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Simulix Evolution is a radiation therapy simulation system is intended to prepare patients for radiation therapy. The Simulator emulates the geometrical positions of radiation therapy treatment machines. Using conventional radiographic and fluorographic system, patients are positioned, filmed and marked to prepare them for treatment. The Ocentra Cone Beam CT option for the Simulis Evolution Radiotion Therapy Simulator is intended to assist the Radiation Oncologist in acquiring 3D "multi slice" planning data in patient set-ups for the purpose of radiation therapy treatment planning and patient positioning

Oncentra ConeBeam is an extension to the Nucletron Simulix Evolution system. The Simulix Evolution is a Radiation Therapy Simulation System which is to be used in radiation therapy simulation, using a fluoroscopic and/or radiographic x-ray system for visualizing the volume to be exposed during radiation therapy and confirming the position and size of the therapeutic irradiation field to be applied. The Simulix Evolution is previously cleared under 510(k) #K033470. The Oncentra ConeBeam extension will give the Simulix Evolution system the capability to acquire Computer Tomography (CT) images. This is done by means of scanning the patient with a cone shaped X-ray beam. The cone shaped beam gives the possibility to acquire CT image information of a volume instead of CT image information of a single slice as with conventional fan beam CT. The images acquired with Oncentra ConeBeam will be used for the purpose of radiation therapy planning and to check the positioning of the patient.

I am sorry, but the provided text does not contain information about the acceptance criteria or a study that proves a device meets those criteria. The document is a 510(k) summary for the Nucletron Simulix-Evolution with Oncentra™ ConeBeam, which describes the device, its intended use, and its substantial equivalence to predicate devices, but it does not include details on acceptance criteria or performance studies.

Therefore, I cannot fulfill your request to provide the following information:

1. A table of acceptance criteria and the reported device performance
2. Sample sized used for the test set and the data provenance
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
4. Adjudication method for the test set
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, and its effect size
6. If a standalone performance (algorithm only) study was done
7. The type of ground truth used
8. The sample size for the training set
9. How the ground truth for the training set was established

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Simulix Evolution is a radiation therapy simulation system is intended to prepare patients for radiation therapy. The Simulator emulates the geometrical positions of radiation therapy treatment machines. Using conventional radiographic and fluorographic system, patients are positioned, filmed and marked to prepare them for treatment.

Simulix Evolution is a Flat Panel detector option to the Nucletron Simulix HP simulator system. The Simulator emulates the geometrical positions of radiation therapy treatment machines. Using a conventional radiographic and fluorographic system, patients are positioned, filmed and marked to prepare them for treatment. The Simulix Evolution option consists of a digital Flat Panel detector and a PC based simulator workstation. The Flat Panel detector option replaces the current Image Intensifiers. The Flat Panel is a Amorphous silicon, digital detector, with a square image area of 41 by 41 cm. The PC based simulator workstation is the current DTI workstation, but ported to a Windows platform. The PC based simulator workstation comes with functionality to support simulation procedures: Image acquisition, Image display, Image enhancement and multiple views, Database and DICOM Import / Export functionality, Simulator controls.

The provided text describes a 510(k) premarket notification for a medical device called "Simulix Evolution." However, it does not include information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, or expert qualifications in the comprehensive manner requested. The document focuses on establishing substantial equivalence to a predicate device and outlines the device's intended use and technological considerations.

Therefore, many of the requested details cannot be extracted from the given text.

In lieu of the specific details, here's what can be inferred or stated that is missing:

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

2. Sample size used for the test set and the data provenance

• Sample Size for Test Set: Not specified.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not specified.
  • Implied: Given it's a submission for a new device, any testing would likely be prospective in a controlled environment, but this is not explicitly stated.

3. 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.
  • Implied: For a radiation therapy simulation system, experts would typically be radiation oncologists, medical physicists, and/or radiation therapists.

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

• Adjudication Method: Not specified.

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 Comparative Effectiveness Study: Not mentioned.
  • Note: The device described is a simulation system, not an AI diagnostic tool, so an MRMC study comparing human readers with and without AI assistance is not directly relevant to the information provided. The "Simulix Evolution" is described as replacing an Image Intensifier with a Flat Panel detector and porting a workstation to Windows, focusing on hardware and software updates for simulation, not AI-driven interpretation.

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

• Standalone Performance Study: Not explicitly mentioned in terms of quantitative data or metrics. The submission focuses on demonstrating substantial equivalence of the system (hardware and software) to its predicate.

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

• Type of Ground Truth: Not specified.
  • Implied: For a simulation system, ground truth would likely involve established geometrical accuracy measurements, phantom studies, and possibly comparisons to existing simulation data from the predicate device.

8. The sample size for the training set

• Sample Size for Training Set: Not specified.
  • Note: The device is not described as having a machine learning component that would require a 'training set' in the traditional sense of AI algorithm development. The software capabilities mentioned (image acquisition, display, enhancement, database, DICOM) are standard functionalities, not indicative of a learning algorithm.

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

• How Ground Truth for Training Set was Established: Not applicable, as a training set, as typically understood for machine learning, is not indicated by the provided description. If 'training set' refers to data used for software validation or testing, the method of establishing ground truth for such data is not specified.

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