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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 Prelude Planning Software for the electron beam IORT treatment can be used for any malignant and benign tumor. For Prelude no limitation is given to the patient population. Local/Regional recommendations or guidelines may indicate patient who will benefit from IORT more than from other treatment modalities.

In general, since Prelude is tailored for the planning with the Mobetron®, it can be used for IORT treatment planning, if a patient is prescribed to be treated with the Mobetron®.

The Prelude software supports the IORT treatment workflow. Prelude Dosimetric measurement data of the radiation device can be displayed by selecting the machine parameters. Upon that information the user can easily plan the treatment and the software calculate the required parameters for the IORT devices.

For quality assurance the machines parameters can be recorded and visualized.

For the calculation of the output factors or the monitor units either the IAEA or AAPM protocol is followed.

The software is intended to be used by medical professionals in the area of radiation therapy.

The main purpose is to plan the technical parameters required to perform an electron beam IORT to treat both malignant and benign tumors

This document describes the MedCom GmbH Prelude planning software, K180308, for electron beam Intraoperative Radiation Therapy (IORT) treatment planning.

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

The provided text does not contain a specific table of acceptance criteria with corresponding device performance metrics in the format typically used for AI/ML device submissions (e.g., sensitivity, specificity, AUC, FROC analysis). Instead, the document focuses on general software safety, effectiveness, and usability assessments, emphasizing that the software meets its intended use and is safe and effective.

The performance details are described qualitatively rather than quantitatively against specific acceptance criteria. Key performance aspects reported include:

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

• Sample Size for Test Set: The document states that "Clinical patient data was simulated." It does not specify a numerical sample size for this simulated data.
• Data Provenance: The data used for testing was "dosimetric measurement data from a Mobetron® device" and "simulated" clinical patient data. The country of origin for the simulated data or the Mobetron® device's data is not explicitly mentioned, but MedCom GmbH is located in Germany. The study appears to be a retrospective analysis of simulated data and device performance.

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)

The concept of "ground truth" as typically defined for AI/ML diagnostic devices (e.g., truth established by pathology or expert consensus on a test set) is not directly applicable here in the same way. The device is a planning software, not a diagnostic one.

Instead, the "truth" or correctness of the outputs was assessed through:

• Comparison to "expected parameters" for the simulated input data.
• Usability testing with "users" and "Mobetron users and other experts in that field" who provided feedback.
• Risk assessment team included "application specialists and a medical expert besides the development team and quality managers with risk management experience." Specific numbers and detailed qualifications of these individuals are not provided, beyond stating they were "medical expert" and "experts in that field."

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

No formal adjudication method (like 2+1 or 3+1 for resolving disagreements among multiple readers) is described for a test set in the context of diagnostic decision-making. The testing involved verification that the software produced "expected parameters" for simulated data and that users could successfully create plans and approve them, and that the software assisted in optimizing the treatment delivery.

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 multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance is mentioned. The software is a planning tool, not an AI diagnostic assistant. Its purpose is to support medical professionals in radiation therapy by assisting in treatment planning and QA, not to be a diagnostic aid that would typically involve an MRMC study.

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

The evaluation described is intrinsically "human-in-the-loop" as Prelude is a planning software intended to be used by medical professionals. The software assists in calculations and visualizations, but the user defines parameters, approves plans, and interprets outputs. The testing included assessing user interaction and ability to create and approve plans.

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

The "ground truth" for evaluating this planning software was based on:

• Expected parameters: For the simulated clinical patient data, the software's calculated output parameters were compared against "expected parameters" for a treatment.
• Usability Feedback/Expert Opinion: Evaluation of whether users could successfully create treatment plans, define parameters, and whether the workflow was understandable. This suggests expert review of the software's functionality and output.
• Established Radiation Therapy Protocols: The software follows IAEA or AAPM protocols for calculation methods, implying adherence to recognized standards.

8. The sample size for the training set

The document does not describe the use of machine learning models requiring a distinct "training set." Prelude is a treatment planning software that performs calculations based on measured dosimetric data and established physical principles (IAEA/AAPM protocols), rather than a system trained on a large dataset of patient images or outcomes. Therefore, the concept of a "training set" in the context of AI/ML is not applicable here.

