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The SuRgical Planner (SRP) BrainStorm is intended for use as a software interface and image segmentation system for the transfer of image information from a CT, MR, or X-ray 3D Angiography (XA) medical scanner to an output file. It can also be used for pre-operative planning and surgical training in a virtual environment.

The SuRgical Planner (SRP) BrainStorm is intended for use as a software interface and image segmentation system for the transfer of image information from a CT, MR, or X-ray 3D Angiography (XA) medical scanner to an output file. It can also be used for pre-operative planning and surgical training in a virtual environment.

The SuRgical Planner (SRP) BrainStorm is not intended to be used for diagnosis.

The SRP BrainStorm software has the ability of creating 3D models of the patient data from 2D scan slices. Additionally, it provides the user with the ability to input, display, color, and manipulate the 2D scan slices via a 3D representation. The software transforms 2D medical images into a dynamic interactive 3D scene with multiple point of views on a high-definition (HD) touch screen monitor. The use of a virtual reality (VR) or augmented reality (AR) headset provides the surgeon a 3D stereoscopic display of the same scene inside the VR / AR headset. While wearing the VR / AR headset, the surgeon can perform a virtual / simulated "fly-through" inside the 3D scene using controllers to perform such actions as rotate, zoom in and zoom out. The use of the SuRgical Planner (SRP) BrainStorm with VR / AR headset and controllers is not intended for use during surgery. The SRP BrainStorm is intended for use for pre-operative planning.

The SRP BrainStorm software includes additional features to facilitate the review of relevant data by a multidisciplinary team that includes neurosurgeons and neurologists for pre-operative surgical planning.

The SRP BrainStorm product does not include any custom hardware and is a software-based device that runs on a high-performance desktop PC assembled using "commercial off-the-shelt" components that meet minimum performance requirements. The design is based on an advanced, touch screen friendly, Graphical User Interface (GUI) that runs an underlying simulation engine to process medical images in DICOM format, and an image generator software engine.

This 510(k) premarket notification describes a software device, SuRgical Planner (SRP) BrainStorm, which is intended for use as a software interface and image segmentation system for the transfer of image information from medical scanners to an output file. It is also used for pre-operative planning and surgical training in a virtual environment. The submission focuses on demonstrating substantial equivalence to a predicate device, SuRgical Planner (SRP) (K170793), rather than presenting a study to prove the device meets specific performance acceptance criteria for a new clinical task.

Therefore, much of the requested information regarding acceptance criteria and performance study specifics (like sample size, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth detailed establishment for training/test sets) is not applicable or not explicitly detailed in the provided document. The document describes a verification and validation (V&V) plan to confirm the device meets its intended use and performance requirements, implying internal testing rather than a clinical effectiveness study against predefined criteria like sensitivity or specificity.

Here's a breakdown of the available information:

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

The document does not provide a table of acceptance criteria with numerical performance targets (e.g., sensitivity, specificity, accuracy) or quantitative performance results. Instead, it states:

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

• Sample Size: Not specified. The document only mentions "a formal verification and validation plan was executed" and "verification and validation tests were performed."
• Data Provenance: Not specified. The source or nature of the data used for the V&V tests (e.g., type of medical images, number of cases, patient demographics, country of origin) is not provided.

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

• Not specified. The document does not describe the use of experts to establish ground truth for a test set in the context of a performance study. Given the nature of the device (software interface and planning tool for pre-operative use), the "ground truth" might refer to the accurate representation of anatomical structures or functional software execution, which would be validated internally rather than through expert clinical review against specific diagnostic criteria.

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

• Not specified. No adjudication method is mentioned, as there is no description of a performance study involving comparison to a ground truth established 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 comparative effectiveness study is mentioned. The device's purpose is not described as an AI-assisted diagnostic tool for human readers but rather as a planning and training tool.

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

• Not explicitly detailed, but the context of "verification and validation tests" implies testing of the software's functionality and performance as an algorithm. The device's primary function is a standalone software system for image processing, 3D modeling, and visualization, with human interaction being part of its intended use (e.g., surgeons using VR/AR headsets). It can be inferred that the software's ability to perform its core functions (e.g., segment images, create 3D models) independently was evaluated.

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

• Not explicitly defined in the document. For a device like SRP BrainStorm, "ground truth" during verification and validation would likely involve:
  • Reference Image Data: Comparing segmented 3D models against known anatomical structures from original medical images.
  • Functional Specification Compliance: Ensuring that the software performs its specified functions (e.g., correct import/export, proper 3D rendering, accurate display of electrode detections) as designed.
  • Usability/User Interface Testing: Confirming that the user interface and interactions (e.g., with VR/AR headsets) meet design requirements and user expectations for pre-operative planning.

8. The sample size for the training set:

• Not applicable. This device is described as an image processing and visualization tool, not an AI/ML algorithm that is trained on a specific dataset for diagnostic or predictive purposes. The "training" mentioned in the context of the device is for surgical training using the virtual environment, not algorithm training.

