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ADMIRE is a CT reconstruction software. The end user can choose to apply either ADMIRE or the weighted filter back-projection (WFBP) to the acquired raw data. Depending on the clinical task, patient size, anatomical location, and clinical practice, the use of ADMIRE can help to reduce radiation dose while maintaining pixel noise, low contrast detectability and high contrast resolution.
Phantom measurements showed that high contrast resolution is equivalent or improved and pixel noise is equivalent between full dose WFBP images and reduced dose ADMIRE images. Additionally, ADMIRE can reduce spiral artifacts by using iterations going back and forth between image space and raw data space.
Images reconstructed with ADMIRE are not intended to be evaluated with syngo Osteo CT or syngo Calcium Scoring.
ADMIRE is an iterative reconstruction option designed to be used on Siemens currently marketed and future CT devices. Its use has been previously cleared by FDA (K133646, clearance date June 20, 2014). No modifications were made to the algorithm or to the implementation of the feature. The changes proposed within this 510(k) only pertain to an extension of the claims associated with the feature as follows:
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- Compared to images reconstructed with WFBP, ADMIRE may simultaneously enable*
- 80 to 85% dose reduction at the same image quality and .
- 73 to 77% image noise reduction at the reduced dose and o
- up to 42% improved high-contrast spatial resolution improvement at reduced o dose and reduced image noise.
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- Alternatively, ADMIRE may enable
- up to 150% improved low contrast detectability (factor 2.5) at the same dose or .
- up to 90% image noise reduction at constant dose or .
- up to 87% improved high-contrast spatial resolution improvement at 85% . reduced dose and constant image noise or
- up to 38% improved high-contrast resolution at 90% reduced image noise and . constant dose.
Furthermore, the following claims have previously been cleared by FDA as part of K133646 (clearance date June 20, 2014) and will be maintained with this clearance:
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- Additionally, ADMIRE
- compared to SAFIRE potentially features a more "FBP-like" noise texture in . terms of the number of "outliers" in the noise texture, especially for higher strength settings of the algorithm and
- can reduce spiral artifacts by using iterations going back and forth between image 0 space and raw data space and
- has the potential to result in a higher noise reduction compared to SAFIRE when . reconstructing thick slices.
- Image quality as defined by low contrast detectability using a model observer method for evaluation. Equivalent low contrast detectability can be achieved with 80% to 85% less dose using ADMIRE at highest strength level for thin (0.6 mm) reconstruction slices in measured and simulated body and head phantoms for low contrast objects with different contrasts. See ADMIRE data sheet for further information.
In clinical practice, the use of ADMIRE may reduce CT patient dose depending on the clinical task, patient size, anatomical location, and clinical practice. A consultation with a radiologist and a physicist should be made to determine the appropriate dose to obtain diagnostic image quality for the particular clinical task.
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Acceptance Criteria and Device Performance Study for ADMIRE
1. Table of Acceptance Criteria and Reported Device Performance:
The document describes performance claims rather than explicit acceptance criteria with specific thresholds for FDA clearance in this section. However, based on the claims being extended and previous clearance, the reported performance is presented below. The "acceptance criteria" are implied by the performance metrics Siemens seeks to claim.
| Metric | Acceptance Criteria (Implied by Claims) | Reported Device Performance (ADMIRE vs. WFBP or SAFIRE) |
|---|---|---|
| Dose Reduction at Same Image Quality* | - | 80% to 85% dose reduction |
| Image Noise Reduction at Reduced Dose | - | 73% to 77% image noise reduction |
| High-Contrast Spatial Resolution Improvement at Reduced Dose & Noise | - | Up to 42% improved high-contrast spatial resolution |
| Low Contrast Detectability (LCD) Improvement at Same Dose | - | Up to 150% improved LCD (factor 2.5) |
| Image Noise Reduction at Constant Dose | - | Up to 90% image noise reduction |
| High-Contrast Spatial Resolution Improvement at 85% Reduced Dose & Constant Noise | - | Up to 87% improved high-contrast spatial resolution |
| High-Contrast Spatial Resolution Improvement at 90% Reduced Noise & Constant Dose | - | Up to 38% improved high-contrast resolution |
| Noise Texture (vs. SAFIRE) | "FBP-like" noise texture (fewer "outliers") | Potentially more "FBP-like" noise texture, especially for higher strength settings |
| Spiral Artifact Reduction | - | Can reduce spiral artifacts |
| Noise Reduction in Thick Slices (vs. SAFIRE) | Higher noise reduction | Potential to result in higher noise reduction |
*Image quality defined by low contrast detectability using a model observer method for evaluation.
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size for Test Set: The document mentions "a large number of CT images" were generated for evaluation by using "computer-simulated as well as measured CT data." However, specific numerical sample sizes are not provided for either the simulated or measured data used in the testing.
- Data Provenance: The study utilized "PhantomLabs® CCT189 and CCT191 phantoms" for low-contrast detectability and a "Teflon edge phantom" for high-contrast spatial resolution. This indicates the testing was conducted using phantom data, not human patient data. There is no information on the country of origin of the data, but it is clear it is retrospective (in the sense of being pre-generated data/scans for evaluation) rather than prospective human trials.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:
- The document does not mention the involvement of experts for establishing ground truth in the context of the phantom-based performance evaluation. The evaluation methods described (model observer for LCD, standard deviation for noise, ImPACT CT evaluation group definition for spatial resolution) are quantitative, objective measurements from the phantom images rather than expert interpretation.
4. Adjudication Method for the Test Set:
- Not applicable. Since the ground truth for the test set was established through objective phantom measurements and model observer studies, there was no need for expert adjudication.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No, an MRMC comparative effectiveness study was not done. The device's performance was evaluated using phantom measurements and model observer studies, focusing on quantitative image metrics rather than human reader performance with or without AI assistance.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:
- Yes, a standalone study was performed. The evaluations of low-contrast detectability, image noise, and high-contrast spatial resolution were conducted on images reconstructed by the ADMIRE algorithm, comparing its output to WFBP reconstructed images or SAFIRE, using objective metrics derived directly from the images. This did not involve a human-in-the-loop component for performance evaluation.
7. Type of Ground Truth Used:
- The ground truth used was phantom-based objective measurements. For low-contrast detectability, a "model observer method" was used. For image noise, "standard deviation across images at all pixel locations" was computed. For high-contrast spatial resolution, it was based on "measured CT data of a Teflon edge phantom as defined by the ImPACT CT evaluation group."
8. Sample Size for the Training Set:
- The document does not provide information on the sample size for the training set for the ADMIRE algorithm. It focuses on the validation of its 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. Since ADMIRE is an iterative reconstruction algorithm, its training (if applicable, as some iterative methods are rule-based or optimized rather than "trained" in a deep learning sense) would likely involve various simulated or measured data with known properties to optimize the reconstruction parameters. However, the details are not explicitly stated in this summary.
§ 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.