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uCT ATLAS Astound is a computed tomography x-ray system, which is intended to produce cross-sectional images of the whole body by computer reconstruction of x-ray transmission data taken at different angles and planes. uCT ATLAS Astound is applicable to head, whole body, cardiac, and vascular x-ray Computed Tomography.

uCT ATLAS Astound is intended to be used for low dose CT lung cancer screening for the early detection of lung nodules that may represent cancer. The screening must be performed within the established inclusion criteria of programs / protocols that have been approved and published by either a governmental body or professional medical society.

*Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

uCT ATLAS is a computed tomography x-ray system, which is intended to produce cross-sectional images of the whole body by computer reconstruction of x-ray transmission data taken at different angles and planes. uCT ATLAS is applicable to head, whole body, cardiac, and vascular x-ray Computed Tomography.

uCT ATLAS has the capability to image a whole organ in a single rotation. Organs include, but not limited to head, heart, liver, kidney, pancreas, joints, etc.

uCT ATLAS is intended to be used for low dose CT lung cancer screening for the early detection of lung nodules that may represent cancer. The screening must be performed within the established inclusion criteria of programs / protocols that have been approved and published by either a governmental body or professional medical society.

*Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

uWS-CT-Dual Energy Analysis is a post-processing software package that accepts UIH CT images acquired using different tube voltages and/or tube currents of the same anatomical location. The various materials of an anatomical region of interest have different attenuation coefficients, which depend on the used energy. These differences provide information on the chemical composition of the scanned body materials and enable images to be generated at multiple energies within the available spectrum. uWS-CT-Dual Energy Analysis software combines images acquired with low and high energy spectra to visualize this information.

The uCT ATLAS Astound with uWS-CT Dual Energy Analysis and uCT ATLAS with uWS-CT Dual Energy Analysis includes the same intended use and same indications for use as their recent cleared versions (K231482). The reason for this submission is to support the following additional functions:

• CardioXphase (optimized)
• CardioBoost
• CardioCapture (optimized)
• AIIR
• Motion Freeze
• Ultra EFOV

The provided text describes a 510(k) premarket notification for a Computed Tomography X-ray System (uCT ATLAS Astound with uWS-CT-Dual Energy Analysis and uCT ATLAS with uWS-CT-Dual Energy Analysis). The submission focuses on additional software functions beyond what was previously cleared.

However, the document does not contain specific acceptance criteria, detailed study designs, or quantitative performance data to establish "proof" in the typical sense of a rigorous clinical trial with defined endpoints and statistical significance. Instead, it relies on demonstrating substantial equivalence to existing predicate devices.

The "acceptance criteria" appear to be implicit in the non-clinical and reader studies, aiming to show that the performance of the new features is "sufficient for diagnosis," "equal or better," or "can improve" compared to a baseline or predicate. No explicit numerical thresholds for metrics like sensitivity, specificity, accuracy, or effect sizes for reader improvement are provided.

Here's an analysis based on the information provided, highlighting what is present and what is missing concerning acceptance criteria and study details:

Overview of Device Performance and Acceptance Criteria

The submission does not explicitly define acceptance criteria in terms of numerical thresholds for performance metrics. Instead, it describes a "bench test" and "reader study" approach to demonstrate that the new functions do not raise new safety and effectiveness concerns and provide an equivalent or improved performance compared to the predicate/reference devices or established techniques.

The implied "acceptance criteria" are qualitative, such as:

• "passed the basic general IQ test which satisfied the requirement of IEC 61223-3-5."
• "showed better LCD comparing with FBP..."
• "showed better noise comparing with FBP."
• "showed better spatial resolution comparing with FBP..."
• "all indicators have met the verification criteria and have passed the verification." (for CardioXphase)
• "can reduce head motion artifacts." (for Motion Freeze)
• "can improve the CT number..." (for Ultra EFOV)
• "images are sufficient for diagnosis and the image quality... is equal or better than..." (for various reader studies)
• "is helpful for both artifact suppression and clinical diagnosis." (for Motion Freeze reader study)
• "can improve the accuracy of image CT numbers..." (for Ultra EFOV reader study)
• "conclude the effectiveness of CardioCapture function for reducing cardiac motion artifacts as expected."

Table of Acceptance Criteria (Implied) and Reported Device Performance

Since explicit, quantitative acceptance criteria are not provided, this table will rephrase the reported performance as the observed outcome against the implied objective.

Study Details

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

   • Test Set Sample Size: The document does not specify the sample sizes (number of cases/studies) used for either the bench tests or the reader studies.
   • Data Provenance: Not explicitly stated (e.g., country of origin, whether retrospective or prospective). The use of "clinical images" implies real patient data, but details are missing.

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

   • Number of Experts: Not specified. The document mentions "readers" (plural) for the reader studies but does not state how many participated.
   • Qualifications of Experts: Not specified. No details are given about their specialty (e.g., cardiologist, radiologist), experience level, or board certification.

