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The ACCUSYTE™ 3D Fiducial Markers are used to mark the location of a tumor cavity after the tumor has been removed. In addition, the Markers are indicated on situations where soft tissue needs to be marked for future medical procedure such as subsequent Radiation Therapy.

The ACCUSYTE™ 3D Fiducial Marker is an implantable marker comprised of an absorbable suture (polylactic acid) component which absorbs completely in less than one year, and a permanent component, a Platinum or Gold Marker attached to the suture by a crimping operation similar to the operation use to attach the Stainless-Steel Needle. The ACCUSYTE™ 3D Fiducial Marker is provided Sterile for single use and is implantable.

The provided text describes a 510(k) submission for the ACCUSYTE™ 3D Fiducial Marker, aiming to establish substantial equivalence to predicate devices. The study focuses on demonstrating the device's technical characteristics and performance, particularly its visualization compatibility and MRI safety. However, it does not contain the information needed to fully answer all aspects of your request, especially regarding specific acceptance criteria, detailed study designs for those criteria, or the role of AI.

Here's an analysis of the available information:

This document describes a medical device called the ACCUSYTE™ 3D Fiducial Marker. It is a K180027 510(k) Pre-market Notification from 2018 for a Medical Charged-Particle Radiation Therapy System, and thus the description below is limited purely to the device as presented in the document.

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state formal acceptance criteria with specific thresholds for visualization or other performance metrics. Instead, it describes performance data gathered to demonstrate the device's capabilities and substantial equivalence to predicate devices.

• Radiographic Imaging 6-8 weeks after implantation.
• Mammography imaging after 1-year post implantation.

(No specific quantitative clarity metrics or acceptance thresholds are provided, only that it was "clear visualization.") |
| MRI Safety | MR Conditional:

• Static magnetic field of 1.5-Tesla or 3-Tesla.
• Maximum spatial gradient magnetic field of 4,000-gauss/cm (40-T/m).
• Maximum MR system reported, whole body averaged specific absorption rate (SAR) of 2-W/kg in the Normal Operating Mode.
• Expected to produce a maximum temperature rise of ≤2°C after 15-minutes of continuous scanning at 3 Tesla. |
  | MRI Image Artifact | - Image artifact not expected to extend more than 10-mm from the device when imaged with a gradient echo pulse sequence and a 3-Tesla MRI system. |
  | Absorbable Suture Testing| Performed on the Absorbable Suture component (K130735):
• Bacterial Endotoxin (USP Pharmacopeia ) - Pyrogenicity.
• Biocompatibility (ISO-10993) - suture component - Implant.
• Physical Testing - USP 30

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

The device is a sterile, single-patient-use, barium sulfate infused polypropylene suture that is radiopaque using standard radiographs (x-ray, mammography). The device is placed into soft tissue sites during open, percutaneous, or endoscopic procedures and standard surgeon's knots are tied to quickly and inexpensively mark the soft tissue so that the integrity and location of the marked soft tissue can be evaluated.

This document is a 510(k) summary for a medical device called a "Radiopaque Tissue Marker." It outlines the device's characteristics, its intended use, and the non-clinical testing performed to establish substantial equivalence to a predicate device.

Here's an analysis based on the provided text, addressing your questions:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state "acceptance criteria" in a quantitative format with corresponding reported performance metrics for the device. Instead, it describes non-clinical tests performed to demonstrate substantial equivalence to a predicate device. The performance is assessed against the predicate device, not against specific, pre-defined numerical thresholds for accuracy, sensitivity, or specificity.

However, based on the non-clinical testing mentioned, we can infer performance aspects:

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

The document describes non-clinical laboratory testing. It does not mention a "test set" in the context of patient data, nor does it specify any sample sizes for patients or data provenance (country of origin, retrospective/prospective). The testing involved physical devices and materials, not patient data in the way one would analyze for an AI algorithm.

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 is not applicable to the study described. The study involves non-clinical testing of a physical device. There is no "ground truth" establishment in the context of expert consensus on medical images or diagnoses.

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

This is not applicable for the study described. There is no "test set" of patient data requiring adjudication of ground truth by multiple experts.

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 MRMC study was performed. The device is a physical radiopaque tissue marker, not an AI algorithm. Therefore, an "effect size of human readers improve with AI vs without AI assistance" is not relevant.

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

No standalone algorithm performance study was done. The device is a physical radiopaque tissue marker, not an AI algorithm.

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

This is not applicable for the study described. The "ground truth" for non-clinical device testing would be the physical and chemical properties of the materials and their behavior under controlled laboratory conditions, as measured by standard testing methods (e.g., ISO 10993 for biocompatibility, specific imaging protocols for radiopacity). It is not based on expert consensus, pathology, or outcomes data related to patient diagnosis.

8. The sample size for the training set

This is not applicable. The device is a physical medical device, not an AI algorithm that requires a "training set."

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

This is not applicable. There is no AI algorithm or training set associated with this device.

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