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ABARIS is a stereotaxic accessory for Computed Tomography (CT), Magnetic Resonance, (MR), Ultrasound (US), Position Emission Tomography (PET), Single Photon Prosonan Computed Tomography (SPECT), Fluoroscopy, Endoscopy and other imaging systems. It displays the simulated image of a tracked insertion tool such as a biopsy needle, guidewire or probe on a computer monitor screen that shows images of the target psy noeans, guidewire and the projected future path of the interventional instrument taking into account movements of the patient. This is intended for treatment planning and intra-onerative guidant for surgical procedures. The device also supports an image-free mode in which the proximity of the interventional device is displayed relative to another device.

The device is intended to be used in clinical interventions and for anatomical structures where imaging is currently used for visualizing such procedures. The device is also intended for use in clinical interventions to determine the proximity of one device relative to ano inchier.

The ABARIS is a computer assisted, image guided surgery system. It guides a surgical instrument to a target that has been defined by the physician. The target can be indicated either preoperatively or intraoperatively using images or relative to an indicated position on the patient.

The ABARIS provides real-time, three-dimensional visualization and navigation tools for all stages of surgery including preoperative planning and intra-operative navigation. ABARIS transforms two-dimensional patient images (scan sets), derived from Computed Tomography (CT), Magnetic Resonance Imaging (MR), Position Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), Ultrasound (US), Fluoroscopy etc. into dynamic representations on which a tool can be navigated. The system performs spatial mapping from one inage space to another image space or from image space to physical space ("vegistation") allowing the physician to correlate scan sets with each other and to the patient The system facilitates minimally invasive surgical procedures. Like other commercially available image guided surgery systems, the ABARIS also offers computer assisted image-free and registration free navigation using the same instrumentation.

Targeted use areas for ABARIS include hospital operating rooms, outpatient surgery centers and procedure rooms.

The K053610 submission for ABARIS describes a computer-assisted image-guided surgery system. The submission does not contain a study to prove acceptance criteria in the format requested. Instead, it relies on substantial equivalence to predicate devices. It states that "The technological characteristics of the ABARIS are the same or similar to those found in the predicate devices."

Therefore, the following information cannot be extracted from the provided text:

• A table of acceptance criteria and reported device performance.
• Sample sizes used for a test set or data provenance.
• Number of experts used to establish ground truth or their qualifications.
• Adjudication method for a test set.
• Results of a multi-reader multi-case (MRMC) comparative effectiveness study, including effect size.
• Results of a standalone (algorithm only) performance study.
• Type of ground truth used (expert consensus, pathology, outcomes data).
• Sample size for a training set.
• How ground truth for a training set was established.

The submission is a 510(k) premarket notification, which often demonstrates substantial equivalence rather than presenting new clinical study data with explicit acceptance criteria. The FDA's letter (APR 19 2006) confirms this by stating, "We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent...".

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The InstaTrak 3000 System is intended as an aid to the surgeon for precisely locating anatomical structures anywhere on the human body during either open or percutaneous procedures. It is indicated for any medical condition that may benefit from the use of stereotactic surgery and which provides a reference to rigid anatomical structures such as sinus, skull, cranial, a long bone or vertebra, visible on medical images such as CT or MR.

The InstaTrak System is an image guidance system indicated for use during sinus, skull base, cranial and axial skeletal procedures. The InstaTrak 3000 is essentially identical to the InstaTrak System cleared under K960330 and the Pediatric InstaTrak System cleared under K981998 which are both indicated for use during sinus surgery. The changes to the system include a computer upgrade, software enhancements, additional indications and the addition of several components. Using the InstaTrak 3000, the surgeon can readily identify the immediate location and position of the surgical instrument during the indicated procedure. The InstaTrak 3000 assists the surgeon in avoiding critical nerves and other anatomical structures. The InstaTrak 3000 offers multiple modes of operation that includes sinus, skull base or axial skeletal, to the user based on the indications the user desires. Software is available to the user for using any one, two, or all three of the operational modes. A selection of the operational modes is made by the user prior to the procedure depending needs of the user. The original InstaTrak System allows the user to view the reconstructed 2D images of the patient's anatomy in response to the mouse or the tracked surgical instrument. Alignment of the patient and medical images is accomplished through either an automatic or fiducial registration. The indications for use include sinus cleared under K960330 and pediatric sinus surgery (K981998). In all types of surgery the goal is the same, to indicate to the surgeon based on the pre-operative medical images, where the position of a tracked surgical tool is with regard to the patient's anatomy. The InstaTrak 3000 is based on the same hardware and software used in the original InstaTrak System and provides all of the above features. It utilizes the same clinically proven electromagnetic tracking technology as its predecessor. A newer version of a Sun computer has been substituted to provide 3D display capability which includes 3D models and planar images on top of 3D models, oblique and trajectory matching views. Additionally, a surgical planning capability has been added. This allows the surgeon to plan a trajectory prior to surgery and to observe the pre-surgical track in relation to the actual track during the surgical procedure. A new registration technique has been added whereby the surface of the anatomy can be registered to. New instruments have been added to which tracking sensors have been built in or may be attached. These, along with the surface registration and the new displays allow the system to be used in the proposed indications encompassing axial skeletal, and cranial surgery, in addition to the cleared and pending indications.

