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This device is a self-help tool for individuals aged 18 or older with diagnosed depression. It is intended to be used in addition to usual care and not as a replacement for it.

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The provided FDA 510(k) Clearance Letter for the HJY VisualNext 3D Endoscopic Vision System focuses on the device's substantial equivalence to a predicate device, as opposed to a detailed standalone or comparative effectiveness study of an AI-powered diagnostic device. Therefore, many of the requested details, particularly those related to AI algorithm performance (e.g., sample size for test/training sets, data provenance, ground truth establishment, MRMC studies, and effect size of human reader improvement with AI assistance), are not present in this document.

However, based on the information available, here's a breakdown of the acceptance criteria and the study that proves the device meets them:

Device Type: The HJY VisualNext 3D Endoscopic Vision System is an endoscopic vision system, not an AI-powered diagnostic device. Its primary function is to provide 3D visualization during surgical procedures, differentiating it from an AI-based system that might perform automated image analysis or diagnosis.

Acceptance Criteria and Reported Device Performance:

The document outlines acceptance criteria implicitly through the performance of various non-clinical tests. The criteria are met if the device "Pass[es]" the respective tests and demonstrates performance metrics comparable to predefined standards or the predicate device.

Study Details (for the Non-Clinical Performance Testing):

Since the device is a vision system and not an AI algorithm, the traditional "test set" and "training set" concepts as applied to AI models do not directly apply in the same way. The non-clinical testing evaluates the physical and functional performance of the device itself.

1. Sample size used for the Test Set and Data Provenance:

   • Bench Testing: The sample size is not explicitly stated, but it involved "aged and non-aged subject devices" and direct comparison to the predicate device. The data provenance would be laboratory-generated data from device performance measurements.
   • Animal Study Testing: "A porcine animal model" was used. The specific number of animals or trials within the animal study is not provided. The data provenance is described as being from a porcine animal model. This would be prospective data collection, specifically for this study.

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

   • This metric is not applicable in the context of this device's testing. The "ground truth" for a vision system's performance is typically established by objective physical measurements (e.g., MTF for resolution, calibrated light meters for illumination) and expert subjective evaluation of visual quality in a controlled setting, rather than a consensus on diagnostic findings. The document does not specify the number or qualifications of any human evaluators involved in the image quality assessment during bench or animal testing, only that the data "met the predefined acceptance criteria."

3. Adjudication Method for the Test Set:

   • Not applicable as the testing involves objective performance measurements and comparison against predefined criteria, not diagnostic interpretations requiring adjudication.

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

   • No. An MRMC study is typically performed for diagnostic devices where human readers interpret medical images, often with and without AI assistance, to measure diagnostic accuracy and efficiency. This device is a surgical visualization tool, not a diagnostic imaging device.

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

   • This is not an AI algorithm, so the concept of "standalone performance" of an algorithm is not applicable. The core function of the device is to provide images for human viewing. The non-clinical tests assess the device's ability to produce high-quality images and function as intended.

6. The Type of Ground Truth Used:

   • For Bench Testing: Objective physical measurements (e.g., resolution targets, light sensors, distortion grids) served as the "ground truth" for parameters like FOV, DOF, resolution, etc., along with comparison to the known performance of the predicate device.
   • For Animal Study Testing: The "ground truth" for image quality (resolution, illumination, color representation, contrast, noise) was likely based on objective evaluation against predefined standards and comparative assessment by skilled observers (e.g., surgeons, imaging specialists) who could judge the clarity and utility of the visualization in an anatomical context, compared to the predicate device's 2D view. Anatomical structures within the porcine model served as the "true" objects being visualized.

7. The Sample Size for the Training Set:

   • Not applicable. This device is a hardware system, not an AI algorithm trained on data. There is no "training set" in the context of machine learning.

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

   • Not applicable, as there is no training set.

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The AURORA Surgiscope System is intended for use in neurosurgery and endoscopic neurosurgery and pure neuroendoscopy (i.e. ventriculoscopy) for visualization, diagnostic, and/or therapeutic procedures, such as ventriculostomies, biopsies and removal of cysts, tumors, and other obstructions.

The Aurora Surgiscope System consists of two components: (1) a sterile, single use, Sheath with integrated illumination LEDs and camera, with an Obturator, and (2) a non-sterile, reusable control unit, Image Control Box (ICB).

The Sheath is intended to provide access to the surgical site by acting as the insertable portion of the device, as well as the instrument channel to accommodate other surgical tools. Depth markers are present along the length of the Sheath for user reference. The proximal end of the Sheath also incorporates a Tab, which serves as the location for fixation arm to hold the device.

At the proximal end of the Sheath is the Imager, which comprises the following components: LEDs (light emitting diodes), camera (and optical components), and focus knob.

• The LEDs provide illumination to the surgical field by directing light down the Sheath, along the working channel.
• The camera captures videos of the surgical field.
• The focus knob allows the user to adjust the focus of the camera to obtain the desired image quality.

