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Vitrea Software Package is an application package developed for use on Vitrea®, a medical diagnostic system that allows the processing, review, analysis, communication and media interchange of multi-dimensional digital images acquired from a variety of imaging devices. Vitrea Software Package has the following additional indications:

Auto MPR Brain application is a post processing software of CT brain images that is intended to align images into a standard anatomical position for review. It provides tools to reformat images parallel to a standard anatomical position.

Subtraction Viewer is a viewer application that is intended for viewing original, subtraction and fusion CT images, but such subtraction processing is not a part of this application. This application supports fusion display of original image and subtraction image generated by other applications.

The Vitrea Software Package, VSTP-002A V2.0, is a portfolio of applications software designed to be used in the Canon Medical Informatics Vitrea workstation. VSTP-002A currently includes post processing applications, Auto MPR Brain and Subtraction Viewer, which use CT image data, obtained from Canon CT Systems, to assist physicians in performing specialized measurements and analysis.

Auto MPR Brain is a software application that aligns CT brain images into a standard anatomical position for review.

Subtraction Viewer, also marketed as SCT Viewer, is a software application intended to view original, subtraction and fusion CT images. This application supports fusion display of original images and subtraction images generated by other applications and includes the ability to adjust fusion rate and ROI measurements of fusion images.

The provided text describes a 510(k) premarket notification for the "Vitrea Software Package, VSTP-002A V2.0". Based on the information provided, the acceptance criteria and study proving the device meets these criteria can be described as follows:

Acceptance Criteria and Device Performance

The acceptance criteria are implicitly derived from the "Performance Testing - Bench" section, which focuses on the "Evaluation of CE Boost Contrast-to-Noise Ratio (CNR)" for the Subtraction Viewer software.

Study Details:

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

   • Sample Size: "images of adult cases". No specific number of cases or images is provided.
   • Data Provenance: The images were "derived from a Canon CT scanner." The anatomical regions included "abdomen, brain, neck, chest, pulmonary embolism, and limb scans." The country of origin is not specified, nor is whether the data was retrospective or prospective.

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

   • The document does not mention the use of experts or the establishment of ground truth by experts for the performance testing. The evaluation described is a quantitative measurement (CNR) of the output from the "Subtraction Viewer" application.

3. Adjudication Method for the Test Set:

   • Not applicable, as no human reader evaluation or expert consensus for ground truth establishment is described. The performance test is a quantitative measurement of CNR.

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

   • No MRMC or human-in-the-loop study is mentioned. The performance evaluation focuses on the technical performance of the software (CNR measurement), not on how human readers interact with or benefit from the AI.

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

   • Yes, the described "Evaluation of CE Boost Contrast-to-Noise Ratio" is a standalone, algorithm-only performance assessment. It directly evaluates the output of the software (CE Boost images) by comparing CNR, without involving human interpretation or decision-making as part of the primary performance metric.

6. Type of Ground Truth Used:

   • The concept of "ground truth" as a clinical reference standard (e.g., pathology, outcomes data, or expert consensus on disease presence) is not directly applicable to the described performance test. The "ground truth" for the CNR evaluation is the original CE image against which the CNR of the CE Boost image is compared. The purpose of the test is to verify the software's ability to enhance contrast as intended.

7. Sample Size for the Training Set:

   • The document does not provide information about the training set size or methodology. This submission is for a "modification of a cleared device" (VSTP-002A V2.0 from VSTP-002A), and the focus of the testing section is on the performance validation of the modified features, specifically the CE Boost functionality within the Subtraction Viewer.

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

   • Not specified, as information regarding the training set and its ground truth establishment is not provided in this document.

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The Low Dose CT Lung Cancer Screening Option for Canon/Toshiba CT systems is indicated for using low dose CT for lung cancer screening. The screening must be conducted with the established program criteria and protocols that have been approved and published by a governmental body, a professional medical society and/or Canon.

Information from professional societies related to lung cancer screening can be found, but is not limited to: American College of Radiology® (ACR)-resources and technical specification; accreditation American Association of Physicists in Medicine (AAPM) - Lung Cancer Screening Protocols; radiation management.

The low dose lung cancer screening option is an indication being added to the following existing, previously FDA-cleared scanners: [List of Aquilion and Lightning CT scanner models and their corresponding 510(k) numbers]. No functional, performance, feature, or design changes are being made to the devices that will be indicated for low dose lung cancer screening. The devices already include low dose lung screening protocols, intended for use in the review of thoracic CT images within the established inclusion criteria of programs/protocols that have been approved and published by either a governmental body or professional medical society.

