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The Diagnostic Ultrasound Systems 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 usinq ultrasound and to provide image information for diaqnosis in the following clinical applications: fetal, abdominal, intra-operative (abdominal), pediatric, small orqans, trans-vaqinal, trans-rectal, neonatal cephalic, adult cephalic, cardiac (both adult and pediatric), peripheral vascular, transesophageal, musculo-skeletal (both conventional and superficial) and laparoscopic.

The Aplio i900 Model TUS-Al900, Aplio i800 Model TUS-Al800 and Aplio i700 Model TUS-Al700, V2.1 are mobile diagnostic ultrasound systems. These systems are Track 3 devices that employ a wide array of probes including flat linear array, convex linear array, and sector array with frequency ranges between approximately 2 MHz to 20 MHz.

Here's a breakdown of the acceptance criteria and the study details for the Aplio i900/i800/i700 Diagnostic Ultrasound System, V2.1, based on the provided text:

Acceptance Criteria and Device Performance

The provided document primarily focuses on demonstrating substantial equivalence to a predicate device, rather than explicit numerical acceptance criteria for a novel AI feature. However, it does highlight the performance of the 2D WMT function.

Table of Acceptance Criteria and Reported Device Performance

Study Details

This document describes a performance study conducted to support the substantial equivalence claim, specifically focusing on the new "2D WMT" feature.

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

   • Sample Size: 10 patients.
   • Data Provenance: Not specified (e.g., country of origin). It is also not specified whether the data was retrospective or prospective, though the description "representative clinical images were obtained" suggests prospective data collection or selection for the purpose of this validation.

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

   • Number of Experts: Three (3) clinicians.
   • Qualifications of Experts: Not specified beyond "clinicians."

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

   • Not explicitly stated. The text mentions "initial contour trace lines created by the clinicians showed little differences," implying that the 3 clinicians each performed measurements and their results were compared, rather than a formal adjudication process to establish a single "ground truth" per case. The low coefficient of variation suggests a high degree of agreement among them.

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:

   • A comparative effectiveness study was conducted regarding workflow improvement. It was concluded that using the 2D WMT full-assist function resulted in reduced operation time over that of the predicate device.
   • Effect Size: The document states that the new feature "resulted in reduced operation time" but does not provide a quantitative effect size (e.g., percentage reduction in time, average time saved).

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

   • The term "2D WMT full-assist function" suggests that this feature is intended to assist a human operator. The evaluation of reduced operation time implies a human-in-the-loop scenario. There is no explicit mention of a standalone algorithm performance study without human interaction in this document. The "initial contour setting" is described as being "created by the clinicians," further supporting that it's not a fully autonomous AI system.

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

   • The ground truth appears to be based on expert consensus/measurement by three clinicians. The measurements of "major parameters EDV, ESV, Long. Strain Inner, Radial Strain, Total and Circumferential Strain Inner" by these clinicians were used for comparison and to assess variability.

7. The sample size for the training set:

   • Not specified. The document primarily details the performance study for the modified device, not the development or training of any AI components. The 2D WMT is mentioned as a "previously cleared feature implemented on subject device" with a "newly implemented" auto initial contour setting. This suggests the "AI" (if any, related to auto contour) was likely trained prior to this submission, and its training data is not discussed here.

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

   • Not specified, as the training set details are not provided in this regulatory submission.

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Vantage Galan 3T 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

Contrast agent use is restricted to the approved drug indications. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Galan 3T (Model MRT-3020) is a 3 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Galan 3T uses 1.6m short and 6.4 tons light weight magnet. It includes the Toshiba Pianissimo™ technology (scan noise reduction technology). The design of the gradient coil and the WB coil of the Vantage Galan 3T provides the maximum field of view of 50 x 50 x 45 cm. The 3T Vantage Galan MRI System is comparable to the current 3T Vantage Titan MRI System (K152371), cleared October 23rd, 2015 with the following modifications.

The provided text is a 510(k) Premarket Notification for the Toshiba Vantage Galan 3T MRI System. This document asserts substantial equivalence to a predicate device and does not contain detailed information about acceptance criteria or specific studies proving device performance against those criteria as would be found in a clinical study report. Therefore, I cannot extract the information required in your request.

