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1. assist with regional assessment of human brain scans, through automated quantification of mean pixel values lying within standardized regions of interest (S-ROI's), and
2. assist with comparisons of the activity in brain regions of individual scans relative to normal activity values found for brain regions in FDG-PET scans, through quantitative and statistical comparisons of S-ROI's.
3. assist with comparisons of activity in brain regions of individual scans between two studies from the same patient, between symmetric regions of interest within the brain PET study, and to perform an image fusion of the patients PET and CT data
4. NeuroQ 3.6 provides added functionality to provide analysis of amyloid uptake levels in brain regions.

NeuroQ™ 3.6 has been developed to aid in the assessment of human brain scans through quantification of mean pixel values lying within standardized regions of interest, and to provide quantified comparisons with brain scans derived from FDG-PET studies of defined groups having no identified neuropsychiatric disease or symptoms, i.e., asymptomatic controls (AC). The Program provides automated analysis of brain PET scans, with output that includes quantification of relative activity in 240 different brain regions, as well as measures of the magnitude and statistical significance with which activity in each region differs from mean activity values of brain regions in the AC database. The program can also be used to compare activity in brain regions of individual scans between two studies from the same patient, between symmetric reqions of interest within the brain PET study, and to perform an image fusion of the patients PET and CT data. The program can also be used to provide analysis of amyloid uptake levels in the brain. This program was developed to run in the IDL operating system environment, which can be executed on any nuclear medicine computer systems which support the IDL software platform. The program processes the studies automatically, however, user verification of output is required and manual processing capability is provided.

The provided text describes the NeuroQ™ 3.6 device, its intended use, and its equivalence to previously cleared devices. However, it does not contain specific acceptance criteria for performance metrics (like sensitivity, specificity, accuracy, or statistical thresholds) or a detailed study description with specific results that would "prove" the device meets such criteria. Instead, it references previous validation studies and states general conclusions about safety and effectiveness.

Therefore, I cannot populate a table of acceptance criteria and reported performance, nor can I provide detailed information for many of the requested points because that specific data is not present in the provided 510(k) summary. The summary focuses on establishing substantial equivalence based on prior versions and a general statement of in-house testing.

Here's a breakdown of what can and cannot be answered based on the provided text:

1. A table of acceptance criteria and the reported device performance

• Cannot be provided. The document does not specify any quantitative acceptance criteria or reported performance metrics (e.g., specific accuracy, sensitivity, specificity values, or statistical thresholds) that the device was tested against. It states that validation for modifications can be found in "Item H. Testing & Validation," but this item itself is not included in the provided text.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Cannot be fully provided. The document mentions "clinical validation studies submitted in our previous 510(k) K041022 and 510(k) #: K072307" for the initial program and earlier versions. For the current version (3.6) it only refers to "in-house testing" and "final in-house validation results."
  • Sample Size (Test Set): Not specified for NeuroQ™ 3.6.
  • Data Provenance (country of origin, retrospective/prospective): Not specified for NeuroQ™ 3.6. The reference database is described as "brain scans derived from FDG-PET studies of defined groups having no identified neuropsychiatric disease or symptoms, i.e., asymptomatic controls (AC)," but no details on its origin are given.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Cannot be provided. The document does not describe how ground truth was established for any test set or mention specific experts involved in such a process for NeuroQ™ 3.6.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Cannot be provided. The document does not describe any adjudication method for a test set.

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, an MRMC comparative effectiveness study is not described as being performed. The document states the program "serves merely as a display and processing program to aid in the diagnostic interpretation...it was not meant to replace or eliminate the standard visual analysis." It emphasizes the physician's ultimate responsibility and integration of all information. There is no mention of a study comparing human reader performance with and without AI assistance, or any effect size.

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

• Yes, implicitly, to some extent, but with a critical caveat. The device itself performs "automated analysis" and provides "quantification of relative activity." This suggests standalone algorithmic processing.
• Caveat: The document explicitly states, "The program processes the studies automatically, however, user verification of output is required and manual processing capability is provided." It also says it is "not meant to replace or eliminate the standard visual analysis" and that the physician "should integrate all of the patients' clinical and diagnostic information." This strongly indicates that while the algorithm runs automatically, its performance is not intended to be "standalone" in a diagnostic sense, as human-in-the-loop verification and interpretation are always required. No specific "standalone performance" metrics are provided.

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

• Cannot be explicitly stated. The document describes a "reference database" of "asymptomatic controls (AC)" used for comparison. This implies a ground truth of "normalcy" based on the absence of identified neuropsychiatric disease or symptoms. However, the precise method of establishing this normal status (e.g., through long-term follow-up, expert clinical assessment, other diagnostic tests) is not detailed. For patient studies, the tool provides quantitative results to be integrated by a physician, but doesn't mention a specific "ground truth" used to validate its diagnostic accuracy in patient cases.

8. The sample size for the training set

• Cannot be provided. The training set size for the algorithms is not mentioned. The document refers to a "reference database" of asymptomatic controls, but its size is not specified.

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

• Partially described for the "reference database." The "reference database" consists of "brain scans derived from FDG-PET studies of defined groups having no identified neuropsychiatric disease or symptoms, i.e., asymptomatic controls (AC)." This indicates that the ground truth for this reference is the absence of neuropsychiatric disease or symptoms. However, the specific methods (e.g., detailed clinical evaluation, exclusion criteria, follow-up) used to establish this "asymptomatic" status are not provided. The document does not explicitly discuss a separate "training set" and associated ground truth, but rather a "reference database" for comparison.

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