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510(k) Data Aggregation
(119 days)
The Elfor L is intended for measuring micro-vascular perfusion in skin and muscle in humans. It is intended to be used for clinical research applications and pre clinical research applications.
The Elfor-L device is making use of Miniaturized Dynamic Light Scattering (mDLS) technology to non-invasively measure micro-vascular perfusion in the skin. The device is comprised of sensor and signal processing station. The device uses Vertical-Cavity Surface-Emitting Lasers (VCSEL) as the light source and two photodetectors for detection.
The Elfor-L design incorporates three major components:
- Sensor - the sensor as its predicate includes a laser light source and two photo sensitive elements. The sensor transfers analog signal to the control unit.
- Control unit - the control unit is connected to the sensor by cable and includes the control circuit for the sensor, microcontroller and communication interface for the PC.
- Dedicated software that processes, displays and record data on the computer. The computer is not part of the system.
The FDA 510(k) clearance letter for the Elfor-L device mentions that performance testing was conducted, including a comparison to its predicate device and an accuracy evaluation. However, the provided document does not contain the specific details required to fully address your request, such as:
- A table of acceptance criteria and reported device performance values. While it states "The test passed and met the predefined acceptance criteria" for comparison testing and "The test passed" for accuracy, the actual numerical criteria and results are not listed.
- Sample sizes used for the test set.
- Data provenance (e.g., country of origin, retrospective/prospective).
- Number of experts and their qualifications for ground truth.
- Adjudication method for the test set.
- Details on Multi-Reader Multi-Case (MRMC) comparative effectiveness study (effect size, human improvement).
- Details on standalone (algorithm only) performance.
- Type of ground truth used (expert consensus, pathology, outcomes data, etc.).
- Sample size for the training set.
- How ground truth for the training set was established.
The document primarily focuses on demonstrating substantial equivalence to a predicate device based on intended use, technological characteristics, and compliance with general safety and performance standards (biocompatibility, software validation, electrical safety, EMC). It implies that the performance was found to be acceptable but does not provide the granular data of the clinical study itself.
Therefore, for the specific questions related to acceptance criteria and study details (especially for an AI/machine learning context, which this device, being a physical measurement device, doesn't explicitly describe), the provided text is insufficient.
Based on the provided text, here's what can be extracted and what remains unknown:
1. A table of acceptance criteria and the reported device performance:
| Acceptance Criterion | Stated Performance (or outcome) |
|---|---|
| Comparison Testing to Predicate Device | "The test passed and met the predefined acceptance criteria." (Specific numerical criteria and results not provided) |
| Perfusion Accuracy | "The test passed." (Accuracy value: 250±10 PU, as per the comparison table under "Perfusion Accuracy" which acts as the acceptance criterion from the predicate. The "reported device performance" would be that Elfor-L achieved this.) |
| Biocompatibility | "The device was found biocompatible." |
| Software Validation | "Software verification and validation testing... were conducted, and documentation was provided as recommended by FDA's Guidance." |
| Electrical Safety (IEC 60601-1) | "The tests passed." |
| EMC (IEC 60601-1-2, IEC 60601-4-2) | "The tests passed." |
| Laser Classification (IEC 60825-1) | "The tests passed." (and device is Class I) |
2. Sample sized used for the test set and the data provenance:
- Sample Size: Not specified.
- Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not specified. The performance testing section describes "comparison testing of the Elfor-L to its predicate device" and evaluating accuracy using a "standardized Motility Standard solution." This suggests an objective, instrument-based ground truth (e.g., comparison to a validated device/standard) rather than expert human interpretation in the traditional sense of medical imaging.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not applicable/not specified, as the ground truth appears to be objective, instrument-based.
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 applicable. The Elfor-L is a direct measurement device ("Cardiovascular Blood Flowmeter") not an AI-assisted diagnostic imaging interpretation system. Therefore, MRMC studies are not relevant to its type of performance evaluation.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The device itself is a standalone measurement instrument. Its performance ("Accuracy of the Elfor-L device") was evaluated in comparison to a predicate and against a standard, which fits the concept of standalone performance for this type of device. There isn't an "algorithm" in the sense of AI interpreting an image; rather, it's a signal processing software function for a physical sensor.
7. The type of ground truth used:
- For "Accuracy of the Elfor-L device," the ground truth was established using a "standardized Motility Standard solution."
- For comparison testing, the ground truth was implied to be the performance of the predicate device.