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

• Not applicable for algorithm training set ground truth. For the surgical training aspect, the "ground truth" is typically the anatomical and physiological accuracy of the virtual environment, which would be established through careful modeling based on medical imaging data and validated by anatomical expertise. However, this is not a training set for the algorithm itself.

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The Surgical Theater, LLC SuRgical Planner (SRP) is intended for use as a software interface and image segmentation system for the transfer of image information from a CT, MR, or X-ray 3D Angiography (XA) medical scanner to an output file. It can also be used for pre-operative planning and surgical training in a virtual environment.

The SuRgical Planner (SRP) is intended for use as a software interface and image segmentation system for the transfer of imaging information from a CT, MR or X-ray 3D Angiography (XA) medical scanner to an output file. It can also be used for pre-operative planning and surgical training in a virtual environment.

The SuRgical Planner is not intended to be used for diagnosis.

The SRP software has the ability of creating 3D models of the patient data from 2D scan slices. Additionally, it provides the user with the ability to input, display, color, and manipulate the 2D scan slices via a 3D representation. The software transforms 2D medical images into a dynamic interactive 3D scene with multiple point of views on a high-definition (HD) touch screen monitor. The use of a virtual reality (VR) headset provides the surgeon a 3D stereoscopic display of the same scene inside the VR headset. While wearing the VR headset, the surgeon can perform a virtual / simulated "fly-through" inside the 3D scene using controllers to perform such actions as rotate, zoom in and zoom out. The SRP with VR headset and controllers is not intended for use during surgery. The SRP is intended for use for pre-operative planning.

The SRP product does not include any custom hardware and is a software-based device that runs on a high-performance desktop PC assembled using "commercial off-the-shelf" components that meet minimum performance requirements. The design is based on an advanced, touch screen friendly, Graphical User Interface (GUI) that runs an underlying simulation engine to process medical images in DICOM format, and an image generator software engine.

The provided text is a 510(k) summary for the Surgical Theater, LLC SuRgical Planner (SRP) software. It describes the device, its intended use, comparison to a predicate device, and performance data. However, the document primarily focuses on regulatory compliance and substantial equivalence rather than a detailed study evaluating the device's performance against specific acceptance criteria.

Therefore, much of the requested information regarding specific acceptance criteria, detailed study design, sample sizes for test and training sets, expert qualifications, and ground truth establishment is not available in the provided text. The document states that "Software verification and validation testing were conducted" and that "A formal verification and validation plan was executed to confirm that the modified SRP continues to meet its intended use and performance requirements." However, it does not provide the specifics of these plans or their results in a way that directly answers the questions about acceptance criteria and performance metrics.

Here's a breakdown of what can be extracted and what is missing:

Acceptance Criteria and Study Details for SuRgical Planner (SRP)

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for Test Set and Data Provenance

• Sample Size: Not specified in the provided document. The document mentions "Software verification and validation testing were conducted," but details on the number of cases or images used in these tests are absent.
• Data Provenance: Not specified. The document states the device processes DICOM images from CT, MR, or X-ray 3D Angiography (XA) medical scanners, but does not indicate the source (e.g., country, hospital, retrospective/prospective) of the data used for testing.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The document states the device is for "pre-operative planning and surgical training in a virtual environment," implying surgical expertise might be relevant, but this is not confirmed for ground truth establishment.

4. Adjudication Method for Test Set

• Adjudication Method: Not specified. The document outlines general software verification and validation but does not detail how ground truth was established or if an adjudication process was involved for performance evaluation.

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

• MRMC Study: No, an MRMC comparative effectiveness study is not mentioned in the provided text. The document focuses on the device's technical specifications and regulatory equivalence, not on evaluating human reader performance with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: Yes, implicitly. The document states that the "SRP was fully tested, verified and validated by Surgical Theater as part of its own internal design control requirements" to "meet its intended use and performance requirements." While details on specific metrics are missing, this implies a standalone evaluation of the software's functionality and accuracy in image segmentation and 3D model generation, which are core algorithmic tasks. However, explicit performance metrics (e.g., segmentation accuracy, speed) are not provided.

7. Type of Ground Truth Used

• Type of Ground Truth: Not specified. Given the device's function involves image segmentation and 3D model generation, ground truth would likely relate to the accuracy of these outputs against a reference. However, the method for establishing this reference (e.g., manual segmentation by experts, phantom scans with known anatomy) is not detailed.

8. Sample Size for the Training Set

• Sample Size: Not specified. The document does not provide information about a training set, as the SRP functions primarily as an image processing and visualization tool, rather than a machine learning model that requires explicit training data in the traditional sense. It processes existing medical images.

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

• Ground Truth Establishment for Training Set: Not applicable, as detailed training set information is not provided and the device description does not explicitly mention machine learning components that require a training set with established ground truth in the context of predictive or diagnostic tasks. The "training" aspect mentioned in the document refers to surgical training in a virtual environment using the device, not training of the device itself.

In summary, the provided document serves as a regulatory submission emphasizing substantial equivalence and general safety/effectiveness through internal verification and validation processes. It lacks the quantitative performance data and detailed study designs typically found in clinical efficacy studies that would address specific acceptance criteria with measured outcomes.

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