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Ablation Confirmation™ (AC), is a Computed Tomography (CT) image processing software package available as an optional feature for use with the NEUWAVE Microwave Ablation System. AC is controlled by the user via an independent user interface on a second monitor separate from the NEUWAVE Microwave Ablation System user interface. AC imports images from CT scanners and facility PACS systems for display and processing during ablation procedures. AC assists physicians in identifying ablation targets, assessing proper ablation probe placement and confirming ablation zones. The software is not intended for diagnosis.

AC is resident on the NEUWAVE Microwave Ablation System and is accessible to the physicians via a second, dedicated monitor with its own user interface separate from the ablation user interface. AC functions are controlled via a USB connected mouse. AC connects to a facility PACS system and CT scanner and receives and sends CT, fused PET and MR images via the DICOM protocol.

AC contains a wide range of image processing tools, including:

• 2D image manipulation
• 3D image generation (from 2D images)
• 3D image manipulation
• Region of interest (ROI) identification, segmentation and measurement
• Automatic identification of ablation probes
• Registration of multiple images into a single view

Here's a breakdown of the acceptance criteria and study information for the NeuWave Medical, Inc.'s Ablation Confirmation device, based on the provided FDA 510(k) summary:

This device is primarily an imaging processing software, and the documentation focuses on its functionality and user interface rather than a clinical outcome study. Therefore, the "performance data" section emphasizes verification and validation testing against a test plan and pre-determined acceptance criteria, rather than a traditional clinical trial or MRMC study.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document doesn't explicitly list a table of quantitative acceptance criteria and their corresponding performance metrics as would be seen for an AI diagnostic device. Instead, it states:

The document details numerous "Modifications" and compares "Feature/Specification" between the subject device and the predicate device. These comparisons implicitly define the acceptance criteria, which seem to be primarily functional and qualitative:

• Improved automatic probe detection feature: Expected to perform better or at least as well as the predicate.
• New feature for manual probe definition: Expected to work as intended.
• Network communication monitoring: Expected to function as a troubleshooting aid.
• Improvements to target/ablation zone edit tools: Expected to allow selection for single or multiple slices.
• Undo/redo capability for segmentation operations: Expected to function correctly.
• Importation of fused PET (and MR) scan for comparison: Expected to perform this display function without manipulation, processing, or registration.
• Viewing Set Up scan as a comparison scan: Expected to function as a comparison option.
• Rendering objects as semi-transparent: Expected new visualization.
• Image registration improvements (manual registration, undo): Expected to function as described and improve user experience.
• New function to measure distance between probe tips: Expected to perform this measurement.
• Displaying diameter of sphere during placement/sizing: Expected to show this information.

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

• Sample Size: The document does not specify a numerical sample size for "test sets" in terms of cases or patient data. The "Performance Data" section broadly refers to tests performed on "all functions." This suggests the testing was more akin to software verification and validation, likely using diverse test cases rather than a statistically powered clinical dataset.
• Data Provenance: Not explicitly stated. Given it's a software update (510k for modifications), it's highly probable that existing CT images (potentially from a variety of sources/countries, retrospective) were used for testing various functionalities. No indication of prospective data collection for this submission.

3. Number of Experts and Qualifications for Ground Truth

• The document does not mention the use of experts to establish ground truth for this specific 510(k) submission. The device is described as assisting physicians, and its functions (segmentation, probe detection, registration) are user-controlled or semi-automatic with user adjustment. The "ground truth" for verifying its functions would likely be defined by internal testing against expected algorithmic outputs or manual verification by engineers against known inputs.

4. Adjudication Method for the Test Set

• No adjudication method is mentioned. This is consistent with the nature of the submission being about software updates and functional verification, not a clinical diagnostic assessment requiring expert consensus.

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

• No MRMC comparative effectiveness study was performed or mentioned. The device's indications for use emphasize "assisting physicians" and "not intended for diagnosis," positioning it as a tool to enhance existing procedures rather than a standalone diagnostic or a system intended to directly replace human interpretation. The claim is about functional equivalence and improvement, not comparative reader performance.

6. Standalone (Algorithm Only) Performance

• The document does not present specific "standalone" performance metrics (e.g., sensitivity, specificity, or object detection accuracy) for its automatic features (like automatic probe detection, or segmentation algorithms). The software is designed to be "user-controlled" and provide "assistance." For instance, for segmentation, "The physician initiates the segmentation with tools provided on the screen. AC then uses segmentation algorithms to construct a 2-D visualization of the target lesion selected. The physician can accept the initial segmentation results or use AC tools to manually adjust the defined target lesion." This implies a human-in-the-loop design where the final decision and potentially the refinement of the algorithm's output rest with the user.

