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510(k) Data Aggregation
(128 days)
The Photonova Spectra, Photonova Spectra Select system is a silicon-based spectral photon counting detector X-ray Computed Tomography scanner.
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 angles.
The system acquires multi-energy data in every scan and natively generates high resolution monochromatic images and material density maps to facilitate visualizing and analyzing information about anatomical and pathological structures.
The system is indicated for head, whole body, cardiac, and vascular CT applications. The system is indicated for patients of all ages. The images can be post-processed to produce additional imaging planes or analysis results.
The system is indicated for lung cancer screening for patients meeting the established inclusion criteria of programs/protocols that have been 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.
Photonova Spectra is the next iteration of the predicate, the Revolution Apex platform (K213715), introducing a new Deep Silicon (dSi) photon counting detector for CT imaging. Photonova Spectra aims to realize an improvement in both spatial resolution and spectral imaging performance relative to traditional Energy Integrating Detector (EID) systems for diagnostic CT. With photon-counting detectors that can better discriminate energies, spectral CT imaging can natively provide valuable information about tissue composition and material density without the need for active filtration or kVp modulation by performing material decomposition directly from native multi-energy data.
The Photonova Spectra system is an ultra-premium multi-slice CT scanning system comprised of a gantry, a detector, an x-ray tube, a power distribution unit (PDU), a table, a system cabinet, a scanner desktop computer and user interface, and associated accessories. It is designed as a volumetric CT scanner to provide advanced imaging capability for a range of clinical applications.
Compared to the predicate Revolution Apex, the key differences of the Photonova Spectra System consist of a Deep Silicon (dSi) X-ray detector capable of directly converting X-ray photons to electrical signals, advanced detector data acquisition hardware for managing and processing of large volumes of data, advanced computer hardware and an enhanced image chain for generating High Definition (HD) Spectral and Ultra High Definition (UHD) image series.
The Photonova Spectra image chain is developed to calibrate, pre-process, reconstruct, and post-process images for use in medical imaging applications. Customized for photon counting detection physics and capability, Photonova Spectra does not require user to choose between single kV and dual energy acquisition modes. With Photonova Spectra, all acquisitions are spectral with 8 energy bins over the full high-resolution detector, and the data is stored real-time on the rotating side as the acquisition completes over the full scan sequence.
The system will be offered with either an 80 mm dSi detector and 40 mm dSi detector model configurations, commercialized as Photonova Spectra and Photonova Spectra Select, respectively. The detector size is the key differentiator, but all core technology and functionality are identical.
The provided FDA 510(k) clearance letter and summary for the Photonova Spectra CT System do not contain detailed information about specific acceptance criteria for device performance or the full study design typically expected for such information. The document focuses on regulatory compliance, technological characteristics compared to a predicate, and a general overview of verification and validation testing.
However, based on the information provided, we can infer some aspects and present them to the best of our ability, while noting the missing details.
Missing Information:
- Specific quantitative acceptance criteria: The document describes the types of tests performed (e.g., image quality metrics, LCD studies) but does not provide numerical thresholds that the device had to meet.
- Specific quantitative reported device performance: While it states "substantial equivalence of image quality was demonstrated," it doesn't provide the actual measured values for metrics like CT number accuracy, resolution, or noise texture.
- Detailed sample size for the test set: It mentions a "sample clinical covering a wide range of clinical scenarios" for the reader study but no specific number of cases.
- Data provenance for the test set: The document does not specify the country of origin of the data for the reader study's test set or whether it was retrospective or prospective.
- Detailed qualifications of experts for ground truth: It states "US board-certified Radiologists" but doesn't specify years of experience or subspecialty.
- Adjudication method for the test set.
- Effect size for MRMC study: It implies a reader study was done to compare DL levels, but doesn't quantify improvement with AI assistance.
- Sample size for the training set.
- How ground truth for the training set was established.
