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Vantage Fortian/Orian 1.5T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

• Proton density (PD) (also called hydrogen density)
• Spin-lattice relaxation time (T1)
• Spin-spin relaxation time (T2)
• Flow dynamics
• Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Fortian (Model MRT-1550/WK, WM, WO, WQ)/Vantage Orian (Model MRT-1550/U3, U4, U7, U8) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. These Vantage Fortian/Orian models use 1.4 m short and 4.1 tons light weight magnet. They include the Canon Pianissimo Σ and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole-body coil of these Vantage Fortian/Orian models provide the maximum field of view of 55 x 55 x 50 cm and include the standard (STD) gradient system.

The Vantage Fortian (Model MRT-1550/WS, WU)/Vantage Orian (Model MRT-1550/AV, AZ) with modified ASGC is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. These Vantage Fortian/Orian models use 1.4 m short and 4.1 tons light weight magnet. They include the Canon Pianissimo Σ and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole-body coil of these Vantage Fortian/Orian models provide the maximum field of view of 55 x 55 x 50 cm and include the standard (STD) gradient system.

The Vantage Orian (Model MRT-1550/ UC, UD, UG, UH, UK, UL, UO, UP) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian models use 1.4 m short and 4.1 tons light weight magnet. They include the Canon Pianissimo and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole-body coil of these Vantage Orian models provide the maximum field of view of 55 x 55 x 50 cm. The MRT-1550/ UC, UD, UG, UH, UK, UL, UO, UP models include the XGO gradient system.

The Vantage Orian (Model MRT-1550/AK, AL, AO, AP, A3, A4, A7, A8, AC, AD, AG, AH (Upgrade only)) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian models MRT-1550/A3, A4, A7, A8 use 1.4 m short and 4.1 tons light weight magnet while the Vantage Orian models MRT-1550/AK, AL, AO, AP, AC, AD, AG, AH use 1.4 m short and 3.8 tons light weight magnet. All of the aforementioned models include the Canon Pianissimo and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole-body coil of these Vantage Orian models provide the maximum field of view of 55 x 55 x 50 cm. The Model MRT-1550/AK, AL, AO, AP includes the XGO gradient system. The MRT-1550/A3, A4, A7, A8, AC, AD, AG, AH models include the standard (STD) gradient system.

The Vantage Orian (Model MRT-1550/AS, AT, AW, AX (Upgrade only)) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian uses 1.4 m short and 4.0 tons light weight magnet. It includes the Canon Pianissimo and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole body coil of the Vantage Orian provides the maximum field of view of 55 x 55 x 50 cm and include the standard (STD) gradient system.

This system is based upon the technology and materials of previously marketed Canon Medical Systems MRI systems and is intended to acquire and display cross-sectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body.

Based on the provided FDA 510(k) clearance letter and summary for the "Vantage Fortian/Orian 1.5T, MRT-1550, V10.0 with AiCE Reconstruction Processing Unit for MR" (K253625), here's a description of the acceptance criteria and the study that proves the device meets them:

I. Acceptance Criteria and Reported Device Performance

The submission K253625 is for a modification of a previously cleared device (K250901). Therefore, the acceptance criteria are primarily focused on demonstrating that the modified device remains as safe and effective as the predicate device. The performance parameters listed relate to safety and overall function rather than specific diagnostic accuracy metrics, as no image quality testing was conducted for this specific submission.

Important Note: The document explicitly states "No image quality testing was conducted" for this specific K253625 submission. This implies that the acceptance criteria and performance evaluation for image quality were established and met in the predicate device (K250901), and the current modifications do not impact those aspects, thus not requiring re-testing.

II. Study Details Pertaining to K253625 (Modification of a Cleared Device)

Since this submission is a modification of a cleared device, the "study" primarily consists of verification and validation testing related to the changes, rather than a full clinical efficacy study.

1. Sample Size used for the test set and the data provenance:

   • The document does not specify sample sizes for any test sets. The testing mentioned is "bench testing," "risk analysis and verification/validation testing," and "Software Documentation" testing. These typically do not involve patient data or conventional "test sets" in the clinical study sense.
   • Data Provenance: Not applicable as no explicit clinical test set data from patients is described. The testing refers to internal verification and validation activities.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not applicable. The document does not describe a clinical test set requiring expert ground truth establishment for diagnostic performance.

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

   • Not applicable. No clinical test set with adjudicated ground truth is described.

4. 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. The document does not mention any MRMC comparative effectiveness study. The AiCE Reconstruction Processing Unit was already part of the predicate device (K250901) and previous versions (K240238, K191662). This submission focuses on system and software modifications, not a new evaluation of AI assistance.

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

   • Not explicitly stated for this particular submission. The device, being an MRI system with an AiCE (presumably AI-enhanced) reconstruction unit, inherently involves an algorithm. However, the performance assessment described in K253625 is about validating the modifications to the system itself, ensuring it meets safety and functional parameters, and that the software changes are correctly implemented. It does not provide data on the standalone performance of the AiCE algorithm in this context. Such data would have been part of the predicate device's clearance.

6. The type of ground truth used (expert concensus, pathology, outcomes data, etc):

   • Not applicable for this submission. The testing is described as "bench testing" and "verification/validation testing," which implies validation against design specifications, functional requirements, and safety standards, rather than diagnostic ground truth from patient studies.

7. The sample size for the training set:

   • Not applicable for this submission. This is a modification of an existing device; no new training of an AI model is described. The original AiCE training set (if applicable) would have been used for the predicate or earlier versions.

8. How the ground truth for the training set was established:

   • Not applicable for this submission as no new training set is mentioned.

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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 Serve 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 algorithm that improves image quality and reduces image noise by employing Deep Convolutional Neural Network methods for abdomen, pelvis, lung, cardiac, extremities, head and inner ear applications.

PIQE is a Deep Learning Reconstruction method designed to enhance spatial resolution. By incorporating noise reduction into the Deep Convolutional Neural Network (DCNN), it is possible to achieve both spatial resolution improvement and noise reduction for cardiac, abdomen, pelvis, and lung applications, in comparison to FBP and hybrid iterative reconstruction.

