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VeriSuite is an image processing software for verification of the patient position of a correction vector for the treatment of tumors during a radiation therapy with photons, electrons (from a linear accelerator) or particles (protons).

An authorized person must evaluate the correctness of the calculation and approve the result for further usage. The system shall only be used after correct installation in appropriate treatment rooms by trained personnel. Legal regulations especially regulation for the operation of X-ray devices must be regarded.

VeriSuite must not be used for diagnostic purposes.

VeriSuite® is an image processing system for verification and correction of the patient position during a radiation therapy treatment. The verification or correction is performed by a comparison of the current patient treatment position with a CT series of the patient and information from the radiation therapy planning. The correction can also be based on fiducial, radio-opaque markers that are implanted in the patient.

With the fluoroscopy extension it is possible to observe the position of the patient and the treatment area during the treatment. Mainly the movements of the patient caused by breathing are in the focus. This information can be used to interrupt the treatment by the user.

With the 3D3D extension it is possible to compare two CT volumes with each other. The positioning volume is received from the TRCS (i.e. from a second CT device located in the treatment room.)

VeriSuite® is a system of devices consisting of the VeriSuite® software and a number of hardware devices.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state a specific numerical sample size for the test set used in the non-clinical performance data section. It mentions:

• "Test have been performed with medical phantoms."
• "Simulated patient data was used to perform the workflow and verify precision and robustness of the algorithm."

Data Provenance:

• Medical Phantoms: These are physical models designed to mimic human anatomy for testing purposes. Their provenance is typically laboratory-based.
• Simulated Patient Data: The source of this simulated data is not specified (e.g., whether it's derived from previous real patient scans, purely synthetic, etc.).
• "Feedback from VeriSuite® users in the EU (CE marked)" indicates some real-world input, but this feedback is used to improve the algorithm and obtain the reported improved robustness and precision, rather than being part of a formal, quantifiable test set for acceptance criteria.

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

The document does not specify the number of experts used or their qualifications for establishing ground truth during the non-clinical testing. The "ground truth" seems to be established by the "expected parameters" for precision and robustness, which would typically be defined by engineering specifications and potentially clinical guidance from experts, but this is not detailed.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method for the test set. The validation appears to be based on the algorithm's performance against predefined "expected parameters" and by expert assessment in the form of "feedback from VeriSuite® users in the EU."

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

No multi-reader multi-case (MRMC) comparative effectiveness study is mentioned for evaluating human reader improvement with or without AI assistance. The study focuses on the standalone performance of the 3D3D extension.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, a standalone performance evaluation was done. The "Non-clinical Performance Data" section describes tests performed with "medical phantoms" and "simulated patient data" to verify the precision and robustness of the algorithm, and the "calculation of a correction vector." This focuses on the algorithm's capabilities without detailing human interaction beyond the assessment of usability.

7. The Type of Ground Truth Used

The ground truth for the non-clinical tests appears to be:

• Phantom-based measurements: For precision and robustness, the known characteristics of the medical phantoms would serve as ground truth.
• Simulated patient data with known outcomes: For simulated data, the ground truth would be the pre-defined correct patient positions and correction vectors.
• "Expected parameters": This implies a pre-defined set of correctness values or ranges for the algorithm's output.

8. The Sample Size for the Training Set

The document does not provide information on the sample size used for the training set of the VeriSuite 3D3D matching module.

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

The document does not explicitly describe how the ground truth for any potential training set was established. The focus of the provided text is on verification and validation of the device's performance after its development, rather than the details of its developmental training.

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The VeriSuite patient position verification and correction of the patient's position during a radiotherapy treatment with external beams or charged particles. It is based on stereoscopic X-ray images and DRRs calculated from a CT image series of the treatment region of the patient and information from the treatment planning.

VeriSuite is an image processing system for verification and correction of the patient position during a radiation therapy treatment. The verification or correction is performed by a comparison of X-ray images that are acquired during the treatment with DRRs (digital reconstructed radiographs) calculated from a CT image series of the patient and information from the radiation therapy planning. The correction can also be based on fiducial, radio-opaque markers that are implanted in the patient.

With the fluoroscopy extension it is possible to observe the position of the patient and the treatment area during the treatment. Mainly the movements of the patient caused by breathing are in the focus. This information can be used to interrupt the treatment by the user.

VeriSuite is a system of devices consisting of the VeriSuite software and a number of hardware devices.

The provided text is a 510(k) Summary for a medical device (VeriSuite) and primarily focuses on regulatory approval and substantial equivalence to predicate devices, rather than detailed performance studies or specific acceptance criteria. Therefore, much of the requested information regarding acceptance criteria, study design, and performance metrics is not explicitly present in this document.

However, I can extract what is available and indicate what is missing.

1. Table of Acceptance Criteria and Reported Device Performance

This information is not provided in the document. The submission focuses on functional equivalence to predicate devices and software verification/validation, but not specific quantitative performance acceptance criteria or results of such tests in a clinical setting.

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

This information is not provided in the document. The document mentions "Non-clinical verification and validation software tests" but does not detail the size or nature of the test set used for these tests, nor the provenance of any data used.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not provided in the document.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study

This information is not provided in the document. There is no mention of a comparative effectiveness study involving human readers with and without AI assistance.