The document states:

• "No change from the previous predicate submission, K152371." regarding imaging performance parameters.
• "The test methods used are the same as those submitted in the previously cleared submissions (K152371)." regarding design control activities.
• "Based upon bench testing, phantom imaging, volunteer clinical imaging, successful completion of software validation and application of risk management and design controls, it is concluded that the subject device is safe and effective for its intended use."

This indicates that the device's performance is asserted to be equivalent to the predicate device and relies on previous testing and adherence to standards rather than new, detailed performance studies for this specific submission.

Therefore, for the specific questions regarding acceptance criteria, reported performance, sample sizes, expert details, adjudication methods, MRMC studies, standalone performance, and ground truth establishment, the information is not present in the provided document.

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The Diagnostic Ultrasound System Xario 200 Model TUS-X200 and Xario 200 Model TUS-X200S are indicated for the visualization of structures, and dynamic processes with the human body using ultrasound and to provide image information for diaqnosis in the following clinical applications: fetal, abdominal, intra-operative(abdominal), laparoscopic, pediatric, small orqans, neonatal cephalic, adult cephalic, trans-rectal, trans-vaginal, musculo-skeletal (conventional), musculo-skeletal (superficial), cardiac adult, cardiac pediatric, trans-esoph(cardiac) and peripheral vessel.

The Xario200 Model TUS-X200 and Model TUS-X200S are mobile diagnostic ultrasound systems. These systems are Track 3 devices that employ a wide array of probes including flat linear array, convex linear array, and sector array with frequency ranges between approximately 2 MHz to 12 MHz.

The provided text describes a 510(k) premarket notification for the Toshiba Medical Systems Corporation's Xario 200 Diagnostic Ultrasound System V5.0. This submission focuses on modifications to a previously cleared device (Xario 200, V3.0) and the introduction of new features and transducers.

The document does not describe acceptance criteria or a specific study proving the device meets those criteria in the way one might expect for a new algorithmic device with quantifiable performance metrics. Instead, it describes substantial equivalence to a predicate device and verification/validation testing against recognized standards.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide a table of acceptance criteria in terms of specific performance metrics (e.g., sensitivity, specificity, accuracy) for an AI component. Instead, it demonstrates performance by stating that the updates "do not raise new questions of safety and effectiveness" and that the added features perform "as expected" and are "substantially equivalent" to predicate devices.

The closest to "reported device performance" is the statement regarding the Superb Micro Vascular Imaging (SMI) feature:

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

The document mentions "Representative clinical images of volunteers were obtained to demonstrate that the implementation of SMI onto the subject device performed as expected." However, it does not specify the sample size (number of images or volunteers) used for this performance testing.

Data provenance: The document does not explicitly state the country of origin or if the data was retrospective or prospective. It only mentions "clinical images of volunteers," which suggests prospective data collection in a clinical setting, but further details are not provided.

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

The document does not specify the number of experts, their qualifications, or how they established the ground truth for any of the performance testing mentioned. This is typical for submissions focused on substantial equivalence where the primary assessment is whether the new features perform comparably to predicate devices, rather than establishing de novo clinical performance metrics against a defined ground truth.

4. Adjudication method for the test set:

The document does not describe any adjudication method used for the test set.

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:

A multi-reader multi-case (MRMC) comparative effectiveness study was not performed or described in this submission. The device is an ultrasound system with modified and new imaging features, not an AI-assisted diagnostic tool that directly aids human readers in interpretation or diagnosis in a quantifiable way measurable by effect size in improved reader performance. The "AI" mentioned (SMI) is an imaging enhancement technique, not an interpretive AI.

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

The performance evaluation described ("SMI was capable of imaging low velocity flow with a significant reduction in clutter noise and was capable of imaging with a high frame rate") appears to be a standalone assessment of the algorithm's technical capabilities in imaging. It describes the intrinsic performance of the SMI algorithm, without explicitly involving human interpretation performance as an outcome measure, which aligns with device modifications for image quality rather than diagnostic AI.

