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The NeuViz 128 Multi-Slice CT Scanner System can be used as a whole body computed tomography X-ray system featuring a continuously rotating X-ray tube and detector array. The acquired X-RAY transmission data is reconstructed by computer into cross-sectional images of the body from either the same axial plane taken at different angles or spiral planes taken at different angles.

The proposed NeuViz 128 Multi-slice CT Scanner System is composed of a gantry, a patient couch, an operator console and includes image acquisition hardware and software, and associated accessories. It is designed to be a head and whole body X-ray computed tomography scanner which features a continuously rotating tube-detector system and functions according to the fan beam principle.

Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

The document describes performance in terms of improvements over Filtered Back Projection (FBP) reconstruction. It does not explicitly state pre-defined "acceptance criteria" with numerical thresholds that the device must meet, but rather reports the observed performance improvements from the testing. The "acceptance criteria" are implied to be achieving demonstrably equivalent or better diagnostic image quality and performance compared to FBP, particularly with dose reduction and improved image characteristics.

2. Sample Size for the Test Set and Data Provenance

• "ClearInfinity" Performance Verification (Quantitative):

  • Sample Size: Not explicitly stated as "test set" for the quantitative phantom studies. These are engineering bench tests using raw datasets.
  • Data Provenance: Raw datasets obtained on NeuViz 128. Implied to be internal testing.

• "ClearInfinity" Clinical Image Evaluation (Reader Study):

  • Sample Size:
    • 30 retrospectively collected clinical cases (for normal dose comparison).
    • 20 retrospectively collected clinical cases (for simulated low dose comparison).
  • Data Provenance: Retrospectively collected clinical cases.
    • For general performance claims, the document states: "US patient-based testing data for ClearInfinity collected from three sites of OK and one site of TX, a total of 445 clinical cases of 297 independent patients." It's unclear if these 445 cases directly constitute the raw data for the specific 30 and 20 cases in the reader study, or a larger pool from which they were selected.

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

• "ClearInfinity" Clinical Image Evaluation (Reader Study):
  • Number of Experts: 3 board-certified radiologists.
  • Qualifications: "board-certified radiologists." No specific years of experience are provided.

4. Adjudication Method

• "ClearInfinity" Clinical Image Evaluation (Reader Study):
  • The document states: "Each image was read by 3 board-certified radiologists who provided an assessment of image quality related to diagnostic use according to a 5-point Likert scale." It does not specify an adjudication method (like 2+1 or 3+1) if there were disagreements among the readers. It implies individual assessments were aggregated or used to determine the overall conclusion of equivalence or betterment.

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

• Was an MRMC study done? Yes, a reader study was performed for "ClearInfinity."
• Effect Size: The document states that the results "indicate that ClearInfinity is equivalent or better than Filtered Back Projection in diagnostic quality" for both normal and low-dose cases. It does not provide a specific quantitative effect size (e.g., AUC improvement, percentage increase in concordance) for how much human readers improve with AI assistance. It focuses on the comparative diagnostic quality of images produced by ClearInfinity versus FBP.

6. Standalone Performance Study (i.e., algorithm only without human-in-the-loop performance)

• Yes, standalone performance was extensively evaluated through "Engineering bench testing" using phantoms. This included quantitative measurements of:
  • Dose reduction capability
  • Low-contrast detectability improvement
  • Image noise reduction
  • Spatial resolution improvement (for ClearInfinity)

7. Type of Ground Truth Used

• Engineering Bench Testing (Phantom Studies): For quantitative metrics, the "ground truth" is established by the known properties of the phantoms (CCT189 and CCT191 MITAIQ LC Phantoms, QA phantom water layer, high-contrast test device) and objective measurements using methods like the channelized Hotelling observer.
• Clinical Image Evaluation (Reader Study): The "ground truth" for diagnostic quality was established by the expert consensus/assessment of 3 board-certified radiologists using a 5-point Likert scale, comparing images reconstructed with FBP and ClearInfinity from the same raw data.

8. Sample Size for the Training Set

• Training Set for ClearInfinity: The document lists "US patient-based testing data for ClearInfinity collected from three sites of OK and one site of TX, a total of 445 clinical cases of 297 independent patients" as performance verification data. It also states ClearInfinity uses a "trained deep learning neural network." However, it does not explicitly state that these 445 cases were used as the training set. It's common for regulatory submissions to mention a larger pool of data used for development/testing, but the specific training set size is not detailed here.

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

• The document mentions "a trained deep learning neural network" for ClearInfinity but does not describe how the ground truth for this training set was established. This information is typically proprietary and part of the manufacturer's internal development process for the AI algorithm.

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The NeuViz 16 Essence Multi-Slice CT Scanner System can be used as a whole body computed tomography X-ray system featuring a continuously rotating X-ray tube and detector array. The acquired X-RAY transmission data is reconstructed by computer into cross-sectional images of the body from either the same axial plane taken at different angles or spiral planes taken at different angles.

