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510(k) Data Aggregation
(202 days)
Kent Imaging Inc.
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.
| Criterion Type | Acceptance Criterion (Implicit/Derived) | Reported Device Performance (SnapshotGLO) |
|---|---|---|
| Non-clinical - Bacterial Fluorescence Detection | Substantially equivalent detection of red fluorescence from porphyrin-producing bacteria (mono- and bi-microbial, biofilms) compared to predicate device. | Provided robust evidence that SnapshotGLO is substantially equivalent to MolecuLightDX in detecting bacterial fluorescence. Confirmed effectiveness for identifying porphyrin-producing bacteria and biofilms. |
| Non-clinical - Wound Dimensions Measurement | Comparable performance in manual wound detection modes to the predicate device, demonstrating agreement in measurement accuracy and repeatability. | Performs comparably to MolecuLightDX in manual wound detection modes, with strong agreement in measurement accuracy and repeatability. Supports claim of substantial equivalence. |
| Clinical - Bacterial Load Identification | When used with clinical signs and symptoms (CSS), demonstrated improved accuracy in identifying wounds with bacterial loads >10^4 CFU per gram compared to predicate device alone. | When used in conjunction with CSS, showed over 88% positive percent agreement and provided improved accuracy (75-82.5%) compared to MolecuLightDX (52.5-65%) when validated against culture results for identifying wounds with bacterial loads >10^4 CFU per gram. |
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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(29 days)
Kent Imaging Inc
SnapshotNIR (KD205) is intended for use by healthcare professionals as a non-invasive tissue oxygenation measurement system that reports an approximate value of:
- oxygen saturation (St02),
- relative oxyhemogoblin level (Hb02), and
- relative deoxyhemoglobin (Hb) level
in superficial tissue. SnapshotNIR (KD205) displays two-dimensional color-coded images of tissue oxygenation of the scanned surface and reports multispectral tissue oxygenation measurements for selected tissue regions.
SnapshotNIR (KD205) is indicated for use to determine oxygenation levels in superficial tissues.
SnapshotNIR (KD205) is a medical device that operates like a camera. The SnapshotNIR device is completely non-contact, capturing images from 12 inches away from the patient or other imaging field-ofviews. The device uses six near-infrared wavelengths of light and white light emitting diodes (LEDs) to produce a resultant tissue oxygenation image and a colour-based "RGB" or clinical image, respectfully, that can be viewed on the touchscreen display.
SnapshotNIR is based on multispectral imaging technology and performs spectral analysis at each pixel to determine the approximate values of tissue oxygen saturation (StO2), oxyhemoglobin levels (HbO2), and deoxyhemoglobin levels (Hb) in superficial tissues and displays a two-dimensional, color-coded image of the tissue oxygen saturation (StO2).
SnapshotNIR consists of:
- · SnapshotNIR
- · Recharger
- · User Guide
- · Quick Start Guide
- · Sterile Drape (Optional)
The intended use and user interaction remained the same in the new model (KD205). The user will notice that the modified device no longer requires the user to take a calibration image prior to image capture. SnapshotNIR now uses an embedded computer module and a touchscreen LCD. Additional minor form factor changes were made on the new model (KD205) to accommodate the hardware change. With respect to the software used by SnapshotNIR, the predicate and new model (KD205) operate similarly.
This document, K240601, is a 510(k) Premarket Notification from the FDA regarding the Kent Imaging SnapshotNIR model KD205. It's a clearance letter, not a study report or a detailed technical submission. Therefore, it does not contain the information requested regarding acceptance criteria and performance studies in the level of detail typically found in a clinical study report or a more comprehensive technical submission to the FDA.
Specifically, the document states:
- "Nonclinical engineering-based tests (e.g., IEC 60601-1-2, etc) among other performance bench tests support conclusions that the KD205 device is safe for use with a low risk of adverse events occurring during the intended use scenarios."
- "These tests and findings are analogous to those conducted on the predicate KD204 SnapshotNIR device and demonstrate that the KD205 device is similarly safe, and effective compared to a current legally marketed device."
- "In a sub-analysis of the pre-clinical dataset, the KD205 device demonstrated no significant differences (derived via 2-way ANOVA models) in STO2 across the ischemia-reperfusion test when comparing cohorts of low versus high tissue scattering effects."
