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The Tag of the RFLS is intended for percutaneous placement in the breast to mark (>30 days) a lesion intended for surgical removal. Using image guidance (such as ultrasound or radiography) or aided by non-imaging guidance (RFLS), the RFID Tag is located and surgically removed with the target tissue. The RFLS is intended only for the non-imaging detection and localization of the Tag that has been implanted in a lesion intended for surgical removal.

The proposed RFID Localization System is a marker-with-detector localization device that employs miniature RFID tags as markers and a hand-held reader that can measure distance to the tag. The RFLS is comprised of a Tag, Tag Applicator/Tag Applicator S, LOCalizer Reader) and LOCalizer Surgical Probe (Surgical Probe). The Tag, when used in conjunction with the Reader and Surgical Probe, can be used as a guide for the surgeon to refer to in the excision of tissue. The RFLS is a prescription device meant only for use by trained professionals.

Since the provided text is a 510(k) summary for a medical device (RFID Localization System), and not a study report for a diagnostic AI/ML device, much of the requested information regarding acceptance criteria for AI/ML performance, sample sizes for AI test/training sets, expert ground truth establishment, and MRMC studies is not directly applicable or present in this document.

The document discusses performance data related to the physical device's function, safety, and compatibility, rather than the performance of an AI model in a diagnostic context. The "RFID Localization System" is a marker-with-detector device, not an AI-powered diagnostic system.

However, I can extract the acceptance criteria and performance data as described for this physical device, along with other relevant information that is present.

Here's the closest possible interpretation of your request based on the provided text, focusing on the device validation rather than AI performance:

Device: RFID Localization System (RFLS)
Intended Use: Percutaneous placement in the breast to mark a lesion intended for surgical removal. Aids in non-imaging detection and localization of the implanted Tag for surgical removal.

1. Table of Acceptance Criteria and Reported Device Performance

For a physical device like the RFLS, "acceptance criteria" relate more to meeting design specifications and safety/performance standards. The document states that the RFLS met the applicable design and performance requirements. The "performance" is demonstrated by passing the various tests listed, affirming its functionality and safety.

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

The document does not specify a "test set sample size" in the context of an AI/ML model. Instead, it refers to various engineering and biological validation tests. For many tests, it explicitly states that the performance was "previously established" through prior 510(k) clearances (e.g., K190932, K181692, K163667, DEN040007/K033440). This indicates that the current submission relies on historical test data and validations, with some additional testing (e.g., multiple tags, updated packaging/shipping in K190932, and the explicitly mentioned electrosurgery and MRI compatibility for K163667, and the current submission's specific software and electrical safety/EMC testing).

• Data Provenance: The document doesn't specify the country of origin for the underlying test data, but it refers to FDA-cleared predicate and reference devices, implying compliance with US regulatory standards. All validations appear to be retrospective or performed as part of device development and previous submissions.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications:

This information is not applicable. This is a physical medical device, not an AI/ML diagnostic algorithm requiring expert "ground truth" for interpretations of medical images or data. The "ground truth" for the device's performance would be established by objective measurements against engineering specifications and validated medical standards.

4. Adjudication Method for the Test Set:

Not applicable. This concept applies to human reader studies often used for AI/ML validation, not the direct performance testing of a physical medical device.

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

Not applicable. This type of study is for evaluating observer performance with or without AI assistance, which is not the subject of this 510(k). The device is a physical marker and localization system, not a diagnostic AI.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance:

Not applicable. This device is not an algorithm; it's a marker-with-detector system that a human surgeon uses. Its performance is inherent in its physical properties and functionality.

7. Type of Ground Truth Used:

The "ground truth" for this device's validation is based on:

• Engineering specifications and design requirements.
• Objective measurements (e.g., distance readings, physical stability, electrical safety parameters).
• Compliance with established international and ASTM standards (e.g., ISO 11607-1, ASTM D4169-09, ISO 10993-1, IEC 60601-1).
• Biocompatibility assessments of materials.
• Validation of sterilization processes.

8. Sample Size for the Training Set:

Not applicable. This device does not use an AI/ML model that requires training data in the conventional sense.

9. How the Ground Truth for the Training Set was Established:

Not applicable, as there is no AI/ML training set. The "ground truth" for the device's design and manufacturing is established through scientific principles, engineering validated methods, and adherence to medical device regulatory standards and best practices.