CLEAR Motion is a Deep Learning Reconstruction (DLR) method designed to reduce motion artifacts. A Deep Convolutional Neural Network (DCNN) is used to estimate the patient's motion. This information is used in the reconstruction process to obtain lung images with less motion artifacts.

The Aquilion Serve SP (TSX-307B) V2.0 This device is indicated to acquire and display cross sectional volumes of the whole body, to include 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 Serve SP has the capability to provide volume sets of the entire organ. These volume sets can be used to perform specialized studies, using indicated software/hardware, of the whole organ 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 study information for the Aquilion Serve SP (TSX-307B) V2.0, based on the provided FDA 510(k) clearance letter.

Overview of New Features:
The Aquilion Serve SP (TSX-307B) V2.0 introduces two new Deep Learning Reconstruction (DLR) methods:

• PIQE: Enhances spatial resolution and reduces noise for cardiac, abdomen, pelvis, and lung applications.
• CLEAR Motion: Reduces motion artifacts for lung applications.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with specific numerical targets and results for each new feature. Instead, it describes evaluations and general statements of meeting acceptance criteria.

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

• CLEAR Motion:

  • Clinical Image Quality Evaluation: Five representative clinical cases.
  • Dynamic and Non-Dynamic Phantom Evaluations: Phantoms were used, so not patient data.
  • Data Provenance: Not explicitly stated for the 5 clinical cases, but likely internal Canon Medical Systems data (retrospective, given it's used for evaluating a release). The document mentions "clinical lung CT datasets acquired on the TSX-307B system with iSeries V2.0 SP0000 software."

• PIQE:

  • IQ Metrics Evaluation: Phantom data and "multiple clinical and phantom-based metrics." No specific number of clinical cases mentioned for the testing set.
  • Data Provenance: Not explicitly stated for the testing data.

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

The document does not provide information on the number of experts, their qualifications, or their involvement in establishing ground truth for the test sets for either CLEAR Motion or PIQE. The evaluations primarily focus on objective phantom measurements and qualitative visual assessments described generally (e.g., "visual improvement," "improved clarity").

4. Adjudication Method for the Test Set

The document does not describe any adjudication method (e.g., 2+1, 3+1, none) for the test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

The document does not report a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. The evaluations focus on direct image quality improvements, not human reader performance with or without AI assistance.

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

Yes, the performance studies described for both PIQE and CLEAR Motion are standalone algorithm evaluations. They assess the algorithms' direct impact on image characteristics (e.g., noise, spatial resolution, CT number accuracy, motion artifact reduction) using phantoms and clinical datasets, without involving human readers for diagnostic tasks.

7. The Type of Ground Truth Used

• CLEAR Motion:

  • Dynamic Phantom: The "ground truth" is derived from the known setup of the dynamic phantom simulating pulmonary vessel motion, against which the algorithm's ability to reduce artifacts is measured.
  • Non-Dynamic Phantom: The "ground truth" is the known CT number of the water phantom, against which the algorithm's accuracy is measured.
  • Clinical Data: The "ground truth" is implicit and refers to the reduction of visually perceived motion artifacts and preservation of anatomical detail relative to conventional reconstructions. It appears to be based on expert visual assessment (though details on experts are missing).

• PIQE:

  • Phantom Data: The "ground truth" is derived from known phantom characteristics for metrics like CNR, CT number accuracy, uniformity, MTF, NPS, and LCD.
  • Clinical Data: The "ground truth" for the "IQ Metrics Evaluation" is based on improvements in objective image quality metrics and subjective visual assessments related to noise reduction, spatial resolution, and low contrast detectability, likely based on expert visual assessment (again, without specified expert details).

8. The Sample Size for the Training Set

• CLEAR Motion:

  • Trained using 3,400 partial image pairs derived from 37 clinical lung CT cases.
  • Cases covered a range of doses, field-of-view sizes, and helical pitches.

• PIQE:

  • Cardiac imaging: 18 anonymized clinical cases (13 UHR-CT and 5 NR-CT) generating over 13,000 training pairs.
  • Body imaging: 28 cases spanning thoracic to pelvic regions, producing 1,845 large training pairs.
  • Data augmentation techniques were applied.
  • 5% of samples reserved for validation.

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

• CLEAR Motion:
  The document states the DCNN was "trained to produce motion-compensated images." This implies that the training data likely consisted of pairs or sets of images where motion-affected images were "corrected" by human experts or other techniques to serve as the desired "ground truth" for motion compensation. However, the exact methodology for generating these "motion-compensated" ground truth images is not detailed.

• PIQE:

  • The retraining process used high-resolution AiCE images from an ultra-high-resolution CT system (Aquilion Precision) as targets (i.e., ground truth).
  • Simulated normal-resolution AIDR3D images were used as inputs.
  • This setup suggests a supervised learning approach where the model learns to transform lower-quality (simulated AIDR3D) inputs into higher-quality (Aquilion Precision AiCE) outputs, effectively learning noise reduction and resolution enhancement by mimicking the ideal high-resolution images as ground truth.

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This device is a digital radiography/fluoroscopy system used in a diagnostic and interventional angiography configuration. The system is indicated for use in diagnostic and angiographic procedures for blood vessels in the heart, brain, abdomen and lower extremities.

aEvolve Imaging is an imaging chain intended for adults, with Artificial Intelligence Denoising (AID) designed to reduce noise in real-time fluoroscopic images and signal enhancement algorithm, Multi Frequency Processing (MFP).

The Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension), is an interventional X-ray system with a floor mounted C-arm as its main configuration. An optional ceiling mounted C-arm is available to provide a bi-plane configuration where required. Additional units include a patient table, X-ray high-voltage generator and a digital radiography system. The C-arms can be configured with designated X-ray detectors and supporting hardware (e.g. X-ray tube and diagnostic X-ray beam limiting device). With Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension), the αEvolve Imaging feature now supports 12-inch, 10-inch, and 3-inch fields of view (FOV) for imaging in adult patients. The αEvolve imaging chain incorporates Artificial Intelligence Denoising (AID) for real-time fluoroscopic noise reduction, as well as Multi-Frequency Processing (MFP), a signal enhancement algorithm.

