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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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