The NeuViz 16 Essence Multi-Slice CT Scanner System is composed of a gantry, a patient couch, an operator console and includes image acquisition hardware and software, and associated accessories. It is designed to be a head and whole body X-ray computed tomography scanner which features a continuously rotating tube-detector system and functions according to the fan beam principle.

The system provides the filter back-projection (FBP) and iterative reconstruction algorithm(ClearView cleared in K133373) to reconstruct images. The end user can choose to apply either ClearView or the FBP to the acquired raw data.

The system software is an interactive program used for X-ray scan control, image reconstruction, and image archive/evaluation. It provides the following digital image processing and visualization tools:

• Support following scan speed: 0.5s、0.6s、0.75s、1.0s、1.5s、2.0s.
• · Surview scan
• Dual surview
• · Spiral scan
• Axial scan
• Image reconstruction
• Plan scan
• Patient information management
• Patient information registration
• Protocol selection
• O-Dose
• . Bolus tracking
• SAS
• Home
• Film
• Report
• 2D
• MPR
• 3D
• VE(Virtual Endoscopy)
• Vessel Analysis
• Dicom Viewer
• · Bar code Reader
• Dual Monitor
• Continuous CT
• ClearView
• Dental Analysis
• Virtual Colonoscopy
• Brain Perfusion
• Body Perfusion
• Lung Nodule Analysis

This document describes the Neusoft Medical Systems NeuViz 16 Essence Multi-Slice CT Scanner System (K171198). The information provided focuses on the substantial equivalence claim to its predicate devices, K092742 (NeuViz 16 Multi-Slice CT Scanner System) and K151383 (NeuViz 128 Multi-Slice CT Scanner System).

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a formal table of quantitative acceptance criteria for image quality metrics or a direct comparison of measured performance against specific thresholds. Instead, it states that "The clinical validation was executed as planned and acceptance criteria met for each requirement." It also mentions that "The Results indicated that the images were of diagnostic quality."

For image quality, the document states:
"Some of the bench tests included the sag and the speed of patient support table, the gantry wobble, CT image quality metrics testing including CT number accuracy and uniformity, MTF, noise, slice sensitivity profiles and CTDI." It also states, "Sample images were provided to show the performance of the system in presence of implants."

The conclusions state: "The results of these tests demonstrate that the subject device performs as intended." and "The result of all conducted testing was found acceptable to support the claim of substantial equivalence."

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

The document indicates that a clinical validation was performed, which included "image evaluation...to evaluate images of the brain, chest, abdomen and spine/extremities of the body area." However, it does not specify the sample size (number of patients or images) used for this test set nor the country of origin of the data. It also does not explicitly state whether the data was retrospective or prospective.

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

The document mentions that "An image evaluation was performed...Images were scored using a 5 point Likert scale by a qualified radiologist." This indicates that one qualified radiologist was used for ground truth assessment. Their specific qualifications (e.g., years of experience, subspecialty) are not detailed beyond "qualified radiologist."

4. Adjudication Method for the Test Set:

Based on the information provided, it appears that no specific adjudication method (like 2+1 or 3+1) was used, as only one radiologist is mentioned for scoring the images.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study, nor does it provide an effect size for human reader improvement with or without AI assistance. The study focuses on demonstrating the diagnostic quality of the images produced by the device.

6. Standalone Performance Study:

The information provided describes the performance of the "NeuViz 16 Essence Multi-Slice CT Scanner System" as a standalone medical device capable of image acquisition and reconstruction. The clinical validation assessed whether the images produced by the device were of diagnostic quality. Therefore, a standalone performance assessment (device only, without human interpretation for improving diagnostic accuracy) was implicitly performed in that the output of the device (the images) was evaluated for its diagnostic utility. The study doesn't contrast with a human-in-the-loop scenario.

7. Type of Ground Truth Used:

The ground truth for the clinical validation was established through expert consensus/reader evaluation. Specifically, "Images were scored using a 5 point Likert scale by a qualified radiologist," who determined if the images were of "diagnostic quality."

8. Sample Size for the Training Set:

The document does not provide any information regarding the sample size of a training set. The descriptions focus on the validation of the device and its algorithms (FBP, ClearView), not on the training data for an AI model. "ClearView" is mentioned as an iterative reconstruction algorithm cleared in K133373, but no details about its training data are given in this K171198 submission.

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

Since no information is provided about a training set for an AI model, there is no information on how its ground truth would have been established. The "ClearView" algorithm, where potentially AI/machine learning could be involved, references a previous 510(k) (K133373), and the current document does not detail its development or training.

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The NeuViz Prime Multi-Slice CT Scanner System can be used as a whole body computed tomography X-ray system featuring a continuously rotating X-ray tube and detector array. The acquired X-RAY transmission data is reconstructed by computer into cross-sectional images of the body from either the same axial plane taken at different angles or spiral planes taken at different angles.

