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510(k) Data Aggregation
(81 days)
Biograph Vision, Biograph mCT Family of PET/CTs
The Siemens Biograph Vision and Biograph mCT PET/CT systems are combined X-Ray Computed Tomography (CT) and Position Emission Tomography (PET) scanners that provide registration 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 and Biograph mCT PET/CT systems are combined multi-slice X-Ray Computed Tomography and Positron Emission Tomography scanners. These systems are designed for whole body oncology, neurology and cardiology examinations. The Biograph Vision and Biograph mCT systems provide 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 and Biograph mCT 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 software for the Biograph Vision and Biograph mCT systems which are the subject of this application is substantially equivalent to the commercially available Biograph Vision and Biograph mCT software. Modifications include, corrections to software anomalies and addition of new software features, including:
- OncoFreeze AI (Data Driven Gating)
- FlowMotion Al (PET FAST Planning)
- FAST PET Workflow
- Updates to HD FoV
- . Updates to PET DICOM dose Report
- Whole Body Scatter Correction (for Biograph Vision)
Additionally, minor modifications have been made to the computers due to obsolescence issue. These changes do not affect system performance characteristics and have no impact on safety or effectiveness.
The provided text describes performance testing for the Biograph Vision PET/CT and Biograph mCT PET/CT systems, which are combined X-Ray Computed Tomography (CT) and Positron Emission Tomography (PET) scanners. The testing was conducted in accordance with NEMA NU2-2018 for the PET subsystem.
Here's an analysis of the acceptance criteria and study information:
1. Table of Acceptance Criteria and Reported Device Performance
For Biograph Vision (6-ring and 8-ring configurations):
| Performance Criteria | Acceptance Criteria (6-ring) | Reported Performance (6-ring) | Acceptance Criteria (8-ring) | Reported Performance (8-ring) |
|---|---|---|---|---|
| Resolution - Full Size | ||||
| Transverse Resolution FWHM @ 1 cm | ≤ 4.0 mm | Pass | ≤ 4.0 mm | Pass |
| Transverse Resolution FWHM @ 10 cm | ≤ 4.8 mm | Pass | ≤ 4.8 mm | Pass |
| Transverse Resolution FWHM @ 20 cm | ≤ 5.2 mm | Pass | ≤ 5.2 mm | Pass |
| Axial Resolution FWHM @ 1 cm | ≤ 4.3 mm | Pass | ≤ 4.3 mm | Pass |
| Axial Resolution FWHM @ 10 cm | ≤ 5.4 mm | Pass | ≤ 5.4 mm | Pass |
| Axial Resolution FWHM @ 20 cm | ≤ 5.4 mm | Pass | ≤ 5.4 mm | Pass |
| Count Rate / Scatter / Sensitivity | ||||
| Sensitivity @435 keV LLD | ≥ 8.0 cps/kBq | Pass | ≥ 15.0 cps/kBq | Pass |
| Count Rate peak NECR | ≥ 140 kcps @ ≤ 32 kBq/cc | Pass | ≥ 250 kcps @ ≤ 32 kBq/cc | Pass |
| Count Rate peak trues | ≥600 kcps @ ≤ 56 kBq/cc | Pass | ≥1100 kcps @ ≤ 56 kBq/cc | Pass |
| Scatter Fraction at peak NECR | ≤ 43% | Pass | ≤ 43% | Pass |
| Mean bias (%) at peak NEC | ≤ +/- 6% | Pass | ≤ +/- 6% | Pass |
| Image Quality (4 to 1) - (% Contrast / Background Variability) | ||||