To facilitate insertion of the Sheath into the surgical site, an Obturator is provided with the device. During device insertion, the Obturator is fully inserted into the Sheath, and the entire AURORA Surgiscope is advanced to the desired surgical location. The distal end of the Obturator is conical in shape to minimize tissue damage during device insertion. In addition, the proximal handle of the Obturator is designed to accommodate various stereotactic instruments for neuronavigation, which can further aid in device placement. The Obturator is removed after insertion.

The ICB is a non-sterile device that provides three main functions in the AURORA Surgiscope System:

• To power the LEDs and camera of the AURORA Surgiscope.
• To relay the video feed captured by the AURORA Surgiscope camera to a connected Medical Grade Surgical Monitor for real-time image visualization.
• To allow the user to make adjustments to the displayed video feed (e.g., contrast, brightness), and to vary the light output of the LEDs.

The user interface is a membrane keypad with buttons located on the ICB that can be depressed for image adjustment, such as zoom, contrast, and brightness. The connection ports to the AURORA Surgiscope, Medical Grade Surgical Display Monitor, and Power are located on the side of the ICB, along with the ON/OFF switch.

The provided FDA 510(k) clearance letter for the AURORA Surgiscope System (K250752) does not contain the detailed information necessary to fully answer all the questions regarding acceptance criteria and the study that proves the device meets them.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (K201840) based on technological characteristics and functional requirements. It explicitly states that "No clinical test/studies were required or performed as all conducted performance tests appropriately support a determination of substantial equivalence compared with the predicate device (K201840)."

Therefore, for many of the requested points, the answer will be that the information is not available in the provided text.

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

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

The document mentions "functional requirements" and "performance tests" but does not detail specific acceptance criteria or quantitative performance results. It only states that the device meets these requirements after sterilization, environmental, and transit conditioning, and equivalent to a 1-year shelf-life.

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

• Sample size for test set: Not specified. The document states "non-clinical testing was performed" but does not detail the number of units tested.
• Data provenance: Not specified. The nature of the testing (functional performance, sterilization effects) suggests it would be laboratory testing rather than patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable / Not specified. Since no clinical studies were performed, there was no need for expert review of clinical data to establish ground truth. The "ground truth" here would be the successful function of the device in engineering tests.

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

• Not applicable / Not specified. No clinical data was being adjudicated.

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: "No clinical test/studies were required or performed". This device is a surgical endoscope, not an AI-assisted diagnostic tool, so an MRMC study comparing human readers with and without AI assistance is not relevant to its clearance.

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

• Not applicable. This is a physical medical device (endoscope), not a standalone algorithm.

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

• For the non-clinical performance tests mentioned, the "ground truth" would be the engineering specifications and functional integrity of the device. This is typically verified through direct measurement, visual inspection, and functional tests (e.g., image quality assessment, illumination intensity, camera function, mechanical integrity) against predefined specifications. It is not based on clinical "ground truth" like pathology or expert consensus.

8. The sample size for the training set

• Not applicable. This notice does not describe an AI/machine learning device that requires a training set.

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

• Not applicable. No training set was involved for this device.

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The cCeLL - In vivo is an optic scanner probe placed in direct contact with tissue to create images of the internal microstructure of tissues and is indicated for use with indocyanine green (ICG) for fluorescence imaging as an aid in the visualization of vessels (micro- and macro-vasculature) blood flow in the cerebrovasculature before, during or after cranial diagnostic and therapeutic procedures, such as tumor biopsy and resection.

The cCeLL - In vivo is used to provide real-time endoscopic images of near-infrared (NIR) indocyanine green (ICG) dye fluorescence during minimally invasive, neurosurgery in adults.

The overall system includes a 6 mm Pixection ICG/NIR Endoscope (0°) for use in neurosurgery, a light source for emission of NIR illumination, a photo-multiplier tube capable of capturing NIR imaging, and a sterile probe sheath intended for maintaining a sterile barrier between the subject device and the patient. The cCeLL - In vivo can be used with any medical grade high definition (HD) monitor with a DVI-D or RGB input. The patient contacting components contact tissue or bone with a duration of less than 24 hours.

The provided text describes the cCeLL - In vivo device and its performance testing to demonstrate substantial equivalence to a predicate device. However, it does not include specific quantitative acceptance criteria or a dedicated study demonstrating the device meets those criteria in the typical sense of showing numerical thresholds for performance. Instead, the performance testing focuses on equivalence to a predicate device.

Here's an analysis of the provided information:

Acceptance Criteria and Reported Device Performance

The document describes various performance tests conducted to demonstrate the substantial equivalence of the cCeLL - In vivo device to its predicate. The "acceptance criteria" are implied to be achieving performance comparable to or equivalent to the predicate device, or meeting recognized safety and design specifications. The reported "device performance" is consistently "PASS" for all tests, indicating that the device met these implicit criteria of equivalence or specification conformance.

Study Details for Performance Testing:

The document does not detail a single comprehensive "study" but rather a series of "Performance Testing" activities.

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

   • For "Image Sensitivity Analysis" and "Image Comparison Analysis," a "small animal model" was used. The exact number of animals is not specified.
   • For other tests like Detection Linearity, Geometric Distortion, Dynamic Range, Illumination & Detection Uniformity, SNR & Sensitivity, and Video Latency, the tests were conducted using the subject and predicate devices, likely in a laboratory setting, without specific mention of "samples" in a patient data context.
   • Data provenance is not explicitly stated as retrospective or prospective, or country of origin for the animal model. Given the context of equivalence testing against a predicate device, it is likely that these were controlled laboratory/pre-clinical tests.

