(321 days)
The Tristan Technologies Model 621/624 Biomagnetometer is intended for use as a tool that noninvasively measures and displays the magnetic signals produced by the electric currents in the heart of human beings of any age or in the heart of a fetus in utero.
The Tristan Technologies Model 621/624 Biomagnetometer (hereinafter referred to as the "Model 621/624") utilizes superconducting signal pickup coils and Superconducting Quantum Interference Devices (SQUIDs) to detect and amplify magnetic fields produced by electrical activity in the heart. The Model 621/624 consists of a sensor unit, an electronics subsystem for preliminary amplification, filtering, and analog to digital conversion of the signals from each SQUID, an electronics rack containing power supplies to power the electronics subsystem, a computer to control the operation of the electronic subsystem and the SQUIDs and to acquire and store the signal values collected by the system.
This document is a 510(k) premarket notification for the Tristan Technologies Model 621/624 Biomagnetometer. The notification primarily focuses on establishing substantial equivalence to a predicate device rather than detailing specific acceptance criteria and a comprehensive study against them. Therefore, many of the requested sections regarding the study and ground truth will not be directly derivable from this document.
Here's an analysis based on the provided text, highlighting what is available and what is not:
1. A table of acceptance criteria and the reported device performance
This document does not present a table of specific, quantifiable acceptance criteria or a direct comparison of the Model 621/624's performance against such criteria. The "performance" assessment is based on demonstrating technological equivalence to a predicate device.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size for Test Set: Not explicitly stated in terms of patient numbers. The "non-clinical test measurements" were conducted at the University of Wisconsin Department of Medical Physics.
- Data Provenance: The tests were "non-clinical" and involved "test measurements" at a university in the US (University of Wisconsin). It is unclear if these were on human subjects or phantoms, but given the context of biomagnetic signals from the heart, it implies human data. The document does not specify if the data was retrospective or prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
Not applicable. The "ground truth" here is the measurement of magnetic signals, not a diagnostic interpretation that would require expert consensus. The study focused on comparing the device's ability to measure these signals against a predicate device's published measurements.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. There was no diagnostic adjudication process involved. The comparison was based on the output signals themselves.
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
No. This is not an AI-based device, and no MRMC study was conducted or mentioned. The device is a "Biomagnetometer" that measures and displays magnetic signals from the heart.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Essentially, yes, in the sense that the "non-clinical test measurements" focused on the device's ability to generate signals. However, this is not an "algorithm-only" device in the AI sense. It's a measurement device. Its performance is its standalone capability to measure. The study aimed to show its measurements were comparable to the predicate device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" was the expected magnetic signals produced by electrical activity in the heart, as measured by a legally marketed predicate device. The comparison was made based on published data from the predicate device. In essence, the predicate device's measurements served as the reference for technological equivalence.
8. The sample size for the training set
Not applicable. This is not a machine learning or AI device that requires a training set.
9. How the ground truth for the training set was established
Not applicable, as there is no training set.
§ 870.2340 Electrocardiograph.
(a)
Identification. An electrocardiograph is a device used to process the electrical signal transmitted through two or more electrocardiograph electrodes and to produce a visual display of the electrical signal produced by the heart.(b)
Classification. Class II (performance standards).