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This device is indicated to acquire and display cross-sectional volumes of the whole body, to include the head.

The Aquilion Prime SP 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 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.

The Aquilion Prime SP (TSX-303B/8) V10.2 with AiCE-i is a 40-row CT System that is intended to acquire and display cross-sectional volumes of the whole body, including the head. An optional Dynamic Volume CT Upgrade Kit can be installed in order to expand the active detector rows to 80. This system is based upon the technology and materials of previously marketed Canon CT systems. In addition, the subject device incorporates the latest reconstruction technology, AiCE-i (Advanced intelligent Clear-IQ Engine - integrated), intended to reduce image noise and improve image quality by utilizing Deep Convolutional Network methods. These methods can more fully explore the statistical properties of the signal and noise. By learning to differentiate structure from noise, the algorithm produces fast, high quality CT reconstruction.

The Aquilion Prime SP (TSX-303B/8) V10.2 with AiCE-i is a CT x-ray system, and information on its acceptance criteria and the study proving it is provided below:

• 1. A table of acceptance criteria and the reported device performance

• 2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

  The document does not explicitly state a sample size for patient data. The testing primarily relies on phantom studies and a review of diagnostic images.

  • Data Provenance: Not specified for any potential patient data. The document mentions "Representative abdomen/pelvis, lung, cardiac, brain, extremities and inner ear diagnostic images" were obtained using the subject device, suggesting prospective acquisition for evaluation, but this is not definitively stated.

• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

  For the assessment of diagnostic image quality:

  • Number of experts: One
  • Qualifications of experts: An "American Board Certified Radiologist." Further details (e.g., years of experience) are not provided.

• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

  Based on the mention of a single American Board Certified Radiologist reviewing images, there was no multi-reader adjudication method (e.g., 2+1, 3+1) described for the diagnostic quality assessment. It appears to be a solitary expert's assessment.

• 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 focusing on human reader improvement with or without AI assistance is described in the provided text. The study focused on assessing image quality and specific performance metrics of the AI-integrated system (AiCE-i) through phantom studies and expert review of diagnostic images.

• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

  Yes, standalone testing of the algorithm (AiCE-i) was a primary component of the study. This is evidenced by:

  • The extensive use of phantom studies to assess various image quality metrics (CNR, CT Number Accuracy, Uniformity, SSP, MTF, SD, NPS, LCD, etc.). These are objective measurements of the algorithm's output.
  • Direct claims stating quantitative dose reduction (82%) and noise reduction (21.4%) by the AiCE algorithm relative to other reconstruction methods.
  • Claims about improved low contrast detectability (13.8%) by the algorithm.
  • Analysis of NPS and kurtosis values to assess noise appearance/texture of the algorithm's output.

• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

  The ground truth used for the evaluation can be categorized as follows:

  • Objective Phantom Measurements: For quantitative image quality metrics like dose reduction, noise reduction, CNR, MTF, NPS, and LCD. The "ground truth" here is the physical properties of the phantom and the established measurement methodologies.
  • Expert Radiologist Review: For confirming the "diagnostic quality" of the AiCE reconstructed images. The "ground truth" in this context is the qualitative assessment and professional judgment of the American Board Certified Radiologist.

• 8. The sample size for the training set

  The document does not provide details on the sample size or characteristics of the training data used for the Deep Convolutional Network methods employed by AiCE-i.

• 9. How the ground truth for the training set was established

  The document does not provide details on how the ground truth for the training set was established for the Deep Convolutional Network methods used by AiCE-i.

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This device is indicated to acquire and display cross-sectional volumes of the whole the head, with the capability to image whole organs in a single rotation. Whole organs include, but are not limited to brain, heart, pancreas, etc.

The Aquilion ONE has the capability to provide volume sets of the entire organ. These volume sets can be used to perform specialized studies, using indicated software, of the whole organ by a trained and qualified physician.

FIRST is an iterative reconstruction algorithm intended to reduce exposure dose and improve high contrast spatial resolution for abdomen, pelvis, chest, cardiac, extremities and head applications.

AiCE is a noise reduction algorithm that improves image quality and reduces image noise by employing Deep Convolutional Neural Network methods for abdomen, pelvis, inner ear and extremities applications.

The Spectral Imaging System allows the system to acquire two nearly simultaneous CT images of an anatomical location using distinct tube voltages and/or tube currents by rapid KV switching. The X-ray dose will be the sum of the dose at each respective tube voltage and current in a rotation.

Information regarding the material composition of various organs, tissues, and contrast materials may be gained from the differences in X-ray attenuation between these distinct energies.

When used by a qualified physician, a potential application is to determine the course of treatment.

Aquilion ONE (TSX-306A/3) V10.0 with Spectral Imaging System 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/hardware, by a trained and qualified physician. This system is based upon the technology and materials of previously marketed Canon CT systems.

