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510(k) Data Aggregation
(23 days)
1717SCV, 1717SGV
1717SCV and 1717SGV X-ray detectors, 127um and 140um, are 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.
1717SCV / 1717SGV 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 an a-Si TFT sensor. This device needs to be integrated with a radiographic imaging system. It can be utilized to capture and digitalize X-ray images for radiographic diagnosis.
1717SCV and 1717SGV have the same Hardware, Software and components.
The type of scintillator layer are different: Cesium Iodide for 1717SCV and Gadolinium Oxsulfide for 1717SGV. Scintillator is a phosphor that produces scintillations.
The subject detectors are not wireless, but they are connected to a viewing station by ethernet connection. Also, the subject detectors have an Automatic Exposure Control (AEC) feature.
The RAW files can be further processed as DICOM compatible image files by separate console SW (K190866 / Xmaruview V1 (Xmaru Chiroview, Xmaru Podview)/ Rayence Co.,Ltd.) for a radiographic diagnosis and analysis.
The software used with the subject detectors is the same as the software XmaruView V1 used with the predicate K190866.
Here's an analysis of the acceptance criteria and study information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The provided text does not contain explicitly defined acceptance criteria (e.g., a specific threshold for MTF or DQE that the device must meet). Instead, it states that the devices (1717SCV / 1717SGV) have "similar MTF and DQE performance" when compared to their predicate devices (1717SCC / 1717SGC). The implicit acceptance criterion is that the subject device's performance should be comparable to, or not significantly worse than, the legally marketed predicate devices.
| Metric (at 3 lp/mm) | Acceptance Criteria (Implicit: Similar to Predicate) | Reported Device Performance (1717SCV / 1717SGV) | Reported Predicate Performance (1717SCC / 1717SGC) | Meets Criteria? |
|---|---|---|---|---|
| MTF | Within acceptable range of predicate | Yes (Claimed) | ||
| 1717SCV (127 type) | Similar to 0.176 | 0.200 | 0.176 | Similar |
| 1717SCV (140 type) | Similar to 0.106 | 0.111 | 0.106 | Similar |
| 1717SGV (127 type) | Similar to 0.119 | 0.120 | 0.119 | Similar |
| 1717SGV (140 type) | Similar to 0.100 | 0.103 | 0.100 | Similar |
| DQE (0.1 lp/mm) | Within acceptable range of predicate | Yes (Claimed) | ||
| 1717SCV (127 type) | Similar to 0.644 | 0.675 | 0.644 | Similar |
| 1717SCV (140 type) | Similar to 0.685 | 0.682 | 0.685 | Similar |
| 1717SGV (127 type) | Similar to 0.401 | 0.405 | 0.401 | Similar |
| 1717SGV (140 type) | Similar to 0.383 | 0.414 | 0.383 | Similar |
2. Sample Size Used for the Test Set and Data Provenance
The document states that "The non-clinical test report for each subject device was prepared and submitted to FDA separately to demonstrate the substantial equivalency..." It then lists the types of tests performed (MTF, DQE, NPS). However, it does not specify the sample size for the test set or the data provenance (e.g., country of origin, retrospective/prospective). These are non-clinical performance evaluations, likely performed in a lab setting rather than on patient data.
3. Number of Experts Used to Establish Ground Truth and Qualifications
The provided text does not mention any human expert review for establishing ground truth. The performance evaluation is based on technical metrics (MTF, DQE, NPS) derived from physical measurements of the devices, not from interpretation of clinical images by experts.
4. Adjudication Method for the Test Set
As the evaluation is based on technical metrics and not human interpretation of images, an adjudication method for a test set of images is not applicable and therefore not mentioned.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No, a MRMC comparative effectiveness study was not done. The study described focuses on the physical performance characteristics of the X-ray detectors themselves (MTF, DQE, NPS) rather than their impact on human reader performance or the diagnostic accuracy of images.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
The performance testing described (MTF, DQE, NPS) is a standalone (algorithm/device only) performance evaluation. These metrics assess the intrinsic image quality and efficiency of the detector itself, independent of human interpretation.
7. Type of Ground Truth Used
The ground truth used for these performance metrics is based on physical measurements and standardized testing protocols (specifically, IEC 6220-1) rather than expert consensus, pathology, or outcomes data. The "ground truth" for MTF, DQE, and NPS refers to the actual physical properties and performance of the detector under controlled conditions.
8. Sample Size for the Training Set
The document does not mention a training set sample size. The devices (1717SCV / 1717SGV) are X-ray detectors, not AI algorithms that would require a training set in the conventional sense. The performance evaluation focuses on the inherent characteristics of the hardware.
9. How the Ground Truth for the Training Set Was Established
Since there is no mention of a training set for an AI algorithm (as this is a medical device clearance for an X-ray detector), the method for establishing ground truth for a training set is not applicable and therefore not described.
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