3. Adjudication Method for the Test Set:

   • Adjudication Method: Not specified. For the reader studies, it only states that images "were shown to the readers to perform a five-point scale evaluation" or "5-point scale evaluation." There's no mention of how discrepancies or disagreements among readers were handled or if a consensus ground truth was established by independent experts (e.g., 2+1, 3+1).

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, What was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance:

   • MRMC Study: Reader studies were conducted comparing images reconstructed with the new AI functions (e.g., CardioBoost) to those reconstructed with traditional methods (e.g., KARL 3D, FBP). These appear to be MRMC studies in structure, as multiple readers evaluate multiple cases.
   • Effect Size: No quantitative effect sizes are provided. The results are qualitative: "equal or better," "sufficient for diagnosis," "helpful." There are no reported metrics like AUC improvement, sensitivity/specificity gains, or statistical significance of differences in reader performance with and without AI assistance.

5. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) Was Done:

   • Standalone Performance: The "bench tests" for CardioBoost, AIIR, Motion Freeze, and Ultra EFOV evaluate the algorithms' image quality metrics (IQ, LCD, noise, spatial resolution, CT value accuracy, artifact reduction) independently of human interpretation. For CardioXphase, the evaluation of the AI module's extraction accuracy (DICE, Precision, Recall) is also a standalone assessment. These can be considered standalone performance evaluations for the image reconstruction/processing algorithms.

6. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.):

   • Ground Truth: For the image quality bench tests (CardioBoost, AIIR, Motion Freeze, Ultra EFOV), the "ground truth" is likely defined by physical phantom measurements and adherence to engineering specifications/standards (e.g., IEC 61223-3-5, CTIQ White Paper, AAPM's report).
   • For CardioXphase, the ground truth for image segmentation accuracy (heart and coronary artery masks) was "annotated results," which typically implies expert manual annotation on imaging data.
   • For the reader studies, the "ground truth" is based on the subjective evaluation of "image quality aspects" by the readers, rather than an objective, clinically validated ground truth for a diagnostic endpoint (e.g., presence/absence of disease confirmed by biopsy or follow-up). The goal was to demonstrate that the image quality generated by the new features is non-inferior or improved for diagnostic purposes.

7. The Sample Size for the Training Set:

   • Training Set Sample Size: The document mentions "datasets augmentation and deep learning network optimization" for CardioBoost and AIIR, and "introduction of a new deep learning based coronaries detection algorithm" for CardioXphase, and "introduces a deep learning network" for Ultra EFOV. However, the specific size of the training datasets (number of images/cases) is not provided.

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

   • Training Set Ground Truth: Not explicitly stated. For deep learning models, training data ground truth is typically established by expert annotation or labels derived from existing clinical reports or imaging features. Given the context of image reconstruction and enhancement, it likely involves high-quality, potentially expert-annotated, imaging data. For instance, for CardioXphase, the ground truth for training the coronary artery detection algorithm would involve expert-labeled coronary anatomy. For features like CardioBoost and AIIR, which optimize image reconstruction, the ground truth for training might involve pairs of raw data and ideal reconstructed images, or image quality metrics derived from expert evaluations on initial datasets.

In summary, the 510(k) submission successfully demonstrates "substantial equivalence" based on qualitative assessments and performance relative to known methods. However, for a detailed "proof" with explicit acceptance criteria and quantitative performance metrics, further information beyond what is presented in this FDA clearance letter summary would be needed. This is characteristic of many 510(k) submissions, which often rely on demonstrating safety and effectiveness relative to existing predicates rather than establishing novel clinical efficacy through large-scale, quantitatively defined trials.

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uCT ATLAS Astound is a computed tomography x-ray system, which is intended to produce cross-sectional images of the whole body by computer reconstruction of x-ray transmission data taken at different angles and planes. uCT ATLAS Astound is applicable to head, whole body, cardiac, and vascular x-ray Computed Tomography.

uCT ATLAS Astound is intended to be used for low dose CT lung cancer screening for the early detection of lung nodules that may represent cancer. The screening must be performed within the established inclusion criteria of programs / protocols that have been approved and published by either a governmental body or professional medical society. * Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

uWS-CT-Dual Energy Analysis is a post-processing software package that accepts UIH CT images acquired using different tube voltages and/or tube currents of the same anatomical location. The various materials of an anatomical region of interest have different attenuation coefficients, which depend on the used energy. These differences provide information on the chemical composition of the scanned body materials and enable images to be generated at multiple energies within the available spectrum. uWS-CT-Dual Energy Analysis software combines images acquired with low and high energy spectra to visualize this information.

uCT ATLAS is a computed tomography x-ray system, which is intended to produce cross-sectional images of the whole body by computer reconstruction of x-ray transmission data taken at different angles and planes. uCT ATLAS is applicable to head, whole body, cardiac, and vascular x-ray Computed Tomography.

uCT ATLAS has the capability to image a whole organ in a single rotation. Organs include, but not limited to head, heart, liver, kidney, pancreas, joints, etc.

uCT ATLAS is intended to be used for low dose CT lung cancer screening for the early detection of lung nodules that may represent cancer. The screening must be performed within the established inclusion criteria of protocols that have been approved and published by either a governmental body or professional medical society.

• Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

uWS-CT-Dual Energy Analysis is a post-processing software package that accepts UIH CT images acquired using different tube voltages and/or tube currents of the same anatomical location. The various materials of an anatomical region of interest have different attenuation coefficients, which depend on the used energy. These differences provide information on the chemical composition of the scanned body materials and enable images to be generated at multiple energies within the available spectrum. uWS-CT-Dual Energy Analysis software combines images acquired with low and high energy spectra to visualize this information.

The proposed device CT system with uWS-CT-Dual Energy Analysis includes image acquisition hardware, image acquisition, reconstruction and dual energy analysis software, and associated accessories.

The proposed CT system is designed to use less radiation dose. Further, the fast scanning capability benefits the clinical applications, especially for cardiac imaging, dynamic whole organ imaging and fast body and vascular imaging.

The computer system delivered with the CT scanner is able to run post processing applications optionally.

The Computed Tomography System family scanners referenced in this submission are comparable in indications for use, and are substantially equivalent in design, material, functionality, technology, energy source and are substantially equivalent to the predicate devices. The reason for this submission is to support the following additional function:

CT intervention provides real-time CT fluoroscopy at 12 IPS with in-room view and in-room X-ray control. It allows the user to adjust the scan parameters during operation, and scan modes can be switched according to technician's operation requirements. Entry path planning based on 2D and 3D images.

The CT guided intervention will be applicable for the UIH qualified CT systems. This indication will also be applicable for future qualified UIH CT systems.

I am sorry, but the provided text does not contain sufficient information to answer your request regarding the acceptance criteria and the study that proves the device meets them. The document is primarily a 510(k) premarket notification letter from the FDA, outlining regulatory compliance and substantial equivalence to predicate devices, and includes device descriptions, indications for use, and a comparison of technological characteristics.

It mentions "Non-clinical testing including dosimetry and image performance tests were conducted...to verify that the proposed device met all design specifications," and lists relevant standards and guidance documents. It also states "The features described in this premarket submission are supported with the results of the testing mentioned above, the proposed device was found to have a safety and effectiveness profile that is similar to the predicate device." However, it does not provide:

• A table of specific acceptance criteria and reported device performance.
• Details about the study's design, such as sample size, data provenance, number or qualifications of experts, or adjudication methods for ground truth creation.
• Information about multi-reader multi-case (MRMC) comparative effectiveness studies or standalone algorithm performance.
• The type of ground truth used, or the sample size and ground truth establishment methods for a training set.

Therefore, I cannot populate the requested table or provide the specific study details you've asked for based on the given input.

Ask a specific question about this device

uCT ATLAS Astound is a computed tomography x-ray system, which is intended to produce cross-sectional images of the whole body by computer reconstruction of x-ray transmission data taken at different angles and planes. uCT ATLAS Astound is applicable to head, whole body, cardiac, and vascular x-ray Computed Tomography.

uCT ATLAS Astound is intended to be used for low dose CT lung cancer screening for the early detection of lung nodules that may represent cancer. The screening must be performed within the established inclusion criteria of programs / protocols that have been approved and published by either a governmental body or professional medical society. * Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

uWS-CT-Dual Energy Analysis is a post-processing software package that accepts UIH CT images acquired using different tube voltages and/or tube currents of the same anatomical location. The various materials of an anatomical region of interest have different attenuation coefficients, which depend on the used energy. These differences provide information on the chemical composition of the scanned body materials and enable images to be generated at multiple energies within the available spectrum. uWS-CT-Dual Energy Analysis software combines images acquired with low and high energy spectra to visualize this information.

The proposed device uCT ATLAS Astound with uWS-CT-Dual Energy Analysis includes image acquisition hardware, image acquisition, reconstruction and dual energy analysis software, and associated accessories.

The uCT ATLAS Astound is a multi-slice computed tomography scanner that features the following specification and technologies.