Here's a breakdown of the acceptance criteria and the studies that prove the device meets them, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary does not explicitly list numerical "acceptance criteria" in the format of a table with pass/fail thresholds. Instead, it describes various tests and claims that demonstrate substantial equivalence to previously cleared devices. The performance is reported in terms of qualitative assessments (e.g., "diagnostic quality," "substantially equivalent") and quantitative improvements (e.g., "dose reduction," "improvement in low contrast detectability," "noise reduction").

Here's an interpretation of the implied acceptance criteria and reported performance:

• More similar to high dose FBP (compared to FIRST);
• More similar to FBP (compared to FIRST);
• Improved (compared to FIRST);
• More natural (compared to FIRST). | AiCE noise appearance/texture:
• More similar to high dose filtered backprojection (compared to FIRST);
• More similar to filtered backprojection (compared to FIRST);
• Improved (compared to FIRST);
• More natural (compared to FIRST). |
  | Clinical Image Quality | AiCE images for abdomen/pelvis, brain, inner ear, and extremity applications are of diagnostic quality. | Representative abdomen/pelvis, brain, inner ear and extremity AiCE images were confirmed to be of diagnostic quality by an American Board Certified Radiologist. |

2. Sample Size Used for the Test Set and Data Provenance

• Spectral Imaging Performance Testing - Bench: The sample size for phantoms used in bench testing is not specified beyond "various phantoms" and "Catphan and Body Phantom." Data provenance is laboratory bench testing.
• Spectral Imaging Performance Testing - Clinical Images: The sample size is not specified beyond "Representative abdomen/pelvis, lung, and extremity Spectral Images." The data provenance of these clinical images (country of origin, retrospective/prospective) is not specified in the provided text.
• Non-Spectral Imaging and AiCE Performance Testing - Bench: The sample size for phantoms used in bench testing is not specified beyond "various phantoms." Data provenance is laboratory bench testing.
• AiCE Imaging Performance Testing - Clinical Images: The sample size is not specified beyond "Representative abdomen/pelvis, brain, inner ear and extremity AiCE images." The data provenance of these clinical images (country of origin, retrospective/prospective) is not specified in the provided text.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• For both Spectral Imaging Clinical Images and AiCE Clinical Images: "an American Board Certified Radiologist" was used. This indicates one expert. The specific years of experience are not mentioned, but "American Board Certified" signifies a high level of qualification.

4. Adjudication Method for the Test Set

• For both Spectral Imaging Clinical Images and AiCE Clinical Images, only one expert (an American Board Certified Radiologist) reviewed the images. Therefore, there was no adjudication method between multiple experts employed for these clinical image quality assessments. The phrase "it was confirmed" implies a singular decision.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No, a MRMC comparative effectiveness study was not explicitly mentioned in the provided text for evaluating human reader improvement with AI assistance. The clinical image reviews were done by a single radiologist to confirm "diagnostic quality" of the AI-processed images, not to compare human reader performance with and without AI. The quantitative performance (dose reduction, LCD improvement, noise reduction) was assessed via model observer evaluation or phantom studies.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was done

• Yes, extensive standalone performance testing was done for both Spectral Imaging and AiCE.
  • Spectral Imaging: Bench testing utilizing phantoms assessed various image quality metrics (CNR, CT Number Accuracy, Uniformity, SSP, MTF-Wire, SD, NPS, LCD) to demonstrate substantial equivalence to the predicate. Other phantom studies supported claims of beam hardening artifact reduction and iodine concentration correlation.
  • AiCE: Bench testing utilizing phantoms assessed similar image quality metrics and pediatric phantom/protocol performance, demonstrating substantial equivalence. A model observer evaluation was specifically mentioned for quantitative assessments of dose reduction, LCD improvement, and noise reduction compared to FBP and AIDR 3D, which is a standalone algorithm-only performance assessment. Other phantom studies supported claims regarding artifact appearance, spatial resolution, and noise appearance/texture.

7. The Type of Ground Truth Used

• For Bench Testing (Spectral and AiCE): The ground truth was based on physical phantom measurements and known properties/compositions of the phantoms. For example, known concentrations of materials for iodine correlation, or predefined structures for MTF and LCD assessments.
• For Clinical Image Reviews (Spectral and AiCE): The ground truth was expert consensus (single expert), specifically the judgment of an American Board Certified Radiologist that the images were of "diagnostic quality." This is a form of expert opinion or interpretation.

8. The Sample Size for the Training Set

• The document does not specify the sample size for the training set for either AiCE (Deep Convolutional Neural Network) or FIRST (Iterative Reconstruction Algorithm). It only mentions that AiCE employs "Deep Convolutional Neural Network methods."

9. How the Ground Truth for the Training Set was Established

• The document does not provide details on how the ground truth for the training set was established. It mentions the use of "Deep Convolutional Neural Network methods" for AiCE, which implies a supervised learning approach requiring labeled training data, but the specifics of that labeling process or who performed it are omitted.

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