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The Xstrahl Photoelectric Therapy System is a low energy X-Ray system intended for superficial radiotherapy and surface electronic brachytherapy treatment of primary malignant epithelial neoplasms of the skin and keloids.

Typical applications include treatment for Basal Cell Carcinoma, Squamous Cell Carcinoma, Metatypic Carcinoma, Cutaneous Appendage Carcinoma, Karposi's Sarcoma, Merkel Cell Carcinoma, Lentigo Maligna, Lentigo Maligna Melanoma, Cutaneous Lymphomas (B and T cell) and Keloids.

The X80 / RADiant / Photoelectric Therapy System (hereafter referred to as the RADiant System) is a compact and ergonomic superficial X-Ray therapy system operating in the 10kV to 80kV range intended for superficial radiotherapy and surface electronic brachytherapy treatment of primary malignant epithelial neoplasms of the skin and keloids.

The RADiant System is a standalone X-Ray radiation therapy system consisting of the X-Ray Therapy Unit, a TP2 Central Control Unit (CCU), a Control POD (Control POD), and a PC on which user interface software is loaded. The system has a time-based control system used with treatment filters and applicators. A range of bespoke treatment applicators and beam filters are available for use with the RADiant System.

The system is freestanding, self-contained, unobtrusive, compact and ergonomic in design, which helps to ensure a reassuring and stress-free patient experience. The system is floor mounted in order to accommodate almost any clinical space, and features ergonomically designed controls ensuring smooth adjustment and safe, simple patient set-up. The system requires connection to the clinical facilities electrical supply and room interlocks.

The Xstrahl Photoelectric Therapy System (RADiant Aura) is a low energy X-Ray system intended for superficial radiotherapy and surface electronic brachytherapy treatment of primary malignant epithelial neoplasms of the skin and keloids.

Here’s an analysis of the provided information regarding its acceptance criteria and the study:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific acceptance criteria for performance metrics in a clinical study. The "acceptance criteria" here are generally understood as meeting design requirements, mitigating risks, and conforming to relevant standards, which are evaluated through non-clinical testing.

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

• Sample Size for Test Set: Not explicitly stated as a "test set" in the context of clinical data. The testing described largely involves non-clinical (engineering and technical) verification and validation. This means the "sample size" would refer to the number of devices or components tested. The document mentions "Twenty Six independent verification tests and 18 independent validation tests were executed on the RADiant Aura systems." This implies that at least one, but likely a limited number (e.g., prototype or production units), of RADiant Aura systems were subjected to these tests.
• Data Provenance: This information refers to the origin of the data. Since the testing is non-clinical, the data provenance is primarily from internal testing conducted by Xstrahl Ltd. and independent testing by the National Physics Laboratory UK (NPL). The context is purely technical performance evaluation, not clinical outcomes from human patients. The data is prospective in the sense that it was generated specifically for this submission to verify the new design. There is no mention of country of origin of clinical data, as no clinical data is presented.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This section is not applicable as the document describes non-clinical performance and safety testing, not a clinical study requiring expert-established ground truth for a test set (e.g., image interpretation or disease diagnosis). The "ground truth" here is adherence to engineering specifications, safety standards, and physical laws, verified by technical measurements and evaluations.

4. Adjudication Method for the Test Set

This is not applicable as the document describes non-clinical performance and safety testing. Adjudication methods are typically used in clinical studies when multiple human readers evaluate data, and their assessments need to be reconciled to establish a ground truth.

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, an MRMC comparative effectiveness study was not done. This device is an X-Ray radiation therapy system, not an AI diagnostic or assistance tool. The submission focuses on the safety and performance of the hardware and software for delivering radiation therapy, not on interpreting medical images or assisting human readers in diagnosis.

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 "algorithm" in this case refers to the embedded software and control systems of the radiation therapy device. The non-clinical testing described (e.g., software run-through functionality test, dose reproducibility) effectively evaluates the "standalone" performance of these systems in meeting their intended technical specifications, without direct human intervention in the treatment delivery process once programmed. However, the device itself is a treatment device, not a diagnostic algorithm.

7. The Type of Ground Truth Used

For the non-clinical testing, the "ground truth" used was based on:

• Engineering specifications and design requirements: The device was tested against its defined operational parameters and expected performance.
• International and national standards: Compliance with standards like BS EN 60601-2-8, IEC 60601-1, etc., served as the ground truth for safety, electrical performance, usability, and software lifecycle.
• Recognized codes of practice: For output measurements, protocols from AAPM (2001) and IPEMB (1996) were used as the benchmark for accurate dose delivery.

8. The Sample Size for the Training Set

There is no mention of a training set in the document. This is because the device is not an AI/ML-based diagnostic or predictive algorithm that typically requires large datasets for training. The software components mentioned (Concerto, Fisica, TP2) appear to be control software and firmware for the device's operation, not machine learning models.

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

This is not applicable as there is no training set for an AI/ML model mentioned in the context of this device.

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