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

As there is no mention of a training set for machine learning, the question of how its ground truth was established is not applicable. The software's calculations leverage "dosimetric measurement data of the radiation device," which serves as input to its algorithms based on physics principles, not as training data for a learning model.

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The BiopSee bundled system is a combination of MobileUS providing the "Medical Image Processing Workstation" which acquires and displays ultrasound images from external ultrasound scanners and the BiopSee "Image Fusion Navigation Software" which is a stereotaxic accessory for Ultrasound (US) devices.

The BiopSee system is intended to be used in clinical interventions and for anatomical structures in a clinical setting where US imaging is currently used for visualizing such procedures. It displays the simulated insertion tool such as a biopsy needle on a computer monitor that shows images of the target organs and the projected future path of the interventional instrument.

The patient population is mainly people who need prostate biopsy.

It is intended to be used mainly in the Urological departments for prostate biopsies.

The BiopSee system is not intended to be used as a standalone diagnostic image device, since it represents information of a patient that could not be congruent with the current (actual) patient position and shall therefore always be seen as an additional source of information.

The BiopSee system when connected with an electromagnetic tracker should not be used on or around persons with a cardiac pacemaker, and should not be used around life supporting equipment. BiopSee is a prescription device.

The BiopSee bundled system (also called BiopSee System) is a medical image processing workstation that provides image quided instrument navigation. The hardware part (MobileUS) consists of the system unit which includes a CPU, a monitor, medical-grade keyboard, mouse and power supply and a medical trolley. It is designed to display ultrasound images from different sources. Optionally it can be equipped with an electromagnetic positioning system to track the ultrasound probe or other medical instruments.

The system is able to load different image modalities such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron emission tomography (PET) and allows organ delineation and planning instrument access paths within the 3D dataset. It is designed to display 2D images from commercially available ultrasound systems and either reconstruct a 3D ultrasound image or fuse the images with pre-loaded other datasets.

The BiopSee software can be installed on standard PCs under Microsoft Windows operating systems which follow the minimum requirements described in the service manual, similar to MobileUS hardware. BiopSee is designed to work in combination with an ultrasound scanner (the Ultrasound System is used in order to display the live US images) and a probe, a positioning system (to track the position of the probe) and medical navigation instruments (to track the position of the medical instruments like needles). The ultrasound scanners connected must be tested with the BiopSee System and shall be legally marketed in the US.

Here's an analysis of the provided text, focusing on the acceptance criteria and study information for the BiopSee, Mobile US device, organized according to your requested points:

The provided text is a 510(k) summary, which is a premarket notification for a medical device. This document primarily focuses on establishing substantial equivalence to previously cleared devices rather than providing a detailed report of clinical study results that would typically be found in a full Clinical Study Report (CSR). Therefore, some of the information you requested may not be explicitly present or might be inferred from the context of substantial equivalence claims and non-clinical data.

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

The document details non-clinical performance data, primarily focusing on system accuracy and tracking quality. It doesn't explicitly state "acceptance criteria" in a tabular format but presents performance metrics.

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

The document does not provide information on the sample size for a test set in the context of clinical data. The performance data presented are from non-clinical verification and validation software tests using CIRS Phantoms. These are physical models used for testing medical imaging systems. There is no mention of human subject data, country of origin, or whether it was retrospective or prospective.

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)

Given that the testing was non-clinical and involved phantoms, there were no human experts or ground truth established in the sense of clinical diagnoses. The "ground truth" for these tests would have been the known physical properties and measurements within the CIRS phantoms, against which the device's measurements and projections were compared.

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

Not applicable. Since the testing was non-clinical and involved phantoms, there was no adjudication method involving human experts. The comparison would be against the known physical dimensions and positions within the phantom.

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

The document does not mention an MRMC comparative effectiveness study. The BiopSee system is described as an "Image Fusion Navigation Software" and a "medical image processing workstation" intended for image-guided instrument navigation, not as an AI-powered diagnostic tool for interpretation by human readers. Therefore, an MRMC study comparing human reader performance with and without AI assistance is not relevant to the described functions of this device in this document.

