Search Results

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.

Ask a specific question about this device