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This software is intended to generate digital radiographic images of the skull, spinal column, extremities, and other body parts in patients of all ages. Applications can be performed with the patient sitting, or lying in the prone or supine position and is intended for use in all routine radiography exams. The product is not intended for mammographic applications.

This software is not meant for mammography, fluoroscopy, or angiography.

The I-Q View is a software package to be used with FDA cleared solid-state imaging receptors. It functions as a diagnostic x-ray image acquisition platform and allows these images to be transferred to hard copy, softcopy, and archive devices via DICOM protocol. The flat panel detector is not part of this submission. In the I-Q View software, the Digital Radiography Operator Console (DROC) software allows the following functions:

• 1. Add new patients to the system; enter information about the patient and physician that will be associated with the digital radiographic images.
• 2. Edit existing patient information.
• 3. Emergency registration and edit Emergency settings.
• 4. Pick from a selection of procedures, which defines the series of images to be acquired.
• 5. Adiust technique settings before capturing the x-ray image.
• 6. Preview the image, accept or reject the image entering comments or rejection reasons to the image. Accepted images will be sent to the selected output destinations.
• 7. Save an incomplete procedure, for which the rest of the exposures will be made at a later time.
• 8. Close a procedure when all images have been captured.
• 9. Review History images, resend and reprint images.
• 10. Re-exam a completed patient.
• 11. Protect patient records from being deleted by the system.
• 12. Delete an examined Study with all images being captured.
• 13. Edit User accounts.
• 14. Check statistical information.
• 15. Image QC.
• 16. Image stitching.
• 17. Provides electronic transfer of medical image data between medical devices.

The provided document is a 510(k) summary for the I-Q View software. It focuses on demonstrating substantial equivalence to a predicate device through bench testing and comparison of technical characteristics. It explicitly states that clinical testing was not required or performed.

Therefore, I cannot provide details on clinical acceptance criteria or a study proving the device meets them, as such a study was not conducted for this submission. The document relies on bench testing and comparison to a predicate device to establish substantial equivalence.

Here's a breakdown of what can be extracted from the provided text regarding acceptance criteria and the "study" (bench testing) that supports the device:

1. Table of Acceptance Criteria and Reported Device Performance

Since no clinical acceptance criteria or performance metrics are provided, this table will reflect the general statements made about the device performing to specifications.

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

• Test Set Sample Size: Not applicable/not reported. The document describes bench testing, not a test set of patient data.
• Data Provenance: Not applicable. Bench testing generally involves internal testing environments rather than patient data from specific countries or retrospective/prospective studies.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not applicable. As no clinical test set was used, no experts were needed to establish ground truth for patient data. Bench testing typically relies on engineering specifications and verification.

4. Adjudication method for the test set

• Not applicable. No clinical test set or human interpretation was involved.

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 document explicitly states: "Clinical Testing: The bench testing is significant enough to demonstrate that the I-Q View software is as good as the predicate software. All features and functionality have been tested and all specifications have been met. Therefore, it is our conclusion that clinical testing is not required to show substantial equivalence." The device is software for image acquisition, not an AI-assisted diagnostic tool.

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

• Yes, in a sense. The "study" described is bench testing of the software's functionality and its integration with solid-state detectors. This is an evaluation of the algorithm/software itself.

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

• For bench testing, the "ground truth" would be the engineering specifications and expected functional behavior of the software and its interaction with hardware components. It's about verifying that the software performs according to its design requirements.

8. The sample size for the training set

• Not applicable. The I-Q View is described as an image acquisition and processing software, not an AI/machine learning model that typically requires a training set of data.

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

• Not applicable, as there is no mention of a training set or AI/machine learning component.

Summary of the "Study" (Bench Testing) for K203703:

The "study" conducted for the I-Q View software was bench testing. This involved:

• Verification and validation of the software.
• Demonstrating the intended functions and relative performance of the software.
• Integration testing to verify that compatible solid-state detectors performed within specification as intended when used with the I-Q View software.

The conclusion drawn from this bench testing was that the software performs to specification and is "as safe and as functionally effective as the predicate software." This was deemed sufficient to demonstrate substantial equivalence, and clinical testing was explicitly stated as not required.