| 10mm sphere | ≥ 55% / ≤ 10% | Pass | ≥ 55% / ≤ 10% | Pass |
| 13mm sphere | ≥ 60% / ≤ 9% | Pass | ≥ 60% / ≤ 9% | Pass |
| 17mm sphere | ≥ 65% / ≤ 8% | Pass | ≥ 65% / ≤ 8% | Pass |
| 22mm sphere | ≥ 70% / ≤ 7% | Pass | ≥ 70% / ≤ 7% | Pass |
| 28mm sphere | ≥ 75% / ≤ 6% | Pass | ≥ 75% / ≤ 6% | Pass |
| 37mm sphere | ≥ 80% / ≤ 5% | Pass | ≥ 80% / ≤ 5% | Pass |
| Co-Registration Accuracy | ||||
| Max Error | ≤ 5 mm | Pass | ≤ 5 mm | Pass |
For Biograph mCT (3-ring and 4-ring configurations):
| Performance Criteria | Acceptance Criteria (3-ring) | Reported Performance (3-ring) | Acceptance Criteria (4-ring) | Reported Performance (4-ring) |
|---|---|---|---|---|
| Resolution - Full Size | ||||
| Transverse Resolution FWHM @ 1 cm | ≤ 4.7 mm | Pass | ≤ 4.0 mm | Pass |
| Transverse Resolution FWHM @ 10 cm | ≤ 5.4 mm | Pass | ≤ 4.8 mm | Pass |
| Transverse Resolution FWHM @ 20 cm | ≤ 6.3 mm | Pass | ≤ 5.2 mm | Pass |
| Axial Resolution FWHM @ 1 cm | ≤ 4.9 mm | Pass | ≤ 4.3 mm | Pass |
| Axial Resolution FWHM @ 10 cm | ≤ 6.5 mm | Pass | ≤ 5.4 mm | Pass |
| Axial Resolution FWHM @ 20 cm | ≤ 8.8 mm | Pass | ≤ 5.4 mm | Pass |
| Count Rate / Scatter / Sensitivity | ||||
| Sensitivity @435 keV LLD | ≥ 5.0 cps/kBq | Pass | ≥ 9.4 cps/kBq | Pass |
| Count Rate peak NECR | ≥ 95 kcps @ ≤ 30 kBq/cc | Pass | ≥ 165 kcps @ ≤ 28 kBq/cc | Pass |
| Count Rate peak trues | ≥350 kcps @ ≤ 46 kBq/cc | Pass | ≥575 kcps @ ≤ 40 kBq/cc | Pass |
| Scatter Fraction at peak NECR | ≤ 40% | Pass | ≤ 40% | Pass |
| Mean bias (%) at peak NEC | ≤ +/- 6% | Pass | ≤ +/- 6% | Pass |
| Image Quality (4 to 1) - (% Contrast / Background Variability) | ||||
| 10mm sphere | ≥ 10% / ≤ 10% | Pass | ≥ 10% / ≤ 10% | Pass |
| 13mm sphere | ≥ 25% / ≤ 10% | Pass | ≥ 25% / ≤ 10% | Pass |
| 17mm sphere | ≥ 40% / ≤ 10% | Pass | ≥ 40% / ≤ 10% | Pass |
| 22mm sphere | ≥ 55% / ≤ 10% | Pass | ≥ 55% / ≤ 10% | Pass |
| 28mm sphere | ≥ 60% / ≤ 10% | Pass | ≥ 60% / ≤ 10% | Pass |
| 37mm sphere | ≥ 65% / ≤ 10% | Pass | ≥ 65% / ≤ 10% | Pass |
| Co-Registration Accuracy | ||||
| Max Error | ≤ 5 mm | Pass | ≤ 5 mm | Pass |
Additional Features Performance (Acceptance Criteria implicitly met by "Pass" or comparison):
OncoFreeze AI (Data Driven Gating)
| Metric | Anzai-based OncoFreeze | OncoFreeze AI |
|---|---|---|
| ΔSUVmax (relative to static) | +29% ± 22% | +27% ± 22% |
| ΔSUVmean (relative to static) | +27% ± 22% | +26% ± 22% |
| ΔVolume (relative to static) | -34% ± 23% | -31% ± 19% |
The document states: "An evaluation of change in SUVmax, SUVmean and volume measurement has been performed comparing Anzai based OncoFreeze and OncoFreeze AI." The implication is that OncoFreeze AI's performance is comparable and acceptable.
FlowMotion AI (PET FAST Planning)
| Performance Metric | Reported Performance |
|---|---|
| Accuracy in defining bed ranges | 87.1% to 100% |
The document states: "Successful identification of all ranges in a FlowMotion AI configuration ranged from 87.1% to 100%, dependent on the configuration set." This implies the high accuracy is considered acceptable.
