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510(k) Data Aggregation

    K Number
    K210278
    Device Name
    Titan SGS
    Date Cleared
    2021-04-28

    (86 days)

    Product Code
    Regulation Number
    878.4750
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Titan SGS

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

    The Titan SGS linear cutter is intended for longitudinal transection of gastric tissue for sleeve gastrectomy pouch creation.

    Device Description

    The Titan SGS with implantable staples (Titan Stapler) is a single patient use, sterile instrument used for cutting and stapling gastric tissue for sleeve gastrectomy pouch creation. The Titan Stapler is supplied preloaded with staples, fires once and cannot be reloaded. The Titan Stapler is comprised of three main sections: Stapler, Cable, and Power Supply Unit. The stapler end effector is 230 mm long and contains 342 staples that are organized in 6 staggered rows, 3 on each side of the cut line. The staples range in closed staple height from 2.2 mm to 1.2 mm. Staples are formed into a traditional 'B' shape: similar to existing devices. As with other powered staylers, the Titan Stapler opens and closes through a simple mechanical linkage housed in the shaft and effector of the device. The device of the single-use Titan Stapler and a reusable power source which is supplied separately. There are no accessories supplied with the instrument. The Titan Stapler Power Source is designed to supply energy to the Titan Stapler and has a unique receptable port specific to the Titan Stapler.

    AI/ML Overview

    The provided text describes the 510(k) premarket notification for the Titan SGS linear cutter. However, it does not contain the specific acceptance criteria and detailed study information requested in your prompt regarding device performance metrics like accuracy, sensitivity, or specificity.

    The document focuses on demonstrating substantial equivalence to a predicate device (Echelon Flex Powered Plus) rather than proving the device meets specific performance criteria against a predefined ground truth in the way one might for an AI/ML diagnostic device.

    Here's a breakdown of what is available and what is missing based on your request:

    1. A table of acceptance criteria and the reported device performance

    This information is not explicitly provided in the document in the format of specific acceptance criteria (e.g., minimum accuracy of X%, sensitivity of Y%). The document states:

    • "Pre-determined performance specifications were tested, and validation activities were conducted to demonstrate that the Titan Stapler met the defined criteria."
    • "The Titan Stapler met acceptance criteria and demonstrated comparable performance to the predicate device for the equivalent indications for use."

    However, the specific quantitative acceptance criteria and the corresponding reported performance values (e.g., specific measurements of staple line integrity, leak rates, etc.) are not detailed. It mentions "hemostasis as compared to the predicate device" in animal studies, but no numerical data.

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Clinical Study: "A comparative clinical study including 36 subjects at one site was conducted between the Titan Stapler and the predicate device, the Echelon Flex Powered Plus GST System on excised human stomach." This implies a prospective study using ex vivo human stomach tissue. The country of origin is not specified but given the FDA context, it's likely the US.
    • IDE Study: "The study enrolled 62 subjects at three sites." This was a prospective study (IDE G200085). Country of origin is not specified, but again, likely the US.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    This information is not provided. The assessment of "comparable performance" in the clinical studies would have involved expert evaluation (e.g., surgeons assessing the staple line), but the number and qualifications of these experts are not detailed.

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

    This information is not provided.

    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

    There is no mention of an MRMC study or AI assistance. This device is a surgical stapler, not an AI/ML diagnostic tool.

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

    This is not applicable as it's a physical medical device (surgical stapler), not an algorithm.

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

    For the "clinical study (36 subjects) on excised human stomach," the ground truth would likely involve direct visual and physical assessment by surgical experts regarding the quality of the stapled tissue (e.g., staple formation, integrity, transection line).

    For the "IDE G200085 study (62 subjects)" which demonstrated "reasonable assurance of safety and effectiveness," the ground truth would typically involve a combination of:

    • Clinical outcomes data: monitoring for adverse events (e.g., leaks, bleeding, stricture formation) specific to the stapler performance.
    • Intraoperative and postoperative assessments: by surgeons and medical staff.

    8. The sample size for the training set

    This is not an AI/ML device, so there is no "training set" in the context of an algorithm. The development of the device would involve engineering design, bench testing prototypes, and animal studies before human studies.

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

    Not applicable as it's not an AI/ML device.

    In summary: The provided document is an FDA 510(k) clearance letter and summary for a surgical stapler, focusing on demonstrating substantial equivalence to a predicate device. It does not provide the kind of detailed performance metrics, acceptance criteria, and AI/ML specific study information you requested, as those types of studies and criteria are typically associated with diagnostic AI/ML products.

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