(126 days)
This computed tomography system is intended to generate and process cross-sectional images of patients by computer reconstruction of x-ray transmission data.
The images delivered by the system can be used by a trained physician as an aid in diagnosis. The images delivered by the system can be used by trained staff as an aid in diagnosis, treatment preparation and radiation therapy planning.
This CT system can be used for low dose lung cancer screening in high risk populations *
- As defined by professional medical societies. Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.
Siemens intends to market a new software version, SOMARIS/7 syngo CT VB10 for the following SOMATOM Computed Tomography (CT) Scanner Systems:
Dual Source CT Systems:
- SOMATOM Force
- SOMATOM Drive
- SOMATOM Flash
Single Source CT Systems:
- SOMATOM Definition AS/AS+
- SOMATOM Definition AS Open
- SOMATOM Definition Edge
- SOMATOM Confidence
The subject device SOMATOM CT Scanner Systems with SOMARIS/7 syngo CT VB10 are Computed Tomography X-ray Systems which feature one (single source) or two (dual source) continuously rotating tube-detector system and function according to the fan beam principle. The SOMATOM CT Scanner Systems with Software SOMARIS/7 syngo CT VB10 produces CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens Healthcare and other vendors as an aid in diagnosis, treatment preparation and therapy planning support (including, but not limited to, Brachytherapy, Particle including Proton Therapy, External Beam Radiation Therapy, Surgery). The computer system delivered with the CT scanner is able to run optional post processing applications.
The platform software for the SOMATOM CT Scanner Systems, SOMARIS/7 syngo CT VB10, is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation.
The provided document is a 510(k) premarket notification for Siemens SOMATOM CT Scanner Systems with software version SOMARIS/7 syngo CT VB10. It describes the device, its intended use, and a comparison with predicate devices to establish substantial equivalence.
However, the document does not contain specific details about acceptance criteria, reported device performance metrics (e.g., sensitivity, specificity, AUC), sample sizes for test sets, data provenance, number or qualifications of experts for ground truth, adjudication methods, multi-reader multi-case (MRMC) comparative effectiveness studies, standalone algorithm performance, or specific ground truth types for image-based diagnostic performance assessments.
The "Performance Data" section primarily focuses on non-clinical testing for system functionality, adherence to general medical device standards (ISO, NEMA, IEC), electrical safety, EMC, software verification and validation (including cybersecurity), and phantom tests to assess device and feature performance. It broadly states that "The test results show that all of the software specifications have met the acceptance criteria" and that "Verification and validation testing of the device was found acceptable to support the claim of substantial equivalence," but it does not quantify these acceptance criteria or the specific performance results in a table or detailed study findings.
The indications for use mention "aid in diagnosis, treatment preparation and radiation therapy planning" and "low dose lung cancer screening in high risk populations," which typically would involve performance metrics like sensitivity and specificity. However, these metrics are not presented. The reference to the National Lung Screening Trial (NLST) is for the clinical context of low-dose lung cancer screening, not for the performance validation of the Siemens CT system itself against a ground truth.
Therefore, I cannot populate a table with acceptance criteria and reported device performance, nor can I provide answers to the majority of the requested points, as that information is not present in the provided text.
Based on the provided text, here's what can be extracted regarding the study and performance claims:
1. A table of acceptance criteria and the reported device performance
The document does not provide specific quantitative acceptance criteria (e.g., sensitivity, specificity, reader performance metrics) or corresponding reported device performance values for diagnostic tasks. It broadly states that "all of the software specifications have met the acceptance criteria" and that testing demonstrates "comparability to the predicate devices in terms of technological characteristics and safety and effectiveness."
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
This information is not provided in the document. The testing mentioned is primarily "non-clinical test (integration and functional) including phantom 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)
This information is not provided in the document. The testing described does not involve expert-adjudicated ground truth as it pertains to diagnostic performance on patient data.
4. Adjudication method (e.g. 2+1, 3+1, none) 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, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
This information is not provided in the document. The study described focuses on technical verification and validation, and comparability to predicate devices, not on human-AI comparative effectiveness.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The document mentions "phantom tests" to assess device and feature performance. However, it does not specify performance metrics for a standalone algorithm related to diagnostic accuracy on clinical cases. The device is a CT scanner, and the software updates are for image processing and system functionality, not a standalone diagnostic AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the non-clinical and phantom tests conducted, the ground truth would be the known and controlled parameters of the phantoms and the expected technical performance outputs. There is no mention of ground truth types for clinical diagnostic accuracy related to patient data.
8. The sample size for the training set
Not applicable. The document describes a software update for a medical imaging device (CT scanner) validated through non-clinical testing and phantom studies, not an AI model trained on a dataset.
9. How the ground truth for the training set was established
Not applicable, as this is not an AI model requiring a training set with established ground truth.
§ 892.1750 Computed tomography x-ray system.
(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.