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The Esteya is intended to deliver X-ray radiation for superficial radiotherapy procedures and surface brachytherapy. Applications include treatment for Basal Cell Carcinoma, Squamous Cell Carcinoma, Kaposi's Sarcoma, Merkel Cell Carcinoma, Lentigo Maligna, Lentigo Maligna Melanoma, Keloids and Cutaneous Lymphomas (B and T cell).

The Esteva is designed for high dose rate treatment of skin surface lesions. The Esteva utilizes a mobile treatment unit with an isotope free small 69.5 kV X-rav source that focuses the treatment dose directly to the skin lesion with the aid of a shielded surface applicator. This technique provides a uniform dose to the underlying tissue within minutes. The small X-ray source is activated by the treatment control panel that is located adjacent to the treatment area where the operator is protected from radiation exposure during the patient treatment. The dedicated computer system of Esteya provides fractionated treatment times, plan approval, patient information and treatment reports in a protected database which is administrator controlled. The quality of the X-ray source output is measured on a daily basis with a dedicated quality assurance device that Is connected directly to the treatment unit. This quality assurance check ensures consistent and accurate electronic brachytherapy & superficial radiotherapy treatment.

The provided text is a U.S. FDA 510(k) summary for the "Esteya" X-ray radiation therapy system. It outlines the device's technical characteristics, intended use, and a comparison to predicate devices, along with a summary of performance testing (non-clinical).

Here's an analysis of the acceptance criteria and study information based on the provided text:

1. Table of acceptance criteria and the reported device performance

The document provides a table summarizing performance parameters for the device, which can be interpreted as demonstrating the device meets certain operational criteria. It does not explicitly state "acceptance criteria" but rather "Performance Data".

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

The document states: "No animal or clinical tests were performed to establish substantial equivalence with the predicate devices." This implies that there was no specific clinical test set with a sample size for human or animal subjects. The performance testing described is non-clinical, focusing on the device's physical and functional characteristics. Therefore, information about data provenance (country of origin, retrospective/prospective) is not applicable to a clinical test set in this context.

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

Not applicable, as no clinical test set was used to establish substantial equivalence.

4. Adjudication method for the test set

Not applicable, as no clinical test set was used to establish substantial equivalence.

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. The device is an X-ray radiation therapy system, not an AI-assisted diagnostic or interpretive tool. The document explicitly states "No animal or clinical tests were performed."

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

This question is not directly applicable in the context of this device. The Esteya is a radiation therapy system, not an algorithm being evaluated for standalone performance. The performance testing was focused on the system's physical and functional attributes.

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

The document indicates that "the device safety and performance have been addressed by non-clinical testing in conformance with predetermined performance criteria. FDA guidance, clinical use and recognized consensus standards." This suggests that the "ground truth" for the non-clinical performance evaluation was based on:

• Predetermined performance criteria: These are likely engineering and design specifications.
• FDA guidance and recognized consensus standards: These provide established benchmarks for safety and effectiveness for such devices.

8. The sample size for the training set

Not applicable. The device is an X-ray radiation therapy system, not a machine learning algorithm that requires a training set in the conventional sense.

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

Not applicable, as no training set was used for an AI algorithm.

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The Esteya electronic brachytherapy system is intended to deliver x-ray radiation for suface brachytherapy procedures. Typical applications include treatment for Basal Cell Carcinoma, Squamous Cell Carcinoma, Kaposi's Sarcoma, Merkel Cell Carcinoma, Lentigo Maligna, Lentigo Malingna Melanoma, Keloids and Cutaneous Lymphoma (B and T cell).

The Esteya Electronic Brachytherapy System is designed for High Dose Rate (HDR) brachytherapy treatment of skin surface lesions. The Esteya Electronic Brachytherapy System utilizes a mobile treatment unit with an isotope free small 69.5 kV X-ray source that focuses the treatment dose directly to the skin lesion with the aid of a shielded surface applicator. This technique provides a uniform dose to the underlying tissue within minutes. The small X-ray source is activated by the treatment control panel that is located adjacent to the treatment area where the operator is protected from radiation exposure during the patient treatment. The Esteya Electronic Brachytherapy dedicated computer system provides fractionated treatment times, plan approval, patient information and treatment reports in a protected database which is administrator controlled. The quality of the X-ray source output is measured on a daily basis with a dedicated quality assurance device that is connected directly to the treatment unit. This quality assurance check ensures consistent and accurate electronic brachytherapy treatment.

The provided text describes a Traditional 510(k) submission for the Esteya Electronic Brachytherapy System (K132092). However, it does not contain the detailed information necessary to fully answer the request regarding acceptance criteria and the study that proves the device meets those criteria, particularly in the context of an AI/algorithm-based device as implied by the sophisticated questions asked.

The document discusses the substantial equivalence of the Esteya system to predicate devices for delivering X-ray radiation for surface brachytherapy procedures. It mentions "non-clinical testing" and "clinical testing" but the details provided are very high-level.

Here's an analysis based on the available information:

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

• Acceptance Criteria: The document generically states that "Testing was performed in accordance with defined test cases with clearly defined acceptance criteria." However, it does not provide a specific table or list of these acceptance criteria.
• Reported Device Performance: The document states:
  • "Esteya Electronic Brachytherapy System has been tested to meet the product requirements, electrical and mechanical safety standards, and clinical expectations."
  • "The results of the clinical testing clearly demonstrated substantial equivalence of the Esteya Electronic Brachytherapy System."
  • This is a general statement of meeting requirements, not specific performance metrics against defined acceptance criteria.

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: This information is not provided in the document.
• Data Provenance: This information is not provided in the document.

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)

• This information is not provided in the document. The document refers to "clinical testing" and comparing "treatment output, dose distribution and clinical acceptance," but does not detail how ground truth was established or if experts were involved in a ground truth process as typically understood for AI device validation.

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

• This information is not provided in the document.

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 provided and is highly unlikely to be relevant. The Esteya system is described as an "Electronic Brachytherapy System" for delivering X-ray radiation, not an AI or diagnostic imaging device that would involve "human readers" or AI assistance in interpretation. The context of an MRMC study and "human readers improve with AI" does not fit the description of this device.

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

• This information is not provided and is not relevant, as the device is a treatment delivery system, not a diagnostic algorithm.

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

• The document implies that "treatment output, dose distribution and clinical acceptance" were compared. This suggests a ground truth related to physical dosimetry and clinical outcomes/acceptance of the treatment process. However, the exact type of ground truth (e.g., specific pathology reports, long-term patient outcomes, or expert consensus on treatment efficacy) for its "clinical testing" is not explicitly stated or detailed.

8. The sample size for the training set

• This information is not provided and is irrelevant as the Esteya system is a hardware device for radiation delivery, not a machine learning algorithm that requires a training set.

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

• This information is not provided and is irrelevant for the same reason as point 8.

In summary:

The provided 510(k) summary is for a physical medical device (an electronic brachytherapy system) and lacks the specific details that would be found in a submission for an AI/algorithm-based device, particularly concerning acceptance criteria, ground truth establishment, expert involvement, and study designs like MRMC or standalone algorithm performance. The information available focuses on demonstrating substantial equivalence in design, technology, functionality, and overall clinical performance to existing predicate devices, rather than validating an AI algorithm against specific performance metrics for diagnosis or prediction.

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