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

The document does not specify a formal ground truth (like pathology or outcomes data) for the evaluation of SMI. The description "SMI was capable of imaging low velocity flow with a significant reduction in clutter noise and was capable of imaging with a high frame rate" implies that the assessment was likely based on qualitative evaluation by imaging experts or quantitative technical measurements of flow and noise reduction, rather than a clinical ground truth for a specific diagnosis.

8. The sample size for the training set:

Ultrasound systems and their imaging enhancements (like SMI, ApliPure, Precision Imaging, etc.) are typically developed through engineering and signal processing, often using simulated data, phantom studies, and then clinical images for refinement and validation. The concept of a distinct "training set" in the context of machine learning, as opposed to engineering development and system optimization, is not mentioned in this document.

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

As no "training set" in the machine learning sense is described, there is no information on how ground truth for a training set was established. The development likely involved iterative engineering adjustments and testing against known benchmarks or expert qualitative assessment of image quality.

Summary of Missing Information:

The provided 510(k) summary is typical for showcasing substantial equivalence for an ultrasound imaging device with updated features rather than a novel AI-driven diagnostic algorithm. Therefore, detailed information about acceptance criteria in terms of clinical performance metrics (sensitivity, specificity), sample sizes for test/training sets, expert qualifications, adjudication methods, or MRMC studies for AI interpretation is largely absent. The focus is on demonstrating that the device remains safe and effective and comparable to previously cleared devices, with new features performing as expected in a technical sense.

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

INFX-8000V, V6.35, is an X-ray system that is capable of radiographic and fluoroscopic studies and is used in an interventional setting. The system consists of a C-arm, which is equipped with an X-ray tube, beam limiter and X-ray receptor, X-ray controller, computers with system and processing software, and a patient radiographic table.

This document describes a 510(k) premarket notification for the Toshiba Medical Systems Corporation's Infinix, INFX-8000V, V6.35 device. This submission is for a modification to a previously cleared device (INFX-8000V, V6.20, K152696). As such, the information provided focuses on the comparative performance of the modified device against its predicate rather than a comprehensive, standalone clinical study with human readers and ground truth established by experts.

Here's an analysis of the provided text in relation to your questions:

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

The document does not explicitly present a table of "acceptance criteria" against "reported device performance" in the format typically seen for a new device's clinical validation. Instead, it states that the testing demonstrates the modified system's performance is "equal to or better than the predicate system." The performance metrics tested are listed, and the implicit acceptance criterion is that the new version performs at least as well as the predicate.

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 specify a "test set" in terms of patient images or clinical data. The testing mentioned appears to be phantom or bench testing rather than clinical performance evaluation on human subjects. Therefore, information about data provenance (country, retrospective/prospective) and sample size for clinical test sets is not applicable or provided. The device is tested against applicable standards published by the International Electromechanical Commission (IEC) for Medical Devices and XR Systems.

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)

Since the testing primarily involved phantom/bench testing and not a clinical study with image interpretation, there is no mention of experts being used to establish a ground truth for a clinical test set.

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

Not applicable, as this was not a clinical study involving human interpretation of clinical images.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No MRMC study was performed or is mentioned. This device does not appear to be an AI-assisted diagnostic tool, but rather an imaging system with technical modifications to its acquisition capabilities and user interface (Virtual ROI, pulse width modulation). The focus is on the performance of the imaging system itself.

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

The testing described (spatial resolution, low contrast resolution, DQE, MTF, etc.) is standalone performance evaluation of the imaging system's technical capabilities, without human in the loop.

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

For the technical performance metrics (spatial resolution, DQE, etc.), the "ground truth" would be established by the physical properties of the phantoms or test objects used and the measurement techniques defined by international standards (IEC). This is not related to expert consensus, pathology, or outcomes data from human patients.

8. The sample size for the training set

Not applicable. This device is an X-ray system, not a machine learning algorithm that requires a "training set" in the context of AI.

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

Not applicable. As stated above, this device does not involve a machine learning training set.

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The Diaqnostic Ultrasound Systems 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 usinq ultrasound and to provide image information for diaqnosis in the following clinical applications: fetal, abdominal, intra-operative (abdominal), pediatric, small orqans, trans-vaqinal, trans-rectal, neonatal cephalic, adult cephalic, cardiac (both adult and pediatric), peripheral vascular, transesophageal, musculo-skeletal (both conventional and superficial) and laparoscopic.