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

The document describes standalone non-clinical performance testing of aspects of the algorithm, particularly for system accuracy (needle navigation), tracking quality, 2nd modality image display, and length measurement. These tests evaluate the device's technical performance metrics without human clinical interpretation or interaction beyond setting up the test and recording results.
However, the device itself is not intended to be used as a standalone diagnostic image device and explicitly states it "shall therefore always be seen as an additional source of information." This implies it is always used with a human in the loop for clinical decision-making.

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

For the non-clinical tests mentioned, the ground truth was known physical properties and measurements of CIRS phantoms. For the tracking system, the manufacturer-stated accuracy of the integrated "Ascension 3D Guidance trakSTAR" (1.4 mm RMS, 0.5 degrees RMS) serves as a ground truth reference for its inherent accuracy. There is no mention of expert consensus, pathology, or outcomes data as ground truth in this submission, as it focuses on technical performance rather than clinical diagnostic accuracy.

8. The sample size for the training set

The document does not provide information on a training set. This is not a machine learning or AI algorithm submission in the sense of a predictive model that requires a labeled training set. It's a medical image processing workstation and navigation software.

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

Not applicable, as no training set is mentioned or implied for the functionalities described.

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The NaviSuite SSI Edition is used to support a clinical ultra-sound session and follow percutaneous procedure by means of providing additional real-time image information from a 2nd modality like CT or MR or US or its combination with the possibility to plan the ideal treatment procedure. The second modality or their combinations are acquired and 3D is generated inside the software permitting the anatomical correlation with the patient position.

"The second modality image is not intended to be used as a standalone diagnostic image since it represents information of a patient that could not be congruent with the current (actual) patient position and shall therefore always been seen as an additional source of information."

"The 2nd modality image only should not be used for diagnostic purposes."

NaviSuite SSI Edition 0.9.10 is a medical product to support a clinical ultrasound session and follow percutaneous procedure by means of providing additional realtime image information from a 2nd modality like CT or MR or US or its combination with the possibility to plan the ideal treatment procedure. The second modality or their combinations are acquired and a 3D is generated inside the software permitting the anatomical correlation with the patient position.

By using the 2nd modality image the user gains security in assessing the morphology of the ultrasound image and obtains a virtual feed-back on the procedure provided by the virtual percutaneous tool position enabled by a dedicated receiver, its treatment region delineated by custom tables and a dedicated computation in 3D of the target region.

The 2nd modality image is not intended to be used as a standalone diagnostic image since it represents information of a patient probably not congruent with the current (real) patient situation and shall therefore always been seen as an additional source of information.

NaviSuite SSI Edition is a software designed for use together with an ultrasound device: AIXPLORER (K142100).

Here's a breakdown of the acceptance criteria and study information for the NaviSuite SSI Edition, based on the provided text:

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 the sample size for a test set in terms of patient data or specific image sets.

• Needle Navigation Test: A CIRS Abdominal Phantom was used for testing. This is a non-human, simulated anatomical model.
• Tracking Quality Test: No specific sample size or type of data (beyond stating "tests... have been carried out") is mentioned for this.

The data provenance for any testing mentioned (phantom-based) is not from human patients, and therefore the concepts of "country of origin" or "retrospective/prospective" do not apply in the context of clinical data for the reported tests.

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

The document does not mention using experts to establish ground truth for any of the reported tests. The tests performed were primarily technical verifications (phantom-based needle navigation, tracking quality) rather than diagnostic performance evaluations requiring expert adjudication.

4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set

No adjudication method is mentioned, as the tests performed do not involve human diagnostic interpretation that would require such a process.

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

No MRMC comparative effectiveness study is mentioned. The device is intended to support a clinical ultrasound session by providing additional real-time image information from a 2nd modality; it is explicitly stated that the 2nd modality image is not intended to be used as a standalone diagnostic image and should not be used for diagnostic purposes. This phrasing suggests the device is an assistive tool rather than a standalone diagnostic AI that would be subject to MRMC studies comparing human performance with and without its assistance.

