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510(k) Data Aggregation

    K Number
    K243227
    Device Name
    B-Scan
    Date Cleared
    2025-07-11

    (276 days)

    Product Code
    Regulation Number
    892.1560
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The B-Scan module is used for imaging the internal structure of the eye, including the opaque media and posterior pathology, for the purpose of diagnosing pathological or traumatic conditions in the eye. The probe is intended to be used on both adult and pediatric patients that require imaging of the eye.

    Device Description

    The B-Scan device is designed as an ultrasound B-Scan, which uses pulsed echo ultrasound to image the structure of the eye. It utilizes an eye-contact probe to generate and receive the ultrasound pulse signals and provides a graphic display of returning pulse echoes to indicate the various structures.

    All of the critical functions of the B-Scan are calculated in the same manner as in the predicate device, B-Scan Plus. The software algorithms for clinically critical functions remain the same as in the predicate device. However, the user interface and the workflow of B-Scan have enhancement to support cybersecurity implementation.

    Both the subject device and predicate device are compatible with the Connect Software (K070943, K123349) and 4Sight (K152573). The software improvements in Connect were focused on enhancing features that optimize integration with the personal computer's processing, data storage, display, and printing capabilities.

    The energy source for the B-Scan is USB power as in the predicate device, B-Scan Plus.

    The software utilized on both the Connect and 4Sight platforms is fundamentally identical in core clinical functions, including image scanning, rendering, IOL calculations, data storage, and report formatting. Additionally, the key features within the B-Scan module do not differ significantly between the two systems, nor do they make an impact on the established clinical workflow.

    Track 1 is being followed for this 510(k) submission.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and the study details for the B-Scan Ultrasonic Imaging System, based on the provided FDA 510(k) clearance letter:

    1. Table of Acceptance Criteria and Reported Device Performance

    The 510(k) summary primarily focuses on demonstrating substantial equivalence to a predicate device rather than explicitly stating pre-defined "acceptance criteria" for a novel device performance. However, we can infer acceptance criteria from the comparison table (Table 2) and the performance data section, where the subject device's performance is either "Same" or "SE" (Substantially Equivalent) to the predicate, or explicitly lists performance metrics.

    For quantitative metrics, the "acceptance criteria" for the subject device can be interpreted as performing comparably or within acceptable limits relative to the predicate device, or meeting specific new specifications.

    ParameterAcceptance Criteria (Inferred/Stated)Reported Device Performance (B-Scan)Remarks/Proof
    Clinical Accuracy (Line)±3% (for 60mm Depth Setting)12MHz: 60mm Depth Setting Clinical Accuracy: ±3%Bench Test: Physical Accuracy and Range Test
    Accuracy Range (Line)60 mm (for 60mm Depth Setting)12MHz: 60mm Depth Setting Accuracy Range: 60 mmBench Test: Physical Accuracy and Range Test
    Clinical Accuracy (Area)±15% (for 60mm Depth Setting)12MHz: 60mm Depth Setting Clinical Accuracy: ±15%Bench Test: Physical Accuracy and Range Test
    Accuracy Range (Area)60 mm (for 60mm Depth Setting)12MHz: 60mm Depth Setting Accuracy Range: 60 mmBench Test: Physical Accuracy and Range Test
    Image Preview TimeDisplayed within 2 seconds of pressing probe buttonImage preview is displayed within 2 seconds of pressing probe button (average time recorded across 5 probes).Bench Test: The specific bench test for this is not named explicitly, but is mentioned within the comparison table as part of the performance metrics.
    Cleaning & DisinfectionValidation per procedures in Instruction for UseReprocessing validation test was conducted on the proposed device.Reprocessing Validation Test
    BiocompatibilityMeet requirements of ISO 10993 series (Cytotoxicity, Ocular Irritation, Skin Sensitization)The proposed device has been tested and met the requirements according to the ISO 10993 series standard for Biocompatibility.Biocompatibility Testing
    Software V&VDocumentation provided as recommended by FDA guidanceSoftware verification and validation testing were conducted, and documentation was provided.Software Verification and Validation Testing
    Cybersecurity ComplianceDocumentation provided in accordance with FDA guidanceCybersecurity compliance was implemented, and documentation was provided.Cybersecurity Implementation and Documentation
    Electrical Safety & EMCMeet requirements of IEC 60601-1, IEC 60601-1-2The proposed device has been tested and met the requirements.Thermal, mechanical, and electrical safety and electromagnetic compatibility testing
    Mechanical/Thermal DurabilityMeet design specifications (implied)Accelerated Thermal Cycling Test; Plastic Component UV Assessment; Transit Performance Test; USB cable Pull Test; B-Scan Integrated Life Testing Verification ReportBench Tests (listed)
    Button ActuationMeet design specifications (implied)Button actuator Validation TestBench Test: Button actuator Validation Test

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

    The document does not explicitly state a sample size for patients or images used in any clinical or test set. The performance data mostly refers to bench testing and validation against standards.

    • The only mention of a "sample" related to performance is "average time recorded across 5 probes" for the image preview time. This refers to hardware units, not patient data.
    • Data Provenance: Not applicable, as no external data set or clinical study on patients is described beyond bench tests. The focus is on device specifications and in-house validation.

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

    Not applicable. The submission does not describe a study involving expert readers establishing ground truth for a test set of images for diagnostic performance evaluation. The "Performance" section outlines bench tests and compliance with recognized standards.

