(30 days)
The system is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission projection data from the same axial plane taken at different ans the capability to image whole organs in a single rotation. Whole organs include but are not limited to brain, heart, liver, kidney, pancreas, etc. The system may acquire data using Axial, Cine, Helical, Cardiac, and Gated CT scan techniques from patients of all ages. These images may be obtained either with or without contrast. This device may include signal analysis and display equipment supports, components and accessories.
This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes. Further, the images can be post processed to produce additional imaging planes or analysis results
The system is indicated for head, whole body, cardiac, and vascular X-ray Computed Tomography applications.
The device output is a valuable medical tool for the diagnosis of disease, trauma, or abnormality and for planning, guiding, and monitoring therapy.
If the spectral imaging option is included on the system can acquire CT images using different kV levels of the same anatomical region of a patient in a single rotation from a single source. The differences in the energy dependence of the attenuation coefficient of the different materials provide information of body materials. This approach enables images to be generated at energies selected from the visualize and analyze information about anatomical and pathological structures.
GSI provides information of the chemical composition of renal calculation and graphical display of the spectrum of effective atomic number. GSI Kidney stone characterization orovides addin the characterization of uric acid versus nonuric acid stones. It is intended to be used as an adjunct to current standard methods for evaluating stone etiology and composition.
The Revolution CT is a multi-slice (256 detector row) CT scanner consisting of a gantry, patient table, scanner desktop (operator console), system cabinet, power distribution unit (PDU), and interconnecting cables. The system includes image acquisition hardware, image acquisition and reconstruction software, and associated accessories.
GE has modified the cleared Revolution CT (K133705) within our design controls to include the Gemstone™ Spectral Imaging (GSI) Option. GSI is the state-of-the-art single source, projection-based, spectral CT application. It is GE's unique dual energy design and implementation which offers clear advantage over traditional dual source Dual Energy implementation. This feature has been previously cleared on Discovery CT750 HD (K081105, K120833) and it is fundamentally the same technology on Revolution CT. Revolution CT however offers a few technology improvements to enable Volume GSI with up to 80mm GSI zcollimation, 245mm/s GSI volumetric scan speed, dose neutrality and more improved workflow to support GSI in routine scanning.
The provided text is a 510(k) summary for the GE Revolution CT with GSI option. The document describes the device, its intended use, and indicates that it is substantially equivalent to predicate devices. However, it does not explicitly detail acceptance criteria in a quantitative table or a specific study proving the device meets acceptance criteria in the way often associated with performance claims for AI/ML devices.
Instead, the document focuses on demonstrating substantial equivalence by outlining:
- Technological similarities and differences with predicate devices.
- Compliance with various industry standards (IEC, 21CFR Subchapter J, NEMA XR-25, XR-26, XR-28, XR-29).
- Adherence to quality system regulations (21CFR 820 and ISO 13485).
- Results from non-clinical (phantom) testing and clinical testing.
The clinical testing aimed to evaluate "image quality related to diagnostic use, reduction of metal artifacts using the MAR algorithm, and suppression of iodine in contrast enhanced acquisitions using VUE algorithm." The evaluation was based on a 5-point Likert scale by radiologists, indicating a subjective assessment of image quality and clinical acceptance rather than predefined quantitative performance metrics or acceptance criteria for a specific diagnostic task.
Therefore, many of the requested items cannot be fully extracted as they are not explicitly or quantitatively provided in the document.
Here's an attempt to answer based on the available information:
1. A table of acceptance criteria and the reported device performance
The document does not provide a quantitative table of acceptance criteria for diagnostic performance metrics (e.g., sensitivity, specificity, AUC) and therefore no numerical performance results against such criteria. The clinical assessment focused on "acceptable diagnostic imaging performance" and "image quality," which are qualitative statements derived from expert review.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size (Test Set): 51 subjects.
- Data Provenance: The clinical data was collected from two sites: one in the US and one in Canada. The study was prospective in the sense that it involved recruitment of patients and collection of clinical images for the specific evaluation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Number of experts: 6 board-certified and qualified radiologists.
- Qualifications: "board certified and qualified radiologists at different institutions in the United States of America." (Specific years of experience are not mentioned).
- Ground Truth establishment for Test Set: This refers to the radiologists evaluating the images for "clinical acceptance and image quality using a 5 point Likert scale." This implies a subjective expert assessment of image quality for diagnostic use, reduction of metal artifacts, and suppression of iodine, rather than a definitive "ground truth" for a specific disease outcome or pathology.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- "Each data set was read by three different radiologists depending on their area of expertise." This implies a consensus or individual review approach, but the specific adjudication method (e.g., how disagreements between the three radiologists were resolved or combined into a single outcome) is not specified. It's unclear if a formal adjudication process like 2+1 or 3+1 was used, or if individual reads were separately analyzed.
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
The document describes an evaluation of the device’s image quality and diagnostic performance by multiple radiologists ("multi-reader"). However, it is not an MRMC comparative effectiveness study comparing human readers with AI assistance vs. without AI assistance. The study evaluated the images produced by the device (which includes the GSI option, a form of advanced image processing, but not explicitly framed as an 'AI assistance' to human interpretation in the common sense of AI CAD/X systems) directly for their diagnostic quality. Therefore, there's no reported effect size of human improvement with vs. without AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The GSI functionality itself could be considered a form of "algorithm only" processing that produces specific images/data (e.g., material density maps, monochromatic images, virtual unenhanced images, information for kidney stone characterization). The document states GSI "provides information of the chemical composition of renal calculi by calculation and graphical display of the spectrum of effective atomic number" and "provides additional information to aid in the characterization of uric acid versus non-uric acid stones." This output is interpreted by humans. The testing described focuses on the quality of these generated images/information as assessed by radiologists, not on an automated diagnostic output from the algorithm itself without human interpretation. So, while GSI involves algorithms, it's not presented as a standalone diagnostic algorithm in the typical sense of AI/CAD systems providing a diagnosis.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- The "ground truth" for the clinical evaluation of the test set was essentially expert assessment/consensus based on image quality and clinical acceptance using a Likert scale. It was not based on definitive pathology, histology, or long-term outcomes data for establishing true disease presence or absence for a diagnostic accuracy study. For kidney stone characterization, it 'provides additional information' and is 'intended to be used as an adjunct to current standard methods for evaluating stone etiology and composition,' implying that the ultimate ground truth for stone composition would come from other established methods.
8. The sample size for the training set
The document does not explicitly mention a "training set" with a specified sample size. This device is an imaging system (CT scanner) with advanced image processing (GSI), not a machine learning model that would typically have a distinct training set for diagnostic classification in the same way. The technologies are based on physics and signal processing, using proprietary algorithms.
9. How the ground truth for the training set was established
Since a "training set" for a machine learning model is not explicitly described, neither is the method for establishing its ground truth. The development of the GSI algorithms would have involved engineering and possibly empirical data to refine the material decomposition and image generation, but this is not characterized as a "training set" in the context of supervised learning.
§ 892.1750 Computed tomography x-ray system.
(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.