(154 days)
Yes
The device description explicitly states that ICTA employs a "Bayesian formulation" and uses "a priori probabilities... computed from the training data set" to provide a detection variable. This is a clear indication of a machine learning approach, specifically a probabilistic model trained on data.
No
The device is described as a 'review tool' to assist clinical practitioners in the 'assessment of EEG traces' and specifically states, "This device does not provide any diagnostic conclusion about the patient's condition to the user." It also mentions that the software does not make 'final decisions that result in any automatic diagnosis or treatment'. These statements indicate no therapeutic function.
No
This device is a review tool to mark previously acquired sections of EEG recordings that may correspond to electrographic seizures. The document explicitly states: "This device does not provide any diagnostic conclusion about the patient's condition to the user." Instead, it assists clinical practitioners in the assessment of EEG traces, and the practitioners exercise professional judgment in using the information, reviewing and modifying the software's "events."
Yes
The device description explicitly states "ICTA is a software only product. It runs on a personal computer and requires no specialized hardware."
Based on the provided information, this device is an IVD (In Vitro Diagnostic).
Here's why:
- Intended Use: The software is intended to "mark previously acquired sections of the adult... EEG recordings... that may correspond to electrographic seizures, in order to assist qualified clinical practitioners... in the assessment of EEG traces." This clearly indicates the analysis of biological samples (EEG recordings are electrical signals from the brain) to provide information for a clinical assessment.
- Device Description: The software "identifies electroencephalographic activity that might correspond to seizures." This is a direct analysis of the EEG data.
- Input: The input is "EEG recordings (surface or intracranial)," which are biological samples.
- Performance Studies: The clinical studies evaluate the device's performance in detecting seizures in EEG recordings, using metrics like Positive Percent Agreement (Sensitivity) and False Detection Rate. This is typical for IVD devices that analyze biological data.
- Predicate Device: The mention of a predicate device (K090019; NeuroWorks Seizure Detector) which is likely also an IVD, further supports this classification.
While the device description states it "does not provide any diagnostic conclusion about the patient's condition to the user" and "does not make any final decisions that result in any automatic diagnosis or treatment," this does not preclude it from being an IVD. IVDs are tools that provide information derived from biological samples to aid in diagnosis or treatment decisions, but the final decision rests with the qualified clinical practitioner.
The analysis of EEG recordings, which are biological signals, for the purpose of assisting in the assessment of potential seizures falls squarely within the definition of an In Vitro Diagnostic device.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device.
Intended Use / Indications for Use
The ICTA software is intended as a review tool to mark previously acquired sections of the adult (greater than or equal to 18 years) EEG recordings (surface or intracranial) that may correspond to electrographic seizures, in order to assist qualified clinical practitioners, who will exercise professional judgment in using the information, in the assessment of EEG traces.
- Surface recordings must be obtained with full montage according to the standard 10/20 . system.
- Intracranial recordings must be obtained with depth electrodes (strips and/or grids). .
This device does not provide any diagnostic conclusion about the patient's condition to the user.
Product codes
OMB
Device Description
ICTA is a software only product. It runs on a personal computer and requires no specialized hardware. It identifies electroencephalographic activity that might correspond to seizures (referred as "events"). These events are then reviewed, accepted, modified and/or deleted by the qualified medical practitioner. The software does not make any final decisions that result in any automatic diagnosis or treatment. The EEG input is read from a file on the personal computer (or available across the network).
The software has two components: ICTA-S for analysis of surface EEG recordings and ICTA-D for analysis of intracranial recordings. Whether a particular module is active is determined by the user. The user also determines parameters that are needed for the algorithm to perform its intended task. None of the components is responsible for data acquisition, review or any other function different from analysis.
Mentions image processing
Not Found
Mentions AI, DNN, or ML
ICTA employs Bayesian formulation to provide a detection variable based on the probabilities that a given section of EEG contains a seizure-like activity. The a priori probabilities that a certain set of features represent seizure or non-seizure data were computed from the training data set. These probabilities are used by the detection method for all seizure detections.