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

   • For the "Image Comparison Analysis," the results state: "as assessed across users with a range of experience." This implies human assessment, but the number of experts, their specific qualifications (e.g., radiologist with X years of experience), and how their input established ground truth are not specified.
   • For all other tests, no experts were mentioned for establishing ground truth; the "ground truth" was likely defined by established physical properties or engineering measurements (e.g., optical power, brightness, tear resistance force).

3. Adjudication method for the test set:

   • The document does not specify any adjudication method (e.g., 2+1, 3+1, none). For the "Image Comparison Analysis" where "users with a range of experience" assessed images, the method of combining their assessments or resolving discrepancies is not provided.

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, an MRMC comparative effectiveness study was not done. The document describes performance testing for substantial equivalence, not a comparative effectiveness study involving human readers with and without AI assistance. The device is a medical imaging device, but the testing focuses on its technical performance and equivalence to a predicate, not on improving human reader performance.

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

   • The device is described as an "optic scanner probe" and a "medical fluorescence imaging device." The tests described are primarily focused on the intrinsic technical performance of this imaging device (e.g., image sensitivity, detection linearity, dynamic range, SNR, video latency). While "Image Comparison Analysis" involved "users," most tests, particularly the quantitative ones, appear to be standalone algorithm/device performance tests. The device itself is an imaging tool, not one that implies an "algorithm only" component separate from the imaging hardware.

6. The type of ground truth used:

   • For "Image Sensitivity Analysis" and "Image Comparison Analysis," the ground truth was inferred from the "visualization of cerebral microstructures and vascular systems" in a small animal model, which represents a biological/physiological ground truth.
   • For other engineering-focused tests (Detection Linearity, Geometric Distortion, Dynamic Range, Illumination & Detection Uniformity, SNR & Sensitivity, Video Latency, Sterile Probe Sheath Tear Resistance, Electrical Safety / EMC), the ground truth would be based on physical measurements and established standards/specifications.
   • For Biocompatibility and Sterility/Shelf Life, the ground truth is adherence to validated international standards and protocols.

7. The sample size for the training set:

   • The document does not provide any information regarding a "training set" or "sample size for the training set." This suggests the device (cCeLL - In vivo) is an imaging system, likely based on established optical and fluorescence imaging principles, and not necessarily an AI/machine learning product that requires a distinct training dataset in the typical sense for its core functionality.

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

   • Since no training set information is provided, this question is not applicable based on the given text.

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The Digital ClarusScope System and Digital NeuroPEN System are intended for use in neurosurgery, endoscopic neurosurgery, and ventriculoscopy for visualization of ventricles and structures within the brain during neurological surgical procedures, diagnostic and/or therapeutic procedures such as ventriculostomies, biopsies and removal of cysts, tumors and other obstructions.

The Digital ClarusScope System and Digital NeuroPEN System are neurological endoscopes which provide a light source, camera, and HDMI output for visualization. Irrigation is provided for flushing during the procedure. The working channel facilitates the use of tools necessary for neurological procedures (Digital ClarusScope versions only). The Digital ClarusScope and Digital NeuroPEN are intended to be used with the non-sterile, reusable Clarus Digital Control Module with standard HDMI video output. The proximal end of the Digital ClarusScope and Digital NeuroPEN terminate in two fittings: the endoscope connector attaches to the Clarus Digital Control Module, which interfaces to a standard off-the-shelf HDMI video monitor which is not provided by Clarus and is not part of this 510(k) application: the other fitting is an irrigation extension tube with a female Luerlock connector.

The provided text describes the regulatory clearance of the Clarus Medical Digital ClarusScope System and Digital NeuroPEN System, but it does not contain the specific acceptance criteria or a study proving that the device meets those criteria, as typically found in clinical performance study results.

The document details non-clinical performance data and a comparison to predicate and reference devices to establish substantial equivalence. It lists various tests performed, such as dimensional verification, mechanical strength, functional tests like fluid patency and image output, simulated use, sterility validation, shelf-life, environmental conditioning, distribution, biocompatibility, electrical safety, and electromagnetic compatibility.

However, it explicitly states:
"H. Non-Clinical Performance Data: The Digital ClarusScope, Digital NeuroPEN, and Digital Control Module have been thoroughly tested through verification of product specifications and user requirements. The following quality assurance and performance measures were applied during the development of the systems:
...

