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The SnapshotGLO is a handheld imaging tool that allows clinicians diagnosing and treating skin wounds, at the point of care, to (i) View and digitally record images of a wound, (ii) Measure and digitally record the size of a wound, and (iii) View and digitally record images of fluorescence emitted from a wound when exposed to an excitation light. The fluorescence image, when used in combination with clinical signs and symptoms, has been shown to increase the likelihood that clinicians can identify wounds containing bacterial loads >104 CFU per gram as compared to examination of clinical signs and symptoms alone. The SnapshotGLO device should not be used to rule-out the presence of bacteria in a wound. The SnapshotGLO does not diagnose or treat skin wounds.

SnapshotGLO is a medical device that operates like a camera. It is a point-of-care, wound imaging device. This device is a non-contact imaging device wherein the wound images are captured from a height of ~12 cm using 395 nm LEDs and a white LED to produce a resultant fluorescence image that aids in visualising the bacteria on the wound and a colour-based "RGB" image or clinical image. Resultant images are viewed on the 7-inch touchscreen display. SnapshotGLO is based on autofluorescence imaging technology and uses native fluorescence of bacteria to determine the presence of bacterial bioburden and displays a two-dimensional, colour-coded highlight of bioburden presence on the wounds. SnapshotGLO is a handheld imaging tool that allows clinicians diagnosing, monitoring and treating skin wounds at the point of care with the help of the following features: . View and digitally record images of a wound, . Measure and digitally record the size of a wound, and View and digitally record images of fluorescence emitted from a wound when exposed to an ● excitation light SnapshotGLO consists of: - SnapshotGLO device - Medical grade adapter - User Manual - Quick Start Guide ● SnapshotGLO is intended for wound care applications as an adjunct tool that uses autofluorescence to detect tissues or structures. The fluorescence image, when used in combination with clinical signs and symptoms, has been shown to increase the likelihood that clinicians can identify wounds containing high bacteria bioburden compared to clinical symptoms alone. SnapshotGLO should not be used to rule-out the presence of bacteria in a wound. This device is not intended to provide a diagnosis.

The provided text is a 510(k) summary for the SnapshotGLO (KB100) device, aiming to demonstrate its substantial equivalence to the MolecuLightDX as a predicate device. While it details the device's function and provides some study information, it does not explicitly state "acceptance criteria" in a tabulated format alongside "reported device performance." Instead, it discusses the outcomes of non-clinical and clinical studies that support the device's equivalence and performance.

Based on the information provided, here's an attempt to structure the response according to your request, extracting the closest equivalents to "acceptance criteria" and "reported performance" from the study descriptions.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly define quantitative acceptance criteria for the clinical study. However, the non-clinical tests imply an acceptance criterion of "comparable performance" or "substantially equivalent performance" to the predicate device. For the clinical study, the acceptance was based on showing "improved accuracy" compared to the predicate device when used with clinical signs and symptoms.

2. Sample Size and Data Provenance

• Test Set Sample Size:
  • Clinical Study: 40 patients.
  • Non-clinical Studies: Not explicitly stated, but conducted on "culture plates" and "wound dimensions."
• Data Provenance: The document does not specify the country of origin for the clinical study. The clinical study was described as retrospective.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Two clinical evaluators were involved in the retrospective clinical study.
• Qualifications: Not explicitly stated in the document.

4. Adjudication Method for the Test Set

The document states "This blinded assessment" for the clinical study, indicating that the evaluators were blinded to some information, but it does not describe a specific adjudication method (e.g., 2+1, 3+1 consensus).

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

• Was an MRMC study done? A clinical study comparing the SnapshotGLO and the predicate device was done, involving two clinical evaluators. While it's a comparative study with multiple readers, the format described does not fully align with a typical MRMC study designed to assess reader improvement with AI assistance. It rather compares the device's performance (with CSS) against the predicate device's performance (with CSS) validated against culture.
• Effect Size of Human Readers Improvement with AI vs. Without AI Assistance: The study compared SnapshotGLO + CSS versus MolecuLightDX + CSS versus CSS alone (implicit, as the basis for comparison), all validated against culture results. It demonstrated:
  • SnapshotGLO + CSS accuracy: 75-82.5%
  • MolecuLightDX + CSS accuracy: 52.5-65%
  • The phrase "increase the likelihood that clinicians can identify wounds containing bacterial loads >10^4 CFU per gram as compared to examination of clinical signs and symptoms alone" (from the Indications for Use) suggests that the device, when combined with CSS, improves performance over CSS alone. The specific "effect size" of improvement of human readers with AI vs. without AI assistance (meaning AI as an added tool for human readers) is not directly quantified as a comparative value in terms of reader gain. The comparison shown is between two different devices (both of which are imaging tools that provide additional information to clinicians) when used with CSS, against culture results.

6. Standalone (Algorithm Only) Performance

The document does not report on standalone (algorithm only without human-in-the-loop performance). The indications for use consistently state that the fluorescence image is to be used "in combination with clinical signs and symptoms."

7. Type of Ground Truth Used

• Clinical Study: The ground truth for identifying wounds with bacterial loads >10^4 CFU per gram was established using culture results.
• Non-clinical Studies: The ground truth for bacterial fluorescence detection was based on bacterial presence in in vitro culture plates. For wound dimensions, it was likely based on known or carefully measured dimensions.

8. Sample Size for the Training Set

The document is a 510(k) summary for a medical device and does not provide information regarding the training set sample size as it primarily focuses on the device's performance for regulatory submission. This device description points to an "autofluorescence imaging technology" for directly visualizing bacterial compounds, rather than a machine learning algorithm that requires a training set. If there is an AI component for image processing or interpretation not explicitly detailed, the training set information is not included in this document.

9. How Ground Truth for Training Set Was Established

As no training set is discussed concerning an AI/ML algorithm, no information is provided on how its ground truth was established. The device utilizes physical principles of autofluorescence.

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