8. The sample size for the training set:
- Not specified. The document doesn't explicitly mention "training sets" in the context of machine learning, as this device measures physical parameters rather than learning from large datasets to perform a classification or detection task. Its "software validation" refers to V&V for software functionality, not machine learning model training.
9. How the ground truth for the training set was established:
- Not applicable/not specified, as no machine learning training set is described.
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(169 days)
The FlowMet-R is a non-invasive probe that is affixed to the fingers or toes and intended to quantify tissue blood flow rate.
The FlowMet-R™ is a non-invasive probe that is affixed to the fingers or toes and intended to quantify tissue blood flow rate. The FlowMet-R™ is a miniaturized clip-on probe, designed to be affixed to the fingers or toes. The FlowMet-R™'s clamshell housing blocks the laser output when not in use or when applied to a digit.
Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:
The document does not explicitly state "acceptance criteria" for performance metrics in a table format. However, it presents performance tests and their outcomes, implying that successful completion of these tests demonstrates the device meets the necessary performance standards for substantial equivalence.
1. Table of Acceptance Criteria and Reported Device Performance
Based on the performance data section, here's a reconstructed table of implied acceptance criteria and reported performance:
| Acceptance Criterion (Implied) | Reported Device Performance |
|---|---|
| Benchtop Testing (Comparison to PeriCam PSI) | |
| Similar response and high linearity (R²) to known flow rates | FlowMet-R™ R² > 0.999, PeriCam PSI R² > 0.95. Both devices demonstrated similar response and high linearity between data output and flow rate for volumetric flow rates from 2-20ml/min. |
| Benchtop Testing (Impact of Skin Coloration) | |
| No significant impact of skin coloration on flow rate measurements | The degree of absorption within a skin tissue analog (simulating skin color) did not significantly affect the flow rate within the sample as determined by the FlowMet-R™. |
| Clinical Testing (Comparison to Laser Doppler Flowmeter) | |
| Measures expected decrease in flow rates during occlusion | FlowMet-R™ system measures the expected decrease in flow rates during occlusion. |
| Measured decrease within +/-22% of Laser Doppler system | Resulting measured decrease is within +/-22% of the laser Doppler system. |
| Significant correlation with Laser Doppler flowmeter | Flow measurements from the FlowMet-R™ and laser Doppler devices were found to be significantly correlated for all patients with significant p values (0.8. |
| Clinical Testing (Impact of Skin Color) | |
| No significant difference in mean flow value among different skin colors | An ANOVA test demonstrated no significant difference in the mean flow value among all grouped skin color/ethnicity groups (White/Caucasian, Hispanic/Latino, Asian, African American). |
| No significant decrease in light source throughput due to skin tone | The difference in mean transmitted intensity between light-skinned (White/Caucasian) patients and any other group demonstrated that skin tone did not significantly decrease light source throughput. |
2. Sample Sizes Used for the Test Set and Data Provenance
- Benchtop Test (FlowMet-R™ vs. PeriCam PSI): No specific sample size in terms of test runs or repeated measurements is provided, but it states "flow rates were varied from 2-20ml/min" and "data was collected concurrently from both systems for a specified length of time (30 seconds) at each flow rate." The data provenance is controlled laboratory conditions using a "tissue analog."
- Benchtop Test (Impact of Skin Coloration): No specific sample size is provided beyond "FlowMet-R™ data was collected under known flow rate conditions using a tissue analog." Skin colors were "simulated by creating silicone-based skin analogs with varying optical absorption." The data provenance is controlled laboratory conditions using "tissue analogs."
- Clinical Test (FlowMet-R™ vs. Laser Doppler):
- Sample Size: 10 patients (5 male, 5 female).
- Data Provenance: Not explicitly stated, but it is a prospective clinical test on human subjects ("Data was collected from 10 patients before, during, and after vascular disruption induced via brachial artery occlusion.").
- Clinical Test (Impact of Skin Color):
- Sample Size: 91 patients (181 total limbs, 84 from females, 97 from males). Grouped by ethnicity/skin color: White/Caucasian (N=144), Hispanic/Latino (N=23), Asian (N=11), and African American (N=3).
- Data Provenance: Not explicitly stated, but implies prospective collection from human subjects ("FlowMet-R™ blood flow and sensor intensity data was collected from 91 patients").
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
The document does not describe the use of experts to establish ground truth in the context of adjudication for the test set.
