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syngo TrueD is a medical diagnostic application for viewing, manipulation, 3D- visualization and comparison of medical images from multiple imaging modalities and/or multiple time-points. The application supports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR. The images can be viewed in a number of output formats including MIP and volume rendering.

syngo TrueD enables visualization of information that would otherwise have to be visually compared disjointedly. syngo TrueD provides analytical tools to help the user assess, and document changes in morphological or functional activity at diagnostic and therapy follow-up examinations.

syngo TrueD is designed to support the oncological workflow by helping the user to confirm the absence or presence of lesions, including evaluation, quantification, follow-up and documentation of any such lesions. The application allows to store and export volume of interest (VOI) structures in DICOM RT format for use in radiation therapy planning systems.

syngo TrueD allows visualization and analysis of respiratory gated studies to support accurate delineation of the farget or treatment volume over a defined phase of the respiratory cycle and thus provide information for radiation therapy planning.

Note: The clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices and visual comparison of the separate unregistered images. syngo TrueD is a complement to these standard procedures.

syngo TrueD is a medical diagnostic application for viewing, manipulation, 3D- visualization and comparison of medical images from multiple imaging modalities and/or multiple time-points. The application supports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR. The images can be viewed in a number of output formats including MIP and volume rendering.

syngo TrueD enables visualization of information that would otherwise have to be visually compared disjointedly. syngo TrueD provides analytical tools to help the user assess, and document changes in morphological or functional activity at diagnostic and therapy follow-up examinations.

syngo TrueD is designed to support the oncological workflow by helping the user to confirm the absence or presence of lesions, including evaluation, quantification, follow-up and documentation of any such lesions. The application allows to store and export volume of interest (VOI) structures in DICOM RT format for use in radiation therapy planning systems.

syngo TrueD allows visualization and analysis of respiratory gated studies to support accurate delineation of the target or treatment volume over a defined phase of the respiratory cycle and thus provide information for radiation therapy planning.

TrueD will be marketed as a software only solution for the end-user (with recommended hardware requirements) .It will be installed by Siemens service engineers. The TrueD described supports DICOM formatted images and information. It is based on the Windows XP operating system.

The provided 510(k) summary for syngo™ TrueD Software (K101749) describes an update to an existing medical image viewing and analysis software. However, it does not contain acceptance criteria for specific device performance metrics or a detailed study proving the device meets such criteria.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (TrueD VC60A, K091373) by describing new features and stating that these new functionalities do not introduce unmitigated risks or functionality that would affect its safe and effective use. The "Safety Information / Nonclinical Testing" section refers to software validation but does not provide specific performance outcomes.

Therefore, many of the requested details cannot be extracted from this document. I will highlight what information is present and explicitly state what is missing.

Description of Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not specified in this document.
• Data Provenance: Not specified in this document. The document refers to "validation testing" but provides no details about the datasets used.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.
  The document states: "The output of the device is evaluated by trained professionals allowing sufficient review for identification and intervention in the event of a malfunction." and "The clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices and visual comparison of the separate unregistered images." This implies physician involvement in interpreting results but does not describe their role in establishing ground truth for testing.

4. Adjudication Method for the Test Set

• Not specified.

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

• Was a MRMC study done? This document does not mention an MRMC comparative effectiveness study. The focus is on demonstrating technical equivalence and safety rather than comparative clinical effectiveness with human readers.
• Effect Size: Not applicable, as no MRMC study is reported.

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

• Was a standalone study done? This document describes a "software only solution" and mentions "validation testing." However, it does not provide details about a standalone performance study with specific metrics like sensitivity, specificity, or accuracy for the new features (e.g., PERCIST quantification, lesion detection). The device is positioned as an "analytical tool to help the user" and a "complement to standard procedures," suggesting it's intended for human-in-the-loop use.

7. Type of Ground Truth Used

• Not specified. Given the nature of the device as an image viewing and analysis tool for oncology, potential ground truths could include expert consensus, pathology, or clinical outcomes, but the document does not elaborate on how ground truth was established for any validation activities.

8. Sample Size for the Training Set

• Not applicable. This is a software update to an existing device (syngo TrueD), and the features described appear to be based on algorithmic implementations of established clinical criteria (e.g., PERCIST) and technical extensions for handling image data types, rather than a learning algorithm that requires a "training set" in the context of machine learning. The document describes "validation testing" but not "training."

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

• Not applicable, as no training set for a learning algorithm is mentioned.

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syngo TrueD is a medical diagnostic application for viewing, manipulation, 3D- visualization and comparison of medical images from multiple imaging modalities and/or multiple time-points. The application supports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR. The images can be viewed in a number of output formats including MIP and volume rendering.

syngo TrueD enables visualization of information that would otherwise have to be visually compared disjointedly. syngo TrueD provides analytical tools to help the user assess, and document changes in morphological or functional activity at diagnostic and therapy follow-up examinations.

syngo TrueD is designed to support the oncological.workflow by helping the user to confirm the absence or presence of lesions, including evaluation, quantification, follow-up and documentation of any such lesions. The application allows to store and export volume of interest (VOI) structures in DICOM RT format for use in radiation therapy planning systems.

syngo TrueD allows visualization and analysis of respiratory gated studies to support accurate delineation of the target or treatment volume over a defined phase of the respiratory cycle and thus provide information for radiation therapy planning.