The Aplio i900 Model TUS-Al900, Aplio i800 Model TUS-Al800 and Aplio i700 Model TUS-Al700, 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 linear array, and sector array with frequency ranges between approximately 2 MHz to 20 MHz.

This document is a 510(k) Pre-market Notification for a diagnostic ultrasound system (Aplio i900/i800/i700, V2.0). It focuses primarily on demonstrating substantial equivalence to a predicate device and safety, rather than providing detailed acceptance criteria and study results for specific performance metrics that a standalone AI/device would typically have.

Here's an analysis based on the provided text, addressing your points where possible:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of quantitative acceptance criteria alongside corresponding test results. Instead, it describes performance in qualitative terms (e.g., "expected," "can be obtained," "acceptable," "improves workflow," "within specified range").

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

The document does not specify exact sample sizes for the test sets. It mentions "various phantom studies" and "representative clinical images of volunteer livers" (plural, suggesting more than one, but no specific number).
The provenance for clinical data is described as "volunteer livers" (in-vivo), but no country of origin is specified. The studies appear to be prospective for the clinical images used for verification.

3. Number of Experts Used to Establish Ground Truth and Qualifications

The document does not explicitly state the number or qualifications of experts used to establish ground truth for the test set.

4. Adjudication Method

The document does not mention any adjudication method used for the test set.

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

No MRMC comparative effectiveness study is mentioned. The focus is on demonstrating the functionality and capabilities of the new features.

6. Standalone (Algorithm Only) Performance

The device is a diagnostic ultrasound system. The performance tests described (phantom studies, clinical images) inherently evaluate the algorithms as part of the overall system performance. There is no specific mention of "algorithm-only" performance metrics separate from the device's integrated operation. The new features incorporate advanced processing, and their performance is assessed directly through imaging and measurement tasks.

7. Type of Ground Truth Used

• Phantom studies: Physical phantoms with known properties (e.g., structures, hardness, attenuation coefficients) were used as ground truth.
• Clinical images: For the in-vivo evaluations, it is implied that the clinical images from "volunteer livers" served as the basis for assessing the qualitative aspects of the new features (e.g., whether the color maps were "acceptable," whether the expected features were visualized). However, there is no explicit mention of an external, independent ground truth (e.g., pathology, other imaging modalities) being used for these volunteer studies, beyond the visual and numerical output of the device itself being deemed acceptable by the evaluators.

8. Sample Size for the Training Set

The document describes pre-market notification for a diagnostic ultrasound system, not a device primarily driven by machine learning with distinct training and test sets in the AI sense. It discusses "new features" and "improvements to previously cleared features." Therefore, the concept of a "training set" in the context of AI models is not applicable or mentioned in this document. The system's development likely involved engineering, signal processing, and iterative refinement, not explicit AI model training.

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

As explained in point 8, the concept of a "training set" for AI is not explicitly relevant to the descriptions in this document. Therefore, no information is provided on how ground truth for a training set was established.

In summary:

This 510(k) submission primarily focuses on establishing substantial equivalence for an ultrasound system with new and improved features. It describes functional performance verification through bench and clinical assessments, but it does not provide the detailed, quantitative acceptance criteria, explicit ground truth methodologies, or extensive statistical study results that would typically be expected for a standalone AI/ML-based medical device. The "acceptance criteria" are implied qualitative expectations for the performance of the new features, and the "study" is the verification and validation testing, predominantly bench testing with phantoms and limited clinical image acquisition in volunteers.

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The Vantage Titan system is 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

Contrast agent use is restricted to the approved drug indications. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Titan (Model MRT-1510) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System, previously cleared under K150427. This system is based upon the technology and materials of previously marketed Toshiba 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 provided text does not contain detailed information about specific acceptance criteria, device performance metrics, or a formal study proving the device meets acceptance criteria in the way a clinical trial report would.

The document is a 510(k) summary for a software update to an MRI system (Vantage Titan 1.5T, MRT-1510, V3.6 Software). It asserts substantial equivalence to predicate devices based on safety and effectiveness, and highlights software changes and various testing activities.