Input Imaging Modality
EEG recordings (surface or intracranial), electrocorticographic (ECoG) recordings
Anatomical Site
Not Found
Indicated Patient Age Range
adult (greater than or equal to 18 years)
Intended User / Care Setting
qualified clinical practitioners, Medical professional trained in EEG analysis, Epilepsy Monitoring Unit
Description of the training set, sample size, data source, and annotation protocol
The a priori probabilities that a certain set of features represent seizure or non-seizure data were computed from the training data set. No further details provided.
Description of the test set, sample size, data source, and annotation protocol
ICTA-S Study:
Subject Population and Test Dataset: Scalp EEG recordings from patients with medically refractory seizures. All patients 18 years of age or older with a history of seizures admitted to an Epilepsy Monitoring Unit for long term EEG-video recordings for diagnostic or pre-surgical evaluation were asked to participate. The validation data set includes EEG studies with full montage (21 channels).
Dataset Description: 615 Seizures, 102 Total Number of Patients, 395 Total Number of Hours (mean ± SD =3.18 ± 0.03; range 2.0 ~5.2). Under the constraint that no more than 3% of the total seizures were included from one subject; detection performance was tested on 615 seizures in a total of 395 hours of scalp EEG recordings from 102 patients. Otherwise, no additional inclusion criteria were applied in the data selection process.
Reference Standard: Each of the EEG recordings was reviewed by three independent, blinded EEG experts (all neurologists/epileptologists) to identify electrographic seizures and spikes. The end point of this independent review was to identify, it any, the seizure onset times in each of the sampled EEG segments. Due to the anticipated inter-rater variability among EEG experts, a majority rule (at least 2 out of 3) was applied to make the final determination of "true" electrographic seizure.
ICTA-D Study:
Subject Population and Test Dataset: All EEGs used for validation were collected from adult patients seen for routine clinical evaluation at the Epilepsy Monitoring Units of Toronto Western General Hospital and NewYork-Presbyterian Hospital. A physician not taking part on the subsequent review/scoring of the data conducted database query and study inclusion from a patient database of consecutive recordings. All studies consisted on electrocorticographic (ECoG) recordings obtained using Natus proprietary hardware/software, with full intracranial electrodes (strips and/or grids), and were included independently of ECoG patterns and technical quality.
Dataset Description: 429 Seizures, 93 Total Number of Patients, 619 hours. AGE (Mean ± SD): 40.8 ± 11.1. GENDER: 57 (Male), 36 (Female). All subjects involved in this study were adult patients (≥18 years old). To avoid over-weighting recordings containing many events, a maximum of 12 events per recording were permitted.
Reference Standard: Each of the ECoG recordings was reviewed by three independent, blinded EEG experts (all neurologists/epileptologists) to identify electrographic seizures. The end point of this independent review was to identify, if any, the presence of seizures in each of the sampled ECoG segments. Due to the anticipated inter-rater variability among EEG experts, a majority rule (at least 2 out of 3) was applied to make the final determination of "true" electrographic seizure.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Non-Clinical: The ICTA Algorithms rely upon underlying mathematical analyses, including signal reqularity, maximum frequency, and amplitude variation. Each mathematical analysis was independently calculated and verified against results generated from published methods.
Clinical: Natus conducted an extensive clinical test to: 1) Evaluate the positive percent agreement (i.e., detection sensitivity) and false detection rate of both components (ICTA-S and ICTA-D) of ICTA Algorithms; and, 2) Demonstrate equivalence of the seizure detection performance, in terms of positive percent agreement and false detection rates, of ICTA Algorithms to that of a predicate device and/or to the gold standard, defined as seizures detected by a panel of 3 board certified Neurophysiologists.
ICTA-S Study Performance:
Inter Rater Performance for Seizure detection:
Inter-rater Positive Percent Agreement (PPA) ranged between 73 and 85%, while False Detection per hour (FD/h) was very close for all three raters (0.3 FD/h, on average) for Seizure Detection.
