(88 days)
This device is indicated to acquire and display cross-sectional volumes of the whole body, to include the head. The Aquilion Exceed LB has the capability to provide volume sets. These volume sets can be used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician.
AiCE (Advanced Intelligent Clear-IQ Engine) is a noise reduction algorithm that improves image quality and reduces image noise by employing Deep Convolutional Network methods for abdomen, pelvis, lung, cardiac, extremities, head and inner ear applications.
Aquilion Exceed LB (TSX-202A/3) V10.9 with AiCE-i (Advanced intelligent Clear-IQ Engineintegrated) is a whole body multi-slice helical CT scanner, consisting of a gantry, couch and a console used for data processing and display. This device captures cross sectional volume data sets used to perform specialized studies, using indicated software, by a trained and qualified physician. This system is based upon the technology and materials of previously marketed Canon CT systems.
The provided document is a 510(k) summary for the Canon Medical Systems Corporation's Aquilion Exceed LB (TSX-202A/3) V10.9 with AiCE-i. It discusses the device's substantial equivalence to a predicate device, focusing on an expanded clinical use for the AiCE (Advanced Intelligent Clear-IQ Engine) feature, specifically to include cardiac applications.
Here's an analysis of the acceptance criteria and the study proving the device meets them, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document primarily focuses on demonstrating that the subject device performs similarly to or better than the predicate device. The acceptance criteria are implicitly tied to maintaining or improving upon the predicate's performance, particularly in image quality and the diagnostic utility of AiCE-reconstructed images.
| Acceptance Criteria (Implicit) | Reported Device Performance |
|---|---|
| Image Quality Metrics (measured via phantoms): | Aquilion Exceed LB (TSX-202A/3) V10.9 with AiCE-i demonstrated: |
| Contrast-to-Noise Ratios (CNR) | Substantially equivalent or improved performance relative to the predicate device. |
| CT Number Accuracy | Substantially equivalent or improved performance relative to the predicate device. |
| Uniformity | Substantially equivalent or improved performance relative to the predicate device. |
| Slice Sensitivity Profile (SSP) | Substantially equivalent or improved performance relative to the predicate device. |
| Modulation Transfer Function (MTF) | Substantially equivalent or improved performance relative to the predicate device. |
| Standard Deviation of Noise (SD) | Substantially equivalent or improved performance relative to the predicate device. |
| Noise Power Spectra (NPS) | Substantially equivalent or improved performance relative to the predicate device. |
| Low Contrast Detectability (LCD) | Substantially equivalent or improved performance relative to the predicate device. |
| Dual Energy (Electron Density): | For Electron Density using the CBCT Electron Density Phantom: |
| Mean and SD error within established criteria | The mean and SD error between measured and true Electron Density values fall within the established criteria. Precise electron density accuracy is maintained throughout the field of view with monoenergetic images. |
| Dual Energy (Effective Atomic Number Map): | For Effective Atomic Number Map using the Catphan 700 phantom: |
| Mean and SD error within established accuracy criteria | The mean and SD error between measured and true Effective atomic number images fall within the established accuracy criteria. |
| Dual Energy (CT Number Accuracy): | For CT Number Accuracy using the Catphan 600 phantom: |
| Precise CT number accuracy throughout the field of view (70keV) | Precise CT number accuracy is maintained throughout the field of view on 70keV monoenergetic images. |
| AiCE Diagnostic Image Quality (Cardiac Application): | For cardiac diagnostic images reconstructed with AiCE: |
| Images of diagnostic quality | Representative cardiac diagnostic images were obtained using the subject device, and it was confirmed by an American Board Certified Radiologist that the AiCE reconstructed images were of diagnostic quality. This indicates the acceptance criteria for diagnostic utility for the new cardiac application were met, maintaining the expected standard of image quality provided by the AiCE feature for other cleared applications. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: The document does not specify exact sample sizes for the phantom studies (e.g., number of scans, repetitions). For the human review of cardiac images, it states "Representative cardiac diagnostic images," but does not provide a numerical count.
- Data Provenance: The document implies the studies were conducted internally by Canon Medical Systems, given the context of a 510(k) submission. No specific country of origin is mentioned for the data, but the submitter is based in Japan (Canon Medical Systems Corporation, Shimoishigami Otawara-Shi, Tochigi-ken, Japan). The studies are inherently "prospective" in the context of validating the device for its submission.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
- Number of Experts: For the evaluation of cardiac diagnostic images, only one expert is explicitly mentioned: "reviewed by an American Board Certified Radiologist."
- Qualifications of Experts: The expert was an "American Board Certified Radiologist." No specific tenure or experience level is mentioned beyond being Board Certified.
4. Adjudication Method for the Test Set
- For the phantom studies, no human adjudication is mentioned, as the results are based on objective image quality metrics.
- For the cardiac diagnostic image review, with only one radiologist reviewing, there was no adjudication method described (e.g., no 2+1 or 3+1 consensus process). The assessment was a single expert's confirmation.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done
- No, an MRMC comparative effectiveness study was not explicitly done or described. The document focuses on technical bench testing (phantom studies) and a single expert's review of "representative cardiac diagnostic images" to confirm diagnostic quality. There is no mention of human readers improving with or without AI assistance, or any comparative analysis of human performance. The AiCE itself is a noise reduction algorithm, not a diagnostic AI intended to assist human interpretation directly in terms of detection or diagnosis.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done
- Yes, in essence, standalone performance (algorithm only) was assessed for the AiCE feature. The "Image Quality Evaluation" using phantoms measured the intrinsic performance of the AiCE algorithm (and the overall system) in terms of various image quality metrics (CNR, CT Number Accuracy, etc.). These are objective measurements of the algorithm's output quality, independent of human interpretation.
- The "Dual Energy" phantom studies also represent a form of standalone performance assessment for those features of the system.
7. The Type of Ground Truth Used
- Physiological Phantom Measurements: For the bulk of the image quality and dual-energy assessments, the ground truth was established by known physical properties of phantoms. These phantoms are designed with specific, measurable characteristics (e.g., known electron densities, accurate CT numbers, specific contrast elements) that serve as the "true" values against which the device's measurements are compared.
- Expert Consensus (single expert): For the "representative cardiac diagnostic images," the ground truth regarding "diagnostic quality" relied on the opinion/assessment of a single American Board Certified Radiologist. While not a "consensus" in the multi-reader sense, this expert's judgment served as the ground truth for diagnostic utility in this specific clinical application.
8. The Sample Size for the Training Set
- The document does not provide information on the sample size used for the training set for the AiCE Deep Convolutional Network. Information on training data is typically proprietary and not included in 510(k) summaries unless specifically relevant to substantial equivalence arguments.
9. How the Ground Truth for the Training Set Was Established
- The document does not provide information on how the ground truth was established for the training set of the AiCE Deep Convolutional Network. This information is usually part of the internal development and validation of the AI algorithm itself, which predates the specific 510(k) submission for this device modification.
§ 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.