The NeuViz Prime Multi-Slice CT Scanner System is composed of a gantry, a patient couch, an operator console and includes image acquisition hardware and software, and associated accessories. It is designed to be a head and whole body X-ray computed tomography scanner which features a continuously rotating tube-detector system and functions according to the fan beam principle. The system provides the filter back-projection (FBP) and iterative reconstruction algorithm(ClearView cleared in K133373) to reconstruct images. The end user can choose to apply either ClearView or the FBP to the acquired raw data. The system software is an interactive program used for X-ray scan control, image reconstruction, and image archive/evaluation. It provides the following digital image processing and visualization tools:

• · Support following scan speed: 0.259s(option), 0.32s(option), 0.374s(option), 0.4s(option), 0.5s, 0.6s, 0.8s, 1.0s, 1.5s, 2.0s.
• . Surview scan
• Dual surview
• Spiral scan
• Axial scan
• Image reconstruction
• Plan scan
• Patient information management
• Patient information registration
• Protocol selection
• O-Dose
• · Bolus tracking
• SAS
• Home
• Film
• Report
• 2D
• MPR
• 3D
• VE(Virtual Endoscopy)
• Vessel Analysis
• Dicom Viewer
• Bar code Reader
• Dual Monitor
• CCT Scan
• ClearView
• iHD
• Cardiac Scan
• Dual Energy Scan and Reconstruction ●
• Dental Analysis
• Virtual Colonoscopy
• Brain Perfusion
• Body Perfusion
• · Lung Nodule Analysis
• Lung Density Analysis
• · Coronary Analysis
• Cardiac Calcium Scoring .
• Cardiac Function Analysis
• Cardiac Viewer
• Fat Analysis
• CTDSA
• Tumor Assessment
• · Preprocessing function
• AVW.Cloud
• · Prism Viewer

The provided document is a 510(k) summary for the NeuViz Prime Multi-Slice CT Scanner System. It describes the device's characteristics and its substantial equivalence to a predicate device but does not contain acceptance criteria for specific performance metrics or detailed results of a study designed to prove the device meets those criteria, especially in an AI context. The document focuses on showing non-inferiority to an existing device rather than meeting specific quantifiable performance targets with clinical evidence in the format you requested for an AI/ML device.

However, I can extract information related to the device's performance characteristics, safety, and the "clinical testing" that was performed, even if it doesn't align perfectly with the AI/ML-focused questions.

Here's an attempt to answer your questions based on the provided text, while acknowledging the limitations for AI-specific criteria:

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

The document does not provide a table of explicit acceptance criteria with numerical targets for clinical performance (e.g., sensitivity, specificity, accuracy for a specific disease detection task). Instead, it states that "the subject device performs as intended" and "NeuViz Prime can be used as defined in its clinical workflow and intended use," and that "The Results indicated that the images were of diagnostic quality."

For image quality metrics, it lists:

• CT number accuracy and uniformity
• MTF (Modulation Transfer Function)
• Noise
• Slice sensitivity profiles
• CTDI (Computed Tomography Dose Index)

The document doesn't report specific numerical acceptance criteria for these image quality metrics, nor does it provide the measured performance values for them. It only states that "The result of all conducted testing was found acceptable to support the claim of substantial equivalence."

It does provide CTDI Dose values for the subject device compared to the predicate:

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

The "clinical testing" involved an "image evaluation" where "sample images were provided to show the performance of the system in presence of implants." This suggests a test set composed of image data.

• Sample Size: Not explicitly stated. The document refers to "images of the brain, chest, abdomen and spine/extremities of the body area," implying multiple images, but no specific count is given.
• Data Provenance: Not explicitly stated. It is likely retrospective data as it describes an "image evaluation" of existing images rather than a prospective clinical trial. The location of data origin (e.g., country) is not mentioned.

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

• Number of Experts: One.
• Qualifications of Experts: "A qualified radiologist." No specific experience level (e.g., "10 years of experience") is provided.

4. Adjudication method for the test set

• Adjudication Method: Not explicitly an adjudication method in the sense of multiple readers reaching consensus. The images were "scored using a 5 point Likert scale by a qualified radiologist." This implies a single-reader assessment rather than a consensus or adjudicated ground truth process.

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: No, a multi-reader multi-case comparative effectiveness study was not reported. The provided document describes a CT scanner system, not an AI-assisted diagnostic tool for which human reader improvement would be typically measured. The "clinical testing" described was an image quality assessment by a single radiologist.

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

• Standalone Performance: Not applicable in the context of this submission. The NeuViz Prime is a CT scanner, a hardware device that generates images. While it has reconstruction algorithms (FBP, ClearView, iHD) and image processing tools (e.g., Lung Nodule Analysis, Cardiac Calcium Scoring), the submission focuses on the overall performance of the imaging system and its substantial equivalence to a predicate device, not on the standalone performance of an AI algorithm intended for diagnostic interpretation. It does mention "The main algorithm of Prism Viewer Application is identifying of substances and calculating of dual energy images," but no standalone performance metrics are provided for this.

