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iPlan's indications for use are the viewing, presentation and documentation of medical imaging, including different modules for image processing, image fusion, atlas assisted visualization and segmentation, intraoperative functional planning where the output can be used e.g. with stereotactic image guided surgery or other devices for further processing and visualization.

Example procedures include but are not limited to:

• Planning and simulation of cranial surgical procedures such as tumor resection, shunt placement, minimal-invasive stereotactic interventions, biopsy, planning and simulation of trajectories for stimulation and electrode recording
• ENT procedures such as sinus surgery, tumor surgery
• Spine procedures such as tumor surgery, pedicle screw planning, vertebroplasty planning
• iPlan View is an application which is intended to be used for reviewing existing treatment plans
• Planning and simulation of cranio-maxillofacial procedures

Typical users of iPlan are medical professionals, including but not limited to surgeons and radiologists.

iPlan is a software based treatment planning application providing functionalities like viewing, processing and documentation of medical data including different modules for image preparation, image fusion, image segmentation where the result is a treatment plan that can be used e.g. for stereotactic and/or image guided surgery.

The provided 510(k) summary for iPlan focuses on demonstrating substantial equivalence to predicate devices through technical characteristics, intended use, and non-clinical performance data. It does not provide detailed acceptance criteria or a specific study proving the device meets those criteria in the format typically associated with AI/ML device performance evaluations (e.g., sensitivity, specificity, AUC).

However, I can extract the information related to non-clinical performance data and application performance testing which served as the basis for the FDA's substantial equivalence determination for this software planning application.

Here's a breakdown of the requested information based on the provided text:

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

The document does not explicitly state quantitative acceptance criteria (e.g., minimum sensitivity, specificity, accuracy) for the device's performance. Instead, it relies on demonstrating equivalence to predicate devices and adherence to internal standards and specifications.

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

The document does not specify a "test set" in the context of a dataset for a performance study.

• For Usability Workshops: The sample size (number of participants) is not mentioned. The workshops were likely conducted on prototypes.
• For Application Performance Testing: The sample size of test cases or data used during bench and integration tests is not specified.
• Data Provenance: Not applicable in the context of a dataset for a performance study.

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

This is not directly applicable as there isn't a traditional "test set" with ground truth established by experts in the context of a performance study for this type of device described.

• For the Expert Group Review in usability: The number of experts is not specified, but they are described as working with Brainlab "to tailor the existing iPlan planning functionalities to the specific needs of CMF surgeons." Their qualifications are implicitly that they are CMF (Cranio-Maxillofacial) surgeons.

4. Adjudication method for the test set

Not applicable, as a dedicated "test set" for performance evaluation with an adjudication process is not 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 MRMC comparative effectiveness study is mentioned. The device is a planning application, and the evaluation focuses on its functional correctness, usability, and equivalence to predicates, not on AI-assisted diagnostic improvement for human readers.

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

This refers to the software performing its functions without human interaction. The "Application performance testing" ("bench and integration tests") would implicitly cover the standalone performance of the algorithms and modules within iPlan to ensure they meet internal standards. However, specific metrics are not provided. iPlan is described as a "software based treatment planning application," implying it's a tool for medical professionals, not a fully autonomous diagnostic or therapeutic AI.

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

For the "Application performance testing," the ground truth would be the expected output or behavior of the software modules based on their specifications and internal standards. This is typically established through:

• Functional Specifications: Defining what each module (e.g., Image Fusion, Object Creation) is supposed to do.
• Reference Data/Known Inputs: Using synthetic or previously validated medical data where the "correct" output of a segmentation, fusion, or trajectory calculation is known or can be analytically derived.
• Comparison to Predicate Devices: Ensuring that functionally similar modules perform comparably to predicate devices.

8. The sample size for the training set

This document does not describe the development of an AI/ML model that would typically have a "training set." iPlan is presented as a software application with various processing and visualization functionalities.

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

Not applicable, as a "training set" for an AI/ML model is not mentioned in this context.

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iPlan's indications for use are the viewing, presentation and documentation of medical imaging, including different modules for image processing, image fusion, atlas assisted visualization and segmentation, intraoperative functional planning where the output can be used e.g. with stereotactic image guided surgery or other devices for further processing and visualization.

