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Modus IR used with the Synaptive Surgical Exoscope is indicated for fluorescence imaging in conjunction with indocyanine green to aid in the visualization of vessels (micro- and macro-vasculature) and blood flow in the cerebrovasculature before, during, and after neurosurgery, plastic, and reconstructive surgeries.

Modus IR is an accessory of the Synaptive surgical exoscope. Modus IR provides surgical staff with a means to visualize vessels and blood flow during surgical procedures that may not be visible under white light conditions. When used with the appropriate imaging agent, light output at a specific wavelength excites the imaging agent, which emits light at a specific wavelength that is detected by the optical system, thereby allowing the user to differentiate the structure that the imaging agent has concentrated in. The imaging agent is not packaged or sold as part of Modus IR. It is the responsibility of the user to source and administer the applicable imaging agent according to the excitation and observation wavelengths of Modus IR. Modus IR is selectively enabled by authorized personnel using software configuration management.

Here's a breakdown of the acceptance criteria and study information for the Modus IR device based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for the Test Set

• Sample Size: 4 comparative video sets, resulting in 40 comparative evaluations (4 video sets * 10 neurosurgeons).
• Data Provenance: Prospective, in vivo animal study using two healthy porcine models. The specific country of origin is not mentioned, but the sponsor is based in Canada.

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

• Number of Experts: 10 neurosurgeons.
• Qualifications of Experts: The document explicitly states "neurosurgeons," implying they are medical professionals specialized in neurosurgery, making them qualified to assess the visualization of cerebrovasculature. Their specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

• The study used an assessment by 10 neurosurgeons who were blinded to which system they were evaluating. The video sets were presented in a randomized order.
• The results state "In all evaluations... was found to be functionally equivalent... (100% confirmation)." This implies a consensus or unanimous agreement among the neurosurgeons regarding the functional equivalence and suitability. It doesn't explicitly state a 2+1 or 3+1 method, but the 100% confirmation suggests that all 10 neurosurgeons agreed on the equivalence.

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

• Yes, an MRMC-like study was done. The in vivo animal study involved multiple readers (10 neurosurgeons) assessing multiple cases (4 comparative video sets) for comparative effectiveness between the subject device and the predicate.
• Effect Size of Human Readers Improve with AI vs. without AI assistance: This information is not provided in the document. The study aimed to demonstrate functional equivalence between the new device (Modus IR) and a predicate device (INFRARED 800 with FLOW 800 option) for aiding human visualization, not to quantify the improvement of human readers with AI assistance compared to without. Modus IR is an imaging accessory, not an AI-powered diagnostic tool in the sense of AI-driven image analysis or decision support for the clinician.

6. Standalone (Algorithm Only) Performance Study

• No, a standalone algorithm-only performance study was not explicitly mentioned or performed. The Modus IR is an imaging accessory that aids human visualization, not an algorithm that performs a task without human interpretation. Its performance is assessed in the context of aiding a human surgeon.

7. Type of Ground Truth Used

• For the in vivo animal study, the ground truth was expert consensus (10 neurosurgeons' unanimous agreement on functional equivalence and suitability of visualization).
• For the bench tests, the ground truth was based on objective measurements and comparisons against the predicate device using established metrics (e.g., limit of detection, spatial resolution measurements, qualitative assessment for image integrity).

8. Sample Size for the Training Set

• The document does not refer to or describe a training set for the Modus IR in the context of an AI/ML algorithm. Modus IR is described as an optical imaging accessory, not a software algorithm that performs diagnostic or analytical functions requiring a training set for machine learning. The software verification and validation mentioned are typically for ensuring software functions as intended, not for training a model.

9. How Ground Truth for the Training Set Was Established

• As no training set is described for an AI/ML algorithm, this information is not applicable.

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The Synq Software is indicated for use in conjunction with Synq, a magnetic resonance diagnostic device (MRDD) that produces axial, sagittal, coronal, and oblique cross-sectional images and displays the internal structure and/or function of the head. Depending on the region of interest, contrast agents may be used. These images when interpreted by a trained physician yield information that may assist in diagnosis.

The Synq Software allows a user to configure and initiate a magnetic resonance scan of a subject. In doing so, the software coordinates the interactions of the magnetic field, gradients, radio frequency (RF) transmitter and receiver coil in Synq (Previously known as EVRY, K200327) to produce axial, sagittal, coronal, and oblique cross-sectional images that represent the spatial distribution of protons with spin. The Synq Software Version 1.3 upgrades the current software version in the Synq system to include additional imaging applications, functionality, and minor bug fixes. The Software should be used only by qualified medical professionals who are trained in magnetic resonance diagnostic devices.

This document describes the Synaptive Medical Inc. Syng Software Version 1.3, a magnetic resonance diagnostic device (MRDD). The 510(k) submission (K232981) asserts its substantial equivalence to the predicate device (Evry, K200327).

Acceptance Criteria and Reported Device Performance

The provided text does not contain a specific table detailing acceptance criteria alongside reported device performance. However, it states:

"As per Bench Testing document attached under Bench Testing the image performance testing and safety testing meet all predefined acceptance criteria. Together, with an attestation from a U.S. Board certified radiologist, demonstrate substantial equivalence to the predicate device (EVRY K200327) by conforming to FDA recognized standards and addressing all requirements in FDA MRDD Guidance."