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

• Type of Ground Truth: The document refers to an "image evaluation" where images were "scored using a 5 point Likert scale by a qualified radiologist." This points to expert opinion/scoring as the basis for evaluating "diagnostic quality." It does not mention pathology, outcomes data, or a consensus of multiple experts.

8. The sample size for the training set

• Training Set Sample Size: Not applicable/not provided. This document describes the clearance of a CT scanner system, not an AI/ML algorithm that would typically have a distinct training set. While the system's reconstruction algorithms (like ClearView, iHD) would have been developed and "trained" or optimized during their creation, this document does not provide details on their specific training sets.

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

• Ground Truth for Training Set: Not applicable/not provided. Similar to point 8, the document does not discuss the training of AI/ML models. If "ClearView" or other advanced algorithms involved machine learning at their core, the method for establishing their training ground truth is not detailed in this 510(k) summary.

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The NeuViz 128 Multi-Slice CT Scanner System can be used as a whole body computed tomography X-ray system featuring a continuously rotating X-ray tube and detector array. The acquired X-RAY transmission data is reconstructed by computer into cross-sectional images of the body from either the same axial plane taken at different angles or spiral planes taken at different angles.

The NeuViz 128 Multi-slice CT Scanner System is composed of a gantry, a patient couch, an operator console and includes image acquisition hardware and software, and associated accessories. It is designed to be a head and whole body X-ray computed tomography scanner which features a continuously rotating tube-detector system and functions according to the fan beam principle.

The system provides the filter back-projection (FBP) and iterative reconstruction algorithm(ClearView cleared in K133373) to reconstruct images. The end user can choose to apply either ClearView or the FBP to the acquired raw data.

The system software is an interactive program used for X-ray scan control, image reconstruction, and image archive/evaluation. It provides the following digital image processing and visualization tools:

• Support following scan speed:0.374s、0.5s、0.6s、0.8s、1.0s、1.5s、2.0s.
• · Surview scan
• · Dual surview
• o Spiral scan
• o Axial scan
• Image reconstruction
• Plan scan
• Patient information management
• Patient information reqistration
• O Protocol selection
• Bolus Tracking
• CCT scan
• . Cardiac scan
• Multi-phase scan
• O Tube Warm-up
• Film
• Report
• O 2D
• DICOM Viewer O
• O MPR
• 0 3D
• Virtual Endoscopy
• . Dental
• Vessel Analysis
• Virtual Colonoscopy
• Brain Perfusion
• · Body Perfusion
• Lung Nodule Analysis
• Lung Density Analysis
• Coronary Analysis
• Cardiac Calcium Scoring
• Cardiac Function Analysis
• Cardiac Viewer
• Fat Analysis
• CTDSA
• Tumor Assessment

The provided text describes the NeuViz 128 Multi-Slice CT Scanner System (K151383), and its substantial equivalence claims against predicate devices. However, it does not contain detailed acceptance criteria for a specific device performance, nor does it present a study that explicitly details the device meeting such criteria with specific metrics.

The document focuses on non-clinical testing for compliance with various standards (electrical safety, EMC, radiation protection, usability, software lifecycle, risk management, DICOM) and states that "Verification and validation activities (including performance testing, safety testing and simulated use testing) are performed" and "The results of these tests demonstrate that the subject device performs as intended." It also mentions "Sample clinical images were provided within the submission. The image quality has been evaluated in bind state by two certified radiologists."

Therefore, based on the provided text, I cannot complete a table of acceptance criteria and reported device performance, nor fully answer all aspects of your request, as the specific performance metrics and detailed study results are not present.

However, I can extract the available information:

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

This information is not explicitly provided in the document. The text states that the device adheres to various international and national standards (listed in the "Nonclinical Testing" section) and that "Verification and validation activities... are performed" and "The results of these tests demonstrate that the subject device performs as intended." However, specific numerical acceptance criteria (e.g., spatial resolution > X lp/cm, contrast resolution > Y HU) and corresponding reported performance values for the NeuViz 128 are not detailed.

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

• Test Set Sample Size: "Sample clinical images were provided within the submission." The exact number of images or cases is not specified.
• Data Provenance: The country of origin and whether the data was retrospective or prospective are not specified.

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):

• Number of Experts: "two certified radiologists."
• Qualifications of Experts: They are described as "certified radiologists." Further details on their experience level are not specified.

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

The term "adjudication method" is not explicitly mentioned. The document states that image quality was "evaluated in bind state by two certified radiologists," implying a consensus or independent review process, but the specific method (e.g., if one disagreed, what was the next step) is not detailed.