Example procedures include but are not limited to:

• Planning and simulation of cranial surgical procedures such as tumor resection, shunt placement, minimal-invasive stereotactic interventions, biopsy, trajectory planning for stimulation and electrode recording
• ENT procedures such as sinus surgery, tumor surgery -
• Spine procedures such as tumor surgery, pedicle screw planning, vertebroplasty planning
• iPlan View is an application which is intended to be used for reviewing existing treatment plans

Following planning sub-modules are available in the functional applications: Load and Import, View and Adjustment, Registration Points, ACPC Localization, Localization, Image Fusion, Object Creation, Advanced Object Planning, BOLD MRI mapping, Fiber Tracking, Trajectory planning, Stereotactic planning, Electrode recording, Save and Export.

The provided text describes the 510(k) summary for the iPlan device (K101627). However, it does not contain specific details about acceptance criteria, device performance metrics, sample sizes, ground truth establishment, or any formal study results (like MRMC comparative effectiveness studies or standalone performance studies) that prove the device meets acceptance criteria.

The document states that:

• "On different levels of development (module, subsystem, system) specific bench and integration tests were conducted."
• "Internal standards were tested and documented as conformance report, environment compatibility and interfaces."
• "Compatibility with previous version and comparable workflows to predicate devices were documented in corresponding review protocols."
• "Side-by-side comparison testing of the new version of iPlan with its predicate device was conducted to determine substantial equivalences of the new version of iPlan with its predicate version."

This indicates that testing was performed, but the results, specific acceptance criteria, and detailed methodology are not included in this summary. The FDA's letter states a "substantial equivalence determination" to a legally marketed predicate device (iPlan K053127) was made, which is the basis for clearance, rather than a detailed performance study against specific acceptance criteria.

Therefore, I cannot populate the requested table and sections with the information provided. The document outlines:

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

• Not provided. The document generally states "specific bench and integration tests were conducted" and "Internal standards were tested," but no specific criteria or performance metrics are detailed.

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

• Not provided.

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 provided.

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

• Not provided.

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:

• Not explicitly mentioned or detailed. The device description focuses on planning and visualization tools, not necessarily AI-assisted interpretation to improve human reader performance in a diagnostic context. "Side-by-side comparison testing" was done with the predicate device to determine substantial equivalence, not typically an MRMC study demonstrating human performance improvement.

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

• Not explicitly mentioned or detailed. The device is described as a "Planning System, Stereotactic Instrument" used by "medical professionals," implying human interaction.

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

• Not provided.

8. The sample size for the training set:

• Not applicable/Not provided. The document describes a medical device software for planning and visualization, not typically an AI/ML model that would have a distinct training set in the conventional sense of deep learning. The testing described focuses on functional equivalence to a predicate device.

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

• Not applicable/Not provided. (See point 8)

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iPlan RT is a radiation treatment planning system that is intended for use in stereotactic, conformal, computer planned, Linac based radiation treatment of cranial, head and neck, and extracranial lesions.

iPlan RT is a software program to generate treatment plans and to simulate the dose delivery for external beam radiotherapy. The system is the evolutionary successor of the predicate devices iPlan RT Image (K080886) and iPlan RT Dose (K080888). It is specialized for stereotactic procedures for cranial as well as extracranial lesions. It includes functions for all relevant steps from outer contour detection to quality assurance. It combines most of its predecessor's functionality iPlan RT Image and iPlan RT Dose together with additional improvements. Therefore, the new version shall be called "iPlan RT".

The device incorporates conformal beams, conformal IMRT beams, circular arcs, and both static and dynamic arc treatments. Moreover, a combination of optimized dynamic arc treatments together with IMRT beams was added to the treatment modalities.

The system calculates dose using a convolution algorithm as the previous version. Alternatively, a Monte Carlo method based calculation algorithm can be used as in iPlan RT Dose (K080888). The documentation & export function facilitates printouts of all parameters and results for the creation of DICOM RT (RT Plan and RT Image) files.

Adapting existing treatment plans during fractionated radiotherapy treatments is facilitated using an elastic deformation algorithm. Existing structures are morphed from an existing treatment plan onto a new follow-up scan. If necessary, these structures can be adapted by the physician and can be used to update the current treatment plan accordingly.