The provided 510(k) clearance letter describes performance testing for an interventional fluoroscopic X-ray system called "Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension)". This device includes "Artificial Intelligence Denoising (AID)" and a "Multi Frequency Processing (MFP)" signal enhancement algorithm. The testing compares the subject device's αEvolve Imaging chain with AID to the predicate device's "super noise reduction filter (SNRF)".

Here's an analysis of the acceptance criteria and the study details:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally defined as the subject device performing "equivalent to or better than" the predicate, or "significantly better" (p < 0.05), or showing "no unexpected distortions" and "maintained or improved" performance.

2. Sample size used for the test set and the data provenance

The document does not specify exact sample sizes for the test sets in terms of number of patients or images. The tests primarily utilized:

• Phantom data: Anthropomorphic chest phantoms and PMMA slab phantoms.
• Clinical datasets: Mentioned in image quality evaluations, but no further details provided regarding number or source.
• Data provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). The use of phantoms is a controlled laboratory setting.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. The reported tests are primarily quantitative bench tests using phantoms or objective image quality metrics, not dependent on expert interpretation for ground truth.

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

Not applicable, as the tests involve quantitative metrics measured from phantoms or images, rather than human expert adjudication.

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 involving human readers is mentioned in the provided text. The testing focuses on objective image quality metrics using phantoms and clinical datasets.

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

Yes, the described performance testing is a standalone assessment of the αEvolve Imaging chain, including the Artificial Intelligence Denoising (AID) algorithm, without a human-in-the-loop component. The "reported device performance" directly reflects the algorithm's impact on image quality parameters.

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

The ground truth for most tests is derived from:

• Physical phantoms: Anthropomorphic chest phantoms and PMMA slab phantoms, which provide known geometries and material properties for objective measurement.
• Defined physical metrics: Metrics like image level, noise magnitude, SNR, NPS, kurtosis, MTF, NEQ, LCD, and CNR are calculated based on the image data and the known characteristics of the phantoms. There is no "ground truth" established by clinical experts or pathology in these technical bench tests.

8. The sample size for the training set

The document does not provide any information regarding the training set size for the Artificial Intelligence Denoising (AID) algorithm.

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

The document does not provide any information on how the ground truth for the AID algorithm's training set was established.

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The Diagnostic Ultrasound System Aplio beyond Model CUS-ABE00, Aplio me Model CUS-AME00 are indicated for the visualization of structures, and dynamic processes within the human body using ultrasound and to provide image information for diagnosis in the following clinical applications: fetal, abdominal, intra-operative (abdominal), pediatric, small organs (thyroid, breast and testicle), trans-vaginal, trans-rectal, neonatal cephalic, adult cephalic, cardiac (both adult and pediatric), peripheral vascular, transesophageal, musculo-skeletal (both conventional and superficial), laparoscopic and thoracic/pleural.

This system provides high-quality ultrasound images in the following modes: B mode, M mode, Continuous Wave, Color Doppler, Pulsed Wave Doppler, Power Doppler and Combination Doppler, as well as Speckle-tracking, Tissue Harmonic Imaging, Combined Modes, Shear wave, Elastography, and Acoustic attenuation mapping.

This system is suitable for use in hospital and clinical settings by physicians or appropriately trained healthcare professionals.

The Aplio beyond, Model CUS-ABE00 and Aplio me, Model CUS-AME00, V2.0 are mobile diagnostic ultrasound systems. These systems are Track 3 devices that employ a wide array of probes including flat linear array, convex, and sector array with frequency ranges between approximately 2MHz to 20MHz.

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The device is a diagnostic imaging system that combines Positron Emission Tomography (PET) and X-ray Computed Tomography (CT) systems. The CT component produces cross-sectional images of the body by computer reconstruction of X-ray transmission data. The PET component images the distribution of PET radiopharmaceuticals in the patient body. The PET component utilizes CT images for attenuation correction and anatomical reference in the fused PET and CT images.

This device is to be used by a trained health care professional to gather metabolic and functional information from the distribution of the radiopharmaceutical in the body for the assessment of metabolic and physiologic functions. This information can assist in the evaluation, detection, localization, diagnosis, staging, restaging, follow-up, therapeutic planning and therapeutic outcome assessment of (but not limited to) oncological, cardiovascular, neurological diseases and disorders. Additionally, this device can be operated independently as a whole body multi-slice CT scanner.

AiCE-i for PET is intended to improve image quality and reduce image noise for FDG whole body data by employing deep learning artificial neural network methods which can explore the statistical properties of the signal and noise of PET data. The AiCE algorithm can be applied to improve image quality and denoising of PET images.

Deviceless PET Respiratory gating system, for use with Cartesion Prime PET-CT system, is intended to automatically generate a gating signal from the list-mode PET data. The generated signal can be used to reconstruct motion corrected PET images affected by respiratory motion. In addition, a single motion corrected volume can automatically be generated. Resulting motion corrected PET images can be used to aid clinicians in detection, localization, evaluation, diagnosis, staging, restaging, follow-up of diseases and disorders, radiotherapy planning, as well as their therapeutic planning, and therapeutic outcome assessment. Images of lesions in the thorax, abdomen and pelvis are mostly affected by respiratory motion. Deviceless PET Respiratory gating system may be used with PET radiopharmaceuticals, in patients of all ages, with a wide range of sizes, body habitus and extent/type of disease.

The Cartesion Prime (PCD-1000A/3) V10.21 combines a high-end CT and a high-throughput PET designed to acquire CT, PET and fusion images.

The high-end CT system is a multi-slice helical CT scanner with a gantry aperture of 780 mm and a maximum scan field of view (FOV) of 700 mm. The high-throughput PET system has a digital PET detector utilizing SiPM sensors with temporal resolution of < 250 ps (238 ps typical). Cartesion Prime (PCD-1000A/3) V10.21 is intended to acquire PET images of any desired region of the whole body and CT images of the same region (to be used for attenuation correction or image fusion), to detect the location of positron emitting radiopharmaceuticals in the body with the obtained images. This device is used to gather the metabolic and functional information from the distribution of radiopharmaceuticals in the body for the assessment of metabolic and physiologic functions. This information can assist research, detection, localization, evaluation, diagnosis, staging, restaging, follow-up of diseases and disorders, as well as their therapeutic planning, and therapeutic outcome assessment. This device can also function independently as a whole body multi-slice CT scanner.

