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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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