K Number
K220848
Device Name
Venue Fit
Manufacturer
Date Cleared
2022-06-27

(96 days)

Product Code
Regulation Number
892.1550
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Venue Fit is a general purpose diagnostic ultrasound system for use by qualified and trained healthcare professionals for ultrasound imaging, measurement, display and analysis of the human body and fluid. Venue Fit is intended to be used in a hospital or medical clinical applications include: abdominal (GYN and Urology), thoracic pleural, ophthalmic. Fetal/OB. Small Organ (including breast, testes, thyroid), VascularPeripheral vascular, neonatal and adult cephalic, pediatric, musculoskeletal (conventional and superficial), cardiac (adults and pediatic), Transrectal, Transvaginal, Transesophageal, Intraoperative (vascular) and interventional guidance (includes tissue biopsy, fluid dramage, vascular and non-vascular access). Modes of operation include: B, M, PW Doppler, CW Doppler, Color Doppler, Color M Doppler, Power Doppler, Harmonic Imaging, Coded Pulse and Combined modes: BM, B/Color M, B/PWD, B/Color/PWD, B/Power/PWD, B/CWD, B/Color/CWD.

Device Description

Venue Fit is a general-purpose diagnostic ultrasound system intended for use by qualified and trained healthcare professionals to evaluate the body by ultrasound imaging and fluid flow analvsis. The Venue Fit is a compact, portable system with a small footprint. The system can be hand carried using the integrated handle, placed on a horizontal surface (if kickstand is attached), attached to a mobile cart or mounted on the wall. It has a high resolution color LCD monitor, with a simple, multi-touch user interface that makes the system intuitive. The system can be powered through an electrical wall outlet for long term use or from an internal battery for a short time with full functionality and scanning. The Venue Fit utilizes a variety of linear, convex, and phased array transducers which provide high imaging capability, supporting all standard acquisition modes. Compatible biopsy kits can be used for needle-guidance procedures. The system is capable of displaying the patient's ECG trace synchronized to the scanned image. This allows the user to view an image from a specific time of the ECG signal which is used as an input for gating during scanning. The ECG signal can be input directly from the patient or as an output from an ECG monitoring device. ECG information is not intended for monitoring or diagnosis. A barcode reader and RFID scanner are available as additional input devices. A roller bag will also be available for the customer to use when transporting the system. Venue Fit is capable of wired or wireless internet connection. The system meets DICOM requirements to support users image storage and archiving needs (local PACS or products such as Q-Path) and allows for output to printing devices. The user documentation is available electronically.

AI/ML Overview

Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance (cNerve feature)

Acceptance Criteria (cNerve)Reported Device Performance (cNerve)
Sequence Accuracy Requirement:Achieved: Not explicitly stated as a percentage in the document, but the text states: "Success criteria were based on conformance of the cNerve detections to ground truth annotations of nerve bundles in individual frames. Since the intended use is nerve tracking during scouting rather than nerve segmentation accuracy, success criteria were derived via a preliminary survey. The target of the survey was to identify thresholds for pixel accuracy in frames and for frame accuracy in sequences that are appropriate for the intended use."
At least 70% of the sequences are meaningfully detected.Achieved: Not explicitly stated as a percentage in the document. The study's focus was on meeting the success criteria derived from the preliminary survey which aimed to define "meaningfully detected" and "successfully detected" based on pixel and frame accuracy thresholds.
At least 80% of the meaningfully detected sequences are successfully detected (meeting frame accuracy criteria).Achieved: Not explicitly stated as a percentage in the document. The study's focus was on meeting the success criteria derived from the preliminary survey which aimed to define "meaningfully detected" and "successfully detected" based on pixel and frame accuracy thresholds.

Note: The document does not provide specific performance percentages against the 70% and 80% thresholds. It states that success criteria were based on conformance to ground truth and that preliminary surveys identified appropriate thresholds for pixel and frame accuracy for the intended use.

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

  • Sample Size:
    • Sequences: 124 sequences
    • Frames: 3776 frames
    • Individuals: 44 individuals
  • Data Provenance: USA, Japan, Israel (Retrospective, as it was a pre-existing dataset used for verification)

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

  • Number of Experts: A single clinical expert.
  • Qualifications of Experts: "clinical expert" - further specific qualifications (e.g., years of experience, specialty) are not provided in the document.

4. Adjudication Method for the Test Set

  • Adjudication Method: None explicitly stated. Ground truth annotations were performed by a single clinical expert.

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

  • No MRMC comparative effectiveness study was done to evaluate human reader improvement with AI assistance. The testing focused on the standalone performance of the cNerve feature.

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

  • Yes, a standalone study was performed. The "AI Summary of Testing" directly addresses the performance of the cNerve algorithm against ground truth annotations.

7. The Type of Ground Truth Used

  • Type of Ground Truth: Expert consensus (from a single clinical expert) on anatomical areas of nerve bundles within individual frames.

8. The Sample Size for the Training Set

  • The document does not specify the sample size for the training set. It only states that the data used for verification is "completely distinct" from the training data.

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

  • The document does not specify how the ground truth for the training set was established. It only ensures that the verification data was distinct from the training data.

§ 892.1550 Ultrasonic pulsed doppler imaging system.

(a)
Identification. An ultrasonic pulsed doppler imaging system is a device that combines the features of continuous wave doppler-effect technology with pulsed-echo effect technology and is intended to determine stationary body tissue characteristics, such as depth or location of tissue interfaces or dynamic tissue characteristics such as velocity of blood or tissue motion. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.