The provided document, a 510(k) summary for Brainlab AG's iPlan RT, does not contain a study that proves the device meets specific acceptance criteria in the manner typically seen for novel medical device algorithms or AI. Instead, it demonstrates substantial equivalence to predicate devices (iPlan RT Image K080886 and iPlan RT Dose K080888) through non-clinical testing.

Here's an analysis based on the provided text, addressing the requested points:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics. The summary of non-clinical testing only states that the device "has met its specifications" and is "substantially equivalent to the predicate devices" and "safe and effective for its intended use." These are general conclusions rather than detailed performance metrics.

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

The document does not mention the use of a "test set" in the context of clinical data for performance evaluation. The evaluation was based on non-clinical testing and comparison to predicate devices. Therefore, there is no information on sample size or data provenance.

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

Since no clinical test set was used to establish performance against a ground truth, this information is not applicable and not provided in the document.

4. Adjudication Method for the Test Set

As no clinical test set requiring ground truth establishment was used, there is no mention of an adjudication method.

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

The document explicitly states: "Clinical testing is not required to demonstrate substantial equivalence or safety and effectiveness." Therefore, an MRMC comparative effectiveness study was not performed.

6. Standalone (Algorithm Only) Performance Study

The document describes non-clinical "Verification and Validation tests" which confirmed the device "met its specifications." This implicitly refers to the algorithm's performance in generating treatment plans. However, no specific metrics like sensitivity, specificity, accuracy, or a detailed study design for standalone performance are provided beyond the general statement of meeting specifications. The focus is on functionality and equivalence to predicate devices.

7. Type of Ground Truth Used

For the non-clinical testing, the "ground truth" would likely have been the expected computational output based on known physics and engineering principles for radiation dose calculation and planning. This is inferred from the statement that the device "has met its specifications." There is no mention of external clinical ground truth (e.g., pathology, outcomes data, or expert consensus on clinical cases) for this 510(k) submission.

8. Sample Size for the Training Set

The document does not mention a "training set" in the context of machine learning or AI models with data-driven training. The iPlan RT is described as an "evolutionary successor" of previous devices, suggesting a development and refinement process rather than a machine learning training paradigm. The core dose calculation uses a convolution algorithm or Monte Carlo method, which are physics-based models rather than models trained on large datasets.

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

As no explicit training set for a machine learning model is mentioned, this question is not applicable based on the provided text.

In summary, the 510(k) for iPlan RT focuses on demonstrating substantial equivalence to existing predicate devices through non-clinical verification and validation, rather than extensive clinical studies with specific acceptance criteria tables and ground truth evaluations typically associated with novel AI/ML devices.

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iPlan RT Image's indications for use are to prepare and present patient and image data based on CT, MR, angiographic and other imaging sources including

• image preparation -
• image localization
• n image fusion
• image segmentation "
• isocenter handling -
• plan review and approval -
  where the result is used for stereotactic radiation treatment planning that is intended for use in stereotactic, conformal, computer planned, LINAC based radiation treatment of cranial, head and neck and extracranial lesions.

Not Found

The provided text is a 510(k) summary for the iPlan RT Image device from BrainLAB AG. This document focuses on establishing substantial equivalence to predicate devices and detailing the intended use. It does not contain information about acceptance criteria, device performance studies, sample sizes, expert ground truth establishment, or any comparative effectiveness studies.

Therefore, I cannot provide the requested information from this document. The sections you asked for, such as "A table of acceptance criteria and the reported device performance," "Sample sized used for the test set," "Number of experts used," "Adjudication method," "MRMC comparative effectiveness study," "standalone performance," "type of ground truth," "training set sample size," and "how ground truth for training set was established," are not present in the provided text.

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iPlan RT Dose is a stereotactic radiation treatment planning system that is intended for use in stereotactic, conformal, computer planned, Linac based radiation treatment of cranial, head and neck, and extracranial lesions.

Not Found

The provided text is a 510(k) summary for the iPlan RT Dose system. It describes the device, its intended use, and its predicate devices, but does not contain information about acceptance criteria or a study proving the device meets acceptance criteria.

Therefore, I cannot fulfill your request to describe acceptance criteria and a study that proves the device meets them based only on the provided input. The document is an FDA approval letter and summary, not a study report.