• Performance Testing (Verification):
  • Endoscope dimensional verification
  • o Mechanical strength requirements
• Functional Tests
  • Endoscope fluid patency o
  • O System image output
• Simulated Use Test
  • o Interconnection testing between endoscope and control module and accessories
  • Compatibility with introducer O
  • Compatibility of endoscope working channel with accessory devices O"

This section indicates that performance testing was conducted for verification, but it does not provide:

1. A table of acceptance criteria and reported device performance against those criteria.
2. Details of a clinical study with patient data, ground truth establishment, or expert reviews, which would be typical for proving performance in a diagnostic or image-interpretation context (e.g., accuracy, sensitivity, specificity).
3. Information regarding sample sizes for test sets, data provenance, number or qualifications of experts, or adjudication methods for establishing clinical ground truth.
4. Whether a multi-reader multi-case (MRMC) comparative effectiveness study was done to assess human reader improvement with AI assistance (the device is a visualization system and not explicitly described as an AI-enabled diagnostic aid in this document).
5. Details on standalone algorithm performance.
6. The type of ground truth used for performance evaluation in a clinical context.
7. Sample size or ground truth establishment for a training set, as this document focuses on the device performance and not the performance of an embedded AI algorithm that would typically require such training data.

Based on the provided text, the device primarily focuses on visualization and mechanical/electrical safety and functionality, not on diagnostic accuracy based on image interpretation by an algorithm. Therefore, the information requested regarding acceptance criteria and clinical study details for diagnostic performance is not present in this document.

The document's conclusion of "Substantial Equivalence" is based on "performance testing, design and non-clinical testing," which aligns with the details provided in section H.

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The Aurora Surgiscope System is intended for use in neurosurgery and endoscopic neurosurgery and pure neuroendoscopy (i.e. ventriculoscopy) for visualization, diagnostic and/or therapeutic procedures such as ventriculostomies, biopsies and removal of cysts, tumors and other obstructions.

The Aurora Surgiscope System consists of two components: (1) a sterile, single use, sheath with integrated illumination LEDs and camera, with an obturator, and (2) a non-sterile, reusable control unit, Image Control Box (ICB).

The sheath is intended to provide access to the surgical site by acting as the insertable portion of the device, as well as the instrument channel to accommodate other surgical tools. Depth markers are present along the length of the sheath for user reference.

At the proximal end of the sheath is the imager, which comprises the following components: LEDs (light emitting diodes), camera (and optical components), and focus knob.

• The LEDs provide illumination to the surgical field by directing light down the sheath, along . the instrument channel.
• The camera captures video image of the surgical field. ●

The proximal end of the sheath also contains a tab, which may be used to manually hold the device. To facilitate insertion of the surgical site, an obturator is provided with the device. During insertion, the obturator is fully inserted into the sheath, and the entire unit is advanced to the desired location. The distal end of the obturator is conical in shape to minimize tissue damage. In addition, the proximal handle of the obturator is designed to accommodate various stereotactic instruments for neuronavigation. Once inserted, the obturator is removed. Two sterile, single use accessories optional for use are provided with the Aurora Surgiscope System: an Irrigation Device and 12 French Suction Device.

The ICB is a non-sterile device that provides three main functions in the Aurora Surgiscope System:

• To power the Surgiscope LEDs and camera
• . To relay the video feed captured by the Surgiscope camera to a display monitor for real-time image visualization
• . To allow the user to make adjustments to the displayed video feed (e.g., contrast, brightness), as well as vary the LED light output.

The user interface is a membrane keypad with buttons located on the ICB that can be depressed for image adjustment, such as zoom, contrast, brightness, and orientation. The ICB is supplied with two cables: A power cable for connection to an AC wall outlet, and a display cable for connection to a high definition surgical monitor.

The provided FDA 510(k) clearance letter and summary for the Aurora Surgiscope System do not contain information typically found in a clinical study report or performance evaluation for an AI/software device. The document focuses on demonstrating substantial equivalence to a predicate device, which means proving that the new device is as safe and effective as a legally marketed device, rather than rigorously quantifying performance against defined acceptance criteria in a study setting.

Specifically, the document does not include:

• A table of acceptance criteria and reported device performance related to a diagnostic or AI function.
• Sample sizes for test sets or data provenance for AI model validation.
• Details about expert readers, ground truth establishment, or adjudication methods for AI performance.
• Information on multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance data.
• Training set details for an AI model.

The "testing" mentioned in the document pertains to traditional medical device testing for hardware, biocompatibility, electrical safety, and mechanical aspects. While it states "Software verification and validation testing" was conducted and "documentation provided as recommended by the FDA Guidance Content of Premarket Submissions for Device Software Functions," it does not provide any specific performance metrics or acceptance criteria for software functionality that would typically be associated with an AI/ML-driven device's diagnostic performance. The "Image Control Box" software mentioned focuses on image adjustment and display, not diagnostic interpretation.

Therefore, based solely on the provided text, it is not possible to describe the acceptance criteria and the study proving the device meets those criteria from an AI/ML perspective. The device, as described, appears to be a neurological endoscope system for visualization, diagnostic, and therapeutic procedures, with software for image display and adjustment, not an AI-powered diagnostic tool.

If this were an AI-powered device, the information requested would be crucial for its evaluation. Without it, I cannot fulfill the request for AI-related performance criteria.

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The Neuroblade System is a neuroendoscopy system indicated for the illumination and visualization of intracranial tissue and fluids, controlled aspiration of tissue and or fluid, powered cutting of soft tissue, and coagulation of tissue under direct visualization during surgery of the ventricular system or cerebrum.

