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The Varian Esophagus Bougie is an applicator used to facilitate delivery of a prescription of radiation to the esophagus when used in conjunction with a Varian high dose rate afterloader.

The Varian Esophagus Bougie is an HDR applicator designed to facilitate delivery of radiation to the Esophagus and has been modified to work with Varian afterloaders. The product can be steam sterilized up to 20 times and has a maximum implantation time of 24 hours. The device does not contain any electronics or software. A high activity radioactive source is placed within the applicator which has previously been placed for a specified clinical purpose in a patient. The radioactive source (enclosed within the wire/cable) is driven via coupling catheters (Transfer Guide Tubes) from the Afterloader into the applicator within the patient. The length of time and position that the High Dose Rate source spends within the applicator is controlled in accordance with an Irradiation Treatment Prescription.

This 510(k) summary describes a medical device, the Varian Esophagus Bougie Applicator, which is an applicator for delivering radiation to the esophagus. It is not an AI/ML powered device, so many of the requested criteria, such as acceptance criteria based on performance metrics (e.g., sensitivity, specificity), sample sizes for test sets, expert-established ground truth, adjudication methods, multi-reader multi-case studies, and training set information, are not applicable.

The submission is for a traditional medical device (an applicator for radiation delivery) and focuses on establishing substantial equivalence to previously cleared predicate devices. Therefore, the "acceptance criteria" here refer to the criteria for demonstrating substantial equivalence based on technological characteristics and intended use, rather than performance metrics of an AI algorithm.

Here's a breakdown of the information that can be extracted from the provided text, and where the requested information is not applicable:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Not Applicable. This is a physical device submission demonstrating substantial equivalence to predicates, not an AI/ML algorithm requiring a specific test set for performance evaluation. Product testing would involve engineering and sterilization validations, potentially using physical samples of the device, but not "data" in the context of AI.

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

• Not Applicable. No ground truth, in the context of diagnostic accuracy or AI performance, was established for this device.

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

• Not Applicable. No test set or related adjudication process for performance evaluation was conducted.

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. This is not an AI-powered device, so no MRMC study involving human readers and AI assistance was conducted.

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

• Not Applicable. This is not an algorithm.

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

• Not Applicable. Ground truth, in the context of diagnostic accuracy, is not relevant for this device. The "truth" for this device would relate to its physical properties, material compatibility, and ability to house and facilitate the movement of a radioactive source as intended, which would be validated through engineering and biocompatibility testing, not clinical "ground truth" data.

8. The sample size for the training set

• Not Applicable. This is not an AI/ML algorithm, so there is no training set.

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

• Not Applicable. As there is no training set, there is no ground truth for it.

In summary: The provided document is a 510(k) summary for a physical medical applicator, not an AI/ML device. Therefore, the "acceptance criteria" and "study" largely revolve around demonstrating substantial equivalence to existing devices based on intended use and technological characteristics, rather than performance metrics derived from large datasets using AI algorithms.

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