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510(k) Data Aggregation
(135 days)
RALCO
R104/A, R108 and R108 F Manual X-Ray Collimators are intended for use in diagnostic radiographic/fluoroscopic applications.
These are square-field single- or, optionally, multi-layer x-ray collimators. They are lightweight and compact, suited for installation on mobile of fired x-ray equipment. In the standard single- layer version, the x-ray field is defined by two pairs of shutters and a conc at the xray beam window. In the version mounting RO 334, he x-ray field is defined by six pairs of shutters, two of which are leadlined. The six pairs of shutters move perpendicularly within the x-ray field. Four pairs of shutters are in bronze: two are located near the focus and two are leated near the entrance window. Two leaded shutters are located near the exit window of the x-ray beam from the collimator and serve to accurately define the x-ray field edges. Shutter movements are manual and controlled by two knobs on the collimator from panel. The square-field X-ray beam Limiting Device is designed for installation on rotating or fixed anode Xray tubes (mounting RO 334) (EN 60601-1-3 par 29.202.3); manual controls provide for the adjustment of the X-ray field dimension to the size of the image receptor or to that of the anatomical area of interest. Adjustment to the area under investigation is possible by using the knobs on the front panel. Direct visualisation of the x-ray field is provided by a light beam which corresponds to the x-ray bean, within a tolerance of two percent of the selected FFD (SID) value. The light-field centre is provided by the intersection of two perpendicular lines silk-screened into the Lexan window and projected on the light field by the light beam. To activate the light field, press the area marked with the light symbol on the front of the device. The light will switch on for 30 seconds and an electronic timer will switch the lamp OFF automatically.
The provided K110856 document details the premarket notification for RALCO's R104/A, R108, and R108 F Manual X-Ray Collimators. However, it does not contain specific acceptance criteria or an explicit study report with performance metrics in the way a clinical trial or algorithm validation study would.
Instead, this submission focuses on establishing substantial equivalence to a predicate device (K030487 Ralco R72 Manual Collimator) based on bench testing and safety testing. The core argument is that the new devices are "as safe and effective" as the predicate device due to similar design, intended use, and conformance to US Performance Standards.
Here's an analysis based on the information provided, highlighting what is and is not present:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (from text, inferred) | Reported Device Performance (from text) |
---|---|
Safety and Effectiveness Equivalence: As safe and effective as the predicate device (K030487 Ralco R72 Manual Collimator). | "The results of bench, safety test, and laboratory testing indicates that the new devices are as safe and effective as the predicate device." |
Technological Differences: Few technological differences compared to the predicate device. | "have few technological differences" (compared to the predicate device). |
Indications for Use: Identical indications for use as the predicate device. | "has identical indications for use" (compared to the predicate device). |
Conformance to Standards: Conforms to US Performance Standards and CSA Listed to US Standards for safety for medical devices. | "The new devices conform to US Performance Standards and are CSA Listed to US Standards for safety for medical devices." |
Light Field Accuracy: Direct visualization of the x-ray field by a light beam that corresponds to the x-ray beam within a tolerance of two percent of the selected FFD (SID) value. | "Direct visualisation of the x-ray field is provided by a light beam which corresponds to the x-ray bean, within a tolerance of two percent of the selected FFD (SID) value." (This is a design specification, not a specific test result from a study in the provided text, but implies it was met). |
Missing Information:
- Specific quantitative metrics for "safety" and "effectiveness" are not provided. For example, there are no reported measurements of radiation leakage, field size accuracy (beyond the 2% tolerance claim), or shutter precision from the bench tests.
- The document does not elaborate on the specific "bench, safety test, and laboratory testing" that led to these conclusions.
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: Not specified. The document refers to "bench, safety test, and laboratory testing" but does not provide details on the number of units tested or the specific conditions.
- Data Provenance: Not specified, but generally, bench and laboratory testing for a device like this would be conducted by the manufacturer (Ralco srl, in Italy). The testing would be prospective in nature, as it's part of the design verification and validation process for the new device.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
- This type of information is not applicable to this submission. The device is a mechanical X-ray collimator. Its performance is evaluated through engineering and physical measurements (e.g., light field accuracy, shutter movement, structural integrity, electrical safety), not through expert interpretation of medical images or clinical outcomes. Therefore, there is no "ground truth" derived from medical experts in the context of a diagnostic reading study.
4. Adjudication Method for the Test Set
- Not applicable. See point 3. Adjudication methods (like 2+1, 3+1) are used in studies involving human interpretation or subjective assessments, typically for AI algorithms or reader performance studies. This is a physical device.
