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The PROcedure Rehearsal Studio software is intended for use as a software interface and image segmentation system for the transfer of imaging information from a medical scanner such as a CT scanner to an output file. It is also intended as pre-operative software for simulating/evaluating surgical treatment options.

The Simbionix PROcedure Rehearsal Studio software allows clinicians to create a patient specific 3D anatomical model based on a patient's CT for the purpose of simulating, analyzing and evaluating for preoperative surgical treatment options. Once the 3D segmentation model has been exported to the Simbionix ANGIO Mentor Simulator Practice Environment, the physician can use it to create a library of modules for training and post operative debriefing. The modifications subject to this Special 510(k) submission are: (1) Graphic User Interface changes in various locations; (2) functional change in various locations which include the addition of a TEVAR module that allows the software to create 3D models of chest scans in addition to the EVAR and carotid options that were previously cleared.

No, this device is not an AI/ML device. It is a software for creating patient-specific 3D anatomical models from CT scans for surgical simulation and evaluation. The document does not provide a table of acceptance criteria or details of a study with performance metrics in the way typically expected for AI/ML device evaluations (e.g., accuracy, sensitivity, specificity, AUC).

Here's an analysis based on the provided text, focusing on why it doesn't fit the requested format for AI/ML device performance and what information is available:

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

The document does not provide a table of acceptance criteria with specific quantitative performance metrics (e.g., accuracy, sensitivity, specificity, F1 score) that are typical for an AI/ML device.

Instead, the "Performance Data" section states:

• "The verification stage of the software consisted of tests performed for each phase of the user work flow, verifying: Correct functionality of each of the software features, which are part of this work phase and Correct UI."
• "The validation stage consisted of a high level integration test of the device module and included a run through of 10 additional datasets, verifying work flow of all software components."
• "The testing activities were conducted according to the following phases of the user work flow: Importing Patient Data, Segmentation and Centerlines. All testing met the Pass criteria."

This describes a software validation process for functionality and user interface, rather than a clinical performance study with statistical endpoints for an algorithm's diagnostic or predictive capabilities. The "Pass criteria" are mentioned, but not specified in detail or linked to quantitative performance.

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

• Test Set Sample Size: "10 additional datasets" were used for the validation stage.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document only refers to "patient's CT" for creating models.

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 or not specified. Since the validation was focused on software functionality and workflow, rather than diagnostic accuracy against a ground truth, this information is not provided. The device aids clinicians in creating models, but its own "performance" isn't measured against expert consensus for disease detection or measurement.

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

Not applicable or not specified. This is relevant for studies where multiple readers interpret cases and their interpretations are adjudicated to establish ground truth or evaluate reader performance. This document describes software workflow verification.

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. This device is not an AI performing automated analysis; it's a tool for clinicians to create 3D models. The focus is on the software's ability to create these models and support a workflow, not on improving human reader performance with AI assistance.

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

Yes, in a sense, the "performance data" describes the standalone performance of the software in terms of its functionality and workflow. However, it's not "standalone" in the context of an AI algorithm making independent decisions. The device is a "software interface and image segmentation system" which implies it's a tool used by a human, not an independent decision-maker. The validation tested whether "all software components" functioned correctly.

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

Not applicable directly in the context of diagnostic accuracy. The "ground truth" for the validation described appears to be the expected functional behavior and correct UI representation of the software features, as determined by the software's specifications and design documents. It's not a clinical ground truth like pathology for disease presence.

8. The sample size for the training set

Not applicable. This device is not an AI/ML system that undergoes a "training" phase with data in the typical sense. It's a deterministic software for segmentation and 3D model creation.

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

Not applicable, as there is no mention of a training set or AI/ML model training.

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The PROcedure Rehearsal Studio software is intended for use as a software interface and image segmentation system for the transfer of imaging information from a medical scanner such as a CT scanner to an output file. It is also intended as pre-operative software for simulating/evaluating surgical treatment options.

The Simbionix PROcedure Rehearsal Studio software allows clinicians to create a patient specific 3D anatomical model based on a patient's CT for the purpose of simulating, analyzing and evaluating for preoperative surgical treatment options. Once the 3D segmentation model has been exported to the Simbionix ANGIO Mentor Simulator Practice Environment, the physician can use it to create a library of modules for training and post operative debriefing. The modifications subject to this Special 510(k) submission are: (1) Graphic User Interface changes in various locations; (2) functional change in various locations which include the addition of an EVAR module that allows the software to create 3D models of abdominal scans in addition to the carotid option that was previously cleared.

The provided text is a 510(k) summary for the PROcedure Rehearsal Studio, a software device. The submission focuses on modifications to a previously cleared device (K093269).

Analysis of the Provided Text regarding Acceptance Criteria and Study:

The document explicitly states: "The company has performed extensive verification and validation activities to ensure the device performs according to its specifications." However, it does not provide any specific acceptance criteria or details about the studies performed (e.g., performance metrics, statistical analyses, sample sizes, ground truth establishment, expert qualifications, etc.) that would prove the device meets said criteria.

