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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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The MSI is a handheld imaging tool that allows clinicians diagnosing and treating skin wounds to:
· View and digitally record images of a wound.
· Measure and digitally record the size of a wound.

• · View and digitally record images of fluorescence emitted from a wound when exposed to an excitation light.
  · View and digitally record thermal images of a wound.
  The MSI does not diagnose or treat skin wounds.

The MSI Kit includes the following: the MSI, a Universal Serial Bus (USB-C) cable, a wall adapter, and a carrying case.
The MSI captures and processes optical data of an imaged wound. The MSI consists of three imaging modalities: white light, autofluorescence and thermal. The MSI has 395nm excitation LEDs for autofluorescence imaging, a sensor for measuring distance to the wound, and a thermal sensor for capturing temperature gradients.
The MSI is powered by an onboard rechargeable battery and has a USB-C connection for uploading images to a computer. The manual provides users of the MSI with detailed instructions for proper use, maintenance, and storage.

The provided text outlines the general safety and performance testing conducted for the Multispectral Imager Kit (MSI Kit) to establish its substantial equivalence to predicate devices, but it does not contain the specific acceptance criteria or detailed results of a study demonstrating the device meets those criteria.

However, based on the information provided, here's a breakdown of what can be inferred and what is missing:

Acceptance Criteria and Reported Device Performance:

The document lists various performance tests, implying certain acceptance criteria for each, but the specific numerical targets or thresholds are not provided. The conclusion statement indicates that the clinical and non-clinical data "indicate that the MSI Kit is as safe and effective as the predicate devices," which serves as a general statement of meeting underlying acceptance criteria for equivalence.

Missing information: The actual acceptance criteria (e.g., minimum accuracy for wound measurement, specific signal-to-noise ratio requirements for fluorescence imaging) and the quantitative results from the study demonstrating the device's performance against these criteria are not detailed in the provided text.

Detailed Information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

As noted above, specific acceptance criteria and detailed quantitative results are not provided in the document. The document lists the types of tests performed and generally states that the device's performance was evaluated, leading to a conclusion of safety and effectiveness comparable to predicate devices.

2. Sample size used for the test set and the data provenance

• Test Set Sample Size: The document does not specify the sample size for any of the performance tests, including the clinical study.
• Data Provenance:
  • Clinical Study: "A clinical study was conducted under anticipated conditions with anticipated users." The location (country of origin) is not specified, nor is whether it was retrospective or prospective. Given the phrasing "conducted," it implies a prospective study.
  • Bench Studies: Performed to verify various performance aspects. No information on data provenance other than being "bench studies."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document states that the MSI is "a handheld imaging tool that allows clinicians diagnosing and treating skin wounds to: ... View and digitally record images of fluorescence emitted from a wound when exposed to an excitation light," and that it "does not diagnose or treat skin wounds." The clinical study evaluated the "ability of the MSI to detect autofluorescence signals from tissues or structures consistent with the indications for use."

This implies that the assessment of autofluorescence signals in wounds would typically require clinical experts. However, the document does not specify the number of experts or their qualifications used to establish ground truth for any test set.

4. Adjudication method for the test set

The document does not specify any adjudication method for establishing ground truth in the clinical study or any other performance testing.

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

The document does not mention a multi-reader, multi-case (MRMC) comparative effectiveness study, nor does it refer to AI assistance or human reader improvement with AI. The device is described as an "imaging tool" for clinicians, not as an AI-powered diagnostic aid that assists in interpretation.

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

The device description focuses on its imaging capabilities and the output of images (white light, fluorescence, thermal) for clinician evaluation. None of the performance data sections suggest a standalone algorithm-only performance assessment where the device makes interpretations without human involvement. The indications for use specifically state it "does not diagnose or treat skin wounds" and provides images for clinicians.

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

The document does not explicitly state the type of ground truth used in the clinical study. For "autofluorescence signals from tissues or structures consistent with the indications for use," the ground truth would likely involve a clinical assessment by wound care specialists or potentially correlated with wound characteristics that are known to exhibit certain autofluorescence, but this is not specified.

8. The sample size for the training set

The document does not mention a training set or its sample size. This suggests that the device's functionality does not rely on a machine learning model that requires a labeled training dataset in the way a diagnostic AI would. The device's operation, as described, appears to be based on capturing and processing optical and thermal data rather than learning from data.

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

Since no training set is mentioned, there is no information on how ground truth for a training set was established.

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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:

• SoC-guided sample: 87.2% (95% CI: 77.7%, 93.7%)
• FL-guided sample: 98.7% (95% CI: 93.06%, 99.97%)
  P-value: P = 0.012 (FL-guided sampling was significantly more sensitive)

Ability to detect a higher number of bacterial species:

• Mean number of species by FL-guided Biopsy: 3.026 (SD 1.667)
• Mean number of species by SoC-guided Biopsy: 2.231 (SD 1.528)
• Difference: 0.795 (SD 1.804)
  P-value: P 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.

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The MolecuLightDX 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 MolecuLightDX device should not be used to rule-out the presence of bacteria in a wound.

The MolecuLightDX does not diagnose or treat skin wounds.

