Search Results

These radiographic systems are 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.

Proteus Radiographic System, Models XR/f ST and XR/f ET; MULTIRAD and MULTIRAD NET. These radiographic systems are designed for general radiography in hospitals, clinics, radiology imaging centers and medical practices. It is 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, chest, abdomen, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. Patients may be physically abled, disabled, immobilized or in state of a shock. The Radiographic Systems are not intended for mammography applications. If children are to be examined, they should always be accompanied by an adult.

Radiographic System Proteus XR/f has been interfaced with the Digital Imaging System of Konica Minolta Inc consisting of the image receptor and application for image acquisition (control console & image processing controller).

Here's an analysis of the provided text regarding the acceptance criteria and study information for the Proteus XR/f, Models ST and ET, Multirad, and Multirad NET Radiographic Systems:

Acceptance Criteria and Device Performance:

The document describes the device as being "substantially equivalent" to a legally marketed predicate device (K090279: Sedecal "Millennium Plus Digital Diagnostic X-Ray System") and references a reference device (K182688: Konica Minolta Wireless Detector SKR3000) without modification. The performance comparison is primarily qualitative, focusing on similar specifications and compliance with standards rather than explicit quantitative acceptance criteria with reported numerical performance.

Here's a table summarizing the implicit acceptance criteria based on the comparison to the predicate devices and the reported device characteristics:

Study Information:

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

   • The document states: "Clinical testing was not required to establish substantial equivalence because all digital x-ray receptor panels have had previous FDA clearance."
   • Therefore, there is no explicit test set of patient images or data described for the Proteus XR/f system itself. The substantial equivalence relies on non-clinical (bench) testing and the prior clearance of its components (particularly the digital x-ray detector panel).

2. 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 requiring expert ground truth establishment for the Proteus XR/f was conducted. The clearance is based on substantial equivalence to predicate devices and component (digital x-ray receptor panel) clearances.

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

   • Not applicable, as no clinical test set was conducted.

4. 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 MRMC comparative effectiveness study was mentioned or performed. This device is an X-ray system, not an AI-powered diagnostic tool, so such a study would not be relevant for its primary clearance.

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

   • Not applicable, as this is an X-ray imaging system, not an AI algorithm. Its performance is related to image quality and system functionality, not diagnostic algorithmic output.

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

   • For the X-ray system itself, the "ground truth" for its performance is assessed through bench testing against established engineering and safety standards (e.g., IEC 60601 series, 21 CFR 1020.30, 1020.31) and comparison of technical specifications (kVp, mA, mAs accuracy, MTF/DQE values) to the predicate devices. The image quality, for instance, is implicitly compared to "diagnostic quality images as good as our predicate generator/panel combination."
   • For the digital X-ray receptor panels used within the system (Konica Minolta Wireless Detector SKR3000), their prior FDA clearances would have involved their own ground truth evaluations, but those details are not provided in this document.

7. The sample size for the training set:

   • Not applicable, as this is an X-ray imaging system, not an AI algorithm that requires a training set.

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

   • Not applicable, as this device does not utilize a training set.

Ask a specific question about this device

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.

Ask a specific question about this device