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The device is designed to perform radiographic x-ray examinations on all pediatric and adult patients, in all patient treatment areas.

The DRX-Revolution Mobile X-ray System is a mobile diagnostic x-ray system that utilizes digital technology for bedside or portable exams. Key components of the system are the x-ray generator, a tube head assembly (includes the x-ray tube and collimator) that allows for multiple axes of movement, a maneuverable drive system, touchscreen user interface(s) for user input. The system is designed with installable software for acquiring and processing medical diagnostic images outside of a standard stationary X-ray room. It is a mobile diagnostic system intended to generate and control X-rays for examination of various anatomical regions.

The provided text describes a 510(k) premarket notification for the DRX-Revolution Mobile X-ray System, which includes changes such as the addition of Smart Noise Cancellation (SNC) functionality and compatibility with a new detector (Lux 35). The study focuses on demonstrating the substantial equivalence of the modified device to a previously cleared predicate device (DRX-Revolution Mobile X-ray System, K191025).

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided information:

1. A table of acceptance criteria and the reported device performance

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The device is designed to perform radiographic x-ray examinations on all pediatric and adult patient treatment areas.

The DRX-Rise Mobile X-ray System is a diagnostic mobile X-ray system utilizing digital radiography technology. The DRX-Rise consists of a self-contained X-ray generator, image receptor(s), imaging display and software for acquiring medical diagnostic images outside of a standard stationary X-ray room. These components are mounted on a motorized cart that is battery powered to enable the device to be driven from location to location by user interaction. The DRX-Rise system incorporates a flat-panel detector that can be used wirelessly for exams such as in-bed chest projections. The device acquires images using Carestream's clinical acquisition software platform (ImageView) and digital flat panel detectors. ImageView is considered software that is of Moderate Level of Concern and not intended for manipulation of medical images. The DRX-Rise Mobile X-ray System is designed for digital radiography (DR) with Carestream detectors.

The provided document is a 510(k) premarket notification for the DRX-Rise Mobile X-ray System, asserting its substantial equivalence to a predicate device (DRX-Revolution Mobile X-ray System, K191025). The document does not describe a study involving acceptance criteria for an AI/CADe device's performance when assisting human readers or evaluating standalone AI performance.

Instead, the document focuses on demonstrating that the DRX-Rise Mobile X-ray System itself, as a physical medical device, is substantially equivalent to an already cleared device. This is achieved through comparisons of technological characteristics and compliance with consensus standards.

Therefore, I cannot provide the requested information regarding acceptance criteria and studies for an AI/CADe device's performance (points 2-9) because the submission does not pertain to such a device or study.

Here's a breakdown of what can be extracted from the provided text, related to the device itself:

1. A table of acceptance criteria and the reported device performance:

The document doesn't present acceptance criteria in the typical "performance target" vs. "achieved performance" format for an AI/CADe. Instead, it compares the modified device's specifications to the predicate device's specifications, arguing that any differences do not impact safety or performance.

2. Sample sized used for the test set and the data provenance: Not applicable. This submission concerns a hardware medical device, not a performance study on a test set of images. The "test set" in this context refers to the device itself being tested against its specifications and existing standards.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for image interpretation by experts is not relevant to this submission.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.

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. No AI assistance mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. The "ground truth" for this device's acceptance is its compliance with recognized consensus standards and its functional equivalence to a predicate device.

8. The sample size for the training set: Not applicable. There is no mention of a training set as this is not an AI/ML device submission.

9. How the ground truth for the training set was established: Not applicable.

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The device is intended to capture for display radiographic images of human anatomy including both pediatric and adult patients. The device is intended for use in general projections wherever conventional screen-film systems or CR systems may be used. Excluded from the indications for use are mammography, fluoroscopy, and angiography applications

The modified DRX Plus 3543C is a scintillator-photodetector device (Solid State X-ray Imager) utilizing an amorphous silicon flat panel image sensor. The modified detector is redesigned with the intent to reduce weight and increase durability, while utilizing a non-glass substrate material and cesium iodide scintillator. The modified detector, like the predicate is designed to interact with Carestream's DRX-1 System (K090318).

The modified DRX Plus 3543C Detector, like the predicate, creates a digital image from the x-rays incident on the input surface during an x-ray exposure. The flat panel imager absorbs incident x-rays and converts the energy into visible light photons. These light photons are converted into electrical charge and stored in structures called "pixels." The digital value in each pixel of the image is directly related to the intensity of the incident x-ray flux at that particular location on the surface of the detector. Image acquisition software is used to correct the digital image for defective pixels and lines on the detector, perform gain and offset correction and generate sub-sampled preview images

The provided text describes a 510(k) submission for a medical device, the Lux 35 Detector, which is a digital X-ray flat panel detector. The submission aims to demonstrate substantial equivalence to a predicate device (DRX Plus 3543 Detector). The information focuses on design modifications and non-clinical testing.