The Neuroblade System is comprised of three components: Neuroblade, Neuropad and Cart. The Neuroblade is a hand-held, sterile neuroendoscope with lighting and camera at its distal end. The camera images are displayed on the Neuropad via a connecting cable that extends from the proximal end of the Neuroblade. It has integrated irrigation and aspiration functions. The distal bipolar electrode allows the application of RF energy from a third-party radiofrequency (RF) generator for coagulation of bleeding vessels in the neuro space. A cutting window on the side of distal end is for the removal of blood clots. The Neuroblade System, like other neuroendoscopes, is advanced into the brain through a burr hole created in the patient's skull. The tip of the Neuroblade is advanced under visualization via the illuminated camera image transmitted from the distal tip of the Neuroblade to the Neuropad. The Neuroblade has irrigation and vacuum tubing (2.0 m) that allows for connection to a third party saline infusion bag and a vacuum waste bucket, respectively. The waste bucket is connected to a vacuum regulator which is attached to the hospital's vacuum system. The bipolar electrode is incorporated into the distal tip of the Neuroblade and has a bipolar plug (20 cm) on the proximal end that allows for connection to a third-party bipolar cord. The proximal end of that bipolar cord connects to the RF Generator. An RF Generator and bipolar cord are common accessories in the operating room. The Neuroblade has a working channel that will facilitate the introduction of flexible endoscopic surgical devices (≤1.7 mm outer diameter) into the surgical site. That same working channel will also facilitate irrigation of the target site and is the channel that supports the aspiration of fluid and tissues. The Neuropad can be installed onto the Cart and adjusted by the user for height and tilt. The Neuropad allows the user to input patient data, control some aspects of the image, and record the case.

I am sorry, but the provided text does not contain the specific acceptance criteria for the device, nor the detailed results of a study that proves the device meets those criteria in a format that would allow me to populate the requested table directly. The document primarily describes the device, compares it to predicate devices, and lists various tests performed (biocompatibility, electrical safety, bench testing, an animal study, etc.) with a "Pass" result, but without specifying the quantitative or qualitative acceptance criteria for each of those tests or linking them to a comprehensive performance evaluation in the way requested.

Specifically, the document lacks:

1. A table of acceptance criteria and reported device performance: While tests are listed, the specific criteria for "Pass" are not detailed, nor are numerical or descriptive performance metrics provided for each criterion.
2. Sample size used for the test set and data provenance: A general animal study is mentioned, but specific sample sizes for particular performance tests are not given.
3. Number of experts used to establish ground truth and their qualifications: Not explicitly stated for any specific test.
4. Adjudication method: Not discussed.
5. MRMC comparative effectiveness study: No mention of such a study or effect sizes of human reader improvement with AI. The device is a neuroendoscopy system, not an AI-assisted diagnostic tool.
6. Standalone performance: The tests are generally standalone device performance evaluations, but the specific metrics are not provided as requested.
7. Type of ground truth: For the animal study, necropsy and histopathology were used for confirmation, but for other tests, "ground truth" in the requested sense is not clearly defined.
8. Sample size for the training set: Not applicable as this is not an AI/ML device with a separate training set.
9. How ground truth for the training set was established: Not applicable.

The document mainly focuses on proving substantial equivalence to predicate devices through various engineering and safety tests, rather than presenting a clinical performance study with detailed acceptance criteria and results.

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The QEVO System is intended for viewing internal surgical sites during general surgical procedures and for use in visualization of ventricles and structures within the brain during neurological surgical procedures as well as for viewing internal surgical sites during anterior spinal procedures, such as nucleotomy, discectory, and foraminotomy.

The QEVO System comprises of the QEVO ECU (Endoscope Control Unit) and QEVO endoscope. The system is intended for viewing internal surgical sites and for use in visualization during general and certain neurosurgical and spinal procedures. The QEVO System has to be installed and integrated with a host display device (surgical microscope, a monitor, etc). Requirements for physical integration, connectivity, power supply, display resolution, and software integration are established and tested.

The provided document is a 510(k) premarket notification summary for the QEVO System, declaring its substantial equivalence to a predicate device (QEVO System with KINEVO 900). This type of submission focuses on demonstrating that a new device is as safe and effective as a legally marketed device, primarily by showing similar technological characteristics and intended use.

Crucially, this document does NOT contain information about acceptance criteria or a study proving the device meets those criteria in the context of AI/ML performance testing. The "Summary of Studies" section only mentions:

• Sterilization and Shelf Life: The device is reusable and the reprocessing instructions are identical to the predicate device.
• Biocompatibility: Testing was done in accordance with ISO 10993 for the patient-contacting component (insertion tube).
• Performance Testing - Bench: Optical safety was assessed according to IEC 62471:2006. It explicitly states: "The determination of substantial equivalence was not based on an assessment of performance data." This indicates that no clinical performance study (like an MRMC study or standalone algorithm performance) was submitted or required for this 510(k) clearance, as the device is an endoscopic visualization system, not an AI/ML diagnostic tool.

Therefore, I cannot extract the information required to answer your prompt because the provided text pertains to a traditional medical device (an endoscope system) clearance, not an AI/ML-driven device that would involve the rigorous testing methodologies you've asked about (e.g., ground truth, reader studies, test set sizes, etc.).