The subject device incorporates the latest reconstruction technology, AiCE-i for PET (Advanced Intelligent Clear-IQ Engine- integrated), intended to improve image quality and reduce image noise for FDG whole body data by employing deep learning artificial neural network methods which can more fully explore the statistical properties of the signal and noise of PET data. The AiCE algorithm will be able to better differentiate signal from noise and can be applied to improve image quality and denoising of PET images compared to conventional PET imaging reconstruction.

A Deviceless PET Respiratory gating system has been implemented for use with the subject device. With this subject device, respiration is extracted using a pre-trained neural network. Respiratory-gated reconstruction is performed at a speed equal to or faster than that with "Normal".

Here's a breakdown of the acceptance criteria and study details for the Cartesion Prime PET-CT System, based on the provided FDA 510(k) clearance letter:

Acceptance Criteria and Device Performance for Cartesion Prime PET-CT System (K251370)

The submission describes two primary feature enhancements: AiCE-i for PET (AiCE2) and Deviceless PET Respiratory gating system (DRG2).

1. Table of Acceptance Criteria and Reported Device Performance

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

For AiCE-i for PET (AiCE2) - Clinical Images:

• Sample Size: 10 PET DICOM clinical 18F-FDG whole body cases.
• Data Provenance: Not explicitly stated, but the submission notes "selected to cover characteristics common to the intended U.S. patient population." The training data for AiCE2 is mentioned to have over half acquired from the U.S.

For Deviceless PET Respiratory Gating (DRG2) - Clinical Images:

• Sample Size: 10 patients.
• Data Provenance: Not explicitly stated, but the submission notes "selected to cover characteristics common to the intended U.S. patient population." The training data for DRG2 was acquired entirely from the U.S.

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

For AiCE-i for PET (AiCE2) - Clinical Images:

• Number of Experts: Three (3) physicians.
• Qualifications: At least 20 years of experience in nuclear medicine.

For Deviceless PET Respiratory Gating (DRG2) - Clinical Images:

• Number of Experts: Three (3) physicians.
• Qualifications: At least 20 years of experience in nuclear medicine.

4. Adjudication Method for the Test Set

The adjudication method is not explicitly stated as 2+1, 3+1, or none. However, for both clinical image evaluations, it states that "All three physicians reported/determined that..." This implies a consensus-based adjudication among the three experts was used to reach the conclusions. It does not indicate individual disagreements were arbitrated by a fourth reader.

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

A formal MRMC comparative effectiveness study, designed to quantify the effect size of human readers improving with AI assistance, was not explicitly described in the provided text. The clinical image evaluations involved expert review and comparison, but the focus was on the algorithm's performance and image quality, not a direct measurement of human reader improvement with vs. without AI assistance.

6. If a Standalone (i.e. algorithm only without human-in-the loop performance) was Done

Yes, standalone performance was extensively evaluated for both features:

• AiCE-i for PET:
  • Bench tests for pediatric use (CRC, BGV, CNR, artifacts, SUVmean equivalence).
  • Bench tests for image intensity (SUV max/mean accuracy, tumor volume improvement).
  • Phantom testing (NEMA NU-2, Adult and Pediatric NEMA phantoms, Small Pool phantom) comparing AiCE2 to AiCE1 and conventional methods across quantitative metrics (SUVmean, BGV, CRC, SNR) and for artifact absence.
• Deviceless PET Respiratory Gating:
  • Bench tests for AI operational mode (equivalence to external device gating, improvements in SUV max/mean, tumor volume).
  • Evaluation against predicate DRG1 using reconstructed clinical raw data and quantified outputs.

7. The Type of Ground Truth Used

• For AiCE-i for PET (AiCE2):
  • Phantom Studies: Objective, physics-based ground truth (e.g., known sphere sizes, activity concentrations) for quantitative metrics like SUV, CRC, BGV, SNR.
  • Clinical Image Evaluation: Expert consensus/opinion of three nuclear medicine physicians for subjective assessments like diagnostic quality, image sharpness, and noise levels.
• For Deviceless PET Respiratory Gating (DRG2):
  • Bench Tests/Comparison to DRG1: Quantitative measurements of SUV (max and mean) and tumor volume from reconstructed data, likely compared against a known or established ground truth from reference reconstructions.
  • Clinical Image Evaluation: Expert consensus/opinion of three nuclear medicine physicians for subjective assessments related to diagnostic quality and motion correction effectiveness.

8. The Sample Size for the Training Set

• For AiCE-i for PET (AiCE2): Subset assembled from FDG studies of sixteen (16) cancer patients.
• For Deviceless PET Respiratory Gating (DRG2): FDG studies of 27 cancer patients.

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

The text indicates that both AI algorithms (AiCE2 and DRG2) use deep learning artificial neural network methods. The ground truth for training these networks is implicitly derived from the input PET data itself, with the algorithms learning statistical properties of signal and noise or motion patterns.

• For AiCE-i for PET: The algorithm was "trained to automatically adapt to different noise levels to produce consistently high-quality images." This suggests the training data contained examples of both "noisy" input and perhaps "ideal" or "denoised" outputs (or features that guided the network to achieve denoised outputs with improved image quality), where the "ground truth" was likely the desired image characteristics or underlying signal.
• For Deviceless PET Respiratory Gating: The neural network was "trained on FDG studies... to extract motion information from acquired PET data and to generate a corresponding gating signal." This implies the "ground truth" for training involved identifying and characterizing respiratory motion within the raw PET data, possibly using external motion tracking data if available during training, or highly curated datasets where experts delineated motion patterns. The text does not explicitly state how this ground truth was established, only that it was trained on these patient studies.

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The Diagnostic Ultrasound System Aplio i900 Model TUS-AI900, Aplio i800 Model TUS-AI800, and Aplio i700 Model TUS-AI700 are indicated for the visualization of structures, and dynamic processes with the human body using ultrasound and to provide image information for diagnosis in the following clinical applications: fetal, abdominal, intra-operative (abdominal), pediatric, small organs (thyroid, breast and testicle), trans-vaginal, trans-rectal, neonatal cephalic, adult cephalic, cardiac (both adult and pediatric), peripheral vascular, transesophageal, musculo-skeletal (both conventional and superficial), laparoscopic and thoracic/pleural. This system provides high-quality ultrasound images in the following modes: B mode, M mode, Continuous Wave, Color Doppler, Pulsed Wave Doppler, Power Doppler and Combination Doppler, as well as Speckle-tracking, Tissue Harmonic Imaging, Combined Modes, Shear wave, Elastography, and Acoustic attenuation mapping. This system is suitable for use in hospital and clinical settings by physicians or appropriately trained healthcare professionals.