While it mentions "pre-clinical dataset" and "tests and findings," it does not provide any specific acceptance criteria, reported performance values, sample sizes, provenance of data, expert qualifications, or details about MRMC studies, standalone performance studies, or ground truth establishment. The purpose of this 510(k) summary is to establish substantial equivalence to a predicate device, not to detail the full performance study results.
Therefore, I cannot populate the requested table or answer most of the questions based solely on the provided text. The document focuses on the conclusion of substantial equivalence rather than the raw data and detailed methodology of the performance studies conducted.
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(184 days)
KENT IMAGING INC.
The Kent Camera is intended for use by healthcare professionals as a non-invasive tissue oxygenation measurement system that reports an approximate value of:
- oxygen saturation (StO2),
- relative oxyhemoglobin level (HbO2), and
- relative deoxyhemoglobin (Hb) level
in superficial tissue. The Kent Camera displays two-dimensional color-coded images of tissue oxygenation of the scanned surface and reports multispectral tissue oxygenation measurements for selected tissue regions.
The Kent Camera is indicated for use to determine oxygenation levels in superficial tissues.
The Kent Camera is a handheld digital camera based on multispectral imaging technology and performs spectral analysis at each point in a two-dimensional scanned area producing an image displaying information derived from the analysis. The Kent Camera determines the approximate values of oxygen saturation (S.O2), relative oxyhemoglobin (HbO2) and deoxyhemoglobin levels (Hb) in superficial tissues and displays a two-dimensional, color-coded image of the tissue oxygenation (StO2).
The camera consists of a camera, a recharger, and a reference card for calibration and is used by healthcare professionals in a healthcare environment to determine oxygenation levels in superficial tissues for a patient population with potential circulatory compromise.
The provided text describes a 510(k) premarket notification for the Kent Camera, a non-invasive tissue oxygenation measurement system.
Acceptance Criteria and Study Details
The primary goal of the study was to demonstrate the substantial equivalence of the modified Kent Camera (KC203, battery-powered) to its predicate device (KC103, AC-powered). The acceptance criteria revolved around demonstrating linear agreement, minimal bias, and a small scale shift between the StO2 measurements of the two devices across a clinically meaningful dynamic range.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Linear relationship of StO2 measurements between the two devices over a clinically meaningful dynamic range. | Demonstrated linear relationship. The Deming regression line of agreement has a 95% confidence interval for the slope [0.932 - 0.959] and intercept [0.020 - 0.040]. StO2 values from both cameras show an excellent linear correlation over a wide range of StO2 levels (normal, mildly ischemic, critically ischemic conditions). |
| Quantify any scale shift (slope) between the devices and estimate the 95% levels of agreement. | The slope -0.0057, with a 95% confidence interval of [-0.009, -0.002], indicates less than a 1% scale shift between the two cameras. The 95% limits of agreement (LoA) for the battery-powered minus the predicate device are -0.13 to 0.12 StO2 units. More than 85% of the paired measurements from the two cameras differ less than 0.1 StO2 units. |
| Quantify any bias (difference in mean values) between the devices. | Bland-Altman analysis shows little to no bias between the devices, with a 95% confidence interval for the intercept of [-0.004, 0.003] StO2 units (using StO2 reported on a scale of 0 to 1). |
| Devices should share a common scale. | The devices share a common scale (within 1%). |
| Devices should show minimal to no bias. | The devices show minimal to no bias. |
| Ability to report a drop in StO2 levels under ischemia and a trend consistent with physiological response. | The study demonstrated that StO2 values from both cameras report a drop from basal StO2 levels under conditions of known ischemia and report a trend in StO2 values consistent with the physiological response expected for forearm ischemia - reperfusion. |
| StO2 readings are not statistically and operationally significantly different. | The two devices show an excellent linear relationship and provide StO2 readings which statistically and operationally are not significantly different. |
2. Sample Size for the Test Set and Data Provenance
- Sample Size: 17 volunteers (7 females, 10 males)
- Data Provenance: The study was a "pre-clinical study" conducted using a "forearm ischemia protocol" in an unnamed location. The volunteers "self-reported as being healthy." The study was prospective in nature, as it involved taking measurements from human subjects under controlled conditions for the purpose of the study.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts
The study did not involve experts establishing a "ground truth" in the traditional sense of diagnostic interpretation. Instead, the study assessed the agreement between two devices by comparing their measurements against each other and against an induced physiological state (forearm ischemia/reperfusion). The "ground truth" was essentially the known physiological changes induced in the forearm, and the device measurements were compared against each other, not against an expert-derived interpretation.
