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The PercuNav Image Fusion and Interventional Navigation System is a stereotaxic accessory for computed tomography (CT), cone beam CT (CBCT), magnetic resonance (MR), ultrasound (US), and positron emission tomography (PET). CT, Ultrasound, PET, and MR may be fused in various combinations, such as CT with ultrasound, and so on. It may include instrumentation to display the simulated image of a tracked insertion tool such as a biopsy needle or probe on a computer monitor screen that shows images of the target organs and the projected future path of the interventional instrument. The Perculav Interventional Navigation System is intended for treatment planning and to assist guidance for clinical, interventional, or diagnostic procedures in a clinical setting.

The PercuNav Image Fusion and Interventional Navigation System is also intended to supplement live imaging in clinical interventions to determine the proximity of one device relative to another.

The PercuNav Image Fusion and Interventional Navigation System is not intended to be the sole guidance for any procedures that can be guided by the PercuNav Image Fusion and Interventional Navigation System adjunctively include, but are not limited to, the following:

• · Image fusion for diagnostic clinical examinations and procedures
• · Soft tissue biopsies
• · Soft tissue ablation
• Bone ablation
• · Bone biopsies
• · Nerve blocks and pain management
• · Drainage placements

The PercuNav Image Fusion and Interventional Navigation System provides image-guided diagnostic and intervention support that enables fusion of diagnostic images and guidance of tracked instruments to physician-defined targets. The target can be indicated either pre-procedurally or intra-procedurally, either using images or relative to an indicated position on the patient. The system transforms two-dimensional patient images into dynamic representations that can be fused with live ultrasound or other previously acquired images. Those two-dimensional patient images, or scan sets, are derived from Ultrasound, CT, PET, PET/CT, and MRI. The resulting dynamic representation supports diagnostic review and instrument navigation.

The user-assisted Ablation Planning software tool enhancement is to aid the user when placing the ablation tip using a computer algorithm to maximize the spatial overlap between the ablation zone volume and the tumor contour.

The user-assisted Co-Registration software tool is to aid the user in co-registering between two different CT series from the same patient using a computer algorithm to create an image that forms the basis to be applied to the various CT sets for landmark registration.

Here's a breakdown of the acceptance criteria and study information for the Philips PercuNav Image Fusion and Interventional Navigation System, based on the provided FDA 510(k) summary:

This submission focuses on software enhancements: user-assisted Ablation Planning and user-assisted Co-Registration. The core PercuNav system was previously cleared (K201053).

1. Table of acceptance criteria and the reported device performance:

The document states: "For feature testing, all pre-determined acceptance criteria were met. Results of these tests show that the proposed PercuNav Image Fusion and Interventional Navigation System meets its intended use."

Unfortunately, the specific numerical acceptance criteria (e.g., accuracy thresholds, success rates) and the detailed reported device performance metrics are not provided in this 510(k) summary. The document only offers a general statement of compliance. This is common in 510(k) summaries, which aim to provide a high-level overview rather than the detailed test reports themselves.

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

• Sample Size for Test Set: Not explicitly stated. The document refers to "non-clinical bench performance testing." This typically involves a set of predefined test cases or datasets, but the number is not specified.
• Data Provenance: The document does not specify the country of origin of the data. It mentions "internal processes" and "non-clinical bench performance testing," suggesting these tests were conducted by Philips. The data would likely be retrospective artificial or representative data used for bench testing, not patient-specific prospective data.

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

• Number of Experts: Not explicitly stated. Given the nature of "non-clinical bench performance testing" for software features that provide a "proposed starting point" for user acceptance/manipulation, the ground truth may have been established through a combination of:
  • Pre-defined gold standard data or simulations.
  • Internal expert review by engineers or clinical specialists at Philips during development and testing.
• Qualifications of Experts: Not explicitly stated. However, for medical device software, it's expected that experts involved in ground truth establishment would include those with relevant clinical (e.g., radiologists, interventionalists) or engineering expertise.

4. Adjudication method for the test set:

• Adjudication Method: Not explicitly stated. Given that the software "proposes an option to the user that they then can manipulate or accept," the "adjudication" (or validation process) likely involved demonstrating that the proposed solutions were reasonable and effective starting points, and that users could successfully refine them to reach desired outcomes. This would be part of the "non-clinical bench performance testing."

5. If a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance:

• MRMC Study: No, an MRMC comparative effectiveness study was not explicitly done or required for this 510(k) submission. The document states: "The proposed PercuNav Image Fusion and Interventional Navigation System did not require clinical data for determination of substantial equivalence."
• Effect Size: Therefore, no effect size for human reader improvement with AI assistance vs. without AI assistance is reported. This submission is for enhancements to a system that aids a human user, not a standalone diagnostic AI aiming to replace or significantly augment diagnostic interpretation in a MRMC setting. The enhancements are framed as workflow improvements rather than a direct comparative effectiveness study on diagnostic accuracy.