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

This document is a 510(k) summary for the MolecuLightDX device. It describes non-clinical testing performed on the device but does not contain information about clinical studies or acceptance criteria for identifying bacterial loads >10^4 CFU per gram. The summary focuses on established equivalence to a predicate device (MolecuLight i:X K191371) based on similar technological characteristics and compliance with electrical safety and software validation standards, rather than direct performance metrics against clinical acceptance criteria for bacterial load detection.

Therefore, the requested information regarding acceptance criteria and a study proving the device meets those criteria, specifically concerning the identification of bacterial loads, cannot be fully provided from the given text.

However, based on the information provided, here's what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily discusses compliance with safety and technical standards rather than specific clinical performance acceptance criteria for bacterial load detection. The key performance claim related to its indication for use is: "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."

While this is an indication of efficacy, the document does not specify quantitative acceptance criteria (e.g., sensitivity, specificity, or AUC thresholds) for this "increased likelihood" or present a study showing the MolecuLightDX device itself met such criteria. Instead, it refers to its predecessor's demonstrated capability.

2. Sample size used for the test set and the data provenance:

Not provided in this document for the MolecuLightDX's bacterial load identification capability. The non-clinical testing mentioned includes:

• Standards Compliance Testing
• Software Verification and Validation
• System Verification and Validation
• Accuracy and Inter/Intra Reader Variability Testing of Wound Measurement Function
• Packaging and Transport validation

These tests do not involve clinical test sets for bacterial load identification. The effectiveness claim for bacterial load identification references earlier work/evidence from the predicate device, implicitly assuming the newer device maintains this capability due to similar technology.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

Not provided in this document.

4. Adjudication method for the test set:

Not provided in this document.

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:

Not provided in this document. The device is a "handheld imaging tool" and not an AI-driven diagnostic algorithm in the typical sense that would necessitate an MRMC comparative effectiveness study for "AI vs without AI assistance". Its primary function is to enable visualization of fluorescence which clinicians then interpret.

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

Not applicable. The device is explicitly described as a "handheld imaging tool that allows clinicians... to view and digitally record images... The fluorescence image, when used in combination with clinical signs and symptoms, has been shown to increase the likelihood that clinicians can identify wounds..." This indicates a human-in-the-loop system.

7. The type of ground truth used:

Not explicitly stated for the MolecuLightDX in this document regarding bacterial load. However, the indication for use refers to "bacterial loads >10^4 CFU per gram," which implies quantitative microbiology (CFU per gram) as the ground truth method in the referenced studies from which the claim of "increased likelihood" originated (likely from the predicate device's clearance).

8. The sample size for the training set:

Not applicable, as this document does not describe a machine learning algorithm requiring a training set for the bacterial load identification claim. The device is an imaging tool.

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

Not applicable.

Summary based on available information:

The provided document (a 510(k) summary) focuses on demonstrating substantial equivalence to a predicate device (MolecuLight i:X K191371) through non-clinical testing, regulatory compliance, and comparison of technological characteristics. It does not detail a specific clinical study for MolecuLightDX to establish performance against acceptance criteria for identifying bacterial loads. Instead, it leverages the known efficacy claim from its predicate device for its indication of use, implying that the MolecuLightDX, being technologically similar, shares this established capability. The "increased likelihood" claim for identifying bacterial loads >10^4 CFU per gram is presented as a previously established benefit from the predicate device's performance.

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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 >104 CFU per grams 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 imaging in wounds and surrounding healthy skin of patients as well as wound area measurements.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) summary for the MolecuLight i:X:

The MolecuLight i:X device is an autofluorescence detection device for general surgery and dermatological use. The 510(k) summary details a modification to the device's labeling to clarify the relationship between cyan fluorescence and the increased likelihood of Pseudomonas aeruginosa bacterial loads. The study's purpose is to demonstrate that this additional labeling statement does not raise new questions of safety or efficacy and is supported by existing clinical data.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly tied to the performance metrics of the device in identifying bacterial loads, specifically Pseudomonas aeruginosa and Total Bacterial Load (TBL), as established in the original K191371 clearance. The current submission's goal is to demonstrate that the expanded labeling around cyan fluorescence's association with P. aeruginosa is supported by the data and does not alter the previous safety and effectiveness profile.

The performance is reported in terms of sensitivity, specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), and Likelihood Ratio for different fluorescence signatures (Cyan, Red, Red or Cyan) in detecting bacterial loads.

Note: The document states "The additional labeling statement does not raise different questions of safety or efficacy. Retrospective analysis has demonstrated the safety and effectiveness of MolecuLight i:X with regards to the additional labeling statement." This implies that the acceptance criteria are met if the performance metrics continue to support the device's utility in identifying bacterial loads and the new labeling is consistent with the observed data.

2. Sample Size and Data Provenance

• Sample Size for Test Set: Data from 350 patients were retrospectively analyzed.
• Data Provenance: The document does not explicitly state the country of origin but refers to "retrospective analysis" of existing clinical study data. Given MolecuLight Inc. is based in Toronto, Canada, and the clinical study was "reported in support of K191371", it is likely the data was collected in either Canada or the US, or potentially a multi-site international study. The study was retrospective.

