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Intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic radiographic exposures of the skull, spinal column, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. Not for mammography.

This is a motorized mobile diagnostic x-ray system. The MDR16 Mobile Direct Radiographic System facilitates X-ray examinations, in situations where it is not possible to transport the patient to a ward with fixed equipment. The unit is stable and precise, yet easy to maneuver due to smooth battery-powered motorization. Electric tube unit and wheel locks, 180º column rotation, and a simple user interface provide for add operator convenience and rapid patient positioning. The MDR17 System allows the acquisition of X-ray images on digital panel, CR, or film, by setting techniques based on anatomic area. Technique presets can be customized. Immediate image display after acquisition, and the possibility of immediate transmission to PACS, help minimize workflow time. Instructions for use are included within the device labeling, and the information provided will enable the user to operate the device in a safe and effective manner. Furthermore, the intended operators of the MDR17 Mobile Direct Radiographic System are health care professionals familiar with and responsible for the x-ray examinations being performed. To minimize electrical, mechanical, and radiation hazards, Del Medical, Inc. adheres to recognized and established industry practice, and all equipment is subject to final performance testing. The digital x-ray panel includes automatic exposure detection. Two different size panels are available: 35 x 43 cm or 24 x 30 cm. The software is compatible with either panel via menu setting.

The provided text does not contain information about acceptance criteria for device performance or a study demonstrating that the device meets such criteria in terms of diagnostic accuracy or clinical outcomes. The document is a 510(k) premarket notification for a mobile X-ray system (MDR17 Mobile Direct Radiographic System), focusing on proving substantial equivalence to a predicate device (RadPRO® Mobile 40kW).

The "Performance Testing" section primarily discusses bench testing for electrical safety, mechanical safety, EMC, and software, and clarifies that clinical testing was not required for a determination of substantial equivalence because the digital X-ray receptor panel had already received FDA clearance.

Therefore, I cannot fulfill the request to provide the acceptance criteria and study details related to device performance in the context of diagnostic accuracy, human reader improvement, or standalone algorithm performance, as this information is explicitly stated as not being required or performed in this submission.

However, I can extract the information provided about the testing that was conducted:

Here's the relevant information based on the provided text, focusing on the evaluations performed for K173018, even though it highlights the absence of clinical performance studies:

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

Since this is a substantial equivalence submission relying on bench testing for safety and electrical/mechanical performance, and not a clinical performance study measuring diagnostic accuracy, there are no specific "acceptance criteria" presented in terms of diagnostic metrics (e.g., sensitivity, specificity, AUC) for the device itself. Instead, the "acceptance criteria" are implied by adherence to recognized consensus standards for safety and electrical characteristics.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided as no clinical performance study or test set for diagnostic accuracy was conducted or required. The testing referred to is bench testing against engineering standards.

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 as no clinical performance study requiring expert ground truth establishment was conducted or required.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not provided as no clinical performance study requiring adjudication was conducted or required.

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 is not required for a determination of substantial equivalence." This device is a mobile X-ray system, not an AI-powered diagnostic tool.

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

No, a standalone performance study was not done. This device is a hardware X-ray system, not an algorithm, and clinical testing was not required.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

This information is not applicable as no clinical performance study requiring ground truth was conducted. For the bench testing, the "ground truth" was adherence to the specifications of the referenced international and national consensus standards.

8. The sample size for the training set

This information is not applicable as this submission is for a hardware medical device (X-ray system), not a machine learning or AI algorithm that requires a training set.

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

This information is not applicable as this submission is for a hardware medical device (X-ray system), not a machine learning or AI algorithm.

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The D-RS AT Digital Dynamic Remote System Is indicated for use in generating fluoroscopic images of human anatomy for diagnostic procedures. It Is intended to replace fluoroscopic images obtained through image intensionaly. Not intended for mammography applications.