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iPlan RT Dose is a stereotactic radiation treatment planning system that is intended for use in stereotactic, conformal, computer planned, Linac based radiation treatment of cranial, head and neck, and extracranial lesions.

iPlan RT Dose is a software program to generate treatment plans and to simulate the dose delivery for external beam radiotherapy. The system is the evolutionary successor of the predicate device BrainSCAN (K994413). It is specialized for stereotactic procedures for cranial as well as extracranial lesions. It includes functions for all relevant steps from outer contract detection to quality assurance.

iPlan RT Dose incorporates most capabilities of the predicate device BrainSCAN. The device incorporates conformal beams, conformal IMRT beams, both static and dynamic arc treatments. The system calculates dose using a convolution algorithm similar to the predicate device BrainSCAN. The documentation & export allows producing printouts of all parameters and results for the creation of DICOM RT (RT Plan and RT Image) files.

This document is a 510(k) summary for the iPlan RT Dose system, a radiation treatment planning system. It establishes substantial equivalence to a predicate device (BrainSCAN, K994413). It does not contain information regarding acceptance criteria, device performance metrics, or details of specific studies conducted to establish performance characteristics in the way you've outlined.

The document states: "iPlan RT Dose has been verified and validated according to BrainLAB's procedures for product design and development. The validation proves the safety and effectiveness of the system." However, it does not provide the specifics of these verification and validation studies, including acceptance criteria or performance results.

Therefore, I cannot provide a table of acceptance criteria and reported device performance from this document. The other requested information (sample sizes, ground truth establishment, expert qualifications, adjudication methods, MRMC studies, standalone performance, training set details) is also not present in this 510(k) summary.

In summary, the provided text does not contain the information needed to fill out your request.

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iPlan Flow is designed as a planning system for pre- and intraoperative planning of stereotactic or image guided surgery treatments. It is specially designed to display anatomical images of a patient acquired with MR and/or CT as well as images derived from DTI-data acquired with Magnetic Resonance Imaging (MRI).

iPlan Flow is a dedicated tool for planning trajectories of intra-cranial catheters. Guidelines for the catheter placement e.g. from catheter suppliers can be visualized and displayed to support the surgeon in improving catheter placement planning. The guidelines, in combination with anatomical information, can be used to suggest areas that are compliant with the guidelines. iPlan Flow does not generate or create rules for the placement of intracranial catheters by any means. iPlan Flow uses MR-DTI and T2weighted MR images to suggest likely volumes of fluid distribution.

The Primary mode of action for iPlan Flow is a device for creating treatment plans for stereotactic or image guided surgical treatment, especially for the creation of plans for the placement of intra-cranial catheters.

The treatment plans can be used in conjunction with other BrainLAB medical devices such as VectorVision for image guided surgical treatment.

Like iPlan!FLOW (K041330), iPlan Flow is a software tool running on a standard, standalone computer (PC or Laptop) or being accessible via the intranet connection for pre- or intraoperative planning of treatments based on stereotactic systems or image guided surgery systems.

Unchanged to iPlan!FLOW (K041330) iPlan Flow provides e.q. tools for the automatic or manual segmentation of anatomical structures which enables the user such as radiologists or neurosurgeons to quickly achieve the desired seamentation results through an unlimited number of automatic and/or manual re-segmentations. Like the predicate device iPlan!FLOW (K041330) iPlan Flow can be used for the planning of intracranial catheters, with image guided surgery. Guidelines provided e.g. by the catheter suppliers for the exact placements of intracranial catheters can be visualized. These quidelines comprise the minimal depth of the catheter tip in the brain tissue, the minimal distance of the catheter tip from intra-cranial surfaces and the minimal distance between different catheter tips. In addition to the predicate device the depth guideline can be calculated from the flow rate and the catheter diameter and warnings will be displayed if the trajectory of a planned catheter is likely to cross an intra-cranial surface. iPlan Flow is able to calculate a likely fluid distribution from the planned catheter positions to support the physician in his decision about appropriate catheter positions.

These features enable the surgeon to better plan and place intra-cranial catheters.

The created treatment plans of iPlan Flow can be used on its own or in conjunction with other BrainLAB medical devices such as VectorVision for performing the planned treatment.