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

• Standalone Performance: While the algorithms themselves (for ablation planning and co-registration) operate in a "standalone" fashion to generate their proposed solutions, the overall system is designed for human-in-the-loop performance. The software "proposes an option to the user that they then can manipulate or accept." Therefore, the "performance" validated was likely the utility and accuracy of these proposed initial solutions as input to a human user's workflow, not as a final, automated decision-maker.

7. The type of ground truth used:

• Type of Ground Truth: The document does not explicitly state the type of ground truth. Given the "non-clinical bench performance testing" for software features that optimize spatial overlap (ablation planning) or co-registration fidelity, the ground truth would likely be pre-defined, gold-standard computational models, synthetic data, or carefully curated clinical image datasets with known geometric relationships and tumor contours. These would be used to evaluate the accuracy of the algorithms' proposed solutions.

8. The sample size for the training set:

• Sample Size for Training Set: Not stated. Training set details are typically not included in 510(k) summaries, especially for software enhancements that might leverage existing or established algorithms rather than entirely new, deep learning models requiring vast training datasets.

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

• How Ground Truth for Training Set was Established: Not stated. As the sample size for the training set is not provided, neither is the method for establishing its ground truth.

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The PerculVav system is a stereotaxic accessory for computed tomography (CT), cone beam CT (CBCT), magnetic resonance (MR), ultrasound (US), and positron emission tomography (PET). CT, Ultrasound, PET, and MR may be fused in various combinations, such as CT with MR, MR with ultrasound, and so on. It may include instrumentation to display the simulated image of a tracked insertion tool such as a biopsy needle or probe on a computer monitor screen that shows images of the target organs and the current and the projected future path of the interventional instrument. The PerculNav system is intended for treatment planning and to assist guidance for clinical, interventional, or diagnostic procedures in a clinical setting.

The PercuNav system is also intended to supplement live imaging in clinical interventions to determine the proximity of one device relative to another.

The PercuNav system is not intended to be the sole guidance for any procedure. Procedures that can be guided by the PercuNav system adjunctively include, but are not limited to, the following:

• · Image fusion for diagnostic clinical examinations and procedures
• · Soft tissue biopsies
• · Soft tissue ablation
• Bone ablation
• · Bone biopsies
• · Nerve blocks and pain management
• · Drainage placements

The Philips PercuNav Image Fusion and Interventional Navigation System provides image-guided diagnostic and intervention that enables fusion of diagnostic images and guidance of tracked instruments to physiciandefined targets. The target can be indicated either pre-procedurally or intra-procedurally, either using images or relative to an indicated position on the patient. The system transforms two-dimensional patient images into dynamic representations that can be fused with live ultrasound or other previously acquired images. Those two-dimensional patient images, or scan sets, are derived from Ultrasound, CT, PET, PET/CT, and MRI. The resulting dynamic representation supports diagnostic review and instrument navigation.

The purpose of this Traditional 510(K) Pre-market Notification is to introduce a new semi-automated visualization tool entitled "Tumor Contouring" to the current PercuNav software system. The Tumor Contouring visualization tool is designed to aid the end user in the planning and targeting of lesions, structures, and other regions of interests prior to an interventional procedure, soft tissue ablation, etc. The Tumor Contouring tool allows the end user to generate and modify a 3D contour around a region or soft tissue structure of interest and then this contour, once accepted by the user, can be visualized and dynamically reformatted and fused in various imaging combinations for later procedures.

The provided text includes a 510(k) summary for the Philips PercuNav Image Fusion and Interventional Navigation System with a new "Tumor Contouring" visualization tool. However, it does not contain explicit acceptance criteria thresholds or detailed study results for the device's performance, as would typically be found in a clinical study report.

The document focuses on demonstrating substantial equivalence to predicate devices through technological comparison and non-clinical testing (software verification, risk analysis, product specifications, design reviews). It explicitly states: "The subject Philips PercuNav System did not require clinical data in order to make a determination for substantial equivalence when compared to the predicate device(s)."

Therefore, based on the provided text:

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

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

No specific sample size for a "test set" (in the context of clinical or performance data) or data provenance is mentioned. The testing described is primarily internal software verification.

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):

Not applicable. The document does not describe a study involving expert-established ground truth for performance evaluation of the Tumor Contouring tool.

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

Not applicable. No such adjudication method is mentioned as part of the described 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 MRMC comparative effectiveness study was done or reported in this document.

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

The "Tumor Contouring" tool is described as "semi-automated," generating a preliminary border that the user must modify and review. This indicates it is not a standalone algorithm without human-in-the-loop performance. The document does not describe a standalone performance study.

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

Not applicable. The document focuses on software verification against specifications and user needs rather than clinical ground truth for the Tumor Contouring feature. The closest mention of "ground truth" would be the implicit correctness against internal software design specifications.

8. The sample size for the training set:

Not applicable. There is no mention of a training set as the device's submission did not involve clinical data or machine learning model training in the context of this summary.

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

Not applicable, as no training set is described.