7. Type of Ground Truth Used

• Given the nature of the software (image processing and visualization), the "ground truth" for its testing would effectively be the expected output or behavior of the software for given inputs. For example:
  • Functional Ground Truth: Does the "undo" button correctly undo the last action? Does the 3D rendering rotate as expected?
  • Algorithmic Ground Truth: Does the automatic probe detection correctly identify probes in a test image (which might be verified manually by an engineer or a simulated ground truth).
  • User Experience Ground Truth: Are the "improvements to the target/ablation zone edit tools" functioning as intended for user adjustment?
    There is no mention of "pathology" or "outcomes data" as ground truth, as the device is not intended for diagnosis or determining clinical outcomes.

8. Sample Size for the Training Set

• The document does not provide any information regarding a "training set" or its size. This device is presented more as a deterministic image processing and visualization tool with semi-automatic features, rather than a deep learning/AI model that typically requires large training datasets. While some "segmentation algorithms" and "automatic probe detection" features might have involved some form of machine learning or rule-based training during their initial development (prior to this 510(k) in 2019), this documentation focuses on the modifications and their functional testing, not the underlying model development.

9. How Ground Truth for the Training Set Was Established

• As no training set is mentioned, there's no information on how its ground truth might have been established.

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Ablation Confirmation™ (AC), is a Computed Tomography (CT) image processing software package available as an optional feature for use with the Certus® 140 2.45 GHz Ablation System. AC is controlled by the user via an independent user interface on a second monitor separate from the Certus 140 user interface. AC imports images from CT scanners and facility PACS systems for display and processing during ablation procedures. AC assists physicians in identifying ablation targets, assessing proper ablation probe placement and confirming ablation zones. The software is not intended for diagnosis.

AC is resident on the Certus® 140 system and is accessible to the physicians via a second, dedicated monitor with its own user interface separate from the ablation user interface. AC functions are controlled via a USB connected mouse. AC connects to a facility PACS system and CT scanner and receives and sends CT and MR images via the DICOM protocol.

AC contains a wide range of image processing tools, including:

• 2D image manipulation
• 3D image generation (from 2D images)
• 3D image manipulation
• Region of interest (ROI) identification, segmentation and measurement
• Automatic identification of ablation probes
• . Registration of multiple images into a single view

Prior to an ablation procedure, physicians can use AC to semi-automatically segment and visualize ablation target lesions in soft tissue including liver, lung and kidney. The physician initiates the segmentation with tools provided on the screen. AC then uses segmentation algorithms to construct a 2-D visualization of the target lesion selected. The physician can accept the initial segmentation results or use AC tools to manually adjust the defined target lesion. Once accepted, the identified target is rendered into a 3D image.

Upon the placement of ablation probes, taking and importing the CT scan, AC can process the image and identify up to three ablation probes. AC can then perform a registration of the initial CT scan, containing the identified target with the second scan containing the ablation probe(s) in place. The resulting image allows the physician to visualize the ablation probe(s) in relation to the identified target. This enables physicians to ensure probe(s) placement prior to starting the ablation.

Following the ablation procedure and a post-procedure CT scan, AC allows the physician to semiautomatically segment and visualize the ablation zone using the same process as in the initial target segmentation. AC then performs a registration of the initial CT scan, containing the identified target, with the final CECT scan containing the segmented ablation zone. The physician also has the option to evaluate the effect of potential tissue contraction to help determine the technical success (ablation zone covers target lesion with desired amount of margin) of the ablation procedure.

All AC processing and viewing is accomplished at the Certus® 140 Ablation System without the physician having to leave the procedure area to utilize separate image processing tools.

Additionally, AC allows for the images to be viewed by a remote physician for time-saving clinical consultation on the current procedure.

The provided text does not contain detailed information about the acceptance criteria or a specific study proving the device meets the acceptance criteria, as one might find for a clinical performance study of an AI/ML medical device. This document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting extensive performance study data with specific metrics.

However, based on the available information, we can infer some aspects and highlight what is explicitly stated:

Overall Statement on Performance Data:
The document states: "Ablation Confirmation™ was tested in accordance with a test plan that fully evaluated all functions performed by the software. The system passed all pre-determined acceptance criteria identified in the test plan." and "Verification and validation testing were completed in accordance with the company's Design Control process in compliance with 21 CFR Part 820, which included testing that fulfills the requirements of FDA "Guidance on Software Contained in Medical Devices"."