In addition to the aforementioned indications for use, when EUS transducer GF-UCT180 and BF-UC190F are connected, Aplio i800 Model TUS-AI800/E3 provides image information for diagnosis of the upper gastrointestinal tract and surrounding organs, airways, tracheobronchial tree and esophagus.

The Aplio i900 Model TUS-AI900, Aplio i800 Model TUS-AI800 and Aplio i700 Model TUS-AI700, V9.0 are mobile diagnostic ultrasound systems. These systems are Track 3 devices that employ a wide array of probes including flat linear array, convex, and sector array with frequency ranges between approximately 2MHz to 33MHz.

This FDA 510(k) clearance letter details the substantial equivalence of the Aplio i900, Aplio i800, and Aplio i700 Software V9.0 Diagnostic Ultrasound System to its predicate device. The information provided specifically focuses on the validation of new and improved features, with particular attention to the 3rd Harmonic Imaging (3-HI), a new deep learning (DL) enabled filtering process.

Acceptance Criteria and Device Performance for 3rd Harmonic Imaging (3-HI)

Detailed Study Information

1. Acceptance Criteria and Reported Device Performance

(See table above)

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

• 3rd Harmonic Imaging (3-HI) Clinical Evaluation:
  • Sample Size: 30 patients.
  • Data Provenance: Previously acquired data from a U.S. clinical site (retrospective). Patients were selected to ensure diverse demographic characteristics representative of the intended U.S. patient population, including a wide range of body mass indices (18.5-36.3 kg/m²), roughly equivalent numbers of males and females, and ages ranging from 23-89 years old.
• 3rd Harmonic Imaging (3-HI) Phantom Study:
  • Sample Size: Five abdominal phantoms.
  • Data Provenance: Phantom data.

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

• 3rd Harmonic Imaging (3-HI) Clinical Evaluation:
  • Number of Experts: Three (3).
  • Qualifications: U.S. board-certified radiologists.

4. Adjudication Method for the Test Set

• 3rd Harmonic Imaging (3-HI) Clinical Evaluation:
  • Adjudication Method: Blinded observer study. The three radiologists compared images with 3-HI to images without 3-HI (predicate functionality) using a 5-point ordinal scale. The median score was then compared with the middle score of 3.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Yes, a MRMC-like comparative effectiveness study was done for 3-HI's clinical evaluation.
• Effect Size: The statistical analysis demonstrated that scores for 3-HI were higher than the middle score of 3 for spatial resolution, contrast resolution, and artifact suppression. This indicates that human readers (radiologists) rated images with 3-HI as improved compared to those without.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance)

• Yes, a standalone study was performed for 3-HI in the phantom study. The phantom studies objectively examined lateral and axial resolution, slice resolution, contrast-to-noise ratio (CNR), reverberation artifact suppression, and frequency spectra without human interpretation.

7. The Type of Ground Truth Used

• 3rd Harmonic Imaging (3-HI) Clinical Evaluation:
  • Type of Ground Truth: Expert consensus (from the three board-certified radiologists) on image quality metrics (spatial resolution, contrast resolution, artifact suppression) through a blinded comparison against predicate functionality. The initial selection of patient images included "representative focal pathologies" suggesting clinical relevance in the images themselves.
• 3rd Harmonic Imaging (3-HI) Phantom Study:
  • Type of Ground Truth: Objective measurements against known physical properties and targets within the phantoms.

8. The Sample Size for the Training Set (for 3-HI)

• The document explicitly states that the "The validation data set [30 patients] was entirely independent of the data set used to train the algorithm during its development." However, the actual sample size for the training set is not provided in the given text.

9. How the Ground Truth for the Training Set Was Established (for 3-HI)

• This information is not provided in the given text, beyond the statement that the algorithm was "locked upon completion of development" and had "no post-market, continuous learning capability."

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This device is a digital radiography/fluoroscopy system used in a diagnostic and interventional angiography configuration. The system is indicated for use in diagnostic and angiographic procedures for blood vessels in the heart, brain, abdomen and lower extremities.

αEvolve Imaging is an imaging chain intended for adults, with Artificial Intelligence Denoising (AID) designed to reduce noise in real-time fluoroscopic images and signal enhancement algorithm, Multi Frequency Processing (MFP).

The Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging, is an interventional X-ray system with a floor mounted C-arm as its main configuration. An optional ceiling mounted C-arm is available to provide a bi-plane configuration where required. Additional units include a patient table, X-ray high-voltage generator and a digital radiography system. The C-arms can be configured with designated X-ray detectors and supporting hardware (e.g. X-ray tube and diagnostic X-ray beam limiting device). The Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging includes αEvolve Imaging, an imaging chain intended for adults, with Artificial Intelligence Denoising (AID) designed to reduce noise in real-time fluoroscopic images and signal enhancement algorithm, Multi Frequency Processing (MFP).

Here's an analysis of the acceptance criteria and the study proving the device meets them, based solely on the provided FDA 510(k) summary:

Overview of the Device and its New Feature:

The device is the Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging. It's an interventional X-ray system. The new feature, αEvolve Imaging, includes Artificial Intelligence Denoising (AID) to reduce noise in real-time fluoroscopic images and a signal enhancement algorithm, Multi Frequency Processing (MFP). The primary claim appears to be improved image quality (noise reduction, sharpness, contrast, etc.) compared to the previous version's (V9.5) "super noise reduction filter (SNRF)."

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary does not explicitly state "acceptance criteria" with numerical thresholds for each test. Instead, it describes various performance evaluations and their successful outcomes. For the clinical study, the success criteria are clearly defined.

