Search Results

The MolecuLight i:X 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 >10^4 CFU per gram) as compared to examination of clinical signs and symptoms alone. The MolecuLight i:X device should not be used to rule-out the presence of bacteria in a wound.

The MolecuLight i:X does not diagnose or treat skin wounds.

The MolecuLight i:X Imaging Device is a handheld medical imaging device comprised of a high-resolution color LCD display and touch-sensitive screen with integrated optical and microelectronic components. MolecuLight i:X uses its patented technology to enable real-time standard digital imaging and fluorescence (FL) imaging in wounds and surrounding healthy skin of patients as well as wound area measurements.

The MolecuLight i:X is a handheld imaging tool that helps clinicians identify wounds containing elevated bacterial loads. The provided text outlines the acceptance criteria and the study that supports the device's claims.

1. Table of Acceptance Criteria and Reported Device Performance

The provided documentation does not explicitly state "acceptance criteria" as a set of predefined thresholds that the device had to meet for clearance. Instead, it presents performance metrics from a clinical study, which implicitly serve as evidence for addressing the added labeling claims. The key performance metrics are related to the device's ability to guide wound sampling for detecting bacterial burden.

Derived Acceptance Criteria (based on the device's claims and study outcomes) and Reported Device Performance:

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

• Sample Size for Clinical Test Set: Data from a post hoc retrospective analysis of 78 patients were analyzed. The analysis specifically looked at "all wounds that had two samples obtained in the study."
• Data Provenance: The document does not explicitly state the country of origin. The study was a retrospective analysis.

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

The document does not specify the number or qualifications of experts used to establish the ground truth for the clinical test set. The ground truth for bacterial load was established through "wound sampling" implying microbiological culture results (CFU/g).

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method for the clinical test set. Given that the ground truth appears to be based on microbiological culture results from wound samples, an adjudication process by experts, as might be seen for image interpretation consensus, would not be directly applicable for this type of ground truth.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study, where human readers interpret images with and without AI assistance, was not explicitly described in the provided text. The clinical performance testing focused on comparing the effectiveness of FL-guided wound sampling versus Standard of Care (SoC) guided sampling to detect bacterial burden, rather than a direct comparison of human reader performance with and without AI assistance in image interpretation. The device's role is presented as a tool to guide sampling, not as an AI for image interpretation by clinicians.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The provided information focuses on the device's clinical utility in guiding sampling with a clinician in the loop. While the device itself processes images to show fluorescence, its performance is evaluated in the context of improving a clinical procedure (wound sampling), not as a standalone diagnostic algorithm for automated interpretation. The non-clinical testing mentions a "custom algorithm" to detect red fluorescence, which implies standalone analytical capability, but this is distinct from clinical diagnostic performance.

7. The Type of Ground Truth Used

• Clinical Performance Testing: The ground truth for bacterial load was established by microbiological culture results from wound samples, quantified as Colony Forming Units (CFU) per gram (CFU/g). Specifically, "bacterial loads >10^4 CFU per gram" were the key threshold. Pathogen identification was also a part of the ground truth.
• Non-Clinical Testing: The ground truth for demonstrating red fluorescence production for specific bacterial species was based on sub-culturing on Porphyrin Test Agar (PTA) and direct observation of fluorescence using the MolecuLight i:X.

8. The Sample Size for the Training Set

The document primarily discusses a retrospective analysis for clinical validation and in-vitro testing. It does not mention a separate training set size for any specific AI/algorithm development, as the device's core functionality appears to be based on known autofluorescence properties of bacteria rather than a deep learning model trained on large datasets for complex pattern recognition. The study mentioned ([K191371](https://510k.innolitics.com/search/K191371)) was used to support subsequent claims, implying this may have provided data for initial claims.

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

As no explicit training set for a machine learning algorithm is detailed, the method for establishing ground truth for such a set is not provided. The non-clinical testing described involves culturing specific bacterial species to verify their autofluorescent properties, which would serve as a 'ground truth' for the physical principle the device leverages.

Ask a specific question about this device