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The IRTS Probe is intended for continuous esophageal temperature monitoring.

The IRTS Patient Monitoring Unit Patient Interface Unit (PIU) is intended to display continuous temperature measurements (C°) from the IRTS Thermal Imaging Probe.

The Securus InfraRed Thermographic System (IRTS) is an esophageal temperature probe and monitoring system intended for continuous temperature monitoring of the patient's esophagus. The Probe includes a thermocouple sensor for temperature monitoring and a thermographic sensor for thermal imaging. Data from both sensors are displayed on a monitor for the user.

The InfraRed Thermographic System (IRTS) consists of three components:

• A. Thermal Imaging Probe (TIP or Probe)
• B. Patient Interface Unit (PIU)
• C. Patient Monitoring Unit (PMU)

The Probe provides esophageal temperature monitoring through the use of a standard thermocouple mounted in a flexible 9 French catheter. In addition, the IRTS incorporates a thermographic sensor and fiber optic assembly to passively collect the infrared radiation that is self-emanating from the surrounding esophageal tissue surface. The thermal data is presented on the Patient Monitoring Unit as a two-dimensional color map with peak temperature over the mapped area. The thermal image and peak temperature are offered as additional temperature monitoring features.

Here's an analysis of the acceptance criteria and study information for the InfraRed Thermographic System (IRTS), based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for the Test Set

The document does not specify the sample size used for the performance tests (accuracy, response time, mechanical testing). It states "Finished devices were tested" and "Probes were tested."

The data provenance is not explicitly stated as retrospective or prospective, nor does it mention the country of origin of the data. However, the nature of the tests (biocompatibility, electrical safety, EMC, software V&V, performance testing, mechanical testing) suggests these were prospective, laboratory-based tests conducted on manufactured devices or components.

3. Number of Experts and Qualifications for Ground Truth (Test Set)

This information is not provided in the document. The performance tests described are primarily objective, quantitative measurements against international standards (e.g., ISO, IEC). There's no indication that human experts were used to establish a "ground truth" in the traditional sense for these technical performance metrics.

4. Adjudication Method for the Test Set

This information is not applicable/not provided. Adjudication methods (like 2+1, 3+1) are typically used in clinical studies where multiple human readers or experts are interpreting data and their disagreements need resolution to establish a consensus ground truth. The tests described here are technical and objective (e.g., measuring temperature accuracy against a known standard, confirming compliance with electrical safety).

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

No. A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not reported. The document focuses on the technical performance and safety of the device itself, not on its comparative effectiveness with or without AI assistance for human readers/clinicians, nor on the impact of its thermal imaging feature on clinical outcomes.

6. Standalone (Algorithm Only) Performance

Partially applicable/implicitly yes. The core performance tests (accuracy, response time) for the thermocouple sensor are standalone performance metrics of the device's ability to measure temperature. The document explicitly states the "InfraRed Thermographic System (IRTS) was tested in accordance with the requirements of ISO 80601-2-56... Testing included accuracy and response time. All performance testing data shows that the IRTS system meets the requirements of ISO 80601-2-56." This describes the standalone performance of the temperature sensing component.

For the thermographic sensor (the "AI-like" component that displays a 2D color map), the document states: "The thermal data of the IRTS is not classified under the Clinical Thermometer designation of ISO 80601-2-56." It also mentions "The thermal image and peak temperature are offered as additional temperature monitoring features." While it describes the function of this feature, it does not provide standalone performance metrics (e.g., accuracy, sensitivity, specificity) specifically for the thermal imaging capability itself, nor does it specify a study proving its individual performance against a ground truth. It states "The performance testing supports substantial equivalence of the IRTS to the predicate," but the predicate did not have this feature.

7. Type of Ground Truth Used

For the thermocouple sensor's performance (i.e., temperature measurement):
The ground truth used for accuracy and response time testing was based on known, standardized reference values or conditions as dictated by ISO 80601-2-56. For example, temperature accuracy is typically measured against a highly accurate reference thermometer in a controlled bath with known temperatures.

For the thermal imaging feature:
The document does not specify a ground truth method or study for the thermal imaging feature's performance in terms of its ability to accurately represent esophageal temperature distribution. It only states its output as "additional temperature monitoring features" and the data "is not classified under the Clinical Thermometer designation."

8. Sample Size for the Training Set

The document does not mention a training set in the context of machine learning or AI. The product description and performance data focus on the physical and electrical characteristics of a medical device (thermometer), not an AI algorithm that would typically require a training set. The "thermal imaging" component is described as passively collecting infrared radiation and presenting it as a map, which sounds more like signal processing and display rather than a machine learning model requiring training.

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

As no training set is mentioned or implied for a machine learning model, this question is not applicable.

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