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The Parcus MiTi Suture Anchors are indicated for attachment of soft tissue to bone. This product is intended for the following indications:

• Shoulder Rotator Cuff Repair, Acromioclavicular Separation Repair, Bankart Lesion Repair, Biceps Tenodesis, Capsular Shift or Capsulolabral Reconstruction, Deltoid Repair, SLAP Lesion Repair.
• Knee Medial Collateral Ligament Repair, Lateral Collateral Ligament Repair, Posterior Oblique Ligament Repair. Extra Capsular Reconstruction, Iliotibial Band Tenodesis, Patellar Ligament and Tendon Avulsion Repair.
• Lateral Stabilization, Medial Stabilization, Midfoot Reconstruction, Achilles Foot/Ankle Tendon Repair, Hallux Valgus Reconstruction, Metatarsal Ligament Repair.
• Elbow Tennis Elbow Repair, Biceps Tendon Reattachment.
• Hand/Wrist Scapholunate Ligament Reconstruction, Ulnar or Radial Collateral Ligament Reconstruction, TFCC.

The Parcus MiTi Suture Anchor is a threaded, tapered fastener for use in attachment of soft tissue to bone. The device is made from a Titanium alloy, Ti-6Al-4V ELI (ASTM F136). The product family includes devices that come preloaded with either one or two sutures between #3-0 and #2 in size either with or without attached needles, and a driver, and is available in three different diameters, 2.0mm, 2.5mm and 3.5mm. The 2.0mm anchor is offered in the following suture configurations: two #3-0 and one or two #2-0 sutures. The 2.5mm anchor is offered in the following suture configurations: two #3-0, two #2-0 and one #2 sutures. The 3.5mm anchor is offered in the following suture configurations: two #3-0, two #1 and two #2 sutures. All configurations are offered in multiple color variations and with or without attached needles.

The provided text describes a 510(k) summary for the Parcus MiTi Suture Anchor, focusing on its substantial equivalence to predicate devices rather than a detailed study demonstrating quantitative acceptance criteria. Therefore, several of the requested sections (sample size, expert ground truth, adjudication method, MRMC studies, specific acceptance criteria table, training set details) cannot be fully populated from this document.

However, based on the Summary Performance Data section, we can infer the acceptance criteria are related to mechanical performance (pull-out strength and insertion torque) and that the device meets these by demonstrating no significant difference compared to predicate devices.

1. Table of acceptance criteria and the reported device performance

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

• Sample Size: Not specified in the document.
• Data Provenance: Not specified, but the testing would likely have been conducted by Parcus Medical, LLC (based in Sturgeon Bay, WI, USA) or a contracted lab. The study is prospective in nature as it involves physical testing of the device.

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)

• This information is not applicable to this type of mechanical device testing. "Ground truth" in this context is the physically measured pull-out strength and insertion torque.

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

• This information is not applicable to objective mechanical device testing.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed. This type of study is relevant for diagnostic or AI-assisted interpretation devices, not for a physical medical device like a suture anchor.

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

• Yes, the performance data provided is for the device as a standalone product. The "pull out strength and insertion torque was measured for the Parcus MiTi Suture Anchors" directly, and compared to predicate devices.

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

• The ground truth for the test set was objective physical measurements of pull-out strength and insertion torque obtained through laboratory testing.

8. The sample size for the training set

• This concept is not applicable as this is not an AI/ML device requiring a training set.

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

• Not applicable.

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