(260 days)
The MIMOSA Imager is intended to non-invasively estimate the spatial distribution of percent oxygen saturation (StO2) in a volume of tissue. This is performed in medical environments including physician offices, hospitals, ambulatory care and Emergency Medical Services. The MIMOSA Imager is indicated for use in monitoring patients during circulatory or perfusion examinations of skeletal muscle or when there is a suspicion of compromised circulation.
The MIMOSA Imager is a non-contacting, cordless, battery powered device that non-invasively estimates the percent oxygen saturation (StO2) in a volume of tissue. The device captures spatially-resolved images that is triggered by the end user via a smartphone-app interface. By tracking the spectral signatures of dominant chromophores in the patient's superficial tissue, the device calculates and displays the StO2 estimate on the connected android device screen.
The MIMOSA Imager is intended for use by healthcare professionals as a non-invasive tissue oxygenation measurement system that maps the tissue oxygen saturation (StO2) values to a spatially registered heatmap. The MIMOSA Imager shares fundamental principles with other oximeters and tissue oxygenation measurement systems. Tissue oximetry exposes tissue to optical radiation of known wavelengths and captures the remitted or reflected light. The remitted back scattered light is then used to calculate StO2 based on principles of multispectral imaging. Spectral analysis is used to measure StO2 using specific both visible (VIS) and near-infrared (NIR) LED-illuminated wavelengths. Other systems that also measure oxygenation levels in superficial tissue may use only VIS or NIR wavelengths.
The provided document is a 510(k) Premarket Notification summary for the MIMOSA Imager, which is a medical device intended to non-invasively estimate the spatial distribution of percent oxygen saturation (StO2) in tissue. The document details the device's description, indications for use, comparison to a predicate device, and performance testing.
Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:
Acceptance Criteria and Reported Device Performance
The acceptance criteria are not explicitly stated in a table format with specific numerical targets. Instead, the document focuses on demonstrating substantial equivalence to a predicate device (ViOptix ODISsey Tissue Oximeter) through a comparative clinical study. The primary metric for this equivalence appears to be the statistical agreement of StO2 measurements between the two devices.
| Acceptance Criteria (Inferred from Study Goal) | Reported Device Performance (MIMOSA Imager vs. ViOptix ODISsey) |
|---|---|
| Statistical Agreement of StO2 Measurements | 95% Confidence Interval of the line of best fit: Narrowly constrains the slope of the line between 0.998 and 1.02. |
| Conclusion: MIMOSA Imager measures were in statistical agreement with Vioptix for thenar eminence and forearm for age between 21-70 and range of Fitzpatrick skin types. | |
| Safety | Conclusion: No adverse events or complications were encountered during or after clinical testing. |
Study Details
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Sample size used for the test set and the data provenance:
- Sample Size: 39 individuals.
- Data Provenance: The document does not explicitly state the country of origin. It describes the study as "clinical testing," which implies it was a prospective study where data was collected specifically for this comparison.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- The concept of "ground truth" in this context is established by the measurements of the predicate device (ViOptix ODISsey Tissue Oximeter), which is legally marketed and considered a benchmark for StO2 estimation.
- No independent experts were used to establish a separate "ground truth" for the StO2 values themselves, as the study was comparative against an established device. The clinical study seems to have involved medical professionals ("healthcare professionals" as stated for device usage) who conducted the vascular occlusion test and measurements, but their number and specific qualifications for establishing ground truth are not detailed.
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Adjudication method for the test set:
- No adjudication method (like 2+1 or 3+1) is mentioned, as the study's goal was to compare the MIMOSA Imager's measurements directly against those of the predicate device, not to adjudicate discrepancies between human readers or between a human and an AI.
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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:
- No MRMC study was done. This device is a measurement tool (oximeter), not an AI-assisted diagnostic imaging device for human interpretation. The study focused on the device's direct measurement performance compared to a predicate device.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The clinical study was a standalone device performance study in the sense that the MIMOSA Imager's measurements were directly compared against the predicate device's measurements. The device generates the StO2 map, and its performance (accuracy/agreement) is assessed as an output of the device itself. Human interaction is for operating the device and interpreting the display, but the core measurement is automated by the device's algorithms.
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The type of ground truth used:
- The "ground truth" for the comparison was the measurements provided by the legally marketed predicate device (ViOptix ODISsey Tissue Oximeter) under controlled conditions (vascular occlusion test). This serves as a "clinical reference standard" rather than an independent expert consensus, pathology, or outcomes data.
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The sample size for the training set:
- The document does not provide details on a separate "training set" or its size. As this is an oximeter, its underlying principles are based on spectrophotometry and known biological chromophores, rather than a machine learning model that requires a dedicated training set in the typical AI/ML sense. The device calculates StO2 based on spectral analysis. Any internal calibration or algorithm development (if using something akin to statistical models) would presumably rely on fundamental physics and potentially pre-clinical or simulated data, not explicitly described as a "training set" in the document.
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How the ground truth for the training set was established:
- Given that no specific "training set" in the context of machine learning is identified, the method for establishing its ground truth is not applicable from the provided text. The device's StO2 estimation relies on principles of multispectral imaging and spectral analysis, with "bench data" demonstrating acceptable accuracy against "clinical/industrial gold standard" which likely refers to established physical or chemical standards for light absorption/reflection by oxygenated/deoxygenated blood.
§ 870.2700 Oximeter.
(a)
Identification. An oximeter is a device used to transmit radiation at a known wavelength(s) through blood and to measure the blood oxygen saturation based on the amount of reflected or scattered radiation. It may be used alone or in conjunction with a fiberoptic oximeter catheter.(b)
Classification. Class II (performance standards).