This indicates that the acceptance criteria were based on FDA recognized standards (NEMA MS 1, 2, 3, 4, 5, 8, 9; IEC 62464-1, IEC-60601-2-33) and FDA MRDD Guidance, focusing on image performance and safety. The reported performance is that the device meets all these predefined acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance

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

The text states: "A small, representative subset of clinical images are provided along with this 510(k) submission, as per guidance document 'Submission of Premarket Notifications for Magnetic Resonance Diagnostic Devices' issued November 18, 2016."

• Sample Size: "A small, representative subset of clinical images." The exact number is not specified in the provided text.
• Data Provenance: The text does not explicitly state the country of origin or whether the data was retrospective or prospective. It refers to "clinical images," which implies human subject data, but further details are absent.

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

The text mentions: "Together, with an attestation from a U.S. Board certified radiologist, demonstrate substantial equivalence to the predicate device (EVRY K200327) by conforming to FDA recognized standards and addressing all requirements in FDA MRDD Guidance."

• Number of Experts: At least one U.S. Board certified radiologist provided an attestation. It's unclear if more than one was involved for ground truth establishment.
• Qualifications: U.S. Board certified radiologist. The number of years of experience is not specified.

4. Adjudication Method for the Test Set

The document does not describe a formal adjudication method (like 2+1 or 3+1) for establishing the ground truth of the test set. It mentions an "attestation from a U.S. Board certified radiologist," suggesting a single expert's assessment was used, possibly against benchmarks.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, and its Effect Size

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "Synq Software Version 1.3 did not require clinical tests since substantial equivalence to the legally marketed predicate device was proven with the verification and validation testing." Therefore, there is no effect size of human readers improving with AI vs. without AI assistance to report.

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

Yes, a standalone performance assessment was effectively conducted through "image performance testing and safety testing" against predefined acceptance criteria derived from FDA recognized standards. This implies the software's output (images) was evaluated independently as part of the verification and validation. The role of the radiologist was for "attestation" and interpretation of images, rather than as part of a human-in-the-loop performance study.

7. The Type of Ground Truth Used

The ground truth for the verification and validation testing appears to be based on conformance to established technical performance standards and safety requirements (NEMA MS and IEC standards, FDA MRDD Guidance). For the clinical images, the "attestation from a U.S. Board certified radiologist" suggests a form of expert consensus/opinion regarding the quality and diagnostic utility of the images produced by the device, likely assessed against expected clinical standards of MRI imaging. Pathology or outcomes data are not mentioned.

8. The Sample Size for the Training Set

The document does not provide information regarding a training set. The submission focuses on verification and validation testing for an updated software version (1.3) of an already cleared device, implying the device's core algorithms were likely developed and validated previously. This 510(k) is for updates and does not detail the original training data for the base software.

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

Since no training set information is provided, there is no information on how its ground truth was established.

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Evry is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces axial, sagittal, coronal, and oblique cross-sectional images and displays the internal structure and/or function of the region of interest, contrast agents may be used. These images when interpreted by a trained physician yield information that may assist in diagnosis.

Evry is a magnetic resonance diagnostic device (MRDD) that uses a superconducting magnet to produce axial, sagittal, coronal, and oblique cross-sectional images, and displays the internal structure and/or function of the head. The system features various pulse sequences, imaging techniques and conform to NEMA DICOM standards (Digital Imaging and Communications in Medicine).

Integrated into the Magnetic Resonance Imaging system are a set of gradient coils which vary the strength of the applied magnetic field as a function of position and time, and are used to spatially encode the radio signals. Computed image reconstruction algorithms are then able to convert the encoded, digitized signals into images which can then be displayed to the user.

As with the predicate device, Evry includes the following technological components: Magnet scanner unit, gradient system and RF transmit coil, Equipment room containing the equipment needed to support the scanner unit functionality, Patient Transporter, 16-Channel Receive-Only Head Coil, Patient Communication System, Operator Console.

The furnished document describes the FDA 510(k) premarket notification for Evry, a magnetic resonance diagnostic device (MRDD). However, the document does not contain the detailed acceptance criteria or results of a clinical study that proves the device meets specific performance criteria in terms of diagnostic accuracy or comparative effectiveness with human readers.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (GE Medical Systems' 1.5T Signa HDx and 3.0T Signa HDx families) primarily through non-clinical performance data and conformity to recognized standards.

Here's an analysis of the provided text in relation to your request, highlighting what is present and what is missing:

Summary based on the provided document:

The provided document describes the FDA 510(k) premarket notification for Synaptive Medical Inc.'s "Evry" Magnetic Resonance Diagnostic Device (MRDD). The submission aims to demonstrate substantial equivalence to a legally marketed predicate device (GE Medical, 1.5T Signa HDx and 3.0T Signa HDx families).

The document primarily outlines non-clinical performance data and adherence to recognized consensus standards and FDA guidance documents. It does not contain a detailed clinical study demonstrating the device's diagnostic performance against specific acceptance criteria in terms of metrics like sensitivity, specificity, or reader improvement with AI assistance.

