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The Spectral CT system is a Computed Tomography X-ray system intended to produce cross-sectional images of the body by computer reconstruction of X-ray transmission data taken at different angles and planes. This device may include signal analysis and display equipment, patient and equipment support, component parts, and accessories.

The Spectral CT system acquires one CT dataset – composed of data from a higher-energy detected X-ray spectrum and a lower- energy detected X-ray spectrum. The two spectra may be used to analyze the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and to provide information about the chemical composition of the body materials and/or contrast agents.

Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number.

This information may be used by a trained healthcare professional as a diagnostic tool for the visualization and analysis of anatomical and pathological structures in patients of all ages, and to be used for diagnostic imaging in radiology, interventional radiology, and cardiology and in oncology as part of treatment preparation and radiation therapy planning. The Extended field of view images and respiratory correlated scanning (4DCT) are for treatment preparation and radiation therapy planning/simulation usage only.

This device is indicated for head, whole body, cardiac and vascular X-ray Computed Tomography applications in patients of all ages.

The system is also 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.

Spectral CT system is a whole-body computed tomography (CT) X-ray system featuring a continuously rotating X-ray tube and detectors gantry, and multi slice capability. The acquired X-ray transmission data is reconstructed by computer into cross-sectional images of the body taken at different angles and planes. This system also includes signals analysis and display equipment, patient and equipment support, components, and accessories.

The Spectral CT system acquires one CT dataset – composed of data from a higher energy detected X-ray spectrum and a lower- energy detected X-ray spectrum. The two spectra may be used to analyze the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and provides information about the chemical composition of the body materials and/or contrast agents. Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number.

The Spectral CT system consists of three main components – a scanner system that includes a rotating gantry, a movable patient couch, and an operator console for control and image reconstruction; a Spectral Reconstruction System; and a Spectral CT Viewer. On the gantry, the main active components are the X-ray high voltage (HV) power supply, the X-ray tube, and the detection system.

The fundamental design and characteristics of the main components used in the proposed Spectral CT system are identical to the currently marketed primary predicate device, Spectral CT system (K203020).

This document is a 510(k) clearance letter for a Spectral CT System, indicating its substantial equivalence to previously cleared predicate devices. While it focuses heavily on design features and compliance with general safety and performance standards for CT systems, it does not contain the detailed clinical study information typically found in submissions for AI/ML-based medical devices that require specific performance metrics and human reader studies.

The provided text only briefly mentions "Clinical Image Evaluation" and "Comparison of performance data against internal performance requirements" as supporting the evaluation of new features. It does not provide specific acceptance criteria or performance results for these "new features" (Pulmonary Gating 4DCT and Extended Field of View (EFOV)) in the context of a clinical study, nor does it detail how substantial equivalence was demonstrated clinically for these features beyond a generic statement.

Therefore, many of the requested items cannot be extracted from this document, as it primarily covers the device's technical specifications and regulatory compliance for a general CT system, rather than specific performance studies for new AI/ML functionalities.

Given the information provided, here's what can be extracted and what cannot:

Acceptance Criteria and Study for Spectral CT System (K244008)

Based on the provided FDA 510(k) clearance letter, the primary method for demonstrating the device meets acceptance criteria and proving its performance is through substantial equivalence to predicate devices and adherence to recognized consensus standards and guidance documents. The document does not detail specific performance metrics, acceptance criteria, or a clinical study for the new features (Pulmonary Gating 4DCT and Extended Field of View (EFOV)) in the format requested for AI/ML device performance.

The document states:

• "Non-clinical performance testing has been performed on the proposed Spectral CT system and demonstrates compliance with the following International and FDA recognized consensus standards and FDA guidance document(s)..."
• "Design verification planning and testing were conducted at the system level. The system is tested against the System Requirements Specifications (SRS)."
• "Design Validation tests the user needs and intended use that are documented in the top-level User Requirement Specification (PRS)."
• "All the validation tests as per validation plan were performed and acceptance criteria met for each of the requirements."
• "Non-clinical design validation testing demonstrates that the proposed Spectral CT system can be used as defined in its clinical workflow and intended use."
• "To support the evaluation of the new features, the submission includes: - Phantom-based image quality (IQ) testing, assessing parameters such as noise, resolution, and artifacts - A representative clinical image assessment - Comparison of performance data against internal performance requirements"

This indicates that the "acceptance criteria" are primarily framed around compliance with established engineering and regulatory standards and internal performance requirements verified through non-clinical and limited clinical assessment, rather than a specific clinical trial with defined performance endpoints for the new features.

Information Extracted from the Document:

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

   The document does not provide a table of specific quantitative acceptance criteria and corresponding reported device performance metrics from a clinical study for the new features (Pulmonary Gating 4DCT and Extended Field of View (EFOV)). Instead, it states that "All the validation tests as per validation plan were performed and acceptance criteria met for each of the requirements." without detailing these.
   The primary "performance" discussed is the technological equivalence to predicate devices. Below is a summary of the technological characteristics being presented as "met" by being identical or substantially equivalent to the predicate.

   Table: Technological Characteristics (Implicit Acceptance Criteria - Equivalence to Predicate)

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

   Not explicitly stated in the provided text. The document refers to "Phantom-based image quality (IQ) testing" and "A representative clinical image assessment" but does not give sample sizes or provenance (country/retrospective/prospective) for these.

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

   Not explicitly stated. The document refers to "A representative clinical image assessment" but does not detail how ground truth was established or the experts involved.

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

   Not explicitly stated.

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 explicitly stated. This type of study is typically done for AI/ML diagnostic tools where human interpretation of medical images is directly affected by the AI output. This 510(k) is for a CT system itself, with new acquisition and reconstruction features (4DCT, EFOV) that are likely intended to provide better images for human interpretation, rather than an AI reading a dataset. The document's statements about "clinical image evaluation" do not elaborate on how this was conducted or whether it involved comparative effectiveness with human readers.

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

   This question is more applicable to diagnostic algorithms. For a CT system with new acquisition/reconstruction capabilities, the "standalone" performance would typically refer to the "Phantom-based image quality (IQ) testing," where the system's output (images) are assessed against objective physical metrics (noise, resolution, artifacts) without human interpretation of clinical findings. The document states this was done: "Phantom-based image quality (IQ) testing, assessing parameters such as noise, resolution, and artifacts."

