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The Beacon Tissue Marker is indicated for use to radiographically mark soft tissue during a surgical procedure or for future surgical procedures.

The proposed Beacon Tissue Marker consists of a radiographic soft tissue marker and the delivery system. The proposed Beacon Tissue Marker is a sterile, single patient use, PEKK discrete marker that is visible on standard radiographs (x-ray, mammography) as well as ultrasound, and Magnetic Resonance Imaging (MRI) at up to 3.0 Tesla field strength. The proposed Beacon Tissue Marker is placed into soft tissue during open, percutaneous, or endoscopic procedures to radiographically mark a surgical location.

The proposed Beacon Tissue Marker is comprised of Oxford Performance Materials (OPM) OXPEKK-IG200 filled with Barium Sulfate (Polyetherketoneketone with 20% BaSO4 by wt%). OXPEKK-IG200 is a radiolucent material and serves as the carrier for the radiopaque BaSO4.

The delivery system is a sterile, single patient use, pre-loaded delivery system incorporating the Beacon Tissue Marker. The delivery system consists of a cannula with a handle, a push rod with a plunger, tabs to retain the tissue marker, and a tip cover. The tissue marker is retained within the delivery system until placement is desired, where it is delivered through the end port by fully depressing the plunger into the handle. The Beacon Tissue Marker delivery system is used to place the Beacon Tissue Marker into soft tissue during open, percutaneous, or endoscopic procedures to radiographically mark a surgical location. The delivery system device has a beveled 12 cm / 14 gauge needle with 1 cm depth marks and a plunger.

Here's an analysis of the acceptance criteria and study for the Beacon Tissue Marker, based on the provided 510(k) summary:

Device: Beacon Tissue Marker™ (Implantable Clip)

1. Table of Acceptance Criteria and Reported Device Performance

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

The 510(k) summary does not specify the exact sample sizes used for each of the non-clinical tests (e.g., deployment force, marker expulsion, etc.). It only broadly states that "All testing met pre-defined acceptance criteria."

The data provenance is also not explicitly stated in terms of country of origin or whether the studies were retrospective or prospective. Given that this is a non-clinical, bench-top testing summary, it would typically be prospective testing conducted in a laboratory setting.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not applicable and not provided in the 510(k) summary. The testing described for this device is non-clinical, engineering-based performance testing (e.g., deployment force, bond strength, dimensions). There is no mention of medical image interpretation or human subject studies that would require experts to establish a "ground truth" for diagnostic or clinical performance.

4. Adjudication Method for the Test Set

This information is not applicable and not provided. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies involving human interpretation or subjective assessments, which are not described in the non-clinical testing for this device.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done, nor is it relevant for the type of device and testing described. MRMC studies are used to assess the impact of a medical device (often AI-assisted diagnostic tools) on human reader performance in interpreting medical images or data. The Beacon Tissue Marker is an implantable clip for marking soft tissue, and its performance is evaluated through engineering and biocompatibility testing, not clinical diagnosis or interpretation by human readers.

6. Standalone (Algorithm Only Without Human-in-the-loop Performance) Study

No. A standalone algorithm performance study was not done. This device is a physical implantable marker and does not involve any algorithms or artificial intelligence for its function or evaluation in the context of this 510(k) summary.

7. Type of Ground Truth Used

The "ground truth" for the non-clinical testing consisted of engineering specifications and predefined performance thresholds. For example:

• Deployment force might have a specified range (e.g., 5N-15N).
• Marker retention might be evaluated by ensuring the marker does not prematurely release under specified forces.
• Dimensions would be compared against design specifications.
• Package integrity would be assessed against industry standards for sterility barrier and leak protection.

There is no mention of expert consensus, pathology, or outcomes data being used as ground truth for this type of non-clinical device testing.

8. Sample Size for the Training Set

This information is not applicable and not provided. Since the device does not involve algorithms or AI, there is no "training set" in the context of machine learning. The testing performed is to validate the physical and functional aspects of the device against engineering requirements.

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

This information is not applicable (as there is no training set).

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[Trade Name] Preloaded Tissue Marker is indicated for use to radiographically mark soft tissue at the surgical site during a surgical procedure or for future surgical procedures.

[Trade Name] Preloaded Tissue Marker Device is a sterile, nonpyrogenic, single use tissue marker consisting of pyrolytic carbon coated zirconium oxide discrete marker that is visible on standard radiographs (x-ray, mammography, fluoroscopy, kV, and CT) as well as ultrasound and Magnetic Resonance Imaging (MRI) incorporated into lyophilized BiomarC Delivery Gel. The [Trade Name] Preloaded Tissue Marker is placed into soft tissue during open, percutaneous, or endoscopic procedures to radiographically mark a surgical location.

This device is a tissue marker, not an AI/ML device, so many of the requested elements pertaining to AI/ML device studies (e.g., test set, training set, ground truth experts, MRMC study, standalone performance) are not applicable or detailed in the provided documents. The provided text outlines a 510(k) summary for a medical device called the "[Trade Name] Preloaded Tissue Marker Device" and its associated FDA clearance letter.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Not applicable in the context of an AI/ML device. For this physical medical device, specific sample sizes for each type of testing (biocompatibility, sterility, etc.) are not provided in the summary. Data provenance is implied to be from laboratory and engineering testing.

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

• Not applicable as this is not an AI/ML device study.

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

• Not applicable as this is not an AI/ML device study.

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, an MRMC comparative effectiveness study was not done, as this is not an AI/ML device.

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

• No, as this is not an AI/ML device. Performance was evaluated for the device itself through various engineering and scientific tests.

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

• For this type of medical device, "ground truth" refers to established scientific and engineering standards and tests. The "ground truth" for the acceptance criteria was based on:
  • Predicate Device Equivalence: The performance and characteristics of the already cleared predicate devices.
  • Standardized Testing: Biocompatibility standards, sterility validation protocols, distribution simulation standards, and shelf life testing protocols.
  • Risk Analysis: Failure Modes and Effects Analysis (FMEA).

8. The sample size for the training set:

• Not applicable, as this is not an AI/ML device.

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

• Not applicable, as this is not an AI/ML device.

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