To summarize why I cannot provide the requested information based on the given text:

• No AI/ML Component: The QEVO System is described as a visualization system (endoscope) that displays images. There's no mention of an embedded AI/ML algorithm for image analysis, diagnosis, or decision support.
• No Performance Data for Clinical Effectiveness: The submission explicitly states that the substantial equivalence determination was not based on performance data. This implies a reliance on technological similarity to the predicate and standard bench testing for safety (electrical, optical) and functionality (image resolution, field of view, etc.).
• Focus on Substantial Equivalence: The entire document is about demonstrating that the new QEVO System is "substantially equivalent" to an existing predicate device, primarily by comparing their specifications and intended use, rather than proving a new diagnostic capability through clinical performance studies.

If you have a document related to an AI/ML medical device, please provide that, and I would be able to address your specific questions about acceptance criteria, study design, and ground truth establishment.

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HJY VisualNext™ Endoscopic Vision System is intended for viewing internal surgical sites during general surgical procedures and for use in visualization of structures within the brain during neurological surgical procedures as well as for viewing internal surgical sites during anterior and posterior spinal procedures, such as nucleotomy, discectomy, and foraminotomy.

The HJY VisualNext™ Endoscopic Vision System is a system used for viewing internal surgical sites during surgical procedures. The system consists of the following components:

• . Endoscope Control Unit (ECU) (Model number: HDSES01)
• . Endoscope (Model number: HDSE201)
  The endoscope is physically connected via a 5m BNC cable to the Endoscope Control Unit (ECU). The Endoscope consists of 2 LED lamps and a CMOS camera, embedded in the proximal end of a rigid metal arthroscope, which captures the image and transmits to and is processed by the Endoscope Control Unit (ECU), subsequently output to and presented on an external monitor. Images are recordable and markable for further analysis. The Endoscope Control Unit (ECU) is not connectable to intranet or Internet.

The provided text describes the acceptance criteria and the study that proves the device meets those criteria for the HJY VisualNext Endoscopic Vision System, a neurological endoscope.

Here's the breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document lists various non-clinical tests performed, each with a "Purpose" (which implicitly contains the acceptance criteria) and "Results" (reported device performance). Since the original document doesn't provide a consolidated table of acceptance criteria with numerical targets before the results, the "Purpose" section of each test effectively serves as the acceptance criteria statement. For clarity, I will present the key performance parameters.

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

• Sample Size for Physical/Optical Tests: For most physical and optical performance tests (FOV, Direction of View, Optical Magnification, Distortion, Image Intensity Uniformity, Signal-to-Noise Ratio, Sensitivity, Depth of Field, Image Resolution), the tests were conducted using a "Disposable endoscope and Endoscope Control Unit (ECU) in both non-aged and aged conditions." The specific number of individual units tested for each parameter is not explicitly stated beyond "disposable endoscope."
• Sample Size for Image Quality Test (Biological Tissue Model):
  • ECU: Non-aged and aged ECU units were used. (Quantity not specified, but implied as at least one of each).
  • Endoscopes: "Six pieces of endoscopes each from non-aged and aged conditions were used for brain and spinal surgery, respectively." This means 6 non-aged endoscopes for brain surgery, 6 non-aged for spinal surgery, 6 aged for brain surgery, and 6 aged for spinal surgery.
  • Comparators: "Two cleared devices each for spine and brain were applied for comparing with non-aged and aged subject devices."
• Data Provenance: The tests were non-clinical laboratory studies. The "Image Quality Test utilizing a clinically relevant biological tissue model" was performed using a "live pig model" in "an animal operating room of a facility accredited under AAALACi standards," following "GLP standard." The country of origin for the data is not specified directly, but the company is based in Taiwan. The document states "No clinical test data was used to support the decision of substantial equivalence," indicating these were not human subject trials.

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

This information is not provided in the document. For the physical/optical tests, the "ground truth" is established by the measurement apparatus and methods themselves. For the Image Quality Test on a biological tissue model, the results state "The image quality of the non-aged and aged subject device passed the pre-defined acceptance criteria," and was "comparable to that of the FDA-cleared comparator devices." It's highly probable that expert assessment was involved in determining "image quality" or "comparability," but the number and qualifications of these experts are not explicitly mentioned in the provided text.

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

This information is not provided in the document. For most non-clinical performance tests, adjudication (as in clinical image review) is not typically applicable. For the image quality assessment in the biological tissue model, while agreement was tested, details of an adjudication method among multiple evaluators (if any) are 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:

This information is not applicable/not provided. The device is an endoscopic vision system, not an AI-assisted diagnostic tool for image interpretation by human readers. The studies described are non-clinical performance evaluations of the device's optical and imaging capabilities, and comparison of its image quality to a predicate device. No MRMC study regarding human reader performance with or without AI assistance was conducted or is relevant to this submission.

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

This information is not applicable/not provided as the device is not an AI algorithm. It is an endoscopic vision system that provides direct visual output for human use. The performance tests are of the hardware's image capture and display capabilities in a standalone manner (i.e., the system itself creating the image).