Acceptance Criteria and Study for Photonova Spectra CT System
Given the limitations of the provided document, the following is constructed based on the available information and educated inferences regarding CT system clearances.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criterion (Inferred from regulatory context) | Reported Device Performance (Inferred from document) |
|---|---|
| Image Quality (various metrics, e.g., low contrast detectability, spatial resolution, noise power spectrum, CT number accuracy, water accuracy, mean CT number over spectral tasks) | "Substantial equivalence of image quality was demonstrated for the system's DL baseline level of denoising with FBP-based reconstruction." "Evaluated using standard IQ, QA, ACR, and anthropomorphic pediatric phantoms." |
| Diagnostic Interpretability | "No reader identified any added, removed, or reduced diagnostic information in any DLIR setting, and all pathologies were consistently visualized across all DL reconstructions." |
| Safety and Effectiveness | "Photonova Spectra is safe and effective for its intended use." (Conclusion of reader study) "No new questions of safety or effectiveness, hazards, unexpected results, or adverse effects stemming from the changes to the predicate." |
| Compliance with Standards | "In compliance with AAMI/ANSI ES 60601-1 and IEC60601-1 Ed. 3.2 and its associated collateral and particular standards, 21 CFR Subchapter J, and NEMA standards XR 25, and XR 28." |
| Low Contrast Detectability (LCD) | "LCD studies were conducted incorporating a model observer approach." (Outcome implies acceptable performance) |
| Dose Performance | "Dose performance evaluation using well established metrics and methods." (Outcome implies acceptable performance) |
2. Sample Size Used for the Test Set and Data Provenance
The document states "a reader study of sample clinical covering a wide range of clinical scenarios, including Neuro, Body, and Cardiac/Chest." It also mentions "challenging cases from the above-mentioned reader study."
- Sample Size: Not explicitly stated (e.g., number of cases or images).
- Data Provenance: Not explicitly stated (e.g., country of origin, retrospective or prospective).
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
The document mentions: "Images were evaluated by US board-certified Radiologists."
- Number of Experts: Not explicitly stated.
- Qualifications of Experts: US board-certified Radiologists. Specific years of experience or subspecialty (e.g., Neuroradiologist, Cardiothoracic Radiologist) are not provided.
4. Adjudication Method for the Test Set
The document does not explicitly state the adjudication method used for the reader study.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Its Effect Size
A reader study was conducted to compare various levels of user-prescribed denoising. It implies a comparative evaluation between the proposed DL reconstruction and FBP-based reconstruction.
- MRMC Study: Yes, a comparative clinical evaluation of challenging cases was performed by "US board certified Radiologists."
- Effect Size: Not quantified. The qualitative finding was: "No reader identified any added, removed, or reduced diagnostic information in any DLIR setting, and all pathologies were consistently visualized across all DL reconstructions." This suggests that the diagnostic interpretability was maintained, implying no negative effect and potential maintenance or improvement in visualization where denoising was effective, though specific metrics of improvement are not provided.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
Yes, extensive standalone performance testing was done, referred to as "Image Performance Testing (Verification)" and "Summary of Non-Clinical Testing."
- This included "evaluation of a comprehensive set of image quality metrics" and "acquisitions at varying dose levels and phantom sizes."
- Metrics like "CT number, water accuracy, mean CT number over a range of spectral tasks, in-plane resolution, cross-plane resolution and noise texture (as measured by the noise power spectrum)" were assessed.
- "Low contrast detectability (LCD) studies were conducted incorporating a model observer approach."
7. The Type of Ground Truth Used
Based on the description of the studies:
- For standalone (non-clinical) testing: Phantoms (standard IQ, QA, ACR, anthropomorphic pediatric phantoms) and model observer approaches for objective metrics.
- For clinical (reader) testing: Expert consensus/interpretation by US board-certified Radiologists was used to determine diagnostic utility and whether pathologies were consistently visualized across different reconstructions.
8. The Sample Size for the Training Set
The document states that the "proposed TrueFidelity DL for PCCT is intended for routine clinical use and based on the same framework and training methodology as the reference devices (DLIR and DLIR-GSI)." However, the specific sample size for the training set (e.g., number of images, patients) for the Photonova Spectra's TrueFidelity DL for PCCT is not provided.
