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510(k) Data Aggregation
(28 days)
The Siemens Symbia series is intended for use 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.
SPECT: The SPECT component is intended to detect or image the distribution of radionuclides in the body or organ (physiology), using the following techniques: planar imaging, whole body imaging, and tomographic imaging for isotopes with energies up to 588 keV.
CT: The CT component is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data (anatomy) from either the same axial plane taken at different angles or spiral planes taken at different angles.
SPECT+CT: The SPECT and CT components used together acquire SPECT/CT images. The SPECT images can be corrected for attenuation with the CT images, and can be combined (image registration) to merge the patient's physiological (SPECT) and anatomical (CT) images.
Software: The syngo MI Applications software is a display and analysis package intended to aid the clinician in the assessment and quantification of pathologies in images produced from SPECT, PET, CT, and other imaging modalities.
The following statement applies only to Siemens Symbia Intevo 16, and Symbia Intevo Bold systems:
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 Siemens Symbia systems consist of Single Photon Emission Computed Tomography (SPECT) scanners and integrated hybrid X-Ray Computed Tomography (CT) and SPECT scanners. The SPECT subsystem images and measures the distribution of radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and integrates CT's anatomical detail for precise reference of the location of the metabolic activity. 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 system can be used as an integrated SPECT and CT modality while also enabling independent functionality of SPECT and CT as stand-alone diagnostic imaging devices.
The provided text, K241898, describes a 510(k) premarket notification for Siemens Healthineers' Symbia SPECT and SPECT/CT Systems (Symbia VB23), which are updates to existing devices. The submission indicates that there are no significant changes to the fundamental technology or indications for use compared to the predicate device (Symbia 6.7 (VB22), K200474). Therefore, the provided text does not contain information about a study that proves the device meets specific acceptance criteria based on clinical performance metrics like sensitivity, specificity, or reader improvement.
Instead, the submission focuses on demonstrating substantial equivalence by highlighting that the core performance specifications of the SPECT detector and CT subsystem remain unchanged from the predicate device and that the updated system continues to comply with relevant safety and performance standards.
Here's an analysis of the information available in the document and a clear statement of what is not present regarding device performance studies:
What is present in the document:
- Acceptance Criteria (Implied / Compliance-based) and Reported Performance: The acceptance criteria are primarily implied through adherence to performance standards and regulations.
- CT Subsystem Performance: "Performance testing for the CT subsystem was included in the original premarket notification for the CT subsystems and there have been no changes affecting this testing. Each CT subsystem is tested and passes the Applicable Performance Standards prior to shipment." These standards include various parts of 21 CFR 1020.30, 21 CFR 1020.33, 21 CFR 1040.10, and 21 CFR 1040.11.
- SPECT Detector and Collimator Performance: "Collimator performance testing is conducted according to NEMA NU-1:2018. All Performance testing met the predetermined acceptance values." The "Detector Specifications" (Figure 2) and "Quantitative Accuracy Specifications" (Figure 3) list specific numerical values for intrinsic spatial resolution, energy resolution, flood field uniformity, count rate performance, system spatial resolution, system planar sensitivity, and quantitative error. These serve as the quantitative acceptance criteria for the SPECT component, and the document states: "The quantitative error for all isotopes with the collimators is smaller or equal to 10%, and met the predefined acceptance criteria."
- Software Validation: "Verification and validation of Siemens software is performed in accordance with documented procedures, test plans and specifications." This ensures functionality and quality.