Here's an analysis of the acceptance criteria and study details based on the provided text, highlighting where information is present and where it is not:

Device: Lux 35 Detector (Carestream Health, Inc.)

Study Type: Non-clinical (bench) testing, specifically a Phantom Image Study, to demonstrate substantial equivalence of image quality to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state "acceptance criteria" for image quality in a tabular format with pass/fail thresholds. Instead, it provides a qualitative comparison of image attributes. The closest interpretation of "acceptance criteria" is that the modified device's image quality needed to be "equivalent to just noticeably better than" the predicate.

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size: Not explicitly stated. The text mentions "a Phantom Image Study" but does not quantify the number of images or runs.
• Data Provenance: This was a non-clinical bench testing study using phantoms. Therefore, there is no patient data or geographical provenance. The study was likely conducted at Carestream's facilities. It is a prospective study in the sense that the testing was performed specifically for this submission.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts:

• Number of Experts: Not specified. The text mentions "Greater than 84% of all responses were rated 0 or higher," implying a group of evaluators, but their number is not provided.
• Qualifications of Experts: Not specified. It's unclear if these were radiologists, imaging scientists, or other relevant personnel.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not specified. The phrase "Greater than 84% of all responses were rated 0 or higher" suggests individual ratings were collected, but how conflicts or multiple ratings were aggregated or adjudicated is not detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

• Answer: No. The study was a "Phantom Image Study" focused on technical image quality attributes, not human reader performance.
• Effect Size of Human Readers: Not applicable, as no MRMC study was performed.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

• Answer: Yes, in a sense. The evaluation of DQE and MTF are standalone technical performance metrics of the detector itself, independent of human interpretation. The "Phantom Image Study" also evaluates the output of the device (images) based on technical attributes, rather than a human diagnostic task.

7. The Type of Ground Truth Used:

• Type of Ground Truth: For the phantom image study, the "ground truth" for evaluating image quality attributes (detail, sharpness, noise, artifacts) is based on technical image quality metrics (DQE, MTF) and potentially expert consensus on visual assessments of phantom images against known ideal phantom characteristics. It is not based on patient outcomes, pathology, or clinical diagnoses.

8. The Sample Size for the Training Set:

• Sample Size for Training Set: Not applicable. This device is a hardware component (X-ray detector) and the study described is a non-clinical evaluation of its image quality, not an AI/algorithm that requires a training set of data.

9. How the Ground Truth for the Training Set Was Established:

• Ground Truth Establishment for Training Set: Not applicable, as this is not an AI/algorithm that requires a training set.

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The Q-Rad Radiographic System is indicated for use in obtaining diagnostic images to aid the physician with diagnosis. The system can be used to perform radiographic imaging of various portions of the human body, including the skull, spinal column, extremities, chest, abdomen and other body parts. The Q-Rad System is not indicated for use in mammography

The Q-Rad System is a general purpose x-ray system used for acquiring radiographic images of various portions of the human body. The system consists of a combination of components including various models of high voltage x-ray generators, control panels or workstation computers, various models of patient support tables, wall-mounted image receptors/detectors for upright imaging, tube supports (ceiling-suspended or floormounted), x-ray tube, and collimator (beam-limiting device).

The Q-Rad System can be used with conventional analog (film cassette), digital radiography (DR) and computed radiography (CR) receptors. Systems equipped with DR or CR receptors can also be configured to include a workstation computer that is fully integrated with the x-ray generator.

The modified (subject) device is the previously cleared Q-Rad System stationary x-ray system which has been modified as follows:

• Integration of the FDA-Cleared ImageView Software (K163203) with the Q-Rad ● System.
• A circuit board (CIB+ Board) has been implemented on the Q-Rad System to ● facilitate a new communication protocol between the ImageView Software and the generator.
• The QMI (Quantum Medical Imaging) high voltage generator has been replaced with a Carestream-designed high voltage generator.
• The VacuTec Dose Area Product (DAP) meter Model 1560015 has been replaced ● with an equivalent DAP from a different supplier, the IBA Kermax plus with Ethernet interface 120-131 ETH (Standard Size).
• The Generator Control Box has been replaced. This control box is used to switch ● the generator on and off. Changes to the control box are cosmetic only and do not impact its functionality.

Here's an analysis of the acceptance criteria and study information provided, focusing on the Q-Rad System:

This document is a 510(k) summary for a modified X-ray system, comparing it to a predicate device. It primarily focuses on demonstrating substantial equivalence rather than a clinical study proving new diagnostic performance. Therefore, many typical AI/software study elements (like expert ground truth, MRMC studies, specific performance metrics like AUC) are not detailed here because they aren't generally required for this type of submission.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

This document describes non-clinical (bench) testing rather than a clinical study with patient data. Therefore, there is no "test set" in the traditional sense of patient cases or images for evaluating diagnostic performance. The testing was focused on the system's technical and functional performance.

