(29 days)
The RSM 2430C is a detector indicated for use in screening and diagnostic mammography.
The RSM 2430C detector panel is an indirect conversion device in the form of a square plate in which the input x-ray photons are absorbed in an x-ray sensitive scintillator layer. The energy of the incoming photons generates light distribution in the scintillator layer. Light is converted to a modulated electrical signal through PIN diode within the pixel of the thin film transistor. The amplified signal is converted to a voltage signal and is then converted from an analog to digital signal which can be transmitted to a viewed image print out, transmitted to remote viewing or stored as an electronic data file for later viewing.
Here's a breakdown of the acceptance criteria and study information for the RSM 2430C device, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Parameter | Acceptance Criteria (Predicate Device K162670) | Reported Device Performance (RSM 2430C) |
|---|---|---|
| DQE @ 2 lp/mm | 43% | 43% |
| DQE @ 5 lp/mm | 30% | 30% |
| MTF @ 2 lp/mm | 70% | 70% |
| MTF @ 5 lp/mm | 30% | 30% |
| Resolution | 3,072 X 2,304 (6.1M) | 3,840 x 3,072 (6.1M) |
| Intended Use | Screening and diagnostic mammography | Screening and diagnostic mammography |
| Technological characteristics | Same as predicate (indirect conversion, CsI scintillator, TFT a-Si) | Same as predicate (indirect conversion, CsI scintillator, TFT a-Si) |
| Operating principle | Same as predicate | Same as predicate |
| Materials Scintillator | CsI | CsI |
| Design features | Same as predicate | Same as predicate |
Note: The document states that the RSM 2430C's performance (DQE, MTF, Resolution) is the same as the predicate device (RSM 1824C). The resolution value provided for the subject device refers to the increased pixel count due to the larger detector size, but the performance characteristics (DQE, MTF) are declared equivalent.
2. Sample size used for the test set and the data provenance
- Sample Size: Not explicitly stated. The document mentions a "single-blinded concurrence study" but does not specify the number of cases or images included in the test set for the clinical image evaluation.
- Data Provenance: Not explicitly stated. The study was "conducted in compliance with CDRH's Guidance," which typically suggests a controlled clinical setting, but the country of origin or whether it was retrospective/prospective is not mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- This information is not provided in the document. The text only mentions a "single-blinded concurrence study" for clinical image evaluation but doesn't detail the methodology for ground truth establishment or the specifics of the expert readers (number, qualifications, or experience).
4. Adjudication method for the test set
- This information is not provided in the document. The text refers to a "single-blinded concurrence study" but does not specify how disagreements or consensus were achieved among readers (e.g., 2+1, 3+1).
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
- No, a MRMC comparative effectiveness study was not done (or at least not described in this context). This submission is for a new Full-Field Digital Mammography System (detector), not an AI-powered diagnostic tool. The clinical study mentioned is a "concurrence study" to demonstrate equivalence in diagnostic capability between the new detector and a predicate detector, not to evaluate human reader performance with or without AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
- No, a standalone algorithm performance study was not done. This device is a digital X-ray detector, which is a hardware component for image acquisition in mammography. It is not an algorithm or AI software for interpretation, so a standalone algorithm performance study is not applicable.
7. The type of ground truth used
- This information is not explicitly stated. For a "clinical image evaluation" and "concurrence study," ground truth would typically be established based on expert interpretation (e.g., biopsy results, long-term follow-up, or consensus readings by highly experienced radiologists). However, the document does not elaborate on how ground truth was determined.
8. The sample size for the training set
- This device is a hardware component (detector) and does not involve a "training set" in the context of machine learning or AI. Therefore, this information is not applicable and not provided.
9. How the ground truth for the training set was established
- As the device is a hardware component and not an AI algorithm, the concept of a "training set" and associated "ground truth" for training is not applicable.
§ 892.1715 Full-field digital mammography system.
(a)
Identification. A full-field digital mammography system is a device intended to produce planar digital x-ray images of the entire breast. This generic type of device may include digital mammography acquisition software, full-field digital image receptor, acquisition workstation, automatic exposure control, image processing and reconstruction programs, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II (special controls). The special control for the device is FDA's guidance document entitled “Class II Special Controls Guidance Document: Full-Field Digital Mammography System.”See § 892.1(e) for the availability of this guidance document.