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The Stereo Navigator Accessory is an optional accessory to the PEM Flex® PET Scanner. It is intended for the localization of lesions in female breasts, as identified on a PET image. By using the Stereo Navigator, the physician is able to guide compatible interventional devices towards the PET abnormality as medically indicated. The Stereo Navigator also provides a means to confirm localization of the lesion in advance of the interventional procedure.

The Stereo Navigator determines the three dimensional coordinates of a userdefined target for an imaged abnormality (e.g. lesion) displayed on the PEM Flex PET Scanner. Since PEM Flex tomographic images are displayed as a series of 2D planar slices, the user must define a target on two orthogonal images to define all three axis coordinates of the target location. These coordinates are processed into stereotactic information by the Stereo Navigator software which is used by the healthcare provider to position a stereotactic frame for guiding the trajectory of an interventional device and for determining the depth to which the interventional device should be inserted along the trajectory.

Additionally, the Stereo Navigator provides a means for the user to confirm that localization has been achieved during the interventional procedure and prior to sampling or marking. This is accomplished by placing an encapsulated positronemitting line source (radioactive line source) through the tissue access port (cannula) of the interventional device to the intended sampling or marking site, acquiring an image and comparing the location of the line source relative to the lesion (in at least two orthogonal image planes).

This 510(k) summary for the Naviscan Stereo Navigator Accessory (K082354) provides a high-level overview of the device and its claimed substantial equivalence. However, it does not detail specific acceptance criteria or a comprehensive study demonstrating direct adherence to such criteria. Instead, it relies on demonstrating substantial equivalence to predicate devices based on intended uses, technological characteristics, principles of operation, and overall safety and effectiveness, supported by preclinical (phantom) and confirmatory clinical studies.

Therefore, a direct table of acceptance criteria vs. device performance as would be expected for a specific performance study is not available in the provided text. The information below is extracted from the provided text, and where specific details are not present, this is noted.

1. Table of Acceptance Criteria and Reported Device Performance

As specific, quantitative acceptance criteria and corresponding reported performance metrics are not explicitly stated in the 510(k) summary, the table below reflects the general claims of the device and the nature of the studies conducted. The document focuses on demonstrating substantially equivalent performance rather than meeting predefined numerical acceptance thresholds directly.

The provided 510(k) summary does not include the following details for a thorough acceptance criteria and study description:

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

• Not specified. The document mentions "confirmatory clinical studies" but does not provide details on sample size for the test set, country of origin, or whether the data was retrospective or prospective.

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 specified.

4. Adjudication method (e.g. 2+1, 3+1, none) 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

• Not applicable/Not specified. This device is described as an accessory for stereotactic guidance, not an AI software intended to improve human reader performance in image interpretation. The focus is on its ability to localize physical coordinates.

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

• Partially applicable. The device's function to "determine the three dimensional coordinates of a user-defined target" and process them into stereotactic info by the software is a standalone algorithmic function. However, the overall system is human-in-the-loop, as the user defines the target and utilizes the output for guidance. The "preclinical (phantom) studies" would likely assess the standalone accuracy of the measurement and calculation aspect.

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

• For "preclinical (phantom) studies": Physical ground truth from a phantom, likely measured precisely.
• For "confirmatory clinical studies": Not explicitly stated, but for lesion localization, ground truth could involve surgical pathology, follow-up imaging, or other established clinical methods for confirming lesion presence and location.

8. The sample size for the training set

• Not specified. This device is a localization system, not a machine learning algorithm in the typical sense that requires a training set for model development (though software development would involve internal testing).

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

• Not specified/Not applicable in the context of machine learning training, as it's not described as an AI/ML device that learns from a training set. If 'training set' refers to internal development data for the software, the ground truth would typically be established through engineering specifications and precision measurement techniques.

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