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: An MRMC comparative effectiveness study, particularly one comparing human readers with and without AI assistance, is not described or mentioned in the provided text. The device is a CT scanner, not an AI-powered diagnostic tool explicitly designed to assist human readers in a comparative effectiveness study as described.

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

The document describes the NeuViz 128 as a CT scanner system that performs image acquisition and reconstruction. While it has advanced image processing and visualization tools (e.g., "ClearView" iterative reconstruction, "Lung Nodule Analysis," "Cardiac Function Analysis"), the submission focuses on its performance as an imaging device. A "standalone" performance evaluation in the context of an algorithm replacing human interpretation is not explicitly described. The evaluation mentioned is of "image quality" evaluated by radiologists, suggesting human interpretation of the images produced by the device.

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

The "ground truth" for the image quality evaluation appears to be the expert opinion/assessment of the two certified radiologists on the "sample clinical images." No mention of pathology, outcomes data, or other objective ground truths is included.

8. The sample size for the training set:

• Training Set Sample Size: The document does not mention a training set sample size. The device is a CT scanner, and while it uses algorithms for image reconstruction and analysis, the details of any machine learning training data are not provided in this 510(k) summary.

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

• Ground Truth for Training Set: Since a training set is not mentioned, how its ground truth was established is also not provided.

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The NeuSight PET/CT Scanner System can be used for the functional and anatomical imaging of human bodies and organs. The device is intended for whole body or regional tumor examination, cardiac examination and head examination. The device can assist in radiotherapy planning and be used as a stand-alone head and whole body multislice computed tomography (CT) diagnostic imaging system. Trained doctors can read useful diagnostic information from the image generated.

The NeuSight PET/CT Scanner System is an integrated multi-slice Computed Tomography and Positron Emission Tomography scanner. It uses CT images to correct for non-uniform attenuation of the PET images and it uses integrated CT and PET images to localize emission activity in the patient anatomy. NeuSight System has capabilities for imaging all available PET tracers and CT contrast agents and can provide inherently registered anatomical and functional information via an integrated graphical user interface. The product provide some reconstruct methods, such as FBP、3DRP、OSEM、 ClearView (cleared in K133373) , and some advance algorithms based on OSEM. These advance algorithms can improve the image quality.

The NeuSight PET/CT Scanner System consists of two variants:

• NeuSight PET/CT 64
• NeuSight PET/CT 16

NeuSight PET/CT 16 is designed based on NeuSight PET/CT 64 and has the same hardware configuration with NeuSight PET/CT 64. Their hardware of CT part is the same as NeuViz64 (K121792). In the performance parameters, NeuSight PET/CT 16 only limits the optional scope of partial scan parameters by software in order to different from NeuSight PET/CT 64. There's no essential technological difference between the two types of PET/CT and the safety and effectiveness of these products could be ensured through verification, validation and difference assessment.

The provided text describes the 510(k) summary for the NeuSight PET/CT 64 and NeuSight PET/CT 16 systems. Here's a breakdown of the requested information based on the document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in a quantitative form for device performance. Instead, it relies on substantial equivalence to a predicate device (GE Discover VCT System, K050559) and compliance with various international standards for safety and performance. The performance claim is that the device "performs as intended" and its image quality was "evaluated in a blind state by a certified radiologist."

While specific quantitative acceptance criteria are not provided in this summary, the general performance claims are:

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

The document states: "Sample clinical images were provided within the submission."

• Sample size: Not specified. It only mentions "sample clinical images."
• Data provenance: Not specified (e.g., country of origin, retrospective or prospective).

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

• Number of experts: Singular, "a certified radiologist."
• Qualifications of experts: "certified radiologist." No further details like years of experience are provided in this summary.

4. Adjudication Method for the Test Set

The document states: "The image quality has been evaluated in blind state by a certified radiologist." This suggests a single reader evaluation. There is no mention of consensus or multi-reader adjudication methods (like 2+1 or 3+1).

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

No, an MRMC comparative effectiveness study is not explicitly mentioned in this document. The evaluation of image quality was performed by a single certified radiologist. There is no information provided regarding human readers improving with AI vs. without AI assistance, as this is a PET/CT scanner system, not specifically an AI-driven image analysis tool.

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

This is a hardware device (PET/CT scanner) with integrated software for image reconstruction and display. The intent is "Trained doctors can read useful diagnostic information from the image generated." Therefore, the entire system is designed for human-in-the-loop performance. While the device contains "advance algorithms based on OSEM" that "can improve the image quality," the performance evaluation mentioned focuses on the output images read by a human. A standalone algorithm only performance, in the sense of an AI diagnostic tool without human review, is not described for this device.

7. The Type of Ground Truth Used

For the sample clinical images, the "ground truth" for evaluating image quality appears to be the expert opinion of a certified radiologist. There is no mention of pathology, outcome data, or expert consensus serving as ground truth for the image quality evaluation described.