• 40 mm z-coverage in a single axial exposure with a 80-row 0.5 mm-slice Z-● Detector
• . 0.25 s rotation speed for high temporal resolution, and maximum 310 mm/s fast helical scanning capability
• 82 cm bore size, 318 kg (700 lbs) maximum table load capacity allows flexible . positioning and access for all patients
• . The new generation reconstruction method, Deep IR (also named AIIR), which combines the model-based iterative reconstruction and deep learning technology together, in order to reduce image noise and artifacts, while at the same time improving low contrast detectability and spatial resolution
• The uAI Vision patient positioning assistance

Built upon these technologies, the uCT ATLAS Astound is designed to use less radiation dose. Further, the fast scanning capability benefits the clinical applications, especially for cardiac imaging, dynamic whole organ imaging and fast body and vascular imaging.

The uWS-CT-Dual Energy Analysis is a post-processing software package that accepts UIH CT images acquired using different tube voltages and/or tube currents of the same anatomical location. The various materials of an anatomical region of interest have different attenuation coefficients, which depend on the used energy. These differences provide information on the chemical composition of the scanned body materials. CT dual energy analysis application combines images acquired with low and high energy spectra to visualize this information.

It appears that the provided document is a 510(k) summary for a medical device (uCT ATLAS Astound with uWS-CT-Dual Energy Analysis) being submitted to the FDA. While it discusses the device's indications for use, technological characteristics compared to a predicate device, and various non-clinical performance data (electrical safety, EMC, software, biocompatibility, etc.), it does not contain detailed information about a specific clinical study aimed at proving the device meets quantitative acceptance criteria related to its performance in terms of diagnostic accuracy or reader improvement.

The section titled "Clinical Image Evaluation" mentions that "Sample image of head, neck, chest, abdomen, spine, hip, knee, pelvis and so on were provided with a board certified radiologist to evaluate the image quality in this submission. Each image was reviewed with a statement indicating that image quality are sufficient for clinical diagnosis." This describes a qualitative assessment of image quality by a radiologist, rather than a rigorous study with predefined acceptance criteria, statistical analysis, and a detailed breakdown of test set characteristics as requested.

Therefore,Based on the provided document, the specific details required to answer your request regarding acceptance criteria and the study that proves the device meets them (especially in the context of diagnostic performance or human reader improvement with AI assistance) are not present. The document focuses on showing substantial equivalence to a predicate device primarily through technical comparisons and non-clinical testing, along with a high-level, qualitative statement about clinical image evaluation.

To directly answer your questions based only on the provided text:

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

• Not provided. The document does not list quantitative acceptance criteria for diagnostic performance or reported performance metrics against such criteria. It states that non-clinical tests (dosimetry, image performance) verified the device met design specifications and that image quality was "sufficient for clinical diagnosis" based on a radiologist's review.

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

• Sample size: Not specified for the "Clinical Image Evaluation" or any other diagnostic performance test.
• Data provenance: Not specified (e.g., country of origin, retrospective/prospective). The general statement "Sample image of head, neck, chest, abdomen, spine, hip, knee, pelvis and so on were provided" does not offer these details.

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

• Number of experts: Singular ("a board certified radiologist").
• Qualifications: "board certified radiologist." No mention of years of experience.
• Ground Truth Establishment: Not described. The radiologist "evaluate[d] the image quality" and provided "a statement indicating that image quality are sufficient for clinical diagnosis." This is an evaluation of image quality, not the establishment of a ground truth for a specific diagnostic task from a test set.

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

• None described. Given only one radiologist is mentioned for image quality evaluation, formal adjudication is not implied.

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, an MRMC comparative effectiveness study was not explicitly mentioned or detailed. The device is a CT system with dual-energy analysis software; the document does not describe AI assistance for human readers or a study evaluating reader improvement.

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

• No standalone diagnostic performance study by the algorithm is described. The software performs image post-processing and analysis (e.g., generating mono-energetic images, material base pairs, virtual non-contrast images), but there's no mention of a study where the algorithm itself made a diagnosis or provided a quantitative output that was evaluated against ground truth without human input.

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

• Not explicitly stated for diagnostic performance. The "Clinical Image Evaluation" relied on a radiologist's qualitative judgment of "image quality" and its sufficiency for "clinical diagnosis," which isn't a direct ground truth for disease presence/absence.

8. The sample size for the training set:

• Not applicable/Not provided. The document describes a CT scanner and post-processing software. While the device incorporates "Deep IR (also named AIIR)" which is described as combining "model-based iterative reconstruction and deep learning technology," there is no mention of a separate "training set" in the context of device performance claims or a diagnostic AI component being evaluated. This deep learning component appears to be part of the image reconstruction process, not necessarily a diagnostic AI algorithm that is trained on a specific dataset with ground truth labels for a clinical condition.

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

• Not applicable/Not provided. (See point 8).

In summary, the provided FDA 510(k) summary focuses on demonstrating substantial equivalence to a predicate device through technical specifications, non-clinical tests, and a qualitative clinical image evaluation. It does not present the type of detailed clinical study data, acceptance criteria, or ground truth establishment relevant to evaluating diagnostic AI performance or human reader improvement with AI assistance as requested in your prompt.

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