Table of Acceptance Criteria and Reported Device Performance (as inferred from the document):
| Acceptance Criteria Category | Specific Criteria (if stated) | Reported Device Performance (if stated) |
|---|---|---|
| CT Subsystem Compliance | Adherence to 21 CFR 1020.30, 1020.33, 1040.10, 1040.11 | "Each CT subsystem is tested and passes the Applicable Performance Standards prior to shipment." "Performance testing performed on the CT subsystem is conducted in accordance with IEC 60601-2-44 and in accordance with US regulations including 21 CFR 1020.33, Computed Tomography (CT) equipment." (Unchanged from predicate) |
| SPECT Detector Specs (NEMA NU-1:2018) | Intrinsic Spatial Resolution (FWHM in CFOV) ≤3.8 mm | ≤3.8 mm (as per Figure 2) |
| Intrinsic Spatial Resolution (FWHM in UFOV) ≤3.9 mm | ≤3.9 mm (as per Figure 2) | |
| Intrinsic Energy Resolution (FWHM in CFOV) ≤9.9% | ≤9.9% (as per Figure 2) | |
| Intrinsic Flood Field Uniformity (Differential in CFOV) ≤2.5% | ≤2.5% (as per Figure 2) | |
| Multiple Window Spatial Registration ≤0.6 mm | ≤0.6 mm (as per Figure 2) | |
| Maximum Count Rate | 310 kcps (as per Figure 2) | |
| System Planar Sensitivity (LEHR at 10 cm) | 202 cpm/µCi (as per Figure 2) | |
| Quantitative Accuracy (NEMA & High Count Performance) | Quantitative error Tc99m LEHR/LPHR ≤10% | "smaller or equal to 10%, and met the predefined acceptance criteria." (as per Figure 3 and accompanying text) |
| Quantitative error I123 LPHR/MELP ≤10% | "smaller or equal to 10%, and met the predefined acceptance criteria." | |
| Quantitative error In111 MELP ≤10% | "smaller or equal to 10%, and met the predefined acceptance criteria." | |
| Quantitative error Lu177 MELP ≤10% | "smaller or equal to 10%, and met the predefined acceptance criteria." | |
| Quantitative error Lu177 MELP at 310kcps ≤10% | "smaller or equal to 10%, and met the predefined acceptance criteria." | |
| Quantitative error I131 HE ≤10% | "smaller or equal to 10%, and met the predefined acceptance criteria." | |
| General Safety and Effectiveness | Compliance with IEC 60601-1 series, 21 CFR 1020.30, 21 CFR 1020.33 | "Siemens Medical Solutions, USA Inc. adheres to recognized and established industry standards such as IEC 60601-1 series and 21 CFR 1020.30 and 21 CFR 1020.33 to minimize electrical, mechanical and radiation hazards." "Symbia VB23 conforms to applicable FDA recognized and international IEC, ISO and NEMA standards with regards to performance and safety as required by the respective SPECT FDA Guidance Documents." |
| Software Verification & Validation | Functionality meets specifications, quality adherence, risk mitigation implemented, appropriate specifications. | "Verification and validation of Siemens software is performed in accordance with documented procedures, test plans and specifications." "System and System Integration testing (validation) was carried out for all features of the project, and all planned test cases were executed." |
| Cybersecurity | Compliance with FDA Guidance for Medical Device Cybersecurity (Sept 2023) | "The Symbia systems' software has specific cybersecurity controls to prevent unauthorized access, modifications, misuse or denial of use. Additionally, controls are enabled to prevent the unauthorized use of information that is stored, accessed or transferred between the Symbia systems and external devices." |
Information NOT present in the document regarding a clinical performance study (e.g., for an AI/CAD algorithm):
The document does not describe a clinical study in the typical sense of evaluating the device's diagnostic performance (e.g., sensitivity, specificity, accuracy) using patient data with established ground truth. This is because the submission is for an updated version of an imaging system, not an AI/CAD software that provides diagnostic interpretations. The "syngo MI Applications software" is described as a "display and analysis package intended to aid the clinician," not as a tool that provides automated diagnostic outputs.
Therefore, the following points remain unaswered by the provided text:
- Sample size used for the test set and the data provenance: Not applicable as no clinical test set for diagnostic performance evaluation is mentioned. The performance testing described is likely phantom-based or engineering-level.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for the system's physical performance is established by NEMA standards and engineering measurements, not clinical expert consensus.
- Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
- 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, as this device itself is not an AI/CAD system for diagnostic assistance, but an imaging scanner.
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
- The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the performance testing cited (NEMA, CFR standards), the ground truth is established by the known physical properties of phantoms and calibrated measurement devices, ensuring the system outputs accurate measurements as per its specifications.
- The sample size for the training set: Not applicable. This is an imaging system, not a machine learning algorithm requiring a training set in the typical sense. Software "verification and validation" is mentioned to ensure functionality, which refers to standard software development lifecycle testing, not ML model training.