    4. Adjudication Method for the Test Set

    Not applicable. Since there's no mention of a clinical test set requiring human expert review to establish ground truth, there is no adjudication method described.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    No. The document does not describe a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it quantify improvement in human readers with AI assistance. The device is purely an imaging system, and there is no mention of AI assistance for image interpretation.

    6. Standalone (Algorithm Only Without Human-in-the-loop Performance)

    The device described is an "B-Scan Ultrasonic Imaging System," which is a diagnostic tool that produces images for human interpretation. It does not contain an AI algorithm for standalone diagnostic performance. Its performance is related to image acquisition parameters, accuracy of measurements, and adherence to safety/design standards.

    7. Type of Ground Truth Used

    For the quantitative performance claims (e.g., Clinical Accuracy Line/Area), the ground truth was established by physical measurements against known standards or calibrated references during bench testing ("Physical Accuracy and Range Test"). For other aspects, the ground truth is adherence to technical specifications, safety standards, and validated manufacturing/reprocessing procedures.

    8. Sample Size for the Training Set

    Not applicable. This device is an ultrasound imaging system, not an AI-driven diagnostic algorithm that requires a "training set" of data in the typical machine learning sense. The software aspects mentioned are primarily for device control, image rendering, data storage, and report formatting, enhanced for cybersecurity and usability – not for learning from data to perform a diagnostic task.

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

    Not applicable, as there is no training set mentioned for an AI algorithm.

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    K Number
    K070943
    Device Name
    B-SCAN PLUS
    Date Cleared
    2007-04-19

    (15 days)

    Product Code
    Regulation Number
    892.1560
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The instrument is used for imaging the internal structure of the eye including the opaque media and posterior pathology for the purpose of diagnosing pathological or traumatic conditions in the eye.

    Device Description

    The B-Scan Plus device is designed as an ultrasound B- Scan which uses pulsed echo ultrasound to image the internal structure of the eye. It utilizes an eye-contact probe to generate and receive the ultrasound pulses, and provides graphic display of returning pulse echoes to image these structures.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and study information for the B-Scan Plus device based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The provided text does not explicitly state specific acceptance criteria in terms of numerical performance metrics (e.g., sensitivity, specificity, accuracy, resolution). Instead, the 510(k) summary focuses on demonstrating substantial equivalence to a predicate device (Advent A/B System K960765).

    The device performance is described functionally rather than parametrically.

    Acceptance Criterion (Implicit)Reported Device Performance
    Ability to image internal structure of the eye using pulsed echo ultrasound."The B-Scan Plus device is designed as an ultrasound B-Scan which uses pulsed echo ultrasound to image the internal structure of the eye. It utilizes an eye-contact probe to generate and receive the ultrasound pulses, and provides graphic display of returning pulse echoes to image these structures."
    Functional equivalence to predicate device (Advent A/B System K960765).The FDA determined the device is "substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices." This implies it meets the same functional and safety performance expectations.
    Intended Use: Diagnosing pathological or traumatic conditions in the eye."The instrument is used for imaging the internal structure of the eye including the opaque media and posterior pathology for the purpose of diagnosing pathological or traumatic conditions in the eye."

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

    The provided 510(k) summary does not contain information about a specific test set, its sample size, or data provenance (e.g., country of origin, retrospective/prospective).

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

    The provided 510(k) summary does not contain information about experts used to establish ground truth or their qualifications. As there's no mention of a clinical test set in this document, this information would not be present.

    4. Adjudication Method for the Test Set

    The provided 510(k) summary does not contain information about an adjudication method for a test set.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    The provided 510(k) summary does not mention or describe a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. This type of study would typically be conducted to evaluate the impact of an AI-assisted device on human reader performance, which doesn't seem to be the focus of this 510(k).

    6. Standalone (Algorithm Only) Performance Study

    The provided 510(k) summary does not describe a standalone (algorithm only) performance study. The device is a B-Scan ultrasound system, which inherently involves human operation and interpretation of images. The concept of a "standalone algorithm" doesn't directly apply in the same way as it would for, say, an AI-powered image analysis software.

    7. Type of Ground Truth Used

    Given the lack of a detailed performance study in the document, there's no explicit mention of the type of ground truth used. For a B-scan ultrasound system, ground truth in clinical validation would typically involve:

    • Clinical Diagnosis: Based on a combination of patient history, physical examination, and other imaging modalities (e.g., MRI, CT, other specialized ophthalmic tests).
    • Surgical Confirmation: If pathology is surgically removed.
    • Histopathology: Microscopic examination of tissue samples.
    • Expert Consensus: Agreement among multiple, highly qualified clinicians (ophthalmologists) on the diagnosis based on the full clinical picture.

    8. Sample Size for the Training Set

    The provided 510(k) summary does not mention a training set or its sample size. The B-Scan Plus is a traditional medical imaging device, not an AI/ML-driven device that typically requires a discrete training set in the same manner.

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

    Since there is no mention of a training set, the document does not describe how ground truth for a training set was established.


    Summary of Study Information Gaps:

    It's important to note that the provided document is a 510(k) summary, which often focuses on demonstrating substantial equivalence to a predicate device rather than presenting extensive clinical trial data with detailed performance metrics. For devices like the B-Scan Plus, the primary means of demonstrating safety and effectiveness relied on showing that its technological characteristics and indications for use were similar to a legally marketed predicate device, and that any differences did not raise new questions of safety or effectiveness. Therefore, many of the detailed study parameters typically associated with AI/ML device submissions are not present here.

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