- For the benchtop tests, the "ground truth" was established by known volumetric flow rates or controlled optical properties of tissue analogs.
- For the clinical tests, the "ground truth" was established by:
- The expected physiological response to vascular occlusion.
- Comparison to a legally marketed predicate device (Laser Doppler flowmeter, K974285, specifically PeriFlux System 5000), which itself serves as a clinical reference.
4. Adjudication Method for the Test Set
No adjudication method involving experts is mentioned for any of the described tests. The comparisons are against physical ground truths (known flow rates, simulated skin colors) or against established medical devices (predicate PeriCam PSI, PeriFlux System 5000 Laser Doppler).
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No MRMC comparative effectiveness study involving human readers and AI assistance is reported. This device is a measurement tool, not an AI for image interpretation that would typically involve human-in-the-loop performance studies.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
The described performance tests are all standalone (algorithm only) performance studies, as the device directly measures and quantifies tissue blood flow rate. There is no human intervention in the interpretation of the raw data that the device outputs; the output itself is the measurement. The studies compare the device's measurements against known physical parameters or another established device, not against human judgment.
7. The Type of Ground Truth Used
- Benchtop Test (FlowMet-R™ vs. PeriCam PSI): Ground truth was based on a known, controlled volumetric flow rate using a pump system and tissue analog.
- Benchtop Test (Impact of Skin Coloration): Ground truth was based on known, controlled optical absorption (simulating skin color) in tissue analogs.
- Clinical Test (FlowMet-R™ vs. Laser Doppler): Ground truth was established by:
- Physiological changes (expected decrease in flow during occlusion).
- Comparison to measurements from a legally marketed predicate device (Laser Doppler flowmeter), which serves as a clinical reference standard.
- Clinical Test (Impact of Skin Color): Ground truth was based on statistical analysis of measured flow values across self-reported or observed ethnicity/skin color groups, to determine if significant differences existed.
8. The Sample Size for the Training Set
The document describes performance testing (validation) of the device. It does not provide information about a "training set" because this device is not presented as an AI/machine learning device that requires a training set in the conventional sense. The device uses "Laser Speckle Imaging" principles, implying fixed algorithms based on physics rather than learned patterns from data.
9. How the Ground Truth for the Training Set Was Established
As no training set is mentioned or implied for this type of device, this question is not applicable.
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(141 days)
Use of the PF 5050 Pressure Unit is indicated for non-invasive Pulse Volume waveform Recordings (PVR) on extremities of patients with vascular diseases.
It is also intended to measure and control the pressure in a blood pressure cuff to simplify simultaneous measurements of perfusion and pressure when used in conjunction with a laser Doppler perfusion monitor.
The PF 5050 Pressure Unit is a modular unit that can be installed in the PeriFlux System 5000. The device provides Pulse Volume waveform Recordings (PVR) on various limb and digit extremities made possible through air plethysmography. The PF 5050 Pressure Unit includes a small display where the mean cuff pressure is displayed.
The PVR tracing is accomplished by attaching a standard blood pressure cuff on various areas of the extremities. To provide skin contact, atmospheric air is inflated to approximately 50 - 65 mmHg using the balloon pump supplied with a standard blood pressure gauge. A pressure transducer records the pressure change in the cuff (Pulse Volume waveforms) secondary to change in v the extremity segment under the cuff during repeated cardiac cycles.
The PeriFlux System 5000 is a multi-channel, multi-functional system capable of hosting one, two, three or four function units including for example a PF 5010 LDPM Unit for blood perfusion measurements. The PeriFlux 5001 Main Unit accommodates up to four different function units of the same type or of different types enabling simultaneous measurements of several parameters. There are three different function unit types available at the moment.
PF 5010 LDPM Unit for blood perfusion measurements.
PF 5020 Temp Unit for temperature measurements.
PF 5040 tcpO2 / pCO2 for measurements of transcutaneous O2 and CO2.
The provided text is a 510(k) summary for the PERIMED PF 5050 Pressure Unit, which describes the device, its intended use, and its substantial equivalence to a predicate device. However, it does not contain any information about acceptance criteria, clinical studies, sample sizes, ground truth establishment, or expert adjudication methods.
Therefore, I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets the acceptance criteria, as this information is not present in the provided document. The 510(k) summary focuses on demonstrating equivalence to a predicate device rather than presenting detailed performance study results against specific acceptance criteria.
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