Details from the document related to your questions:

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

   • Not explicitly provided. The document states that "Non-clinical verification and validation tests have been performed with regards to the intended use, technical claims, requirement specifications and risk management results." It also notes that "The verification and validation test results demonstrate that Evry conforms with the aforementioned FDA-recognized consensus standards and guidance documents and meets the acceptance criteria."
   • However, specific quantitative acceptance criteria (e.g., minimum SNR, image quality metrics) and the exact reported values are not listed in a table format within this summary. It implicitly states that the device's performance is sufficient given its compliance with various engineering and safety standards (ISO, IEC, NEMA).

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

   • No specific test set for diagnostic accuracy is described. The document mentions a "direct determination peripheral nerve stimulation (PNS) volunteer study" with 20 subjects to characterize stimulation thresholds for safety purposes. This is a safety study, not a diagnostic performance study.
   • Data Provenance: The document does not specify the country of origin for the PNS study data or if it was retrospective or prospective, beyond stating it was a "volunteer study."
   • It mentions that "a representative set of clinical images of the proposed subject device have been reviewed by a U.S. Board Certified radiologist attesting that images produced by the device are of sufficient quality for diagnostic use." This implies some form of qualitative assessment of imaging, but not a large-scale test set for diagnostic performance.

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

   • For the qualitative image review, it mentions one U.S. Board Certified radiologist. No specific details about the radiologist's years of experience are provided in this excerpt.
   • For the PNS study, ground truth isn't applicable in the same diagnostic sense; it's about physiological response to stimulation.

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

   • Not applicable/Not described for diagnostic performance, as no such study is detailed. For the single radiologist review, no adjudication method would be necessary.

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 or AI assistance study was conducted or described. This device is an MRDD (MRI scanner), not an AI-powered diagnostic algorithm. Its function is to produce images for interpretation by a physician, not to interpret or assist in the interpretation of those images. Therefore, questions regarding AI assistance or human reader improvement are not relevant to the scope of this particular device's submission as described.

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

   • Not applicable. As stated above, this is an imaging device, not a diagnostic algorithm.

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

   • For the limited "clinical images review," the "ground truth" was the attestation by a U.S. Board Certified radiologist regarding the diagnostic quality of the images produced by the device. This is a qualitative assessment of image quality, not a diagnostic accuracy assessment against a confirmed patient condition.
   • For the PNS study, the "ground truth" was the direct observation of physiological responses (nerve stimulation) in volunteers.

8. The sample size for the training set:

   • Not applicable/Not described. This device is a hardware imaging system, not a machine learning algorithm that requires a training set in the typical sense.

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

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

Conclusion:

The provided document describes a Class II MRI device (Evry) seeking 510(k) clearance by demonstrating substantial equivalence. The clearance is primarily based on non-clinical performance data, conformance to recognized engineering and safety standards (e.g., ISO, IEC, NEMA, FDA guidance), and qualitative review of image quality by a radiologist. A safety study (PNS) was conducted with 20 subjects.

The document does not contain information related to a clinical study on diagnostic accuracy, sensitivity, specificity, or the comparative effectiveness of human readers with or without AI assistance, because the device itself is an MR scanner, not an AI-driven diagnostic tool. Therefore, many of the questions asked are not addressed by the provided content.

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Modus Nav is intended as a planning and intraoperative guidance system to enable open and percutaneous computer assisted surgery. The system is indicated for medical conditions requiring neurosurgical cranial procedures where the use of computer assisted planning and surgery may be appropriate. The system can be used for intra-operative guidance where a reference to a rigid anatomical structure can be identified. The user should consult the "Accuracy Characterization" section of the User Manual to assess if the accuracy of the system is suitable for their needs.

The subject device, Modus Nav, is a modified version of its predicate, BrightMatter Guide with SurfaceTrace Registration. The system is a surgical planning and image guided surgical system that enables open or percutaneous computer-assisted cranial surgery. The system uses optical 3D tracking technology to display the location and orientation of tracked (also known as navigated) surgical instruments relative to the pre-operative scan images of the patient. The system consists of a software application installed on a computer, tracked surgical instruments, and accessories to enable the tracking of those instruments.

The planning functionality of the device is provided by an already cleared device called BrightMatter Plan 1.6.0 (K180394). The remaining functionality of the system can be broadly grouped into data preparation, registration and visualization of surqical tools. Data preparation and registration is performed during the initial stages of a surgical procedure and visualization of the tools is performed as needed during the surgical procedure.

General use of the system as an image guided surgical tool is composed of the following key steps:

• . Equipment setup
• . Plan selection and data preparation
• Patient registration .
• . Tool localization and visualization

An optical Tracking Camera provides the position and orientation of the tools with respect to the tracking origin. The navigated surgical tools are tracked using singleuse passive reflective markers (K033621) that are attached to the surgical tools prior to each surqical procedure. An external display can be used by the surgical staff if needed, given that the Tracking Camera mounted on a cart maintains a line of sight between the Cranial Reference and the Tracked Surqical Tools. Both the User Cart (also known as Navigation Cart) and Auxiliary Carts are placed outside the sterile field.

The primary purpose of this 510(k) submission is to introduce new navigated tools such as the Short Pointer, Shunt Stylet, and the corresponding Calibration Device. It also introduces new software features to support the navigation of these tools, the ability to navigate with Synaptive's Trackable Suction tools, and minor workflow improvements to facilitate the surgical procedure.