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The PercuNav system is a stereotaxic accessory for computed tomography (CT), magnetic resonance (MR), ultrasound (US), and positron emission tomography (PET). CT, Ultrasound, PET, and MR may be fused in various combinations, such as CT with MR, MR with ultrasound, and so on. It may include instrumentation to display the simulated image of a tracked insertion tool such as a biopsy needle or probe on a computer monitor screen that shows images of the target organs and the current and the projected future path of the interventional instrument. The PercuNav system is intended for treatment planning and guidance for clinical, interventional, or diagnostic procedures. The PercuNav system also supports an image-free mode in which the proximity of the interventional device is displayed relative to another device.

The PercuNav system is intended to be used in interventional and diagnostic procedures in a clinical setting. The PercuNav system is also intended for use in clinical interventions to determine the proximity of one device relative to another.

Example procedures include, but are not limited to, the following:

• · Image fusion for diagnostic clinical examinations and procedures
• · Soft tissue biopsies (liver, lung, kidney, breast, pancreas, bladder, adrenal glands, lymph node, mesentery, and so on.)
• · Soft tissue ablation (liver, kidney, breast, pancreas, lung, and so on)
• Bone ablations
• Bone biopsies
• · Nerve blocks and pain management
• Drainage placements
• Tumor resections

The proposed PercuNav provides image-guided diagnostic and intervention that enables fusion of diagnostic images and guidance of tracked instruments to physician-defined targets. The target can be indicated either pre-procedurally or intra-procedurally, either using images or relative to an indicated position on the patient.

The proposed PercuNav provides real-time, three-dimensional visualization and navigation tools for all stages of diagnosis and intervention, including pre-procedure planning and procedure navigation. The system transforms two-dimensional patient images into dynamic representations that can be fused with live ultrasound or other previously acquired images. Those two-dimensional patient images, or scan sets, are derived from Ultrasound, CT, PET, PET/CT, and MRI. The resulting dynamic representation supports diagnostic review and instrument navigation.

The PercuNav system performs spatial mapping from one image space to another image space or from image space to physical space (registration), allowing the physician to correlate scan sets with each other and to the patient. The system facilitates minimally invasive diagnostic and interventional procedures.

Features include the following:

• Multiple Applications: The PercuNav system supports multiple applications and can be used for ablations, biopsies, and other diagnostic and guidance procedures.
• Multiple Modalities: The PercuNav system works with images from multiple modalities, including but not limited to CT, MR, PET, and ultrasound.

The Philips PercuNav Image Fusion and Interventional Navigation system, as described in the provided 510(k) summary, adds automatic MR/ultrasound registrations as a new technological characteristic compared to its predicate device. The performance data presented focuses on the accuracy of these new auto-registration features.

Here's a breakdown of the acceptance criteria and the study proving the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document states that "The accuracy test was done for the liver vessel and liver surface auto registrations." However, it does not specify the sample size used for this testing.

Regarding data provenance, the document does not explicitly state the country of origin of the data. Given Philips Ultrasound Inc. is in Bothell, WA, USA, and the FDA is a U.S. regulatory body, it's highly probable the data is primarily from the United States. The study is a non-clinical performance test, and it's implied to be retrospective as it's a test of the developed feature, not a prospective clinical trial.

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

The document does not specify the number of experts used or their qualifications for establishing ground truth. The ground truth for the accuracy test is implicitly the "existing manual registration method available on the currently cleared PercuNav (K132087)." This suggests that the accuracy of the manual registration was used as the benchmark against which the auto-registrations were compared, rather than a separate expert-derived ground truth.

4. Adjudication Method for the Test Set

The document does not describe any explicit adjudication method. The comparison is between the automated process and an existing manual process, implying the manual process provided the reference.

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

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "The proposed PercuNav did not require clinical study, since substantial equivalence to the currently marketed predicate devices... was demonstrated with the following attributes... Non-clinical performance testing." The testing described is a non-clinical accuracy test of the auto-registration feature itself, not a study of how human readers improve with AI assistance.

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

Yes, a standalone (algorithm only) performance study was done for the auto-registration features. The accuracy test directly assessed the performance of the auto-registration algorithm by comparing it to the manual registration method. This is an algorithm-only test, as there is no human decision-making loop described for the output of the auto-registration.

7. The Type of Ground Truth Used

The ground truth used for the accuracy test was the established accuracy of the "existing manual registration method available on the currently cleared PercuNav (K132087)." This implies that the accuracy of this manual method served as the reference against which the automated method was deemed "as good as." This is not expert consensus from independent readers, pathology, or outcomes data. It is a comparison to a previously validated manual system.

8. The Sample Size for the Training Set

The document does not specify the sample size used for the training set for the auto-registration algorithms.

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

The document does not explicitly state how the ground truth for the training set was established. Given the nature of the device (image fusion and navigation), it is highly probable that the training data's "ground truth" for registration would involve:

• Careful manual registration performed by trained operators/engineers.
• Potentially, phantoms with known geometric properties.
• Utilizing the established accuracy of the predicate device's manual registration technology.

However, this is inferred, as the document provides no specific details on the training data or its ground truth establishment.

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