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The Imagen3D™ system is software application that works in conjunction with ImagenPRO® to correct for photon scatter and prompt gamma contamination present in PET 3D data. The resulting 3D datasets can be reconstructed using ImagenPRO® to produce PET and/or PET/CT reconstructed tomograms.

Imagen3D™ is a Windows application that works in conjunction with ImagenPRO® as an additional processing step for data acquired in 3D (septa retracted mode). Because of the increase count rate of PET scanners in 3D mode, a lower dosage of the radiopharmaceutical is recommended to avoid dead time issues with the scanners. The resulting 3D sinograms can then be processed in ImagenPRO® to produce 3D tomograms. The use of this system is limited to qualified, licensed healthcare providers (radiologists, nuclear cardiologists or nuclear medicine physicians) trained in the use of nuclear medicine imaging devices.

The Imagen3D™ system is designed to take Fourier rebinned sinogram data from commercially available dedicated PET and PET/CT systems acquired in 3D (septa retracted) and scatter correct the data for export into ImagenPRO® for tomographic processing.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Imagen3D™ device:

Based on the provided text, the Imagen3D™ application functions as a pre-processing step for PET 3D data, specifically to correct for photon scatter and prompt gamma contamination before reconstruction by ImagenPRO®. The FDA clearance is based on a determination of substantial equivalence to predicate devices, rather than a clinical trial demonstrating specific performance metrics against pre-defined acceptance criteria.

Therefore, many of the requested elements regarding acceptance criteria, performance metrics, and detailed study methodologies (like sample sizes, expert qualifications, adjudication, effects of AI on human readers, and detailed ground truth establishment methods for large datasets) are not present in this 510(k) summary. This type of summary typically focuses on demonstrating equivalence to legally marketed devices based on similar technological characteristics and intended use.

Here's a breakdown of what can be inferred and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Not applicable in the provided document. The 510(k) summary does not define specific numerical acceptance criteria (e.g., sensitivity, specificity, accuracy, or quantitative image quality metrics) that the device had to meet. Instead, the basis for clearance is "substantially equivalent" to predicate devices.

2. Sample Size Used for the Test Set and Data Provenance

Not explicitly stated for a formal test set with performance metrics. The summary mentions "testing and comparison of technological characteristics" but does not detail the nature or sample size of this testing, nor the provenance of any data used beyond the implicit use of "Fourier rebinned sinogram data from commercially available dedicated PET and PET/CT systems." It doesn't specify if this testing involved a distinct "test set" in the sense of a clinical validation study.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

Not applicable. Since specific performance metrics based on a defined "test set" and ground truth are not detailed in this 510(k) summary, information about experts for ground truth establishment is not provided.

4. Adjudication Method for the Test Set

Not applicable. As above, a formal adjudication method for a test set is not described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. The summary does not mention an MRMC study or any assessment of how human readers improve with or without AI assistance. The device is a pre-processing software, not directly an AI interpretive assistant for readers.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study Was Done

Yes (implicitly, for its intended technical function). The Imagen3D™ is described as a "software application" that "works in conjunction with ImagenPRO® to correct for photon scatter and prompt gamma contamination." Its performance, therefore, is its ability to execute this correction. The statement "Testing and comparison of technological characteristics and intended uses found that all components of the Imagen3D™ system are equivalent to the predicates" implies a standalone assessment of its functional capability as a scatter correction algorithm, even if not quantified with clinical performance metrics in this summary.

7. The Type of Ground Truth Used

Implicitly, the expected output of successful scatter correction. Given the device's function to "correct for photon scatter," the "ground truth" for its operation would be what an ideal, scatter-corrected PET 3D dataset should look like or how it should behave. This is typically established through physics models, phantom studies, or comparisons to established scatter correction methods on relevant data, rather than clinical outcomes or pathology for diagnostic performance. The summary doesn't explicitly state the methodology for establishing this ground truth (e.g., physical phantoms, simulated data, or comparison to established algorithms).

8. The Sample Size for the Training Set

Not applicable / Not provided. The summary does not describe any machine learning or AI models that would require a distinct "training set." The Imagen3D™ appears to be a rule-based or algorithmic scatter correction software rather than a learned model.

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

Not applicable / Not provided. Since there's no mention of a training set, the establishment of ground truth for such a set is not detailed.

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