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510(k) Data Aggregation

    K Number
    K061999
    Date Cleared
    2006-08-15

    (32 days)

    Product Code
    Regulation Number
    892.2040
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    DRY LASER IMAGER, DRYPRO MODEL 832

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Dry Laser Imager, DRYPRO Model 832 is intended to be used to receive image data from diagnostic equipment such as CT, MRI, DSA and other medical devices and print them on medical dry-film. The output image is not a high resolution and DRYPRO Model 832 is not intended for use with FFDM systems.

    Device Description

    The Dry Laser Imager, DRYPRO Model 832 is a Laser Imager to receive image data from diagnostic equipment such as CT, MRI, DSA and other medical devices and print them on medical dry-film. The device consists of film supplying unit, film transferring unit, exposing unit, heat-developing unit, operating unit, power supplying unit and main control unit. This product employs semiconductor laser scanning, but it complies with the Federal Performance Standard 21 CFR Part 1040.10. This device has no patient contacting materials and is intended to be used by trained personnel only. The output of the device is evaluated by additionally trained personnel capable of sufficient review to afford identification and intervention in case of malfunction.

    AI/ML Overview

    This document describes the Konica Minolta Medical & Graphic, Inc. Dry Laser Imager, DRYPRO Model 832, a medical image hardcopy device, seeking 510(k) clearance. The device is intended to receive image data from diagnostic equipment (CT, MRI, DSA) and print it on medical dry-film. It explicitly states that the output image is not high resolution and is not intended for use with FFDM (Full Field Digital Mammography) systems.

    Here's the breakdown of the acceptance criteria and study information:

    1. Table of Acceptance Criteria and Reported Device Performance

    The provided document does not explicitly state "acceptance criteria" in a typical quantitative pass/fail format for clinical performance. Instead, it presents a comparison table between the new device (DRYPRO Model 832) and its predicate device (DRYPRO Model 771) to demonstrate substantial equivalence based on technical specifications and intended use. The implicit acceptance criterion is that the new device's performance characteristics are comparable to or improved over the predicate device, or any changes do not raise new questions of safety or effectiveness.

    ItemPredicate Device (DRYPRO Model 771) Reported PerformanceNew Device (DRYPRO Model 832) Reported Performance
    Laser SourceLaser Diode [LD] (810nm)Laser Diode [LD] (785nm)
    Laser Power100mW (Maximum Output)240mW (Maximum Output)
    Laser ModulatorDirect driving modulatorDirect driving modulator
    Film TypeKonica Medical Imaging Film (SD-P & SD-Pc)Konica Medical Imaging Film (SD-P & SD-Pc)
    Film Sizes14"x 17", 14"x 14", 11"x 14"14"x 17", 14"x 14", 11"x 14", 10"x 12", 8"x 10"
    Film Supply1 unit1 unit or 2 units (125 or 50 film on each) for installation of Optional Supply
    Interface10/100base-TX, 4 network ports maximum10/100/1000base-TX, 4 network ports maximum
    ProtocolDICOM version 3.0, Print service classDICOM version 3.0, Print service class
    Image Data Storageone Hard Disk Driveoutside PC
    Image Formatting1,2,4,6,9,12,15,16,20,24,25,30,35,36,42, and 48 frame formats, and mixed formats available.1,2,4,6,9,12,15,16,20,24,25,30,35,36,42, and 48 frame formats, and mixed formats available.
    Pixel Size78.6 micro-meters minimum78.6 micro-meters minimum
    Density Resolution14bits / pixel14bits / pixel
    Cycle Time30 sec.40 sec.
    Test PatternPre-programmed SMPTE patternPre-programmed SMPTE pattern
    SmoothingChoice of Pixel replication, Bi-linear. Spline functions via networkChoice of Pixel replication, Bi-linear. Spline functions via network
    Image RotationChoice of 0 (normal), 90 degrees via networkChoice of 0 (normal), 90 degrees via network
    Exposure Setting8 types / port via network8 types / port via network
    Image BordersChoice of black or clear via networkChoice of black or clear via network
    Image FramingChoice of framing or no framing via networkChoice of framing or no framing via network
    Print DevelopingChoice between negative and positive printing via networkChoice between negative and positive printing via network
    Character InputData and message data printed in margins via networkData and message data printed in margins via network
    Copying99 copies per print maximum via network99 copies per print maximum via network
    Controller DisplayBacklight liquid-crystal display (20 places, 2 lines)Backlight liquid-crystal display (20 places, 2 lines)
    External DimensionsW630mm x D600mm x H1125mmW599mm x D585mm x H570mm
    WeightApprox. 175KgApprox. 95Kg
    Power Consumption1020VA maximum (destination of USA)1200VA maximum (destination of USA)
    Exhaust HeatApprox. 950kJ / hourApprox. 1200kJ / hour
    Purpose of useThe device is intended for the use at the X-ray department of the hospital, etc. the device that will acquire data from diagnostic equipment and then print the data onto laser imaging film.The device is intended for the use at the X-ray department of the hospital, etc. the device that will acquire data from diagnostic equipment and then print the data onto laser imaging film.

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

    The document does not describe a clinical performance study with a "test set" in the context of an AI/algorithm-driven device for diagnosis. This device is a hardcopy printer. The evaluation for substantial equivalence relies on comparing technical specifications and intended use with a predicate device. Therefore, there's no explicitly defined "sample size" or "data provenance" as would be relevant for an algorithm's diagnostic performance. The testing would have focused on the device's functional performance, image quality, and safety standards, but the details of such internal testing are not provided in this summary.

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

    Not applicable. As a medical image hardcopy device, the "ground truth" refers to the fidelity and accuracy of the printed image compared to the digital input and established image quality standards for medical prints. There are no mentions of "experts" establishing clinical ground truth for diagnostic purposes in this document, as the device does not perform diagnosis.

    4. Adjudication Method for the Test Set

    Not applicable for this type of device. Adjudication methods are relevant for evaluating diagnostic accuracy from algorithms or readers.

    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 applicable. This device is a printer, not an AI diagnostic tool.

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

    Not applicable. This is a hardware device for printing, not a standalone algorithm.

    7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

    The "ground truth" for this hardcopy device would implicitly refer to the technical specifications of image quality (e.g., pixel size, density resolution, print fidelity) as verified against industry standards (like those in DICOM and potentially SMPTE patterns mentioned). It's about ensuring the printed output accurately represents the digital input according to established technical benchmarks, rather than a clinical ground truth for a diagnostic finding.

    8. The Sample Size for the Training Set

    Not applicable. This device is a laser imager, a hardware product, not an AI model requiring a training set.

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

    Not applicable, as there is no training set for this type of device.

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