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510(k) Data Aggregation
(202 days)
cNeuro cDAT
cNeuro™ cDAT is intended for use by Nuclear Medicine or Radiology practitioners and referring physicians for display, processing, and reporting of Nuclear Medicine Imaging data.
cNeuro™ cDAT enables visual evaluation and quantification of ioflupane I 123 (DaTscan™) images. The software enables automated quantification of tracer uptake and comparison with the corresponding tracer uptake in healthy subjects as provided by normal population databases of ioflupane I 123 (DaTscan™) images. cNeuro™ cDAT assists in detection of loss of functional dopaminergic neuron terminals in the striatum, which is correlated with Parkinson disease or Dementia with Lewy Bodies (DLB).
cNeuro™ cDAT has not been demonstrated to improve ioflupane I 123 reader performance for distinguishing positive from negative patients. This device should not be used to deviate from ioflupane I 123 dosing and administration instructions. Refer also to ioflupane I 123 prescribing information for instructions.
cNeuro™ cDAT is Software as a Medical Device (SaMD) intended to aid physicians in the evaluation of the loss of functional dopaminergic neuron terminals in the striatum through the quantification of ioflupane I 123 (DaTscan™) images. cNeuro™ cDAT is a fully automated image analysis software tool that provides tools for viewing DaTscan™ images and quantification of tracer uptake in the striatum with comparison to reference data from healthy controls. The results are summarized in a PDF-report.
cNeuro™ cDAT quantifies DaTscan™ brain images and computes Striatal Binding Ratios (SBRs) for different volumes of interest (VOIs). SBRs are computed by subtracting the uptake in a background VOI from the tracer uptake in the target VOI and then dividing this value with uptake in a background VOI. Results are compared with normative values in a reference database and z-scores are presented.
cNeuro™ cDAT quantifies the data by registering the images to a template where VOIs are defined. Quantification results are summarized in PDF-reports that are sent to the organization's PACS. cNeuro™ cDAT also offers interactive review of the DaTscan™ images and the quantification results in a browser-based viewer.
Here's a breakdown of the acceptance criteria and study details based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Performance Requirement) | Reported Device Performance (cNeuro™ cDAT) |
|---|---|
| Percentage of patients with paired z-value outputs differing by >0.5 from the predicate device | Ranged from 5.4% to 7.6% for the left and right putamen, caudate, anterior putamen, and posterior putamen. This implies 92.4% to 94.6% of patients had z-value outputs within ±0.5 of the predicate. |
| Compliance with DICOM Standard (NEMA PS 3.1 - 3.20 (2021)) | Complies with NEMA PS 3.1 - 3.20 (2021) Digital Imaging and Communications in Medicine (DICOM) Set (Radiology) standard. |
| Adequate quality of displayed images and other software functions to not present a hazardous situation. | Failure or latent flaw of software functions would not present a hazardous situation with a probable risk of death or serious injury. (This is a safety assessment rather than a specific performance metric, but it functions as an acceptance criterion for safety). |
2. Sample Size for Test Set and Data Provenance
- Sample Size for Test Set: Imaging from 370 patients was initially available. A subset of 48 images could not be processed with the predicate device and were excluded. Therefore, the effective test set size used for comparison was 322 patients (370 - 48).
- Data Provenance: The imaging data was obtained from third-party clinical investigations (NCT01952678, NCT01141023). The text does not explicitly state the country of origin, but clinical trial identifiers common in the US suggest it could be US-based or international. The data is retrospective as it was available following these completed clinical investigations.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of those Experts
The document does not provide information on the number or qualifications of experts used to establish ground truth for the test set. The performance testing was a comparison against a predicate device's output (z-values), not against a separate expert-defined ground truth for the test set.
4. Adjudication Method for the Test Set
The document does not specify an adjudication method for the test set in the context of expert review. As noted above, the testing involved a direct comparison of z-value outputs between the subject device and the predicate device.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted to assess human reader improvement with AI assistance. The Indications for Use section explicitly states: "cNeuro™ cDAT has not been demonstrated to improve ioflupane I 123 reader performance for distinguishing positive from negative patients."
6. Standalone (Algorithm Only) Performance Study
Yes, a standalone performance study was done. The performance testing described involved the cNeuro™ cDAT software (the algorithm) independently processing patient images and generating z-value outputs, which were then compared to the predicate device's z-value outputs. There is no mention of a human-in-the-loop component in this specific performance comparison.
7. Type of Ground Truth Used
The "ground truth" for the performance comparison was the output values (z-scores) generated by the predicate device (DaTQUANT Application / GE Medical Systems, LLC.) for the same patient images. This is a comparison against an established, legally marketed device's quantitative outputs, rather than a clinical ground truth (like pathology or outcomes data) directly determining disease status. The device "assists in detection of loss of functional dopaminergic neuron terminals," but the performance study focused on agreement with the predicate's quantification.
8. Sample Size for the Training Set
The document does not explicitly state the sample size for the training set used to develop the cNeuro™ cDAT algorithm. It mentions that "Data from DaTscan™ studies of healthy controls is used to define a reference normal database," which is part of the device's functionality, but this is distinct from the training data for the image processing and quantification algorithm itself.
9. How Ground Truth for the Training Set Was Established
The document does not provide details on how the ground truth for the training set was established for the image processing and quantification algorithm. It does mention that the "Normal Database" used for comparison within the device is defined from "Data from DaTscan™ studies of healthy controls." This normal database would have its own "ground truth" definition (i.e., these individuals were determined to be healthy controls), but this isn't directly the ground truth for training the core quantification algorithm.
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