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The Titanium Fletcher-style Applicator Set - Defined Geometry is indicated for use for cancer treatment of the uterus, cervix, paracervix, endometrium and vagina using HDR or PDR brachytherapy.

The Smit Cervical Sleeves are indicated for use where any intrauterine tandem is used for HDR or PDR brachytherapy.

The Titanium Fletcher-style Applicator Set – Defined Geometry is intended for use for cancer treatment of the uterus, cervix, paracervix, endometrium and vagina when performing HDR or PDR brachytherapy.

The device does not contain or consist of software/firmware. The device does not contain any biologics or drug components. The device has patient-contacting materials. The device is designed for repeated use. No parts of the system are provided sterile. The device can be steam sterilized with common parameters using pre-vacuum sterilization.

The Titanium Fletcher-Style Applicator Set Defined Geometry includes patients whose cancer can be treated using HDR or PDR brachytherapy, as determined by the prescribing physician. The Titanium Fletcher-Style Applicator Set Defined Geometry is intended to be used in a healthcare or treatment facility by trained and qualified personnel.

This 510(k) submission is also inclusive of the Smit Cervical Sleeve which is an optional component that may be used with the Titanium Fletcher Style Applicator Set Defined Geometry but is not required to successfully perform the intended use.

The provided text describes a 510(k) premarket notification for a medical device, the "Titanium Fletcher-Style Applicator Set Defined Geometry" and "Smit Cervical Sleeves" by Varian Medical Systems, Inc. This document focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than proving that a new AI/software-based device meets specific acceptance criteria through a clinical study.

The acceptance criteria and study information requested in your prompt (e.g., sample size for test sets, data provenance, number of experts for ground truth, MRMC study, standalone performance, ground truth types for training/test sets) are highly relevant for AI-powered medical devices (software as a medical device - SaMD). However, this 510(k) submission is for a physical medical device used in brachytherapy, not an AI or software device.

Therefore, many of the specific questions in your prompt are not applicable to this non-AI medical device submission. The document details the device's technical specifications, intended use, indications for use, and a comparison to a predicate device to argue for substantial equivalence. The "performance testing" mentioned is primarily non-clinical (biocompatibility, MR compatibility, cleaning/sterilization, human factors, mechanical/acoustic testing), focusing on the device's physical properties and safety, not its diagnostic or therapeutic performance in a statistical sense that would require large clinical studies with ground truth derived from experts or pathology.

Here's a breakdown based on the provided text, addressing the points where information is available and noting where it's not applicable:

Acceptance Criteria and Device Performance (for a non-AI physical device)

The concept of "acceptance criteria" for this type of physical device is framed around demonstrating that its design and performance characteristics are equivalent to or do not raise new questions of safety and effectiveness compared to a legally marketed predicate device. The "performance" is primarily assessed through non-clinical laboratory testing to ensure physical integrity, material compatibility, and functionality within its intended use.

Table of Acceptance Criteria and Reported Device Performance (as inferred for a non-AI device through a 510(k))

Study Information (as applicable to a non-AI physical device 510(k) submission):

1. Sample size used for the test set and the data provenance:

   • N/A (for clinical performance data): This is a submission for a physical device, not an AI/software device requiring a clinical test set for performance evaluation (e.g., diagnostic accuracy). The "testing" refers to non-clinical lab tests (biocompatibility, MR, mechanical, sterilization, human factors).
   • For the non-clinical tests (e.g., sterilization cycles, human factors study), the sample size would be determined by the specific ISO/ASTM standards referenced, but typically isn't a large "test set" in the sense of clinical cases. The document does not specify these sample sizes.
   • Data Provenance: Not applicable in the context of clinical data for a physical device. Testing is conducted in a laboratory environment, not on patient data from specific countries.

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

   • N/A: Ground truth established by medical experts is not listed as a component of this non-AI device's performance testing for 510(k) clearance. The device's "performance" is assessed through engineering testing against physical and safety standards and comparison to a predicate.

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

   • N/A: Not applicable as there is no clinical test set requiring expert adjudication for accuracy or performance.

4. 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: This is not an AI-powered device, so an MRMC study comparing human performance with and without AI assistance was not conducted.