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

The 510(k) summary provides the following information about the clinical test set:

• Clinical Dataset Source: Patient image sequences were acquired from three hospitals:
  • Memorial Hermann Hospital (Houston, Texas, USA)
  • Waikato Hospital (Hamilton, New Zealand)
  • Saiseikai Kumamoto Hospital (Kumamoto, Japan)
• Data Provenance: The study used retrospective "patient image sequences" for side-by-side comparison. The summary does not specify if the acquisition itself was prospective or retrospective, but the evaluation of pre-existing sequences makes it a retrospective study for the purpose of algorithm evaluation.
• Sample Size: The exact number of patient image sequences or cases used in the clinical test set is not specified in the provided document. It only mentions that the sequences were split into four BMI subgroups.

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

• Number of Experts: The document states the clinical comparison was "reviewed by United States board-certified interventional cardiologists." The exact number of cardiologists is not specified.
• Qualifications: "United States board-certified interventional cardiologists." No mention of years of experience or other specific qualifications is provided.

4. Adjudication Method for the Test Set

The document describes a "side-by-side comparison" reviewed by experts in the clinical performance testing section. For the overall preference and individual image quality metrics, statistical tests (Wilcoxon signed rank test and Binomial test) were used. This implies that the experts rated or expressed preference for both AID and SNRF images, and these individual ratings/preferences were then aggregated and analyzed.

The exact adjudication method (e.g., 2+1, 3+1 consensus) for establishing a ground truth or a final decision on image quality aspects is not explicitly stated. It seems each expert provided their assessment, and these assessments were then statistically analyzed for superiority rather than reaching a consensus for each image pair.

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

• MRMC Study: Yes, a type of MRMC comparative study was conducted. The clinical performance testing involved multiple readers (US board-certified interventional cardiologists) evaluating multiple cases (patient image sequences).

• Effect Size of Human Readers' Improvement with AI Assistance: The study directly compared AID-processed images to SNRF-processed images in a side-by-side fashion. It doesn't measure how much humans improve with AI assistance in a diagnostic task (e.g., how much their accuracy or confidence improves when using AI vs. not using AI). Instead, it measures the perceived improvement in image quality of the AI-processed images when evaluated by human readers.

  • The study determined: "the mean score of the AID imaging chain images was significantly higher than that of the SNRF imaging chain with regard to sharpness, contrast, confidence, noise, and the absence of image artifacts."
  • And for overall preference, "the Binomial test found that the image sequences denoised by AID were chosen significantly more than 50% of the time."

  This indicates a statistically significant preference for and higher perceived image quality in AID-processed images by readers. However, it does not quantify diagnostic performance improvement with AI assistance, as it wasn't a study of diagnostic accuracy but rather image quality assessment. The "confidence" metric might hint at improved reader confidence using AID images, but it's not a direct measure of diagnostic effectiveness.

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

Yes, extensive standalone performance testing of the AID algorithm was conducted through "Performance Testing – Bench" and "Image Quality Evaluations." This involved objective metrics and phantom studies without human subjective assessment.

Examples include:

• Change in Image Level, Noise and Structure
• Signal-to-Variance Ratio (SVR) and Signal-to-Noise Ratio (SNR)
• Modulation Transfer Function (MTF)
• Robustness to Detector Defects (visual comparison, but the algorithm's output is purely standalone)
• Normalizes Noise Power Spectrum (NNPS)
• Image Lag Measurement
• Contrast-to-Noise Ratio of a Low Contrast Object
• Contrast-to-Noise Ratio of a High Contrast Object

7. The Type of Ground Truth Used

• For Bench Testing: The ground truth for bench tests was primarily established through physical phantoms and objective image quality metrics. For example, the anthropomorphic chest phantom, low-contrast phantom, and flat field fluoroscopic images provided known characteristics against which AID and SNRF performance were measured using statistical tests.
• For Clinical Study: The ground truth for the clinical reader study was established by expert opinion/subjective evaluation (preference and scores for sharpness, contrast, noise, confidence, absence of artifacts) from "United States board-certified interventional cardiologists." There is no mention of a more objective ground truth like pathology or outcomes data for the clinical image evaluation.

8. The Sample Size for the Training Set

The document does not provide any information about the sample size used for the training set of the Artificial Intelligence Denoising (AID) algorithm.

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

The document does not provide any information about how the ground truth for the training set was established. It describes the AID as "Artificial Intelligence Denoising (AID) designed to reduce noise," implying a machine learning approach, but details on its training are missing from this summary.

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Self-Propelled CT Scan Base Kit, CGBA-035A:
The movable gantry base unit allows the Aquilion ONE (TSX-308A) system to be installed in the same procedure room as the INFX-8000C system, enabling coordinated clinical use within a shared workspace. This configuration provides longitudinal positioning along the z-axis for image acquisition.

Alphenix, INFX-8000C/B, INFX-8000C/S, V9.6 with Calculated DAP:
This device is a digital radiography/fluoroscopy system used in a diagnostic and interventional angiography configuration. The system is indicated for use in diagnostic and angiographic procedures for blood vessels in the heart, brain, abdomen and lower extremities. The Calculated Dose Area Product (DAP) feature provides an alternative method for determining dose metrics without the use of a physical area dosimeter. This function estimates the cumulative reference air kerma, reference air kerma rate, and cumulative dose area product based on system parameters, including X-ray exposure settings, beam hardening filter configuration, beam limiting device position, and region of interest (ROI) filter status. The calculation method is calibration-dependent, with accuracy contingent upon periodic calibration against reference measurements.

The Alphenix 4DCT is composed of the INFX-8000C interventional angiography system and the dynamic volume CT system, Aquilion ONE, TSX-308A. This combination enables patient access and efficient workflow for interventional procedures. Self-Propelled CT Scan Base Kit, CGBA-035A, is an optional kit intended to be used in conjunction with an Aquilion ONE / INFX-8000C based IVR-CT system. This device is attached to the Aquilion ONE CT gantry to support longitudinal movement and allow image acquisition in the z-direction (Z-axis), both axial and helical. When this option is installed, the standard CT patient couch is replaced with the fixed catheterization table utilized by the interventional x-ray system, INFX-8000C. The Self-Propelled CT Scan Base Kit, CGBA-035A, will be used as part of an Aquilion ONE / INFX-8000C based IVR-CT system. Please note, the intended uses of the Aquilion ONE CT System and the INFX-8000C Interventional X-Ray System remain the same. There have been no modifications made to the imaging chains in these FDA cleared devices and the base system software remains the same. Since both systems will be installed in the same room and to prevent interference during use, system interlocks have been incorporated into the systems.

