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The DigiX FDX radiographic systems are used in hospitals, clinics and medical practices. DigiX FDX enables radiographic exposure of the whole body including: Skull, chest, abdomen, and extremities and may be used on pediatric, adult and bariatic patients. It can also be used for intravenous, small interventions (like biopsy, punctures, etc.) and emergency (trauma critical ill) applications. Exposure may be taken with the Patient's sitting, standing, or in the prone/ supine position.

The DigiX FDX System is not meant for mammography.

The DigiX FDX uses an integrated or portable or fixed or wi-fi digital detector for generating diagnostic images by converting X-Ray into electronics signals. DigiX FDX is also designed to be used with conventional film/screen or Computed Radiography (CR) Cassettes.

The DigiX FDX system is a diagnostic X-Ray system intended for general purpose radiographic imaging of the human body. It is not intended for mammographic imaqing.

The DigiX FDX system is comprised of a combination of devices that include a ceiling mounted X-Ray tube suspension, vertical Bucky stand, fixed or mobile patient Bucky table, X-Ray generator, X-Ray tube, beam limiting device, and a solid-state image receptor.

The DigiX FDX systems are not intended to be operated with any other cleared devices, or to be integrated with other software/hardware devices via direct or indirect connections.

Here's a breakdown of the acceptance criteria and study information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document focuses on demonstrating substantial equivalence to predicate devices rather than defining specific quantitative performance metrics as "acceptance criteria" for a new AI/software feature in the way clinical performance studies usually do. Instead, the "acceptance criteria" are implied to be that the modifications do not negatively impact safety or effectiveness, and that the device performs comparably to the predicate devices and meets relevant safety standards.

For the new features explicitly mentioned (Automatic Stitching and Dual Energy Subtraction), the document states they add functionality without affecting patient safety or effectiveness. For the other components, the criteria are often "Same" or "Similar functionality with same imaging results" or "doesn't affect the safety or effectiveness."

To represent this in a table, we'll extract performance comparisons from the "Functional and Specification Differences" table (Table 4) and the "Justification for Differences" (Table 5).

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

The document states:

• "Non-clinical testing included verification and validation testing, image evaluation, testing, and safety testing."
• "Performance testing included functional testing of all motions of the system(s) with respect to the design specifications. Image performance testing was conducted and results included in the submission."
• "Clinical testing is not applicable due to the fact that no new clinical applications were introduced to the system."

The document does NOT specify a sample size for any test set (clinical or otherwise) in terms of patient data or images used for validation of the radiographic system itself, nor does it mention data provenance (country of origin, retrospective/prospective). It primarily relies on hardware and software equivalence, and compliance with industry standards.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. The document explicitly states "Clinical testing is not applicable." Therefore, there was no clinical study conducted that would necessitate expert readers to establish ground truth for a test set. The evaluation focuses on technical performance and equivalence to predicate devices.

4. Adjudication Method for the Test Set

Not applicable. As no clinical test set requiring expert adjudication was performed, no adjudication method is mentioned.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was done. The document states "Clinical testing is not applicable due to the fact that no new clinical applications were introduced to the system." Therefore, there is no information on how much human readers improve with or without AI assistance. The new software features (Automatic Stitching, Dual Energy Subtraction) are presented as additional functionalities that don't affect safety or effectiveness, not as AI-assisted diagnostic tools requiring a comparative effectiveness study.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Not applicable. The device is a radiographic system, not an AI algorithm intended for standalone diagnostic performance. While it includes new software features (Automatic Stitching, Dual Energy Subtraction), these are integrated functionalities of the imaging system and not described as standalone diagnostic algorithms requiring independent performance evaluation without human interaction.

7. Type of Ground Truth Used

The "ground truth" for the evaluation is primarily based on:

• Compliance with technical specifications and design requirements: Functional testing, image performance testing.
• Adherence to safety and performance standards: IEC 60601 series, EN ISO 14971, IEC 62366-1, IEC 62304, 21 CFR 1020.30, 21 CFR 1020.31.
• Substantial equivalence to predicate devices: Demonstration that the new device has the same intended use, fundamental technological characteristics, and that any differences do not raise new questions of safety or effectiveness.
• Software documentation assessment: For the software components, including the new features, documentation was provided for a "Moderate Level of Concern" software as per FDA guidance.

