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510(k) Data Aggregation
(27 days)
1717FCC is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic systems in all general purpose diagnostic procedures. Not to be used for mammography.
1717FCC is a digital solid state X-ray detector that is based on flat-panel technology. This radiographic image detector and processing unit consists of a scintillator coupled to amorphous silicon (a-Si) / Indium Gallium Zinc Oxide (IGZO) on TFT sensor. This device is connected to the user PC via wired LAN (ethernet cable) and it needs to be integrated with a radiographic imaging system. It does not operate as an X-ray generator controller but can be utilized to capture and digitalize X-ray images for radiographic diagnosis. The RAW files can be further processed as DICOM compatible image files by separate console SW(Xmaru RF) for a radiographic diagnosis and analysis.
The provided text describes a 510(k) summary for the Rayence 1717FCC Digital Flat Panel X-Ray Detector, claiming substantial equivalence to predicate devices (1717SCC, K171420) and a reference device (DRF 4343, K080859). The performance claims primarily revolve around demonstrating equivalent or better image quality and technical specifications compared to these predicate devices, rather than establishing acceptance criteria against a specific clinical performance threshold.
Therefore, the typical structure for answering questions about acceptance criteria and clinical study results for a new AI/CAD device (which usually involves specific metrics like sensitivity, specificity, AUC, human reader improvement, etc.) is not directly applicable to this document. This submission is for a hardware device (a digital X-ray detector), not an AI algorithm, and the primary method of demonstrating "acceptance" is through showing substantial equivalence to existing hardware rather than meeting specific clinical performance metrics.
However, I can interpret the request in the context of this 510(k) submission for a hardware device and extract relevant information to address the spirit of your questions as much as possible.
Here's an analysis based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance
For this hardware device, "acceptance criteria" are based on demonstrating equivalent or superior technical performance and image quality compared to a legally marketed predicate device, rather than diagnostic accuracy metrics.
| Characteristic | Acceptance Criteria (Equivalent/Better than Predicate/Reference) | Reported Device Performance (1717FCC) | Relationship to "Acceptance" |
|---|---|---|---|
| Indications for Use | Same as predicate (general radiographic system, not mammography) | "1717FCC is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to... replace film or screen based radiographic systems in all general purpose diagnostic procedures. Not to be used for mammography." | Met (Same) - The core "intended use" is identical to the predicate, forming a foundational aspect of substantial equivalence. |
| Detector Type | Similar to predicate (Amorphous Silicon (a-Si) TFT) | Amorphous Silicon (a-Si) TFT + PIN type photodiode; IGZO TFT + PIN type photodiode (option) | Met (Similar, with enhancement) - The change to IGZO TFT is noted as an option, but the fundamental technology (flat panel, TFT) is similar. The document doesn't indicate this as a failing point; rather, an innovation. |
| Scintillator | Same as predicate (CsI:Tl) | CsI:Tl | Met (Same) - Explicitly stated as the same, which is a key component for image generation. |
| Imaging Area | Similar to predicate (17 x 17 inches) | 17 x 17 inches | Met (Same) - Physical size is the same. |
| Pixel Matrix/Pitch | Similar pixel matrix/pitch to predicate (e.g., 140 μm) | 140 type: 3000 x 3000 (Full resolution), 140 μm / 280 μm/ 420 μm/ 560 μm | Met (Similar, with enhancements/options) - While offering different pixel options (280/420/560 μm, and associated binning), the 140 μm is comparable to the predicate. The document states "The pixel matrix and pixel pitch sizes are different imaging areas but the differences do not raise new concerns for the safety and effectiveness of the subject device." |
| A/D Conversion | Same as predicate (14 bit / 16 bit) | 14 / 16 bit | Met (Same) |
| MTF (Image Sharpness) | Equivalent or better than predicate | a-Si TFT: 1.0 lp/mm, Typ. 0.535; 2.0 lp/mm, Typ. 0.220; 3.0 lp/mm, Typ. 0.099; 3.5 lp/mm, Typ. 0.073. IGZO TFT: Comparison to predicate not directly given for IGZO, but implied as strong performance. | Met (Equivalent or Better) - "1717FCC demonstrated equivalent or better performance in terms of MTF... compared to 1717SCC, the predicate device, at all spatial frequencies." |
| DQE (Image Quality/Dose Efficiency) | Equivalent or better than predicate | a-Si TFT: Typ. 0.751 (at 0 lp/mm). IGZO TFT: Typ. 0.766 (at 0 lp/mm). Predicate 1717SCC was Typ. 0.740 (at 0 lp/mm). | Met (Equivalent or Better) - "1717FCC demonstrated equivalent or better performance in terms of... DQE as well as NPS compared to 1717SCC, the predicate device, at all spatial frequencies." |
