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510(k) Data Aggregation
(27 days)
The Siemens Biograph Vision Quadra systems are combined X-Ray Computed Tomography (CT) and Position Emission Tomography (PET) scanners that provide registration and fusion of high resolution physiologic and anatomic information.
The CT component 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. The PET subsystem images and measures the distribution of PET radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and utilizes the CT for fast attenuation correction maps for PET studies and precise anatomical reference for the fused PET and CT images.
The system maintains independent functionality of the CT and PET devices, allowing for single modality CT and / or PET diagnostic imaging. These systems are intended to be utilized by appropriately trained health care professionals to aid in detecting, localizing, diagnosing, staging of lesions, tumors, disease and organ function for the evaluation of diseases and disorders such as, but not limited to, cardiovascular disease, neurological disorders and cancer. The images produced by the system can also be used by the physician to aid in radiotherapy treatment planning and interventional radiology procedures.
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 Biograph Vision Quadra PET/CT system is a combined multi-slice X-Ray Computed Tomography and Positron Emission Tomography scanner. This system is designed for whole body oncology, neurology and cardiology examinations. The Biograph Vision Quadra system provides registration and fusion of high-resolution metabolic and anatomic information from the two major components of each system (PET and CT). Additional components of the system include a patient handling system and acquisition and processing workstations with associated software.
Biograph Vision Quadra 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 Biograph Vision Quadra is an extended Field of View scanner based on the Biograph Vision 600 Edge scanner. The system incorporates the same CT on the Biograph Vision 600 Edge but incorporates a 106 cm axial PET FoV. The gantry mechanical frame has been updated to support four (4) times the detectors available on the Biograph Vision 600 systems.
The software for the Biograph Vision Quadra PET/CT system, which is the subject of this application, is substantially equivalent to the commercially available Biograph Vision Quadra software (K210262). Modifications have been made to the commercially available Biograph Vision Quadra software to provide for additional features that are already commercially available in the reference device Biograph Vision software (K193248). These include the following features:
- Gated List Mode (HD Chest)
- Simultaneous Mode
- Continuous Bed Motion
- Shuttle Mode PET Acquisition
- . FlowMotion Al (PET FAST Planning)
- FlowMotion MultiParametric PET Al
- OncoFreeze Motion Correction
- OncoFreeze Al
- Quality Guard
Additionally, the following new features have been implemented into the updated Software:
- PET SMART Image Framer (workflow improvement to focus on specific body area) -PET Reconstruction
- . Ultra-High Sensitivity Reconstruction - PET Reconstruction
The provided text describes the Siemens Biograph Vision Quadra PET/CT System (K223547). The acceptance criteria and performance study details are presented in the "Performance Testing / Safety and Effectiveness" section.
Here's a breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance:
The document provides two tables (Table 1 and Table 2) outlining the PET NEMA 2018 Performance Summary for the Biograph Vision Quadra with different Maximum Ring Differences (MRD). Both tables show that the device met all predetermined acceptance values.
Table 1: PET NEMA 2018 Performance Summary Biograph Vision Quadra with a Maximum Ring Difference (MRD) of 85.
Performance Criteria | Reported Device Performance (Results) | Acceptance Criteria |
---|---|---|
Resolution - Full Size | ||
Transverse Resolution FWHM @ 1 cm | Pass | ≤ 4.0 mm |
Transverse Resolution FWHM @ 10 cm | Pass | ≤ 4.8 mm |
Transverse Resolution FWHM @ 20 cm | Pass | ≤ 5.2 mm |
Axial Resolution FWHM @ 1 cm | Pass | ≤ 4.3 mm |
Axial Resolution FWHM @ 10 cm | Pass | ≤ 5.4 mm |
Axial Resolution FWHM @ 20 cm | Pass | ≤ 5.4 mm |
Sensitivity @435 keV LLD | Pass | ≥ 70 cps/kBq |
Count Rate peak NECR | Pass | ≥1200 kcps @ ≤ 36 kBq/cc |
Count Rate peak trues | Pass | ≥3400 kcps @ ≤ 36 kBq/cc |
Scatter Fraction at peak NECR | Pass | ≤43% |
Mean bias (%) at NEC of 1060 kcps | Pass | [-12,12] |
Co-Registration Accuracy | Pass | ≤ 5 mm |
Time of Flight Resolution at 5.3kBq/cc | Pass | ≤249 ps |
10mm sphere (Contrast / Background Variability) | Pass | ≥ 55.0% / ≤ 10.0% |
13mm sphere (Contrast / Background Variability) | Pass | ≥ 60.0% / ≤ 9.0% |
17mm sphere (Contrast / Background Variability) | Pass | ≥ 65.0% / ≤ 8.0% |
22mm sphere (Contrast / Background Variability) | Pass | ≥ 70.0% / ≤ 7.0% |
28mm sphere (Contrast / Background Variability) | Pass | ≥ 75.0% / ≤ 6.0% |
37mm sphere (Contrast / Background Variability) | Pass | ≥ 80.0% / ≤ 5.0% |
Lung Residual Error | Pass | ≤ 5.0% |
Table 2: PET NEMA 2018 Performance Summary Biograph Vision Quadra with a Maximum Ring Difference (MRD) of 322.
