(462 days)
GeoSource is intended for use by a trained/qualified EEG technologist or physician on both adult and pediatric subjects at least 3 years of age for the visualization of human brain function by fusing a variety of EEG information with rendered images of an idealized head model and an idealized MRI image.
GeoSource is an add-on software module to EGI's Net Station software and can only be used on EEG data generated by EGI hardware. It runs on a personal computer. It is used to approximate source localization of EEG signals and visualize those estimated locations. It uses the linear inverse methods LORETA, LAURA, and sLORETA and the sphere and Finite Difference forward head models.
Here's a summary of the acceptance criteria and study details for the GeoSource device, based on the provided 510(k) notification:
Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria
1. A table of acceptance criteria and the reported device performance
The primary acceptance criterion for GeoSource was demonstrating substantial equivalence to predicate devices in terms of source localization accuracy. The study aimed to show that the GeoSource algorithms (LORETA, sLORETA, LAURA with FDM) provided similar source localization results to the predicate algorithm (LORETA with spherical head model).
Since this was a substantial equivalence submission, specific quantitative performance metrics and acceptance thresholds (e.g., sensitivity > X%, accuracy > Y%) are not explicitly stated in the provided text. The "reported device performance" is essentially the conclusion that the GeoSource algorithms were found to be substantially equivalent to the predicate device.
| Acceptance Criteria | Reported Device Performance (as concluded by the study) |
|---|---|
| Substantial equivalence in source localization accuracy to predicate device algorithm (LORETA with spherical head model). | The proposed GeoSource algorithms (LORETA, sLORETA, and LAURA with GeoSource finite difference model [FDM]) were demonstrated to be substantially equivalent to the predicate device algorithm (LORETA using a spherical head model). |
2. Sample size used for the test set and the data provenance
- Sample Size for Test Set: 20 epilepsy subjects.
- Data Provenance: Retrospective data analysis. Country of origin is not explicitly stated but implied to be from the University of Washington's Regional Epilepsy Center (USA).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Number of Experts: Three.
- Qualifications of Experts: Experienced epileptologists from the University of Washington's Regional Epilepsy Center. Specific years of experience are not mentioned.
4. Adjudication method for the test set
The adjudication method involved each of the three experienced epileptologists reviewing the source localization results for each algorithm and summaries of the postoperative reports. They were then asked to rate whether each of the four algorithm solutions (GeoSource LORETA, sLORETA, LAURA with FDM, and predicate LORETA with spherical head model) were located within the resected brain regions. The text does not specify a specific consensus or majority voting method (e.g., 2+1, 3+1). It states "The results demonstrated...", implying a collective finding rather than individual expert opinions being the final ground truth.
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
- Was an MRMC comparative effectiveness study done? No, not in the typical sense of evaluating human reader performance with and without AI assistance. This study focused on the performance of the algorithms themselves by having experts evaluate the algorithm's outputs in relation to the ground truth. It did not directly measure how much human readers improved by using the GeoSource software.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
- Was a standalone study done? Yes, in essence. The study's primary goal was to evaluate the GeoSource algorithms' source localization accuracy in a standalone manner, with expert epileptologists providing the "ground truth" assessment of whether the algorithm's output correlated with the resected region. The experts were evaluating the algorithms' predictions, not using the algorithm as assistance for their own interpretation.
7. The type of ground truth used
- Type of Ground Truth: A combination of clinical and outcome data:
- Clinical Neurophysiologist review: Identification and averaging of spikes in EEG data.
- Operative data: Descriptions of the resected zone from surgery.
- Outcomes Data: Postoperative Engel 1 or 2 determination (indicating good seizure control after resection).
- Expert Consensus/Evaluation: The decision of three experienced epileptologists on whether the source localization algorithm's output was within the resected brain regions, using all available clinical information (postoperative reports, resected zone descriptions) as context.
8. The sample size for the training set
The document does not provide information about a separate "training set" for the GeoSource algorithms. The mentioned clinical study was a retrospective data analysis of subjects who had previously undergone resection surgery, and this data was used to test the algorithms' performance, not to train them. Source localization algorithms like LORETA, sLORETA, and LAURA are typically model-based and do not require a separate "training set" in the same way machine learning models do.
9. How the ground truth for the training set was established
As no specific training set is identified for the GeoSource algorithms, the question of how its ground truth was established is not applicable in the context of this 510(k) submission. These linear inverse methods are derived from mathematical and biophysical principles rather than being "trained" on a dataset with a predefined ground truth.
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GeoSource 510(k) Notification
510(k) SUMMARY
DEC 2 1 2010
| Submitter's name: | Electrical Geodesics, Inc.1600 Millrace Drive, Suite 307, Eugene, OR 97403 | ||
|---|---|---|---|
| Contact name and address: | Paul HolmanElectrical Geodesics, Inc.1600 Millrace Dr., Suite 307, Eugene, OR 97403541-687-7962 | ||
| Date summary prepared: | 12/21/10 | ||
| Device name: | . | ||
| Proprietary name: | GeoSource | ||
| Common or usual name: | Electroencephalograph software | ||
| Classification name: | Electroencephalograph, Class II, 882.140084 OLX, Source Localization Software forElectroencephalograph or Magnetoencephalograph |
Legally marketed devices for substantial equivalence comparison:
| 510(k) Number | Product Code | Trade Name | Manufacturer |
|---|---|---|---|
| K002631 | GWQ882.1400 | Electroencephalograph Softwareeemagine EEG | eemagine MedicalImaging Solutions GmbH |
| K001781 | GWQ882.1400 | CURRY Multimodal NeuroimagingSoftware | Neurosoft, Inc. |
Description of the device:
GeoSource is an add-on software module to EGI's Net Station software and can only be used on EEG data generated by EGI hardware. It runs on a personal computer. It is used to approximate source localization of EEG signals and visualize those estimated locations. It uses the linear inverse methods LORETA, LAURA, and sLORETA and the sphere and Finite Difference forward head models.