Here's a breakdown of the available information in response to your questions:

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

The document does not provide a table of acceptance criteria for specific performance metrics (e.g., sensitivity, specificity, accuracy) or quantitative reported device performance values. Instead, it states that:

• Safety Parameters: The device's safety parameters (Static field strength, Operational Modes, SAR dB/dt display, Operating mode access requirements, Maximum SAR, Maximum dB/dt, Potential emergency condition and means provided for shutdown) are "Same" as the predicate device (Vantage Titan 1.5T, V3.1 (K150427)).
• Imaging Performance Parameters: There is "No change from the previous predicate submission, K150427."
• Conclusion: "Based upon bench testing, phantom imaging, volunteer clinical imaging, successful completion of software validation and application of risk management and design controls, it is concluded that the subject device is safe and effective for its intended use."

This indicates that the acceptance criteria for these aspects were likely the maintenance of equivalence to the predicate device's established performance and safety profiles. However, the exact quantitative criteria are not disclosed in this summary.

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

The document mentions "bench testing, phantom imaging, volunteer clinical imaging" but does not specify the sample size for human subjects (volunteers) or the data provenance (country of origin, retrospective/prospective nature).

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)

This information is not provided in the document. It speaks generally about "Images ... when interpreted by a trained physician," but no details on experts for ground truth establishment.

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

This information is not provided in the document.

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

The document does not mention an MRMC comparative effectiveness study or any AI assistance for human readers. The software updates primarily concern new pulse sequences and automatic positioning assistance (NeuroLine+, CardioLine+, SureVOI), which enhance image acquisition and planning, not necessarily image interpretation by a human reader in an AI-assisted workflow.

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

This document describes an MRI system's software update, which is a diagnostic imaging modality. It does not refer to a standalone algorithm for diagnosis without human-in-the-loop performance. The indications state that images "yield information that can be useful in diagnosis" when "interpreted by a trained physician."

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

The document does not explicitly state the type of ground truth used for specific performance evaluations. Given the nature of MRI systems, it would typically involve clinical assessments, expert review of images, and potentially correlation with other diagnostic modalities or pathology where applicable, but this is not detailed here.

8. The sample size for the training set

The document does not specify a training set size. The software changes involve new pulse sequences and automatic positioning assistance, which would be developed and validated through a combination of engineering testing, phantom studies, and "volunteer clinical imaging," but a distinct "training set" per machine learning terminology is not mentioned.

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

Since a training set with explicitly established ground truth (in the machine learning sense) is not described, this information is not provided.

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This device is indicated to acquire and display cross sectional volumes of the whole body, to include the head, with the capability to imaqe whole orqans in a sinqle 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 orqan. These volume sets can be used to perform specialized studies, usinq indicated software/hardware, of the whole organ by a trained and qualified physician.

FIRST 2.0 is an iterative reconstruction alqorithm intended to reduce exposure dose and improve high contrast spatial resolution for abdomen, pelvis, chest, cardiac and extremities applications.

Aquilion ONE Vision with FIRST 2.0 (CCRS-001B) V7.4 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 Toshiba CT systems. In addition, the subject device incorporates the latest iterative reconstruction technology, FIRST 2.0, intended to reduce exposure dose while maintaining and/or improving image quality.

The provided text describes a 510(k) premarket notification for a Computed Tomography (CT) system named Aquilion ONE Vision with FIRST 2.0 (CCRS-001B) V7.4. The documentation focuses on demonstrating substantial equivalence to a predicate device (Aquilion ONE Vision with FIRST 1.0) by updating an iterative reconstruction algorithm (FIRST 2.0).

Based on the provided document, here's a breakdown of the requested information:

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

The document does not explicitly state "acceptance criteria" in a numerical or pass/fail table format for clinical performance. Instead, it describes performance in terms of improvements or equivalency compared to the predicate device and filtered back projection (FBP).