8. The Sample Size for the Training Set

The document does not mention a training set or its sample size. This summary pertains to the regulatory submission for a PET/CT scanner system, not typically a machine learning algorithm that requires an explicit training set for its primary function. While it mentions "advance algorithms based on OSEM" that improve image quality, it does not describe their development or training data in this context.

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

Since a training set is not mentioned, the method for establishing its ground truth is also not applicable/provided in this document.

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ClearView is a CT reconstruction software. The end user can choose to apply either ClearView or the filter back-projection (FBP) to the acquired raw data.

Depending on the clinical task, patient size, anatomical location, and clinical practice, the use of ClearView can help to reduce radiation dose while maintaining Pixel noise, low contrast detectability and high contrast resolution. Phantom measurements showed that high contrast resolution and pixel noise are equivalent between full dose FBP images and reduced dose ClearView images. Additionally, ClearView can reduce body streak artifacts by using iterations between image space and raw data space.

A Model Observer evaluation showed that equivalent low contrast detectability can be achieved with less dose using ClearView at highest noise reduction level for thin (0.625 mm) reconstruction slices in MITA body and ACR head phantoms for low contrast objects with different contrasts.

ClearView are not intended to be used in CCT and Pilot.

ClearView reconstruction technology may enable reduction in pixel noise standard deviation and improvement in low contrast resolution. ClearView reconstruction algorithm may allow for reduced mAs in the acquisition of image, thereby it can reduce the dose required.

In clinical practice, the use of ClearView reconstruction may reduce CT patient dose depending on the clinical task, patient size, and clinical practice. A consultation with a radiologist and physicist should be made to determine the appropriate dose to obtain diagnostic image quality for the particular clinical task.

As a reconstruction option, ClearView can be selected before scanning or after scanning. There are 9 ClearView Levels from 10% to 90%. Users can select t.the level of ClearView that is appropriate for the clinical task being performed. According to the comparison based on the requirements of 21 CFR 807.87, we stated that ClearView reconstruction software is substantially equivalent to the FBP of NeuViz 64 Multi-Slice CT Scanner System.

ClearView is a moderate concern device.

Here's an analysis of the acceptance criteria and study information for the ClearView device as presented in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document provides performance claims for ClearView, primarily in comparison to Filtered Back Projection (FBP) and related to dose reduction. It doesn't explicitly state "acceptance criteria" in a numerical table form, but rather describes how the device performs against certain metrics.

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

The provided text does not contain information about the sample size used for a test set based on human patient data. The evaluations mentioned are based on:

• Phantom measurements: Performed on "MITA body and ACR head phantoms." No specific sample size (number of phantom scans) is provided.
• Data Provenance: The studies are described as "Phantom measurements" and "A Model Observer evaluation." This implies laboratory or simulated data, not retrospective or prospective human clinical data. The country of origin of the data is not specified beyond the manufacturer being in China.

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

The document does not detail the use of human experts to establish ground truth for a test set. The evaluations primarily relied on phantom measurements and a model observer, which are objective, quantitative metrics. While "A consultation with a radiologist and physicist should be made to determine the appropriate dose to obtain diagnostic image quality for the particular clinical task," this refers to clinical practice guidance and not a component of the device's validation study itself as described.

4. Adjudication Method for the Test Set

Not applicable. The reported evaluations (phantom measurements, Model Observer) do not involve human adjudication for a test set's ground truth.

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

No. The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. The evaluation focuses on standalone phantom performance and model observer results, not on how human readers' performance improves with or without the AI (ClearView) assistance.

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

Yes. The described studies are standalone evaluations of the ClearView reconstruction software's performance, primarily using phantom measurements and a "Model Observer evaluation." These do not involve a human in the loop for the performance assessment. The device itself is a reconstruction software.

7. Type of Ground Truth Used

The ground truth used in the described studies is:

• Physical Phantom Measurements: For pixel noise, high contrast resolution, and effectively for low contrast detectability (as measured by the Model Observer on phantoms). These are objective physical properties measured with specific phantoms and known targets.
• Model Observer Results: Used for low contrast detectability, which is a quantitative measure from a computational model mimicking human perception, applied to phantom data with known contrast objects.

8. Sample Size for the Training Set

The document does not provide any information about the sample size used for any training set. ClearView is described as CT reconstruction software, but details on its development or any machine learning training data are absent.

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

The document does not provide any information on a training set or how its ground truth might have been established.

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The NeuViz 64 Multi-Slice CT Scanner System can be used as a whole body computed tomography X-ray system featuring a continuously rotating X-ray tube and detector array. The acquired X-RAY transmission data is reconstructed by computer into cross-sectional images of the body from either the same axial plane taken at different angles or spiral planes taken at different angles.

The NeuViz 64 Multi-slice CT Scanner System is composed of a gantry, a patient couch, an operator console and includes image acquisition hardware and software, and associated accessories. It is designed to be a head and whole body X-ray computed tomography scanner which features a continuously rotating tube-detector system and functions according to the fan beam principle. The system software is an interactive program used for X-ray scan control, image reconstruction, and image archive/evaluation.