Whole Body Scatter Correction (for Biograph Vision)
| Difference from ground truth In simulation study of phantom | Single Bed Scatter Correction | Whole Body Scatter correction |
|---|---|---|
| ROI close to phantom exhibiting high signal | +87% | -2% |
| ROI close to phantom exhibiting low signal | -42% | -3% |
| ROI inside phantom | +0.5% | -0.4% |
The document states: "An evaluation was performed to evaluate ROI's using single bed scatter compared to whole body scatter." This table demonstrates significantly improved accuracy with Whole Body Scatter correction, implying its acceptance.
2. Sample size used for the test set and the data provenance
The document indicates that PET testing was carried out on two different configurations of the Biograph Vision systems (a 6-ring and an 8-ring version) and two configurations of the Biograph mCT (a 3-ring and a 4-ring version). These are physical devices/configurations being tested, not patient data sets. The testing for the core PET performance criteria (Resolution, Count Rate, Image Quality, Co-registration Accuracy) was conducted using NEMA NU2-2018 standards. This standard uses phantoms, not human patient data.
For the AI-powered features:
- OncoFreeze AI (Data Driven Gating): An evaluation was performed comparing OncoFreeze AI to Anzai-based OncoFreeze. The data provenance is not specified, nor is the sample size (number of patients or scans). The data is presented as statistical metrics (mean and standard deviation of percentage change) suggesting a dataset with multiple measurements.
- FlowMotion AI (PET FAST Planning): Testing was done to evaluate accuracy in defining bed ranges. The results are presented as a range of percentages (87.1% to 100%) "dependent on the configuration set." The sample size or data provenance (e.g., retrospective/prospective, country of origin) is not specified.
- Whole Body Scatter Correction: An "evaluation was performed to evaluate ROI's using single bed scatter compared to whole body scatter." This was a simulation study of phantom.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- For the core PET performance criteria (NEMA NU2-2018), ground truth is established through physical measurements of phantoms according to standardized protocols, not expert consensus.
- For the AI-powered features (OncoFreeze AI, FlowMotion AI, Whole Body Scatter Correction), the document does not mention the involvement of experts for establishing ground truth.
- For OncoFreeze AI, the ground truth for comparison seems to be "static" measurements and the "Anzai-based OncoFreeze" system.
- For FlowMotion AI, the "correct" bed ranges are likely determined by system specifications or a reference method, not necessarily human experts.
- For Whole Body Scatter Correction, the "ground truth" was established in a "simulation study of phantom."
4. Adjudication method for the test set
No adjudication method for expert consensus is described because the primary performance testing relies on standardized phantom measurements (NEMA NU2-2018) or comparisons to existing system outputs/simulated phantom ground truth for the AI features.
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
No MRMC comparative effectiveness study is mentioned. The studies described focus on device performance characteristics (resolution, sensitivity, image quality) and the performance of new AI algorithms in terms of measurement accuracy or task completion. There is no information provided about human reader performance with or without AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Yes, the studies focusing on the AI-powered features (OncoFreeze AI, FlowMotion AI, Whole Body Scatter Correction) appear to be standalone algorithm performance evaluations. The metrics provided (ΔSUV, ΔVolume, accuracy of bed range definition, difference from ground truth in scatter correction) are direct outputs of the algorithms, without explicit human-in-the-loop evaluation of these outputs as part of the reported performance metrics.
7. The type of ground truth used
- For core PET performance (NEMA NU2-2018): Phantom measurements/specifications.
- For OncoFreeze AI: Comparative measurements against "static" scans and an "Anzai-based OncoFreeze" system. The "ground truth" here is relative rather than an absolute truth from pathology or long-term outcomes.
- For FlowMotion AI: Implicitly, the system's intended or ideal definition of bed ranges. Not explicitly stated where this "ground truth" originated.
- For Whole Body Scatter Correction: "Ground truth" established in a simulation study of phantom.
8. The sample size for the training set
The document does not specify the sample size for the training set for any of the AI-powered features. It only describes the performance evaluation (test set performance).
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 for any of the AI-powered features.
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