The provided text describes the Modus Nav system, a surgical planning and image-guided surgical system for neurosurgical cranial procedures. Below is a summary of the acceptance criteria and the study that proves the device meets them, based on the provided document.

Acceptance Criteria and Reported Device Performance

The document primarily focuses on demonstrating substantial equivalence to a predicate device (BrightMatter Guide with SurfaceTrace Registration) rather than setting specific clinical performance metrics with target values for new device features. The acceptance criteria are largely centered around functional verification, safety, and equivalence to the predicate.

Additional Information Regarding the Study:

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

   • Accuracy Characterization: An "accuracy measurement phantom of similar volume to an adult head" was used. The specific number of measurements or trials conducted on this phantom is not specified.
   • Algorithm pipeline verification: "Known data sets" or "truth data sets" were used. The size, type, or provenance (country of origin, retrospective/prospective) of these datasets is not detailed.
   • For other tests like software verification, human factors, and user acceptance, the "test set" refers to the specific test cases, scenarios, or participants involved, but detailed numerical sample sizes are not provided.

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

   • Accuracy Characterization: Ground truth for the accuracy phantom was "obtained using a Coordinate Measurement Machine (CMM)." This implies a metrology standard rather than human experts.
   • Algorithm pipeline verification: "Expert review of output generated by the pipeline" was used. However, the number of experts and their qualifications are not specified.
   • User acceptance testing and Human Factors Validation: These tests were conducted "by intended user in a simulated use environment" and "by intended users," respectively. While these "users" would be qualified medical professionals, their specific number and detailed qualifications are not provided.

3. Adjudication method for the test set:

   • The document primarily describes verification and validation activities rather than studies requiring adjudicator consensus (like clinical trials for sensitivity/specificity).
   • For the "Algorithm pipeline verification," it mentions "expert review of output," but does not detail an adjudication method (e.g., 2+1, 3+1).
   • For other tests, the "documentation results" simply state that acceptance criteria were met, implying direct pass/fail assessment rather than a multi-reader adjudication process.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

   • No MRMC comparative effectiveness study was done. The document explicitly states: "This technology is not new; therefore, a clinical study was not considered necessary prior to release. The substantial equivalence of the device is supported by the nonclinical testing."

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

   • Algorithm pipeline verification: Yes, an "Automated performance verification of the core data processing facility of the software (known as 'algorithm pipeline'). Uses known data sets and expert review of output generated by the pipeline at various stages of processing." This suggests a standalone evaluation of the algorithm's output against known data.
   • Accuracy Characterization: This would also be considered a standalone performance test of the system's accuracy, without human interpretation of images directly impacting the accuracy measurement.

6. The type of ground truth used:

   • Accuracy Characterization: Ground truth was established using a "Coordinate Measurement Machine (CMM)" on an accuracy phantom, which is a physical measurement standard.
   • Algorithm pipeline verification: "Known data sets or 'truth data sets'" and "expert review" were used to establish ground truth for algorithm outputs. The nature of these "truth data sets" (e.g., expert consensus, pathology, simulated data) is not specified.
   • Software verification: Ground truth refers to the defined "software requirements specifications (SRS) items."

7. The sample size for the training set:

   • The document does not mention any training sets for machine learning models. The device's functionality as described primarily involves image-guided navigation based on optical tracking and pre-operative scans, rather than an AI/ML component requiring a separate training set for classification or detection tasks. The reference to "algorithm pipeline" suggests image processing, but no specific machine learning training is detailed.

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

   • Not applicable, as no training set for machine learning is explicitly mentioned or described.

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BrightMatter Plan is indicated for:

· Viewing, presentation and documentation of medical imaging, including different modules for image processing, image fusion, and image segmentation where the output can be used for image guided surgery.

· Planning and simulation of cranial surgical procedures.

· Reviewing of existing treatment plans.

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

BrightMatter Plan is a treatment planning software that enables the user to view and process medical image data. The software is intended for pre-operative planning of neuro-surgical treatments based on image guided surgical systems. The planning software system provides the ability to visualize diagnostic images in 2D and 3D formats and fusion of image datasets. The software automatically segments the skull from the acquired image and generates diffusion tracts from Diffusion Tensor Imaging (DTI) data. The user can also manually annotate regions of interest, resulting in structures which can subsequently be visualized in 3D. A trained person can use the software to segment structures, define regions of interest and establish one or more trajectories.

The software, operated on a stand-alone computer workstation, is expected to be used by a Clinician in an office or home setting, in preparation for one of several possible surgical procedures. The end of the processing is a surgical plan which can be exported to a Picture Archiving and Communication Systems (PACS) for subsequent use in image guided surgery.

Here's a breakdown of the acceptance criteria and study information for BrightMatter Plan 1.6.0, based on the provided FDA 510(k) summary:

Acceptance Criteria and Device Performance

Study Details

1. Sample Size used for the test set and the data provenance:

   • Test Set Sample Size: Not explicitly stated as a number of cases/patients. The document mentions "representative preoperative images" for design validation.
   • Data Provenance: Not specified in the provided text (e.g., country of origin, retrospective/prospective). It only mentions "representative preoperative images."

