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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 trained staff as an aid in diagnosis, treatment and radiation therapy planning as well as for diagnostic and therapeutic interventions.

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.

The subject device SOMATOM CT Scanner Systems with SOMARIS/7 syngo CT VB30 are Computed Tomography X-ray Systems which feature one (single 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 VB30 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 VB30, is a commandbased program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

The document primarily focuses on functional verification and validation testing rather than explicit, quantifiable acceptance criteria with corresponding performance metrics for each feature in a tabular format. Instead, it describes the objective of each test and then states that the results were found to be acceptable or passed.

However, we can extract the objectives and the documented outcomes for features where some quantifiable or descriptive performance is mentioned:

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

• FAST Bolus: The test describes using a "real contrast enhancement curve" determined by measurements with a dynamic scan mode. The subsequent supporting peer-reviewed studies provide more detail:

  • Korporaal et al. (2015): Not explicitly stated, but implies a cohort undergoing bolus tracking.
  • Hinzpeter et al. (2019): 108 patients received patient-specific trigger delay (subject), 108 patients received fixed trigger delay (reference). Prospective CT angiography scans of the aorta.
  • Gutjahr et al. (2019): 3 groups, 20, 20, and 40 patients respectively.
  • Yu et al. (2021): 104 patients (52 per group, implied) in abdominal multiphase CT, comparing individualized vs. fixed post-trigger delay.
  • Yuan et al. (2023): 204 consecutive participants randomly divided into two groups (102 patients each). A prospective study in coronary CT angiography (CCTA).
  • Schwartz et al. (2018): Not explicitly stated, but implied patient-specific data.
  • Data Provenance: The supporting studies imply a mix of retrospective analysis (e.g., Korporaal et al. simulating retrospectively differences) and prospective studies based on the descriptions provided. The locations of these studies are not explicitly mentioned in the excerpt, but given Siemens' global presence, it's likely multi-national.

• FAST 3D Camera, FAST Isocentering, FAST Range, FAST Direction, FAST Planning, Tin Filtration: For these features, the testing is described as "bench testing" using phantoms and internal validation. "Patient data" is mentioned for FAST Planning but without specific numbers.

  • Sample Size: Not specified for these internal bench tests; often involves phantom studies rather than patient-level data for performance metrics. For FAST Planning, it refers to "patient data" for validation, but the sample size is not indicated.
  • Data Provenance: Implied internal testing, likely at Siemens R&D facilities. No external patient data provenance details are given.

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

• For FAST Bolus, the "ground truth" for the internal bench test was defined as an "ideal post bolus delay" determined by measurements with a dynamic scan mode. This suggests an objective, data-driven approach rather than expert consensus on individual cases for the initial ground truth. However, the supporting studies mention:
  • Hinzpeter et al. (2019): Mentions subjective image quality and CNR, which would typically involve expert readers, but the number and qualifications are not provided.
  • Yuan et al. (2023): Mentions "Both readers rated better subjective image quality." suggesting at least two readers, but their qualifications are not provided.
• For other features (FAST 3D Camera, FAST Planning, etc.), the ground truth seems to be established through objective measurement against predefined targets (e.g., "calculated by FAST Planning algorithm that are correct and can be applied without change"). No specific expert involvement for ground truth establishment for these features is detailed.

4. Adjudication Method for the Test Set

• The document does not describe a formal adjudication method (e.g., 2+1, 3+1) for the establishment of ground truth or for reader studies. Where multiple readers are mentioned (e.g., Yuan et al. for FAST Bolus), it only states their findings without detailing an adjudication process. This suggests either independent readings or consensus where needed, but not a formal adjudication protocol.

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

• Yes, implicitly for FAST Bolus: The supporting publications function as comparative effectiveness studies where human assessment (e.g., subjective image quality, diagnostic confidence) is evaluated with or without the aid of the FAST Bolus prototype.
  • Hinzpeter et al. (2019): "higher overall and more uniform attenuation in the individualized cohort compared to the fixed cohort. No difference between the cohorts for image noise was found, but a higher contrast-to-noise ratio (CNR) and higher subjective image quality in the individualized cohort compared to the fixed cohort." This indicates improvement with the AI-assisted timing.
  • Yu et al. (2021): "In the arterial phase, the images of group A with the individualized post-trigger delay provided higher attenuation for all organs... Furthermore, the contrast-to-noise ratio (CNR) of liver, pancreas and portal vein were significantly higher in the group with the individualized scan timing compared to the fixed scan delay. The overall subjective image quality and diagnostic confidence between the two groups were similar." This indicates improved quantitative metrics, with subjective similar.
  • Yuan et al. (2023): "Both readers rated better subjective image quality for Group B with the individualized scan timing. Also, the mean vessel enhancement was significantly higher in Group B in all coronary vessels. After adjusting for the patient variation, the FAST Bolus prototype was associated with an average of 33.5 HU higher enhancement compared to the fixed PTD." This provides a direct effect size for enhancement.
• For the other features, the description is focused on the device's inherent performance (e.g., accuracy of landmark detection, successful implementation) rather than human reader improvements. So, no MRMC study for those.

