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syngo. CT Colonography is used for easy-to-perform and efficient inspection of the colonic surface. It facilitates the search and diagnosis of colon lesions. The workflow management ensures that the required data and tools are offered to you according to your role and task.

syngo. CT Colonography is a clinical post-processing workflow for basic virtual colonoscopy. It is designed to support the following image reconstruction techniques:

• · Multiplanar Reconstruction (MPR)
• · Volume Rendering Technique (VRT)
• · Perspective surface shaded display (pSSD)
• The following evaluation tools are provided with this workflow:
• Virtual Flight
• · Panoramic View
• Polyp Lens
• Stool Tagging Stool Subtraction
• Polyp Enhanced Viewing (PEV)
• Movie

syngo.CT Colonography supports reporting with appropriate reporting tools such as lesion location, lesion characterization, and key image creation. Commercially available digital image processing tools with an optimized workflow and reporting tools, the software is designed to support the physician on confirming the presence or absence of physician identified colon lesions (for example, polyps) in addition to evaluation, and follow-up of any such lesions using standard or low-dose spiral CT scanning.

syngo.CT Colonography is a self-contained image analysis software package for evaluating CT volume data sets. The software is designed to support the physician in studying the inside, wall, and outside of the colon. It helps the physician to classify conspicuous regions of tissue with respect to their size, shape, and position.

Therefore, it combines tools for

• visualization of the data: ●
  • Panoramic Endoluminal View a)
  • Stool Tagging b)
  • Workflow Improvements C)
  • Virtual Dissection d)
  • e) Polyp Lens
  • Stool Subtraction f)
• navigation through the CT volume data sets ●
• evaluation of potential findings: ●
  • a) Semi-automatic measurements
• reporting of results:
  • a)

Here's a breakdown of the acceptance criteria and study information for syngo.CT Colonography based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state specific numerical acceptance criteria for clinical performance (e.g., sensitivity, specificity, accuracy for polyp detection). Instead, it relies on demonstrating that the device functions as intended and supports the physician in evaluating colon lesions.

The document refers to non-clinical and clinical performance tests to ensure the device fulfills requirements. The reported device performance is described in a general statement rather than specific metrics against a pre-defined threshold.

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

The document does not provide specific details on the sample size used for the clinical test set. It states:

• "Clinical performance tests were conducted to demonstrate performance, safety, and effectiveness of syngo.CT Colonography."
• "Testing was provided to cover a variety of clinical situations that would be seen in daily clinical use of the subject device."

The data provenance (country of origin, retrospective/prospective) is not specified.

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

The document does not provide information on the number of experts used or their qualifications for establishing ground truth in the clinical testing.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method used for the test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

The document does not mention or describe a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. Therefore, no effect size of human reader improvement with AI assistance is provided.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The document notes that syngo.CT Colonography is "designed to support the physician" and assists in "confirming the presence or absence of physician identified colon lesions." This implies a human-in-the-loop scenario. While "Performance tests were conducted to test the functionality of the syngo.CT Colonography post processing application," which might involve some standalone functional testing of its features, the document does not explicitly present data from a standalone algorithm-only performance study. The overall context is that of a tool assisting a physician.

7. The Type of Ground Truth Used

The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). Given the nature of a colonography device, it is highly probable that a combination of expert review (e.g., endoscopist review, radiology consensus) and potentially pathology reports for confirmed lesions would be used, but this is not confirmed in the text.

8. The Sample Size for the Training Set

The document does not provide any information regarding the sample size of a training set. This is not surprising as the document primarily focuses on demonstrating substantial equivalence to a predicate device, and the details of model training are typically not elaborated in such 510(k) summaries unless there are novel AI capabilities requiring specific validation.

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

Since no training set information is provided, the document does not describe how ground truth for a training set was established.

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