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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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Medicsight ColonCAD™ API is a non-invasive computer aided detection (CAD) image analysis software tool designed to assist radiologists in the detection of colorectal polyps during their review of digital images derived from CT colonography (CTC). This CAD software post-processes the CTC image data obtained from multi-detector computed tomography (MDCT) scanners.

The device is intended to be used on patients referred for a CT Colonography examination, as an overlay tool to prompt the radiologist to colonic findings that have been identified by the device. The CAD can assist radiologists after they have made an initial review of all the CTC image data, supporting their evaluation ("second read").

Medicsight ColonCAD API is a medical imaging software tool designed to assist radiologists in the detection of polyps in CT scans of the product is packaged as an Application Programming Interface (API) which allows it to be integrated into existing medical imaging solutions.

The ColonCAD API assists the radiologist in detecting colorectal polyps using mathematical image processing techniques. The CAD assists the radiologist by highlighting potential polyps in 2D and 3D image views. The results are displayed in the form of "CAD marks" on or near the potential polyps. The radiologist must assess every CT scan image to search for polyps and review the CAD marked images to determine if the indicated findings are polyps.

Patient management decisions should not be made solely on the results of ColonCAD analysis.

The information provided details the Medicsight ColonCAD API device, its intended use, and a summary of studies conducted. However, the document does not explicitly state specific acceptance criteria (e.g., a required sensitivity or specificity value) or the reported device performance in a numerical table. It only mentions that the device's accuracy was "significantly higher" with CAD assistance.

Therefore, I cannot populate a table of acceptance criteria and reported device performance with specific numerical values based on this document.

Here's an analysis of the provided information concerning the study:

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 explicitly stated in the provided document.
• Data Provenance: Not explicitly stated in the provided document (e.g., country of origin, retrospective or prospective).

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

• Number of Experts: Not explicitly stated in the provided document.
• Qualifications of Experts: Not explicitly stated in the provided document.

4. Adjudication Method for the Test Set

• Adjudication Method: Not explicitly stated in the provided document.

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

• Was an MRMC study done? Yes. The document states: "The results of the MRMC study demonstrated that radiologists' accuracy for detecting colorectal polyps of any size was significantly higher with CAD than in the unassisted read, as measured by the segment-level area under the ROC curve (AUC)."
• Effect Size: The document states that accuracy was "significantly higher" with CAD, and mentions "segment-level area under the ROC curve (AUC)" as the metric. However, it does not provide a numerical effect size (e.g., the specific AUC values for assisted vs. unassisted read, or the magnitude of improvement).

6. Standalone Performance Study

• Was a standalone study done? The document focuses on the C-CAD (Computer Aided Detection) device assisting radiologists, implying a human-in-the-loop scenario. While it mentions "internal clinical evaluations" as part of non-clinical studies, it does not detail a standalone algorithm-only performance study with specific metrics. The primary clinical study discussed is an MRMC study evaluating human-in-the-loop performance.

7. Type of Ground Truth Used

• Type of Ground Truth: Not explicitly stated in the provided document for the clinical study. It refers to "detecting colorectal polyps," implying a definitive diagnosis, but the method for establishing this truth is not detailed (e.g., pathology, expert consensus).

8. Sample Size for the Training Set

• Sample Size for Training Set: Not explicitly stated in the provided document. The document mentions the ColonCAD API uses the "same underlying image processing technology" and "same algorithm" as the predicate ColonCAR 1.2 device (K042674), suggesting the training might have occurred prior to this specific API version's development or relies on pre-trained models.

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

• How Ground Truth Was Established (Training Set): Not explicitly stated in the provided document. As with the test set, the method for establishing the ground truth for training data (if new training was performed) is not detailed.

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Colon CAR 1.2 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the colon derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of polyps, cancers and other lesions. The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting single or double seed points followed by interactive fine-tuning the boundaries of the ROI. It also allows for the simultaneous display of supine and prone images.

Colon CAR 1.2 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the non-enhanced view.

Colon CAR™ (Computer Assisted Reader) 1.2 is a software tool designed to assist radiologists and other clinicians in the evaluation of polyps and other lesions in the colon. The software allows the user to select regions of interest either manually or by selecting a single or double seed point, followed by semi-automatic detection of the ROI boundary. It provides 2D and 3D visualisation of polyps and measurement of polyp characteristics such as size and volume. The further feature of Colon CAR™ 1.2 as compared to the cleared device is a Polyp Enhanced Viewing Filter (PEV), the results of which are presented in a Joint Reader filter view (enhanced and non-enhanced data viewed simultaneously). The PEV filter identifies intra-colonic filling defects protruding into the colonic lumen, thereby highlighting potential polyp candidates for further interrogation by the reporting radiologist. This filter is fully adjustable and, in deciding the desired characteristics of the objects to be highlighted, the radiologist may specify the degree of object sphericity (or roundness), the height of the protruding object in relation to its base (object 'flatness') as well as select an approximate object diameter range.

The provided text does not contain specific acceptance criteria or an explicit study describing the device's performance against such criteria. The document is a 510(k) summary for the Medicsight Colon CAR 1.2, focusing on its substantial equivalence to a predicate device rather than presenting detailed performance statistics or an independent study to prove acceptance criteria.

However, based on the information provided, we can infer some aspects and highlight what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Size for Test Set and Data Provenance:

• Sample Size: Not explicitly stated. The document mentions "Test data are provided to validate the performance of the system," but does not specify the size of this test set.
• Data Provenance: Not explicitly stated. The document mentions "Medicsight PLC." is located in "London W1J 5AT UK," but there is no information about the origin of the test data (e.g., country of origin, retrospective or prospective).

