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For use in the acquisition, processing, display, and analysis of planar images of the thyroid and other small organs.

The Scandia-45 is a high resolution, SFOV digital gamma camera for thyroid and small organs imaging. The Scandia-45, is made up of a single, small-field detector assembled with high optical and mechanical quality. The systems has 45 high quantum efficiency photomultipliers characterized by improved energy resolution, magnetic shielding and long-term stability and utilizes a compact, highly integrated, one board, easily serviceable construction without tuning potentiometers. The acquisition console has full-digital electronics, including fast PCI bus acquisition interface. The system also has a light-weight, easilyadjustable gantry and light, easily-exchangeable microcast collimators.

The Scandia-45 device's performance was evaluated through NEMA NU1 phantoms and clinical imaging in human subjects.

Here's a breakdown of the acceptance criteria and the study details:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• NEMA NU1 Phantoms: The sample size for the phantom testing is not explicitly stated, but it would involve a set of calibrated phantoms as defined by the NEMA NU1 standard.
• Clinical Images: "Clinical images were obtained using the Scandia-45 in human subjects." The exact number of human subjects is not specified in the provided text.
• Provenance: The clinical images were obtained from "human subjects," implying a prospective collection within a clinical setting. While the specific country of origin is not mentioned, it would typically be the country where the manufacturer (Scandia Corporation, based in Urbandale, Iowa, USA) conducts its studies or where the device is intended for initial market release.

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

The document does not explicitly state the number of experts or their qualifications used to establish ground truth for the clinical images. The phrasing "Image quality was at least equal to images produced by reference predicate devices" suggests a subjective comparison, likely by experienced personnel, but details are not provided. For NEMA phantom tests, the "ground truth" is inherent in the known physical properties and measurements of the phantoms themselves, not requiring expert anatomical interpretation.

4. Adjudication Method for the Test Set:

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for either the NEMA phantom tests or the clinical image quality assessment. The comparison for clinical images appears to be a direct qualitative comparison to images from predicate devices.

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

The document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was performed to assess how much human readers improve with AI vs. without AI assistance. The Scandia-45 is a gamma camera system, a medical imaging device, and the evaluation focuses on its inherent performance characteristics and image quality, not specifically on an AI assistance component for human readers.

6. Standalone Performance:

Yes, a standalone performance evaluation was done. The performance testing (NEMA NU1 phantoms) and the generation of clinical images with the Scandia-45 itself directly evaluate the algorithm/device performance without explicit human-in-the-loop assistance being part of the primary performance claim. The "image quality" assessment for clinical images is comparing the output of the Scandia-45 device standalone against predicate devices.

7. Type of Ground Truth Used:

• For NEMA NU1 Phantoms: The ground truth is established by the physical properties and known measurements of the NEMA NU1 phantoms, which are industry standards for characterizing gamma camera performance.
• For Clinical Images: The ground truth is implied to be a qualitative assessment of image quality compared to "reference predicate devices." This suggests a consensus among experienced observers regarding acceptable diagnostic image quality, rather than a definitive "pathology" or "outcomes" ground truth in this context. The focus is on the diagnostic capability of the image, rather than the definitive diagnosis itself for specific conditions.

8. Sample Size for the Training Set:

The document does not mention a training set in the context of device performance. This device is a hardware imaging system, and its performance evaluation does not involve machine learning models that require a separate training set.

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

As there is no mention of a training set or a machine learning component for this device in the provided text, this question is not applicable.

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