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The WBR- HR is indicated for the acquisition, formatting and storage of scintigraphy camera output data. It is capable of processing and displaying the acquired information in traditional formats, as well as in pseudo three dimensional renderings, and in various forms of animated sequences, showing kinetic attributes of the image organs.

The WBR - HR is an image processing system, which is interfaced to gamma cameras. The camera-acquired data is reconstructed by the WBR - HR, which utilizes parallel and non - parallel beams and produces high resolution images. The images can be transferred to any other PACS device, which is DICOM or Interfile compatible.

The provided text is a 510(k) summary for the WBR-HR device. It describes the device, its intended use, and claims substantial equivalence to a predicate device. However, it does not contain the specific details required to complete your request for acceptance criteria and a detailed study description.

The document states: "Bench and clinical data demonstrate that reconstructed images are equivalent or of better resolution comparing to the images of the predicate device. No adverse affects have been detected." This is a summary statement of the study's conclusion, not a detailed description of the study itself.

Therefore, I cannot provide the requested information in the format you specified. Here's why and what's missing:

Missing Information:

• Acceptance Criteria: The document does not define specific performance metrics (e.g., resolution, signal-to-noise ratio, diagnostic accuracy) that the device needed to meet to be deemed "equivalent or of better resolution."
• Reported Device Performance: While it states "equivalent or of better resolution," it doesn't provide quantitative results or specific measurements for the WBR-HR or the predicate device.
• Sample Size for Test Set: No information is given about the number of images or patients used in the clinical or bench evaluations.
• Data Provenance: The country of origin and whether the data was retrospective or prospective are not mentioned.
• Number of Experts and Qualifications: No details on radiologists or other experts involved in evaluating the images or establishing ground truth.
• Adjudication Method: Not specified.
• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: No mention of such a study or any effect size related to AI assistance. The WBR-HR is an image processing system, not explicitly an "AI" device as understood today.
• Standalone Performance: While it processes images, the context implies comparison to a predicate, not a standalone evaluation against a clinical gold standard in terms of diagnostic utility.
• Type of Ground Truth: Not specified (e.g., pathology, clinical follow-up, expert consensus).
• Sample Size for Training Set: The document is about a 510(k) submission, and the WBR-HR is described as an image processing system, not an AI/machine learning device that would typically have a "training set" in the modern sense.
• Ground Truth for Training Set: Not applicable given the above.

Conclusion:

Based on the provided text, it is not possible to fill out the table and detailed study information as requested because the document is a high-level summary of a 510(k) submission, not the detailed study report itself. It simply states that data demonstrating equivalence or better resolution was provided to the FDA.

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The Cedars-Sinai Motion Correction (MoCo) software program is intended for use in correcting patient motion artifacts in SPECT data acquired on a nuclear medicine gamma camera system.

The MoCo program is an independent, standalone software application developed by Cedars-Sinai Medical Center for the automatic and manual correction of SPECT acquisition motion artifacts from gated and ungated projection datasets. MoCo is the most popular motion correction application in the field of nuclear myocardial perfusion SPECT imaging. The software has the same indication for use and function as the Motion Correction function module of Mirage software (Segami Corporation, K972886), which is currently being used on Digirad 2020tc SPECT Imaging systems.

The provided document describes the Cedars-Sinai Motion Correction (MoCo) Software, a standalone application for correcting patient motion artifacts in SPECT data. However, it does not contain information regarding detailed acceptance criteria, a specific study proving it meets these criteria, or a table comparing acceptance criteria to device performance metrics beyond a general statement of "Functionality tests were conducted to demonstrate that the MoCo software application functioned as per its specifications. All tests passed with the actual results substantially matching the expected results."

Here's an analysis of the available information, noting what is missing based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

Not available in the provided document. The submission states that functionality tests were conducted and passed, but it does not specify the quantitative acceptance criteria or the reported performance metrics (e.g., specific accuracy, sensitivity, or specificity values) from these tests.

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

Not available in the provided document. The document mentions "functionality tests" but does not detail the number of cases or datasets used in these tests. Information on the country of origin of the data or whether it was retrospective or prospective is also not provided.

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

Not available in the provided document. The method and number of experts for establishing ground truth for any test set are not mentioned.

4. Adjudication Method for the Test Set

Not available in the provided document. No information is provided regarding any adjudication method (e.g., 2+1, 3+1, none) used for the test set.

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

Not available in the provided document. There is no mention of an MRMC study being conducted, nor any effect size regarding human reader improvement with or without AI assistance.

6. Standalone Algorithm Performance

The document states that the MoCo program is an "independent, standalone software application." The functionality tests described imply a standalone evaluation, where the software's performance against its specifications was assessed. However, specific performance metrics are not given.

7. Type of Ground Truth Used

Not available in the provided document. The document does not specify how the "expected results" for the functionality tests were determined or what type of ground truth (e.g., expert consensus, pathology, outcomes data) was used.

8. Sample Size for the Training Set

Not available in the provided document. The document does not provide any information about a training set or its sample size.

9. How Ground Truth for the Training Set Was Established

Not available in the provided document. Since no training set is mentioned, there is no information on how its ground truth was established.

Summary of available information related to testing:

The document mentions "Functionality tests were conducted to demonstrate that the MoCo software application functioned as per its specifications. All tests passed with the actual results substantially matching the expected results." This indicates that some form of internal validation was performed to ensure the software performed as designed, but the details of this validation (specific criteria, data used, and quantitative outcomes) are not present in this submission. The submission primarily focuses on the device's classification, intended use, and substantial equivalence to predicate devices, rather than a detailed performance study with quantifiable acceptance criteria.

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