The provided text describes a 510(k) premarket notification for a "Low Dose CT Lung Cancer Screening Option" from Canon Medical Systems Corporation. The submission seeks to add this indication to existing, previously FDA-cleared CT scanners. The key claim is substantial equivalence to a predicate device (Aquilion RXL, K121553, which is a successor to the Aquilion 16 used in the National Lung Screening Trial - NLST). The device's performance is demonstrated through bench testing only, not a clinical study involving human subjects or AI-assisted readings.

Therefore, the following information can be extracted/inferred:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document states that performance was "substantially equivalent" to the predicate. Specific numerical values for the reported performance are not provided in this regulatory summary.

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

• Test Set Sample Size: Not applicable in the traditional sense of a clinical test set with patient data. The "test set" consists of bench testing data from representative scanners from different CT system families. One device from each of the three identified families (Aquilion 16/32/64/RXL, PRIME/PRIME SP, ONE/ViSION/Genesis, and Lightning) was used for bench testing.
• Data Provenance: The data is from bench testing performed by Canon Medical Systems Corporation. The document does not specify the country of origin for this bench testing data, but the manufacturer is Canon Medical Systems Corporation (Japan) with a U.S. agent. The original NLST data (which the predicate is compared against) was from a large-scale, prospective clinical trial conducted in the United States.

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

Not applicable. This submission relies on bench testing for substantial equivalence, not a clinical study requiring expert ground truth for image interpretation.

4. Adjudication Method for the Test Set

Not applicable, as no human readers or clinical image interpretation were part of the presented performance data.

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. This submission is for a CT scanner's indication for low-dose lung cancer screening, not an AI-powered diagnostic assist device. The performance demonstration is based on the physical imaging characteristics of the CT system.

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

Not applicable. This is for a CT imaging device, not a standalone algorithm.

7. The Type of Ground Truth Used

The "ground truth" for this substantial equivalence argument is the performance of the predicate device (Aquilion RXL), which is stated to have similar technological characteristics and performance equivalent to the Aquilion 16 used in the NLST. The "ground truth" for the benefit of low-dose CT lung cancer screening itself comes from clinical literature, specifically referencing the National Lung Screening Trial (NLST) results, which demonstrated reduced mortality from lung cancer with low-dose CT screening. However, the device's performance itself is measured against established phantom-based image quality metrics.

8. The Sample Size for the Training Set

Not applicable. This is a CT imaging device, not an AI/ML algorithm that requires a training set of data.

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

Not applicable.

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Optional movable gantry base unit for use with an Aquilion ONE (TSX-305A) system to support longitudinal movement and allow acquisition of images in the z-direction (z-axis).

Note: When installed with the movable gantry base unit, Aquilion ONE can be used with the INFX-8000C system in the same room.

The Infinix 4DCT is composed of the INFX-8000C interventional angiography system and the dynamic volume CT system, Aquilion ONE, TSX-305A/3. This combination enables patient access and efficient workflow for interventional procedures. Aquilion ONE Self-Propelled Scan Base Kit for IVR-CT, CGBA-034A, is an optional kit intended to be used in conjunction with an Aquilion ONE / INFX-8000C based IVR-CT system. This device is attached to the Aquilion ONE CT gantry to support longitudinal movement and allow image acquisition in the z-direction (Z-axis), both axial and helical. When this option is installed, the standard CT patient couch is replaced with the patient handling system utilized by the interventional x-ray system, INFX-8000C. The Aquilion ONE Self-Propelled Scan Base Kit for IVR-CT, CGBA-034A, will be used as part of an Aquilion ONE / INFX-8000C based IVR-CT system. Please note, the intended uses and technological characteristics of the Aquilion ONE CT System and the INFX-8000C Interventional X-Ray System remain the same. There have been no modifications made to the imaging chains in these FDA cleared devices and the base system software remains the same. Since both systems will be installed in the same room and to prevent interference during use, system interlocks have been incorporated into the systems.

The provided text does not contain detailed information on the acceptance criteria and a study proving the device meets those criteria in a format suitable for the requested table. The document is a 510(k) summary for a medical device, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed clinical study with specific performance metrics and acceptance thresholds.

However, based on the text, I can infer some aspects and extract relevant information to address your request as much as possible.

Here's an attempt to answer your questions by extracting information from the provided document:

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

The document describes verification/validation testing conducted through bench testing to demonstrate that requirements for modifications have been met. It lists several functional aspects that were evaluated. While it doesn't provide specific quantitative acceptance criteria or numerical performance results in the provided text, it states that these functions "performed according to specifications."