9. How the Ground Truth for the Training Set Was Established
The document does not explicitly state how the ground truth for the training set was established for the TrueFidelity DL for PCCT, beyond mentioning it uses the "same framework and training methodology" as previously cleared DLIR products. Typically, for deep learning reconstructions in CT, the "ground truth" during training refers to high-quality, often low-noise or high-dose, reference images from which the algorithm learns to denoise or reconstruct lower-quality/lower-dose inputs. These reference images are usually generated from the CT scanner itself (e.g., by repeating scans at very high doses or using iterative reconstruction techniques to establish a cleaner image for comparison). Specific details are not provided.
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(126 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 angles. 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, patient and 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, 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 about the chemical composition of body materials. This approach enables images to be generated at energies selected from the available spectrum to visualize and analyze information about anatomical and pathological structures.
GSI provides information of the chemical composition of renal calculi by calculation and graphical display of the spectrum of effective atomic number. GSI Kidney stone characterization provides additional information to aid in the characterization of uric acid versus non-uric acid stones. It is intended to be used as an adjunct to current standard methods for evaluating stone etiology and composition.
The CT system is indicated for low dose CT for lung cancer screening. 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.
This proposed device Revolution Vibe is a general purpose, premium multi-slice CT Scanning system consisting of a gantry, table, system cabinet, scanner desktop, power distribution unit, and associated accessories. It has been optimized for cardiac performance while still delivering exceptional imaging quality across the entire body.
Revolution Vibe is a modified dual energy CT system based on its predicate device Revolution Apex Elite (K213715). Compared to the predicate, the most notable change in Revolution Vibe is the modified detector design together with corresponding software changes which is optimized for cardiac imaging providing capability to image the whole heart in one single rotation same as the predicate.
Revolution Vibe offers an accessible whole heart coverage, full cardiac capability CT scanner which can deliver outstanding routine head and body imaging capabilities. The detector of Revolution Vibe uses the same GEHC's Gemstone scintillator with 256 x 0.625 mm row providing up to 16 cm of coverage in Z direction within 32 cm scan field of view, and 64 x 0.625 mm row providing up to 4 cm of coverage in Z direction within 50 cm scan field of view. The available gantry rotation speeds are 0.23, 0.28, 0.35, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1.0 seconds per rotation.
Revolution Vibe inherits virtually all of the key technologies from the predicate such as: high tube current (mA) output, 80 cm bore size with Whisper Drive, Deep Learning Image Reconstruction for noise reduction (DLIR K183202/K213999, GSI DLIR K201745), ASIR-V iterative recon, enhanced Extended Field of View (EFOV) reconstruction MaxFOV 2 (K203617), fast rotation speed as fast as 0.23 second/rot (K213715), and spectral imaging capability enabled by ultrafast kilovoltage(kv) switching (K163213), as well as ECG-less cardiac (K233750). It also includes the Auto ROI enabled by AI which is integrated within the existing SmartPrep workflow for predicting Baseline and monitoring ROI automatically. As such, the Revolution Vibe carries over virtually all features and functionalities of the predicate device Revolution Apex Elite (K213715).
This CT system can be used for low dose lung cancer screening in high risk populations*.
The provided FDA 510(k) clearance letter and summary for the Revolution Vibe CT system does not include detailed acceptance criteria or a comprehensive study report to fully characterize the device's performance against specific metrics. The information focuses more on the equivalence to a predicate device and general safety/effectiveness.
However, based on the text, we can infer some aspects related to the Auto ROI feature, which is the only part of the device described with specific performance testing details.
Here's an attempt to extract and describe the available information, with clear indications of what is not provided in the document.
Acceptance Criteria and Device Performance for Auto ROI
The document mentions specific performance testing for the "Auto ROI" feature, which utilizes AI. For other aspects of the Revolution Vibe CT system, the submission relies on demonstrating substantial equivalence to the predicate device (Revolution Apex Elite) through engineering design V&V, bench testing, and a clinical reader study focused on overall image utility, rather than specific quantitative performance metrics meeting predefined acceptance criteria for the entire system.