The provided text is a 510(k) summary for the iPlan Flow device. It states that "The validation proves the safety and effectiveness of the system," and that the device was found "substantially equivalent" to its predicate device, iPlan!FLOW (K041330). However, the document does not describe any specific acceptance criteria for performance metrics or any detailed study demonstrating that the device meets such criteria.

Therefore, many sections of your request cannot be fulfilled based on the given document.

Here's a breakdown of what can and cannot be extracted from the provided text:

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

• Cannot be provided. The document states that the device was "verified and validated according to BrainLAB's procedures for product design and development" and was found "substantially equivalent" to the predicate device. However, it does not specify any quantitative acceptance criteria (e.g., accuracy, precision, sensitivity, specificity) or report specific performance metrics for the iPlan Flow device.

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

• Cannot be provided. The document does not mention any specific test set, its sample size, or data provenance.

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)

• Cannot be provided. The document does not describe any specific test set or the establishment of ground truth for such a set. It mentions that the software enables users like "radiologists or neurosurgeons to quickly achieve the desired segmentation results through an unlimited number of automatic and/or manual re-segmentations," but this refers to the use of the device, not the process of establishing ground truth for a validation study.

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

• Cannot be provided. No information about a test set or adjudication methods is present.

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

• Cannot be provided. The document does not describe an MRMC study or any results related to human reader improvement with or without AI assistance. The device is a "planning system" and an "aid" for surgeons in planning, not directly an AI for improving human reader diagnostic performance in a typical MRMC study context.

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

• Cannot be provided. While iPlan Flow is a software tool, the document doesn't detail a standalone performance study in the way this question implies (e.g., algorithmic accuracy without human interaction on a test dataset). Its functionality is inherently tied to assisting human planning.

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

• Cannot be provided. The document does not describe the specific ground truth used for any validation studies.

8. The sample size for the training set

• Cannot be provided. The document does not mention a training set or its sample size.

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

• Cannot be provided. The document does not mention a training set or how its ground truth was established.

Summary based on the provided text:

The 510(k) summary for iPlan Flow (K053164) focuses on demonstrating substantial equivalence to its predicate device, iPlan!FLOW (K041330). It states that the device was "verified and validated according to BrainLAB's procedures for product design and development" and that "The validation proves the safety and effectiveness of the system." However, it does not provide the detailed study results, acceptance criteria, sample sizes, ground truth establishment methods, or expert qualifications that would be required to answer your specific questions about performance metrics and validation studies. Such detailed information is typically found in the full 510(k) submission, which is more extensive than the summary provided.

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iPlan's indications for use is to prepare and present patient and image data based on CT, MR, Xray(Fluoro), including

• . image preparation
• . image fusion
• image segmentation .
  where the result is used for the creation of treatment plans for Stereotactic Surgery:
• Surgery Planning
• BrainMAP
• Functional Planning
  In addition iPlan's indications for use is to prepare and present patient and image data based on CT, MR, X-ray(Fluoro) including
• . image preparation
• . image fusion
• image segmentation .
  where the result is preplanned data to be used by other BrainLAB medical devices such as VectorVision (for performing the planned treatment) where these medical devices are used for:
• Image Guided Surgery
• FiberTracking
• BOLD MRI
  iPlan BOLD MRI indication for use is to prepare image data based on BOLD (blood oxygen level dependent) MRI scan studies and display the result as parametric images. When interpreted by a trained physician or surgeon this information may be used with other anatomical information for planning and image guided surgery.

The BrainLAB iPlan BOLD MRI module is software used for processing BOLD (blood oxygen level dependent) MRI sequences and display of calculation results. The slight MRI susceptibility changes between the images are visualized as parametric images.

The provided document is a 510(k) summary for the iPlan BOLD MRI module, a software used for processing BOLD MRI sequences and displaying calculation results as parametric images. The document states that the device has been verified and validated according to BrainLAB's procedures, and that this validation "proves the safety and effectiveness of the system." However, it does not contain specific details about acceptance criteria, a formal study protocol, or performance metrics to demonstrate the device meets acceptance criteria. The approval is based on substantial equivalence to a predicate device (BrainLAB iPlan K041703).

Therefore, most of the requested information regarding acceptance criteria and performance studies cannot be extracted from this document.

Here's a breakdown of what can and cannot be provided based on the input:

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

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

• Sample Size (Test Set): Not specified in the document.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not specified in the document.

