(210 days)
The NeuroQ™-PET DP program is indicated to perform a quantitative analysis of FDG-PET brain scans using a ROI count method. NeuroQ™ 3.0 provides added functionality which allows for analyzing the difference between two FDG-PET brain studies for the same patient, calculating values within user defined regions of interest, and displaying CT and PET brain studies for the patient.
NeuroQ™ 3.0 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 regions of interest within the brain PET study, and to perform an image fusion of the patients PET and CT data. 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 document is a 510(k) summary for NeuroQ 3.0, a display and analysis program for PET Brain studies. It details the device's intended use and substantial equivalence to a predicate device but does not contain detailed information about specific acceptance criteria or a dedicated study proving performance against such criteria for NeuroQ 3.0 itself.
Instead, it refers to the validation of the initial program, NeuroQ™ - PET DP, and states that "The validation for modifications in version 3.0 can be found in Item F, Testing & Validation of this 510(k)". However, Item F is not included in the provided text.
Therefore, many of the requested details cannot be extracted directly from the given information.
Here's what can be inferred or stated based on the provided text:
1. A table of acceptance criteria and the reported device performance
- Cannot be provided. The document refers to validation in "Item F, Testing & Validation" which is not included. It broadly claims "safety and effectiveness" based on in-house testing and clinical validation studies for the previous version, but no specific quantifiable acceptance criteria or performance metrics for NeuroQ 3.0 are given.
2. Sample size used for the test set and the data provenance
- Cannot be provided directly for NeuroQ 3.0. The document mentions "clinical validation studies submitted in our previous 510(k) K041022" for the initial program, but details for NeuroQ 3.0's test set are not present.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Cannot be provided. This information would typically be detailed within the "Testing & Validation" section (Item F) which is missing.
4. Adjudication method
- Cannot be provided. This information is not present in the given text.
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
- Not explicitly stated for NeuroQ 3.0. The device is described as "a display and processing program to aid in the diagnostic interpretation" and not meant to "replace or eliminate the standard visual analysis." It performs automated analysis but requires "user verification of output." While it assists physicians, an MRMC comparative effectiveness study to quantify human reader improvement with AI assistance is not described in this summary.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Yes, implicitly. The device "provides automated analysis of brain PET scans" and "quantification of relative activity in 240 different brain regions, as well as measures of the magnitude and statistical significance." This suggests the algorithm performs an analysis independently of immediate human interaction, though "user verification of output is required." However, specific standalone performance metrics are not given.
7. The type of ground truth used
- Cannot be provided directly. The document refers to comparing patient studies to a "reference database" of "FDG-PET studies of defined groups having no identified neuropsychiatric disease or symptoms, i.e., asymptomatic controls (AC)." This suggests "normal" or "healthy" controls form a basis for comparison, but the specific type of ground truth for assessing the accuracy of its quantitative analyses (e.g., against pathology, clinical outcomes, or expert consensus on abnormal findings) is not detailed.
8. The sample size for the training set
- Cannot be provided directly. The document mentions an "AC database" (asymptomatic controls) used for comparison, but the size of this database, or any other specific training set for model development (if applicable to this type of analysis program), is not disclosed.
9. How the ground truth for the training set was established
- Implicit for the AC database: The text states the AC database consists of "FDG-PET studies of defined groups having no identified neuropsychiatric disease or symptoms." This implies a clinical assessment or screening process to confirm the asymptomatic status, which serves as their "ground truth" for normality. However, the specific methodology of this establishment is not detailed.
§ 892.1200 Emission computed tomography system.
(a)
Identification. An emission computed tomography system is a device intended to detect the location and distribution of gamma ray- and positron-emitting radionuclides in the body and produce cross-sectional images through computer reconstruction of the data. This generic type of device may include signal analysis and display equipment, patient and equipment supports, radionuclide anatomical markers, component parts, and accessories.(b)
Classification. Class II.