| NPS (Noise Power Spectrum) | Equivalent or better than predicate | (Specific values not detailed, but comparison mentioned) | Met (Equivalent or Better) - "1717FCC demonstrated equivalent or better performance in terms of... NPS compared to 1717SCC, the predicate device, at all spatial frequencies." |
| Preview Time | Same as predicate (<2 seconds) | <2 seconds | Met (Same) |
| Data Output | Same as predicate (RAW, convertible to DICOM 3.0) | RAW; "The RAW files are convertible into DICOM 3.0 by console S/W" | Met (Same) |
| Frame Rate | Equivalent or better than reference device | GigE: 6@ (1x1), 25@ (2x2), 45@ (3x3), 60@ (4x4). Camera Link: 9@ (1x1), 30@ (2x2), 45@ (3x3), 60@ (4x4). 5GigE: 15@ (1x1), 30@ (2x2), 45@ (3x3), 60@ (4x4). | Met (Better) - "The frame rate and image resolution for 1717 FCC, the subject device, perform better than the specification of the reference device, DRF 4343 (K080859)..." |
| Image Resolution | Equivalent or better than reference device | Up to 3.5 lp/mm (Reference: Up to 3.4 lp/mm) | Met (Better) - "The frame rate and image resolution for 1717 FCC, the subject device, perform better than the specification of the reference device, DRF 4343 (K080859)..." |
Summary of the "Study" (Performance Testing):
The "study" described is a technical performance comparison and a qualitative review of radiographic images, not a clinical trial involving patient outcomes or diagnostic accuracy per se.
2. Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: Not explicitly quantified as a number of images or patients. The document states a "broad review of plain radiographic images taken with 1717FCC and 1717SCC_140μm" was performed. This suggests a qualitative comparison rather than a statistically powered quantitative diagnostic study.
- Data Provenance: Not specified regarding country of origin. The study appears to be retrospective in the sense that existing images from the predicate device were compared to images from the new device. It's not a prospective clinical trial.
3. Number of Experts Used to Establish Ground Truth and Qualifications:
- Number of Experts: Not specified. The phrase "broad review" suggests clinical input, but no specific number of reviewers is given.
- Qualifications of Experts: Not specified. It's implied that the review was done by qualified personnel ("There is little difficulty in evaluating a wide range of anatomic structures necessary to provide a correct conclusion."), likely radiologists or clinical specialists experienced in interpreting plain radiographic images.
4. Adjudication Method for the Test Set:
- Adjudication Method: Not applicable/not specified. Given the nature of a "broad review" for qualitative comparison (rather than a quantitative diagnostic accuracy study with ground truth establishment), formal adjudication methods (like 2+1, 3+1) are not mentioned.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:
- Was it done?: No. This submission does not describe an MRMC study comparing human readers with and without AI assistance. The device is a digital X-ray detector, not an AI diagnostic algorithm for human assistance. The comparison is between the new detector and existing detectors.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Was it done?: Not applicable in the context of an AI algorithm. The performance testing was "standalone" in a sense, as it focused on the intrinsic technical characteristics of the detector itself (MTF, DQE, NPS, frame rate, resolution) through non-clinical laboratory tests, and a qualitative image comparison. It's not an "algorithm" being tested.
7. The Type of Ground Truth Used:
- Type of Ground Truth: For the "image quality" comparison, the "ground truth" seems to be a qualitative assessment by unspecified experts that the images from 1717FCC were of "equivalent or better quality" in terms of "spatial and soft tissue contrast resolution" compared to the predicate.
- For the technical performance metrics (MTF, DQE, NPS), the "ground truth" is measured against standardized tests (IEC 62220-1) and compared directly to the measured performance of predicate devices. These are objective engineering measurements.
8. The Sample Size for the Training Set:
- Training Set Sample Size: Not applicable. This document describes a hardware device (X-ray detector), not an AI/machine learning algorithm that requires a training set.
9. How the Ground Truth for the Training Set was Established:
- Ground Truth Establishment for Training Set: Not applicable, as there is no AI training set for this hardware device.
In conclusion, this 510(k) submission for the Rayence 1717FCC detector demonstrates substantial equivalence based on a comparison of technical specifications, qualitative image review, and objective non-clinical performance metrics (like MTF, DQE, NPS) against predicate and reference hardware devices. It does not involve complex clinical accuracy studies or AI performance metrics as would be seen for a software-based diagnostic AI device.
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