6. Standalone (Algorithm Only) Performance Study

The document mentions "Non-clinical verification and validation software tests were conducted to confirm that VeriSuite 1.8 with fluoroscopy meets its intended use and is safe and effective." This implies foundational testing of the algorithm itself. However, specific standalone performance metrics (e.g., accuracy, precision) in a clinical context are not reported in this summary. The device's function is a "patient position verification system" and "calculation of a correction vector," which, by its nature, involves algorithm-only operation to produce outputs for human review.

7. Type of Ground Truth Used

This information is not provided in the document. For the "Non-clinical verification and validation software tests," the nature of the ground truth would depend on the specific tests conducted (e.g., simulated data with known positions, comparison to known anatomical landmarks in a phantom). Explicit details are missing.

8. Sample Size for the Training Set

This information is not provided in the document. As a "patient position verification system" that calculates DRRs from CT data and identifies correction vectors, the system's core functionality likely relies on computational geometry and image processing rather than a "training set" in the machine learning sense for image recognition. If there were any machine learning components, the training set size is not disclosed.

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

This information is not provided in the document, and likely less relevant given the description of the device's function.

Summary of available information from the document:

• Device Function: VeriSuite is an image processing system for verification and correction of patient position during radiation therapy. It compares X-ray images with DRRs calculated from CT series and can also use fiducial markers. The fluoroscopy extension allows observation of patient movement (e.g., breathing) to interrupt treatment.
• Safety and Effectiveness: "Non-clinical verification and validation software tests were conducted to confirm that VeriSuite 1.8 with fluoroscopy meets its intended use and is safe and effective."
• Substantial Equivalence: The submission concludes that the device is "as safe and effective and substantially equivalent to the predicate devices described herein." This is the primary "proof" offered in a 510(k) summary for new features.
• Predicate Devices:
  • VeriSuite 1.8 (K092653) for the core system.
  • EXACTRAC 5.5 / ExacTrac X-RAY 6D (K072506) for the fluoroscopy functionality.
• Differences from Predicate (EXACTRAC 5.5): VeriSuite does not support optical prepositioning or internal respiratory gating signal display. Minor differences in hardware (higher resolution flat panels, X-ray image, and pixel size for VeriSuite).

In essence, this 510(k) summary acts as a declaration of substantial equivalence based on the stated intended use, technological comparison, and internal verification/validation, rather than a detailed report of a clinical efficacy study with specific statistical acceptance criteria. For such details, one would typically need to review the full 510(k) submission, which is not provided here.

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The VeriSuite patient position verification system is used for verification and correction of the patient's position during a radiotherapy treatment with external beams or charged particles. It is based on stereoscopic X-ray images and DRRs calculated from a CT image series of the treatment region of the patient and information from the treatment planning.

Not Found

Here's a breakdown of the acceptance criteria and study information for the VeriSuite device, based on the provided text.

Note: The provided document is a 510(k) premarket notification summary, which primarily focuses on demonstrating substantial equivalence to a predicate device. It does not contain the detailed study protocols, results, or comprehensive acceptance criteria that would typically be found in a full clinical or performance study report. Therefore, much of the requested information (like specific sample sizes for test sets, expert qualifications, adjudication methods, MRMC studies, or detailed ground truth establishment for training data) is not present in this document. The information provided below is extracted directly from the available text.

Acceptance Criteria and Device Performance (Limited Information)

The document states: "We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices..." This indicates that the primary acceptance criterion for the 510(k) submission was demonstrating substantial equivalence to existing predicate devices (specifically, EXACTRAC 5.5 / ExacTrac X-RAY 6D K072506).

Table of Acceptance Criteria and Reported Device Performance

Study Information (Based on Available Text)

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

   • Sample Size: Not specified in the provided document.
   • Data Provenance: Not specified in the provided document. The document primarily focuses on the regulatory review rather than detailed study methodology. It is likely that testing data would have been generated internally by the manufacturer during development and validation, but specific details are absent here.

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

   • Number of Experts: Not specified.
   • Qualifications of Experts: Not specified.

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

   • Not specified.

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 evidence of an MRMC study related to human readers or AI assistance in this document. The VeriSuite system is described as a "patient position verification system" based on X-ray images, implying an automated or semi-automated system for patient positioning rather than an AI-assisted diagnostic tool that would typically involve human readers and diagnostic accuracy studies.

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

   • The description "patient position verification system... It is based on stereoscopic X-ray images and DRRs calculated from a CT image series..." suggests that the system operates in a standalone capacity to perform its verification function. However, the document does not explicitly present a "standalone performance study" with specific metrics or results. The FDA's determination of substantial equivalence implies they reviewed performance data, but the details are not included in this summary.

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

   • The document implies that the "ground truth" for patient position verification would be the actual patient position or a carefully measured, validated reference position. This would likely be established through precise physical phantoms or highly accurate imaging modalities. However, the exact method for establishing ground truth for any testing is not specified in this regulatory filing summary.

7. The sample size for the training set:

   • Not specified. The document does not describe a training set as would be relevant for machine learning models. If the system uses algorithms that were "trained," the details are not in this summary.

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

   • Not applicable/Not specified, as no training set is described in the provided text.

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