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

• Yes, for multiple features. The "Bench Testing" descriptions primarily evaluate the algorithm's performance in a standalone manner against a defined ground truth or objective:
  • FAST Bolus: "the post bolus delay as calculated by FAST Bolus to an ideal post bolus delay... was calculated. The objectives of the test were to investigate the deviation from the post bolus delay as determined by FAST Bolus to an ideal/ground truth delay..." This is standalone.
  • FAST 3D Camera, FAST Isocentering, FAST Range, FAST Direction: The tests "demonstrate that the FAST 3D Camera feature... achieves comparable or more accurate results," "lateral isocenter accuracy... comparable," "robustness of the groin landmark is improved," "comparable accuracy of the pose detection." These are assessments of the algorithm's direct performance.
  • FAST Planning: "assess the fraction (percentage) of ranges calculated by the FAST Planning algorithm that are correct and can be applied without change." This is a direct measurement of the algorithm's output quality.
  • Tin Filtration: Verifies "successful implementation" and investigates "improved contrast-to-noise ratio (CNR) in spectral results." This is standalone performance of the image reconstruction/processing.

7. The Type of Ground Truth Used

• Objective/Measured Data:
  • FAST Bolus: "ideal post bolus delay" determined by "measurements with a dynamic scan mode" and "averaged dynamic scans."
  • FAST 3D Camera, FAST Isocentering, FAST Range, FAST Direction: Implied ground truth based on objective measurements of spatial accuracy relative to predefined targets or phantoms.
  • FAST Planning: "correct" ranges are the ground truth, implying comparison to a predefined standard or ideal plan.
  • Tin Filtration: Objective image quality criteria and spectral property measurements are used as ground truth indicators.
• Expert Consensus/Subjective Assessment (as secondary metric in supporting studies): Some of the supporting publications for FAST Bolus also incorporate subjective image quality ratings by human readers, which would likely involve some form of expert consensus or individual expert assessment.

8. The Sample Size for the Training Set

• The document does not provide information on the sample size used for the training set for any of the AI/algorithm features. This information is typically proprietary and not usually disclosed in a 510(k) summary unless specifically requested or deemed critical for demonstrating substantial equivalence.

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

• The document does not provide information on how the ground truth for the training set was established. Given the nature of these features (automated bolus timing, patient positioning, scan range planning), the training data would likely involve large datasets of CT scans annotated with physiological events, anatomical landmarks, and optimal scan parameters. These annotations would typically be established by highly qualified medical professionals (e.g., radiologists, technologists) or through automated processes validated against gold standards. However, the specific methodology is not detailed in this excerpt.

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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.

The SOMATOM Edge Plus systems are multi-slice X-Ray Computed Tomography scanners.

The device produces cross-sectional images of the body by computer reconstruction of X-Ray transmission data from either the same axial plane taken at different angles or spiral planes taken at different angles.

These systems are intended to be utilized by appropriately trained health care professionals. Typical uses of the systems include neurology, oncology and cardiology in standard practice as well as in trauma or emergency situations. The images produced by the system can also be used by the physician to aid in radiotherapy treatment planning and simulation, as well as during interventional radiology procedures.

Each SOMATOM Edge Plus consists of a 78 cm bore size gantry (including mechanical and electrical components), a patient handling system (PHS) that moves the patient into and out of the gantry during the scans (various beds can be paired with this system), a Power Distribution Cabinet (PDC) and an Image Management System (comprised of various computers).

The SOMATOM Edge Plus software is a command based program used for patient management, data management, scan control, image reconstruction and image archival and evaluation. All images conform to DICOM imaging format requirements.

The SOMATOM Edge Plus is based on the commercially available SOMATOM Definition Edge system (K152036). The software (VB10) has been updated to incorporate additional features as well as provide updates for workflow and anomaly corrections as compared to the predicate device. Key changes compared to the primary predicate include:

• Updated X-Ray Tube
• Tin Filter Technology
• Touch Panel Controls
• Improvements to patient positioning
• Updated computers due to obsolescence
• Updates to software to add improved features and functionality
• Inclusion of the features available on other SOMATOM CT systems such as SOMATOM Drive (K161196) and SOMATOM Confidence (K162302)
• HD FoV Improvements
• CARE and FAST feature improvements
• kV and Filter Independent CaScore

The SOMATOM Edge Plus consists of the following key specifications:

The provided text does not contain the details of a study proving the device meets acceptance criteria related to AI/algorithm performance, nor does it list specific acceptance criteria for such a study.

The document is a 510(k) Premarket Notification for a CT system (SOMATOM Edge Plus). It focuses on demonstrating substantial equivalence to previously marketed CT systems based on hardware changes, software updates for workflow and anomaly corrections, and adherence to established medical device standards (e.g., IEC, NEMA for electrical, mechanical, and radiation safety, and basic software development).

Instead of an AI/algorithm performance study, the document describes:

• Indications for Use: The system generates and processes cross-sectional images for aid in diagnosis, treatment preparation, and radiation therapy planning, including low-dose lung cancer screening.
• Performance Testing/Safety and Effectiveness: This section primarily discusses compliance with safety standards (IEC, FDA regulations for radiation, electrical, mechanical hazards), risk management (ISO 14971), and cybersecurity.
• Verification, Validation, and Performance testing: This refers to standard engineering validation, ensuring the device functions as intended and performance is comparable to predicate devices in terms of image acquisition, reconstruction, and basic system operation, not AI-driven diagnostic performance metrics.

Therefore, I cannot populate the table or answer the specific questions related to acceptance criteria and a study proving device meeting those criteria in the context of AI/algorithm performance, multi-reader multi-case studies, or standalone algorithm performance, as these topics are not addressed in the provided text.

The text generally states: "Performance testing met the predetermined acceptance values," and "The successful verification and validation testing demonstrates that the SOMATOM Edge Plus functions as intended and that performance is comparable to the predicate devices." However, these "acceptance values" are not detailed in terms of specific diagnostic performance metrics (e.g., sensitivity, specificity, AUC) for an AI or algorithm.

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