(20 days)
The GR17 is a selenium-based direct conversion DR detector intended for use by a qualified/trained doctor or technician and is designed to perform radiographic images of human anatomy. It is intended to replace radiographic film/screen systems in all general purpose diagnostic procedures. The GR17 is not used for mammography.
The GR17 is a 17" x 17" Flat Panel Digital Radiographic Detector for General Radiographic Use. It uses amorphous Selenium (a-Se) as the primary photoconductor.
The provided text is a 510(k) summary for the ANRAD Corporation GR17 Digital Detector, which is an X-ray imager. The submission is for a "Modification to specification for defective pixel detection and correction."
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 document mentions a modification to the algorithm for detecting bad pixels and refers to "Pixel defect correction Comparison tests and Results are provided in APPENDIX E." However, the specific acceptance criteria values and the reported device performance in relation to those criteria for the defective pixel detection and correction algorithm are not explicitly stated in the provided text. The text only states that the "Verification Tests were chosen to ensure test coverage of the areas changed in the specifications for pixel defects."
| Acceptance Criteria (for defective pixel detection and correction) | Reported Device Performance |
|---|---|
| Not explicitly stated in the provided text. | Not explicitly stated in the provided text. |
| (Likely involved thresholds for the number and clustering of defective pixels, and the effectiveness of correction algorithms) | (Likely demonstrated the modified algorithm met the new specifications for pixel defects, as per Appendix E, which is not provided) |
2. Sample Size Used for the Test Set and Data Provenance:
The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It only refers to "Verification Tests" and "Comparison tests" related to pixel defect correction. These tests would likely involve various X-ray images with simulated or real pixel defects.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications:
The document does not mention the use of human experts to establish ground truth for the test set regarding pixel defect detection and correction. For technical performance metrics like pixel defects, it is more common for ground truth to be established through objective measurements and technical specifications rather than human expert interpretation of images.
4. Adjudication Method for the Test Set:
Given that the ground truth for pixel defects is typically established through objective technical means, an adjudication method like 2+1 or 3+1 involving human readers is not applicable or mentioned in this context.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
A multi-reader multi-case (MRMC) comparative effectiveness study was not mentioned in the provided text. This type of study is more relevant for evaluating diagnostic accuracy with human readers, which is not the focus of this particular modification related to pixel defect correction. The submission is for a technical modification rather than a diagnostic performance claim.
6. Standalone (Algorithm Only) Performance Study:
A standalone performance study for the pixel defect detection and correction algorithm was implicitly performed. The text states:
- "The particular verification tests were chosen to ensure test coverage of the areas changed in the specifications for pixel defects."
- "Pixel defect correction Comparison tests and Results are provided in APPENDIX E."
This indicates that the algorithm's performance in identifying and correcting pixel defects was evaluated on its own against specified technical criteria. The results of this standalone evaluation are expected in Appendix E, which is not provided here.
7. Type of Ground Truth Used:
The ground truth used for evaluating the pixel defect detection and correction algorithm would be technical specifications and objective measurements of pixel defects. This would involve:
- Deliberately introduced or simulated "defective" pixels.
- Pre-defined criteria for what constitutes a "defective pixel" (e.g., dead pixels, stuck-on pixels, clusters).
- Objective methods to verify if the algorithm correctly identifies these defects and effectively applies corrections without introducing artifacts.
8. Sample Size for the Training Set:
The document does not provide any information about a training set or its sample size. This type of submission, focusing on a modification to a pixel correction algorithm, may not require a separate "training set" in the traditional machine learning sense, especially for algorithms based on predefined rules or thresholds rather than complex learned features. If the algorithm uses machine learning, the training data would be specific to pixel patterns, not necessarily patient images.
9. How Ground Truth for the Training Set Was Established:
Since no training set information is provided, how its ground truth was established is not discussed or applicable based on the provided text.
§ 892.1680 Stationary x-ray system.
(a)
Identification. A stationary x-ray system is a permanently installed diagnostic system intended to generate and control x-rays for examination of various anatomical regions. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II (special controls). A radiographic contrast tray or radiology diagnostic kit intended for use with a stationary x-ray system only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.