Here's a breakdown of the acceptance criteria and study information for the Neusoft NeuViz 64 Multi-Slice CT Scanner System, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The provided document does not explicitly state quantitative acceptance criteria for image quality or clinical performance. Instead, it relies on a qualitative assessment and substantial equivalence to a predicate device.

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

• Sample Size: 260 subjects
• Data Provenance: Obtained from 2 sites. The document does not specify the country of origin of the data or whether the study was retrospective or prospective.

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

• Number of Experts: Radiologist (singular, implying at least one, but the exact number is not specified).
• Qualifications: "Radiologist" - no further specific qualifications (e.g., years of experience, subspecialty) are mentioned.

4. Adjudication Method for the Test Set:

• The document states that a "Radiologist assessed the diagnostic quality of the images." It does not provide details on an adjudication method (e.g., 2+1, 3+1, none) if multiple radiologists were involved. Given the singular "Radiologist," it's possible a single reader assessed the images.

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

• No, an MRMC comparative effectiveness study is not mentioned. The study described is a clinical image assessment, not a comparative study with and without AI assistance or a comparison among multiple readers using the device.

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

• This device is a CT scanner, a hardware device that acquires and reconstructs images. It is not an AI algorithm intended for standalone diagnostic interpretation. Therefore, a "standalone algorithm only" study, as typically understood for AI, is not applicable or described. The study focuses on the diagnostic quality of the images produced by the scanner, which are then interpreted by a human radiologist.

7. Type of Ground Truth Used:

• Expert Consensus: The diagnostic quality of the images was assessed by a "Radiologist," which represents expert opinion. There is no mention of pathology, outcomes data, or other objective ground truth measures being used to validate the radiologist's assessment in this context.

8. Sample Size for the Training Set:

• The document describes a clinical evaluation of the scanner's output and its substantial equivalence to a predicate device. There is no mention of an "AI" or machine learning component that would require a separate training set. Therefore, this question is not applicable to the information provided.

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

• As there is no mention of a training set for an AI algorithm, this question is not applicable.

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The NeuColonCARE is a soft-copy reading workstation intended for clinical review of CT abdominal (gastrointestinal) images which allows easy acquisition, transmission and review of the medical images and supports VC (Virtual Colonoscopy) function. Images may be interpreted by a trained physician to obtain information that may be useful in the determination of a diagnosis.

NeuColonCARE software product is a soft-copy reading workstation used to clinically evaluate the CT abdominal (gastrointestinal) images. It is a self-contained software package, providing the functions of patient information management, image viewer (2D view, standard MPR views and 3D visualization view), and the analysis and processing of the gastrointestinal system, especially the colon. It allows the user to conduct air segmentation based on a customized threshold value, extract the centerline automatically and interactively, view the colon lumen structure in the manner of virtual colonoscopy or virtual dissection along the centerline, view the ROI, and finally acquire useful clinical information by marking and measuring the ROI (3D distance and CT value).

The provided text is a 510(k) summary for the Neusoft NeuColonCARE device. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does not contain the detailed information required to answer all parts of your request, specifically regarding acceptance criteria and a study proving those criteria are met.

Here's an analysis of what can and cannot be answered based on the provided text:

Acceptance Criteria and Study (Cannot be fully answered):

The document states:

• "The device has been evaluated for conformance to its design specifications and applicable industry standards for software development. A summary of the software design description, risk management, level of concern and verification&validation testing information can be found in the attached submission."
• "It is further verified for system compatibility with the devices with which it communicates, including conformance to DICOM 3.0 standard."
• "Neusoft Medical Systems considers the NeuColonCARE software product to be as safe, as effective, and performance is substantially equivalent to the predicate devices."

This broadly indicates that some form of "verification and validation testing" was performed to show conformance to design specifications and industry standards. However, the document does not provide specific acceptance criteria (e.g., a certain sensitivity/specificity threshold for polyp detection, or accuracy of measurements) nor does it describe any specific study that quantitatively measures the device's performance against such criteria. The basis for clearance is substantial equivalence to predicate devices, not a demonstration of specific performance metrics against pre-defined acceptance criteria.

Therefore, the table of acceptance criteria and reported device performance cannot be generated from the provided text. The subsequent questions (#2-9) regarding sample sizes, ground truth, experts, etc., are also not addressed because there is no description of a performance study in the provided text.

Summary of available information:

1. Table of acceptance criteria and the reported device performance:

   • N/A. The document does not provide specific acceptance criteria or reported device performance metrics from a clinical study. It relies on a comparison to predicate devices for substantial equivalence.

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

   • N/A. No such details are provided as no specific performance study is detailed.

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):

   • N/A. No such details are provided as no specific performance study is detailed.

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

   • N/A. No such details are provided as no specific performance study is detailed.