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Intended for use in generating radiographic images of human anatomy. This device is intended to replace film/screen systems in all general purpose diagnostic procedures. This device is not intended for mammography applications. This device is intended for use by qualified medical personnel and is contraindicated when, in the physician, procedures would be contrary to the best interest of the patient.

Intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. The kit allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

This is a Windows 10 based software to be used in conjunction with an FDA cleared digital x-ray receptor panel. It can be used to upgrade film-based systems. This upgrade allows to acquire digital medical diagnostic X-ray images and transfer the images to hardcopy, softcopy, and archive devices on the same network. Some functions allowed with the E-COM DR-2000 DR software:
a. Add new patients to the system, enter information about the patient and physician that will be associated with the digital radiographic images.
b. Edit existing patient information.
c. Emergency registration and edit Emergency settings.
d. Pick from a selection of procedures, which defines the series of images to be taken.
e. Adjust technique settings before capturing the X-ray image.
f. Preview the image, accept or reject the image entering comments or rejection reasons to the image. Accepted images will be sent to the selected output destinations.
g. Save an incomplete procedure, for which the rest of the exposures will be made at a later time.
h. Close a procedure when all images have been captured.
i. Review History images, resend and reprint images.
j. Re-exam a completed patient.
k. Protect patient records from being deleted by the system.
l. Delete an examined Study with all images being captured.
m. Edit user accounts.
n. Check statistical information.
o. Image QC.
p. Image stitching.

This document describes the FDA 510(k) premarket notification for the E-COM DR-2000 DR, a stationary x-ray system. However, it does not provide details regarding specific acceptance criteria, a study proving the device meets those criteria, or information on AI/standalone performance, expert adjudication, or ground truth establishment typically associated with such studies.

Here's a breakdown of the requested information based only on the provided text, highlighting what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not provided in the document. The submission focuses on demonstrating substantial equivalence to a predicate device rather than presenting specific quantitative performance metrics against acceptance criteria.

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

This information is not provided in the document. No specific test set for performance evaluation is mentioned. The submission states "Clinical Testing: Not required for a showing of substantial equivalence," implying a lack of a dedicated clinical test set for new performance evaluation.

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

This information is not provided in the document. Since no clinical testing or performance study is detailed, there's no mention of experts establishing ground truth for a test set.

4. Adjudication Method for the Test Set

This information is not provided in the document. As no test set is described, no adjudication method is mentioned.

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

This information is not provided in the document. The device is a "Stationary X-ray System" with software for image acquisition and management. There is no indication that it includes AI for interpreting images or assisting human readers. Therefore, an MRMC study related to AI assistance is not applicable and not mentioned.

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

This information is not provided in the document. As there is no mention of an algorithm for image interpretation or analysis, a standalone performance study is not applicable and not mentioned. The device's software functions are primarily for image acquisition, processing, and management.

7. The Type of Ground Truth Used

This information is not provided in the document. Since no clinical performance study is described, there's no mention of the type of ground truth used (e.g., expert consensus, pathology, outcomes data).

8. The Sample Size for the Training Set

This information is not provided in the document. The submission pertains to a conventional x-ray system and its control software. There is no discussion of machine learning or AI components that would require a "training set."

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

This information is not provided in the document. As no training set is discussed (see point 8), the establishment of its ground truth is also not mentioned.

Summary of the Document's Content Regarding Testing:

The K193644 submission's primary focus is on demonstrating substantial equivalence to a predicate device (K130883, Sedecal Digital Radiographic Upgrade Model SDRU-T). This is achieved by comparing the new device's indications for use and technological characteristics to the predicate.

The document states:

• "Bench/Performance Testing: The results of bench testing (software validation and risk analysis for a moderate level of concern device) shows that this new device poses no new issues of safety or effectiveness, has essentially the same technological characteristics as the predicate, and is therefore substantially equivalent to the predicate device."
• "Clinical Testing: Not required for a showing of substantial equivalence."

This indicates that the FDA clearance for E-COM DR-2000 DR was based on demonstrating similar technical specifications and safety/effectiveness profiles to an already cleared device, along with adherence to relevant software development and risk management guidance documents. It does not involve a new performance study with specific quantitative acceptance criteria or extensive clinical data as would be required for a novel device or one incorporating advanced AI algorithms.

