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510(k) Data Aggregation

    K Number
    K210309
    Date Cleared
    2021-03-05

    (30 days)

    Product Code
    Regulation Number
    892.1650
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Cios Select is a mobile X-ray system intended for use in Operating room, Traumatology, Endoscopy, Intensive Care Station, Pediatrics, Ambulatory patient care and in Veterinary Medicine.

    The Cios Select can operate in three different modes, Digital Radiography, Fluoroscopy, and Pulsed Fluoroscopy which are necessary in performing wide variety of clinical procedures, such as intraoperative bile duct display, fluoroscopic display of an intra-medullary nail implants in various positions, low dose fluoroscopy in pediatrics, fluoroscopic techniques utilized in pain therapy and positioning of catheters and probes.

    Device Description

    The Cios Select (VA21) Mobile X-ray System is designed for the surgical environment. The Cios Select (VA21) is a modification of the Cios Select originally cleared under Premarket Notification K181767 on August 17, 2018.

    The Cios Select consists of two major units:

    The Siemens Healthineers Cios Select mobile fluoroscopy C-arm system is an X-ray imaging system consisting of two mobile units: a mobile acquisition unit and a monitor cart as the image display station.

    The mobile acquisition unit is comprised of the X-ray control, the C-arm which supports the single-tank high-frequency generator/X-ray tube assembly, the flat panel detector, and user controls.

    The monitor cart connects to the acquisition unit by a cable. It integrates the TFT flat panel displays, Digital Imaging Processing System, user controls and image storage devices (DVD, USB).

    AI/ML Overview

    The provided text describes a 510(k) submission for the Cios Select (VA21) Flat Panel X-ray system, which is a modification of an existing device. A 510(k) submission primarily focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving novel clinical effectiveness or "new" device performance metrics directly applicable to AI/ML systems or diagnostic accuracy studies.

    Therefore, the document does not contain the level of detail typically found in studies designed to prove a device meets specific acceptance criteria for diagnostic performance, especially concerning AI/ML algorithms where terms like "ground truth," "expert consensus," "sample size for training/test sets," and "MRMC studies" are paramount.

    The modifications described in this 510(k) are mainly related to:

    • Upgraded software (VA21) with new optional features (Cios OpenApps, Target pointer)
    • New optional laser aimers (tube side and flat detector side)
    • Enhanced cybersecurity

    The acceptance criteria and study conducted are primarily focused on verifying that these modifications do not introduce new safety or effectiveness concerns and that the device continues to meet established performance and regulatory standards, particularly for safety and electromagnetic compatibility (EMC). It's a "Special 510(k)," indicating minor changes to a cleared device.

    Therefore, many of the requested items (e.g., sample size for test set, number of experts, MRMC study, standalone performance) are not explicitly detailed in the provided K210309 submission as it is not a submission for a new AI/ML diagnostic algorithm requiring such clinical performance validation.

    Here's an attempt to extract and interpret the information based on the provided text:


    Acceptance Criteria and Device Performance for Siemens Cios Select (VA21)

    As this is a 510(k) submission for modifications to an existing X-ray system, the "acceptance criteria" are primarily related to general safety, effectiveness, and continued compliance with established standards for medical devices and X-ray systems, rather than accuracy metrics for a specific diagnostic task typically seen with AI/ML algorithms. The study conducted is mainly focused on verification and validation of the modifications to ensure they do not alter the substantial equivalence of the device.

    1. Table of Acceptance Criteria and Reported Device Performance

    Given the nature of this 510(k) (modifications to an existing device, not a new diagnostic AI), the acceptance criteria are based on compliance with general medical device standards and the assessment that changes do not introduce new safety or effectiveness concerns.

