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The SSMPD is intended as a general use clinical laboratory gamma radiation counter. The SSMPD is designed for use by operators qualified to measure gamma-ray emissions from radiolabelled reagents within particular energy bands or energy regions of interest (ROI) as part of diagnostic radioassay or radioimmunoassay methods. The standard quantitative units of measure reported are the measured count per minute (cpm) and the calculated disintegrations per minute (dpm).

The ssMPD is a twelve sample, bench-top gamma radiation counter that can be used to measure counts per minute and calculate disintegrations per minute emitted by multi-photon emission isotopes, including 125I. In volumes of 0.05 to 2.0 mls contained in 12 mm x 75 mm or 13 mm x 100 mm sample tubes disintegrations are measured over the range of 1 to 106 dpms. The sample tubes must be capped to minimize the possibility of contaminating the detector chamber. The full detector assembly is a twin detector system consisting of two scintillator crystals--each coupled to a high resolution planar photomultiplier. The entire detector is encased in a composite lead-tin-copper shield to minimize environmental background. In addition to permitting efficient counting of gamma emitters, the sample holder acts as a separator to reduce crosstalk within the twin scintillator detector assembly. The complete SSMPD system is comprised of a standalone SSMPD connected directly to a personal computer (PC) configured with SSMPD read-out electronics, MPDATA™ control and data logger software, and optionally, a printer.

The BioTraces Inc. SEQUENTIAL SAMPLE MULTI-PHOTON DETECTOR (SSMPD) is a gamma scintillation counter intended for general use in clinical laboratories to measure gamma-ray emissions from radiolabelled reagents.

Here's an analysis of the provided text regarding acceptance criteria and supporting studies:

1. Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state quantitative acceptance criteria or report specific performance metrics in a structured table. Instead, it focuses on describing the device's capabilities and comparing them to a predicate device.

However, based on the Description and Intended Use sections, we can infer some general performance expectations:

Note: The document primarily focuses on describing the technical features and intended use of the SSMPD and establishing substantial equivalence to a predicate device. It does not present a formal study with detailed statistical results to "prove" the device meets acceptance criteria. Instead, the argument for effectiveness is made through the device's technical specifications and a comparison to a previously cleared device.

2. Sample Size and Data Provenance for the Test Set

The provided text does not describe an explicit "test set" in the context of a performance study with a defined sample size or data provenance. The document is a 510(k) summary, which typically focuses on demonstrating substantial equivalence to a predicate device rather than presenting raw clinical or performance data from novel studies.

The detailed descriptions of the device's capabilities (e.g., measuring dpms from 1 to 10^6, handling 125I) are likely derived from internal engineering evaluations and characterization studies performed by BioTraces Inc. However, no specific details about these studies (sample size, country of origin, retrospective/prospective nature) are provided in this summary.

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

Because no explicit "test set" and a corresponding independent performance study are detailed, there is no information provided regarding experts used to establish ground truth for such a test set.

4. Adjudication Method (Test Set)

Given the lack of a described test set with human assessment, there is no adjudication method mentioned.

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

The provided text does not describe a multi-reader multi-case (MRMC) comparative effectiveness study. The SSMPD is a standalone gamma counter, meaning its performance is based on measurements of radioactivity rather than interpretation of images by human readers. Therefore, the concept of human readers improving with or without AI assistance is not applicable to this type of device.

6. Standalone (Algorithm Only) Performance Study

The entire description of the SSMPD can be considered a description of its standalone performance (i.e., algorithm/device only performance without human-in-the-loop performance). The device itself performs the measurement and calculation of cpm and dpm. The details provided, such as the measurement range of 1 to 10^6 dpms and the ability to detect 125I, characterize its standalone capabilities. However, a formal "study" with statistical results for standalone performance is not detailed in this summary.

7. Type of Ground Truth Used

For the characterization of the SSMPD's performance, the "ground truth" would be the known radioactivity levels or concentrations of the radiolabelled samples used during the device's development and testing. This would typically involve:

• Reference Standards: Samples with precisely known activities or disintegrations per minute (dpm) measured using established gold-standard methods.
• Known Isotope Samples: Samples containing specific isotopes (like 125I) at known concentrations to verify detection and energy windowing.

The text implies that the ground truth for its performance claims (e.g., 1 to 10^6 dpms measurement range) was established through such physical and chemical reference standards, but it does not explicitly state this.

8. Sample Size for the Training Set

The concept of a "training set" is typically associated with machine learning or AI algorithms where a model learns from data. While the SSMPD uses "pulse shape as well as pulse height analysis in software and hardware," which involves signal processing, it's not explicitly framed as a machine learning model requiring a distinct training set in the conventional sense.

Therefore, the provided text does not specify a "sample size for the training set."

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

As there is no explicit mention of a "training set" in the context of a machine learning algorithm, there is no information provided on how ground truth for such a training set was established. Any internal calibration or tuning of the pulse analysis algorithms would have relied on the same fundamental principles of known radioactivity standards as described in point 7.

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