The Alphenix, INFX-8000C/B, INFX-8000C/S, V9.6 with Calculated DAP, is an interventional x-ray system with a ceiling suspended C-arm as its main configuration. Additional units include a patient table, x-ray high-voltage generator and a digital radiography system. The C-arms can be configured with designated x-ray detectors and supporting hardware (e.g. x-ray tube and diagnostic x-ray beam limiting device). The INFX-8000C system incorporates a Calculated Dose Area Product (DAP) feature, which provides an alternative method for determining dose metrics without the use of a physical area dosimeter. This function estimates the cumulative reference air kerma, reference air kerma rate, and cumulative dose area product based on system parameters, including X-ray exposure settings, beam hardening filter configuration, beam limiting device position, and region of interest (ROI) filter status. The calculation method is calibration-dependent, with accuracy contingent upon periodic calibration against reference measurements.

N/A

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Vantage Fortian/Orian 1.5T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

• Proton density (PD) (also called hydrogen density)
• Spin-lattice relaxation time (T1)
• Spin-spin relaxation time (T2)
• Flow dynamics
• Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Fortian (Model MRT-1550/WK, WM, WO, WQ)/Vantage Orian (Model MRT-1550/U3, U4, U7, U8) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. These Vantage Fortian/Orian models use 1.4 m short and 4.1 tons light weight magnet. They include the Canon Pianissimo™ Sigma and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole-body coil of these Vantage Fortian/Orian models provide the maximum field of view of 55 x 55 x 50 cm and include the standard (STD) gradient system.

The Vantage Orian (Model MRT-1550/ UC, UD, UG, UH, UK, UL, UO, UP) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian models use 1.4 m short and 4.1 tons light weight magnet. They include the Canon Pianissimo™ and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole-body coil of these Vantage Orian models provide the maximum field of view of 55 x 55 x 50 cm. The Model MRT-1550/ UC, UD, UG, UH, UK, UL, UO, UP includes the XGO gradient system.

This system is based upon the technology and materials of previously marketed Canon Medical Systems MRI systems and is intended to acquire and display cross-sectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body. The Vantage Fortian/Orian MRI System is comparable to the current 1.5T Vantage Fortian/Orian MRI System (K240238), cleared April 12, 2024, with the following modifications.

Acceptance Criteria and Study for Canon Medical Systems Vantage Fortian/Orian 1.5T with AiCE Reconstruction Processing Unit for MR

This document outlines the acceptance criteria and the study conducted to demonstrate that the Canon Medical Systems Vantage Fortian/Orian 1.5T with AiCE Reconstruction Processing Unit for MR (V10.0) device meets these criteria, specifically focusing on the new features: 4D Flow, Zoom DWI, and PIQE.

The provided text focuses on the updates in V10.0 of the device, which primarily include software enhancements: 4D Flow, Zoom DWI, and an extended Precise IQ Engine (PIQE). The acceptance criteria and testing are described for these specific additions.

1. Table of Acceptance Criteria and Reported Device Performance

The general acceptance criterion for all new features appears to be demonstrating clinical acceptability and performance that is either equivalent to or better than conventional methods, maintaining image quality, and confirming intended functionality. Specific quantitative acceptance criteria are not explicitly detailed in the provided document beyond qualitative assessments and comparative statements.

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

• 4D Flow & Zoom DWI: Evaluated utilizing phantom images and "representative volunteer images." Specific numbers for volunteers are not provided.
• PIQE Clinical Image Review Study:
  • Subjects: A total of 75 unique subjects.
  • Scans: Comprising a total of 399 scans.
  • Reconstructions: Each scan was reconstructed multiple ways with or without PIQE, totaling 1197 reconstructions for scoring.
  • Data Provenance: Subjects were from two sites in USA and Japan. The study states that although the dataset includes subjects from outside the USA, the population is expected to be representative of the intended US population due to PIQE being an image post-processing algorithm that is not disease-specific and not dependent on factors like population variation or body habitus.

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

• PIQE Clinical Image Review Study:
  • Number of Experts: 14 USA board-certified radiologists/cardiologists.
  • Distribution: 3 experts per anatomy (Body, Breast, Cardiac, Musculoskeletal (MSK), and Neuro).
  • Qualifications: "USA board-certified radiologists/cardiologists." Specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

• PIQE Clinical Image Review Study: The study describes a randomized, blinded clinical image review study. Images reconstructed with either the conventional method or the new PIQE method were randomized and blinded to the reviewers. Reviewers scored the images independently using a modified 5-point Likert scale. Analytical methods used included Gwet's Agreement Coefficient for reviewer agreement and Generalized Estimating Equations (GEE) for differences between reconstruction techniques, implying a statistical assessment of agreement and comparison across reviewers rather than a simple consensus adjudication method (e.g., 2+1, 3+1).

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Yes, an MRMC comparative effectiveness study was done for PIQE.
• Effect Size of Human Readers' Improvement with AI vs. Without AI Assistance: The document states that "the Reviewers' scoring confirmed that: (a) PIQE generates higher spatial in-plane resolution images from lower resolution images (with the ability to triple the matrix dimensions in both in-plane directions, i.e. a factor of 9x); (b) PIQE contributes to ringing artifact reduction, denoising and increased sharpness; (c) PIQE is able to accelerate scanning by reducing the acquisition matrix only, while maintaining clinical matrix size and image quality; and (d) PIQE benefits can be obtained on regular clinical protocols without requiring acquisition parameter adjustment."
  • While it reports positive outcomes ("scored on average at, or above, clinically acceptable," "strong agreement at the 'good' and 'very good' level"), it does not provide a quantitative effect size (e.g., AUC difference, diagnostic accuracy improvement percentage) of how much human readers improve with AI (PIQE) assistance compared to without it. The focus is on the quality of PIQE-reconstructed images as perceived by experts, rather than the direct impact on diagnostic accuracy or reader performance metrics. It confirms that the performance is "similar or better" compared to conventional methods.

