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The UniCam Evo Software package is indicated for nuclear medicine image post-processing software for scinitigraphic and SPECT imaging. UniCam Evo is indicated for processing and quantification of planar and tomographic bone scintigraphy scans, processing of cerebrovascular scintigraphic scans, processing of planar and tomographic cardiovascular scintigraphic studies, renal dynamic scans, planar and SPECT lung scintigraphy, planar gastrointestinal scintigraphic scans, liver scintigraphy, thyroid scintigraphy and displaying multimodal image fusion between SPECT/CT/MR/PET/ultrasound modalities.

UniCam Evo is a software package for processing planar, whole body, dynamic planar and SPECT nuclear medicine data sets. The UniCam Evo Software is used for digital images capture, pre-processing, saving, post-processing, multiplanar reconstruction, multimodal image fusion, multimodal image registration, 3D rendering, viewing, archiving and transferring between image viewing workstations. The UniCam Evo Software is intended for nuclear medicine specialists, nuclear medicine radiologists, or trained medicine technologists. The operator shall have basic computer operation skills.

The software loads scintigraphic data sets in Dicom 3.0 format from the local database or queries the corresponding dicom data from a PACS archive. The operator may perform analysis on the data, ROI analysis, tomographic reconstruction, organ dependent procedure steps and the software displays the results in form of images, numerical data or curves. The operator may print the results, store as an image or dicom secondary capture. Reconstructed transversal, coronal and sagittal slices can be also stored in Dicom format.

The data to be processed can be transferred via the DICOM 3.0 Standard to another Nuclear Medicine Workstations of another Manufacturer or from a Gamma Camera / SPECT acquisition workstation.

The software runs under standard Windows operating systems, such as XP, 7, 8, 10, 11.

The document provided does not contain a detailed study with specific acceptance criteria and performance metrics for the UniCam Evo Software. Instead, it describes a 510(k) Premarket Notification for the device, which focuses on demonstrating substantial equivalence to legally marketed predicate devices.

Here's what can be inferred and what is not available from the provided text:

No Specific Acceptance Criteria and Device Performance Table:
The document does not include a table of acceptance criteria with reported device performance metrics (e.g., accuracy, sensitivity, specificity values). The verification and validation testing mentioned are to confirm that "product specifications are met" and that "functional testing met for the acceptance of the device," but the specific quantifiable metrics are not detailed.

Inferred Study Type:
The provided text suggests that the study performed was primarily focused on verification and validation (V&V) testing to ensure the software's functionality, design adherence to specifications, and to support the claim of substantial equivalence to predicate devices. It's a general claim about testing rather than a specific clinical performance study.

Information Not Found in the Document:

1. A table of acceptance criteria and the reported device performance: This is not provided. The V&V testing is mentioned generally, stating all tests passed and met acceptance criteria, but no specific performance metrics are quantified.
2. Sample sizes used for the test set and the data provenance: Not mentioned. It states "phantom studies are generated" and "a carefully selected series of studies," but no specific numbers or patient demographics/origin are given.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned.
4. Adjudication method for the test set: Not mentioned.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance: An MRMC study is not described. The document focuses on the software's inherent functionality and its equivalence to predicate devices, not on human-in-the-loop performance improvement with the AI. The device is described as "Medical image management and processing system" and "nuclear medicine image post-processing software," which typically doesn't involve AI assistance in the direct diagnostic interpretation sense that would necessitate an MRMC study for reader improvement.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The "Nonclinical testing summary" broadly suggests standalone testing of the software's functions (e.g., "results from the current version with the results from reference values wherever possible the phantom studies are generated and the results from the program are validated with the expected values calculated in an independent way"), but specific performance metrics are absent.
7. The type of ground truth used: It mentions using "expected values calculated in an independent way" for phantom studies and "values from the published original reference" for a "carefully selected series of studies." This suggests a combination of simulated/calculated truth (for phantoms) and potentially literature-based/expert consensus/established clinical outcomes (for reference values), but it's not explicitly detailed.
8. The sample size for the training set: Not applicable based on the description of the device as post-processing software rather than a machine learning model that requires a training set. The descriptions focus on the functionality and data handling.
9. How the ground truth for the training set was established: Not applicable, as there's no mention of a machine learning component requiring a training set and corresponding ground truth.

Key Statements Regarding Acceptance and Study:

• Nonclinical testing summary: "Verification and validation testing confirms that product specifications are met which are equivalent in design and technological characteristics as the predicate devices. The testing results support that the functional testing met for the acceptance of the device. The UniCam Evo Software passed all testing and supports the claims of substantial equivalence to the predicate devices."
• Summary of the performed tests: "All performed tests passed and have met the acceptable test criteria. There were no test failures."
• Summary conclusion: "Bench and clinical data demonstrate that processing methods, images and results are equivalent comparing to the predicate devices. No adverse effect has been detected."

In summary, the provided FDA 510(k) clearance letter and summary are a regulatory document demonstrating substantial equivalence. They indicate that internal verification and validation testing was conducted and passed, but they do not provide the detailed public study results and performance metrics that would typically be found in a clinical trial report or a scientific publication. The "acceptance criteria" here are that the software correctly performs its specified post-processing functions and that it is substantially equivalent to existing cleared devices based on functional checks, rather than clinical performance thresholds like sensitivity/specificity for a diagnostic AI.

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