- How the ground truth for the training set was established: Not applicable.
In summary, the provided document details a 510(k) submission for a SPECT/CT imaging system update, focusing on demonstrating substantial equivalence to an existing predicate device and compliance with established performance standards and regulations rather than presenting a clinical performance study of a diagnostic AI algorithm.
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(23 days)
The Siemens Symbia series is intended for use by appropriately trained health care professionals to aid in detecting, localizing, diagnosing, staging and restaging 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.
SPECT: The SPECT component is intended to detect or image the distribution of radionuclides in the body or organ (physiology), using the following techniques; Planar imaging, and tomographic imaging for isotopes with energies up to 588 keV.
CT: The CT component is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data (anatomy) from either the same axial plane taken at different angles or spiral planes take at different angles.
SPECT+CT: The SPECT and CT components used together acquire SPECT/CT images can be corrected for attenuation with the CT images, and can be combined (image registration) to merge the patient's physiological (SPECT) and anatomical (CT) images.
Software: the syngo MI Applications software is a display and analysis package intended to aid the clinician in the assessment and quantification of pathologies in images produced from SPECT, PET, CT and other imaging modalities.
The following statement applies only to Siemens Symbia T16, and Symbia Intevo Bold systems: 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 Siemens Symbia systems consist of Sinqle Photon Emission Computed Tomography (SPECT) scanners and integrated hybrid X-Ray Computed Tomography (CT) and SPECT scanners. The SPECT subsystem images and measures the distribution of radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and integrates CT's anatomical detail for precise reference of the location of the metabolic activity. 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 system can be used as an integrated SPECT and CT modality while also enabling independent functionality of SPECT and CT as standalone diagnostic imaging devices.
The provided text describes a 510(k) premarket notification for the Siemens Symbia 6.7 system, primarily focusing on its substantial equivalence to predicate devices and adherence to performance and safety standards. However, it does not contain information about a study proving the device meets specific acceptance criteria for AI/algorithm performance, nor does it specify detailed acceptance criteria for a new software feature.
The document states:
- Modifications: The Symbia 6.7 includes software updates, specifically enhancements to "xSPECT features" (gastric retention addition, renal processing improvement), addition of SPECT Dose Reporting, and expansion of xSPECT Quantification to support Absolute Quantification of I-131. It also notes an upgrade to Windows 10 and updated third-party applications.
- Performance Testing: It mentions "Performance testing for the CT subsystem was included in the original premarket notification for the CT subsystems and there have been no changes affecting this testing." For the SPECT component, it states: "Collimator performance testing is conducted according to NEMA NU-1:2018. All Performance testing met the predetermined acceptance values." It also shows "Quantitative accuracy specifications" (Figure 3) which demonstrate "accurate quantification in phantoms for all the isotopes and collimators tested" and state that "The quantitative error for all isotopes with the collimators is smaller or equal to 10%, and met the predefined acceptance criteria."
Based on the provided text, I cannot describe acceptance criteria and a study that proves the device meets the acceptance criteria in the context of AI/algorithm performance, because no specific AI/algorithm performance study or associated acceptance criteria are detailed. The document primarily focuses on hardware specifications and general system performance as per NEMA standards, and software updates for existing features, rather than the introduction or validation of a new AI-driven diagnostic algorithm.
Therefore, I am unable to provide the requested information fully, particularly points 2-7, 9, as the document does not describe a study that validates new AI/algorithmic features against specific, measurable acceptance criteria in a clinical or reader study setting.
However, I can extract the general quantitative acceptance criteria mentioned for existing features:
1. Table of acceptance criteria and reported device performance (for quantitative accuracy, as stated):
| Acceptance Criteria (Quantitative Accuracy) | Reported Device Performance (Quantitative Error) |
|---|---|
| Quantitative error for Tc99m LEHR/LPHR ≤10% | ≤10% |
| Quantitative error for I123 LPHR/MELP ≤10% | ≤10% |
| Quantitative error for In111 MELP ≤10% | ≤10% |
| Quantitative error for Lu177 MELP ≤10% | ≤10% |
| Quantitative error for Lu177 MELP at 310kcps ≤10% | ≤10% |
| Quantitative error for I131 HE ≤10% | ≤10% |
Note: These criteria and performance metrics are stated to be "In phantoms for objects with negligible partial volume effect" and "incident count rate" for the Lu177 metric.