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

The NaviSuite SSI Edition, as described, is not a standalone diagnostic algorithm. It is a software designed to be used "together with an ultrasound device" and provides "additional real-time image information." The provided texts highlight that the "2nd modality image is not intended to be used as a standalone diagnostic image" and "The 2nd modality image only should not be used for diagnostic purposes." Therefore, a standalone performance study in the context of diagnostic accuracy would not be applicable or appropriate for this device's intended use. The technical tests performed (system accuracy, tracking quality) are standalone in the sense that they evaluate the software's functional performance, but not its diagnostic capability.

7. The Type of Ground Truth Used

• System Accuracy (2nd Modality Image Display): The ground truth for the 5mm accuracy claim relies on the "presumption that the registration has been done with an overall error better than 5mm." This implies a technical measurement or calculation of registration error.
• Needle Navigation Testing: The ground truth for this appears to be the physical location of the needle within the CIRS Abdominal Phantom compared to the software's projected virtual needle position. This would be a physical phantom-based ground truth.
• Tracking Quality Test: The ground truth would be the known presence or absence of factors causing "low sensor tracking quality" or "distorted tracking" (e.g., metallic objects) and the software's ability to correctly detect and report these. This is also a technical ground truth.

8. The Sample Size for the Training Set

The document does not mention any training set size. This device appears to be primarily an image registration and visualization tool rather than a machine learning model that would require a dedicated training set of images with established ground truths for learning.

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

Since no training set is mentioned, information on how its ground truth was established is not provided.

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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 PVS 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.

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I apologize, but the provided text focuses on an FDA 510(k) clearance letter for a medical device (PVS 1.0) and its indications for use. It does not contain the specific information required to complete the detailed request about acceptance criteria and a study proving device performance.

The document confirms the device is substantially equivalent to a predicate device and can be marketed, but it doesn't describe the technical details of acceptance criteria, study methodology, sample sizes, ground truth establishment, or expert involvement in the way the prompt requires.

Therefore, I cannot provide the requested table and study details based on the given information.

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Bridge-RT is a Medical Device intended to be used for reviewing and assessment of DICOM based datasets which may occur in a radiotherapy environment. It is used by qualified specialist to load and display data generated by different DICOM devices including: RT-STRUCT, RT-PLAN, RT-DOSE, RT-IMAGE, CR, CT, MR and PET.

The software provides the radiotherapy specialist with the necessary visualization and image manipulation tools to review, present or compare DICOM-RT related datasets including the geometrical super imposition of 3D plan data.

Bridge-RT is intended for reviewing purposes only and is not capable to generate new or modified RT plan data.

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The provided text is a 510(k) premarket notification FDA letter for the Bridge-RT 2.0 device. This type of document does not contain the detailed study information, acceptance criteria, or performance data that would typically be found in a clinical trial report or a more comprehensive technical submission.

The letter explicitly states that the device is for "reviewing and assessment of DICOM based datasets" and "is intended for reviewing purposes only and is not capable to generate new or modified RT plan data." This indicates that the device is primarily a visualization and image manipulation tool, not an AI diagnostic or treatment planning system that would require performance metrics like sensitivity, specificity, or reader improvement studies.

Therefore, I cannot provide the requested information from the given text. The text does not describe an acceptance criteria or a study that proves the device meets specific performance criteria in the context of AI or diagnostic accuracy.

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The VeriSuite patient position 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.

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.

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

• Beam limiting collimator device (Ralco 302)
• X-ray generator (Sedecal XHF 835) -
• X-ray tubes (Varian A277 or A272)
• Flat panel digital imager (Varian 4030E -
  Optional:
  All these hardware devices are legally marketed in the US as listed in previous section D.

This document, a 510(k) submission for VeriSuite 1.8, does not contain information regarding detailed acceptance criteria, the methodology of a study to prove device performance against these criteria, or specific data pertaining to ground truth establishment, expert qualifications, or sample sizes for training and test sets.