The D2RS AT Digital Dynamic Remote System is a direct digital dynamic remote-controlled fluoroscopy and radiography system equipped with the latest generation of Trixell Flat Panel Detector (FPD). The single FPD can perform both fluoroscopy and radiography and is detachable and portable for direct projections to create a unique and highly versatile 3-in-1 imaging solution. The receptor panel directly converts the X-ray images captured by the sensor into a high-resolution digital images. The instrument is suited for use inside a patient environment. This unit converts the X-rays into digital signals. The unit can acquire still and moving images. The system includes a remotely controlled tilting/elevating table. Panel information: Based on a flat-panel digital detector with the largest field-of-view in the market, the Pixium RF 4343 FL is designed for easy integration in classical R&F tables. It allows manufacturers to offer radiologists an all-digital real-time system, generating high-quality images for both routine dynamic applications and high-end static ones. Digital technology facilitates the work of X-ray technicians and speeds up the process, allowing medical centers to optimize patient throughput. Universal: a single detector for both Radiography and Fluoroscopy. An optional static panel may be added to the system: Trixell Pixium 3543EZ. The 3543EZ panel has already been cleared in various 510(k)s including K131314 and K141440. That panel is not mounted and can be moved around by the technician. The system must always have either the Pixium RF 4343, Pixium RF 4343FL for the system to be able to perform fluoroscopy. These fluoroscopic panels were not to our knowledge previously cleared by FDA, so complete performance information as requested by the FDA guidance document on solid state x-ray panels has been provided.

This document describes the D²RS_AT Digital Dynamic Remote System, an image-intensified fluoroscopic x-ray system seeking 510(k) clearance. The provided text outlines the device's characteristics, its comparison to a predicate device, and the testing conducted to demonstrate its safety and effectiveness.

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

1. Table of Acceptance Criteria and Reported Device Performance:

The document implicitly defines acceptance criteria through comparison to a predicate device (Stephanix D²RF K102529) and adherence to various standards and guidance documents. Explicit quantitative acceptance criteria are not provided as a list with pass/fail thresholds. Instead, performance metrics are presented for both the new device's panels and the predicate device's panel, and the conclusion states that the new device performs "comparably to and is substantially equivalent to the predicate device."

Study Proving Acceptance Criteria:

The study conducted to prove the device meets the acceptance criteria is detailed under "Bench/Performance Testing/Data" and "Clinical Evaluation."

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

• Test Set Sample Size: Not explicitly stated. The "Clinical Evaluation" mentions a "board certified radiologist reviewed both static and moving images." This implies a qualitative assessment of some images, but the number of images or cases reviewed is not specified.
• Data Provenance: The document does not specify country of origin for the data or whether it was retrospective or prospective. Given that the device is manufactured in France (Rue Jean Moulin - ZI du Bayon La Ricamarie - FRANCE), it's plausible testing was conducted there or in another location appropriate for device evaluation. The context of a 510(k) submission typically involves data collected specifically for the regulatory submission, making it akin to a prospective study for that purpose, even if the cases themselves might be simulated or representative.

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

• Number of Experts: "a board certified radiologist reviewed..." indicates one radiologist.
• Qualifications of Experts: "board certified radiologist." Specific experience (e.g., "10 years of experience") is not provided.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not applicable or "none" for multiple readers. Since only one radiologist is mentioned as reviewing the images, there was no multi-reader consensus or adjudication process described. The single radiologist's assessment served as the "truth" for the clinical evaluation.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No, an MRMC comparative effectiveness study was not explicitly described. The "Clinical Evaluation" section mentions a single board-certified radiologist reviewing images but does not present a comparison of human reader performance with and without AI assistance, nor does it quantify an effect size of improvement. The study focuses on the device's image quality for diagnostic purposes rather than the reader's comparative performance with different aids.

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

• Yes, a standalone study (or rather, non-human-in-the-loop performance evaluation) was done as part of the bench testing. The "Bench/Performance Testing/Data" section discusses objective metrics like MTF, DQE, spatial resolution, and pixel pitch. These are measurements of the device's inherent image quality characteristics, independent of a human observer's interpretation.

7. The Type of Ground Truth Used:

• For Bench/Performance Testing: The ground truth is objective physical measurements of the system's performance characteristics (e.g., specific X-ray phantom designs for MTF/DQE, calibrated measurement tools for spatial resolution, etc.).
• For Clinical Evaluation: The "ground truth" was established by the subjective assessment of "good diagnostic quality" by a single board certified radiologist. This is an expert opinion-based ground truth.

8. The Sample Size for the Training Set:

• Not Applicable / Not Provided. This device is an X-ray imaging system, not an AI / machine learning algorithm that typically requires a training set of data. The document describes a physical medical imaging device and its components (flat panel detectors). Therefore, no "training set" in the context of machine learning is applicable or mentioned.

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

• Not Applicable / Not Provided. As there is no mention of an AI/ML component requiring a training set, the establishment of ground truth for such a set is not relevant to this submission.

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