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The Tag of the RFLS is intended for percutaneous placement in the breast to mark (>30 days) a lesion intended for surgical removal. Using image guidance (such as ultrasound or radiography) or aided by non-imaging guidance (RFLS), the RFID Tag is located and surgically removed with the target tissue. The RFLS is intended only for the non-imaging detection and localization of the Tag that has been implanted in a lesion intended for surgical removal.

The Tag, Tag Applicator, Tag Applicator S, LOCalizer Reader, and LOCalizer Surgical Probe are components of the Health Beacons RFID Localization System (RFLS). The proposed device is a marker-with-detector localization device that employs miniature RFID tags as markers and a handheld reader that can measure distance to the Tag. The Tag, when used in conjunction with the Reader and Surgical Probe, can be used as a guide for the surgeon during the excision of tissue. The RFLS is a prescription device meant only for use by trained professionals, specifically breast surgeons and diagnostic radiologists.

This document describes the 510(k) summary for the Health Beacons, Inc. RFID Localization System (RFLS). However, based on the provided text, there is no detailed information about acceptance criteria and a specific study proving the device meets those criteria, especially in the context of AI assistance or human reader performance improvement.

The document is a 510(k) summary for a medical device (RFID Localization System) intended to mark and locate lesions in the breast for surgical removal. While it mentions performance testing was conducted to support substantial equivalence, it does not provide the specific acceptance criteria or the results from those tests in a format that would allow filling out the requested table or answering many of the follow-up questions.

The device itself is an RFID localization system, which uses miniature RFID tags as markers and a handheld reader to measure distance to the tag. This is a physical localization device, not an AI/software-based diagnostic tool that would typically involve acceptance criteria related to sensitivity, specificity, or human reader improvement with AI assistance.

Therefore, many of the requested details, particularly those pertaining to AI/ML algorithms (e.g., acceptance criteria for diagnostic accuracy, standalone algorithm performance, MRMC studies, training/test set details, ground truth for AI models), are not applicable or not present in this specific 510(k) summary.

Here's what can be extracted and what cannot, based on the provided text:

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

• Not explicitly provided in the document. The document states that "All verification and validation activities identified as necessary were performed... and results demonstrate that predetermined acceptance criteria were met." However, the specific criteria and the numerical performance results are not tabulated or detailed.
• The "performance testing" subsections (VIII) list categories of tests but not acceptance criteria or outcomes. These tests include:
  • Magnetic field emission testing per IEC 60601-1-2:2014
  • Delivery testing
  • Deployment Force testing
  • Needle Penetration Force testing
  • Usability testing

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

• Not provided. The document states "performance testing was provided," but offers no details on sample size, study design (retrospective/prospective), or data provenance.

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

• Not applicable/Not provided. This is relevant for diagnostic AI/ML devices where human expert consensus often establishes ground truth. This device is a physical localization system, not a diagnostic imaging AI.

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

• Not applicable/Not provided. Same reasoning as point 3.

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. This device is a physical localization system; it's not an AI assisting human readers with diagnostic tasks.

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

• Not applicable/Not provided. The device is a "marker-with-detector localization device" that involves a Tag and a Reader/Probe used by a surgeon. There isn't an "algorithm only" component in the sense of a standalone diagnostic AI.

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

• Not explicitly stated for the listed performance tests. For a physical device, ground truth for performance tests would likely involve physical measurements (e.g., actual vs. measured distance, force applied, magnetic field readings).

8. The sample size for the training set:

• Not applicable/Not provided. This device is not an AI/ML algorithm that requires a training set.

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

• Not applicable/Not provided. Same reasoning as point 8.

In summary of the provided text:

This FDA 510(k) summary describes a physical medical device (RFID Localization System), not an AI/ML diagnostic software. The document asserts that performance testing was conducted and met predetermined acceptance criteria, which supported the substantial equivalence determination to a predicate device. However, it does not provide the specific numerical acceptance criteria or the detailed results of those performance tests. Information regarding sample sizes, data provenance, expert involvement for ground truth, or MRMC studies (which are highly relevant for AI/ML diagnostic devices) is absent as these concepts are not directly applicable to the type of device described.