3. Number of Experts and their Qualifications

The document does not specify the number of experts used to establish the ground truth for the test set, nor does it explicitly state their qualifications. The interpretation of "fluorescence image, when used in combination with clinical signs and symptoms" suggests that the ground truth was established by clinicians based on the convergence of factors, potentially including microbiological culture results (as indicated by CFU/g measurements).

4. Adjudication Method for the Test Set

The document does not describe any adjudication method for the test set. Given that the analysis is "retrospective analysis" of existing clinical study data, the ground truth was likely established as part of the original study design.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed for this 510(k) submission. This submission is a "Real-World Data" (retrospective analysis) supporting a labeling change for a previously cleared device, not a new device clearance or a comparative effectiveness study with human readers. The document states: "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 grams as compared to examination of clinical signs and symptoms alone." This sentence refers to a finding from the original K191371 clearance, not a new MRMC study in this submission.

6. Standalone (Algorithm Only) Performance

This device, the MolecuLight i:X, is an imaging tool used by clinicians to view and record images of fluorescence. It is not an AI algorithm that generates a diagnosis or interpretation autonomously. Therefore, a standalone (algorithm only) performance study was not applicable or performed in the context of this 510(k). The device provides visual information (fluorescence images) that clinicians interpret in conjunction with clinical signs and symptoms.

7. Type of Ground Truth Used

The ground truth for the test set appears to be microbiological culture results (bacterial loads measured in CFU/g) combined with clinical assessment. The specific phrases "identify wounds containing bacterial loads >10^4 CFU per grams" and "Pseudomonas aeruginosa at Species Specific Levels ≥ 10^4 CFU/q" clearly indicate that quantitative bacterial culture was the definitive ground truth for bacterial presence and load.

8. Sample Size for the Training Set

The document does not describe a training set in the context of an AI/algorithm. The "study" described is a retrospective analysis of previously collected clinical data to support a labeling claim for a medical device. If there was any machine learning involved (which is not directly implied for this device's function as an imaging tool), that would have been part of the original K191371 submission and is not detailed here.

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

As no training set (in the context of an AI/ML algorithm) is described, this question is not applicable based on the provided document. The device's function described (capturing and displaying fluorescence) implies it is a viewing tool, not an AI-powered diagnostic algorithm requiring a training phase for its output beyond the initial development of its optical and imaging capabilities.

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The MolecuLight i:X is a handheld imaging tool that allows clinicians diagnosing and treating skin wounds, at the point of care, to

• View and digitally record images of a wound, (i)
• Measure and digitally record the size of a wound, and (ii)
• View and digitally record images of fluorescence emitted from a wound when exposed to an excitation light. (iii)

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 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 imaging in wounds and surrounding healthy skin of patients as well as wound area measurements.

Here's a breakdown of the acceptance criteria and the study that proves the MolecuLight i:X device meets them, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The core clinical claim for the MolecuLight i:X related to bacterial identification is: "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."

While the document doesn't explicitly state quantitative acceptance criteria in the "we will achieve X performance" format, the demonstrated performance serves as the evidence for meeting their stated claim. The crucial part of the performance is the improvement in identifying wounds with relevant bacterial loads.

Acceptance Criteria (Implied by Clinical Claim and Study Results)

*   Microbiology Negative (10^4 CFU/g) was "quantitative microbiological analysis," which is a lab-based, objective method, not dependent on expert consensus.

4. Adjudication Method for the Test Set

• The document does not describe an adjudication method for the clinical evaluation of CSS or the interpretation of MolecuLight i:X images. It compares these clinical assessments directly against the quantitative microbiological analysis. This suggests that individual clinicians' interpretations were the data points, rather than a consensus interpretation.

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

• A formal MRMC study is not explicitly mentioned as having been performed. The study evaluates the likelihood that clinicians can identify wounds, comparing performance with and without the device. While it involves multiple clinicians, it's presented as a direct comparison of the combined CSS+iX approach versus CSS alone, rather than a statistical comparison of reader performance improvement.
• Effect Size:
  • The sensitivity for identifying high bacterial loads increased from 15.33% (CSS alone) to 60.98% (CSS + iX). This is a substantial increase, making the device significantly more likely to flag relevant wounds.
  • The specificity decreased from 93.65% (CSS alone) to 84.13% (CSS + iX). This indicates a trade-off where more wounds were incorrectly identified as having high bacterial loads with the device, but the report explicitly states this increase in false positives was "10^4 CFU per gram). This is an objective and laboratory-confirmed ground truth, considered a strong reference standard for bacterial burden.

8. Sample Size for the Training Set

• The document does not specify a separate training set or its size. This is typical for a medical device that provides direct imaging for human interpretation, rather than a machine learning algorithm that is "trained" on data. The clinical study described here functions as the pivotal performance validation.

9. How Ground Truth for the Training Set was Established

• As no separate training set or AI/ML training is indicated, this point is not applicable. The ground truth for the clinical study was established by quantitative microbiological analysis of wound samples.

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