Rater 1 vs Rater 2: PPA 0.85, FD/h 0.2
Rater 1 vs Rater 3: PPA 0.80, FD/h 0.4
Rater 2 vs Rater 1: PPA 0.78, FD/h 0.4
Rater 2 vs Rater 3: PPA 0.73, FD/h 0.5
Rater 3 vs Rater 1: PPA 0.80, FD/h 0.3
Rater 3 vs Rater 2: PPA 0.80, FD/h 0.3
Detection Performance for Seizure detection Algorithm:
ICTA-S Algorithm had a 75% PPA and an FDR of 2.0 FD/h compared to the reference standard.
At Th_2: PPA 75 (70 – 80)%, FDR 2.0 (1.5 - 2.4) FP/h.
At Th_3: PPA 69 (62 - 72)%, FDR 1.0 (0.7 - 1.3) FP/h.
At Th_4: PPA 63 (54 - 66)%, FDR 0.5 (0.3 - 0.7) FP/h.
ICTA-D Study Performance:
Inter Rater Performance:
REV1 (vs. Rev2+Rev3): PPA 77 (74-86)%, FDR 0.8 (0.6 - 1.0) FP/h.
REV2 (vs. Rev1+Rev3): PPA 70 (66-80)%, FDR 0.7 (0.5 -0.9) FP/h.
REV3 (vs. Rev1+Rev2): PPA 71 (67-82)%, FDR 0.8 (0.5 - 1.0) FP/h.
ICTA-D Seizure Detection Performance:
With detection threshold at 2, ICTA-D achieved 75% positive percent agreement and a false detection rate of 1.8 FP/hr.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
ICTA-S:
Positive Percentage Agreement (PPA - Detection Sensitivity): 75% (at Th_2)
False Detection Rate (FDR): 2.0 FP/h (at Th_2)
ICTA-D:
Positive Percentage Agreement (PPA - Detection Sensitivity): 75% (at Threshold 2)
False Detection Rate (FDR): 1.8 FP/hr (at Threshold 2)
Predicate Device(s)
NeuroWorks Seizure Detector (K090019)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 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).
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510K Summary
JUN 2 9 2012
Date: June 19, 2012
Submitted by: Natus Medical Incorporated DBA Excel-Tech Ltd. (XLTEK) 2568 Bristol Circle Oakville, Ontario Canada L6H 5S1
Contact Person: Daniel Ramirez, MD, PhD Clinical Scientist Natus Medical Inc. Tel.: (905) 829-5300 ext 356 Fax .: (905) 829-5304 E-mail: dramirez@natus.com
Propietary Name: ICTA
Common Name: EEG software or Electroencephalogram
Classification Name: Automatic event detection software for full-montage electroencephalograph.
Product code: OMB
Device Class: II
Predicate Devices: NeuroWorks Seizure Detector (K090019)
Description
ICTA is a software only product. It runs on a personal computer and requires no specialized hardware. It identifies electroencephalographic activity that might correspond to seizures (referred as "events"). These events are then reviewed, accepted, modified and/or deleted by the qualified medical practitioner. The software does not make any final decisions that result in any automatic diagnosis or treatment. The EEG input is read from a file on the personal computer (or available across the network).
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Image /page/1/Picture/0 description: The image shows the logo for "xltek, a division of natus". The logo features a stylized symbol resembling an upward-pointing arrow with a starburst effect above it. The text "xltek" is written in a simple, sans-serif font to the right of the symbol. Below the text and symbol, the phrase "a division of natus" is written in a smaller font size.
ICTA employs Bayesian formulation to provide a detection variable based on the probabilities that a given section of EEG contains a seizure-like activity. The a priori probabilities that a certain set of features represent seizure or non-seizure data were computed from the training data set. These probabilities are used by the detection method for all seizure detections.
The software has two components: ICTA-S for analysis of surface EEG recordings and ICTA-D for analysis of intracranial recordings. Whether a particular module is active is determined by the user. The user also determines parameters that are needed for the algorithm to perform its intended task. None of the components is responsible for data acquisition, review or any other function different from analysis.