The 510(k) summary for this device focuses on demonstrating substantial equivalence to a predicate device based on modifications to GUI and the addition of an EVAR module. The "Performance Data" section merely states that "extensive verification and validation activities" were performed, but does not elaborate on what these activities entailed in terms of clinical or technical performance studies, or what their outcomes were.

Therefore, I cannot populate the requested table and answer the specific questions about the study from the provided text. The document is too high-level in its description of performance data.

Missing Information:

• Specific Acceptance Criteria: The document does not list any quantitative or qualitative acceptance criteria for the device's performance (e.g., accuracy, precision, sensitivity, specificity for segmentation, or simulation fidelity).
• Reported Device Performance: No actual performance results are reported against any criteria.
• Sample Size for Test Set and Data Provenance: No information is given about the size or characteristics of any test datasets.
• Number of Experts and Qualifications for Ground Truth: No mention of experts or how ground truth was established for testing.
• Adjudication Method: No adjudication method is described.
• MRMC Comparative Effectiveness Study: No mention of such a study.
• Standalone Performance: While the device is a software tool, no specific standalone performance metrics (e.g., segmentation accuracy) are presented.
• Type of Ground Truth: The method for establishing ground truth for any testing is not specified.
• Sample Size for Training Set: The document does not mention any training sets, which would typically be relevant for machine learning-based devices. This device is described as an "image segmentation system," which could potentially use AI/ML, but no details are provided.
• How Ground Truth for Training Set was Established: Not applicable as training set details are missing.

Conclusion:

Based solely on the provided text, it is not possible to construct the requested table or answer the detailed questions about acceptance criteria and the study that proves the device meets them. The document is a regulatory summary focused on substantial equivalence rather than a detailed performance report.

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The PROcedure Rehearsal Studio software is intended for use as a software interface and image segmentation system for the transfer of imaging information from a medical scanner such as a CT scanner to an output file. It is also intended as pre-operative software for simulating/evaluating surgical treatment options.

The Simbionix PROcedure Rehearsal Studio software allows clinicians to create a patient specific 3D anatomical model based on a patient's CT for the purpose of simulating, analyzing and evaluating for preoperative surgical treatment options. Once the 3D segmentation model has been exported to the Simbionix ANGIO Mentor Simulator Practice Environment, the physician can use it to create a library of modules for training and post operative debriefing.

Here's an analysis of the provided text regarding the acceptance criteria and study for the PROcedure Rehearsal Studio™ device, presented in the requested format:

It's important to note that the provided text is a 510(k) summary, which is a regulatory document. These summaries typically focus on demonstrating substantial equivalence to a predicate device rather than providing extensive details on a comprehensive clinical study with specific acceptance criteria and detailed performance metrics. As such, several requested pieces of information are not available in the provided document.

Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria

Summary: The PROcedure Rehearsal Studio™ device performance was validated through bench tests and phantom studies, demonstrating substantial equivalence to its predicate device, Mimics® by Materiallise N.V. (K073468). The primary claim is substantial equivalence, not a specific performance metric against a predefined numerical acceptance criterion.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not specify quantitative acceptance criteria (e.g., specific accuracy, sensitivity, specificity thresholds) that the device had to meet. The acceptance was based on demonstrating equivalence.

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

• Sample Size (Test Set): Not specified. The document only mentions "bench tests and phantom studies."
• Data Provenance: Not specified. "Bench tests and phantom studies" typically imply engineered test scenarios and physical models, not patient data from a specific country or retrospective/prospective collection.

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

• Number of Experts: Not mentioned.
• Qualifications of Experts: Not mentioned.

4. Adjudication Method for the Test Set

• Adjudication Method: Not mentioned.

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

• Was an MRMC study done? No, an MRMC comparative effectiveness study is not mentioned. The validation involves comparison to a predicate device, not human reader performance.
• Effect Size of Human Readers with vs. without AI: Not applicable, as no MRMC study was performed.

6. Standalone Performance Study

• Was a standalone study done? Yes, the device's performance was evaluated independently through "bench tests and phantom studies" in comparison to the predicate device. This implies an algorithm-only (standalone) assessment of the software's ability to perform its intended functions (image segmentation, 3D model creation). The comparison to the predicate device itself is a form of standalone performance evaluation against an established benchmark.

7. Type of Ground Truth Used for the Test Set

• Type of Ground Truth: Implied to be engineered "ground truth" models within "bench tests and phantom studies." This would likely involve phantoms with known anatomical structures and precise measurements against which the device's segmentation and 3D model generation capabilities could be compared. It is not expert consensus, pathology, or outcomes data in the traditional clinical sense.

8. Sample Size for the Training Set

• Sample Size (Training Set): Not mentioned. The document primarily focuses on validation for regulatory clearance, not detailed algorithm development.

9. How Ground Truth for the Training Set Was Established

• Ground Truth for Training Set: Not mentioned. The document does not provide details on the algorithm's training process or how ground truth for any potential training data was established.

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