This indicates that internal testing was conducted against a set of acceptance criteria, but the specific metrics, thresholds, and study design details (like sample size, ground truth establishment, etc.) are not included in this 510(k) summary. The focus is on functional testing and compliance with design controls rather than a clinical multi-reader, multi-case (MRMC) or standalone performance study.

Given this limitation, I will address the requested points by stating what is present, inferred, or explicitly missing from the provided text.

1. Table of acceptance criteria and the reported device performance

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

• Sample Size: Not specified in the provided text. The document refers to "a test plan," but does not detail the number of cases or scans used in this testing.
• Data Provenance: Not specified. It's likely internal testing data, but the country of origin, or whether it was retrospective or prospective data, is not mentioned.

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

• This information is not provided. The document describes software segmentation where "The physician can accept the initial segmentation results or use AC tools to manually adjust the defined target lesion." This suggests user interaction for defining targets/zones, but it doesn't describe a formal expert-driven ground truth establishment process for a test set.

4. Adjudication method for the test set

• This information is not provided. As a formal clinical performance study with expert readers is not detailed, an adjudication method would not be relevant in the context of the testing described.

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 is not described or referenced in this 510(k) summary. The device "assists physicians," but no study on the impact of this assistance on human reader performance (e.g., diagnostic accuracy, time saving) is presented.

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

• The document implies that the software includes "segmentation algorithms" and "automatic identification of ablation probes." It states "Prior to an ablation procedure, physicians can use AC to semi-automatically segment..." and "AC then uses segmentation algorithms to construct a 2-D visualization..." and "AC can process the image and identify up to three ablation probes." While these algorithms likely underwent internal standalone testing for functionality and accuracy, the details of such standalone performance (e.g., specific metrics like Dice coefficient for segmentation, sensitivity/specificity for probe detection) are not provided in this summary. The summary focuses on the end-user workflow involving physician interaction ("semi-automatically segment," "physician can accept... or manually adjust").

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

• For the internal "test plan" mentioned, the specific type of ground truth used to evaluate the software's performance (e.g., for segmentation accuracy or probe identification) is not explicitly stated. Given the device's function, anatomical landmarks and physician-defined regions (either through manual outlining or verification of semi-automatic results as described) would likely serve as a practical form of ground truth for functional verification. Pathology or outcomes data are generally not applicable for confirming image processing and segmentation accuracy.

8. The sample size for the training set

• This information is not provided. The document does not describe a machine learning training process with a distinct training set. It refers to "segmentation algorithms" but does not detail their development or the data used to train them.

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

• This information is not provided, as details about a distinct training set and its ground truth establishment are absent from the summary.

Ask a specific question about this device

Ablation Confirmation™ (AC), is a Computed Tomography (CT) image processing software package available as an optional feature for use with the Certus® 140 2.45 GHz Ablation System. AC is controlled by the user via an independent user interface on a second monitor separate from the Certus 140 user interface. AC imports images from CT scanners and facility PACS systems for display and processing during ablation procedures. AC assists physicians in identifying ablation targets, assessing proper ablation probe placement and confirming ablation zones. The software is not intended for diagnosis.

AC is resident on the Certus® 140 system and is accessible to the physicians via a second, dedicated monitor with its own user interface separate from the ablation user interface. AC functions are controlled via a USB connected mouse. AC connects to a facility PACS system and CT scanner and receives and sends CT and MR images via the DICOM protocol.

AC contains a wide range of image processing tools, including:

• 2D image manipulation
• 3D image generation (from 2D images) ●
• 3D image manipulation
• Region of interest (ROI) identification, segmentation and measurement ●
• Automatic identification of ablation probes
• . Registration of multiple images into a single view

Prior to an ablation procedure, physicians can use AC to semi-automatically segment and visualize ablation target lesions in soft tissue including liver, lung and kidney. The physician initiates the segmentation with tools provided on the screen. AC then uses segmentation algorithms to construct a 2-D visualization of the target lesion selected. The physician can accept the initial segmentation results or use AC tools to manually adjust the defined target lesion. Once accepted, the identified target is rendered into a 3D image.

Upon the placement of ablation probes, taking and importing the CT scan, AC can process the image and identify up to three ablation probes. AC can then perform a registration of the initial CT scan, containing the identified target with the second scan containing the ablation probe(s) in place. The resulting image allows the physician to visualize the ablation probe(s) in relation to the identified target. This enables physicians to ensure proper probe(s) placement prior to starting the ablation. Following the ablation procedure and a post-procedure CT scan, AC allows the physician to semi-automatically segment and visualize the ablation zone using the same process as in the initial target segmentation. AC then performs a registration of the initial CT scan, containing the identified target, with the final CECT scan containing the segmented ablation zone. The physician also has the option to evaluate the effect of potential tissue contraction to help determine the technical success (ablation zone covers target lesion with desired amount of margin) of the ablation procedure.