6. Standalone (Algorithm Only) Performance Study

• Yes, standalone performance was conducted for PIQE and other features.
  • 4D Flow and Zoom DWI: Evaluated using phantom images, which represents standalone, objective measurement of the algorithm's performance against known physical properties.
  • PIQE: Bench testing was performed on typical clinical images to evaluate metrics like Edge Slope Width (sharpness), Ringing Variable Mean (ringing artifacts), Signal-to-Noise ratio (SNR), and Contrast Ratio. This is an algorithmic-only evaluation against predefined metrics, without direct human interpretation as part of the performance metric.

7. Type of Ground Truth Used

• 4D Flow & Zoom DWI:
  • Phantom Studies: Known physical values (e.g., known flow values for velocity measurement, known distortion levels, known ADC values).
• PIQE:
  • Bench Testing: Quantitative imaging metrics derived from the images themselves (Edge Slope Width, Ringing Variable Mean, SNR, Contrast Ratio) are used to assess the impact of the algorithm. No external ground truth (like pathology) is explicitly mentioned here, as the focus is on image quality enhancement.
  • Clinical Image Review Study: Expert consensus/opinion (modified 5-point Likert scale scores from 14 board-certified radiologists/cardiologists) was used as the ground truth for image quality, sharpness, ringing, SNR, and feature conspicuity, compared against images reconstructed with conventional methods. No pathology or outcomes data is mentioned as ground truth.

8. Sample Size for the Training Set

The document explicitly states that the 75 unique subjects used in the PIQE clinical image review study were "separate from the training data sets." However, it does not specify the sample size for the training set used for the PIQE deep learning model.

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 for PIQE was established. It only mentions that the study test data sets were separate from the training data sets.

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This device is indicated to acquire and display cross-sectional volumes of the whole body (abdomen, pelvis, chest, extremities, and head) of adult patients.

TSX-501R 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.

CT Scanner TSX-501R/1 V11.1 employs a next-generation X-ray detector unit (photon counting detector unit), which allows images to be obtained based on X-rays with different energy levels. 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 study that proves the device meets them, based on the provided 510(k) clearance letter.

It's important to note that a 510(k) summary typically doesn't provide the full, granular detail of a clinical study report. The information often indicates what was tested and the conclusion, but less about the specific methodologies, statistical thresholds for acceptance, or detailed performance metrics.

Understanding the Context: 510(k) Clearance

This document is a 510(k) clearance letter for a new CT scanner (CT Scanner TSX-501R/1 V11.1). The primary goal of a 510(k) submission is to demonstrate "substantial equivalence" to a legally marketed predicate device, not necessarily to prove absolute safety and effectiveness through extensive new clinical trials (which is more typical for a PMA - Premarket Approval). Therefore, the "acceptance criteria" and "study" described here are geared towards demonstrating this equivalence.

The core technology difference is the shift from an Energy Integrating Detector (EID) in the predicate to a Photon Counting Detector in the new device. The testing focuses on ensuring this new detector performs equivalently or better in terms of image quality and safety.

Acceptance Criteria and Reported Device Performance

Given the nature of a 510(k) for a CT scanner's hardware update (new detector), the "acceptance criteria" are implicitly tied to demonstrating equivalent or improved image quality and safety compared to the predicate device. The performance is assessed through bench testing with phantoms and review of clinical images.

Table of Acceptance Criteria and Reported Device Performance:

Study Details:

1. Sample Size Used for the Test Set and Data Provenance:

   • Test Set (Clinical Images): The specific number of clinical images/cases reviewed is not provided. The text states "Representative chest, abdomen, brain and MSK diagnostic images." This implies a selection of images from various body regions.
   • Data Provenance: The document does not specify the country of origin for the clinical images. It also does not explicitly state whether the data was retrospective or prospective, though for a 510(k) supporting equivalence, retrospective data collection for image review is common.

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

   • Number of Experts: The document states "reviewed by American Board-Certified Radiologists." The specific number is not provided.
   • Qualifications: "American Board-Certified Radiologists." This indicates a high level of qualification and experience in medical imaging interpretation.

3. Adjudication Method for the Test Set:

   • The document does not specify an adjudication method (like 2+1 or 3+1) for the clinical image review. It simply states they were "reviewed by American Board-Certified Radiologists" and "it was confirmed that the reconstructed images using the subject device were of diagnostic quality." This implies a consensus or individual assessment of diagnostic quality, but the process is not detailed.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • Was it done? No, a formal MRMC comparative effectiveness study demonstrating how human readers improve with AI vs. without AI assistance was not conducted or described for this submission. This makes sense as the device is a CT scanner itself, not an AI-assisted diagnostic software. The clinical image review was to confirm diagnostic quality of the images produced by the new scanner, not to assess reader performance with or without an AI helper.

5. Standalone (Algorithm Only) Performance:

   • Was it done? Yes, in a sense. The "bench testing" focusing on Objective Image Quality Evaluations and Fundamental Properties of the Photon Counting Detector can be considered "standalone" performance for the device's imaging capabilities. These tests used phantoms and measured technical specifications without human interpretation as the primary endpoint. The device's stated function is to acquire and display images, so its "standalone" performance is its ability to produce good images.

6. Type of Ground Truth Used:

   • Bench Testing (Phantoms): The ground truth is the physical properties of the phantoms and the expected performance characteristics based on established physics and engineering principles (e.g., a known object size for MTF, known density for CT number accuracy).
   • Clinical Images: The ground truth for confirming "diagnostic quality" is expert consensus/opinion from American Board-Certified Radiologists. It's an assessment of whether the image contains sufficient information and clarity for diagnostic purposes, not necessarily a comparison to a biopsy or long-term outcome.

7. Sample Size for the Training Set:

   • The document does not mention a training set in the context of typical AI/machine learning development. This device is a CT scanner hardware system, not an AI diagnostic algorithm that learns from training data. Therefore, the concept of a "training set" as it relates to AI models is not applicable here.

8. How Ground Truth for the Training Set Was Established:

   • As stated above, the concept of a "training set" as applied to AI/machine learning development does not directly apply to this CT scanner hardware submission. The device's performance is based on its physical design and engineering, not on learning from a large dataset.

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