    Acceptance Criteria (Implied from Regulatory Standards & Submission Type)Reported Device Performance/Compliance
    General Safety (Electrical, Mechanical, Radiation)Cios Select "has been tested to meet the requirements for conformity to multiple industry standards." Complies with:
    • 21 CFR 1020.30 (Diagnostic X-Ray Systems), 1020.31 (Radiographic), 1020.32 (Fluoroscopic), 1040.10 (Laser products).
    • AAMI ANSI ES60601-1:2005/(R)2012 (Electrical Safety)
    • IEC 60601-1-2:2014 (EMC)
    • IEC 60601-1-3:2013, IEC 60601-2-28:2017, IEC 60601-2-43:2017, IEC 60601-2-54:2009/A1:2015 (X-ray system specific safety)
    • ISO 14971:2007 (Risk Management)
      "Electrical safety and EMC testing were conducted... The system complies with the IEC 60601-1, IEC 60601-2-43 and IEC 60601-2-54 standards for safety and the IEC 60601-1-2 standard for EMC." |
      | Software Functionality & Performance (for VA21 upgrade & new features) | "The system software was upgraded to support new software features (1-3)."
      "Upgraded software VA21 with Cios Open Apps and Target Pointer. There are no technological differences in these features and the functionality of these features have not changed except for better visualization of moving k-wires. These features are the exact same features cleared in the Secondary Predicate Device Cios Flow (VA30) K1203504. Software Testing was conducted per Software Guidance."
      "The performance data demonstrates continued conformance with special controls for medical devices containing software."
      "Non-clinical tests were conducted on the Subject Device Cios Select software version VA21 during product development."
      "The testing results support that all the software specifications have met the acceptance criteria."
      "Testing for verification and validation for the device was found acceptable to support the claims of substantial equivalence."
      "All testable requirements... have been successfully verified and traced in accordance with the Siemens product development (lifecycle) process."
      "The software verification and regression testing has been performed successfully to meet their previously determined acceptance criteria as stated in the test plans." |
      | New Hardware Components (Laser Aimer functionality) | "Same: The green laser aimers on the side of the tube and flat detector is the same exact laser aimer cleared in the Secondary Predicate Device Cios Spin (VA30) K181550." (Implies functional equivalence and safety verification). |
      | Cybersecurity | "Enhanced Cybersecurity."
      "Same: Cybersecurity features are the same features cleared in Cios Select VA20 (K181767)."
      Siemens "conforms to the cybersecurity requirement... Provided in this submission is a cybersecurity statement that considers IEC 80001-1:2010." |
      | Human Factors/Usability | "The Cios Select software (VA21) was tested and found to be safe and effective for intended users, uses and use environments through the design control verification and validation process."
      "The Human Factor Usability Validation showed that Human factors are addressed in the system test according to the operator's manual and in clinical use tests with customer report and feedback form." |
      | Substantial Equivalence (Overall - no new safety/effectiveness concerns introduced by modifications) | "The Cios Select does not introduce any new potential safety risks and is substantially equivalent, and performs as well as the predicate devices."
      "Results of all conducted testing and clinical assessments were found acceptable and do not raise any new issues of safety or effectiveness." |

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

    The document does not specify a "sample size" in the context of clinical images for a diagnostic test set. The testing described is primarily engineering bench testing, software verification/validation, and compliance with performance standards. These tests are conducted on the device itself and its components.

    • Test Set: Not applicable in the context of a clinical image test set for diagnostic accuracy. The "test set" here refers to the device and its updated software/hardware components undergoing various engineering and compliance tests.
    • Data Provenance: Not applicable for clinical image data. The product is manufactured by Siemens Shanghai Medical Equipment Ltd. (Shanghai, China) and Siemens Medical Solutions USA, Inc. (Malvern, PA, USA) is the importer/distributor. The testing appears to be internal verification and validation conducted by Siemens. The clinical use tests mentioned might involve feedback from "customer employees" (users) but the origin of any "clinical assessments" or "clinical use tests" data (e.g., country, retrospective/prospective collection) is not specified.

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

    This information is not provided. The ground truth for this device's performance is established by engineering specifications, regulatory standards, and functional verification, not by expert clinical interpretation because it is an imaging system, not a diagnostic AI tool that renders interpretations.

    4. Adjudication Method for the Test Set

    Not applicable. There is no mention of a human adjudication process for a diagnostic outcome, as the study focuses on the device's functional and safety performance, not its diagnostic accuracy in interpreting images.

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

    No, an MRMC study was not performed or reported in this 510(k) submission. This type of study is typically done to evaluate the impact of an AI diagnostic aid on human reader performance, which is not the focus of this submission. The device is an X-ray system, not primarily an AI diagnostic tool.

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

    Not applicable. The AI/ML aspects (if any, as "Cios OpenApps" might imply some advanced processing) are described as "optional" software features that are "the exact same features cleared in the Secondary Predicate Device Cios Flow (VA30) K1203504." The submission does not detail standalone performance of any such algorithms, as the primary focus is on the substantial equivalence of the modified X-ray system.

    7. The Type of Ground Truth Used

    The "ground truth" for this submission is based on:

    • Engineering Requirements Specifications (ERS) and Subsystem Requirements Specifications (SRS): Performance is measured against predefined technical requirements.
    • Regulatory Standards: Compliance with established safety (e.g., IEC 60601 series, 21 CFR standards) and quality standards.
    • Equivalence to Predicate Devices: The "ground truth" is that the modified device performs comparably to the predicates and does not introduce new safety or effectiveness concerns, demonstrating substantial equivalence.
    • Risk Management Hazard Keys: Verification that identified hazards have been mitigated.

    There is no mention of "expert consensus," "pathology," or "outcomes data" being used as ground truth for a diagnostic performance evaluation in this document.

    8. The Sample Size for the Training Set

    Not applicable. The document describes modifications to an X-ray system and its software, not the development of a new AI/ML algorithm that would require a distinct training set. The software updates are "upgraded software" or "same features" as predicate devices, implying a focus on verification rather than new algorithm training data.

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

    Not applicable, as no dedicated training set for a new AI/ML algorithm is mentioned.

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