4. Adjudication Method for the Test Set
No adjudication method was described, as the study design was an agreement study comparing two devices' direct measurements, not an interpretation task requiring expert consensus.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No MRMC comparative effectiveness study was done. The study focused on device-to-device agreement, not the improvement of human readers with AI assistance.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done
The study implicitly evaluated the standalone performance of the device's algorithm by comparing the StO2 measurements generated by the KC203 directly with those generated by the KC103. Both devices generate StO2 values independently, and the comparison assesses the equivalence of these generated values. Human operators were involved in taking the measurements, but the performance being evaluated (StO2 measurement accuracy and agreement) is that of the device's algorithmic output.
7. The Type of Ground Truth Used
The "ground truth" for the test set was:
- Known physiological changes: The forearm ischemia protocol provided a controlled and expected range of StO2 values (normal, ischemic, reperfusion). The basis for comparison was the agreement between the two devices' measurements across these known physiological states, rather than a single absolute "ground truth" reference measurement (like pathology).
8. The Sample Size for the Training Set
The document does not specify a training set sample size. This is a 510(k) submission, typically focusing on demonstrating substantial equivalence of a modified device to a predicate device, rather than a novel algorithm development where training set details are paramount. The "training" of the device involves its inherent multispectral imaging technology and the application of a modified Beer-Lambert model, which are fundamental scientific principles rather than a machine learning training process with a distinct training dataset.
9. How the Ground Truth for the Training Set Was Established
Not applicable/not provided. As mentioned above, the device's operation is based on established physical principles of light absorption and scattering for tissue oxygenation, rather than a machine learning model trained on a specific dataset with established ground truth labels in the typical sense. The "ground truth" for developing the underlying technology would be physiological models and empirical data relating light spectroscopy to oxygen saturation, but this is not described in terms of a "training set" in the context of this regulatory document.
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(254 days)
KENT IMAGING INC.
The Kent Camera is intended for use by healthcare professionals as a non-invasive tissue oxygenation measurement system that reports an approximate value of:
- oxygen saturation (StO2), .
- oxyhemoglobin level (HbO2), and ●
- deoxyhemoglobin (Hb) level .
in superficial tissue. The Kent Camera displays two-dimensional color-coded images of tissue oxygenation of the scanned surface and reports multispectral tissue oxygenation measurements for selected tissue regions.
The Kent Camera is indicated for use to determine oxygenation levels in superficial tissues for patients with potential circulatory compromise.
The Kent Camera is based on multispectral imaging technology and performs spectral analysis at each point in a two-dimensional scanned area producing an image displaying information derived from the analysis. The Kent Camera determines the approximate values of oxygen saturation (StO₂), oxyhemoglobin levels (HbO₂), and deoxyhemoglobin levels (Hb) in superficial tissues and displays a two-dimensional, color-coded image of the tissue oxygenation (StO2).
The device consists of:
Imaging Head: Contains light sources, camera, and spectral filters for collecting image data.
Touchscreen Computer: User interface, display of images, and image data processing.
Cart: Support and attachment points for imaging head and touchscreen computer.
The provided document is a 510(k) summary for the Kent Camera, a tissue oximeter. It describes the device, its intended use, and its substantial equivalence to a predicate device (Hypermed Inc.'s OxyVu-1). However, it does not contain any information about acceptance criteria, specific performance studies, sample sizes, expert qualifications, or ground truth establishment for the Kent Camera.
The document primarily focuses on establishing substantial equivalence based on similar intended uses, technology, and a general statement about "results from performance testing," but it does not detail these performance tests.
Therefore, I cannot provide the requested information from the given text.
The following information is NOT available in the provided document:
- A table of acceptance criteria and the reported device performance: No acceptance criteria or specific performance values are listed.
- Sample sized used for the test set and the data provenance: No information on test set sample size or data provenance.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: No mention of experts or ground truth establishment.
- Adjudication method: No information about adjudication.
- 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: This device is not described as an AI-assisted device, and no MRMC study is mentioned.
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: No standalone performance metrics are provided.
- The type of ground truth used: No ground truth type is specified.
- The sample size for the training set: No information about a training set or its size.
- How the ground truth for the training set was established: No information about a training set or its ground truth.
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