3. Number of Experts and Qualifications for Ground Truth:

• Not explicitly stated. The document refers to "radiologists and other clinicians" as intended users, but there is no information about experts used to establish ground truth for any test sets.

4. Adjudication Method for Test Set:

• Not explicitly stated. No details are provided regarding how ground truth was established or if any adjudication process was used.

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

• Not explicitly stated. The document does not describe an MRMC study comparing human readers with and without AI assistance, nor does it provide an effect size. The device is described as "a software tool designed to assist radiologists," implying human-in-the-loop, but no comparative effectiveness study is presented.

6. Standalone Performance Study:

• Not explicitly stated. While the device is "PC-based, stand-alone, non-invasive, image analysis software," the document does not present a standalone performance study of the algorithm without human-in-the-loop. The "Polyp Enhanced Viewing Filter (PEV)" is described as highlighting "potential polyp candidates for further interrogation by the reporting radiologist," indicating an assisted workflow rather than a standalone diagnostic output.

7. Type of Ground Truth Used:

• Not explicitly stated. Given the context of colon polyp detection, common ground truths include expert consensus (e.g., colonoscopy findings, pathology reports), but the document does not specify.

8. Sample Size for Training Set:

• Not explicitly stated. There is no information provided about a training set or its size.

9. How Ground Truth for Training Set was Established:

• Not explicitly stated. Since no training set is mentioned, there is no information on how its ground truth might have been established.

Summary of Missing Information:

The provided 510(k) summary primarily focuses on demonstrating substantial equivalence to a predicate device, which often relies on functional comparisons and hazard analysis rather than detailed performance studies with explicit acceptance criteria and corresponding results. The document lacks the specific details requested regarding test set size, data provenance, expert qualifications, ground truth establishment methods, and detailed performance metrics that would be found in a comprehensive clinical or technical study report.

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syngo Colonography - Software Package with Extended Functionality is a self-contained image analysis software package for evaluating CT volume data sets. This software package can also be utilized for evaluating suitable MR volume datasets. Combining enhanced commercially available digital image processing tools with an optimized workflow and reporting tools, the software is designed to support the physician in confirming the presence or absence of physician identified colon lesions (e.g. polyps) in addition to evaluation, documentation, and follow-up of any such lesions using standard or low-dose spiral CT or MR scanning.

The syngo Colonography - Software Package with Extended Functionality contains modifications for CT data only which support the user with a special workflow based on automated segmentation for the visual identification of possible lesions (Polyp Enhanced Viewing), Furthermore workflow improvements, like "segmentation in global view". "automatic size measurement", "synchronization of prone and supine" and "unseen areas" are included in this software package.

This visualization tool allows for volumetric analysis of colonic lesion size over time. helping the physician to assess the changes in its growth. It is also designed to help the physician to classify conspicuous regions of tissue unambiguously having determined their size, dimensions, shape, and position.

The syngo Colonography - Software Package with Extended Functionality is limited to CT volume data sets.

This pre-market notification covers Siemens syngo Colonography - Software Package with Extended Functionality. It is based on Siemens syngo software platform.

syngo Colonography is a self-contained image analysis software package for evaluating CT volume data sets. This software package can also be utilized for evaluating suitable MR volume datasets. Combining enhanced commercially available digital image processing tools with an optimized workflow and reporting tools, the software is designed to support the physician in confirming the presence or absence of physician identified colon lesions (e.g. polyps) in addition to evaluation, documentation, and follow-up of any such lesions using standard or lowdose spiral CT or MR scanning.

The syngo colonography Software Package with Extended Functionality contains modifications for CT data only which support the user with a special workflow based on automated segmentation for the visual identification of possible lesions (Polyp Enhanced Viewing). Furthermore workflow improvements, like "segmentation in global view", "automatic size measurement", "synchronization of prone and supine" and "unseen areas" are included in this software package.

This visualization tool allows for volumetric analysis of colonic lesion size over time, helping the physician to assess the changes in its growth. It is also designed to help the physician to classify conspicuous regions of tissue unambiguously having determined their size, dimensions, shape, and position.

The provided document describes the "syngo Colonography - Software Package with Extended Functionality" (K042605). However, it does not contain any information regarding acceptance criteria, performance studies, sample sizes, ground truth establishment, or expert qualifications.

The document is a 510(k) summary and an FDA clearance letter, which primarily focuses on:

• General Information: Device name, classification, manufacturer, contact.
• Substantial Equivalence: Comparing the device to a predicate device (syngo Colonography Software Package, K030982) and stating that it does not introduce new safety risks.
• Device Description and Intended Use: Explaining what the software does (image analysis for evaluating CT/MR volume data, supporting physicians in identifying colon lesions, volumetric analysis, etc.) and new features (Polyp Enhanced Viewing, segmentation in global view, automatic size measurement, synchronization of prone and supine, unseen areas).
• FDA Clearance: The official letter from the FDA confirming clearance.

Therefore, I cannot provide a table of acceptance criteria and reported device performance or answer most of the requested questions because the necessary information is not present in the provided text.

Based on the provided text, I can only state the following:

• Study Information: The document states that "Risk management is ensured via a hazard analysis, which is used to identify potential hazards. These potential hazards are controlled via software development, verification and validation testing." This indicates that some form of internal testing was conducted for safety and effectiveness, but no details of these tests (e.g., specific acceptance criteria, performance metrics, or study design) are provided.
• Substantial Equivalence: The primary "proof" of the device meeting its intended purpose and safety is its substantial equivalence to a previously cleared predicate device (syngo Colonography Software Package, K030982). The assumption is that if the predicate device met certain criteria, and the new device is substantially equivalent with new features, those new features also meet those implicit criteria through validation testing.

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