Performance Criteria | Reported Device Performance (Results) | Acceptance Criteria |
---|---|---|
Resolution - Full Size | ||
Transverse Resolution FWHM @ 1 cm | Pass | ≤ 4.0 mm |
Transverse Resolution FWHM @ 10 cm | Pass | ≤ 4.8 mm |
Transverse Resolution FWHM @ 20 cm | Pass | ≤ 5.2 mm |
Axial Resolution FWHM @ 1 cm | Pass | ≤ 4.3 mm |
Axial Resolution FWHM @ 10 cm | Pass | ≤ 5.4 mm |
Axial Resolution FWHM @ 20 cm | Pass | ≤ 5.4 mm |
Sensitivity @435 keV LLD | Pass | ≥ 150 cps/kBq |
Count Rate peak NECR | Pass | ≥2200 kcps @ ≤ 36 kBq/cc |
Count Rate peak trues | Pass | ≥6600 kcps @ ≤ 36 kBq/cc |
Scatter Fraction at peak NECR | Pass | ≤43% |
Mean bias (%) at peak NEC | Pass | [-12,12] |
Co-Registration Accuracy | Pass | ≤ 5 mm |
Time of Flight Resolution at 5.3kBq/cc | Pass | ≤249 ps |
10mm sphere (Contrast / Background Variability) | Pass | ≥ 55.0% / ≤ 10.0% |
13mm sphere (Contrast / Background Variability) | Pass | ≥ 60.0% / ≤ 9.0% |
17mm sphere (Contrast / Background Variability) | Pass | ≥ 65.0% / ≤ 8.0% |
22mm sphere (Contrast / Background Variability) | Pass | ≥ 70.0% / ≤ 7.0% |
28mm sphere (Contrast / Background Variability) | Pass | ≥ 75.0% / ≤ 6.0% |
37mm sphere (Contrast / Background Variability) | Pass | ≥ 80.0% / ≤ 5.0% |
Lung Residual Error | Pass | ≤ 5.0% |
2. Sample size used for the test set and the data provenance:
The document states that "PET Testing in accordance with NEMA NU2-2018 was conducted on the Biograph Vision Quadra system." NEMA NU2-2018 is a standard for the performance measurements of PET and PET/CT scanners using standardized phantom measurements. This implies the "test set" consists of phantom-based measurements, not patient data. Therefore, the concept of data provenance (country of origin, retrospective/prospective) and sample size in the traditional clinical trial sense for human data is not directly applicable here. The test is a technical performance validation using a single device and standardized phantom setups.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Since the study is based on NEMA NU2-2018 phantom testing, the ground truth is established by the physical and measurable properties of the phantoms and the precise adherence to the NEMA standard protocols. This does not involve human expert interpretation of images for establishing ground truth, as would be the case for AI-based diagnostic devices.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable. As noted above, the study is a technical performance validation using standardized phantom measurements, not a clinical study requiring human adjudication of findings.
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:
Not applicable. The description focuses on the technical performance of the PET/CT system itself (image resolution, sensitivity, count rates, etc.) rather than the performance of an AI algorithm or its impact on human reader performance. There is no mention of AI assistance in relation to diagnostic accuracy for human readers. While the device does have "AI" features listed (e.g., FlowMotion AI, OncoFreeze AI), the presented performance testing is for the core PET/CT system metrics, not a human-in-the-loop AI effectiveness study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Not applicable in the context of an AI algorithm's standalone performance. The standalone performance presented is for the PET/CT imaging system itself, demonstrating its ability to meet physical imaging quality and sensitivity metrics as specified by the NEMA standard.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
The ground truth for this device performance study is based on physical phantom measurements and the defined parameters of the NEMA NU2-2018 standard. The acceptance criteria are quantitative values derived from these physical measurements.
8. The sample size for the training set:
Not applicable. This is a performance validation study of a PET/CT scanner, not a machine learning model that requires a training set.
9. How the ground truth for the training set was established:
Not applicable. As this is not a study involving a machine learning model, there is no training set or associated ground truth establishment process.
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