The document primarily focuses on:

• Device Identification: Trade names, common names, classification, and product codes of VeriSuite and its components.
• Predicate Device: Details of VeriSuite 1.6 and other predicate devices (X-Ray Generator, X-Ray Tubes, Flat Panel Digital Imager, Collimator).
• Device Description: VeriSuite is an image processing system for verifying and correcting patient position during radiation therapy by comparing X-ray images with DRRs or fiducial markers. It's a system comprising software and legally marketed hardware components.
• Intended Use: Verification and correction of patient position during radiation therapy using stereoscopic X-ray images and DRRs. Emphasizes evaluation and approval by an authorized person, and notes it's not for diagnostic purposes.
• Summary of Technical Considerations: States substantial equivalence to the predicate device.
• FDA Communication: A letter from the FDA confirming the review of the 510(k) premarket notification and determining substantial equivalence for the stated indications for use.
• Indications for Use Statement: A formal statement on the intended use of the VeriSuite patient position system.

Therefore, I cannot provide the requested information as it is not present in the provided text.

To answer your request, the document would need to include sections on:

1. Clinical Performance Study, Validation Study, or Bench Testing: Describing the study design, objectives, and methods for evaluating the device's accuracy and performance.
2. Acceptance Criteria: Specific quantitative thresholds for performance metrics (e.g., accuracy, precision, repeatability) that the device must meet to be considered safe and effective.
3. Study Results: The measured performance of the device against the established acceptance criteria.
4. Sample Size and Data Provenance: Details on the number of cases/patients used, where the data originated (e.g., specific hospitals, countries), and whether it was collected retrospectively or prospectively.
5. Ground Truth Establishment: How the "true" patient position or correction vector was determined for the study data, including the number and qualifications of experts involved, and their adjudication method (e.g., consensus, majority vote).
6. Standalone vs. Reader Study: Whether the device's performance was evaluated independently (algorithm only) or as part of a human-in-the-loop study (MRMC). If MRMC, the effect size of AI assistance on human readers.
7. Training Data: Information on the size and characteristics of the dataset used to train the VeriSuite algorithm (if applicable, as this is an older device submission, specific AI/ML training details might not be explicit in this format).
8. Training Ground Truth: How the ground truth for the training set was established.

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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.

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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.

Ask a specific question about this device

The Exomio Radiation Treatment Simulation System is used for CT-based diagnostic image analysis, while also providing treatment planning tools to the physician, such as: contouring and segmentation (manual or automatic), radiation treatment field editing and 3D visualization of the virtual treatment setup. Moreover, it includes useful treatment setup export capabilities to enable the communication with compatible medical devices.

Exomio is a programmable (Software) medical device aiming to fully provide the physicians with necessary visualisation and image manipulation tools to prepare the patient's RT simulation virtually in absence of the physical patient and the physical simulator. This is done using the patient's CT data set, including the attached on the patient's skin reqistration markers, instead of the physical patient. This process it called virtual simulation and Exomio, as well as other similar systems, is called CT-based or Virtual Radiation Treatment Simulation System.

Exomio provides tools to support clinician's decision making through the use of enhanced visualization of the patient data set and treatment parameters. 3-D visualization provides an excellent overview of the patient's anatomy. In addition, the relation between treatment beams and tumor can be investigated in detail using Exomio's navigation tools. All this unique functionality is provided to the clinics with aim the overall improvement of the RT simulation process.

Exomio is able, using the DICOM standard, to export all parameters necessary for the treatment of the patient as well as the images to other devices supporting DICOM RT Plan and Structure Set. This way the whole procedure becomes a lot faster savinq even more time for the physician and the rest medical staff.

The provided document is a 510(k) submission for a medical device (Exomio Model 2.0 SP1 Radiation Therapy Simulation System) and an FDA clearance letter. It describes the device's intended use and substantial equivalence to a predicate device but does not contain any information about acceptance criteria, device performance, studies conducted, sample sizes, ground truth establishment, or expert involvement.

Therefore, I cannot fulfill your request for a table of acceptance criteria and reported device performance or details about a study to prove the device meets these criteria. This type of information is typically found in detailed technical reports, validation studies, or clinical trial summaries, which are not present in this 510(k) summary.

The document primarily focuses on establishing substantial equivalence to a predicate device, which usually means demonstrating that the new device has the same intended use, technological characteristics, and safety and effectiveness profiles as a previously cleared device, often without requiring extensive new clinical studies if the differences are minor.

Ask a specific question about this device