The InstaTrak 3000 is an image guidance system that aids surgeons in locating anatomical structures during surgical procedures. The provided 510(k) summary (K983529) describes the device and its claimed substantial equivalence to predicate devices. However, the summary does not contain detailed information regarding the specific acceptance criteria or a comprehensive study report with quantitative performance metrics as typically expected for medical device evaluations.

Based on the provided text, here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary lacks a formal table of acceptance criteria and reported numerical device performance metrics. The performance testing mentioned is qualitative and focuses on a specific aspect:

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

The 510(k) summary does not specify the sample size used for the performance testing. It also does not provide information on data provenance (e.g., country of origin, retrospective or prospective nature). The testing appears to have been conducted internally by the manufacturer ("Testing was performed...").

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

The 510(k) summary does not mention the use of experts to establish ground truth for any test set, nor does it detail their qualifications. The testing described focuses on the device's accuracy with new components, implying a technical evaluation rather than a clinical one involving expert consensus on patient data.

4. Adjudication Method for the Test Set

Since the summary does not detail the use of experts or a clinical test set, an adjudication method (like 2+1, 3+1) is not applicable and not mentioned.

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

The 510(k) summary does not describe a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. There is no mention of comparing human reader performance with or without AI assistance, or any effect size of such improvement.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance

The InstaTrak 3000 is an "image guidance system" intended to "aid the surgeon." This inherently implies a human-in-the-loop device. Therefore, a standalone (algorithm-only) performance study as typically understood for diagnostic AI devices is not described and would likely not be the primary evaluation method given the device's nature. Its function is to provide information to a human operator.

7. Type of Ground Truth Used

The type of "ground truth" for the performance testing mentioned appears to be related to the "device accuracy" with new components. This would likely involve engineered or laboratory-based measurements against known physical parameters or standards, rather than clinical ground truth like pathology, expert consensus, or outcomes data. The summary does not specify the exact nature of this "specification" or how accuracy was measured against it.

8. Sample Size for the Training Set

The 510(k) summary does not provide information regarding a training set or its sample size. This is a premarket notification for a navigation system, not a machine learning or AI-driven diagnostic algorithm that typically relies on extensive training data. While the system has "software enhancements," the summary primarily emphasizes its technological similarity to predicate devices and the function of new components.

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

As no training set is mentioned, information on how its ground truth was established is not provided.

Summary of Study Described:

The study referenced in the 510(k) summary (Section 7, "PERFORMANCE TESTING") was a limited internal validation focused on the new components of the InstaTrak 3000 System.

• Objective: To determine if the newly added components (nasal specula, mouth gag, pharyngeal retractor, straight extended aspirator, sterile disposable pointer, transmitter, receiver, and head frame) affected the device's accuracy.
• Methodology (implied): The new components were incorporated into the system, and accuracy tests were performed.
• Results: The manufacturer concluded that "the device performed within the specification while using the new components."
• Limitations (from the provided text):
  • No quantitative accuracy metrics are provided.
  • The "specification" against which performance was measured is not defined.
  • No details on the number of tests, test conditions, or specific methodology are given.
  • The testing was not a clinical trial with patient-specific ground truth or human reader evaluations.

In essence, the 510(k) summary confirms that a technical performance test was conducted to ensure the new hardware components did not degrade the system's accuracy, based on the manufacturer's internal specifications. It does not provide the detailed evidence typically found in studies for AI-driven diagnostic devices, which often involve large datasets, expert ground truth, and comprehensive statistical analysis of clinical performance measures. The substantial equivalence argument primarily relies on the core technology being largely identical to predicate devices.