2. Sample size used for the test set and the data provenance: Not specified in the provided text for the quantitative accuracy tests beyond "in phantoms." No clinical test sets are described.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified. Ground truth appears to be based on physical phantom measurements, not expert consensus on clinical images for a new AI feature.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not specified.
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 study or AI assistance evaluation is mentioned.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: The "Quantitative accuracy specifications" appear to be standalone phantom tests, but not for a new AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the quantitative accuracy, the ground truth appears to be established through physical phantom measurements and known isotope properties, rather than clinical consensus, pathology, or outcomes data.
8. The sample size for the training set: Not applicable, as no new AI model training is described.
9. How the ground truth for the training set was established: Not applicable, as no new AI model training is described.
In summary, the provided document is a 510(k) summary for a SPECT/CT system, focusing on its substantial equivalence to predicates and adherence to established performance standards (like NEMA NU-1:2018) for its existing imaging capabilities. It does not detail the validation of a new AI/algorithmic feature with the type of acceptance criteria and study design requested in the prompt.
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(86 days)
The Siemens Biograph Horizon PET/CT systems are combined X-Ray Computed Tomography (CT) and Positron 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 and re 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 Horizon 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 Horizon 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 Horizon 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 Horizon systems which is the subject of this application is substantially equivalent to the commercially available Biograph Horizon software. Modifications include, corrections to software anomalies and addition of new software features, including:
- OncoFreeze
- OncoFreeze AI (Data Driven Gating)
- CardioFreeze
- FlowMotion Multi-Parametric PET AI ●
- PET FAST Planning (FlowMotion Al)
- FAST PET Workflow
- QualityGuard
- . Updates to HD FoV
- Updates to PET DICOM dose Report
- Whole Body Scatter Correction
Additionally, minor modifications have been made to the computers due to obsolescence issues and to the controllers of the PHS for cost improvement. These changes do not affect system performance characteristics and have no impact on safety or effectiveness.
The Siemens Biograph Horizon PET/CT system (K193178) underwent performance testing against NEMA NU2-2018 standards for its PET subsystem. The device also had specific evaluations for new software features: OncoFreeze AI, OncoFreeze/CardioFreeze, FlowMotion Multi-Parametric PET AI, FlowMotion AI (PET FAST Planning), QualityGuard, and Whole Body Scatter Correction.
Here's the breakdown of the acceptance criteria and study information:
1. Table of Acceptance Criteria and Reported Device Performance:
| Performance Criteria | Acceptance | Reported Device Performance | Study Performed For |
|---|---|---|---|
| Resolution - Full Size | PET (NEMA NU2-2018) | ||
| Transverse Resolution FWHM @ 1 cm | ≤ 4.7 mm | Pass | PET (NEMA NU2-2018) |
| Transverse Resolution FWHM @ 10 cm | ≤ 5.5 mm | Pass | PET (NEMA NU2-2018) |
| Transverse Resolution FWHM @ 20 cm | ≤ 7.6 mm | Pass | PET (NEMA NU2-2018) |
| Axial Resolution FWHM @ 1 cm | ≤ 5.0 mm | Pass | PET (NEMA NU2-2018) |
