(15 days)
The Radiotherapy Solution Based on CR25.0 is indicated for producing simulation and quality control images for use in radiation therapy planning and quality control.
The Radiotherapy Solution Based on CR allows the application of Portal Imaging in a very wide dose range (1 MU - 400 MU's and higher) by using two different Portal Imaging Cassette types, which are optimised for image quality at their intended dose range. The Radiotherapy Solution Based on CR supports both low- and high-dose applications (sometimes called localisation and verification portal imaging). Not only does the system enable the acquisition of the images under the typical Radiotherapy conditions, the specific requirements for these images are also met which allows their use by the typical "next-in-line" radiotherapy applications. Typical "next-in-line" applications for simulation imaging are, for instance, image comparison and bloc compensator/MLC calculations. For portal imaging, a typical "next-in-line" application is image comparison with a reference image (this can be a simulation image or DRR: comparisons are made between hardcopy prints or on a digital workstation).
The provided text describes a 510(k) premarket notification for a medical device called "Radiotherapy Solution Based on CR" (later referred to as "Radiotherapy Solution Based on CR25.0"). This submission focuses on demonstrating substantial equivalence to previously marketed predicate devices, rather than establishing specific performance criteria through a detailed clinical study with acceptance criteria.
The submission is for an accessory to a CR system and emphasizes its technical characteristics and intended use being similar to existing cleared devices. Therefore, the information typically found in a clinical study demonstrating performance against acceptance criteria in terms of accuracy, sensitivity, specificity, or other quantitative metrics is largely absent.
Here's an analysis based on the provided text, highlighting what is available and what is not:
1. A table of acceptance criteria and the reported device performance:
This information is not explicitly provided in the submission. The submission states that the device "has been tested for proper performance to specifications through various in-house reliability and imaging performance demonstration tests." However, the specific acceptance criteria for these "specifications" and the quantitative results are not detailed.
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):
The text mentions "Clinical performance has been tested in the typical environment of a clinical radiotherapy department, and sample clinical images have been provided in this 510(k)." The sample size for this "clinical performance" test is not specified, nor is the exact data provenance (country of origin, retrospective/prospective). The emphasis is on demonstrating "sample clinical images" as confirmatory evidence of equivalence.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience):
This information is not provided. Given the nature of a 510(k) submission focused on substantial equivalence rather than a de novo clinical performance study, the establishment of ground truth by multiple experts is not detailed. The "clinical performance" testing seems to be more about confirming the device functions as expected in a real-world setting rather than a rigorous diagnostic accuracy study.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
This information is not provided.
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:
An MRMC comparative effectiveness study was not conducted or reported. The device is an image acquisition and processing system, not an AI-assisted diagnostic tool for human readers. Its primary function is to enable "Portal Imaging" and produce images for "simulation and quality control" in radiotherapy.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
A standalone performance evaluation of the "algorithm" in the sense of a diagnostic accuracy study is not explicitly detailed. The device is an integrated system (cassettes, image acquisition, and processing) for producing images. The "performance to specifications" would likely involve objective image quality metrics (e.g., spatial resolution, contrast, noise, dose linearity) which are inherent to the algorithm and hardware working together. However, specific acceptance criteria and detailed results for these are not provided in the summary.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
Given the device's function in radiotherapy imaging (localization and verification, simulation, quality control), the "ground truth" for its performance would likely relate to the accuracy of anatomical representation, consistency of image quality, and ability to meet the requirements for "next-in-line" radiotherapy applications. However, the specific methodology for establishing this "ground truth" (e.g., comparison to known anatomical landmarks, phantoms, established dosimetry) is not detailed in the provided summary. There is no mention of expert consensus, pathology, or outcomes data in the context of establishing ground truth for the clinical performance.
8. The sample size for the training set:
The concept of a "training set" in the context of machine learning is not applicable to this device. This device is an imaging system, not a machine learning model.
9. How the ground truth for the training set was established:
As the concept of a "training set" is not applicable, this information is not relevant.
In summary:
This 510(k) summary is typical for a device demonstrating substantial equivalence, where the focus is on comparing the new device's intended use and technological characteristics to already cleared predicate devices. It does not provide the detailed performance metrics, acceptance criteria, multi-reader studies, or comprehensive ground truth establishment methodologies that would be expected for a de novo device or an AI-based diagnostic tool requiring rigorous clinical validation. The "testing" mentioned is primarily for "proper performance to specifications" and "clinical performance" to confirm its functionality in a radiotherapy environment, without specific quantitative results against predefined acceptance criteria being disclosed in this summary.
§ 892.1630 Electrostatic x-ray imaging system.
(a)
Identification. An electrostatic x-ray imaging system is a device intended for medical purposes that uses an electrostatic field across a semiconductive plate, a gas-filled chamber, or other similar device to convert a pattern of x-radiation into an electrostatic image and, subsequently, into a visible image. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.