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The KDR™ AU-DDR System Advanced U-Arm with Dynamic Digital Radiography and KDR™ AU System Advanced U-Arm with Static Digital Radiography is indicated for use by qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic static and serial radiographic exposures of the skull, spinal column, chest, abdomen, 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).

The proposed System is a digital radiography diagnostic system that has the capability of obtaining two modes (static mode and dynamic modes) of radiographic exposures of the skull, spinal column, chest, abdomen, extremities, and other body parts. Images may be obtained with the patient sitting, standing, or lying in the prone or supine position. It is not intended for mammographic use. The system is configurable in two options. Both are exactly the same with the exception of the option to select one of two flat panel detectors. One configuration, referred to as KDR™ AU-DDR System Advanced U-Arm with Dynamic Digital Radiography contains a HD/FNB flat panel and the other configuration, referred to as KDR™ AU System Advanced U-Arm with Static Digital Radiography a HQ/KDR panel. The technological feature of each flat panel detector is described below.

The proposed system is a compact, floor and wall mounted radiographic system with proprietary ULTRA software and DICOM 3 connectivity.

The system consists of a combination of several components. The System's hardware consists of the 3 kev components:

1. A floor and wall-mounted Positioner (also referred to as a stand)
2. A generator
3. An off-the-shelf computer with proprietary software (also referred to as an acquisition workstation)

The positioner has a swivel arm that has several rotating and linear movements, and movement controls including an information screen. Mounted on the positioner are:
a) A collimator,
b) An X-ray tube
c) An Automatic Exposure Control (AEC)
d) A flat panel detector (There are 2 configurations available for the end user to select. The KDR™ AU-DDR System Advanced U-Arm with Dynamic Digital Radiography contains a HD/FNB flat panel detector capable of obtaining both static and dynamic images and the KDR™ AU System Advanced U-Arm with Static Digital Radiography, which contains the HQ/KDR flat panel detector capable of obtaining static images only.

Hardware accessories include:

1. A mobile patient table
2. Stitching stand
3. Weight bearing stand

Optional Hardware accessories include:

1. Motorized height adjustable table
2. 3 knob collimator
3. Dose area product meter
4. Advanced weight bearing stand

The proposed system has a proprietary ULTRA software as the central interface of the system. The software for the proposed system enables users to acquire static and dynamic images.

There are two modes within the software package of the proposed system, "static mode," which may be used to generate, a single frame of radiographic images captured at a single time and "dynamic mode" (or "Dynamic Digital Radiography," abbreviated "DDR,") which generates multiple frames in a single series, presenting the physician with a diagnostic view of dynamic density and anatomic motion without using fluoroscopy or cine. The number of images acquired with the proposed system are limited to 300 compared with flouroscopy or cine, which do not limit the number of images (Note: only the configuration with the HD/FNB flat panel detector is capable of obtaining both static and dynamic images. The other configuration may only obtain static images).

The system is also capable of quickly assuming a preprogrammed position when a new exam is selected, saving time when positioning the equipment. This is referred to as "auto positioning," and made possible by the positioner and image processing software working together.

The provided document is a 510(k) summary for the Konica Minolta Healthcare Americas KDR™ AU-DDR System Advanced U-Arm with Dynamic Digital Radiography and KDR™ AU System Advanced U-Arm with Static Digital Radiography.

This document describes the device and its substantial equivalence to predicate devices, focusing on regulatory compliance and technical specifications rather than specific clinical performance data for AI/software components. The primary performance data discussed refers to compliance with safety and performance standards for X-ray systems, not an AI-driven diagnostic or assistive feature.

Therefore, many of the requested points regarding acceptance criteria and study details (like sample size for test/training sets, expert ground truth, adjudication methods, MRMC studies, or standalone performance for an AI component) are not present in this document. The document primarily addresses the safety and effectiveness of the X-ray system hardware and its software for image acquisition, not an AI-based diagnostic tool.

Based on the provided text, here's what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a table of acceptance criteria with specific performance metrics for an AI component. Instead, it refers to compliance with various electrical, safety, and imaging standards for the overall X-ray system.

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

• Not explicitly stated in the provided document. The document discusses compliance with technical standards for an X-ray system, not the performance of an AI algorithm on a specific medical image dataset.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable / not stated. This document focuses on the technical and safety performance of an X-ray imaging system, not on a machine learning model requiring expert-annotated ground truth for diagnostic accuracy.