| Axial Resolution FWHM @ 10 cm | ≤ 7.0 mm | Pass | PET (NEMA NU2-2018) |
| Axial Resolution FWHM @ 20 cm | ≤ 11.3 mm | Pass | PET (NEMA NU2-2018) |
| Resolution - 256 x 256 | PET (NEMA NU2-2018) | ||
| Transverse Resolution FWHM @ 1 cm | ≤ 7.3 mm | Pass | PET (NEMA NU2-2018) |
| Transverse Resolution FWHM @ 10 cm | ≤ 7.6 mm | Pass | PET (NEMA NU2-2018) |
| Transverse Resolution FWHM @ 20 cm | ≤ 8.9 mm | Pass | PET (NEMA NU2-2018) |
| Axial Resolution FWHM @ 1 cm | ≤ 6.1 mm | Pass | PET (NEMA NU2-2018) |
| Axial Resolution FWHM @ 10 cm | ≤ 7.3 mm | Pass | PET (NEMA NU2-2018) |
| Axial Resolution FWHM @ 20 cm | ≤ 11.9 mm | Pass | PET (NEMA NU2-2018) |
| Count Rate / Scatter / Sensitivity | PET (NEMA NU2-2018) | ||
| Sensitivity @435 keV LLD | ≥ 5.8 cps/kBq (≥ 10.9 cps/kBq for TrueV) | Pass | PET (NEMA NU2-2018) |
| Count Rate peak NECR | ≥ 78 kcps @ ≤ 26 kBq/cc (≥ 135 kcps @ ≤ 26 kBq/cc for TrueV) | Pass | PET (NEMA NU2-2018) |
| Count Rate peak trues | ≥285 kcps @ ≤ 53 kBq/cc (≥ 465 kcps @ ≤ 42 kBq/cc for TrueV) | Pass | PET (NEMA NU2-2018) |
| Scatter Fraction at peak NECR | ≤ 40% | Pass | PET (NEMA NU2-2018) |
| Mean bias (%) at peak NEC | ≤ +/- 6% | Pass | PET (NEMA NU2-2018) |
| Image Quality (4 to 1) - (% Contrast / Background Variability) | PET (NEMA NU2-2018) | ||
| 10mm sphere | ≥ 10% / ≤ 10% | Pass | PET (NEMA NU2-2018) |
| 13mm sphere | ≥ 25% / ≤ 10% | Pass | PET (NEMA NU2-2018) |
| 17mm sphere | ≥ 40% / ≤ 10% | Pass | PET (NEMA NU2-2018) |
| 22mm sphere | ≥ 55% / ≤ 10% | Pass | PET (NEMA NU2-2018) |
| 28mm sphere | ≥ 60% / ≤ 10% | Pass | PET (NEMA NU2-2018) |
| 37mm sphere | ≥ 65% / ≤ 10% | Pass | PET (NEMA NU2-2018) |
| Co-Registration Accuracy | System Performance | ||
| Max Error | ≤ 5 mm | Pass | System Performance |
| OncoFreeze AI (Data Driven Gating) | Change in SUVmax / SUVmean / Volume similar to Anzai-based gating | Pass | Comparison of motion-corrected images |
| ΔSUVmax (relative to static) | N/A (compared to Anzai) | 27% ± 22% (vs. 29% ± 22%) | OncoFreeze AI vs. Anzai-based OncoFreeze |
| ΔSUVmean (relative to static) | N/A (compared to Anzai) | 26% ± 22% (vs. 27% ± 22%) | OncoFreeze AI vs. Anzai-based OncoFreeze |
| ΔVolume (relative to static) | N/A (compared to Anzai) | -31% ± 19% (vs. -34% ± 23%) | OncoFreeze AI vs. Anzai-based OncoFreeze |
| FlowMotion AI (PET FAST Planning) | Successful identification of bed ranges at high percentage | 87.1% to 100% | Evaluation of accuracy in defining bed ranges |
| QualityGuard | Time savings and reduction in staff exposure | Up to 30 mins/day savings, 98% exposure reduction | Evaluation of time and exposure reduction |
| Whole Body Scatter Correction | Reduced difference from ground truth in ROI measurements compared to Single Bed Scatter Correction | Pass | Simulation study of phantom ROIs (ground truth) |
| Representative ROI close to phantom (high signal) | N/A (compared to Single Bed) | -2% (vs. +87%) | Whole Body Scatter Correction vs. Single Bed Scatter Correction |
| Representative ROI close to phantom (low signal) | N/A (compared to Single Bed) | -3% (vs. -42%) | Whole Body Scatter Correction vs. Single Bed Scatter Correction |
| Representative ROI inside phantom | N/A (compared to Single Bed) | -0.4% (vs. +0.5%) | Whole Body Scatter Correction vs. Single Bed Scatter Correction |
2. Sample size used for the test set and the data provenance:
- PET Testing (NEMA NU2-2018): The document implies physical phantom testing which is standard for NEMA NU2-2018. The number of samples (scans or measurements) from the phantom is not explicitly stated, but these tests are typically performed on two different configurations: a 3-ring version and a 4-ring version (TrueV). Data provenance is from physical phantom measurements on the device itself.