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

For the various physical and optical parameters, the "ground truth" is based on instrumented measurements against defined engineering specifications and comparison to the predicate device's characteristics. For the "Image Quality Test utilizing a clinically relevant biological tissue model," the ground truth for acceptability was based on pre-defined acceptance criteria and comparability to FDA-cleared comparator devices. While expert evaluation likely played a role in assessing "image quality" and "comparability," the final "ground truth" for the test was determined by whether these qualitative and quantitative assessments met the pre-defined criteria. The results state: "The image quality... passed the pre-defined acceptance criteria" and was "comparable to that of the FDA-cleared comparator devices." There is no mention of pathology or outcomes data being used as ground truth.

8. The sample size for the training set:

This information is not applicable/not provided. The HJY VisualNext Endoscopic Vision System is a hardware device (endoscope and control unit) that captures and displays images; it is not an AI/ML device that requires a training set.

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

This information is not applicable/not provided as there is no training set for this type of device.

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1688 4K Camera System with Advanced Imaging Modality (AIM):

The 1688 Video Camera is indicated for use in general laparoscopy, ear endoscopy, ear endoscopy, sinuscopy, neurosurgery and plastic surgery whenever a laparoscope/ arthroscope/ sinuscope/ sinuscope is indicated for use. The 1688 Video Camera is indicated for adults and pediatric patients.

A few examples of the more common endoscope surgeries are Laparoscopic cholecystectomy, Laparoscopic hernia repair, Laparoscopic appendectomy, Laparoscopic pelvic lymph node detection, Laparoscopically assisted hysterectomy, Laparoscopic and thorascopic anterior spinal fusion, Anterior cruciate ligament reconstruction, Knee arthroscopy, Small joint arthroscopy, Decompression fixation, Wedge resection, Lung biopsy, Dorsal sympathectomy, Pleurodesis, Internal mammary artery dissection for coronary artery bypass grafting where endoscopic visualization is indicated and Examination of the evacuated cardiac chamber during performance of valve replacement.

The users of the 1688 Video Camera are general and pediatric surgeons, gynecologists, cardiac surgeons, thoracic surgeons, plastic surgeons, orthopedic surgeons, neurosurgeons and urologists.

L11 LED Light Source with Advanced Imaging Modality (AIM) and SafeLight Cable:

Upon intravenous administration of SPY AGENTTM GREEN (indocyanine green for injection, USP), the L11 LED Light Source with AIM and SafeLightTM Cable are used with SPY AGENT GREEN to provide real-time endoscopic visible and near-infrared fluorescence imaging. The L11 LED Light Source with AIM and SafeLight Cable enable surgeons to perform minimally invasive surgery using standard endoscopic visual assessment of vessels, blood flow and related tissue perfusion in adults and pediatric patients aged one month and older, and visualization of at least one of the major extra-hepatic bile duct, common bile duct and common hepatic duct) in adults and pediativ patients 12 to 17 years of age, using near-infrared imaging.

Fluorescence imaging of biliary ducts with the L11 LED Light Source with AIM and SafeLight Cable is intended for use with standard-of-care white light and, when indicated, intraoperative cholangiography. The devices are not intended for standalone use for biliary duct visualization.

Additionally, the L11 LED Light Source with AIM and SafeLight Cable enable surgeons to perform minimally invasive cranial neurosurgery in adults and pediatric patients and endonasal skull base surgery in adults and pediatric patients > 6 years of age using standard endoscopic visible light as well as visual assessment of vessels, blood flow and related tissue perfusion using near-infrared imaging.

Upon interstitial administration of SPY AGENT GREEN, the L11 LED Light Source with AIM and SafeLight Cable is used to perform intraoperative fluorescence imaging and visualization of the lymphatic system, including lymphatic vessels and lymph nodes.

The L11 LED Light Source is also intended to transilluminate the ureter during open or laparoscopic surgical procedures.

Precision S 4K Sinuscope:

The Precision S 4K Sinuscope is intended for use in otolaryngology and head and neck procedures, including thinology, endoscopic plastic and reconstructive surgery. The Precision S 4K Sinuscope is also intended for use in minimally invasive cranial neurosurgery in adults and pediatric patients and endonasal skull base surgery in adults and pediatric patients > 6 years ofage.

The AIM (Advanced Imaging Modality) System is an endoscopic real-time 4K visible white light and near-infrared light illumination and imaging system. The AIM (Advanced Imaging Modality) System includes the following components: (1) A Camera System for processing nearinfrared and visible light images; (2) A Light Source and SafeLight Cable for emitting light within the visible light as well as near-infrared light spectrum; (3) An Endoscope for visible light and near-infrared light illumination and imaging; (4) The IRIS Ureteral Kit for transillumination of the ureters; and, (5) SPY AGENT 104 GREEN (indocyanine green for injection, USP) an optical imaging agent used for fluorescence imaging.

The provided document is a 510(k) premarket notification from the FDA for Stryker's AIM (Advanced Imaging Modality) System. It details the device's indications for use and a comparison to predicate and reference devices, along with performance data. However, the document does not report specific acceptance criteria for device performance or a study demonstrating the device meets those criteria from an AI/algorithm performance perspective.

