered as "Not Applicable" or "Not Provided" based on the content of the document.

Here's a breakdown based on the provided text:

Acceptance Criteria and Device Performance

Study Information (Based on provided document)

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

   • Not Provided / Not Applicable: The document describes a biocompatibility (Toxicity) test using Limulus Amebocyte Lysate (LAL). This is a laboratory test on the device material, not a clinical study involving a "test set" of patient data or cases. The sample size would refer to the number of devices tested or the replicates of the LAL test, which is not specified but is typically much smaller than a clinical sample size. No country of origin or retrospective/prospective status is relevant or provided for this type of test.

2. 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 / Not Provided: Ground truth in the context of clinical performance (e.g., diagnostic accuracy) is not relevant to the LAL toxicity test. The "ground truth" for the LAL test is the regulatory standard for endotoxin levels.

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

   • Not Applicable / None: No adjudication method is relevant for a biocompatibility test.

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: No MRMC study was done, as this device is a physical implant, not an AI-assisted diagnostic 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)

   • Regulatory Standard for Endotoxin Levels: For the toxicity test, the "ground truth" is the established regulatory limit for endotoxin levels in medical devices in contact with cerebrospinal fluid.

7. The sample size for the training set

   • Not Applicable: This is a physical medical device, not a machine learning algorithm that requires a training set. The device is custom-manufactured for each patient based on their CT imaging data, but "training set" is not relevant here.

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

   • Not Applicable: As there is no training set for an algorithm, this question is not relevant.

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