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:

   • N/A. The document does not mention any MRMC comparative effectiveness study or AI assistance. The device is described as a "soft-copy reading workstation" and focuses on visualization and analysis tools, not AI-driven improvement for human readers.

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

   • N/A. The document describes the device as a "soft-copy reading workstation" intended for "clinical review of CT abdominal (gastrointestinal) images" where "Images may be interpreted by a trained physician." This implies a human-in-the-loop system. No standalone algorithm performance is described.

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

   • N/A. No such details are provided as no specific performance study is detailed.

8. The sample size for the training set:

   • N/A. No such details are provided as no specific training of a machine learning algorithm is discussed.

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

   • N/A. No such details are provided as no specific training of a machine learning algorithm is discussed.

Conclusion from the document:

The Neusoft NeuColonCARE device was cleared based on substantial equivalence to its predicate devices (Voxar 3D Entreprise with ColonMetrix K070831 and Philips ViewForum 2003 K032096). The text outlines that the device shares similar technological characteristics and functions (e.g., standard MPR, Virtual Endoscopy, Virtual Dissection, ROI bookmarking and measurement) with the predicate devices. It states that the device "employs the same or similar fundamental technology as its predicate devices and dose not introduce any new potential safety risks," leading to the conclusion that it is "as safe, as effective, and performance is substantially equivalent to the predicate devices."

The description of "non-clinical tests" refers to conformance to design specifications, industry standards (DICOM 3.0), software design description, risk management, and verification & validation—these are general software development and regulatory compliance activities, not a detailed clinical performance study with specific acceptance criteria and outcome metrics.

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BeyondImage Workstation is a software application that is used for viewing medical images. Beyond mage Workstation receives digital images and data from various sources (including but not limited to CT, MR, US, RF units, computed and digital radiographic devices). Images are stored, communicated, processed and displayed on the local disc of a workstation and/or across computer networks at distributed locations. Taking that users may perform when viewing images include, but are not limited to adjustment of window width and center; image stacking; annotation and measurement of regions of interest; and inversion, rotation, and flips of images, it also provides standard Multi-Planar Reconstruction (MPR) views, Curved-Planar Reconstruction (CPR) views and 3D views of Volume Rendering for digital images from CT, MR, and PET unit. In addition, using Beyondlmage Workstation, users can edit and print report.

Beyondlmage Workstation cannot display and process mammograms.

Typical users of Beyondlmage Workstation are trained medical professionals, including but not limited to radiologists, clinicians, technologists, and others.

BeyondImage Workstation is a software application that provides image viewing and manipulation in a diagnostic imaging setting. The functions of this application are applied to medical images that are acquired and stored on an image server in DICOM format. Beyondlmage Workstation can also transfer images in DICOM 3.0 format over a medical imaging network, as well as exporting images to applications in other proprietary formats.

The provided text is a 510(k) Summary of Safety and Effectiveness for the BeyondImage Workstation 2.0. This document primarily focuses on establishing substantial equivalence to predicate devices and describes the device's functionality. It does not contain details about acceptance criteria, a specific study proving the device meets those criteria, or information on sample sizes, ground truth establishment, or expert involvement for a performance study.

Therefore, I cannot extract the requested information from the provided text. The document acts as a regulatory submission confirming the device's intended use and technological similarity to existing approved devices, rather than a detailed report of a performance study with specific metrics and methodologies.

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The NeuViz 16 Multi-Slice CT Scanner System can be used as a whole body computed tomography X-ray system featuring a continuously rotating X-ray tube and detector array with multislice capability up to 16 slices simultaneously. The acquired X-RAY transmission data is reconstructed by computer into cross-sectional imagers of the body from the same axial plane taken at different angles. The system is suitable for all patients.

Not Found

The provided document is a 510(k) clearance letter from the FDA for the "NeuViz 16 Multi-Slice CT Scanner System." This type of document declares substantial equivalence to a predicate device based on performance specifications and safety, but does not typically contain detailed information about a clinical study with acceptance criteria, sample sizes, expert adjudication, or AI performance metrics.

Therefore, based solely on the provided text, I cannot provide the requested information about acceptance criteria, study details, and AI performance. The document focuses on regulatory clearance, not on a detailed clinical performance study report.

To answer your specific questions based on the provided text:

1. A table of acceptance criteria and the reported device performance: Not available in this document. This document is a regulatory clearance letter, not a performance study report.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not available in this document.
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): Not available in this document.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not available in this 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: Not available in this document. This device is a CT scanner, not an AI-powered diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not available in this document. This device is a CT scanner, not an AI algorithm.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not available in this document.
8. The sample size for the training set: Not available in this document.
9. How the ground truth for the training set was established: Not available in this document.

In summary, the provided document is a regulatory decision letter and does not contain the detailed technical and clinical study information you are asking for regarding a device's performance against specific acceptance criteria or an AI-related study.

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