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syngo. CT Clinical Extensions is intended to provide advanced visualization tools to prepare and process medical images for diagnostic purpose. The software package is designed to support technicians and physicians in qualitative and quantitative measurements and in the analysis of clinical data that was acquired and reconstructed by Computed Tomography (CT) scanners, and possibly other medical imaging modalities (e.g. MR scanners).

An interface shall enable the connection between the syngo.CT Clinical Extensions software package and the interconnected CT Scanner system.

Result images created with the syngo. CT Clinical Extensions software package can be used to assist trained technicians or physicians in diagnosis.

syngo.CT Clinical Extensions is a software bundle that offers tools to support special clinical evaluations. syngo.CT Clinical Extensions can be used to create advanced visualizations and measurements on clinical data that was acquired and reconstructed by Computed Tomography (CT) scanners or other medical imaging modalities (e.g. MR scanners). syngo.CT Clinical Extensions is an extension of the previously cleared primary predicate device post-processing application software syngo.CT Extended Functionality and includes the following modifications in comparison to the primary predicate device:

• 1. New Marketing Name: syngo.CT Clinical Extensions
• 2. Modified Indications for Use Statement
• 3. Support of software version SOMARIS/8 VB30 which supports the following functionality:
  • a. Vascular Tool modification:
    • i. Modified Coronary Vessel Tracing Support
    • ii. Heart and Coronary Tree Isolation Tools
    • iii. Support of MR data
    • iv. Support of additional workflow improvement visualization tools
  • b. Oncology Tool modification:
    • i. Support of Mean Diameter Value
    • ii. Support of Lung Lesion Segmentation Tool
  • ﻥ Support of Dual Energy Tool
  • Support of Endoscopic View Tool ರ
  • Editing of Pre-generated Results e.

Depending on the clinical question, the user can select functionality which supports the explicit clinical fields as listed below. The syngo.CT Clinical Extensions software package is designed to operate on syngo-compatible post-processing platforms, software version SOMARIS/8 VB30 or later.

The provided text is a 510(k) summary for the syngo.CT Clinical Extensions device, which is a software bundle for advanced visualization and measurement of medical images. Based on the document, here's a breakdown of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a specific table of quantitative acceptance criteria for device performance. Instead, it states that "The testing supports that all software specifications have met the acceptance criteria" and "The result of all conducted testing was found acceptable to support the claim of substantial equivalence."

The device's performance is reported in a comparative manner, asserting substantial equivalence to predicate devices based on:

• Functionality: The subject device offers an extension of previously cleared post-processing application software, including modifications to the Vascular Tool and Oncology Tool, and support for additional functionalities like Dual Energy Tool and Endoscopic View Tool.
• Technological Characteristics: The subject device uses the same or similar technological characteristics as the predicate devices, with differences noted as not raising "different questions of safety and effectiveness."
• Safety and Effectiveness: "Test results show that the subject device, syngo.CT Clinical Extensions are comparable to the predicate devices in terms of technological characteristics and safety and effectiveness."

Summary of Reported Performance (Qualitative, based on stated substantial equivalence):

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

The document does not specify the sample size (number of images or cases) used for the test set.

Data provenance is also not explicitly stated in terms of country of origin or whether it was retrospective or prospective. The statement "The subject device is also tested using the same methods as used for the predicate devices" implies that similar types of data as used for predicate devices (likely retrospective clinical images) were utilized for testing.

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

The document does not mention the number of experts used or their specific qualifications for establishing ground truth for the test set. It describes the device as supporting "trained technicians or physicians in diagnosis," implying that the expected users are medical professionals, but it doesn't detail how the ground truth for testing was established. Given the nature of a 510(k) for a software update/bundle, it's possible that the "ground truth" was established by comparing the software's output with existing, clinically accepted measurements or visualizations, rather than through independent expert consensus on raw images.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method (e.g., 2+1, 3+1) for the test set.

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

The document does not mention an MRMC comparative effectiveness study comparing human readers with AI vs. without AI assistance. The submission focuses on the software's performance against its own specifications and its equivalence to predicate devices, rather than a human-in-the-loop performance study.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) was Done

The testing described appears to be primarily focused on the standalone performance of the algorithm/software functionalities. "Non-clinical tests (integration and functional) were conducted... Performance tests were conducted to test the functionality... The results of these tests demonstrate that the subject device performs as intended." This implies testing the software's ability to process images, perform measurements, and generate visualizations accurately, which is a standalone evaluation of its capabilities.