- OncoFreeze AI (Data Driven Gating): The document mentions "motion-corrected (OncoFreeze) images comparing Anzai based gating and deviceless gating." It does not specify the number of patient images or specific phantom studies. The provenance isn't explicitly stated as retrospective or prospective, nor a country of origin.
- FlowMotion AI (PET FAST Planning): No specific sample size (i.e., number of cases or scans) is given. The study evaluated "configuration set" effectiveness. The provenance is not explicitly stated.
- Whole Body Scatter Correction: This was a "simulation study of phantom." The sample size (number of ROIs or simulation runs) is not specified. Provenance is simulation data based on a phantom.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- For the NEMA NU2-2018 PET testing, the ground truth for performance metrics (resolution, sensitivity, scatter fraction, image quality) is established by the known physical properties and activity concentrations of the NEMA phantom according to the standard. No human experts are involved in establishing this ground truth.
- For OncoFreeze AI, the "ground truth" for motion correction comparison is implicitly the static image or the Anzai-based gated images acting as a reference for comparison of SUV and Volume changes. No explicit expert involvement for ground truth is mentioned.
- For FlowMotion Multi-Parametric PET AI, the "ground truth" for improved noise characteristics and delineation is a comparison against the Patlak transformation performed during reconstruction without the automatic feature. This implies qualitative assessment, but no expert details are given.
- For FlowMotion AI (PET FAST Planning), the "ground truth" for correctly defined bed ranges would be based on the known or intended bed ranges. No expert involvement in establishing this ground truth is mentioned.
- For QualityGuard, the "ground truth" for time savings and exposure reduction would be direct measurement or comparison to previous workflows. No expert involvement for ground truth is mentioned.
- For Whole Body Scatter Correction, "ground truth" was established by a "simulation study of phantom," implying that the true values for activity in different regions of interest were known from the simulation setup. No human experts are involved in establishing this ground truth; it's inherent to the simulation.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
No adjudication method for expert review of images or data is mentioned for any of the tests described. The tests are primarily technical performance evaluations (NEMA standards, quantitative comparisons, simulation studies) or workflow efficiency observations.
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 multi-reader multi-case (MRMC) comparative effectiveness study evaluating human reader improvement with AI assistance is mentioned in the provided text. The AI features mentioned (OncoFreeze AI, FlowMotion Multi-Parametric PET AI, FlowMotion AI (PET FAST Planning)) are related to image processing and workflow automation rather than direct diagnostic assistance for human readers in a comparative effectiveness setting.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
The device itself is a diagnostic imaging system (PET/CT), not an AI algorithm that provides a diagnostic output to a human. The AI features described within the device, such as OncoFreeze AI and FlowMotion AI, are designed to improve image quality, correct for motion, or automate planning. The performance metrics focus on the output of these features (e.g., changes in SUV, bed range identification accuracy, scatter correction accuracy) as part of the overall imaging system's functionality. Therefore, these features are evaluated in a standalone manner within the machine's operation, without explicit human-in-the-loop performance studies described here.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- NEMA NU2-2018 PET testing: Physical phantom with known activity concentrations and physical dimensions.
- OncoFreeze AI: Comparison to static images and Anzai-based gating, which implicitly serve as a reference or "ground truth" for the motion-corrected measurements.
- FlowMotion Multi-Parametric PET AI: Comparison to non-automated Patlak transformation results.
- FlowMotion AI (PET FAST Planning): Known or intended bed ranges from the configuration setup.
- QualityGuard: Measured time and staff exposure.
- Whole Body Scatter Correction: Known values from a "simulation study of phantom."
In summary, the ground truth types are primarily known physical properties of phantoms (or simulated phantoms), comparative measurements against established methods, or direct measurements of efficiency/safety.
8. The sample size for the training set:
The document does not provide any information about the training set size for the AI features (OncoFreeze AI, FlowMotion AI).
9. How the ground truth for the training set was established:
Since no information on training sets is provided, there is also no information on how ground truth for any training sets was established.
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