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
- Not applicable. This submission is for a physical medical device (X-ray collimator), not an AI-powered diagnostic tool. Therefore, no MRMC study or AI assistance evaluation was performed or is relevant to this submission.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable. This is a hardware device, not an algorithm.
7. The Type of Ground Truth Used
- The "ground truth" for this device's performance would be objective physical measurements and engineering specifications, e.g., using calibrated measuring equipment to verify dimensions, light intensity, field accuracy, mechanical movement tolerances, and electrical safety parameters. It is not based on expert consensus, pathology, or outcomes data in the medical sense.
8. The Sample Size for the Training Set
- Not applicable. This is a physical device, not a machine learning model. There is no concept of a "training set" for its development or validation.
9. How the Ground Truth for the Training Set Was Established
- Not applicable. See point 8.
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(53 days)
RALCO, MODEL R225 ACS
Model R225 ACS Automatic X-RAY Collimator is intended for use in diagnostic radiographic/fluoroscopic applications.
This x-ray collimator Multilayer, square-field, automatic collimation system. Stepper motors control the movements of shutters and the additional filter. There is a mounting plane at 80 mm (3.15") from the focus. A microprocessor circuit controls the stepper motors and provides the stepless adjustment of the square field dimensions at variable FFD (SID). The field dimensions may be decreased and increased to the set value by two knobs placed on the collimator front panel.
The provided text describes a submission for a 510(k) premarket notification for the RALCO Model R225 ACS Automatic X-RAY Collimator. This device is a collimator, which is a component of an X-ray system, and therefore, the assessment criteria and study design are different from those for AI-powered diagnostic devices.
The submission focuses on establishing substantial equivalence to a predicate device (K072780, Ralco Model R302DACS Automatic Collimator) rather than demonstrating a specific performance metric against a "ground truth" in the way an AI diagnostic algorithm would.
Based on the provided text, here's a breakdown of the requested information:
1. Table of acceptance criteria and the reported device performance:
Acceptance Criteria | Reported Device Performance |
---|---|
Safety and Effectiveness Equivalence to Predicate Device: The new device must be as safe and effective as the predicate device (K072780, Ralco Model R302DACS Automatic Collimator). | "The results of bench, safety test, and laboratory testing indicates that the new device is as safe and effective as the predicate device." |
Conforms to US Performance Standards: The device must meet applicable US performance standards. | "The new device conforms to US Performance Standards." |
CSA Listed to US Standards for safety for medical devices: The device must be listed by CSA to US safety standards. | "and is CSA Listed to US Standards for safety for medical devices." |
Identical Indications for Use: The new device must have the same indications for use as the predicate device. | "and has identical indications for use" (Indications for Use: Intended for use in diagnostic/fluoroscopic applications.) |
Technological Differences: Differences should be minimal and not raise new questions of safety or effectiveness. | "has few technological differences" (The primary described difference is that the predicate employs a round field, similar to the new device, but the new device also features "Multilayer, square-field, automatic collimation system" which suggests an enhancement over the predicate's possibly singular "round field" description; however, the conclusion emphasizes "few technological differences.") |
2. Sample size used for the test set and the data provenance:
- Test Set Sample Size: Not applicable in the context of this submission. The submission relies on "bench, safety test, and laboratory testing" rather than a clinical dataset with a specific "test set" for performance evaluation against a diagnostic ground truth.
- Data Provenance: Not explicitly stated as clinical data from specific countries or retrospective/prospective studies. The testing is described as "bench, safety test, and laboratory testing," which typically refers to engineering and quality assurance activities conducted by the manufacturer (RALCO srl in Biassono, Italy).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable. This is not a study requiring expert consensus for a diagnostic "ground truth." The evaluation focuses on the engineering performance and safety of the collimator itself, which are assessed through engineering tests and adherence to standards.
4. Adjudication method for the test set:
- Not applicable. There is no specific "test set" requiring adjudication in the context of this submission.
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 MRMC comparative effectiveness study was done. This device is a hardware component (an X-ray collimator), not an AI algorithm intended to assist human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable. This is a hardware device, not an algorithm.
7. The type of ground truth used:
- Not applicable in the sense of clinical diagnostic ground truth (e.g., pathology, patient outcomes). The "ground truth" here is adherence to engineering specifications, safety standards (e.g., CSA Listed to US Standards), and functional equivalence to the predicate device as demonstrated through "bench, safety test, and laboratory testing."
8. The sample size for the training set:
- Not applicable. This is a manufactured hardware device, not a machine learning model that requires a training set.
9. How the ground truth for the training set was established:
- Not applicable. As noted above, this device does not involve a training set or associated ground truth in the context of machine learning.
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