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

• Number of Experts: Not specified in the document.
• Qualifications of Experts: Not specified in the document. The document states that the information "may be used with other anatomical information for planning and image guided surgery" when interpreted by a "trained physician or surgeon," but this is an intended use statement, not a description of ground truth establishment for a study.

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

• Not specified in the document.

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

• Not specified in the document. The document focuses on the software processing and display, not a comparative effectiveness study with human readers assisted by AI.

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

• The document implies a standalone performance (algorithm only) as it describes the software's ability to process BOLD MRI sequences and display results as parametric images. However, it does not provide specific performance metrics for this standalone function to prove it meets certain acceptance criteria. The assessment is based on verification and validation according to internal BrainLAB procedures.

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

• Not specified in the document.

8. The sample size for the training set

• Not specified in the document.

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

• Not specified in the document.

Summary of what is present:

• Device Name: iPlan BOLD MRI
• Manufacturer: BrainLAB AG
• Intended Use: To prepare image data based on BOLD MRI scan studies and display the result as parametric images. This information, when interpreted by a trained physician or surgeon, may be used with other anatomical information for planning and image-guided surgery.
• Device Description: Software used for processing BOLD MRI sequences and displaying calculation results. Visualizes slight MRI susceptibility changes between images as parametric images.
• Basis for Approval: Substantial equivalence to predicate device iPlan (K041703). The device underwent internal verification and validation procedures by BrainLAB to prove safety and effectiveness.

The 510(k) summary provides the regulatory and intended use context but lacks the detailed study results and performance metrics that would typically be found in a clinical trial report or a more comprehensive technical document.

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iPlan RT FiberTracking's indications for use is to prepare and present patient and image data based on CT, MR, Angiographic and other imaging sources including

• image preparation -
• image localization -
• image fusion -
• image segmentation -
• isocenter handling -
• plan review and approval
• fiber tracking -
  where the result is used for stereotactic radiation treatment planning that is intended for use in stereotactic, conformal, computer planned, LINAC based radiation treatment of cranial, head and neck and extracranial lesions.

Fiber Tracking:
iPlan RT FiberTracking's indication for use is to prepare and present patient and image data based on MRI scanned with diffusion-weighted sequences. These diffusion images are used for the calculation and display of fiber bundles in a selected region of interest. The created treatment plans of iPlan TT FiberTracking can be used million in a scienced region of interest. The StainLAB medical devices such as BrainSCAN, iPlan RT Image, and iPlan RT Dose where this medical device is used for radiotherapy treatment planning.

iPlan RT FiberTracking is developed to enhance the functionality of Intuition Image software with the import and il lan in 11 Tiber Husking to do volupes (DTI). Additional to the basic functions of Intuition Image (viewing, drawing, planning of annuolen concernment of this application provides functions for the import and inflage fusion and attrootable racessing of the DTI data and the display of calculated fiber tracks.

This document provides a summary of the iPlan RT FiberTracking device and its substantial equivalence to a predicate device, rather than a detailed study proving its acceptance criteria. Therefore, I cannot fully complete all sections of your request based solely on the provided text.

However, I can extract the information that is present and highlight what is missing.

Here's a breakdown of the available and missing information regarding acceptance criteria and a study proving device performance:

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

The provided text does not contain a table of acceptance criteria or reported device performance metrics for the iPlan RT FiberTracking. It states that the device "has been verified and validated according to BrainLAB's procedures for product design and development," and "The trailer was found to be substantially equivalent with the predicate device iPlan! FiberTracking (K041703) and Intuition Image (K032511)." This indicates that the device met internal validation criteria and regulatory substantial equivalence, but specific performance metrics or their comparison against acceptance criteria are not detailed.

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

This information is not provided in the text.

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)

This information is not provided in the text.

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

This information is not provided in the text.

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

This information is not provided in the text. The document describes a "planning system" and "medical charged-particle radiation therapy system" that includes "fiber tracking." While fiber tracking involves advanced image processing, the text does not characterize it as an "AI" system in the modern sense or discuss human-in-the-loop performance studies with AI assistance. The focus is on the device's functionality and substantial equivalence.