Intended use of device:
GeoSource is intended for use by a trained/qualified EEG technologist or physician on both adult and pediatric subjects at least 3 years of age for the visualization of human brain function by fusing a variety of EEG information with rendered images of an idealized head model and an idealized MRI image.
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GeoSource 510(k) Notification
Technological characteristics:
| Characteristic | GeoSourceK092844 | ElectroencephalographSoftware eemagine EEGK002631 | CURRY MultimodalNeuroimaging SoftwareK001781 |
|---|---|---|---|
| Software only product? | Yes | Yes | Yes |
| EEG system | Geodesic EEG System using NetStation | Variety of systems | Variety of systems |
| Computer OS | Mac OS | MS-Windows based | MS-Windows XP based |
| Method of calculation | Idealized head model (average) | Idealized head model (average) | Idealized head model (average)Individualized head model |
| Method of display | Idealized MRI (average) | Idealized MRI (average) | Idealized MRI (average) |
| Source estimate methods: | |||
| Dipole fit | No | Yes | Yes |
| Linear inverse methods | LORETA, LAURA, sLORETA | No | LORETA |
| Forward head models | Sphere | Boundary Element Model (BEM) | SphereBoundary Element Model (BEM)Finite Element Model (FEM) |
| Finite Difference Model (FDM) |
Both GeoSource and CURRY use the LORETA linear inverse method and sphere head models. These were demonstrated to be substantially equivalent. Then a retrospective clinical study was done that the other linear inverse methods and head models gave similar results. Therefore, the linear inverse methods and forward head models have been shown to be substantially equivalent.
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Non-clinical testing conducted:
Software verification and validation testing has been conducted. This includes verification of the algorithms and checks of accuracy.
Clinical testing:
In order to compare the source localization accuracy of the GeoSource as compared to that of the predicate device, a retrospective data analysis of 20 epilepsy subjects aged 3 to 55 who had previously undergone resection surgery was provided. The analysis compared the source localization accuracy of the GeoSource software algorithms (i.e., LORETA, sLORETA, and LAURA with the GeoSource finite difference model [FDM]) to that of the predicate algorithm (i.e., LORETA using a spherical head model). All subjects had previously undergone high density (> 128 electrodes) EEG analysis prior to resection surgery, had operative data available that described the resected zone, and were determined to be Engel 1 or 2 postoperatively. The study included subjects with temporal and extratemporal resected zones.
Each subject's EEG data was reviewed by a clinical neurophysiologist who identified spikes within the EEG. Spikes were then grouped according to topographic distribution and then averaged relative to the peak of the spike to increase the signal-to-noise ratio. The average of this dominant group was used in the source estimate. The time point used in the source estimate was the rising slope of the spike. The data were then run through the GeoSource software algorithms (i.e., LORETA, sLORETA, and LAURA with the GeoSource finite difference model [FDM]) and the predicate algorithm (i.e., LORETA using a spherical head model).
Three experienced epileptologists from the University of Washington's Regional Epilepsy Center were provided the source localization results along with summaries of the postoperative reports and asked to rate whether each of the four algorithm solutions (i.e., LORETA, sLORETA, and LAURA with the GeoSource finite difference model [FDM] and the LORETA using a spherical head model) were located within the resected brain regions. The results demonstrated that the proposed GeoSource algorithms were substantially equivalent to the predicate device algorithm.
Conclusions:
The conclusions drawn from the non-clinical and clinical tests demonstrate that GeoSource is as safe and effective as the predicate devices, Electroencephalograph Software eemagine EEG and CURRY Multimodal Neuroimaging Software.
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Image /page/3/Picture/1 description: The image shows the logo for the Department of Health & Human Services USA. The logo features a stylized eagle with three lines forming its body and wings. The eagle is enclosed in a circle with the text "DEPARTMENT OF HEALTH & HUMAN SERVICES USA" around the perimeter.
Food and Drug Administration 10903 New Hampshire Avenue Document Control Room -WO66-G609 Silver Spring, MD 20993-0002
Electrical Geodesics, Inc. c/o Mr. Paul Holman 600 Millrace Dr. Suite #307 Eugene, OR 97403
DEC 21 20100
Re: K092844
Trade/Device Name: GeoSource Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph (EEG) Regulatory Class: Class II Product Code: OLX Dated: November 16, 2010 Received: November 19, 2010
Dear Mr. Holman:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28. 1976. the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food. Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
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Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please go to http://www.fda.gov/AboutFDA/CentersOffices/CDRH/CDRHOffices/ucm115809.htm for the Center for Devices and Radiological Health's (CDRH's) Office of Compliance. Also, please note the regulation entitled. "Misbranding by reference to premarket notification" (21CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to
http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.
Sincerely yours,
E. Arthur Brown Jr.
Malvina B. Eydelman, M Director Division of Ophthalmic, Neurological, and Ear, Nose and Throat Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known):
Device Name: GeoSource
Indications for Use:
GeoSource is intended for use by a trained/qualified EEG technologist or physician on both adult and pediatric subjects at least 3 years of age for the visualization of human brain function by fusing a variety of EEG information with rendered images of an idealized head model and an idealized MRI image.
Prescription Use
(Part 21 CFR 80T Subpart D)
AND/OR
Over-The-Counter Use 21 CFR 801 Subpart
(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE OF NEEDED)
Concurrence of CDRH, Office of Device Evaluation (ODE)
signature
(Division Sign-Off) Division of Ophthalmic, Neurological and Ear, Nose and Throat Devices
510(k) Number K092844
§ 882.1400 Electroencephalograph.
(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).