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

   For the "Phantom-based IQ testing," the ground truth would be the known physical properties and measurements of the phantoms.
   For the "representative clinical image assessment," the type of ground truth is not specified.

8. The sample size for the training set:

   Not applicable. This 510(k) is for a CT hardware and software system, not an AI/ML diagnostic algorithm that would typically have a "training set" in the machine learning sense. The "new features" (Pulmonary Gating 4DCT and EFOV) are descriptions of how the system acquires and processes data, not separate AI algorithms trained on massive datasets to perform a diagnostic task.

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

   Not applicable, as there's no mention of a "training set" in the context of an AI/ML algorithm.

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The Spectral CT 7000 family is a Computed Tomography X-Ray System intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes. This device may include signal analysis and display equipment, patient and equipment parts, and accessories.

The Spectral CT 7000 family system acquires one CT dataset - composed of data from a higher energy detected x-ray spectrum and a lower- energy detected x-ray spectra may be used to analyze the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and to provide information about the chemical composition of the body materials and/or contrast agents. Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number.

This information may be used by a trained healthcare professional as a diagnostic tool for the visualization and analysis of anatomical and pathological structures in patients of all ages, and to be used for diagnostic imaging in radiology, interventional radiology, and cardiology as part of treatment preparation and radiation therapy planning. The Extended field of view images and respiratory correlated scanning (4DCT) are for treatment and radiation therapy planning/simulation usage only.

This device is indicated for head, whole body, cardiac and vascular X-ray Computed Tomography applications in patients of all ages.

The system is also 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.

Spectral CT 7500 RT system is a whole-body computed tomography (CT) X-ray system featuring a continuously rotating X-ray tube and detectors gantry, and multi slice capability. The acquired X-ray transmission data is reconstructed by computer into cross-sectional images of the body taken at different angles and planes. This system also includes signals and display equipment, patient and equipment support, components, and accessories.

The Spectral CT 7500 RT system acquires one CT dataset – composed of data from a higher energy detected X-ray spectrum and a lower- energy detected X-ray spectra may be used to analyze the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and provides information about the chemical composition of the body materials and/or contrast agents. Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number. The Spectral CT 7500 RT system consists of three main components – a scanner system that includes a rotating gantry, a movable patient couch, and an operator control and image reconstruction; a Spectral Reconstruction System; and a Spectral CT Viewer. On the gantry, the main active components are the X-ray high voltage (HV) power supply, the X-ray tube, and the detection system.

The provided documentation describes the acceptance criteria and the study that proves the Philips Medical Systems Technologies Ltd. Spectral CT 7500 RT device meets these criteria.

Here's the detailed breakdown:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly derived from the successful verification and validation of the device against System Requirements Specifications (SRS) and User Requirement Specification (URS), as well as compliance with recognized standards. The reported device performance is presented as meeting these criteria for the key features considered in the 510(k) submission: Pulmonary Gating 4DCT and Extended Field of View (EFOV).

• Spectral Phantom Testing: No significant differences in Pulmo spectral results compared to non-Pulmo chest scans.
• Clinical External Image Quality Review: Overall image quality graded as satisfactory for use in CT simulation for radiotherapy planning, meeting defined success criteria. | - Motion Phantom Testing: "The review and the analysis showed that the level and magnitude of artifacts is similar to existing products under similar conditions and additionally that the differences seen are explainable based on design differences between the Spectral CT 7500 RT and the existing currently marketed and predicate device, Philips Big Bore system (K171850). Clinical evaluation determined the gated reconstruction is acceptable for RT simulation purposes."
• Spectral Phantom Testing: "Review of all of the spectral results did not reveal any significant differences between the Pulmo spectral results and the non-Pulmo chest scan that was used as a reference. This supports the conclusion that there are no significant differences in the Pulmo spectral results compared with the non-Pulmo spectral results."
• Clinical External Image Quality Review: "Clinical images were externally reviewed, by US board certified reviewers, grading their overall image quality for use in CT simulation for radiotherapy planning. The external IQ assessments of Pulmonary Gating 4DCT for both conventional 4DCT results and Spectral 4DCT results, were completed and the defined success criteria were met. All images were rated as satisfactory for radiation therapy planning/ simulation." |
  | Extended Field of View (EFOV) | - IQ Integration Tests: Meeting SRS IQ requirements for RT applications.
• Clinical External Image Quality Review: Overall image quality graded as satisfactory for use in CT simulation for radiotherapy planning, meeting defined success criteria. | - Overall Conclusion of the IQ Testing: "The review achieved its goal of reviewing the results of IQ integration tests for the extended FOV feature in the proposed Spectral CT 7500 RT system. The results showed that the IQ testing meets the SRS IQ requirements. These results are only intended to support RT applications."
• Conclusion of Clinical External Image Quality Review: "Clinical images were externally reviewed, by US board certified reviewers, grading their overall image quality for use in CT simulation for radiotherapy planning. The external IQ assessment of eFOV was completed and the defined success criteria were met. All images were rated as satisfactory for radiation therapy planning/ simulation." |
  | General System Performance | Compliance with recognized international and FDA consensus standards (listed in the document). Meets established system and sub-system level design input requirements. User needs and intended use are met. | The document states: "Non-clinical performance testing has been performed on the proposed Spectral CT 7500 RT system and demonstrates compliance with the following International and FDA recognized consensus standards and FDA guidance document(s)... System and sub-system verification activities demonstrate the system meet the established system and sub-system level design input requirements... All the validation tests as per validation plan were performed and acceptance criteria met for each of the requirements." |

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

• Sample Size for Test Set: The document does not explicitly state the numerical sample size (number of patients or scans) used for the "Clinical External Image Quality Review" for either Pulmonary Gating 4DCT or EFOV.
• Data Provenance: The document states that "Clinical images were externally reviewed." It also mentions "US board certified reviewers." While not explicitly stated, this suggests the clinical images are likely from a relevant patient population, and the review was conducted by US-based experts. The studies appear to be retrospective clinical evaluations of image quality rather than prospective patient studies, as there is no mention of patient enrollment, intervention, or clinical outcomes. The focus is on image quality review for simulation purposes.