1. Table of Acceptance Criteria and Reported Device Performance (Specific to Auto ROI)
| Feature/Metric | Acceptance Criteria (Implicit) | Reported Device Performance |
|---|---|---|
| Auto ROI Success Rate | "exceeding the pre-established acceptance criteria" | Testing resulted in "success rates exceeding the pre-established acceptance criteria." (Specific numerical value not provided) |
Note: The document does not provide the explicit numerical value for the "pre-established acceptance criteria" or the actual "success rate" achieved for the Auto ROI feature.
2. Sample Size and Data Provenance for the Test Set (Specific to Auto ROI)
- Sample Size: 1341 clinical images
- Data Provenance: "real clinical practice" (Specific country of origin not mentioned). The images were used for "Auto ROI performance" testing, which implies retrospective analysis of existing clinical data.
3. Number of Experts and Qualifications to Establish Ground Truth (Specific to Auto ROI)
- Number of Experts: Not specified for the Auto ROI ground truth establishment.
- Qualifications of Experts: Not specified for the Auto ROI ground truth establishment.
Note: The document mentions 3 readers for the overall clinical reader study (see point 5), but this is for evaluating the diagnostic utility and image quality of the CT system and not explicitly for establishing ground truth for the Auto ROI feature.
4. Adjudication Method for the Test Set (Specific to Auto ROI)
- Adjudication Method: Not specified for the Auto ROI test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
-
Was an MRMC study done? Yes, a "clinical reader study of sample clinical data" was carried out. It is described as a "blinded, retrospective clinical reader study."
-
Effect Size of Human Readers Improvement with AI vs. without AI assistance: The document states the purpose of this reader study was to validate that "Revolution Vibe are of diagnostic utility and is safe and effective for its intended use." It does not report an effect size or direct comparison of human readers' performance with and without AI assistance (specifically for the Auto ROI feature within the context of reader performance). The study seemed to evaluate the CT system's overall image quality and clinical utility, possibly implying that the Auto ROI is integrated into this overall evaluation, but a comparative effectiveness study of the AI's impact on human performance is not described.
- Details of MRMC Study:
- Number of Cases: 30 CT cardiac exams
- Number of Readers: 3
- Reader Qualifications: US board-certified in Radiology with more than 5 years' experience in CT cardiac imaging.
- Exams Covered: "wide range of cardiac clinical scenarios."
- Reader Task: "Readers were asked to provide evaluation of image quality and the clinical utility."
- Details of MRMC Study:
6. Standalone (Algorithm Only) Performance
- Was a standalone study done? Yes, for the "Auto ROI" feature, performance was tested "using 1341 clinical images from real clinical practice," and "the tests results in success rates exceeding the pre-established acceptance criteria." This implies an algorithm-only evaluation of the Auto ROI's ability to successfully identify and monitor ROI.
7. Type of Ground Truth Used (Specific to Auto ROI)
- Type of Ground Truth: Not explicitly stated for the Auto ROI. Given the "success rates" metric, it likely involved a comparison against a predefined "true" ROI determined by human experts or a gold standard method. It's plausible that this was established by expert consensus or reference standards.
8. Sample Size for the Training Set
- Sample Size: Not provided in the document.
9. How Ground Truth for the Training Set Was Established
- Ground Truth Establishment: Not provided in the document.
In summary, the provided documentation focuses on demonstrating substantial equivalence of the Revolution Vibe CT system to its predicate, Revolution Apex Elite, rather than providing detailed, quantitative performance metrics against specific acceptance criteria for all features. The "Auto ROI" feature is the only component where specific performance testing (standalone) is briefly mentioned, but key details like numerical acceptance criteria, actual success rates, and ground truth methodology for training datasets are not disclosed. The human reader study was for general validation of diagnostic utility, not a comparative effectiveness study of AI assistance.
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