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ADAC MCD-AC option to ADAC Dual Head Emission Tomographic System produces images of biodistribution of positron-emitting radioisotopes previously administered to the human body. The system is intended to provide an enhancement to the emission images acquired using the ADAC MCD System by correcting for attenuation effects in the human body.

MCD-AC is a system that will be marketed as an optional addition to the ADAC EPIC-MCD Gamma Camera System (e.g., Vertex+, any other ADAC camera in a dual-head configuration which can take 180° images). MCD-AC is short for Molecular Coincidence Defection Attenuation Correction, and is a modification to the EPIC-MCD system, cleared in 510k K952684. The MCD-AC uses the same principle of coincidence imaging used by the EPIC-MCD, but adds the image quality enhancing feature of attenuation correction. When a radioactive material is administered to a patient and the resulting gamma ray emission detected, attenuation is observed due to the internal parts (e.g., bones, breast tissue, etc.) of the patient. The resulting image is then an underestimation of the actual image, due to the presence of bone or tissue in the pathway of the emission radiation. When an image is generated representing the density of the patient, it is possible to compensate for the attenuation effects, since the attenuation of gamma rays are largely proportional to the density. Such an image can be obtained by sending a known flux of gamma rays from an external source, through the patient at different angles, registering what fraction is transmitted through the patient, and then reconstructing these projections to form an attenuation image (attenuation map). The count density in this image is inversely proportional to the density of the patient and can be used in the reconstruction of the emission image to compensate for gamma ray attenuation.

The provided text describes a 510(k) submission (K971980) for the ADAC MCD-AC, an optional addition to the ADAC EPIC-MCD Gamma Camera System designed to enhance emission images by correcting for attenuation effects.

Here's an analysis of the provided information against your requested points:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state quantitative acceptance criteria for the MCD-AC device. It focuses on demonstrating that the device produces similar image quality to predicate devices.

2. Sample size used for the test set and the data provenance

• Test Set Sample Size: "Images were obtained using phantoms and humans." The exact number of phantoms or humans is not specified.
• Data Provenance: The document does not specify the country of origin. Given ADAC Laboratories is located in Milpitas, CA, USA, it's highly probable the human data was collected in the USA. The study design (retrospective or prospective) is not explicitly stated, but "Images were obtained" implies a prospective collection for the purpose of this study.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not provide information on the number of experts, their qualifications, or their role in establishing ground truth for the test set. The evaluation seems to be a qualitative comparison of image quality rather than a quantitative diagnostic performance study requiring expert adjudication.

4. Adjudication method for the test set

The document does not specify any adjudication method for the test set. The assessment appears to be a direct comparison of image quality.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The document describes a technical modification (attenuation correction) to an existing gamma camera system and compares the resulting image quality to predicate devices. It does not evaluate the performance of human readers with or without the assistance of this specific AI (attenuation correction is a processing step, not necessarily an AI in the modern sense of deep learning) at making diagnostic interpretations. Therefore, no effect size for human reader improvement is provided.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Yes, a standalone performance assessment was effectively done. The study described focuses on the "single source attenuation correction technique on MCD cameras" and evaluates the "quality of the images produced" by the device itself, both with phantoms and humans. This is a technical performance assessment of the algorithm's output (images) rather than a diagnostic performance study involving human interpretation.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

The document does not explicitly state the type of ground truth used. For phantoms, the ground truth would inherently be "known" (e.g., known distribution of radioactivity). For human images, given the focus on "image quality" and "anatomical density," the "ground truth" implicitly refers to the physical reality of attenuation effects and their correction as observable in the images. It's not a diagnostic ground truth like pathology or outcomes.

8. The sample size for the training set

The document does not mention or specify a training set sample size. This type of device (attenuation correction algorithm) might not involve a distinct "training set" in the same way modern AI/machine learning models do. The algorithms would likely be deterministic or based on established physical models and signal processing techniques.

9. How the ground truth for the training set was established

As no training set is mentioned (see point 8), the document does not describe how ground truth for a training set was established.

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