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

• Number of Experts: The document does not specify the exact number of experts used. It refers to "US board certified reviewers" in the plural, indicating more than one.
• Qualifications of Experts: The experts were "US board certified reviewers" who are involved in "CT simulation for radiotherapy planning." This implies they are likely board-certified radiologists or radiation oncologists with expertise in CT imaging for radiation therapy planning.

4. Adjudication Method for the Test Set

The document does not explicitly mention an adjudication method (e.g., 2+1, 3+1). It states "Clinical images were externally reviewed, by US board certified reviewers, grading their overall image quality..." This phrasing suggests that each reviewer likely provided their individual assessment against the success criteria, and the "defined success criteria were met," implying a consensus or a pass/fail threshold based on these independent gradings rather than a formal adjudication process to resolve disagreements.

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

No multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with AI assistance versus without AI assistance was done. The device is a CT imaging system with new features (Pulmonary Gating 4DCT and EFOV) primarily for radiation therapy planning, not an AI-assisted diagnostic tool for human readers. The evaluation focused on the image quality of the device output itself.

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

Yes, a standalone performance study in terms of technical image quality was performed. For both Pulmonary Gating 4DCT and EFOV, there were:

• Motion Phantom Testing (for Pulmonary Gating 4DCT): Evaluated artifacts and reconstruction.
• Spectral Phantom Testing (for Pulmonary Gating 4DCT): Evaluated spectral results.
• IQ Integration Tests (for EFOV): Evaluated image quality against SRS requirements.

These phantom and integration tests assess the device's technical performance and image output without direct human interpretation in a clinical decision-making loop. The "Clinical External Image Quality Review" also assessed the images themselves, albeit by human experts, to confirm their suitability.

7. Type of Ground Truth Used

The ground truth for the test set was:

• Expert Consensus/Grading: For the "Clinical External Image Quality Review," the ground truth was established by "US board certified reviewers" who graded the overall image quality as "satisfactory for radiation therapy planning/simulation" against "defined success criteria."
• Phantom Measurements/Technical Specifications: For the phantom tests and IQ integration tests, the ground truth was based on pre-defined technical specifications and expected phantom characteristics (e.g., artifact levels, spectral properties, adherence to SRS IQ requirements).

8. Sample Size for the Training Set

The document does not mention a training set. This is because the Spectral CT 7500 RT is a hardware and software system for image acquisition and reconstruction, not a machine learning or AI model that typically requires a separate training set. The changes described are new software features and an extended field of view for an existing CT system.

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

As no training set is mentioned or implied for this type of device, this question is not applicable. The device's performance demonstration relies on verification against design inputs, validation against user needs, and comparison to predicate devices, along with phantom and clinical image quality evaluations.

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The Spectral CT on Rails is a Computed Tomography X-Ray System intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes. This device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories. The Spectral CT on Rails system acquires one CT dataset – composed of data from a higher-energy detected x-ray spectrum and a lower- energy detected x-ray spectra may be used to analyze the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and to provide information about the chemical composition of the body materials and/or contrast agents. Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number.

This information may be used by a trained healthcare professional as a diagnostic tool for the visualization and analysis of anatomical and pathological structures in patients of all ages, and to be used for diagnostic imaging in radiology, interventional radiology, and cardiology and in oncology.

The system is also 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.

The proposed Spectral CT on Rails System is a whole-body computed tomography (CT) X-Ray System featuring a continuously rotating x-ray tube and detectors gantry and multi-slice capability. The acquired x-ray transmission data is reconstructed by computer into cross-sectional images of the body taken at different angles and planes. The proposed Spectral CT on Rails System consists of three main components: a rotating gantry that slides on a carriage in the horizontal direction, stationary patient support and an operator console for scan control and image reconstruction. On the gantry, the main active components are the X-ray HV power supply, the X-ray tube and the detection system. The fundamental design and characteristics of the main components used in the proposed Spectral CT on Rails System, are identical to the cleared to market primary predicate device, Spectral CT System (K203020). The proposed Spectral CT on Rails System consists of main components that are similar to the cleared for market primary predicate device, Spectral CT (K203020) Gantry. The Gantry consists of the following main internal units: Stator - a fixed mechanical frame that carries HW and SW Rotor - A rotating circular stiff frame that is mounted in and supported by the stator. X-Ray Tube (XRT) and its power Generator, and the upper beam mechanism – fixed to the Rotor frame Rails - the rails system includes a carriage which the gantry sits on so that it may be moved back and forth on the rails horizontally relative to a stationary patient support that the patient lays on. The moving gantry functionality has previously been cleared in, Philips CT Big Bore Sliding Gantry Configuration (K181797), secondary predicate device. Data Measurement System (DMS) – a detectors array, fixed to the rotor in front of the XRT.

Console - A computer and display that interfaces between the system and the user. Common Image Reconstruction Unit (CIRS) – a dedicated powerful image reconstruction system

In addition to the above components and the operating software, the system includes: Workstation hardware and software for data acquisition and image display, manipulation, storage, and filming; as well as post-processing into views other than the original axial images. Spectral Reconstruction System Spectral CT Viewer.

Here's a breakdown of the acceptance criteria and study information for the Philips Medical Systems Nederland B.V. Spectral CT on Rails (K212875), based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to a predicate device (Spectral CT K203020) rather than listing explicit quantitative acceptance criteria for each image quality metric. Instead, the acceptance criterion for the Spectral CT on Rails is that its performance is "equivalent" to the predicate device.

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

• Sample Size for Anthropomorphic Phantom Image Review Testing: Not explicitly stated, but it involved "an anthropomorphic phantom" scanned on both the proposed device and the predicate device. It implies a single phantom, however, multiple "scans" were performed.
• Sample Size for Image Quality Performance Testing: Not explicitly stated, but involved "physics image quality test phantoms" scanned on both devices. It implies multiple phantoms covering different image quality metrics.
• Data Provenance: The data is generated internally by Philips through testing of their devices (proposed and predicate). It is not retrospective or prospective clinical data from patients but rather non-clinical phantom-based image quality data. The country of origin of the data is not specified beyond being Philips' internal testing.

