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The PulmOne MiniBox+ is intended to measure lung function in adult and pediatric patients, 5 years and older, while at rest (including spirometry, lung volumes and diffusing capacity). The PulmOne MiniBox+ is to be used by a physician, respiratory therapist, or technician in a hospital or clinic setting

The PulmOne MiniBox+ is intended to measure lung function in adult and pediatric patients while at rest (including spirometry, lung volumes and diffusing capacity). The PulmOne MiniBox+ is to be used by either a physician, respiratory therapist, or technician. A cleared single-use, disposable viral-bacterial filter separates the patient from the internal components of the device.

The MiniBox+ measures all common spirometric measurements as well as relative and absolute lung volumes and diffusing capacity.

The MiniBox+ is equipped with a diffusing capacity module which is embedded into the MiniBox+ enclosure and located in the upper end of the device. This feature allows easy measurement of the volumes and concentrations (CO and CH4) of inspired and expired breath, of the test gas mixture and patient sample respectively, making possible the calculation of the diffusion capacity [DLco]. MiniBox + DLco [diffusing capacity factor of the lung for carbon monoxide (CO)] module uses the single breath concept and enables the measurements by setting and controlling the maneuver stages as defined in ATS/ETS DLco guidelines.

Here's a breakdown of the acceptance criteria and study information for the PulmOne MiniBox+ device, based on the provided document:

Acceptance Criteria and Device Performance

The document describes the performance and technical specifications of the MiniBox+ and compares them to predicate devices. The MiniBox+ is a pulmonary function data calculator, and its performance is evaluated against established standards for spirometry, lung volumes, and diffusing capacity measurements.

Table of Acceptance Criteria and Reported Device Performance

Study Information

1. Sample size used for the test set and the data provenance:

   • DLco human comparative testing: Not specified in the provided text.
   • DLco human reproducibility testing: Not specified in the provided text.
   • No other "test set" sample sizes or data provenance (e.g., country of origin, retrospective/prospective) are mentioned for non-clinical or clinical studies in this document. The focus of the non-clinical testing appears to be on simulator and comparative studies rather than a large clinical test set.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not specified. The document mentions "DLco human comparative testing" and "DLco human reproducibility testing," but does not detail how ground truth was established for these or the number/qualifications of experts involved.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not specified.

4. 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 mentioned. The device is a "Pulmonary-Function Data Calculator," and the documentation does not describe an AI component that would assist human readers in interpreting images or data in an MRMC setting. It's for direct measurement and calculation.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

   • The document implies standalone performance testing for the device's measurement accuracy, particularly for DLco using a simulator ("DLco performance verification against simulator [Hans Rudolf]"). However, the "human comparative testing" and "human reproducibility testing" suggest interaction with humans, but not necessarily in an AI-assistive role. The core function is measurement and calculation, which is inherently "standalone" in its data generation, regardless of human interaction for the test.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • For the DLco gas analyzer, ground truth was established through OEM manufacturer verification (linearity) and testing against a DLco gas simulator [Hans Rudolf, Inc.].
   • For human measurements, the ground truth was implied to be established through internal repeatability measurements and comparison against the predicate device, ZAN Function Lab [ZAN-500]. This suggests that the ZAN 500's measurements served as a de-facto ground truth for comparative purposes.

7. The sample size for the training set:

   • Not applicable as this device is a measurement and calculation device, not a machine learning model that requires a training set in the conventional sense. Its "training" or calibration would involve ensuring its sensors and algorithms accurately reflect physical properties.

8. How the ground truth for the training set was established:

   • Not applicable for the same reasons as above. The internal algorithms are based on established scientific principles of pulmonary function testing (e.g., ATS/ETS guidelines, Boyle's law for lung volume calculation) and calibrated against known standards and other validated devices.

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