Indications for Use
The ICTA software is intended as a review tool to mark previously acquired sections of the adult (greater than or equal to 18 years) EEG recordings (surface or intracranial) that may correspond to electrographic seizures, in order to assist qualified clinical practitioners, who will exercise professional judgment in using the information, in the assessment of EEG traces.
- Surface recordings must be obtained with full montage according to the standard 10/20 . system.
Intracranial recordings must be obtained with depth electrodes (strips and/or grids). . This device does not provide any diagnostic conclusion about the patient's condition to the user.
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Predicate Comparison
| Predicate device | Subject device | Comment | |
|---|---|---|---|
| Neuroworks Seizure | |||
| Detector(K090019) | ICTA | ||
| Device | |||
| Class | Class II | Class II | |
| Class Name | Automatic event | ||
| detection software for | |||
| full-montage | |||
| electroencephalograph | Automatic event detection | ||
| software for full-montage | |||
| electroencephalograph | Same | ||
| User Input | Mouse/keyboard | Mouse/keyboard | Same |
| Intended use | The Seizure Detection | ||
| component of | |||
| Neuroworks is | |||
| intended to mark | |||
| previously acquired | |||
| sections of the adult | |||
| (greater than or equal | |||
| to 18 years) EEG | |||
| recordings that may | |||
| correspond to | |||
| electrographic | |||
| seizures, in order to | |||
| assist qualified clinical | |||
| practitioners in the | |||
| assessment of EEG | |||
| traces. EEG | |||
| recordings should be | |||
| obtained with full scalp | |||
| montage according to | |||
| the standard 10/20 | |||
| system. | The ICTA software is | ||
| intended as a review tool | |||
| to mark previously | |||
| acquired sections of the | |||
| adult (greater than or equal | |||
| to 18 years) EEG | |||
| recordings (surface or | |||
| intracranial) that may | |||
| correspond to | |||
| electrographic seizures, in | |||
| order to assist qualified | |||
| clinical practitioners, who | |||
| will exercise professional | |||
| judgment in using the | |||
| information, in the | |||
| assessment of EEG | |||
| traces. | |||
| Surface recordings must | |||
| be obtained with full | |||
| montage according to the | |||
| standard 10/20 system. | |||
| Intracranial recordings | |||
| must be obtained with | |||
| depth electrodes (strips | |||
| and/or grids). This device | |||
| does not provide any | |||
| diagnostic conclusion | |||
| about the patient's | |||
| condition to the user. | Equivalent. | ||
| Both devices are | |||
| intended to for | |||
| computer -assisted | |||
| event marking that a | |||
| qualified user can | |||
| use for diagnosis. | |||
| ICTA is able to | |||
| analyze surface | |||
| recording and | |||
| intracranial | |||
| recordings. | |||
| IFU- | |||
| Intended | |||
| user | Medical professional | ||
| trained in EEG | |||
| analysis | Medical professional | ||
| trained in EEG analysis | Same | ||
| Number of | |||
| channels | Up to 128 channels | Up to 128 channels | Same |
| Predicate device | Subject device | Comment | |
| Neuroworks Seizure | |||
| Detector(K090019) | ICTA | ||
| Functional | |||
| output | Spikes, spike burst, | ||
| rhythmic burst | Seizures (i.e generically | ||
| refer to as stellate event in | |||
| the software) | Equivalent. Only | ||
| difference is due to | |||
| ICTA not used in the | |||
| detection of spikes. | |||
| User control | |||
| of detection | |||
| parameters | Detection montage | ||
| customization. | |||
| User defines detector | |||
| settings. | Detection montage | ||
| customization. | |||
| User defines detector | |||
| settings. | Same | ||
| Event | |||
| detection | |||
| sensitivity%* | 76% | ICTA-Surface / ICTA- | |
| Depth* | |||
| 75% / 75% | Equivalent | ||
| False | |||
| positive rate | |||
| for events* | 0.6 FP/h | ICTA-Surface / ICTA- | |
| Depth* | |||
| 2.0 / 1.8 FP/h | Equivalent |
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Image /page/3/Picture/0 description: The image shows the logo for "xltek, a division of natus". The logo consists of a stylized star-like symbol to the left of the word "xltek". Below the word "xltek" is the phrase "a division of natus" in a smaller font. The logo is black and white.