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

• Anthropomorphic Phantom Image Review Testing: The review was performed to "determine if the two scanners produced comparable image quality." It does not specify the number or qualifications of experts involved in this review. It states "After the review of the clinical scenarios it was concluded..." This suggests a qualitative assessment by an unnamed reviewer(s).
• Image Quality Performance Testing: This involved quantitative measurements on physics phantoms. Ground truth is established by the known physical properties and measurement methods for metrics like CT number, uniformity, noise, spatial resolution, etc., rather than expert reader consensus. Therefore, no "experts" in the sense of radiologists establishing ground truth for clinical cases are mentioned for this type of test.

4. Adjudication Method for the Test Set:

• For the anthropomorphic phantom image review, the document simply states "Each scan was reviewed to determine if the two scanners produced comparable image quality" and "it was concluded that the image quality... was equivalent." No specific adjudication method (e.g., 2+1, 3+1) is mentioned.

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

• No MRMC comparative effectiveness study was done. The submission states: "The subject of this premarket submission, the proposed Spectral CT on Rails did not require clinical studies to support equivalence Clinical Performance Data." The studies performed were non-clinical image quality comparisons.

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

• The Spectral CT on Rails is a complete computed tomography x-ray system, not an AI algorithm. Therefore, the concept of "standalone (algorithm only)" doesn't directly apply here in the way it would for an AI-powered diagnostic software. The device's performance, as a system, was evaluated.
• However, the image quality performance testing can be considered an objective, quantitative assessment of the system's output (images) without human interpretation influencing the primary metrics being measured (CT number, noise, spatial resolution, etc.). The anthropomorphic phantom review has a human qualitative component, but the quantitative image quality metrics are standalone.

7. The Type of Ground Truth Used:

• Phantom-based Ground Truth: For the "Image quality performance testing," the ground truth is established by the known physical characteristics of the test phantoms (e.g., Catphan phantom for low contrast resolution) and the objective physical measurements performed on the acquired images.
• Qualitative Comparison for Anthropomorphic Phantom: For the "Anthropomorphic phantom image review testing," the ground truth for "comparable image quality for typical clinical applications" is based on a qualitative review, implicitly against established expectations for CT image quality and the predicate device's performance.

8. The Sample Size for the Training Set:

• This submission describes a hardware and software system ("Spectral CT on Rails"), not an AI/Machine Learning model that requires a "training set" in the conventional sense. The "training" for such a system typically involves engineering design, development, and validation against specifications, not data-driven machine learning training. Therefore, no training set sample size is applicable or provided.

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

• As concluded in point 8, this question is not applicable as there is no "training set" for an AI/ML model described in this submission for this device.

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The Spectral CT is a Computed Tomography X-Ray System intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes. This device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.

The Spectral CT system acquires one CT dataset - composed of data from a higher-energy detected x-ray spectrum and a lower- energy detected x-ray spectra may be used to analyze the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and to provide information about the chemical composition of the body materials and/or contrast agents. Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number.

This information may be used by a trained healthcare professional as a diagnostic tool for the visualization and analysis of anatomical and pathological structures in patients of all ages, and to be used for diagnostic imaging in radiology, interventional radiology, and cardiology as part of treatment preparation and radiation therapy planning.

The system is also 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.

The proposed Spectral CT System is a whole-body computed tomography (CT) X-Ray System featuring a continuously rotating x-ray tube and detectors gantry and multi-slice capability. The acquired x-ray transmission data is reconstructed by computer into cross-sectional images of the body taken at different angles and planes. This device also includes signal analysis and display equipment; patient and equipment supports; components; and accessories. The proposed Spectral CT System includes a detector array, which has spectral capability same as the cleared to market predicate device - Philips IQon Spectral CT System (K193454).

The proposed Spectral CT System consists of main components that are similar to the cleared to market predicate device, Philips IQon Spectral CT cleared under (K193454):
➤ Gantry -
On the rotating gantry, the main active components are:
• x-ray high voltage (HV) power supply,
• the x-ray tube,
• detection system
➤ Patient couch
➤ Operator console for control
➤ Common Image Reconstruction Unit (CIRS)
In addition to the above components and the operating software, the system includes:
• Workstation hardware and software for data acquisition and image display, manipulation, storage, and filming; as well as post-processing into views other than the original axial images.
• Patient supports (positioning aids) are used to position the patient.
• Spectral Reconstruction System
• Spectral CT Viewer.

This document is a 510(k) summary for the Philips Spectral CT system (K203020). It seeks to demonstrate substantial equivalence to a predicate device, the Philips IQon Spectral CT (K193454).

Here's an analysis of the provided information regarding acceptance criteria and supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present acceptance criteria in a quantitative table with specific performance metrics (e.g., sensitivity, specificity, accuracy thresholds). Instead, the acceptance criteria are generally described as compliance with consensus standards and guidance documents, and meeting design input requirements.

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

The document explicitly states: "There was no clinical testing conducted for the submission." This means there is no "test set" in the sense of patient data used to evaluate device performance on clinically relevant outcomes. The testing described is non-clinical performance testing.

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

Since no clinical testing was performed and therefore no clinical "test set" was used, there were no experts used to establish ground truth from patient data.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set was used.

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

No. The document explicitly states: "There was no clinical testing conducted for the submission." Therefore, no MRMC study comparing human readers with and without AI assistance was performed.

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

The device is a Computed Tomography X-Ray System, not a standalone AI algorithm. The performance evaluation focuses on the system's ability to acquire and reconstruct images and provide spectral analysis, not on an algorithm's diagnostic performance without human input. The "spectral results for cardiac" improvement is an algorithmic modification, but its performance is assessed as part of the overall system's technical capabilities and compliance with standards, not as a standalone diagnostic tool.

7. The Type of Ground Truth Used

For the non-clinical performance testing, the "ground truth" or reference was based on:

• Engineering specifications and design input requirements.
• International and FDA-recognized consensus standards (e.g., IEC 60601 series, ISO 14971).
• FDA guidance documents.
• The performance and characteristics of the predicate device (Philips IQon Spectral CT K193454).