No clinical ground truth (e.g., expert consensus, pathology, outcomes data) was used or required given the nature of this submission.

8. Sample Size for the Training Set

Not applicable. The document describes an X-ray imaging system, not an AI/ML device that requires a training set of data. The new software features (Automatic Stitching, Dual Energy Subtraction) are described as functionalities, not adaptive algorithms that learn from data.

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

Not applicable. As there was no training set, there was no ground truth to establish for it.

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The Ultimax-i multipurpose digital X-ray system is designed for gastrointestinal studies, general radiography, and fluoroscopy.

The Ultimax-i system has medical applications ranging from but not limited to: contrast-enhanced studies, support of endoscopic studies, nonvascular contrast enhanced studies, nonvascular contrast-enhanced studies, support of vascular IVR, and general radiography.

Note: This system is not intended for cardiovascular contrast studies or interventional radiology procedures for the cardiac or cerebral blood vessels.

Ultimax-i, DREX-UI80, is a fixed C-arm fluoroscopic device intended to provide radiographic and fluoroscopic images in a variety of studies. The unit consists of a C-arm with X-ray tube, beam limiter and digital flat panel detector (FPD), a wireless flat panel detector, a patient table that can tilt in both directions, an 80kW X-ray generator, an overhead tube support assembly, an image processor and both remote and table side control.

This document (K181834) describes a 510(k) premarket notification for the Ultimax-i, DREX-UI80, V1.60, an image-intensified fluoroscopic x-ray system. The submission concerns a modification to a previously cleared device (K170832) by adding a wireless general radiography solid-state x-ray detector (TFP-1417W).

Here's an analysis of the provided text in relation to acceptance criteria and supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly provide a table of acceptance criteria or quantitative performance metrics for the device itself. Instead, it focuses on demonstrating substantial equivalence to a predicate device after a modification. The acceptance criteria appear to be implicit in the regulatory standards and the demonstration that the modification does not negatively impact the system's performance or intended use.

The relevant statement is:
"This submission contains integration test data that demonstrates that the system modifications result in performance that is equal to or better than the predicate system."

Given the information, an inferred "acceptance criteria" and "reported performance" table would look like this, though it's the lack of specific numbers that is notable:

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

• Sample Size: The document does not specify the sample size used for the integration test data. It broadly states "integration test data."
• Data Provenance: The document does not specify the country of origin of the data or whether the data was retrospective or prospective. It only mentions that the manufacturing site is Canon Medical Systems Corporation in Tochigi-ken, Japan.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

This information is not provided in the document. The study described is not a clinical study involving experts establishing ground truth for diagnostic accuracy, but rather an engineering and integration test to demonstrate equivalence after a hardware modification.

4. Adjudication Method for the Test Set:

This information is not applicable/not provided. There is no mention of a human-read test set requiring adjudication in this technical submission.

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

No, an MRMC comparative effectiveness study was not done as described in this submission. This is a technical modification submission, not a human reader performance study. The focus is on the device's technical performance and safety, not on how human readers interact with or improve using the device.

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

This is not applicable in the context of an x-ray imaging system being developed. The "device" itself is the imaging system (hardware and associated software), not an AI algorithm that produces an output for interpretation. The software version (V1.6) remained unchanged from the predicate device and thus no new software performance testing was required beyond integration.

7. The Type of Ground Truth Used:

The concept of "ground truth" as typically applied in AI/diagnostic studies (e.g., pathology, outcomes data) is not explicitly stated or relevant to the type of testing described. The "truth" here is the technical performance of the system against established engineering and safety standards, as well as its functional equivalence to the predicate. This would have been established through phantom measurements, quality assurance checks, and functional testing to ensure image quality, dose, and system operation were maintained or improved.

8. The Sample Size for the Training Set:

This information is not applicable/not provided. The device is an x-ray imaging system, not an AI algorithm that requires a training set for model development. The software was already developed and its version (1.6) was not changed as part of this submission.

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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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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