Brief Summary of Non-Clinical and Clinical Performance Tests
All functionalities and performance of the ICTA software have been verify/validated through Bench
and clinical performance tests according to the intended use- and user- of the device.
Non-Clinical: The ICTA Algorithms rely upon underlying mathematical analyses, including signal reqularity, maximum frequency, and amplitude variation. Each mathematical analysis was independently calculated and verified against results generated from published methods.
Clinical: Natus conducted an extensive clinical test to: 1) Evaluate the positive percent agreement (i.e., detection sensitivity) and false detection rate of both components (ICTA-S and ICTA-D) of ICTA Algorithms; and, 2) Demonstrate equivalence of the seizure detection performance, in terms of positive percent agreement and false detection rates, of ICTA Algorithms to that of a predicate device and/or to the gold standard, defined as seizures detected by a panel of 3 board certified Neurophysiologists.
4
Image /page/4/Picture/0 description: The image shows the logo for "xltek", which is described as a division of "natus". The logo features a stylized symbol resembling a mountain or a stylized letter "A" with three small circles above it, followed by the text "xltek" in a simple, sans-serif font. Below the text, in a smaller, more stylized font, is the phrase "a division of natus".
ICTA-S Study.
Subject Population and Test Dataset
The seizure detection performance of ICTA-S Seizure detection algorithm was evaluated on scalp EEG recordings from patients with medically refractory seizures. All patients 18 years of age or older with a history of seizures admitted to an Epilepsy Monitoring Unit for long term EEG-video recordings for diagnostic or pre-surgical evaluation were asked to participate. The validation data set includes EEG studies with full montage (21 channels).
Dataset Description
Number of Seizures: 615 Total Number of Patients: 102 Total Number of Hours: 395 (mean ± SD =3.18 ± 0.03; range 2.0 ~5.2)
Under the constraint that no more than 3% of the total seizures were included from one subject; detection performance was tested on 615 seizures in a total of 395 hours of scalp EEG recordings from 102 patients. Otherwise, no additional inclusion criteria were applied in the data selection process.
Reference Standard
Each of the EEG recordings was reviewed by three independent, blinded EEG experts (all neurologists/epileptologists) to identify electrographic seizures and spikes. The end point of this independent review was to identify, it any, the seizure onset times in each of the sampled EEG segments. Due to the anticipated inter-rater variability among EEG experts, a majority rule (at least 2 out of 3) was applied to make the final determination of "true" electrographic seizure.
Statistical Analysis for Seizure Detection Algorithm
-
- Inter Rater Performance for Seizure detection: Inter-rater Positive Percent Agreement (PPA) ranged between 73 and 85%, while False Detection per hour (FD/h) was very close for all three raters (0.3 FD/h, on average) for Seizure Detection.
| Seizure | ||||||
|---|---|---|---|---|---|---|
| Rater | Rater2 | Rater3 | ||||
| PPA | FD/h | PPA | FD/h | PPA | FD/h | |
| Rater 1 | - | - | 0.85 | 0.2 | 0.80 | 0.4 |
| Rater 2 | 0.78 | 0.4 | - | - | 0.73 | 0.5 |
| Rater 3 | 0.80 | 0.3 | 0.80 | 0.3 | - | - |
-
- Detection Performance for Seizure detection Algorithm: Based on the seizure samples determined by the independent EEG review panel, the positive percentage agreement (i.e., detection sensitivity) and false detection rate were estimated for both ICTA-S algorithm and the predicate device. Bootstrap method was applied to construct 95% confidence intervals for the estimated performance statistic.
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Image /page/5/Picture/0 description: The image shows the title of a document, which is "510(K): ICTA SEIZURE DETECTION ALGORITHM". Below the title, it says "510K SUMMARY". The image also indicates that it is page 6 of 8.
