K Number
K210619
Device Name
SKR 3000
Date Cleared
2021-08-24

(176 days)

Product Code
Regulation Number
892.1680
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

This device is indicated for use in generating radiographic images of human anatomy. It is intended to a replace radiographic film/screen system in general-purpose diagnostic procedures.

This device is not indicated for use in mammography, fluoroscopy, and angiography applications.

Device Description

The digital radiography SKR 3000 performs X-ray imaging of the human body using an Xray planar detector that outputs a digital signal, which is then input into an image processing device, and the acquired image is then transmitted to a filing system, printer, and image display device as diagnostic image data.

The subject device SKR3000 is not intended for use in mammography
This device is also used for carrying out exposures on children.

The Console CS-7, which controls the receiving, processing, and output of image data, is required for operation. CS-7 implements the following image processing; gradation processing, frequency processing, dynamic range compression, smoothing, rotation, reversing, zooming, and grid removal process/scattered radiation - correction (Intelligent-Grid). The Intelligent-Grid is cleared in K151465.

The proposed SKR 3000 is modified to consist of new FPD P-65 and P-75 in addition to previously cleared P-61, P-71, and P-81, Console CS-7 and other peripherals. The DR Detector uses the exposure signal or exposure from the X-ray device to generate X-ray digital image data for diagnosis, including serial exposure images, and send to the image processing controller.

The operator console software, Console CS-7, is a software program for installation on a OTC PC. Software module modifications have been made to use new FPDs (P-65 and P-75) (Cassette Type Detection Software (CTDS)) and to support 40 seconds serial radiography (SIC).

The FPDs used in SKR 3000 can communicate with the image processing device through the wired Ethernet and/or the Wireless LAN (IEEE802.11a/n and FCC compliant). The WPA2-PSK (AES) encryption is adopted for a security of wireless connection.

The new DR panels, P-65 and P-75, employ the surface material containing antibacterial agent in both radiation and irradiation sides. In the serial radiography settings, acquisition time has been changed from up to 20 seconds to 40 seconds to observe a variety of dynamic objects. Other control parameters of serial radiography are not changed from the predicate device.

The SKR 3000 is distributed under a commercial name AeroDR 3.

AI/ML Overview

This document describes the Konica Minolta SKR 3000, a digital radiography system, and its substantial equivalence to a predicate device. The information provided focuses on the device's design, specifications, and performance testing to demonstrate compliance with standards, but does not include a detailed study proving the device meets specific acceptance criteria related to diagnostic accuracy or clinical outcomes through a prospective trial involving human readers. The provided text primarily focuses on engineering and regulatory compliance, not clinical performance metrics in the context of AI assistance or human reader improvement.

However, based on the provided text, here's a breakdown of the acceptance criteria met through performance testing as described, and the absence of certain study types:

1. Table of Acceptance Criteria and Reported Device Performance

The document broadly states that "the performance tests according to the 'Guidance for the Submission of 510(k)s for Solid State X-ray Imaging Devices' and the other verification and validation including the items required by the risk analysis for the SKR3000 were performed and the results demonstrated that the predetermined acceptance criteria were met."

While specific numerical acceptance criteria and their corresponding reported device performance values are not explicitly detailed in the text, the comparison table implicitly highlights characteristics where performance is expected to be equivalent or improved. For instance, the Signal-to-Noise Ratio (SNR) and Detective Quantum Efficiency (DQE) are critical performance metrics for X-ray detectors, and based on the equivalence asserted, one can infer that these metrics met predefined acceptance thresholds.

Given the information in the "Comparison Table", the following can be inferred as performance aspects that were evaluated and met criteria for substantial equivalence:

Acceptance Criteria (Implied from comparison)Reported Device Performance (Implied from comparison)
Image Quality Metrics:
MTF (1.0 cycle/mm)Non-binning: 0.62
MTF (1.0 cycle/mm)2x2 binning: 0.58
DQE (1.0 cycle/mm)56% @ 1mR
DQE (0 cycle/mm)65% @ 0.02mR
Exposure Acquisition TimeMax. acquisition time: 40 seconds (for serial radiography)
Battery Duration in StandbyP-65: Approx. 13.2 hours; P-75: Approx. 12.2 hours
Antibacterial PropertiesSurface infused with Silver ions (antibacterial properties)
Environmental Protection (IPX)IPX6
Regulatory ComplianceAAMI/ANSI ES 60601-1 (Ed.3.1), IEC 60601-1-2 (Ed.4.0), and ISO 10993-1 (2018) met.
Software FunctionalityNew FPD support (CTDS) and 40 seconds serial radiography support (SIC) operating as intended.
Absence of New Safety/Effectiveness IssuesPerformance tests demonstrated no new issues compared to predicate device.

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

The provided document does not detail any clinical test set or data provenance in terms of patient images or specific study populations. The performance data mentioned refers to engineering and quality assurance tests, not clinical performance studies with patient data.

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

This information is not applicable or disclosed in the provided text. The document refers to engineering performance tests and compliance with regulatory standards, not expert-adjudicated clinical ground truth.

4. Adjudication Method for the Test Set

This information is not applicable or disclosed as there is no mention of a human-reviewed test set or adjudication process for diagnostic performance.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not mentioned in the provided text. The document indicates that "the results of risk management did not require clinical studies to demonstrate the substantial equivalency of the proposed device," which suggests that comparative effectiveness with human readers or AI assistance was not a component of this 510(k) submission.

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

The device itself is a digital radiography system, which generates images. While there are software components (like Console CS-7 for image processing), the submission focuses on the hardware (FPDs) and overall system performance in generating X-ray images, not an AI algorithm's standalone diagnostic performance. Therefore, such a standalone diagnostic algorithm study is not mentioned. The "performance tests" refer to technical specifications and safety, not diagnostic accuracy.

7. The Type of Ground Truth Used

Based on the document, the "ground truth" for the acceptance criteria was primarily based on technical specifications, regulatory standards, and engineering performance requirements. These include metrics like MTF, DQE, mechanical dimensions, battery life, IPX ratings, and compliance with electrical safety and electromagnetic compatibility standards. No clinical ground truth (e.g., pathology, outcomes data, or expert consensus on disease presence) is mentioned as being used for performance evaluation in this submission.

8. The Sample Size for the Training Set

This is not applicable or disclosed. The document does not describe the development or training of an AI algorithm in the context of machine learning, so there is no mention of a training set of images.

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

This is not applicable or disclosed as there is no mention of an AI training set.

§ 892.1680 Stationary x-ray system.

(a)
Identification. A stationary x-ray system is a permanently installed diagnostic system intended to generate and control x-rays for examination of various anatomical regions. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II (special controls). A radiographic contrast tray or radiology diagnostic kit intended for use with a stationary x-ray system only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.