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

   • Number of Experts: Not explicitly stated. The design validation was conducted by "the intended user population," which typically implies multiple clinicians, but a specific number is not provided.
   • Qualifications of Experts: The intended user population consists of "medical professionals, including but not limited to surgeons and radiologists." No specific experience level (e.g., 10 years) is mentioned.

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

   • Not specified. The document states "evaluation of resulting plan for conformance to clinical expectations," which implies a qualitative assessment by the users, but no formal adjudication method is detailed.

4. 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 performed. The non-clinical testing and design validation focused on the software's performance and conformance to clinical expectations, assuming the user would utilize the tool. The comparison was primarily to a previous version of the same device.

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

   • The performance testing and unit/integration verification assessed the "algorithm pipeline" and "functional verification," which are inherent to standalone algorithm performance. However, the design validation explicitly involved "the intended user population," indicating a human-in-the-loop evaluation for the overall system. The focus appears to be on the device as a tool for clinicians, rather than a fully autonomous AI system.

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

   • Expert Consensus/Clinical Expectation: The ground truth for the design validation was "conformance to clinical expectations" as determined by the "intended user population." This implies clinical assessment and consensus on the accuracy and utility of the generated plans.

7. The sample size for the training set:

   • Not applicable/Not provided. This device is an updated version of a previous planning software (BrightMatter Plan 1.0) and primarily focuses on image viewing, processing, and surgical planning based on existing medical images. It's not described as a deep learning or machine learning model that requires a distinct "training set" in the conventional sense for a new algorithm. The "underlying technology used to process images is the same" as the predicate device.

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

   • Not applicable (see point 7).

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BrightMatter Guide is intended as a planning and intraoperative guidance system to enable open and percutaneous computer assisted surgery. The system is indicated for medical conditions requiring neurosurgical cranial procedures where the use of computer assisted planning and surgery may be appropriate. The system can be used for intraoperative guidance where a reference to a rigid anatomical structure can be identified. The user should consult the "Accuracy Characterization" section of the User Manual to assess if the accuracy of the system is suitable for their needs.

The BrightMatter Pointer is intended to be used for anatomy palpation and as a pointing tool to enable spatial localization and identification by BrightMatter Guide navigational systems.

BrightMatter Guide is a planning and image guided surgical system that enables computer assisted surgery where use of stereotactic image guidance may be considered appropriate. The BrightMatter Pointer is a handheld passive instrument which can be used for anatomy palpation using its tip. This tool can be tracked using passive reflective markers in order for BrightMatter Guide to identify and spatially track its location. There are rigid features on the subject device where the markers (passive spheres) that reflect infrared (IR) signals can be attached. The markers are arranged in a unique pattern on the device so that the BrightMatter Guide can differentiate it from other instruments. The Pointer portion of the device is provided non sterile and requires steam sterilization before use. The passive reflective markers are single-use.

The BrightMatter Pointer is made of either titanium alloy conforming to ASTM F136, Standard Specification for Wrought Titanium-6 Aluminum-4 Vanadium ELI (Extra Low Interstitial) Alloy for Surgical Implant Applications (UNS R56401) or 17-4 stainless steel conforming to ASTM A564 Standard Specification for Hot-Rolled and Cold-Finished Age-Hardening Stainless Steel Bars and Shapes.

The provided text describes a 510(k) premarket notification for a medical device called "BrightMatter Guide with BrightMatter Pointer." This document focuses on demonstrating the substantial equivalence of the new titanium version of the "Pointer tool" to previously cleared predicate devices. It outlines non-clinical testing performed to show this equivalence, rather than a clinical study establishing the device's efficacy against specific performance criteria for AI-assisted human reading.

Therefore, many of the requested details, such as those related to AI effectiveness studies, multi-reader multi-case studies, ground truth establishment for training and test sets, and sample sizes for training/test sets as they pertain to clinical performance, are not explicitly present in the provided document. The "acceptance criteria" discussed are primarily related to non-clinical performance and biocompatibility to prove substantial equivalence, not clinical efficacy or an improvement in human reader performance with AI.

Here's an attempt to extract and infer information based on the document, focusing on what is available regarding acceptance criteria and the non-clinical study:

Acceptance Criteria and Device Performance (Non-Clinical)

The document does not present clinical acceptance criteria for demonstrating improved diagnostic performance (e.g., sensitivity, specificity for a particular disease) or human reader performance. Instead, the acceptance criteria are focused on non-clinical performance and biocompatibility to prove substantial equivalence of a new material (titanium) for an existing device component (Pointer tool).

1. Table of Acceptance Criteria (Non-Clinical) and Reported Device Performance:

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BrightMatter Guide with SurfaceTrace Registration is intended as a planning and intraoperative guidance system to enable open and percutaneous computer assisted surgery. The system is indicated for medical conditions requiring neurosurgical cranial procedures where the use of computer assisted planning and surgery may be appropriate. The system can be used for intraoperative guidance where a reference to a rigid anatomical structure can be identified. The user should consult the "Accuracy Characterization" section of the User Manual to assess if the system is suitable for their needs.

The subject device, BrightMatter Guide with SurfaceTrace Registration is a modification of the software component of BrightMatter Navigation system that is presented in K142024. The system is a planning and image guided surgical system that enables computer assisted surgery where use of stereotactic image guidance may be considered appropriate. In particular, the device is suitable for neurosurgical cranial procedures. The planning functionality of the device is provided by an already cleared device, BrightMatter Planning (K140337). The remaining system provides a sequence of discrete workflow activities (or phases) that guide a surgeon through the process of data preparation for the surgical procedure. Then the device aids the surgeon in visualizing the location of the surgical tools relative to clinical images and physical location of the patient.