Image /page/5/Figure/1 description: The image shows the logo for "xltek", with a stylized arrow pointing upwards to the left of the text. A dashed line underlines the text, and below the line is the text "a division of natus" in a smaller font size. The logo appears to be for a company or organization named "xltek", which is a division of "natus".
Results of Seizure Detection Algorithm - Summary
Image /page/5/Figure/3 description: The image is a plot of PPA (%) vs FDR (FP/h) for ICTA-S. The plot shows a line with three data points, with the detection threshold indicated by the shape of the data point. The data points are (0.6, 0.63), (1.0, 0.69), and (2.0, 0.75), with corresponding false positive rates of 0.5 FP/h, 1.0 FP/h, and 2.0 FP/h.
ICTA-S seizure detection algorithm performance as a function of detection threshold level.
One characteristic of the ICTA-S algorithm is the possibility for the user to adjust the detection threshold (Th) value. Changing the threshold value affects performance of the algorithm. As can be seen on the figure above, there is a tradeoff between PPA and the FDR. At lower values of the detection threshold the PPA improves (i.e at Th = 2, PPA= 75%) while the FDR increases. Higher values of Th result in the opposite behavior, that is, PPA decreases and the FDR improves (at Th= 4, FDR= 0.5 FP/h). The ICTA-S Algorithm had a 75% PPA and an FDR of 2.0 FD/h compared to the reference standard. Detailed performance data of the ICTA-S seizure detector is shown on the table below.
| Detection
| Threshold | PPA (95% CI) | FDR (FP/h) |
|---|---|---|
| Th_2 | 75 (70 – 80) | 2.0 (1.5 - 2.4) |
| Th_3 | 69 (62 - 72) | 1.0 (0.7 - 1.3) |
| Th_4 | 63 (54 - 66) | 0.5 (0.3 - 0.7) |
(95% C.I.) - 95% Bootstrap Confidence Interval
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Image /page/6/Picture/0 description: The image shows the logo for "xltek", which is described as a division of "natus". The logo features a stylized letter "A" with a small circle above it, resembling a person with outstretched arms. To the right of the symbol is the word "xltek" in a simple, sans-serif font. Below the word "xltek" is the phrase "a division of natus" in a smaller font size.
ICTA-D Study
Subject Population and Test Dataset
All EEGs used for validation were collected from adult patients seen for routine clinical evaluation at the Epilepsy Monitoring Units of Toronto Western General Hospital and NewYork-Presbyterian Hospital. A physician not taking part on the subsequent review/scoring of the data conducted database query and study inclusion from a patient database of consecutive recordings. All studies consisted on electrocorticographic (ECoG) recordings obtained using Natus proprietary hardware/software, with full intracranial electrodes (strips and/or grids), and were included independently of ECoG patterns and technical quality.
Dataset Description
Number of Seizures: 429 Total Number of Patients: 93 Number of Hours: 619 hours
| AGE (Mean ± SD) | 40.8 ± 11.1* |
|---|---|
| GENDER | 57 (Male) |
| 36 (Female) |
All subjects involved in this study were adult patients (≥18 years old).
To avoid over-weighting recordings containing many events, a maximum of 12 events per recording were permitted.
Reference Standard
Each of the ECoG recordings was reviewed by three independent, blinded EEG experts (all neurologists/epileptologists) to identify electrographic seizures. The end point of this independent review was to identify, if any, the presence of seizures in each of the sampled ECoG segments. Due to the anticipated inter-rater variability among EEG experts, a majority rule (at least 2 out of 3) was applied to make the final determination of "true" electrographic seizure.