• Contrast-to-noise ratio
• CT number accuracy
• Uniformity
• Slice sensitivity profile
• Modulation transfer function
• Line pair gauge
• Low contrast detectability
• Standard deviation of noise
• Noise power spectra. |
  | Diagnostic Quality | Representative diagnostic images reviewed by an American Board Certified Radiologist demonstrated that the device produces images of diagnostic quality and performs as intended. |

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

• Test Set Sample Size: The document mentions "Representative diagnostic images... including chest, abdomen and pelvis, extremity and cardiac exams." However, it does not specify the number of images or cases used for this review.
• Data Provenance: The document implies the data was collected from the device itself ("obtained using the subject device"). There is no information about the country of origin of the data or whether it was retrospective or prospective. Given it's a premarket submission for a new version of an existing device, it's likely part of internal validation testing.

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

• Number of Experts: "an American Board Certified Radiologist" – indicates one expert was used.
• Qualifications: "American Board Certified Radiologist" – this implies a board certification, which generally requires specific training, residency, and passing board examinations, demonstrating a certain level of expertise in radiology. The document does not specify the years of experience of this radiologist.

4. Adjudication method for the test set

• Since only one radiologist was used for the diagnostic image review, an adjudication method (like 2+1 or 3+1) was not applicable/performed. The single expert's review served as the 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 MRMC study was mentioned or performed as part of this submission. The evaluation was primarily focused on technical image quality metrics and a single radiologist's review of diagnostic image quality, not the impact on human reader performance with or without AI assistance. The "AI" here (FIRST 2.0) is an iterative reconstruction algorithm, which enhances image quality/dose reduction, rather than an AI-driven diagnostic aid that would typically warrant a comparative reader study.

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

• Yes, an algorithm-only (standalone) performance evaluation was done in terms of quantitative image quality metrics (e.g., contrast-to-noise ratio, spatial resolution, dose reduction claims) using phantoms.
• "A model observer evaluation" directly assessed the algorithm's performance in achieving "equivalent low contrast detectability" with reduced dose, which is a standalone assessment of the algorithm's output.

7. The type of ground truth used

• For quantitative image quality metrics and dose reduction claims: Phantoms (e.g., MITA-FDA phantom) were used to provide a known, controlled ground truth.
• For diagnostic image quality review: The "ground truth" was established by the expert opinion of an American Board Certified Radiologist who reviewed representative images for "diagnostic quality." This is essentially expert consensus (albeit from a single expert).

8. The sample size for the training set

• The document does not provide any information about the sample size used for training the FIRST 2.0 iterative reconstruction algorithm. This information is typically proprietary to the manufacturer and not required in this level of 510(k) summary.

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 training set (if any, as iterative reconstruction algorithms might use phantoms or specific patient data for training their models without needing human-labeled "ground truth" for diagnosis) was established. This detail is also not typically shared in a 510(k) summary.

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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 Lightning 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.

The Aquilion Lightning, TSX-035A/4 and /5, v7.0 is a 16-row CT System that is intended to acquire and display cross-sectional volumes of the whole body, including the head. This system is based upon the technology and materials of previously marketed Toshiba CT systems.

I am sorry, but the provided text is a 510(k) premarket notification for a Computed Tomography (CT) X-ray system (Aquilion Lightning, TSX-035A/4 and /5, V7.0). This type of document is a submission to the FDA to demonstrate that a device is substantially equivalent to a predicate device already on the market.

This specific document does not contain information about the acceptance criteria or a study proving the device meets acceptance criteria in the manner requested (e.g., using metrics like sensitivity, specificity, or performance against a ground truth dataset).

The document primarily focuses on:

• Indications for Use: What the device is intended for.
• Technological Characteristics Comparison: How the new device differentiates from its predicate (e.g., gantry rotation speed, X-ray rated output, patient couch specifications).
• Safety and Performance Standards Conformance: Listing of relevant IEC standards and CFR parts that the device adheres to.
• Testing: Mentions "summary tables detailing the risk analysis and verification/validation testing conducted through bench testing" and "successful completion of software validation." It does not provide details of such studies or specific performance metrics that would be considered acceptance criteria for AI/algorithm performance.

Therefore, I cannot provide the requested information about acceptance criteria, device performance, sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, or training set details because these are not present in the provided text. This document is for a general CT system, not an AI-powered diagnostic algorithm with performance metrics relative to a ground truth dataset.

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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.