Following is a summary of steps involved in data preparation and registration of the patient's head position relative to pre-surgical clinical images:

• . Importing plan and imaging data
• Reviewing and selecting a previously generated surgical plan .
• . Optionally fusing (merging or co-registering) additional imaging data
• Registering the clinical images to the patient using either Point registration or . SurfaceTrace based registration.

Following steps are provided as visualization tools during the execution of the surgical procedure:

• . Aid in visualizing location of the surgical site as planned by the surgeon (using BrightMatter Planning software, K140337)
• . For trajectory-centric procedures, help visualize insertion of tracked surgical tools by identifying location of surgical tool's position and orientation relative to clinical images and the surgical plan developed by the surgeon
• . Visualize location of tracked surgical tools after the intended target location has been reached
• . The purpose of this 510k submission is introduce a new registration methodology using changes that are limited to the software component of the previously cleared system. Key functional components of the system are an optical tracking sub-system, navigated surgical tools, custom software application and an external display. The navigated surgical tools are tracked using single-use passive reflective markers (K033621) that are attached to the surgical tools prior to each surgical procedure.

The surgical display and tracking camera are mounted on an Auxiliary Cart. The computer is housed in a Navigation Cart. These components have been cleared as part of the BrightMatter Navigation system (K142024).

As with many systems in the OR, not all components need to be sterile during use. The only subcomponents that come in contact with the patient are the Pointing Tool, Port Reference Tool and Calibration Block. These tools fit in the limited contact duration category. The tools have been cleared as part of the BrightMatter Navigation system (K142024).

Here's a breakdown of the acceptance criteria and study information for the BrightMatter Guide with SurfaceTrace Registration device, based on the provided document:

Acceptance Criteria and Device Performance

Study Details:

1. Sample Size Used for the Test Set and Data Provenance:

   • Test Set Sample Size: The document refers to an "accuracy measurement phantom of similar volume to an adult head." It does not specify a numerical sample size for individual measurements on this phantom but implies a comprehensive set of measurements taken at various locations (center and boundaries of the tracking volume).
   • Data Provenance: The study was conducted internally by Synaptive Medical Inc. in Canada (based on the submitter's address). The data is prospective in the sense that the testing was performed on the device to characterize its performance for this submission.

2. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

   • The ground truth for the test set (the accuracy measurement phantom) was established using a Coordinate Measurement Machine (CMM). This implies mechanical measurement, not expert human assessment directly for the ground truth of the phantom. No human experts are explicitly mentioned as establishing the ground truth for the CMM measurements themselves.

3. Adjudication Method for the Test Set:

   • Not applicable. The ground truth for the phantom was established by a CMM, an objective mechanical measurement, not through human consensus.

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

   • No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly described. The testing focused on the standalone accuracy and performance of the device's new registration method. The "Design Validation" mentions simulated use with intended users, but this is described as confirming substantial equivalence and not an MRMC study measuring reader improvement with AI assistance.

5. Standalone Performance (Algorithm Only without Human-in-the-Loop Performance):

   • Yes, a standalone performance evaluation was conducted. The "Characterization of system accuracy" section directly assesses the device's ability to measure positional and angular errors using the SurfaceTrace registration method on an accuracy phantom, explicitly stating "Positional error was measured to be less than 2 mm and angular error was measured to be less than 2 degrees." This is an algorithm-only assessment of the core accuracy of the registration.

6. Type of Ground Truth Used:

   • Mechanical Measurement (CMM): The ground truth for the accuracy phantom was obtained using a Coordinate Measurement Machine (CMM).

7. Sample Size for the Training Set:

   • The document does not specify the sample size for any training set. It describes a modification to the software component of a previously cleared device and focuses on the performance characterization of the new SurfaceTrace Registration method. This submission is for a modification, and while the underlying BrightMatter Navigation system would have had development, the details of its training data are not provided here.

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

   • Since the document does not specify a training set sample size or details about a training set, it does not provide information on how its ground truth was established.

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Synaptive ImageDrive Pro is a device that displays medical images (including mammograms) and data from various imaging sources. Images and data can be viewed, communicated, processed and displayed within the system or across computer networks at distributed locations.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 Megapixel resolution and meet other technical specifications reviewed and accepted by the FDA.

Typical users of this system are trained professionals, including but not limited to radiologists, physicians, nurses, medical technicians, and assistants.