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

• Not applicable / not stated. The context of this document does not involve diagnostic interpretations requiring adjudication.

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 done / not stated. The device described is an X-ray acquisition system; it does not present itself as an AI-assistive diagnostic tool for human readers in the context of this 510(k) summary.

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

• Not applicable / not stated. The device is an X-ray system, which includes software for image acquisition ("proprietary ULTRA software"), but the document does not describe a standalone AI algorithm for diagnostic interpretation.

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

• Not applicable / not stated. Ground truth, in the context of diagnostic AI models, is not relevant to the compliance testing of an X-ray imaging system described here.

8. The sample size for the training set:

• Not applicable / not stated. The document describes an X-ray system, and there's no mention of a machine learning component requiring a training set in this context.

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

• Not applicable / not stated. As no training set is mentioned for an AI algorithm, ground truth establishment is not relevant to the information provided.

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The PowerDR™ Digital X-ray Imaging System is indicated for use as an X-ray imaging modality to acquire, process, display, quality assure and store digital medical X-ray images.

The PowerDR™ Digital X-ray Imaging System is indicated for use in general radiographic and fluoroscopic examinations of any anatomy for adult, pediatric, and neonatal patients. It is not indicated for use in mammography.

The PowerDR™ Console Application is a digital medical X-ray imaging system consisting of an X-Ray detector, computer hardware and the PowerDR™ software. The User supplies the X-Ray generator. The PowerDR™ Console Application is intended to enable a procedure of medical image acquisition, processing, display, quality assurance, and storage. The software interfaces to an X-Ray detector from variety of vendors to acquire raw pixel data. Its image-processing algorithms transform raw pixel data into diagnostic quality images and image sequences to aid the medical professional in diagnosis. For temporary storage, image data can be stored on the local computer. For long term storage, image data can be stored on a portable media device or a remote PACS (Picture Archive and Communication System) server. The PowerDR™ Digital X-ray Imaging System is intended for use in general radiographic and fluoroscopic examinations of any anatomy for adult, pediatric, and neonatal patients. It is not intended for use in mammography. The system can be sold with or without a computer, and with or without a compatible, previously cleared, digital receptor panel.

The provided text is a 510(k) Premarket Notification for the PowerDR™ Digital X-ray Imaging System. This type of submission focuses on demonstrating substantial equivalence to a previously legally marketed device (predicate device), rather than proving the device meets specific performance acceptance criteria through the kind of studies typically seen for novel AI/ML devices.

Therefore, the document does not contain the information requested regarding acceptance criteria and a study proving the device meets those criteria for AI/ML performance.

Specifically:

• No table of acceptance criteria and reported device performance is provided because this is a substantial equivalence submission, not a performance validation against defined metrics for an AI/ML component. The "performance" demonstrated is that the new device operates similarly to the predicate device in terms of image acquisition, processing, display, quality assurance, and storage.
• No sample size for a test set or data provenance is mentioned in the context of an AI/ML performance study. The "test set" here refers to the validation of the system's ability to acquire and process images, not to a diagnostic performance evaluation of an AI algorithm. The document states "image inspection, bench, and test laboratory results" were used, and "Each available digital receptor panel has undergone a rigorous verification and validation procedure."
• No number of experts or qualifications of experts used for ground truth establishment for a test set. This is not an AI/ML diagnostic study.
• No adjudication method is mentioned, as there is no diagnostic ground truth establishment process described for an AI/ML algorithm.
• No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done because there is no AI assistance component to evaluate.
• No standalone (algorithm only) performance study was done; the focus is on the integrated system's functionality.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.) is not applicable in the context of an AI/ML performance study. The "ground truth" for this device relates to the technical specifications and image quality relative to the predicate device.
• No sample size for the training set is applicable; this is not an AI/ML algorithm that undergoes a training phase as typically understood.
• How the ground truth for the training set was established is not applicable for the same reason.