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The Tag of the RFLS is intended for percutaneous placement in the breast to temporarily (

The RFID Localization System (RFLS) is a marker-with-detector localization device that employs miniature RFID tags as markers and a hand-held reader that can measure distance to the tag. The RFLS is comprised of a Tag, Tag Applicator, Reader, and Surgical Probe. The Tag, when used in conjunction with the Reader and Surgical Probe, can be used as a guide for the surgeon during the excision of tissue. The RFLS is a prescription device meant only for use by trained professionals, specifically breast surgeons and diagnostic radiologists.

The provided text details the 510(k) summary for the RFID Localization System (RFLS). While it outlines various performance tests conducted, it does not provide a specific table of acceptance criteria with corresponding reported device performance, nor does it detail a comparative effectiveness study involving human readers (MRMC). The information focuses on demonstrating substantial equivalence to a predicate device through non-clinical testing.

Based on the provided text, here's an attempt to answer the questions, highlighting what information is available and what is not:

Acceptance Criteria and Study for RFID Localization System (RFLS)

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a formal table with specific numerical acceptance criteria and corresponding reported performance for each criterion. It broadly states that "performance testing was conducted to evaluate and characterize the performance of the RFLS."

However, one specific performance metric is mentioned under "Localization Accuracy" in the comparison table:

Other performance aspects mentioned (without specific numerical criteria or reported values):

• RFLS System Verification
• Reader/Probe Design Verification
• Localizer System and Component Accuracy, Repeatability Evaluation
• Test Media Evaluation
• Reader and Surgical Probe Operating Environment Evaluation
• Tissue Marker Migration Evaluation
• Usability Verification and Validation
• Electrosurgical tool compatibility
• EMC/Safety Testing
• Biocompatibility
• Magnetic Resonance Testing
• Packaging Validation
• Sterilization Validation

The document states that these tests "demonstrates the safety of the system for its intended use and confirms the performance of the system for use in intra-operative surgical guidance. Specifically, the performance testing demonstrates the safe use of the system to facilitate intra-operative guided surgical procedures by detecting the presence of the Tag by providing an audible tone which increases pitch and volume with decreased distance, a visible bar indicator, and a measurement readout."

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

The document does not specify the sample sizes used for the various performance tests (e.g., number of RFLS tags tested, number of measurement repetitions for accuracy, etc.).

It also does not detail the data provenance in terms of country of origin or whether the studies were retrospective or prospective. Given that this is a 510(k) summary for a medical device cleared by the FDA (USA), it's highly probable the testing was conducted in the USA, but this is not explicitly stated. The tests are described as "non-clinical testing," implying they were not conducted on human patients.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The document does not mention the use of experts or the establishment of ground truth by experts for the described performance tests. The tests appear to be primarily engineering and bench-top evaluations (e.g., accuracy, repeatability, EMC, sterilization validation) rather than studies requiring expert clinical judgment for ground truth.

4. Adjudication Method for the Test Set

Not applicable, as expert involvement and clinical ground truth establishment are not described for the non-clinical performance tests.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

No, the document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was performed to assess how human readers improve with AI vs. without AI assistance. The RFLS is a localization device, not an AI-assisted diagnostic tool that would typically involve comparative reader studies for diagnostic accuracy.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done

The performance testing appears to be primarily focused on the standalone performance of the device's components and system operation (e.g., localization accuracy of ±7mm, detection of the tag, providing audible tone and visible indicators). The device's function is explicit: "The RFLS is intended only for the non-imaging detection and localization of the Tag that has been implanted in a lesion intended for surgical removal." This implies an "algorithm only" type of measurement in terms of its core function, but it's part of a human-guided surgical procedure.

7. The Type of Ground Truth Used

For "Localization Accuracy (±7 mm)," the ground truth would likely be established by a highly precise physical measurement system (e.g., an optical tracking system, a precisely calibrated measurement jig) during bench testing, rather than expert consensus, pathology, or outcomes data, as it's a direct physical measurement. For other tests like "Sterilization Validation" or "Biocompatibility," the ground truth would be adherence to established standards and test protocols.

8. The Sample Size for the Training Set

The document does not mention a training set. The RFLS is described as a marker-with-detector localization device, relying on RFID technology for detection and distance measurement. This does not suggest the use of machine learning or algorithms that require a distinct "training set" in the conventional sense (e.g., for image classification or prediction). The device's function appears to be based on direct physical principles of radiofrequency wave detection rather than learned patterns from a training dataset.

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

Not applicable, as a training set is not mentioned.

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