All AC processing and viewing is accomplished at the Certus® 140 Ablation System without the physician having to leave the procedure area to utilize separate image processing tools.

Additionally, AC allows for the images to be viewed by a remote physician for time-saving clinical consultation on the current procedure.

The provided text describes the NeuWave Medical, Inc. Ablation Confirmation™ system and its 510(k) submission (K161285). However, it contains very limited direct information on acceptance criteria and the detailed study that proves the device meets specific acceptance criteria. The document states that "The system passed all pre-determined acceptance criteria identified in the test plan" and "Verification and validation testing were completed in accordance with the company's Design Control process in compliance with 21 CFR Part 820.30, which included testing that fulfills the requirements of FDA "Guidance on Software Contained in Medical Devices"". It does not provide the specifics of these acceptance criteria or the study details.

Below is a summary of the information that is available in the provided text, and explicit statements about what information is not available.

1. Table of Acceptance Criteria and Reported Device Performance

Not available directly in the provided text. The document states that "The system passed all pre-determined acceptance criteria identified in the test plan," but it does not list these criteria or report specific performance metrics against them.

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

Not available in the provided text. The document does not specify the sample size for the test set or the provenance of the data (e.g., country of origin, retrospective or prospective).

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

Not available in the provided text. The document does not mention the number of experts or their qualifications used to establish ground truth for any test set.

4. Adjudication Method for the Test Set

Not available in the provided text. The document does not describe any adjudication method used for a test set.

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

Not available in the provided text. The document does not mention an MRMC comparative effectiveness study or any effect size of human readers improving with AI vs. without AI assistance. The device assists physicians, but no comparative study is described.

6. Standalone (Algorithm Only) Performance

Partially available, but not with specific performance metrics. The document implies that the software performs several functions (segmentation, identification of probes, registration) semi-automatically or automatically. However, it does not provide standalone performance metrics (e.g., accuracy, sensitivity, specificity) for these functions. It states that "AC uses segmentation algorithms to construct a 2-D visualization" and "AC can process the image and identify up to three ablation probes."

7. Type of Ground Truth Used

Not explicitly stated for performance evaluation. For segmentation purposes, the text states that "The physician can accept the initial segmentation results or use AC tools to manually adjust the defined target lesion," implying that physician judgment (expert input) forms the ultimate "ground truth" for the intended use of identifying and adjusting target/ablation zones. However, for formal performance evaluation against acceptance criteria, the specific type of ground truth (e.g., pathology, outcomes data, consensus) is not detailed.

8. Sample Size for the Training Set

Not available in the provided text. The document does not mention any training set or its size.

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

Not available in the provided text. Given that the document does not mention a training set, the method for establishing its ground truth is also not provided.

Summary of what can be gleaned from the text regarding performance and validation:

The document indicates that:

• Ablation Confirmation™ "passed all pre-determined acceptance criteria identified in the test plan."
• "Verification and validation testing were completed in accordance with the company's Design Control process in compliance with 21 CFR Part 820.30, which included testing that fulfills the requirements of FDA "Guidance on Software Contained in Medical Devices"."
• "Potential risks arising from the addition of the Tissue Contraction feature were analyzed and satisfactorily mitigated in the device design and labeling."

However, the specific details of these acceptance criteria, the performance metrics achieved, and the methodologies for the underlying studies (e.g., test set size, expert involvement, ground truth establishment) are not included in the provided 510(k) summary letter.

Ask a specific question about this device

Ablation Confirmation™ (AC), is a Computed Tomography (CT) image processing software package available as an optional feature for use with the Certus® 140 2.45 GHz Ablation System. AC is controlled by the user via an independent user interface on a second monitor separate from the Certus 140 user interface. AC imports images from CT scanners and facility PACS systems for display and processing during ablation procedures. AC assists physicians in identifying ablation targets, assessing proper ablation probe placement and confirming ablation zones. The software is not intended for diagnosis.

AC is resident on the Certus® 140 system and is accessible to the physicians via a second, dedicated monitor with its own user interface separate from the ablation user interface. AC functions are controlled via a USB connected mouse. AC connects to a facility PACS system and CT scanner and receives and sends CT and MR images via the DICOM protocol.