Synaptive ImageDrive Pro is a medical imaging informatics system that allows the storage, management, display and analysis of imaging and non-imaging data. The Synaptive ImageDrive Pro data repository can be populated either by manually uploading data through the user interface (UI) or in an unattended fashion by automatically receiving DICOM objects or HL7 messages from other information systems such as PACS and EMRs. Automatic data processing rules can be configured to process data when it arrives in the system. An example of this is when pre-operative MR scans are done and sent to ImageDrive to ensure that they were acquired using appropriate scan protocol before they are consumed downstream by other Synaptive applications, such as BrightMatter Plan (cleared as a Class-II device, K140337). Once in the system, the data is indexed so that it can be easily searched in the future. Imaging data can also be de-identified and securely shared with authorized persons. Further, the system provides an extensible architecture to enable local or distributed processing of the data. As data accumulates in the system, analytics can be generated to summarize, for example, intra- and inter-patient statistics and trends in surgical treatment planning based on surgical plan data that is output from external software that can generate data in compatible formats. An example of such external system is the surgical planning software manufactured by this applicant - - BrightMatter Plan. The subject device is composed of the following key features: A hierarchical folder system Three data storage areas Data processing functionality Analytics capability Image viewing capability

The provided text does not contain specific acceptance criteria or an explicit study describing the device's performance against those criteria in a quantitative manner. The document is a 510(k) summary for the Synaptive ImageDrive Pro, focusing on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance metrics from a dedicated clinical or non-clinical study to meet specific acceptance criteria.

However, based on the non-clinical testing and design validation sections, we can infer the intent of the acceptance criteria was to ensure the device performs as intended and is safe and effective.

Here's an attempt to answer your request based on the available information, with many points marked as "N/A" or "Not specified" due to the nature of the document:

1. Table of acceptance criteria and the reported device performance

Since specific quantitative acceptance criteria are not provided, I will infer general categories of performance based on the non-clinical testing performed.

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

• Sample size for the test set: Not specified. The document mentions "System validation testing using intended users" but does not provide details on the number of users or the test cases/data used.
• Data provenance: Not specified. It's a medical imaging informatics system that displays images from "various imaging sources," but the origin of data used for testing is not detailed. The product description indicates it receives DICOM objects or HL7 messages from PACS and EMRs, implying it handles clinical data.

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

• Not specified. The document mentions "System validation testing using intended users," which implies clinical professionals, but does not detail how ground truth was established for the validation tests or how many experts were involved.

4. Adjudication method for the test set

• Not specified.

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. The document explicitly states: "This technology is not new, therefore a clinical study was not considered necessary prior to release." The device is a Picture Archiving and Communication System (PACS) and generally, these systems are cleared based on substantial equivalence to existing technology, and not typically through MRMC studies that assess reader performance with and without AI. The device described does not appear to have an "AI" component that assists readers in interpretation in the way that would necessitate such a study.

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

• The device itself is a PACS for viewing, communicating, processing, and displaying medical images. It's not an algorithm that performs a diagnostic task independently. Its "performance" is tied to its functional capabilities (storage, management, display, processing, communication). Software verification and system validation were done, which tests the algorithm/system's internal functionality.

7. The type of ground truth used

• Not explicitly stated for the "test set" in the context of diagnostic performance. For general software verification and system validation, the "ground truth" would be the expected behavior of the system as defined by its requirements and design specifications. For the "intended users" validation, it would be the successful execution of tasks by users in a simulated environment.

8. The sample size for the training set

• Not applicable. This device is a PACS, not a machine learning algorithm that requires a "training set" in the conventional sense. Its "training" is in its development and programming, rather than learning from data.

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

• Not applicable, as there is no "training set."

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BrightMatter Navigation System is intended as a planning and intraoperative guidance system to enable open and percutaneous computer assisted surgery. The system is indicated for medical conditions requiring neurosurgical cranial procedures where the use of computer assisted planning and surgery may be appropriate. The system can be used for intra-operative guidance where a reference to a rigid anatomical structure can be identified.

The subject device, BrightMatter Navigation system, is a planning and image guided surgical system that enables computer assisted surgery where use of stereotactic image guidance may be considered appropriate. In particular, the device is suitable for neurosurgical cranial procedures. The planning functionality of the device is provided by an already cleared device, BrightMatter Planning (K140337). The remaining system provides a sequence of discrete workflow activities (or phases) that guide a surgeon through the process of data preparation for the surgical procedure. Then the device aids the surgeon in visualizing the location of the surgical tools relative to clinical images and physical location of the patient.

Following is a summary of steps involved in data preparation and registration of the patient's head position relative to pre-surgical clinical images:

• Importing plan and imaging data
• Reviewing and selecting a previously generated surgical plan
• Optionally fusing (merging or co-registering) additional imaging data
• Preparing and executing point-based registration

Following steps are provided as visualization tools during the execution of the surgical procedure:

• Aid in visualizing location of the surgical site as planned by the surgeon (using BrightMatter Planning software, K140337)
• For trajectory-centric procedures, help visualize insertion of tracked surgical tools by identifying location of surgical tool's position and orientation relative to clinical images and the surgical plan developed by the surgeon
• Visualize location of tracked surgical tools after the intended target location has been reached

Key functional components of the subject device are an optical tracking sub-system, navigated surgical tools, custom software application and an external display. The navigated surgical tools are tracked using single-use passive reflective markers (K033621) that are attached to the surgical tools prior to each surgical procedure.

The surgical display and tracking camera are mounted on an Auxiliary Cart. The computer is housed in a Navigation Cart.

As with many systems in the OR, not all components need to be sterile during use. The only subcomponents that come in contact with the patient are the Pointing Tool, Port Reference Tool and Calibration Block. These tools fit in the limited contact duration category.