The "Performance Data" section (page 9) lists several tests completed and their "Pass" results, but these relate to general medical device standards (electrical safety, EMC, laser safety, biocompatibility, cleaning, sterilization, software validation, usability, and bench performance) and animal testing for general device functionality, not specific performance metrics against acceptance criteria for an AI or advanced imaging modality's analytical accuracy or diagnostic capability.

The "Clinical Data" section states: "Published literature was provided to support a reasonable assurance of safety and effectiveness for the AIM System for use in the neurosurgery indications." This implies that existing clinical evidence, likely from non-AI-specific studies, was used to support the device's safety and effectiveness for its intended neurosurgery applications. There is no mention of a study involving AI-driven performance metrics, ground truth, or expert review for the AIM system's "Advanced Imaging Modality" in the context of diagnostic or interpretive accuracy.

Therefore, the requested information cannot be fully provided from the given text as it focuses on general device regulatory clearance rather than specific algorithm performance evaluation.

Here's a breakdown of what can be inferred or explicitly stated based on the document, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document explicitly states "There are no new issues of safety and/or effectiveness introduced by the AIM System". This implies that the device, including its advanced imaging modality, is considered equivalent to predicate devices in its safety and effectiveness profiles, which were previously established without explicit AI performance metrics in this submission.

Missing Information (as per the request, not present in the document):

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not provided. The document mentions "Published literature was provided to support a reasonable assurance of safety and effectiveness," but gives no specifics on the study design or data characteristics that would be relevant for an AI/algorithm performance study.
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. This type of information would be crucial for an AI/algorithm performance study.
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 provided. The document does not describe an MRMC study.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not provided. The "Advanced Imaging Modality" is part of a system used by surgeons, suggesting a human-in-the-loop context, but no standalone algorithm performance is detailed.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not provided.
8. The sample size for the training set: Not provided.
9. How the ground truth for the training set was established: Not provided.

Conclusion based on the document:

The FDA 510(k) clearance for the Stryker AIM System is based on established general medical device safety and performance standards, and a demonstration of substantial equivalence to predicate devices for its intended uses. The document does not contain specific information regarding the performance evaluation of an AI or advanced imaging algorithm against defined acceptance criteria, ground truth, or expert review, as would typically be required for a novel AI/ML-driven diagnostic or interpretive device. The "Advanced Imaging Modality" likely refers to enhanced visualization techniques (visible and near-infrared fluorescence imaging, transillumination) rather than an AI-driven analytical tool requiring specific AI performance metrics for clearance in this submission.

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The ClearPath Disposable Introducer is indicated to obtain and maintain a temporary pathway into the ventricular system and cerebrum of the brain.

The ClearPath™ Disposable Introducer is a sterile, single-use, neurological endoscope Introducer, consisting of a Sheath and a Dilator.

A locking mechanism design allows the Dilator to lock into the Sheath and prevent "push back" during insertion into the brain. The Dilator tip is designed to be atraumatic during insertion. The Sheath is graduated in centimeters to assist the surgeon in determining the Introducer insertion depth. The Sheath's transparency is useful for full endoscopic visualization during insertion.

The proximal end of the Sheath is labeled 20F, indicating the inner diameter of the Sheath.

The provided text is a 510(k) summary for the ClearPath™ Disposable Introducer. It focuses on demonstrating substantial equivalence to a predicate device (MINOP® Disposable Introducer 26F, K142315) rather than providing extensive details about acceptance criteria and a specific study proving device performance against those criteria in the context of an AI/ML device.

Therefore, many of the requested details, such as AI-specific acceptance criteria, sample sizes for test and training sets, expert qualifications for ground truth, adjudication methods, MRMC studies, standalone performance, and how ground truth for training was established, are not available in this document as it pertains to a mechanical medical device, not an AI/ML device.

However, I can extract the available information related to performance and testing from the document:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• The document does not specify a "test set" in the context of data for an algorithmic device. The testing described (biocompatibility, bench testing, transit testing, shelf life) refers to physical device testing, not data-driven performance evaluation. Therefore, sample sizes for data-driven testing and data provenance are not applicable or provided.

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

• This information is not applicable as the device is a physical medical instrument, not an AI/ML diagnostic or prognostic tool that would require expert-established ground truth from a test set of data.

4. Adjudication method for the test set:

• This information is not applicable for the same reasons as point 3.

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 applicable as the ClearPath™ Disposable Introducer is a physical medical device, not an AI-assisted device.

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

• This information is not applicable as the device is a physical medical instrument, not an algorithm.

7. The type of ground truth used:

• For the performance aspects mentioned (biocompatibility, bench testing, transit testing, shelf life), the "ground truth" would be established by pre-defined engineering specifications, international standards (ISO 10993, ASTM D4169), and validated laboratory testing procedures. There is no "expert consensus" or "pathology" in the context of data for this type of device.

8. The sample size for the training set:

• This information is not applicable as the device is not an AI/ML algorithm requiring a training set.

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

• This information is not applicable for the same reasons as point 8.

In summary, the provided FDA 510(k) document is for a conventional medical device (an introducer) and thus does not contain the detailed AI/ML specific information requested in many of the questions. It uses standard engineering and biocompatibility testing to demonstrate safety and effectiveness and substantial equivalence to a predicate device.

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