8. The Sample Size for the Training Set

Not applicable. This submission is for a CT scanner system, not a machine learning model that requires a "training set" of data for its core functionality as described. While there are "Software life-cycle processes" compliant with IEC 62304, these relate to the overall development and verification of the software components of the CT system, not the training of a predictive AI model from a distinct dataset. The mention of "modification of the previously cleared classification method to target calcified structures" within the "Improved Spectral results" does imply some form of algorithm (or "classification method") development, but the document does not provide details on a specific training set size for this, nor does it present this as a primary subject of the 510(k) submission requiring clinical validation with a training set.

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

Not applicable, as there's no defined "training set" in the context of this 510(k) summary for a CT system. Any underlying algorithms for spectral analysis would have had their "ground truth" derived from physics principles, material science, and possibly phantoms or validated datasets, but these details are not provided as part of this regulatory submission.

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The IQon Spectral CT is a Computed Tomography X-Ray System intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes. This device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.

The IQon Spectral CT system acquires one CT dataset – composed of data from a higher-energy detected x-ray spectrum and a lower- energy detected x-ray spectra may be used to analyse the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and to provide information composition of the body materials and/or contrast agents. Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number.

This information may be used by a trained healthcare professional as a diagnostic tool for the visualization and analysis of anatomical and pathological structures and to be used for diagnostic imaging in radiology, interventional radiology, and cardiology and in oncology as part of treatment preparation and radiation therapy planning.

The system is also 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.

The proposed IQon Spectral CT System is a whole-body computed tomography (CT) X-Ray System featuring a continuously rotating x-ray tube and detectors gantry and multi-slice capability. The acquired x-ray transmission data is reconstructed by computer into cross-sectional images of the body taken at different angles and planes. This device also includes signal analysis and display equipment; patient and equipment supports; components; and accessories. The proposed IQon Spectral CT System includes the detector array, which is identical to the currently marketed and predicate device – Philips IQon Spectral CT System (K163711).

The proposed IQon Spectral CT System consists of three main components, that are identical to the currently marketed and predicate device. Philips IQon Spectral CT System (K163711) - a scanner system that includes a rotating gantry, a movable patient couch, and an operator console for control and image reconstruction; a Spectral Reconstruction System; and a Spectral CT Viewer. On the gantry, the main active components are the x-ray high voltage (HV) power supply, the x-ray tube, and the detection system.

In addition to the above components and the software operating them, the proposed IQon Spectral CT System includes workstation hardware and software for data acquisition; image display, manipulation, storage, and filming, as well as post-processing for views other than the original axial images. Patient supports (positioning aids) are used to position the patient.

The provided text is a 510(k) summary for the Philips IQon Spectral CT system. It states that the device is substantially equivalent to a previously cleared predicate device (K163711) and describes non-clinical performance and a "change of indication for use statement and minor modifications." Crucially, this document explicitly states, "The proposed IQon Spectral CT system did not require any external clinical study."

Therefore, many of the requested details regarding acceptance criteria for an AI/CADe device performance study, sample sizes for test sets, expert ground truth establishment, MRMC studies, and standalone performance tests are not applicable in this context. This 510(k) is for a CT scanner itself and highlights updates to its indications for use and minor modifications, not for a new AI/CADe algorithm requiring specific clinical performance evaluation as described in the prompt.

However, based on the information provided, I can infer the "acceptance criteria" for the device itself and how the non-clinical performance demonstrates it meets those criteria, as detailed in the document.

Here's an interpretation based on the provided text, addressing the prompt as best as possible given the nature of the submission (a CT scanner, not an AI model):

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

Since this is a submission for a CT scanner and not an AI/CADe device with specific performance metrics like sensitivity/specificity for disease detection, the "acceptance criteria" relate to safety, effectiveness, and compliance with standards.

• IEC 60601-1:2005 (Third Edition) + CORR. 1:2006 + CORR. 2:2007 + A1:2012
• IEC 60601-1-2:2014
• IEC 60601-1-3:2008+A1:2013
• IEC 60601-1-6:2010 +A1: 2013
• IEC 60601-2-44:2009/AMD2:2016
• IEC 62304:2006 + A1: 2015
• ISO 10993-1:2009/Cor.1:2010
• ISO 14971 2nd Edition. |
  | Compliance with Device Specific Guidance Documents | Non-clinical performance testing demonstrates compliance with:
• Guidance for Industry and FDA Staff - Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" (May 11, 2005)
• Content of Premarket Submissions for Management of Cybersecurity in Medical Devices (October 2, 2014). |
  | Meeting established system and sub-system level design input requirements | Design Verification planning and testing was conducted at sub-system and system levels; activities demonstrate system/sub-systems meet requirements. |
  | Image Quality Verification | Included in Design Verification; "Sample clinical images were provided... reviewed and evaluated by certified radiologists. All images were evaluated to have good image quality." |
  | Risk Analysis and Mitigation | Risk analysis risk mitigation testing included in Design Verification. Traceability Matrix links requirements, hazard mitigations, and test protocols. |
  | Usability and Clinical Workflow Validation for intended use and commercial claims | Non-Clinical design validation testing covered intended use and commercial claims as well as usability testing with representative intended users, including clinical workflow validation and service validation. |
  | Demonstration of Substantial Equivalence to Predicate Device (K163711) in Safety and Effectiveness | Demonstrated through: Indication for use (updated statement not introducing new risk), Technological characteristics (identical fundamental scientific technology), Non-clinical performance testing (compliance with standards), and Safety and effectiveness (as safe/effective as predicate). |

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

• Test Set Sample Size: Not explicitly stated as a number of patient cases or images, as this was a non-clinical evaluation focusing on system performance and compliance, not a clinical trial for an AI/CADe's diagnostic accuracy. The document mentions "Sample clinical images were provided," but not the quantity, provenance, or whether they constituted a standardized "test set" in the sense of an algorithm performance evaluation.
• Data Provenance: Not specified. Given it's a CT scanner, images would likely be from existing clinical data or phantom studies. The document mentions "Sample clinical images were provided," but doesn't detail their origin (e.g., country, retrospective/prospective).
• Retrospective or Prospective: Unspecified, but likely retrospective for image evaluation.

