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ExacTrac Dynamic is intended to position patients at an accurately defined point within the treatment beam of a medical accelerator for stereotactic radiosurgery or radiotherapy procedures, to monitor the patient position and to provide a beam hold signal in case of a deviation in order to treat lesions, tumors and conditions anywhere in the body when radiation treatment is indicated.

ExacTrac Dynamic is a patient positioning device used in a radiotherapy environment as an addon system to standard linear accelerators. It uses patient planning and CT data to determine the patient's planned position and compares it via oblique x-ray images to the actual patient position. The calculated correction shift will then be transferred to the treatment machine to align the patient correctly at the machine's treatment position. During treatment is monitored with a surface camera and X-ray to ensure no misalignment due to patient movement.

ExacTrac Dynamic 1.1.2 is a modification of the previously cleared device ExacTrac Dynamic 1.1 that features a Deep Inspiration Breath-Hold (DIBH) functionality to treat breast cancer. This functionality helps correctly position the patient to a deep inspiration breath-hold level and then to monitor this position using surface tracking and x-ray positioning technology. The aim of this technology is to treat the patient only during breath-hold phases where the breast is at a defined position with a maximum distance to critical structures like the heart. Additionally the surface tracking functionality was extended, which monitors the patient after an initial 3rd party positioning.

The main functionalities has remained same for the Subject Device. The modifications are done on a specification level to implement additional measures.

The provided text describes a 510(k) premarket notification for the Brainlab AG ExacTrac Dynamic (1.1.2) device. This submission outlines that the device is a modification of a previously cleared predicate device (ExacTrac Dynamic 1.1) and primarily focuses on addressing identified software bugs and extending existing functionality (Deep Inspiration Breath-Hold and surface tracking).

Crucially, the document states: "In order to address the identified bugs, certain specifications and tests related to the bug fixes (as detailed in Section 4) with ExacTrac Dynamic 1.1.2 were modified to include additional measures. These modified specifications were verified via incremental tests. All tests were passed."

It also explicitly states: "The bug fix did not require any change to the existing software architecture." and "There was no change of intended use, technological characteristics or typical users."

Therefore, the information required to fully answer your request (acceptance criteria and a study that proves the device meets the acceptance criteria, as detailed in your bullet points) is largely absent from this 510(k) summary.

This type of 510(k) submission, focused on minor software modifications (bug fixes) to an already cleared device, typically relies on verification and validation (V&V) testing to demonstrate that the bug fixes have been successfully implemented and have not introduced new issues or adversely affected existing functionalities. It does not typically involve the kind of extensive clinical performance study (like an MRMC study with human readers, or a standalone algorithm performance study with a large, adjudicated test set) that would be conducted for a new AI/ML-driven diagnostic device or a device with significant functional changes.

Here's an analysis based on the provided text, highlighting what is missing:

Absence of Clinical Performance Study Details:

The document explicitly states that the modifications were "verified via incremental tests" and that "All tests were passed." This indicates a focus on engineering and software testing rather than a clinical performance study involving human readers or a large-scale, algorithm-only performance study against clinical ground truth. The acceptance criteria described are implicitly tied to the successful resolution of the identified bugs and the continued proper functioning of the device features.

The document lists numerous bug fixes, primarily concerning software behavior, data handling, and specific use case scenarios (e.g., DIBH beam control, patient deletion, X-ray triggering). The "performance data" section (Section 3) is very brief and refers back to the bug fixes and incremental tests rather than presenting a detailed study.

Detailed Breakdown of Missing Information as per your Request:

Given the nature of this 510(k) for bug fixes, many of your requested points are not applicable or the information is not present in the provided document.

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

   • Acceptance Criteria: Not explicitly laid out in a table in the provided text. The implicit acceptance criteria are that the bug fixes resolve the identified issues and that other functionalities remain unaffected and continue to meet their original design specifications.
   • Reported Device Performance: No quantitative performance metrics (e.g., sensitivity, specificity, accuracy, or precise shift measurements) are reported. The performance is implied by the passing of "incremental tests" for the bug fixes.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • Sample Size: Not specified. "Incremental tests" suggest a focused set of tests for each bug, likely using synthetic data or a limited set of real-world scenarios to reproduce and verify the fix for each bug. This is not a "test set" in the sense of a large, independent clinical dataset.
   • Data Provenance: Not specified. Given this is a software update for an existing device, the testing would likely involve internal company testing environments.

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):

   • Number of Experts/Qualifications: Not applicable and not mentioned. The "ground truth" for bug fixes is the correct software behavior as defined by the design specifications and user requirements, not a clinical diagnosis established by experts.

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

   • Adjudication Method: Not applicable. This concept is for establishing ground truth in clinical image interpretation studies, not for software bug verification.

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:

   • MRMC Study: No. This type of study focuses on clinical benefit and human-AI interaction for diagnostic or interpretive tasks. ExacTrac Dynamic is a patient positioning and monitoring system for radiation therapy, not a diagnostic imaging AI. The changes here are bug fixes, not enhancements that would directly impact a human reader's diagnostic performance.

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

   • Standalone Performance: No quantitative standalone performance data is presented in the context of clinical metrics (e.g., accuracy of positioning, false positives/negatives for beam hold signals). The "performance data" refers to the successful passing of internal verification tests for bug fixes.

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

   • Type of Ground Truth: For bug fixes, the "ground truth" is the predefined correct behavior of the software feature according to its specifications. This is established during the software development and design phase, not through external clinical adjudication.

8. The sample size for the training set:

   • Training Set Sample Size: Not applicable and not mentioned. This device (or this specific update) does not describe using machine learning models that require a "training set" in the typical sense of AI/ML development for image analysis. The "Deep Inspiration Breath-Hold" functionality and "surface tracking" are described as features, but the document does not indicate that new ML models were trained as part of this specific update. The changes are described as "bug fixes" and "modified specifications."

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

   • Ground Truth for Training Set: Not applicable, as there's no mention of a training set for machine learning.

Conclusion:

This 510(k) summary for ExacTrac Dynamic (1.1.2) is a "minor change" submission focusing on software bug fixes to an already cleared predicate device. It explicitly highlights that there were no changes to the intended use, technological characteristics, or typical users. As such, the supporting documentation provided in the snippet is consistent with the type of verification and validation (V&V) typically conducted for such modifications, which relies on internal engineering and software testing ("incremental tests") to ensure the fixes are effective and do not introduce new issues, rather than large-scale clinical performance studies. Therefore, the detailed information requested regarding clinical study design, sample sizes, expert ground truth, and AI/ML training is not present in this particular FDA submission document snippet.

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