AC contains a wide range of image processing tools, including:

• 2D image manipulation
• 3D image generation (from 2D images)
• 3D image manipulation
• Region of interest (ROI) identification, segmentation and measurement
• Automatic identification of ablation probes
• . Registration of multiple images into a single view

Prior to an ablation procedure, physicians can use AC to semi-automatically segment and visualize ablation target lesions in soft tissue including liver, lung and kidney. The physician initiates the segmentation with tools provided on the screen. AC then uses segmentation algorithms to construct a 2-D visualization of the target lesion selected. The physician can accept the initial segmentation results or use AC tools to manually adjust the defined target lesion. Once accepted, the identified target is rendered into a 3D image.

Upon the placement of ablation probes, taking and importing the CT scan, AC can process the image and identify up to three ablation probes. AC can then perform a registration of the initial CT scan, containing the identified target with the second scan containing the ablation probe(s) in place. The resulting image allows the physician to visualize the ablation probe(s) in relation to the identified target. This enables physicians to ensure proper probe(s) placement prior to starting the ablation. Following the ablation procedure and a post-procedure CT scan, AC allows the physician to semi-automatically segment and visualize the ablation zone using the same process as in the initial target segmentation. AC can then performs a registration of the initial CT scan, containing the identified target, with the final CECT scan containing the segmented ablation zone. The resulting image set includes the ablation zone overlaid onto the initial target lesion segmentation to help physicians determine the technical success (ablation zone covers target lesion with desired amount of margin) of the ablation procedure.

All AC processing and viewing is accomplished at the Certus® 140 Ablation System without the physician having to leave the procedure area to utilize separate image processing tools.

Additionally, AC allows for the images to be viewed by a remote physician for time-saving clinical consultation on the current procedure.

The acceptance criteria for the Ablation Confirmation™ device were based on the device successfully passing all pre-determined criteria identified in the test plan for its functions, including segmentation and registration accuracy. While the document states that these accuracies were demonstrated through adequate bench testing and clinical experience, it does not explicitly provide numerical acceptance criteria or reported performance metrics in a tabular format.

Here's a breakdown of the available information:

1. Acceptance Criteria and Reported Device Performance:

The document states: "Ablation Confirmation™ was tested in accordance with a test plan that fully evaluated all functions performed by the software. The system passed all pre-determined acceptance criteria identified in the test plan."

However, specific numerical acceptance criteria (e.g., minimum accuracy percentages, maximum error margins) and the corresponding reported device performance values are not explicitly provided in this document. The document generally states that "Segmentation and Registration accuracy were demonstrated through adequate bench testing and also through clinical experience of qualified users."

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

• Sample Size: Not explicitly stated.
• Data Provenance: "Testing was performed using retrospectively obtained CT image series from ablation procedures." The country of origin for the data is not specified.

3. Number of Experts and Qualifications:

• Number of Experts: Not explicitly stated. The document refers to "clinical experience of qualified users" but does not quantify the number of users or their specific roles.
• Qualifications: "Qualified users" are mentioned, but their specific qualifications (e.g., "radiologist with 10 years of experience") are not detailed.

4. Adjudication Method:

• The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for establishing the ground truth or evaluating the device's performance within the test set.

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

• The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study, nor does it quantify any effect size of human readers improving with AI vs. without AI assistance. The device is described as assisting physicians, but a comparative study as described is not presented.

6. Standalone Performance:

• Yes, a standalone performance evaluation was conducted. The document states, "Ablation Confirmation™ was tested in accordance with a test plan that fully evaluated all functions performed by the software. The system passed all pre-determined acceptance criteria identified in the test plan." This implies an assessment of the algorithm's performance independent of human input, as its functions are described to "assist physicians" and "perform" certain tasks like segmentation and registration.

7. Type of Ground Truth Used:

• The ground truth appears to be based on expert interpretation and manual adjustments. For target lesions, the "physician initiates the segmentation with tools provided on the screen. AC then uses segmentation algorithms to construct a 2-D visualization of the target lesion selected. The physician can accept the initial segmentation results or use AC tools to manually adjust the defined target lesion." A similar process is described for the ablation zone. This suggests that the "true" segmentation or identification was ultimately confirmed and potentially modified by a qualified user. This combines algorithmic output with expert consensus/manual correction.

8. Sample Size for the Training Set:

• The document does not specify the sample size used for the training set.

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

• The document does not explicitly describe how the ground truth for the training set was established. It describes the process for how the device assists in segmentation during an actual procedure, which involves physician initiation and manual adjustment of the algorithmic output. While this provides insight into the intended use and validation approach, it doesn't detail the training data ground truth establishment.

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