The core argument for the PowerDR™ system is that it is substantially equivalent to the predicate device (Nexus DRF Digital X-ray Imaging System, K130318) in terms of its intended use, technology, and safety and effectiveness. The evidence provided to support this is:

• Bench testing: "The results of image inspection, bench, and test laboratory results indicates that the new device is as safe and effective as the predicate devices."
• Use of previously cleared components: All compatible digital panels supported by PowerDR™ "have previously received FDA 510(k) clearances" and "undergone a rigorous verification and validation procedure."
• Compliance with FDA guidance documents: Specifically, guidance for software in medical devices, cybersecurity, and pediatric imaging information.
• Comparison chart: A detailed "Substantial Equivalence Chart" (Section 5) outlining similarities in identification, intended use, description, where used, image processing, image storage, image data source, configuration, primary digital panel support (multiple for proposed vs. one for predicate, with all proposed panels being previously cleared), system software, image data format, image presentation, application software, tracking X-ray dose, fluoro image processing, MultiRad image support, dose and processing auto optimization, quality assurance, DICOM 3.0 conformance, IHE Integration profile, power source, and computer platform.

Conclusion stated in the document: "After analyzing bench testing and risk analysis and compliance to the DICOM standard, it is the conclusion of Radiology Information Systems, Inc. that the PowerDR™ Digital X-ray Imaging System is as safe and effective as the predicate device, have few technological differences, and has the same indications for use, thus rendering it substantially equivalent to the predicate device."

In summary, this 510(k) submission does not describe an AI/ML device or a study validating AI/ML performance using acceptance criteria. Instead, it demonstrates substantial equivalence to a predicate device through bench testing and comparison of technical specifications.

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Opal Chiro and 20/20 P-DR are intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography.

The Opal Chiro and 20/20 P-DR system represents the straightforward integration of a new digital x-ray receptor panel (cleared in K062376) and our previously cleared (K123644 and K133139) software. The Opal Chiro and 20/20 P-DR are Digital Radiography systems, featuring an integrated flat panel digital detector (FPD). The Opal Chiro and 20/20 P-DR is designed to perform digital radiographic examinations as a replacement for conventional film. This integrated platform provides the benefits of PACS with the advantages of digital radiography for a filmless environment and improves cost effectiveness. The major functions and principle of operation of the Viztek PACS and the new receptor panel were not changed. Our main predicate is ViZion + DR, K123644, wherein we combined our OPAL-RAD software with two new digital panels. The upgrade kits are compatible with modern HF diagnostic X-ray generators like Sedecal and CPI. The 20/20 P-DR has been tested with X-Cel 700/900 series of generators.

The provided text describes Opal Chiro and 20/20 P-DR, a Digital Radiography system. However, it does not contain specific acceptance criteria, detailed study designs, or performance metrics that would allow for a comprehensive answer to all parts of your request. The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance studies against specific acceptance criteria.

Based on the available information, here's what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria for device performance. Instead, it relies on a qualitative assessment compared to a predicate device.

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

The document does not specify the sample size used for the clinical image acquisition and review. It states that "Clinical images were acquired and evaluated." The provenance of the data (country of origin, retrospective or prospective) is also not mentioned.

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

The test set involved evaluation by "a board certified radiologist." The number of experts is one. Their specific qualifications beyond "board certified radiologist" are not detailed (e.g., years of experience, subspecialty).

4. Adjudication Method for the Test Set

With only one radiologist evaluating the images, an adjudication method like 2+1 or 3+1 is not applicable or mentioned. The single expert's evaluation served as the basis for comparison.

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

No, an MRMC comparative effectiveness study is not indicated. The document describes a comparison of images by a single radiologist against a predicate, not a study of human reader improvement with or without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The device itself is a digital X-ray receptor panel and associated software for image capture and processing. The performance evaluated here is essentially the standalone performance of the imaging system in producing images. It's not an AI algorithm in the sense of making diagnoses, but rather an image acquisition and processing system. The evaluation focused on the quality of the output images.

7. The Type of Ground Truth Used

The ground truth for the clinical images was established through expert visual assessment/consensus by a board-certified radiologist, comparing the images to those from a predicate device. There is no mention of pathology or outcomes data being used as ground truth.

8. The Sample Size for the Training Set

The document does not provide any information about a training set since the device described is an imaging system (hardware and associated software for image processing), not a machine learning model that typically requires a distinct training set. The software mentioned (OpalRad Software) is described as "previously cleared" and its major functions and principle of operation "were not changed," implying it was not "trained" in the typical AI sense for this submission.

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

Since there is no mention of a training set for an AI model, the method for establishing its ground truth is not applicable or described in this document.

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