INFX-8000C, V6.20, is an X-ray system that is capable of radiographic and fluoroscopic studies and is used in an interventional setting. The system consists of a C-arm, which is equipped with an X-ray tube, beam limiter and X-ray receptor, X-ray controller, computers with system and processing software, and a patient radiographic table.

The provided text describes modifications to an X-ray system (INFX-8000C, V6.20) and its substantial equivalence to a predicate device, rather than a study evaluating an AI-powered medical device against specific clinical acceptance criteria.

Therefore, the requested information regarding acceptance criteria, device performance, sample size, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for an AI device cannot be extracted from this document.

The document primarily focuses on:

• Changes made to the device (flat panel detectors and C-arm support assembly).
• Compliance with regulatory standards and previous clearances.
• Confirmation that the modifications do not change the indications for use or raise new questions of substantial equivalence.

It does not contain information about an AI device or its performance study.

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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 1.0 is an iterative reconstruction algorithm intended to reduce exposure dose and improve high contrast spatial resolution for chest (excluding cardiac), abdomen and pelvis applications. This algorithm is not intended for head or extremity applications.

Aquilion ONE Vision with FIRST 1.0 (CCRS-001A) 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 Toshiba CT systems. In addition, the subject device incorporates the latest iterative reconstruction technology, FIRST 1.0, intended to reduce exposure dose while maintaining and/or improving image quality.

The provided text describes the Aquilion ONE Vision with FIRST 1.0 (CCRS-001A) CT system and its iterative reconstruction algorithm, FIRST 1.0. Here's an analysis of its acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Quantitative Dose Reduction Evaluation: A simulated body phantom (MITA-FDA phantom with a body ellipse surrounding it) was used. This indicates a phantom study, not human data.
• Artifact Reduction: A body phantom was used for truncation and streak artifact assessment. This indicates a phantom study.
• Image Quality Check: Existing clinical data was used. The specific sample size of clinical cases is not provided. The provenance of this clinical data (e.g., country of origin, retrospective/prospective) is not specified.

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

• For the "Image Quality Check" using existing clinical data, one American Board Certified Radiologist reviewed a representative diagnostic image set for chest, abdomen, and pelvis exams. Their specific years of experience are not provided, only that they are "American Board Certified."
• For the quantitative dose reduction and artifact reduction studies, phantoms were used, so expert ground truth establishment for patient images was not directly applicable.

4. Adjudication Method for the Test Set

• For the image quality check, with only one American Board Certified Radiologist reviewing images, there was no adjudication method (e.g., 2+1, 3+1) described.
• For the phantom studies, the assessment was based on objective measurements (e.g., model observer evaluation, image SD values) and visual comparison to AIDR 3D, and thus, an adjudication method for experts was not applicable.

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

• No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was explicitly described. The document mentions a single radiologist's review of diagnostic images and phantom studies. No comparison of human reader performance with and without AI assistance is presented.

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

• Yes, a standalone performance assessment was conducted for FIRST 1.0.
  • Quantitative Dose Reduction Evaluation: This was performed using a "model observer evaluation" on a phantom, indicating an algorithm-only assessment of low contrast detectability.
  • Image Quality Evaluation (Phantom Studies): Various CT image quality metrics (spatial resolution, CT number accuracy, contrast-to-noise ratio, noise properties, uniformity, slice sensitivity profile, low contrast detectability, standard deviation of noise) were measured using phantoms, which are objective algorithm-only assessments.
  • Artifact Reduction (Phantom Studies): Objective measures like image SD values and visual comparisons (implied to be algorithm output comparison) were made.

7. The Type of Ground Truth Used

• Phantom Measurements: For quantitative dose reduction, spatial resolution, CT number accuracy, CNR, noise properties, uniformity, SSP, low contrast detectability, and artifact reduction, the ground truth was derived from objective measurements on phantoms (e.g., MITA-FDA phantom, body phantoms).
• Expert Visual Confirmation: For the "Image quality check" using clinical data, the ground truth for "diagnostic quality" and "no significant artifacts and missing anatomical structures" was established by visual confirmation from a single American Board Certified Radiologist.

8. The Sample Size for the Training Set

• The document does not provide any information regarding the sample size used for training the FIRST 1.0 algorithm.

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

• The document does not provide any information regarding how the ground truth for the training set was established.

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