Results
1. Inter Rater Performance
Each Rater was compared against the "consensus" marking of the remaining two raters. The results are shown on table below. Rater 1 showed the highest possible PPA with 77%, which was also accompanied by higher FDR though within the performance of the other reviewers. PPA and FDR for the other reviewers were similar with 70% PPA. Reviewer 2 (compared to Reviewer 1 + Reviewer 3) showed the lowest FDR of 0.7 FP/h.
| PPA (95% CI)* | FDR (95% CI)* | |
|---|---|---|
| REV1 | ||
| (vs. Rev2+Rev3) | 77 (74-86) | 0.8 (0.6 - 1.0) |
| REV2 | ||
| (vs. Rev1+Rev3) | 70 (66-80) | 0.7 (0.5 -0.9) |
| REV3 | ||
| (vs. Rev1+Rev2) | 71 (67-82) | 0.8 (0.5 - 1.0) |
Inter-rater Positive Percent Agreement and False Detection Rate
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Image /page/7/Picture/0 description: The image shows the logo for Xltek, a division of Natus. The logo features a stylized arrow pointing upwards, followed by the text "xltek" in lowercase letters. Below the text is the phrase "a division of natus" in a smaller font size.
Image /page/7/Figure/2 description: The image is a summary of the results of a seizure detection algorithm. The plot shows PPA on the y-axis and FDR on the x-axis. There are three data points for the estimated values, with the data point at FDR of 0.6 and PPA of 0.64, the data point at FDR of 1.1 and PPA of 0.70, and the data point at FDR of 1.8 and PPA of 0.75.
With detection threshold at 2, ICTA-D achieved 75% positive percent agreement and a false detection rate of 1.8 FP/hr. As was the case for ICTA scalp detector, for ICTA-D also the variation of "threshold detection" levels translated into a trade-off between PPA and FDR. At lower threshold values (i.e. =2) PPA increases at same time that the "specificity" decreases, that is, the number of false detections increases.
Unlike other algorithms reported in the scientific literature, ICTA-D was built to allow for user tuneability, which gives the flexibility of regulating performance as desired. Users can control algorithm behavior by adjusting thresholds to tune performance as they see fit. At default thresholds, results comparable to expert reviewers were obtained with no need of altering the algorithm at run time.
Conclusion
Based on the results of the non-clinical and clinical testing we conclude that ICTA (ICTA-S and ICTA-D) seizure detection algorithm is substantially equivalent to the predicate device and reference standard.
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DEPARTMENT OF HEALTH & HUMAN SERVICES
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Food and Drug Administration 10903 New Hampshire Avenue Document Control Room -WO66-G609 Silver Spring, MD 20993-0002
Excel-tech Ltd. c/o Daniel Ramirez, MD, PhD Clinical Scientist, Division of Natus Medical Inc. 2568 Bristol Circle Oakville, Ontario Canada L6H 5S1
JUN 2 9 2012
Re: K120260 Trade/Device Name: ICTA Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OMB Dated: April 6, 2012 Received: June 14, 2012
Dear Dr. Ramirez:
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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Page 2 - Daniel Ramirez, MD, PhD
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,
Kesia Alexander
Image /page/9/Picture/7 description: The image shows a signature in black ink on a white background. The signature appears to be stylized and cursive, with a prominent loop at the top and a flowing line extending downwards. The overall impression is that of a quick, practiced signature.
Malvina B. Eydelman, M.D. 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 Statement
510(k) Number (if known):
Device Name: ICTA
Indications for Use:
The ICTA software is intended as a review tool to mark previously acquired sections of the adult (greater than or equal to 18 years) EEG recordings (surface or intracranial) that may correspond to electrographic seizures, in order to assist qualified clinical practitioners, who will exercise professional judgment in using the information, in the assessment of EEG traces.
- Surface recordings must be obtained with full montage according to the standard 10/20 . system.
- Intracranial recordings must be obtained with depth electrodes (strips and/or grids). .
This device does not provide any diagnostic conclusion about the patient's condition to the user.
Prescription Use (Per 21 CFR 801.109) OR
Over-The Counter Use
(PLEASE DO NOT WRITE BELOW THIS LINE – CONTINUE ON ANOTHER PAGE IF NEEDED)
Concurrence of CDRH, Office of Device Evaluation (ODE)
John Grimes, Ph.D.
(Division Sign-Off) Division of Ophthalmic, Neurological and Ear, Nose and Throat Devices
510(k) Number K120260
(Optional Format 1-2-96)