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The intended use of the COHERENCE Workspaces are as optional accessories to the linear accelerator systems to aid and support in the quality assurance, planning and delivery of x-ray radiation for the therapeutic treatment of cancer.

The COHERENCE Workspaces encompasses a number of syngo software applications who's indication for use include the viewing, manipulation, filming, communications, and archiving of medical images and data on exchange media.

The COHERENCE Oncologist Workspace permits localization, contouring, image calibration and conditioning, and review of treatment parameters. In addition, it includes tools and administrative functions to aid in the diagnosis, staging, and prescription of radiation therapy. The indications for use for the COHERENCE Oncologist 2.0 workspace remain unchanged from the previously cleared COHERENCE Oncologist workspace (K031764).

The COHERENCE Physicist Workspace is a syngo software application package for the use with radiation therapy devices for viewing, manipulation and conditioning, communication and storage of medical images and data on exchange media; and as a quality assurance tool for radiation therapy linear accelerators and their accessories.

The COHERENCE Physicist Workspace is an optional accessory to a medical linear accelerator and is based on the previously cleared ONCOR Avant-Garde with COHERENCE Workspaces (K031764) and syngo™ software design architecture previously cleared on the LEONARDO workstation (K040970). The Quality Assurance software applications support the COHERENCE Data Conditioner and customer configurable Quality Assurance applications that Siemens believes are substantially equivalent to those previously cleared on the RIT 113 Film Analysis System (K935928).

The Physicist workspace will support the current manual methodologies for managing quality assurance data using the ONCOR COHERENCE Therapist (or PRIMEVIEW3) workspace) as sources of QA data. The Physicist WS will also offer a suite of customizable QA test protocols (user created and configured macros), test analysis and documentation tools.

The Physicist Workspace will support the COHERENCE Data Conditioner software application which allows the input of DICOM and non-DICOM conforming data objects that have been converted from electronically scanned film (bitmap or TiFF format), EPID data and electronic data from analyzers and The new COHERENCE Data Conditioning application will provide a method of film digitizers. importing non-DICOM data from a variety of electronic media, as mentioned above, and provide the user a method of converting the non-DICOM data into DICOM RT standard images. The DICOM RT standard images can then be processed using a combination of the previously cleared syngo software applications and the new conditioning, calibration and analysis software applications as described in this submission.

The previously cleared COHERENCE Oncologist Workspace provided a syngo based interface for 2D, 3D, and volumetric targeting of the radiation treatment using the Portal Imaging application for the purposes of patient position and setup. This revision to the Oncologist workspace adds.

COHERENCE Data Conditioner: The same syngo based software application module to enable the medical physicist and/or oncologist a method to convert non-DICOM data into DICOM RT conforming data where non image dependent information is missing such as gantry angle, collimator angle, etc.

Adaptive Targeting TM: Improvements to the volume targeting application for advanced Image Guided Radiation Therapy (IGRT) is featured in the new syngo based Adaptive Targeting application module, which supports alignment of 3D planning data for the purposes of patient setup and patient position localization. The Adaptive Targeting application supports the automatic calculation of the table offsets when comparing 3D planning data and current 2D or 3D portal imaging.

Here's an analysis of the provided text regarding the acceptance criteria and study for the COHERENCE™ Workspaces (Physicist, Oncologist) device:

Important Note: The provided text is a 510(k) summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device. This type of submission typically does not include detailed performance studies with explicit acceptance criteria, sample sizes, expert ground truth establishment, or multi-reader multi-case studies in the way a de novo or PMA submission might. The "study that proves the device meets the acceptance criteria" in a 510(k) context is primarily the demonstration of substantial equivalence by comparing the new device's features and safety/effectiveness to a predicate device.

Given this context, I will extract what information is available and highlight what is not present in the document.