• Sample Size: Not applicable in the context of patient data. The "sample" would be the modified Q-Rad System itself and its components undergoing various bench tests.
• Data Provenance: Not applicable for patient data. The testing was described as "non-clinical (bench) testing." No information on country of origin for any data or retrospective/prospective nature is provided, as it's not a clinical data study.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not provided and is not applicable because the study described is non-clinical bench testing for substantial equivalence of an X-ray system, not a clinical diagnostic performance study requiring expert ground truth for patient findings.

4. Adjudication Method for the Test Set

This information is not provided and is not applicable for the same reasons as #3.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance

There is no indication that an MRMC study was performed. This submission is for an X-ray imaging system, not an AI-powered diagnostic algorithm for which an MRMC study would typically be conducted to evaluate human reader performance with and without AI assistance. The "ImageView Software" mentioned is already FDA-cleared (K163203) and its integration into the Q-Rad System is one of the modifications, but its diagnostic performance with human readers is not reassessed here.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Study was done

This is not applicable. The Q-Rad System is an X-ray imaging device, not an AI algorithm performing a standalone diagnostic task. While it integrates an "ImageView Software," the 510(k) submission describes physical and software modifications to the system overall, not a standalone evaluation of an AI algorithm.

7. The Type of Ground Truth Used

This is not applicable for a clinical sense of "ground truth" (e.g., pathology, outcomes data). The ground truth for bench testing would typically involve engineering specifications, defined performance metrics, and compliance with consensus standards.

8. The Sample Size for the Training Set

This is not applicable. This document describes modifications to an existing X-ray system and its non-clinical testing. It does not mention any machine learning or AI models being trained as part of this specific submission. The ImageView Software is already cleared.

9. How the Ground Truth for the Training Set was Established

This is not applicable for the same reasons as #8.

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The device is designed to perform radiographic x-ray examinations on all pediatric and adult patient treatment areas.

The DRX-Revolution Mobile X-ray System is a diagnostic mobile x-ray system utilizing digital radiography (DR) technology. The system consists of a self-contained x-ray generator, image receptor(s), imaging display and software for acquiring medical diagnostic images outside of a standard stationary xray room. The DRX-Revolution system incorporates a flat-panel detector that can be used wirelessly for exams such as in-bed chest projections. The system can also be used to expose CR phosphor screens or films.

The Carestream DRX-Revolution Mobile X-ray System (K191025) underwent modifications compared to its predicate device (K120062). The primary changes include a different X-ray tube supplier, additional support for DRX Plus detectors, updated image acquisition software (ImageView), and a replaced high-voltage X-ray generator.

Here's an analysis of the acceptance criteria and the study proving adherence:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample size used for the test set and the data provenance:

• Sample Size: Not explicitly stated as a number of images or cases. The document mentions a "Phantom Imaging study."
• Data Provenance: The study was a "Phantom Imaging study," which implies the use of test phantoms rather than real patient data. This is typically done in a controlled laboratory environment. The country of origin is not specified but given Carestream's location (Rochester, New York), it is likely the US. The study type is retrospective, as it's bench testing to compare a modified device to an already marketed predicate.

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. As the study was a non-clinical "phantom imaging study" evaluating technical image quality attributes, it might not have involved human expert readers establishing diagnostic ground truth in the traditional sense. The evaluation likely relied on quantitative measurements of image quality metrics.

4. Adjudication method for the test set:

• This information is not provided as the study was a phantom imaging study focusing on technical image quality. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies with human readers interpreting medical images.

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, an MRMC comparative effectiveness study was not done. The submission explicitly states: "Clinical testing was not required to establish substantial equivalence. Bench testing was sufficient to assess the device safety and effectiveness." This device is a mobile X-ray system, not an AI-powered diagnostic software.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

• Yes, in a sense, a "standalone" evaluation of the device's image quality was performed through the "Phantom Imaging study" and DQE/MTF data. This tested the device's inherent capability to produce images without direct human interpretation for diagnostic purposes, focusing on technical image quality attributes rather than diagnostic accuracy.

7. The type of ground truth used:

• The ground truth used was based on technical image quality attributes such as detail, sharpness, noise, and appearance of artifacts, as evaluated through a "Phantom Imaging study" and by DQE/MTF data. This is an objective technical assessment against established metrics for image quality, rather than a clinical ground truth like pathology or expert consensus on a diagnosis.

8. The sample size for the training set:

• This information is not applicable/not provided. This device is a hardware X-ray system with standard image processing software, not an AI/Machine Learning algorithm that undergoes a "training" phase with a large dataset. The "ImageView" software is a web-based application to improve usability, and its image processing is stated to be the same as previously cleared versions.

9. How the ground truth for the training set was established:

• This information is not applicable/not provided for the same reasons as point 8.

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