Note: The clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices and visual comparison of the separate unregistered images. syngo Truen in a complement to these standard procedures.

syngo TrueD is a medical diagnostic application for viewing, manipulation, 3D- visualization and comparison of medical images from multiple imaging modalities and/or multiple time-points. The application supports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR. The images can be viewed in a number of output formats including MIP and volume rendering.

syngo TrueD enables visualization of information that would otherwise have to be visually compared disjointedly. syngo TrueD provides analytical tools to help the user assess, and document changes in morphological or functional activity at diagnostic and therapy follow-up examinations.

syngo TrueD is designed to support the oncological workflow by helping the user to confirm the absence or presence of lesions, including evaluation, quantification, follow-up and documentation of any such lesions. The application allows to store and export volume of interest (VOD structures in DICOM RT format for use in radiation therapy planning systems.

syngo TrueD allows visualization and analysis of respiratory gated studies to support accurate delineation of the target or treatment volume over a defined phase of the respiratory cycle and thus provide information for radiation therapy planning.

TrueD will be marketed as a software only solution for the end-user (with recommended hardware requirements) . It will be installed by Siemens service engineers. The TrueD described supports DICOM formatted images and information. It is based on the Windows XP operating system.

This 510(k) summary primarily focuses on the substantial equivalence of the "syngo™ TrueD Software" to existing predicate devices, rather than providing detailed acceptance criteria and a specific study demonstrating performance against those criteria. It's a submission for a software device used for image viewing, manipulation, and 3D visualization, targeting applications in oncology and radiation therapy planning.

Based on the provided text, the following information can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not specify quantitative acceptance criteria or report specific performance metrics for the syngo™ TrueD Software that would typically be found in a performance study (e.g., sensitivity, specificity, accuracy for a diagnostic task). The submission emphasizes substantial equivalence to predicate devices for its intended use and technical characteristics.

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

The document does not mention a specific test set, its sample size, or data provenance (e.g., country of origin, retrospective/prospective). This type of information is usually associated with performance studies assessing diagnostic accuracy or similar metrics.

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

The document does not describe any specific ground truth establishment process for a test set, nor does it mention the number or qualifications of experts involved.

4. Adjudication Method for the Test Set:

No adjudication method is mentioned as there is no described test set or ground truth establishment process.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

No MRMC comparative effectiveness study is mentioned. The document primarily argues for substantial equivalence based on intended use and technological characteristics compared to predicate devices. The final "Note" states: "The clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices and visual comparison of the separate unregistered images. syngo TrueD in a complement to these standard procedures." This suggests the device is an assistive tool and not designed to replace human interpretation in diagnostic decision-making, which is often the focus of MRMC studies.

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

The document does not describe a standalone performance study. The device is presented as an image viewing and manipulation tool to support clinicians.

7. The Type of Ground Truth Used:

No specific ground truth type is mentioned as no performance study with a defined test set is described.

8. The Sample Size for the Training Set:

The document does not mention any training set or its sample size. This suggests the device may not heavily rely on machine learning models that require extensive training data in the same way as some contemporary AI diagnostics. Its function is primarily visualization and analysis, with tools to help users assess changes.

9. How the Ground Truth for the Training Set was Established:

Not applicable, as no training set is mentioned.

Summary of what the document does provide regarding "proof":

The document argues for the device's substantial equivalence to existing legally marketed predicate devices, rather than providing direct "proof" of meeting novel acceptance criteria through a performance study. It emphasizes:

• Identical Intended Use: The device's intended use is described as viewing, manipulation, 3D visualization, and comparison of medical images, similar to the functions of its predicate devices. It supports oncology workflows (lesion evaluation, quantification, follow-up, documentation) and radiation therapy planning (visualization/analysis of respiratory gated studies).
• Similar Technological Characteristics: It is a software-only solution, supports DICOM images, and runs on Windows XP, implying comparable technology to its predicates.
• Safety Information: A hazard analysis was conducted, and appropriate preventive measures were taken, resulting in a determination of "minor level of concern." It highlights that the device has no patient-contacting materials, is used by trained professionals, and device output is subject to review by these professionals. It also states the device "does not impact the quality or status of the original acquired data."

Conclusion:

This 510(k) submission for syngo™ TrueD software in 2009 is a premarket notification for substantial equivalence. It does not include a detailed study with quantitative acceptance criteria and performance data like those commonly seen for AI/ML diagnostic algorithms today. Instead, its "proof" is centered on demonstrating that it is as safe and effective as, and performs as well as, already legally marketed predicate devices with similar intended uses and technological features.

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