Acceptance Criteria and Reported Device Performance

• Processing of QA data.
• Support for DICOM and non-DICOM conforming data.
• Customizable QA test protocols, analysis, and documentation.
• Viewing, manipulation, archiving of medical images and data.
• Localization, contouring, image calibration, review of treatment parameters (for Oncologist Workspace).
• Enhanced patient positioning accuracy through Adaptive Targeting. | The device, COHERENCE™ Workspaces (Physicist, Oncologist), successfully provides these functionalities. It enables the input, conversion, processing, and display of various QA data types (DICOM and non-DICOM), offers tools for QA practices, and enhances treatment planning and patient setup. | The entire submission implies that the device meets these functional requirements, as it claims substantial equivalence to predicate devices (K031764, K040970, K935928) and describes its new features (Data Conditioner, Adaptive Targeting) as performing these tasks. Page 2-4 describe the new functionalities in detail. |
  | Safety and Effectiveness Equivalence:
• The new device should be as safe and effective as the predicate device(s) for its intended use. | The FDA cleared the device, stating it is "substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices." | Page 5, FDA clearance letter. |
  | Compliance with Standards (implicit):
• Adherence to medical physics standards (AAPM Task Group 40). | The rationale for development cites AAPM standards as defining current QA practices, implying the device supports these. | Page 1, "The American Association of Physicist in Medicine, (AAPM) currently defines the standard of care for the quality assurance practices..." |
  | Conversion of Non-DICOM to DICOM RT:
• Ability to convert electronically scanned film (bitmap/TiFF), EPID data, and electronic data from analyzers/film digitizers into DICOM RT standard images. | The COHERENCE Data Conditioning application is described as providing "a method of importing non-DICOM data from a variety of electronic media... and provide the user a method of converting the non-DICOM data into DICOM RT standard images." | Page 2-3, "COHERENCE Data Conditioner" section. |
  | Automatic Calculation of Table Offsets (Adaptive Targeting):
• Ability to automatically calculate table offsets by comparing 3D planning data and current 2D or 3D portal imaging. | The Adaptive Targeting application "supports the automatic calculation of the table offsets when comparing 3D planning data and current 2D or 3D portal imaging." | Page 3, "Adaptive Targeting™" section. |

Detailed Study Information from the Provided Text:

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

   • Not explicitly stated. A 510(k) submission primarily relies on demonstrating equivalence to predicate devices and describing the new features. It does not typically involve new clinical performance studies with specific test sets and data provenance as would be seen in a PMA or de novo submission. The document describes functionalities and claims equivalence to previously cleared software.

2. 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):

   • Not explicitly stated. Since there is no mention of a formal "test set" or ground truth establishment process for a new performance study in this 510(k), information regarding experts for ground truth is absent. The document mentions that Medical Physicists, Medical Oncologists, Dosimetrists, and Radiation Therapists define and perform QA practices per AAPM and JCAHO guidelines, implying these professionals use and interpret the data generated by such systems.

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

   • Not explicitly stated. No adjudication method is mentioned as a formal test set was not described.

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, an MRMC comparative effectiveness study was not done according to the provided document. This document is a 510(k) for an accessory to a linear accelerator, which is software for managing and processing radiation therapy data and QA. It's not an AI diagnostic or assistive device in the sense that would typically warrant an MRMC study comparing human reader performance with and without AI assistance. The "Adaptive Targeting" feature offers automated calculations for position offsets, but this is presented as a functional improvement rather than an AI-driven diagnostic aid requiring MRMC.

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

   • Not explicitly mentioned as a formal "standalone" study. The device's functionalities, such as calculating table offsets and converting non-DICOM to DICOM, are inherently automated processes. However, these are presented as features of the software accessory rather than a standalone algorithm performance study. The device is an "accessory to a medical linear accelerator" and designed to "aid and support" human users (physicists, oncologists, therapists).

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

   • Not explicitly stated. Since a new performance study with a dedicated "test set" and ground truth establishment is not described, the type of ground truth is not detailed. The "ground truth" for radiation therapy QA and planning would generally derive from established clinical protocols, dosimetry measurements, and expert interpretation, which the software aims to facilitate and automate where possible.

7. The sample size for the training set:

   • Not applicable / Not explicitly stated. This device is software for managing and processing radiotherapy data, not a machine learning model that relies on "training sets" in the conventional sense of AI. Its development relies on established physics principles and software engineering practices, ensuring compatibility with existing radiotherapy systems and data standards.

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

   • Not applicable / Not explicitly stated. As there's no mention of a "training set" for a machine learning model, the establishment of its ground truth is not discussed.

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