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

• Number of Experts: Not specified.
• Qualifications of Experts: "Certified radiologists" were used to evaluate image quality. No further details on experience or specialization are provided within this document.
• Establishment of Ground Truth: For image quality, the radiologists' evaluation of "good image quality" served as the assessment. For the system's overall safety and effectiveness, compliance with standards and internal testing served as the primary proof, rather than establishing a diagnostic "ground truth" for disease as would be needed for an AI algorithm.

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

Not applicable as there was no formal "test set" in the context of an AI/CADe performance study requiring ground truth adjudication. The radiologists' image quality evaluation method 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

No. The document explicitly states: "The proposed IQon Spectral CT system did not require any external clinical study." Therefore, no MRMC study comparing human readers with and without AI assistance was performed or reported here.

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

Not applicable. This is for the CT scanner hardware/software system, not a standalone AI algorithm. The image reconstruction and analysis features like "Electron Density" and "Calcium Suppression Index" are integrated capabilities of the CT system, not separate AI algorithms undergoing standalone performance evaluation for diagnostic accuracy.

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

For image quality, the "ground truth" was based on the qualitative assessment of "good image quality" by certified radiologists. For system compliance, the "ground truth" was the defined requirements of international standards and internal specifications, tested through verification and validation activities. No pathology or outcomes data ground truth for disease diagnosis was required or used in this submission as it's not for an AI diagnostic aid.

8. The sample size for the training set

Not applicable. This document describes a CT scanner system, not a machine learning model that requires a training set. The descriptions of "Electron Density" and "Calcium Suppression Index" involve dedicated algorithms, but no details of training data for these are provided, nor would they typically be detailed in this type of submission for established image processing techniques in a CT scanner.

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

Not applicable, as there is no mention of a training set for an AI model.

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The IQon Spectral CT is a Computed Tomography X-Ray System intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes. This device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories. The IQon Spectral CT system acquires one CT dataset - composed of data from a higher-energy detected x-ray spectrum and a lower- energy detected x-ray spectra may be used to analyze the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and to provide information about the chemical composition of the body materials and/or contrast agents. Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number.

This information may be used by a trained healthcare professional as a diagnostic tool for the visualization and analysis of anatomical and pathological structures.

The system is also 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.

The IQon Spectral CT is a whole-body computed tomography (CT) X-Ray System featuring a continuously rotating x-ray tube and detectors gantry and multi-slice capability. The acquired xray transmission data is reconstructed by computer into crosssectional images of the body taken at different angles and planes. This device also includes signal analysis and display equipment; patient and equipment supports; components; and accessories. The IQon Spectral CT includes the detector array previously described in K133674 "Philips IQon Spectral CT".

The IQon Spectral CT consists of three main components - a scanner system that includes a rotating gantry, a movable patient couch, and an operator console for control and image reconstruction; a Spectral Reconstruction System; and a Spectral CT Viewer. On the gantry, the main active components are the x-ray high voltage (HV) power supply, the x-ray tube, and the detection system.

In addition to the above components and the software operating them, the system includes workstation hardware and software for data acquisition; and image display, manipulation, storage, and filming, as well as post-processing into views other than the original axial images. Patient supports (positioning aids) are used to position the patient.

This document, a 510(k) Pre-Market Notification for the Philips IQon Spectral CT (K163711), indicates that no new clinical study was required to demonstrate substantial equivalence for the core device to its predicate (K133674). The addition of "Low Dose CT Lung Cancer Screening" to the Indications for Use was supported by a comparative assessment to another cleared device (K153444), rather than a de novo clinical study for the IQon Spectral CT itself.

Therefore, much of the requested information about acceptance criteria for a specific study conducted for this device, sample sizes for test sets, ground truth establishment, expert qualifications, and MRMC studies, is not present in this document as it pertains to this specific 510(k) submission for the IQon Spectral CT. The document relies heavily on the substantial equivalence to previously cleared devices.

However, I can extract information related to the general acceptance of the device based on non-clinical testing and its reliance on previously cleared predicate devices.

Acceptance Criteria and Device Performance (Based on Non-Clinical Data and Substantial Equivalence)

• IEC 60601-1:2005+A1:2012
• IEC 60601-1-2:2007
• IEC 60601-1-3 Edition 2.0:2008
• IEC 60601-1-6:2010
• IEC 60601-2-44:2009
• ISO 14971:2007 (Application of risk management to medical devices) |
  | Compliance with FDA device-specific guidance documents | The IQon Spectral CT System complies with:
• Guidance for Industry and FDA Staff – "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" (May 11, 2005)
• Content of Premarket Submissions for Management of Cybersecurity in Medical Devices (Oct 2, 2014) |
  | Adequacy for intended use | "Non-Clinical verification and or validation tests have been performed with regards to the intended use, the technical claims, the requirement specifications and the risk management results."
  "The results of these tests demonstrate that the IQon Spectral CT System met the acceptance criteria and is adequate for its intended use." |
  | Image Quality and Technological Characteristics (for LDCT) | "The addition of lung cancer screening to the IFU statement was supported with a comparative assessment of image quality and technological characteristics to the devices cleared for this use in K153444 [Philips Multislice CT System with Low Dose CT Lung Cancer Screening]." (This implies that the IQon Spectral CT's performance for LDCT was deemed comparable to a previously cleared device for that specific indication, but specific metrics are not detailed in this document). |
  | Safety and Effectiveness | "The IQon Spectral CT System is substantially equivalent to the currently marketed and predicate device, Philips IQon Spectral CT (K133674, Nov. 21, 2014) in terms of safety and effectiveness." |

Study Details (as inferable from the document):

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

   • This 510(k) relies on non-clinical verification and validation testing, and comparative assessment to predicate devices, rather than a new clinical study. Therefore, there is no "test set" in the context of a new prospective or retrospective clinical study of patients, or information on data provenance, within this specific submission. The non-clinical tests would have involved phantom or laboratory testing.

