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510(k) Data Aggregation
(31 days)
CareView 750Cw/750C X-ray Flat Panel Detectors
The CareView 750Cw/750C detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.
CareView 750Cw/750C is a kind of wireless(750C does not have wireless, it has only wired fuction.) portable digital X-ray flat panel detectors which have 244 mm x 307 mm imaging area. The device communicates by not only the wireless communication but also wired communication feature (Giga-bit Ethernet communication mode by connecting the power box) optionally.
The device intercepts X-ray photons and then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. After the electrical signals are generated, it is converted to a digital value and an image will be displayed on the monitor.
The detector should be integrated with an operating PC and an X-ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic.
The detector can't provide feedback to the generator to terminate the x-ray exposure.
System Software Version is API V4.5.0 (NDT V3.5.5) that based on V4.2.0. But V4.5.0 is more powerful than old version. Please see the comparison of section 7 Technological Characteristics.
The provided document describes the CareView 750Cw/750C X-ray Flat Panel Detectors and compares them to a predicate device, the CareView 1500Cw. The document primarily focuses on demonstrating substantial equivalence to the predicate device through technical specifications and performance testing. However, it does not contain specific acceptance criteria for a device's diagnostic performance (e.g., sensitivity, specificity, AUC) and therefore does not include a study proving it meets such criteria.
The information available focuses on the device's technical performance and safety.
Here's an analysis of the requested information based on the provided text:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state "acceptance criteria" in terms of diagnostic performance (e.g., sensitivity, specificity for a particular disease). Instead, it provides performance specifications of the proposed device and compares them to the predicate device. The implicit "acceptance" is that the device's technical specifications are comparable to or better than the predicate device and meet relevant regulatory standards.
| Performance Metric | Acceptance Criteria (Implied by Predicate) | Reported Device Performance (CareView 750Cw/750C) |
|---|---|---|
| Image Matrix Size | 2304 x 2816 pixels (Predicate) | 2048 x 2560 pixels |
| Pixel Pitch | 154μm (Predicate) | 120μm |
| Effective Imaging Area | 355 mm x 434 mm (Predicate) | 244 mm x 307 mm |
| Grayscale | 16 bit, 65536 grayscale (Predicate) | 16 bit, 65536 grayscale |
| Spatial Resolution | Min. 3.3 line pair/mm (Predicate) | Min. 4.2 line pair/mm |
| MTF (@ 1lp/mm) | ~70% (Predicate) | ~70% |
| MTF (@ 2lp/mm) | ~40% (Predicate) | ~40% |
| MTF (@ 3lp/mm) | ~22% (Predicate) | ~22% |
| DQE (@RQA5, 30 μGy, 0lp/mm) | ~65% (Predicate) | ~65% |
| DQE (@RQA5, 30 μGy, 3lp/mm) | ~20% (Predicate) | ~20% |
| Dynamic Range | ~82 dB (Predicate) | ~82 dB |
| Electrical Safety & EMC | Complies with IEC/ES 60601-1 and IEC/EN 60601-1-2 (Implied "satisfactory") | All test results are satisfactory according to IEC/ES 60601-1 and IEC/EN 60601-1-2 |
| RF Module Compliance | In compliance with ANSI C63.4-2003 and 47 CFR FCC Part 15 Subpart C | Compliant with ANSI C63.4-2003 and 47 CFR FCC Part 15 Subpart C |
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document mentions "Performance Testing" for metrics like Offset Stability, Dark Noise, Spatial Resolution, Low-contrast Resolution, Dynamic Range & Sensitivity, Lag, Ghost, MTF, and DQE. However, it does not specify a sample size for any clinical test set for diagnostic performance, nor does it mention data provenance (country of origin, retrospective/prospective). The tests described appear to be technical bench tests or phantom studies.
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)
This information is not provided in the document. The document describes technical and safety testing, not clinical studies involving expert interpretation of images for ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided as there is no mention of a diagnostic test set requiring adjudication.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
There is no mention of an MRMC study, comparative effectiveness study, or any assessment of human reader improvement with or without AI assistance. The device described is an X-ray flat panel detector, not an AI-powered diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
This is not applicable as the device is a hardware component (X-ray detector) and not a standalone algorithm.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
For the technical performance tests mentioned (Offset Stability, Dark Noise, Spatial Resolution, etc.), the "ground truth" would be established by physical measurements and calibration standards, not by clinical expert consensus, pathology, or outcomes data. The document does not describe any clinical ground truth.
8. The sample size for the training set
This is not applicable. The device is a hardware X-ray detector; it does not involve a "training set" in the context of machine learning or AI.
9. How the ground truth for the training set was established
This is not applicable as there is no training set for this device.
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