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

   • N/A: This is a physical medical device, not an algorithm.

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

   • N/A: "Ground truth" in the sense of clinical reference standards (pathology, expert consensus) is not applied to this type of 510(k) submission for a non-AI physical device. The "truth" or reference is established by engineering specifications, material standards, and functional test results (e.g., "does it sterilize correctly?", "is it MR compatible?").

7. The sample size for the training set:

   • N/A: This is not a machine learning/AI device, so there is no training set in the AI sense.

8. How the ground truth for the training set was established:

   • N/A: Not applicable.

In summary: The provided document is a 510(k) letter for a physical brachytherapy applicator set, demonstrating substantial equivalence to a predicate device. The regulatory pathway for such devices involves rigorous non-clinical testing (e.g., material testing, mechanical testing, sterilization validation) and a comparison of technical characteristics to a predicate, rather than large-scale clinical performance studies or AI-specific validation methods outlined in your prompt.

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The Titanium Fletcher-style Applicator Set with defined geometry was developed for brachytherapy treatment of cancer of the uterus, cervix, endometrium and vagina.

The GM11006200 Titanium Fletcher-Style Applicator Sets are designed for intracavitary radiotherapy treatments in the uterus, cervix, endometrium and vagina. They are compatible with Varian afterloaders and can be used in combination with the appropriate accessories.

Here's a breakdown of the acceptance criteria and study information for the "Titanium Fletcher-Style Applicator Set," based on the provided 510(k) summary:

This device is not an AI/ML device, but a physical medical device. Therefore, the questions related to AI/ML specific studies (MRMC comparative effectiveness study, standalone algorithm performance, training set details) are not applicable. The provided document is a 510(k) summary which focuses on demonstrating substantial equivalence to a predicate device, rather than providing detailed clinical study results of performance against acceptance criteria in the way an AI/ML device would.

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary for the Titanium Fletcher-Style Applicator Set does not explicitly state "acceptance criteria" in terms of performance metrics (like accuracy, sensitivity, specificity) as one would expect for a diagnostic or AI-based device. Instead, the "acceptance criteria" are implied by demonstrating substantial equivalence to a predicate device (K980590 Henschke Type GYN Applicator Set) through a comparison of technological characteristics. The performance is measured by compliance with these characteristics and validation of new features.

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

For a 510(k) submission of a physical medical device like this, there isn't a "test set" in the sense of a dataset of patient images or clinical outcomes used for an algorithm's performance evaluation.

Instead, "testing" involves:

• Engineering verification and validation (e.g., material testing, sterilization validation, dimensional accuracy, compatibility with afterloaders).
• Biocompatibility testing.
• MR compatibility testing.

The document does not specify numerical "sample sizes" for these tests in terms of patient data. The provenance of such testing data would typically be from in-house lab testing, vendor testing, and potentially external accredited labs. Such testing is based on established engineering and materials standards, not patient data in the context of a "test set" for an AI device.

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

This question is not applicable. The device is a physical medical instrument, not an AI/ML algorithm that requires expert-established ground truth from diagnostic images or clinical data.

4. Adjudication Method for the Test Set

This question is not applicable. There is no "adjudication method" in the context of a physical device's engineering validation or biocompatibility testing. These tests are evaluated against predefined specifications and standards.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for evaluating the impact of an AI diagnostic aid on human reader performance, which is not applicable to a physical brachytherapy applicator.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

No, a standalone algorithm performance study was not done. This is a physical device, not an algorithm.

7. The Type of Ground Truth Used

For this physical device, the "ground truth" used for its validation would be:

• Engineering Specifications and Standards: Compliance with dimensional tolerances, material strength, compatibility interfaces.
• Biocompatibility Standards: Compliance with ISO 10993 series.
• Sterilization Validation Protocols: Efficacy of sterilization cycle.
• MR Compatibility Standards: Performance under MR conditions.

It's not "expert consensus, pathology, or outcomes data" in the typical sense for a diagnostic device.

8. The Sample Size for the Training Set

This question is not applicable. The device is a physical instrument and does not involve a "training set" in the context of machine learning.

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

This question is not applicable. The device is a physical instrument and does not involve a machine learning training set or its associated ground truth establishment.

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