2. 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 applicable, as no new clinical test set requiring expert ground truth establishment is described in this 510(k). The "ground truth" for compliance testing would be defined by the standards and technical specifications being verified.

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

   • Not applicable, as no new clinical test set is described.

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

   • No MRMC study is mentioned or appears to have been conducted for this 510(k) submission. The device is a CT scanner, not an AI-assisted diagnostic tool in the typical sense that would necessitate an MRMC study for improved reader performance for this submission. The "minor improvements to some spectral algorithms" are internal technical refinements, not standalone AI algorithms for interpretation.

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

   • Not applicable. The IQon Spectral CT is a medical imaging device. Its function involves acquiring and processing images for interpretation by a human healthcare professional. There isn't a standalone algorithm performance evaluation described independent of the imaging system. The modifications mentioned ("minor improvements to some spectral algorithms") are part of the image generation/processing pipeline, not a separate diagnostic algorithm.

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

   • For the non-clinical performance data, the ground truth would be the established specifications and requirements defined by the international and FDA-recognized consensus standards (e.g., image quality metrics, dose measurements in phantoms, electrical safety parameters) and the technical design requirements of the device.
   • For the Low Dose CT Lung Cancer Screening indication, the ground for clinical validity would stem from the clinical literature referenced (e.g., National Lung Screening Trial) and the established inclusion criteria/protocols of governmental/professional medical societies, which inherently rely on outcomes data and pathology for nodule malignancy. The IQon Spectral CT's role is to provide the imaging data.

7. The sample size for the training set:

   • Not applicable. This document describes a medical device clearance based on substantial equivalence and non-clinical testing, not a machine learning model requiring a training set. The "spectral algorithms" receiving "minor improvements" are likely image reconstruction and processing algorithms that have been refined based on engineering principles and potentially internal validation, not AI models trained on large datasets.

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

   • Not applicable, as no training set for a machine learning model is described in this 510(k) submission.

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The Philips Spectral CT Applications support viewing and analysis of images at energies selected from the available spectrum in order to provide information about the chemical composition of the body materials and/or contrast agents. The Spectral CT Applications provide for the quantification and graphical display of attenuation, material density, and effective atomic number. This information may be used by a trained healthcare professional as a diagnostic tool for the visualization and analysis of anatomical and pathological structures.

The Spectral enhanced Advanced Vessel Analysis (SAVA) application is intended to assist clinicians in viewing and evaluating CT images, for the inspection of contrast-enhanced vessels.

The Spectral enhanced Comprehensive Cardiac Analysis (SCCA) application is intended to assist clinicians in viewing and evaluating cardiovascular CT images.

The Spectral enhanced Tumor Tracking (sTT) application is intended to assist clinicians in viewing and evaluating CT images, for the inspection of tumors.

The Spectral CT Applications package introduces a set of three SW clinical applications: spectral enhanced Comprehensive Cardiac Analysis (sCCA), spectral enhanced Advanced Vessel Analysis (sAVA), and spectral enhanced Tumor Tracking (sTT). Each application provides tools that assist a trained personal in visualization and analysis of anatomical and pathological structures.

The sCCA application is targeted to assist the user in analysis and diagnostic of Cardiac Cases, as contrast enhanced and ECG triggered scans. The application input is a cardiac case that was acquired on the IQon CT scanner; the application takes the user through typical workflow steps that allow him to extract qualitative and quantitative information on the coronary tree and chambers. The output of this application is information on physical (length, width, volume) and composition properties (Effective Atomic number, Attenuation, HU) of the coronary vessel & findings along it.

The sAVA application is targeted to assist the user in analysis and diagnostic of CT Angiography cases, as contrast enhanced and whole body CT-angiography scans. The application input is a CT Angiography case that was acquired on the IQon CT scanner; the application takes the user through typical workflow steps that allow him to extract qualitative and quantitative information on the vessel of interest. The output of this application is information on physical (length, width, volume) and composition properties (Effective Atomic number, Attenuation, HU) of the vessels & findings along it.

The sTT application is targeted to assist the user in analysis of tumors, as contrast enhanced, soft tissue oriented, and whole body scans. The application input is a tumor suspected contrast enhanced case that was acquired on the IQon CT scanner; the application takes the user through typical workflow steps that allow him to extract qualitative and quantitative information on the tumor of interest. The output of this application is information on physical (length, width, volume) and composition properties (Effective Atomic number, Attenuation, HU) of the tumor.

The provided text describes the Philips Spectral CT Applications, a set of software clinical applications (sCCA, sAVA, sTT) designed to assist clinicians in viewing and evaluating CT images with spectral data. While the document mentions verification and validation, it does not provide explicit acceptance criteria in a quantitative table or detailed performance metrics against those criteria. It generally states that "SW requirements were met" and "intended uses and defined user needs were met."

Therefore, I cannot populate a table of acceptance criteria and reported device performance with specific numerical values from the provided text. However, I can extract information related to the study that proves the device meets its intended uses and user needs, as described in the "Summary of Clinical Testing" section.

Here's a breakdown of the available information:

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

No explicit quantitative acceptance criteria or corresponding reported device performance metrics are provided in the document. The document states that "SW requirements were met" and "intended uses and defined user needs were met."

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

• Test Set Sample Size: "clinical datasets" – specific number not provided.
• Data Provenance: The datasets were "derived from Philips IQon Spectral CT system (K133674)." The country of origin is not specified, but the manufacturer is Philips Medical Systems Nederland B.V. and the regulatory contact is in the USA. The data appears to be retrospective, as it's referred to as "clinical datasets" used for validation, not newly acquired data specifically for this study.

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

• Number of Experts: "Philips Internal certified radiologists" – specific number not provided.
• Qualifications of Experts: "certified radiologists" - specific experience level (e.g., 10 years) not provided. They are referred to as representing "a typical user."

4. Adjudication method for the test set:

• Adjudication Method: Not explicitly stated. The document mentions that "The evaluators were questioned against each of the intended uses and provided score to describe their level of satisfaction." This suggests individual evaluation rather than a formal consensus or adjudication process among multiple readers for ground truth establishment.

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 MRMC comparative effectiveness study, comparing human readers with and without AI assistance, is described. The validation focused on whether the applications meet intended uses and user needs, as evaluated by radiologists. The applications are described as "assistive tools" for clinicians.