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

The document mentions "bench testing" but does not specify a sample size for the test set or the data provenance (e.g., country of origin, retrospective or prospective). Bench testing typically involves testing a device or its components in a laboratory setting.

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

No information is provided regarding experts used to establish ground truth for a test set. Bench testing for this type of device (a movable gantry base unit) would likely involve technical verification against engineering specifications rather than expert interpretation of images or clinical outcomes.

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

No information is provided regarding an adjudication method. This is typically relevant for studies involving human interpretation or clinical endpoints, which are not detailed here.

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. This device is a mechanical accessory (movable gantry base unit for a CT scanner), not an AI-powered diagnostic tool, so an MRMC study comparing human reader performance with and without AI assistance is not applicable.

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

No standalone algorithm performance was done/mentioned. As noted, this is a hardware accessory, not an algorithm.

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

Given the nature of the device and the "bench testing" described, the "ground truth" would likely be defined by engineering specifications and functional requirements for mechanical movement, positioning accuracy, safety interlocks, and imaging capabilities (e.g., ability to acquire images in the z-direction). It is not based on clinical "truth" such as pathology or expert consensus on disease.

8. The sample size for the training set:

No training set is mentioned or applicable. This device is a mechanical component, not a machine learning model that requires a training set.

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

Not applicable, as there is no training set for this type of device.

In summary, the provided document (a 510(k) summary) focuses on regulatory submission for a device modification and substantial equivalence. It highlights that "bench testing" was conducted to confirm the device's functional performance against specifications and to ensure safety and effectiveness. However, it does not detail specific quantitative acceptance criteria or results in a table, nor does it conduct the types of studies (like MRMC or AI performance studies) that would involve human readers, ground truth established by experts, or training sets.

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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 Precision has the capability to provide volume sets. These volume sets can be used to perform specialized studies, usinq indicated software/hardware, by a trained and qualified physician.

FIRST 3.0 is an iterative reconstruction algorithm intended to reduce exposure dose and improve high contrast spatial resolution for abdomen, pelvis, chest, cardiac, extremities and head applications.

Aquilion Precision (TSX-304A/2) V8.6 with FIRST 3.0 is an ultra-high resolution whole body multi-slice helical CT scanner, consisting of a gantry, couch and a console used for data processing and display. Aquilion Precision incorporates a 160-row, 0.25 mm detector, a 5.7-MHU large-capacity tube, and 0.35 s scanning, enabling wide-range scanning with short scan times to capture cross sectional volume data sets used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician. In addition, the subject device incorporates the latest iterative reconstruction technology, FIRST 3.0, intended to reduce exposure dose while maintaining and/or improving image quality.

The provided document describes the Aquilion Precision (TSX-304A/2) V8.6 with FIRST 3.0, a Computed Tomography (CT) system, and its substantial equivalence to a predicate device. The performance validation focuses heavily on image quality metrics and spatial resolution, particularly for the new HR (High Resolution) and SHR (Super High Resolution) modes and the FIRST 3.0 iterative reconstruction algorithm.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and the Reported Device Performance:

The document doesn't present a formal table of acceptance criteria with corresponding performance metrics like a typical study design. Instead, it describes various tests and their outcomes, often in qualitative terms comparing the new device to a predicate or describing improvements. However, we can infer some criteria and their met outcomes:

• The HR and SHR modes "yield improved high contrast spatial resolution with some tradeoff in noise and LCD relative to NR mode."
• The FIRST algorithm "demonstrates equivalent or improved image quality relative to FBP for all modes." |
  | High Contrast Spatial Resolution | Achieve a specific high contrast spatial resolution, particularly with HR mode and FC90 reconstruction. | - A high contrast spatial resolution claim of "up to 46.1 lp/cm based upon the 2% of the MTF of images of a wire test object acquired in HR mode, under the axial scan mode and reconstructed with FC90" is supported initially.
• Later, it's stated that "a high contrast spatial resolution claim of up to 49.5 lp/cm, based upon the 2% of the MTF of images of a wire test object acquired in HR mode and reconstructed with FC90, is supported." This suggests an even better performance than initially stated, or a refinement of the measurement. |
  | Low Contrast Detectability (LCD) and Dose | Maintain equivalent or reasonable LCD, and ideally demonstrate dose reduction capabilities with FIRST. | - HR and SHR modes "may result in equivalent or a modest increase in X-ray dose as compared to scanning in normal resolution mode (NR)."
• "As demonstrated by the performance of FIRST at reduced mA values for standard deviation, MTF, and visual LCD as compared to FBP at higher mA values a qualitative claim of Dose Reduction with FIRST is supported."
• A study on Head and Body MITA-FDA LCD phantoms established baseline LCD (AUC) values and indicated potential trade-offs. |
  | Size Discrimination | Demonstrate improved size discrimination. | - A 50% improvement in size discrimination was observed with High Resolution mode compared to Normal Resolution mode at the same dose, using Catphan 10HU contrast rods (4-9mm diameter) in a model observer study. |
  | Diagnostic Quality | Produce images of diagnostic quality across various anatomical regions. | - "Representative diagnostic images, reviewed by an American Board Certified Radiologist, including head, chest, abdomen/pelvis, extremity and cardiac exams were also obtained using the subject device which demonstrates that the device produces images of diagnostic quality and; therefore, performs as intended." |
  | Substantial Equivalence | Demonstrate substantial equivalence to the predicate device. | - "The Aquilion Precision in NR mode is substantially equivalent to the predicate device."
• "NR mode and predicate device images were substantially equivalent." |

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

The document does not explicitly state sample sizes for all tests.

• Spatial Resolution Confirmation: "the MTF results of seven Aquilion Precision systems" were measured. This is a sample size of 7 systems, likely involving phantom data.
• Low Contrast Detectability: "Head and Body MITA-FDA LCD phantoms" were utilized. The number of phantoms or scans is not specified.
• Size Discrimination Performance: "Catphan 10HU contrast rods, 4-9mm in diameter" were used. The number of scans or virtual phantoms is not specified.
• Cadaver and Cardiac Stent Images: "cadaver and cardiac stent images" were provided. The number of cadavers or stents is not specified.
• Diagnostic Quality Images: "Representative diagnostic images... including head, chest, abdomen/pelvis, extremity and cardiac exams" were obtained. The number of cases is not specified.

Data Provenance: Primarily phantom data and some cadaver/stent images appear to be used for the technical performance assessments. The diagnostic quality images were "obtained using the subject device," implying prospective acquisition for the purpose of this submission rather than retrospective data. The location of data acquisition (country of origin) is not specified, but the submission is by Toshiba Medical Systems Corporation, Japan, and Toshiba America Medical Systems, Inc., USA.

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

• Diagnostic Quality Images: "Representative diagnostic images, reviewed by an American Board Certified Radiologist."

  • Number of Experts: Singular, "an American Board Certified Radiologist" (implying one).
  • Qualifications: "American Board Certified Radiologist." No specific experience level is mentioned (e.g., 10 years of experience).

• For the phantom-based studies (spatial resolution, LCD, size discrimination), the "ground truth" is typically inherent in the phantom design and physical measurements, rather than established by human experts.

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

• For the diagnostic quality image review by "an American Board Certified Radiologist," no adjudication method is mentioned, implying it was a single reader 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 comparative effectiveness study involving human readers and AI assistance (FIRST 3.0) is described. The studies primarily focus on the objective image quality metrics of the device itself and its reconstruction algorithms. The "model observer study" for size discrimination is a computational model, not human readers.

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

• Yes, the majority of the image quality evaluations (CT number accuracy, contrast-to-noise ratio, uniformity, slice sensitivity profile, MTF, LCD, etc.) of the FIRST 3.0 algorithm and the new acquisition modes (HR, SHR) are "standalone" performance evaluations. They assess the inherent image characteristics produced by the system and its algorithms using phantoms, independent of a human observer's interpretation in a clinical context.

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

• Phantom-based studies: The ground truth is the known properties of the phantoms (e.g., known dimensions of rods, known contrast differences, known noise levels).
• Diagnostic Quality Images: The ground truth for this qualitative assessment is the subjective expert opinion of "an American Board Certified Radiologist" that the images are of "diagnostic quality." This is a form of expert opinion, but not "consensus" as only one expert is mentioned.
• No pathology or outcomes data is mentioned as ground truth.

8. The sample size for the training set:

The document does not provide any information about the training set or its sample size. This is typical for submissions focused on the hardware and reconstruction algorithms of a CT scanner, where the "training" (if applicable for AI components) would be part of the algorithm development process, not usually detailed in a 510(k) summary for hardware clearance unless the AI itself is the primary new component. FIRST 3.0 is an iterative reconstruction algorithm, which generally relies on mathematical models and image processing, not necessarily on "training data" in the machine learning sense to learn to identify specific pathologies.

