(114 days)
The Axxent® Electronic Brachytherapy System is a high dose rate Brachytherapy device for use with Axxent Applicators to treat lesions, tumors and conditions in or on the body where radiation is indicated.
The Axxent Electronic Brachytherapy System consists of three primary components: the Axxent System Controller (Controller); the Axxent HDR X-ray Source-2.2 (Source); and an Axxentcompatible applicator (Applicator). The System is designed to deliver doses of X-ray radiation to the tissue in proximity to the applicator using a disposable, miniature X-ray tube powered by the Controller.
The Axxent Electronic Brachytherapy Controller is a mobile, computer-controlled platform that is responsible for the overall operation of the System. The Controller is designed to work with the Source, which is a disposable, miniature X-ray tube located at the end of a flexible cable. The Source is inserted into a lumen of the appropriate Applicator.
Here's an analysis of the provided text regarding the Axxent Electronic Brachytherapy System, focusing on acceptance criteria and study details.
Important Note: The provided text is a 510(k) summary and FDA clearance letter, which primarily focuses on demonstrating substantial equivalence to predicate devices and general safety/effectiveness. It does not contain the detailed information typically found in a clinical study report addressing specific performance metrics, sample sizes for ground truth, expert qualifications, or MRMC studies for AI devices. This device is a radiation therapy system, not an AI-powered diagnostic tool, so many of the requested categories (like MRMC, standalone AI performance, and AI-specific ground truth details) are not directly applicable or reported in this type of submission.
Acceptance Criteria and Reported Device Performance
Given that this is a radiation therapy system and the submission focuses on substantial equivalence, the "acceptance criteria" here refer more to the successful demonstration of the device meeting its performance, functional, and system requirements during verification and validation testing, rather than specific diagnostic accuracy metrics.
| Acceptance Criteria Category | Reported Device Performance/Statement |
|---|---|
| System Functionality & Performance | All performance, functional, and system requirements were met. |
| Safety and Effectiveness | Device labeling contains instructions, cautions, and warnings for safe and effective use. Risk management via risk analysis. Potential hazards are controlled via software development, verification, and validation testing. |
| Substantial Equivalence to Predicates | The technological characteristics are the same as Axxent Electronic Brachytherapy System (K072683) and similar to Varian VariSource 200 HDR Afterloader (K061582) in terms of design, materials, principles of operation, and product specifications. |
Study Details (Based on Available Information)
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Sample size used for the test set and the data provenance:
- Test Set Sample Size: Not explicitly stated in the provided documents. The validation testing likely involved a series of engineering and functional tests on the device itself, rather than a "test set" of patient data in the way an AI diagnostic device would.
- Data Provenance: Not applicable in the context of patient data for a performance study. The "data" here refers to the outcomes of the engineering and software validation tests.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This question is not directly applicable to a hardware/software system validation in the way it would be for a diagnostic AI system requiring expert consensus on images. The "ground truth" for this device's performance would be established by engineering specifications and regulatory standards. Expert oversight would be from the development and testing engineers and regulatory affairs personnel within iCAD/Xoft.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not applicable. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies for diagnostic accuracy to resolve discrepancies between readers, particularly for ground truth establishment or comparative reader performance. This submission describes performance and functional testing of a radiation delivery system.
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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 MRMC study was done or reported. This device is a therapeutic device (radiation delivery system), not an AI-assisted diagnostic tool. Therefore, human reader (e.g., radiologist) improvement with AI assistance is not a relevant metric for this submission.
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Standalone performance (algorithm only) is partially relevant in that the device's control system and dose delivery algorithm operate in a "standalone" fashion to execute a treatment plan. The "Assessment of Non-Clinical Performance Data" indicates "Validation testing was performed according to a Software System Test Plan. All performance, functional and system requirements were met." This implies the software and system were tested independently to ensure they meet their specifications. However, this is not an "AI algorithm only" performance as conceptualized for diagnostic AI.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The "ground truth" for the device's function and performance is its adherence to predefined engineering specifications, design requirements, and regulatory standards. This is assessed through various verification and validation tests (e.g., electrical safety, radiation output accuracy, software functionality, mechanical integrity). For safety, a risk analysis identifies potential hazards.
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The sample size for the training set:
- Not applicable. This device is not an AI/machine learning system that requires a "training set" of data for model development. Its software and control algorithms are developed through traditional engineering and programming methods.
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How the ground truth for the training set was established:
- Not applicable, as there is no "training set" for this type of medical device as described in the provided document.
§ 892.5900 X-ray radiation therapy system.
(a)
Identification. An x-ray radiation therapy system is a device intended to produce and control x-rays used for radiation therapy. This generic type of device may include signal analysis and display equipment, patient and equipment supports, treatment planning computer programs, component parts, and accessories.(b)
Classification. Class II.