Here's a breakdown of the acceptance criteria and study information for the BrightMatter Navigation System v1.0, based on the provided FDA 510(k) document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not explicitly stated as a number of "samples" in a traditional clinical sense. The accuracy testing was conducted using a "measurement phantom" that mimicked brain volume.
• Data Provenance: The document does not specify the country of origin for the phantom data. The study was a non-clinical study, primarily involving engineering and system performance testing.

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

• Number of Experts: Not applicable. The ground truth for the accuracy testing was established using a Coordinate Measurement Machine (CMM), which is a precision metrology instrument, not human experts.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The ground truth was established by CMM measurements, not human consensus requiring adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

• MRMC Study: No, an MRMC comparative effectiveness study was not conducted.
• Effect Size: Not applicable. The device is a navigation system for surgical guidance, not an AI diagnostic tool primarily evaluated by human reader performance on a diagnostic task.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Standalone Performance: Yes, the described accuracy testing (positional and angular error) is a form of standalone performance evaluation for the tracking and guidance algorithm. It assesses the device's inherent measurement capabilities without direct surgeon interaction in the measurement process (though it simulates surgical workflow via CT images of the phantom).

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth for the accuracy testing was established by Coordinate Measurement Machine (CMM) measurements on a measurement phantom. This provides high-precision physical measurements. In addition, for biocompatibility testing, established laboratory standards and measurement techniques were used to determine results.

8. The Sample Size for the Training Set

• Sample Size for Training Set: The document does not provide information about a "training set" in the context of an AI/machine learning model. The BrightMatter Navigation System is described as using an "optical tracking sub-system" and software for guidance. It's not explicitly stated to be an AI/ML device in the sense of requiring a large training dataset for model development. The software development follows a standard Software Development Life Cycle.

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

• Ground Truth for Training Set: Not applicable, as there's no explicit mention of a training set or AI/ML model training in the conventional sense. The "training" of such a system would typically involve calibrating the optical tracking hardware and validating the software algorithms against known physical parameters, where the "ground truth" would be the precisely known physical dimensions and positions.

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BrightMatter Planning's indications for use are the viewing, simulation of cranial surgical procedures and reviewing of existing treatment plans. Typical users of the software are medical professionals, including but not limited to surgeons and radiologists.

BrightMatter Planning is a treatment planning software that enables the user to view and process medical image data. The software is intended for pre-operative planning of neuro-surgical treatments based on image guided surgical systems. The planning software system provides the ability to visualize diagnostic images in 2D and 3D formats and fusion of image datasets. The software automatically segments the skull from the acquired image and generates diffusion tracts from DTI data. The user can also manually annotate regions of interest, resulting in structures which can subsequently be visualized in 3D. The end result of such processing is a set of images that can be used to develop a treatment plan for a neuronavigational procedure. The treatment plan is developed by a trained person. A trained person can use the software to segment structures, define regions of interest and establish one or more trajectories. The software, operated on a stand-alone computer workstation, is expected to be used by a Surgical Planner in an office setting, in preparation for one of several possible surgical procedures. The resulting treatment plan can be exported to a PACS for subsequent use in image guided surgery.

Here's a breakdown of the acceptance criteria and study information for the BrightMatter Planning Software, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly state quantitative acceptance criteria for the BrightMatter Planning Software. Instead, it focuses on demonstrating substantial equivalence to predicate devices and verifying software functionality. The key performance comparison is for DTI-derived image creation and tractography.

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

The document does not specify a separate "test set" in the context of clinical data for performance assessment. The "testing" primarily refers to non-clinical software verification and validation.

• Sample Size for Test Set: Not specified, as it's primarily a software validation and comparison to an existing system's output, not a clinical study with patient samples.
• Data Provenance: Not applicable in the context of a "test set" for clinical performance. The comparison for DTI tractography was against the output of Siemens syngo MR B17 software, implying existing data processed by that tool.

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

This information is not provided in the document. The performance assessment is based on comparison to an existing software's output rather than expert-established ground truth on a test image set.

4. Adjudication Method for the Test Set

Not applicable. There is no mention of a test set requiring adjudication from multiple readers.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Improvement with AI vs. Without AI Assistance

No, a Multi Reader Multi Case (MRMC) comparative effectiveness study was not done. The documentexplicitly states: "This technology is not new, therefore a clinical study was not considered necessary prior to release. Additionally, there was no clinical testing required to support the medical device as the indications for use is equivalent to the predicate device." Therefore, there is no information on the effect size of human improvement with or without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, a "standalone" evaluation of the algorithm's performance for DTI-derived image creation and tractography was done. The document states: "The DTI-derived image creation and tractography results were compared with Siemens syngo MR B17 software and were demonstrated to be equivalent in performance." This suggests an assessment of the algorithm's output directly against a benchmark, without necessarily involving a human reader in the performance metric itself.

7. The Type of Ground Truth Used

The "ground truth" for the DTI-derived image creation and tractography comparison was the output of a commercially available and cleared software: Siemens syngo MR B17. This serves as a comparative benchmark rather than an independent expert consensus, pathology, or outcomes data.

8. The Sample Size for the Training Set

The document does not mention a training set. This is consistent with a 510(k) submission for a software device that relies on established algorithms and demonstrates equivalence to predicate devices, rather than a new AI/ML device that requires extensive training data.

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

Not applicable, as no training set is mentioned or implied for this device.

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