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

• Standalone Performance: Not explicitly evaluated or described. The validation confirms that the applications "allow visualization, manipulation and analysis of spectral data" and "assist clinicians in viewing and evaluating CT images." This implies human interaction as part of the intended use.

7. The type of ground truth used:

• Ground Truth Type: The ground truth for the validation appears to be based on the subjective evaluation and "satisfaction scores" provided by "Philips Internal certified radiologists" against the stated intended uses and user needs. It is based on expert consensus/evaluation of the utility of the application's outputs, rather than a separate, independent "ground truth" like pathology or outcomes data.

8. The sample size for the training set:

• Training Set Sample Size: Not specified. The document primarily discusses verification and validation using "datasets that were generated by the Philips IQon Spectral CT system" and "clinical datasets." It does not provide details on a distinct training set.

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

• Ground Truth for Training Set: Not specified, as details about a separate training set or how its ground truth was established are not provided in the document.

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The Philips IQon Spectral CT is a Computed Tomography X-Ray System intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes. This device may include signal analysis and display equipment, patient and equipment parts, and accessories.

The IQon Spectral CT system acquires one CT dataset – composed of data from a higher-energy detected x-ray spectrum and a lower- energy detected x-ray spectramay be used to analyze the differences in the energy dependence of the attenuation coefficient of different materials. This allows for the generation of images at energies selected from the available spectrum and to provide information about the chemical composition of the body materials and/or contrast agents. Additionally, materials analysis provides for the quantification and graphical display of attenuation, material density, and effective atomic number.

This information may be used by a trained healthcare professional as a diagnostic tool for the visualization and analysis of anatomical and pathological structures.

The Philips IQon Spectral CT is a whole-body computed tomography (CT) X-Ray System featuring a continuously rotating x-ray tube and detectors gantry and multi-slice capability. The acquired x-ray transmission data is reconstructed by computer into cross-sectional images of the body taken at different angles and planes. This device also includes signal analysis and display equipment; patient and equipment supports; components; and accessories. The Philips IQon Spectral CT includes the detector array previously described in K131773 "Modified Brilliance iCT".

The IQon Spectral CT consists of three main components – a scanner system that includes a rotating gantry, a movable patient couch, and an operator console for control and image reconstruction; a Spectral Reconstruction System; and a Spectral CT Viewer. On the gantry, the main active components are the x-ray high voltage (HV) power supply, the x-ray tube, and the detection system.

In addition to the above components and the software operating them, the system includes workstation hardware and software for data acquisition; and image display, manipulation, storage, and filming, as well as post-processing into views other than the original axial images. Patient supports (positioning aids) are used to position the patient.

The Philips IQon Spectral CT is a Computed Tomography (CT) X-Ray System. The provided document is a 510(k) Summary, which describes the device and its intended use, and provides a summary of non-clinical and clinical testing to demonstrate substantial equivalence to a predicate device. However, it does not contain specific acceptance criteria, detailed study designs, or reported device performance metrics in the format requested, such as sensitivity, specificity, or AUC calculated from a clinical trial. The document focuses on regulatory compliance and the types of tests performed rather than the quantitative results against specific criteria.

Therefore, I cannot fully complete the requested table and answer all questions with the detailed information usually found in a clinical study report. I will extract what information is present.

Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list quantitative acceptance criteria in a table format for specific performance metrics (e.g., sensitivity, specificity, accuracy) that would be typically established for a diagnostic device. It focuses on demonstrating conformance to standards and the utility of new spectral imaging capabilities.

Instead of specific acceptance criteria, the document states general conformance to standards and demonstrates capabilities:

Study Details (Based on available information)

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

   • Test Set Sample Size: Not explicitly stated in terms of number of patients or cases. The document mentions "Clinical images were collected and analyzed," but does not provide a specific count.
   • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). It is a "Summary of Clinical Testing," suggesting real-world clinical data was used, but details are absent.

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

   • Not specified. The document states "This evaluation demonstrated that spectral images were useful for the visualization and analysis of anatomical and pathological structures," implying evaluation by trained healthcare professionals, but no details on the number or qualifications of these experts are provided.

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

   • Not specified.

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

   • The document describes the Philips IQon Spectral CT as a device for generating images and quantitative data, not an AI software/algorithm that assists human readers. Therefore, a multi-reader, multi-case (MRMC) comparative effectiveness study focusing on the improvement of human readers with AI assistance is not applicable to this device as described. The clinical testing mentioned focused on the utility of the spectral images themselves for visualization and analysis.

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

   • The IQon Spectral CT is a CT scanner system that produces images and performs material analysis. Its core function is image acquisition and reconstruction, and spectral capabilities like quantification of iodine, calcium, and effective atomic number are inherent features of the device's processing capabilities. It's not an "algorithm only" in the sense of a separate AI-driven diagnostic tool. The "performance" in this context refers to the system's ability to generate these specific types of images and quantitative data accurately and consistently, which was assessed through non-clinical (phantom-based) and clinical evaluation. The clinical evaluation primarily confirmed the usefulness of the generated spectral images.

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

   • For non-clinical testing, the ground truth appears to be established through the specifications of phantoms and reference measurements (e.g., assessing CT linearity, spatial resolution, low contrast detectability against known values).
   • For clinical testing, the "ground truth" for demonstrating usefulness in "visualization and analysis of anatomical and pathological structures" would typically involve comparison with existing diagnostic methods, expert interpretation of images, or correlation with pathology/clinical outcomes. However, the document does not specify the exact type of ground truth used for the clinical evaluation. It only states that the images were found "useful."

7. The sample size for the training set:

   • The document describes a CT System, not a machine learning algorithm that requires a "training set" in the conventional sense. The "training" for such a system would involve engineering and calibration using diverse data to ensure robustness across various patient anatomies and conditions, but this is not a "training set" as understood in AI/ML performance studies.

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

   • As this is not an AI/ML algorithm requiring a "training set" with ground truth labels in the typical sense, this question is not applicable here. The system's design and calibration are based on physical principles of CT imaging and spectral analysis.

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