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The noninvasive INVOS 5100B is intended for use as an adjunct trend monitor of regional hemoglobin oxygen saturation of blood in the brain of an individual. It also is intended for use as an adjunct trend monitor of hemoglobin oxygen saturation of blood in a region of skeletal muscle tissue beneath the sensor in infants, children, or adults at risk for reduced-flow or no-flow ischemic states. The prospective clinical value of data from the INVOS System has not been demonstrated in disease states. The INVOS System should not be used as the sole basis for diagnosis or therapy.

The principles of operation of the cerebral oximeter system are based on the assumption that hemoglobin exists in two principal forms in the blood: oxygenated hemoglobin (HbO2) and reduced hemoglobin (Hb). Functional oxygen saturation (SO2) is defined as the ratio of oxyhemoglobin (HbO2) to total hemoglobin (HbO2 + Hb) and is commonly presented as a percentage.

SO2 = (HbO2 / (HbO2 + Hb)) * 100%

Since oxygenated and reduced hemoglobin are different colors and absorb light as a known function of wavelength, selected wavelengths of light can be used to assess the relative percentage of these two constituents. This fundamental approach of assessing the color of blood using various wavelengths of light to measure hemoglobin oxygen saturation trends is used in all currently marketed oximetry systems.

For cerebral monitoring, a disposable sensor of medical grade materials is applied to the patient's forehead (Figure 1). The sensor incorporates a light source and two return signal detectors at different predetermined distances from the light source. The signal detector nearest the light source (3 cm) is considered the "shallow detector" and the further detector from the light source (4 cm) the "deep detector."

While the light reaching the deep detector has sampled about the same amount of skin, scalp, and skull as the light reaching the shallow detector, it has sampled more brain tissue. This difference is used to help separate out the brain signal and suppress anatomical differences in patients. The additional information unique to the deep signal return is predominately from brain tissue blood which is composed mostly of venous blood. The information contained in the shallow and deep signal returns is processed by an algorithm to measure changes in hemoglobin oxygen saturation in a small region of tissue beneath the sensor, predominately in the brain.

For non-cerebral monitoring, a somatic sensor which is similar to the cerebral sensor is placed on skeletal muscle in an area free of large fat deposits, bony protuberances and hair. Since the tissue being interrogated is relatively homogeneous, the resultant rSQ2 index is an average of the hemoglobin oxygen saturation of blood in the region of tissue below the sensor.

The SomaSensor is connected to a preamplifier (1.4 x 7.65 x 3.75 in.) which is placed close to the patient and amplifies the rSO2 signal. The signal is then carried to a display unit (8.4 x 9.6 x 8.5 in.) where the values and trends are displayed on the screen. The display unit controls all functions of the system with selections made by keys with onscreen labels. The system will operate for up to 120 minutes on battery, enabling patient transport without loss of data.

The Somanetics INVOS 5100B Oximeter System, including the SSFB Somatic SomaSensor, was granted substantial equivalence based on prior clinical studies and nonclinical testing that demonstrated its performance. The provided document does not explicitly present a table of acceptance criteria with numerical targets and direct comparisons to device performance for this specific 510(k) submission. Instead, it relies heavily on the substantial equivalence to previously cleared devices (INVOS 5100, Spectros Corporation T-Stat™ 303, and Hutchinson InSpectra) and results from previous studies.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a formal table with acceptance criteria outlined for this specific submission. However, it references performance characteristics from a previous animal study for skeletal muscle tissue monitoring.

2. Sample Sizes and Data Provenance:

• Test Set (for the mentioned animal study related to somatic sensor): The document states an "animal study using isolated perfused porcine limbs" was conducted. The specific number of limbs or animals used is not provided.
• Data Provenance:
  • Adult Hypoxia Study: Not explicitly stated, but typically these are conducted in controlled clinical environments, likely in the US given the submission to the FDA. Retrospective/Prospective is not specified.
  • Pediatric Cath Lab Study: Not explicitly stated, but likely clinical data collected in a hospital setting, probably in the US. Retrospective/Prospective is not specified.
  • Animal Study (Somatic Sensor): Porcine limbs, prospective in nature. Country of origin not specified.
  • Multiple Peer-Reviewed Studies: Referencing existing literature, data provenance would vary by study.
  • Two Published Studies (Exercise): Referencing existing literature, data provenance would vary by study.
• The 510(k) submission itself primarily relies on substantial equivalence and previously established performance, rather than new, large-scale clinical trials for the specific 5100B device.

3. Number of Experts and Qualifications for Ground Truth:

• The document does not specify the number of experts or their qualifications for establishing ground truth for any of the studies mentioned.
• For the cerebral studies, the "ground truth" was established by co-oximetry analysis of blood samples, which is considered a gold standard for blood oxygen saturation measurement. This is an objective measurement rather than an expert interpretation.
• For the animal study, the "ground truth" was also a direct measurement, implied to be derived from the isolated perfused porcine limbs' blood oxygen saturation.

4. Adjudication Method:

• Not applicable/Not specified. Since objective measurements like co-oximetry were used as ground truth, expert adjudication methods (like 2+1 or 3+1 for imaging consensus) were not relevant or mentioned.

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

• No. An MRMC comparative effectiveness study was not done or reported in this document. The INVOS 5100B is a trend monitor, not an interpretive diagnostic device that relies on human reader input in the same way imaging AI does. Therefore, a study to assess how human readers improve with AI assistance is not relevant to this type of device.

6. Standalone Performance Study:

• Yes, in essence. The reported performance from the adult hypoxia study, pediatric cath lab study, and the animal study on porcine limbs demonstrate the standalone performance of the INVOS System in tracking oxygen saturation against a gold standard (co-oximetry or direct measurement). The device is intended to provide measurements, and its accuracy in doing so is what these studies assessed.

7. Type of Ground Truth Used:

• Objective Measurement/Physiological Gold Standard:
  • For cerebral oxygen saturation, the ground truth was established using co-oximetry analysis of blood samples.
  • For skeletal muscle tissue, the ground truth was also a direct measurement of blood oxygen saturation in the isolated perfused porcine limbs.

8. Sample Size for the Training Set:

• The document does not provide information on the sample size used for training any algorithms within the INVOS 5100B system. This product pre-dates the widespread use of deep learning and large-scale training sets as discussed in modern AI/ML medical devices. The device's operation is based on established principles of near-infrared spectroscopy and algorithmic processing of light absorption, likely with parameters developed through engineering and calibration, rather than extensive "training sets" in the contemporary AI sense.

9. How Ground Truth for Training Set was Established:

• As the document does not refer to a distinct "training set" in the context of modern AI/ML, it does not describe how ground truth for such a set was established. The device's underlying principles and algorithms would have been developed and validated through scientific understanding of optical properties of blood and tissue, and engineering calibration, possibly against reference measurements in laboratory settings or smaller physiological studies.

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