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

The text describes the iPlan RT FiberTracking as a system that "prepares and presents patient and image data" and is used for "calculation and display of fiber bundles." This suggests it's an algorithm-driven component. However, the document does not explicitly state that a standalone performance study was conducted or provide its results. The substantial equivalence claim implies that its performance is comparable to predicate devices, which would have undergone their own validation.

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

This information is not provided in the text.

8. The sample size for the training set

This information is not provided in the text. The device's description does not explicitly mention "training set" in the context of machine learning, as this document predates the widespread use of deep learning in medical devices. The development process emphasizes "verification and validation," which implies testing against established data, but not necessarily a distinct "training set" as understood today.

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

This information is not provided in the text.

In summary:

The provided document is a 510(k) premarket notification summary focused on establishing substantial equivalence to existing predicate devices. It states that the device was "verified and validated according to BrainLAB's procedures for product design and development" to ensure its safety and effectiveness. However, it does not include the detailed study methodology, acceptance criteria, specific performance metrics, or patient data acquisition details that would typically be found in a clinical study report. The substantial equivalence argument itself serves as the regulatory "proof" that the device meets acceptance criteria by being similar to already-accepted devices.

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The iPlan Hip Templating system is indicated for the preoperative planning of orthopedic treatments. It is specially developed for the preparation and display of anatomical patient data that has been acquired using xray, CT or MR equipment.

iPlan Hip Templating creates treatment plans in conjunction with 2D / 3D implant models are provided by a separate database. Both 2D and 3D planning are supported, depending on the anatomical information available.

The treatment plan can either be saved or printed as required.

iPlan Hip Templating is a stand-alone system for preoperative orthopedic treatment planning which facilitates digital template planning for anatomical images. Once image scaling has been completed, using an object of known size that is positioned next to the anatomical area of interest during image acquisition, the surgeons can use a range of measurement tools in order to select the optimum implant for the patient. The software overlays 2D / 3D implant models onto the image data and displays the result. The measurement tools can also be used to display preplanned and current values where required.

The digital implant models are provided by a separate implant database. Both 2D implant contours and 3D implant models are available.

Treatment plans can be saved and printed out as required. The information stored in the treatment plan can be loaded to other BrainLAB applications and used to support image guided surgery in a VectorVision system, for example.

Here's an analysis of the provided text regarding the iPlan® Hip Templating device, focusing on acceptance criteria and the study proving its performance:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state specific acceptance criteria (e.g., target accuracy percentages, precision thresholds) or detailed reported device performance in a quantitative manner.

Instead, the document makes a general statement:

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

The document does not provide any specific information regarding:

• The sample size used for any test set.
• The country of origin of the data.
• Whether the data was retrospective or prospective.

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

The document does not provide any information regarding:

• The number of experts used to establish ground truth.
• The qualifications of those experts.

4. Adjudication Method for the Test Set

The document does not mention any adjudication method used for a test set.

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

The document does not mention or describe a multi-reader multi-case (MRMC) comparative effectiveness study. Therefore, no effect size of human improvement with AI vs. without AI assistance can be determined from this text.

6. Standalone (Algorithm Only) Performance Study

The document mentions that "iPlan Hip Templating is a stand-alone system for preoperative orthopedic treatment planning," implying its intended use as an algorithm-only tool for planning. However, it does not describe a specific standalone performance study in terms of metrics. The phrase "The validation proves the safety and effectiveness of the system" is a general statement about the system as a whole, not a detailed report of standalone algorithmic performance.

7. Type of Ground Truth Used

The document does not specify the type of ground truth used for any validation or testing.

8. Sample Size for the Training Set

The document does not provide any information regarding the sample size for the training set.

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

The document does not provide any information regarding how the ground truth for the training set was established.

Summary of Findings:

The provided document (K042543 510(k) Summary) is a high-level regulatory submission focusing on demonstrating substantial equivalence to a predicate device (iPlan!®2 K020631). It asserts that the validation process (per BrainLAB's procedures) proves the safety and effectiveness of the system. However, it lacks the detailed technical information and study results typically found in reports specifically designed to describe acceptance criteria and evidence of meeting them. This type of information is often contained in the full 510(k) submission, which is not fully provided here. The summary focuses on the intended use, device description, and the FDA's concurrence with substantial equivalence rather than granular performance metrics and study details.

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