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The Skull Based InstaTrak System is intended for image guided assistance during skull base surgical procedures. It is intended to be used during skull base surgery involving procedures on the base of the brain (junction of the face and neurocranium).

The InstaTrak System is an image guidance system indicated for use during skull base procedures. The Skull Base InstaTrak System is identical in principles of operation to the InstaTrak System cleared under K960330 and the Pediatric InstaTrak System cleared under K981998, which are indicated for use during nasal surgery. Using the Skull Base InstaTrak System, the surgeon can readily identify the immediate location and position of the surgical instrument during skull base procedures. The Skull Base InstaTrak System assists the surgeon in avoiding critical nerves and other anatomical structures. The Skull Base InstaTrak System includes several new components that were not included in K960330 or K981998, such as a head frame, transmitter arm, extended straight sterile pointer, mouth gag, pharyngeal retractor and nasal speculum. The remainder of the components used in the Skull Base System are identical to those described in the original submission. The additional components do not affect the overall operation of the system as the principles of operation are identical to that described in K960330. Like that system, the Skull Base InstaTrak System is an image guided surgery system that employs a computer with a top mounted swiveling monitor, software and an electromagnetic tracking system. The System uses a Sun SPARC STATION™. The System's proprietary software builds a CT model by taking axial CT images and reconstructing the coronal and sagittal views. The electromagnetic tracking system correlates the movement of surgical instruments to the CT model. The tip of the instrument is displayed as a set of cross hairs in the axial, coronal, and sagittal planes on the InstaTrak System monitor. With the InstaTrak System, CT images are used to assist the surgeon in guiding the position of the instrument during skull base surgery.

The Skull Base and InstaTrak Systems allow pre-operative viewing of the patients' CT images, contextual visualization of the pathology, intra-operative localization, screen display outputs for video recording and positional guidance. The system is operated by acquiring an axial CT scan while the patient wears the InstaTrak System headset and associated instruments. The axial images are then transferred via a network connection or cartridge to the InstaTrak System. The Headset position which stays fixed relative to the patients' anatomy, is automatically identified in the CT images by an image processing algorithm. Coronal and sagittal images are reconstructed and along with the Axial images, provide the CT model that will be used as a road map in surgery.

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

Acceptance Criteria and Device Performance

The provided document {3} states: "Testing was performed using the new components of the Skull Base InstaTrak System to determine if the new components affected device accuracy. The results showed that the device performed within the specification while using the new components."

While the document explicitly states that the device "performed within the specification," it does not provide the specific numerical acceptance criteria or the reported device performance metrics. It only refers to a general "specification" for accuracy.

Study Details

The provided 510(k) summary offers limited details about the study. Here's what can be inferred:

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

   • Sample size: Not specified.
   • Data provenance: Not specified (e.g., country of origin, retrospective or prospective). The summary only states that "Testing was performed using the new components."

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

   • Not specified. The summary does not mention the involvement of experts for establishing ground truth during the accuracy testing.

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

   • Not specified. Given the nature of accuracy testing for an image guidance system, it's likely physical measurements against a known standard were used rather than expert adjudication in the traditional sense, but this is not explicitly stated.

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 device is an image guidance system that assists surgeons, not an AI-driven diagnostic tool that impacts human reader performance in interpreting images. The study focused on the device's accuracy with new components.

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

   • Yes, a standalone performance assessment was effectively done regarding the device's accuracy. The testing aimed to determine if the new components affected device accuracy {3}. This implies evaluating the system's ability to accurately track instruments relative to the CT model, which is a standalone function of the device. However, the exact methodology (e.g., phantom studies, cadaver studies) is not detailed.

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

   • Not explicitly stated. For "accuracy" testing of an image guidance system, the ground truth would likely involve physical measurements against precisely known spatial references or benchmarks (e.g., phantom models with known dimensions and fiducial markers) rather than expert consensus on medical findings, pathology, or outcomes data.

7. The sample size for the training set:

   • Not applicable as this is not an AI/Machine Learning device that undergoes training in the conventional sense. The "training" for such a system would involve engineering and calibration, not a data-driven training set.

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

   • Not applicable for the same reason as above.

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