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

Not applicable, as no information on a training set or its ground truth establishment is provided.

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

The Aquilion Prime SP has the capability to provide volume sets. These volume sets can be used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician.

The Aquilion Prime SP TSX-303B/1 is an 80-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.

The provided text describes a 510(k) submission for the Toshiba Aquilion Prime SP, TSX-303B/1, v8.4. It outlines modifications to a previously cleared CT system. While the document mentions various performance evaluations and studies, it does not contain specific acceptance criteria tables nor detailed study designs that definitively "prove" the device meets acceptance criteria in the format of a typical peer-reviewed clinical study. Instead, it focuses on demonstrating substantial equivalence to a predicate device through engineering and performance testing.

However, I can extract and infer information about the testing and performance as described in the document.

Missing Information:

• A clear table of acceptance criteria for specific performance metrics. The document describes improvements but doesn't explicitly state "acceptance criteria" values met.
• Detailed sample sizes for all tests.
• Specific data provenance for all tests (e.g., country of origin, retrospective/prospective).
• Number and qualifications of experts for all ground truth establishment.
• Adjudication methods.
• MRMC comparative effectiveness study details (effect size of human reader improvement with AI).
• Standalone algorithm performance (the device is a CT system, not an algorithm in the AI sense).
• Sample size for the training set.
• How ground truth for the training set was established.

Based on the provided text, here's what can be extracted and inferred:

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

The document does not explicitly present a table of acceptance criteria. Instead, it describes performance improvements and that the modified system "demonstrates equivalent or slightly improved image quality characteristics." The performance evaluations are primarily focused on physical parameters and dose reduction, not diagnostic accuracy in the way an AI algorithm might be assessed against clinical endpoints.

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

• Sample Size for Physical Performance Tests: Not explicitly stated. The tests involved "model observer studies" using MITA-FDA LCD Head and MITA-FDA LCD Body phantoms, implying a phantom-based test set rather than patient data.
• Sample Size for Image Review: "Representative diagnostic images" were obtained. The exact number is not specified.
• Data Provenance: Not specified. Phantoms for performance tests. Clinical images for diagnostic quality assessment (implicitly from a clinical setting, but no country of origin or retrospective/prospective status is 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 Expert: An "American Board Certified Radiologist." Further details on experience (e.g., years) are not provided.
• Role: This radiologist "reviewed" the "representative diagnostic images" to confirm they were of "diagnostic quality."

4. Adjudication method for the test set

• Adjudication Method: Not applicable or not specified in detail. The document states a single American Board Certified Radiologist reviewed images. There is no mention of consensus or multi-reader adjudication for this informal review of diagnostic quality. For the quantitative performance metrics (dose reduction, LCD, noise), these were based on phantom studies and model observer analysis, not human reader adjudication.

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

• MRMC Study: No. The document does not describe a MRMC comparative effectiveness study. This submission is for a CT system itself, not an AI-assisted diagnostic tool in the typical sense of showing improved human reader performance. The "AI" mentioned (AIDR 3D Enhanced, SEMAR) refers to image processing algorithms within the CT system to improve image quality or reduce artifacts, not a separate AI application for diagnosis or interpretation assistance that would warrant an MRMC study comparing human readers with and without its aid.

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

• Standalone Performance: Yes, in a way. The "performance testing" of the modified system, including spatial resolution, CT number, noise properties, LCD, and CNR, as well as the quantitative dose reduction and LCD/noise improvement studies using phantoms and model observers, represent a standalone evaluation of the system's technical image quality parameters. These are inherent algorithmic and hardware performance metrics of the CT scanner, not dependent on human interpretation for their measurement.

7. The type of ground truth used

• For Quantitative Performance: Model observer studies using MITA-FDA LCD Head and MITA-FDA LCD Body phantoms. These phantoms represent a controlled, objective ground truth for physical image quality parameters.
• For Diagnostic Quality: The subjective assessment of an "American Board Certified Radiologist" confirming images were of "diagnostic quality." This is expert opinion/consensus for a qualitative judgment rather than a definitive "ground truth" like pathology.

8. The sample size for the training set

• Training Set Sample Size: Not applicable / Not provided. This document describes a 510(k) submission for a CT scanner, not a machine learning algorithm that requires a "training set" in the conventional sense. While there might be internal development and validation data, it's not discussed as a distinct "training set" within this regulatory context.

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

• Ground Truth Establishment for Training Set: Not applicable / Not provided, as there is no described training set for an AI algorithm in the context of this submission.

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