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syngo.CT Cardiac Function is an image analysis software package for evaluating CT images of the heart. Combining digital image processing and visualization tools (2D, 3D and 4D display of dynamic data), evaluation tools (structural and functional analysis of heart chambers and valves, and analysis of myocardial tissue) and reporting tools, the software package is designed to support the physician in determining the functional and morphological parameters of the heart chambers, heart valves and confirming the presence or absence of physician-identified myocardial disease and evaluation, documentation and follow-up of any such finding.

syngo.CT-Cardiac Function is a dedicated application for cardiac and vascular post processing. Accordingly, syngo.CT-Cardiac Function has been designed in order to support diagnosis of cardiovascular lesions with a particular focus on conditions affecting cardiac function. syngo.CT Cardiac Function includes tools that support the clinician at different steps during diagnosis, including reading and reporting. The user has full control of the reported measurements and images, and is able to choose the appropriate function suited for their clinical need. Features included in this software that aid in diagnosis can be grouped into the following categories: Basic reading: commodity features that are commonly available on CT cardiac post-processing workstations. Advanced reading: additional features for increased user support during CT cardiac post-processing. If results are not as expected by the user (e.g. due to bad image quality caused by image artifacts, such as: noise, pacemaker artifacts, stair steps, wrong contrast timing, etc), he or she can easily modify the computations or discard them and do a manual diagnosis. The corresponding information will be kept in the reporting object which is stored in the syngo via database.

The provided text describes a Special 510(k) Submission for syngo.CT Cardiac Function. However, it does not contain a detailed study proving the device meets specific acceptance criteria with performance metrics, sample sizes, ground truth establishment, or expert involvement. The document primarily focuses on establishing substantial equivalence to predicate devices and adherence to relevant standards.

Here's an attempt to answer the questions based on the available information, noting where information is explicitly not present:

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

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

• Sample size for the test set: Not provided.
• Data provenance: Not provided. The document mentions "Non clinical tests were conducted for syngo.CT Cardiac Function software package during product development" but does not specify the origin or nature of the data used for these tests.

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)

• Number of experts: Not provided.
• Qualifications of experts: Not provided.
  These details are not discussed in the provided document.

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

• Adjudication method: Not provided.

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 study: Not indicated. The document focuses on the device's technical characteristics and substantial equivalence, not on comparative effectiveness with human readers.
• Effect size: Not applicable, as no MRMC study is reported.

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

• The document implies standalone testing through its references to "Non clinical tests" and "testing results supports that all the software specifications have met the acceptance criteria." However, it does not provide specific performance metrics for this standalone testing beyond a general statement of compliance. The device is described as a "support" tool for the physician ("designed to support the physician"), implying a human-in-the-loop context for its clinical use, but the reported testing doesn't detail this interaction.

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

• Type of ground truth: Not specified.

8. The sample size for the training set

• Sample size for the training set: Not provided. The document mentions "current image processing algorithms" but does not detail any machine learning or AI training phases or associated data.

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

• How ground truth was established: Not applicable, as information about a training set or its ground truth establishment is not provided.

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