7. The Type of Ground Truth Used

The document does not explicitly state the type of ground truth used. However, given the device's function (advanced visualization and quantitative measurements), the ground truth for the "functional" and "performance" tests would likely involve:

• Reference Measurements: Comparing the software's quantitative measurements (e.g., vessel diameter, lesion mean diameter, bone mineral content) against established or known values, or measurements performed by validated methods/tools.
• Visual Fidelity: Assessing the accuracy and clinical utility of the advanced visualizations in comparison to a reference standard.
• Software Specifications: Meeting predefined software specifications for each tool's output and behavior.

It is unlikely to be pathology or outcomes data, as this device primarily focuses on image processing and measurement for diagnosis assistance rather than direct disease detection or prognosis.

8. The Sample Size for the Training Set

The document does not mention a training set or its sample size. This is typical for a 510(k) for a software platform that bundles existing functionalities and adds incremental updates. While the underlying algorithms within these functionalities might have been developed using training data, this specific 510(k) submission does not detail the training set for the syngo.CT Clinical Extensions bundle itself. The changes described (e.g., "Semi-automatic vessel tracing tool that allows tracing with less user-interaction") suggest algorithmic improvements, which would benefit from training data, but the specifics are not provided in this summary.

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

Since a training set is not mentioned, the method for establishing its ground truth is also not described.

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The syngo.CT Lung CAD device is a computer-aided detection (CAD) tool designed to assist radiologists in the detection of solid pulmonary nodules during review of multi-detector computed tomography (MDCT) examinations of the chest. The software is an adjunctive tool to alert the radiologist to regions of interest (ROI) that may have been initially overlooked. The syngo. CT Lung CAD device is intended to be used as a second reader after the radiologist has completed his/her initial read.

syngo.CT Lung CAD is a medical device that is designed to perform CAD processing in thoracic CT examinations for the detection of solid pulmonary nodules ≥ 3 mm in size. The device processes images acquired with Siemens multi-detector CT scanners with 4 or more detector rows.

The syngo.CT Lung CAD device supports the full range of nodule locations (central, peripheral) and contours (round, irregular). The detection performance of the syngo.CT Lung CAD device is optimized for nodules between 3 mm and 10 mm in size. Additionally, the syngo.CT Lung CAD device can be used in scans with or without contrast enhancement.

The device receives images via an input data interface, performs CAD processing and provides locations of suspected nodules as an output. Specific visualizations, such as the syngo PET&CT Oncology application (K093621) or equivalent Siemens products, should be used (but are not part of this clearance) to display the CAD marks. The syngo.CT Lung CAD device is intended to be used as a second reader only after the initial read is completed.

The provided document, K143196 for syngo.CT Lung CAD, largely focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study proving performance against explicit acceptance criteria with specific metrics. The document states that "Non-clinical tests were conducted... The modifications described in this Premarket Notification were supported with verification and validation testing." However, it does not explicitly outline a table of acceptance criteria nor the corresponding reported device performance.

Nonetheless, based on the information provided, we can infer some aspects of the performance and the nature of the testing:

1. Table of Acceptance Criteria and the Reported Device Performance

The document does not provide a quantitative table of acceptance criteria or reported device performance metrics like sensitivity, specificity, or false positive rates. It generally states that "The results of these tests support the substantial equivalence of this device" and that "Testing, including standalone performance testing, were conducted to assess the new syngo.CT Lung CAD device and compare it to the predicate device with respect to false positives, sensitivity, and the dismissibility of false positives." This implies that these metrics were assessed and found acceptable for substantial equivalence, but the actual numbers and predefined thresholds are not disclosed.

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

The document does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). It simply refers to "non-clinical tests" and "testing."

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

This information is not provided in the document.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

The document mentions that the device is intended to be used as a "second reader after the radiologist has completed his/her initial read." It also states, "Testing, including standalone performance testing, were conducted to assess the new syngo.CT Lung CAD device and compare it to the predicate device with respect to false positives, sensitivity, and the dismissibility of false positives." However, it does not explicitly describe an MRMC comparative effectiveness study that quantitatively assesses how much human readers improve with AI assistance versus without. The focus seems to be on the performance of the CAD system itself and its equivalence to a prior version.

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

Yes, a standalone performance test was done. The document explicitly states: "Testing, including standalone performance testing, were conducted to assess the new syngo.CT Lung CAD device and compare it to the predicate device with respect to false positives, sensitivity, and the dismissibility of false positives." This indicates that the algorithm's performance without direct human intervention was evaluated.

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 context of detecting "solid pulmonary nodules," it is highly likely that the ground truth would have been established by a consensus of expert radiologists or possibly through follow-up imaging or pathology reports where available, but this is not explicitly detailed.

8. The Sample Size for the Training Set

The document does not provide any information regarding the sample size used for the training set.

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

The document does not provide any information on how the ground truth for the training set was established.

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