CT CoPilot™ is intended for automatic labeling, visualization and volumetric quantification of segmentable structures from sets of CT images of the brain. This software is intended to automate the current manual process of identifying, labeling and quantifying structures identified on CT images of the brain and to provide automated registration and reformatting of data.

Device Description

CT CoPilot™ is intended for use in automating post-acquisition quantitative analysis of CT images of the brain for patients aged 18 or older. CT CoPilot™ performs automatic reformatting, labeling and quantification of segmentable structures from a set of CT images. Output of the software provides these values as numerical volumes and images which have been annotated with graphical color overlays, with each color representing a specific segmental structure. When CT imaging is performed more than once on a patient, the current data is coregistered to the most recent processed prior exam of the same patient, facilitating comparison between the studies using CT CoPilot™. Voxel-by-voxel subtraction maps of the pixel density change in Hounsfield Units (HU) are generated in up to 3 dimensions between the current and most recent processed prior exam of the patient.

CT CoPilot™ incorporates registration, alignment, and segmentation methods similar to a previous 510(k) cleared device, known as NeuroQuant (K061855), to automatically label and quantify the volume of segmentable structures in MRI images of the head. CT CoPilot™ output is provided in standard DICOM format as additional series of images (with appropriate descriptors) and reports that can be displayed on most third-party commercial DICOM workstations. CT CoPilot™ is intended to provide visualization and quantification data for CT scans of the brain. CT CoPilot™ includes safety procedures and error reporting similar to those adopted by NeuroQuant to identify cases that may not be processed for any reason. CT CoPilot™ is intended to be used by trained personnel in Neuro CT imaging. Patient management decisions should not be made based solely on the results of CT CoPilot™ quantitative data.

In laboratory testing, CT CoPilot™ demonstrates the following registration accuracy based on 100 randomly acquired CT head scans on both normal patients and those with abnormal pathologies: 1) The inter-subject variability of the angle formed by the inter-hemispheric plane and the vertical line, as measured on axial views (yaw), is less than 15 degrees. 2) The intersubject variability of the positioning of the inter-hemispheric plane and the vertical line, as measured on coronal views (roll), is less than 15 degrees. 3) The inter-subject variability of the positioning of the AC/PC plane and the horizontal line, as measured on sagittal views, is less than 15 degrees. Laboratory testing of CT CoPilot™ software on 179 scans from 34 patients with ventriculostomy catheters demonstrates the following correlation coefficients between the automatic software segmentation accuracy of relevant anatomical structures when compared against the same group of medical expert manually segmented subjects: (Lateral Ventricle Volume = 98%, Total CSF Volume = 98%, Intra-Cranial Volume = 99%, Midline Shift Index = 95%). Laboratory testing of CT CoPilot™ segmentation reliability demonstrates equivalent test-retest performance as expert manually segmented subjects. The accuracy testing of CT CoPilot™ registration and segmentation performance was similar to the predicate device (NeuroQuant) without additional safety risk.

CT CoPilot™ consists of proprietary software developed by ZepMed, Inc. installed on an offthe-shelf personal computer. The output of CT CoPilot™ is intended for Picture Archive and Communications System (PACS) display systems. PACS display systems must contain sufficient functionality to display color images (either MR or Secondary Capture), and to display report text and graphics output either in DICOM Structured Report or display of Adobe PDF or JPEG files.

The accuracy of the automatic cross-sectional registration and segmentation in CT CoPilot™ is affected by the subject's deviation from the features embedded in the reference neuroanatomic Atlas. In general, the accuracy of the CT CoPilot™ system software may decrease when the subject's head includes pathologic features not present in the Atlas, lacks features present in the Atlas, or is structurally different than that defined in the preexisting neuroanatomic Atlas. The accuracy of the CT CoPilot™ single image and serial image analysis program may also be degraded by patient motion or by artifacts which are introduced into the patient scanning process, or if patient positioning severely deviates from expectations. Alignment of subject to Atlas space is an important software step in the overall process of registration and segmentation. CT CoPilot™ uses the mechanism for determination of alignment accuracy instantiated in the predicate device (NeuroQuant) for establishing the relationship between image quality and overall alignment accuracy. Specifically, a "measurement index" is determined for each study based on the deviation of each image from the normalized anatomic index embedded in the program. The measurement index is determined by the deviation of the image volumes from normal atlas space. The automatically determined "measurement index" is used to define the limit of anatomic alignment variance which has been determined through laboratory testing of CT CoPilot™ to be accepted by the program. As a safety feature, the CT CoPilot™ software calculates and reports a measurement index number which reflects the adequacy of overall single image and serial image alignment. If the measurement index exceeds specified limits, an error report is generated to inform the user and further processing is terminated.

Factors that may degrade the technical quality and accuracy of CT CoPilot™ registration and segmentation results include:

a) Patient's motion during scan.
b) Artifacts affecting overall image quality.
c) Reconstruction artifacts.
d) Pathological and or anatomical deviations from the Atlas.
e) Large initial alignment deviations between the patient and the Atlas.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study information for the CT CoPilot™ device, based on the provided document:

Acceptance Criteria and Device Performance

Metric	Acceptance Criteria (Implicit)	Reported Device Performance
Registration Accuracy (Angle of Inter-hemispheric plane and vertical line - axial views)	Less than 15 degrees	Less than 15 degrees
Registration Accuracy (Angle of Inter-hemispheric plane and vertical line - coronal views)	Less than 15 degrees	Less than 15 degrees
Registration Accuracy (Angle of AC/PC plane and horizontal line - sagittal views)	Less than 15 degrees	Less than 15 degrees
Segmentation Accuracy (Lateral Ventricle Volume)	Not explicitly stated, inferred from high correlation	98% correlation coefficient (vs. expert manual)
Segmentation Accuracy (Total CSF Volume)	Not explicitly stated, inferred from high correlation	98% correlation coefficient (vs. expert manual)
Segmentation Accuracy (Intra-Cranial Volume)	Not explicitly stated, inferred from high correlation	99% correlation coefficient (vs. expert manual)
Segmentation Accuracy (Midline Shift Index)	Not explicitly stated, inferred from high correlation	95% correlation coefficient (vs. expert manual)
Segmentation Reliability	Equivalent to expert manual segmentation	Equivalent test-retest performance as expert manually segmented subjects
Error Reporting (Measurement Index exceeds limits)	Generate an error report and terminate processing	Error report generated, further processing terminated

Note: The document explicitly states acceptance criteria for registration accuracy (less than 15 degrees for the angles). For segmentation accuracy, the acceptance criteria are not numerically defined, but the high correlation coefficients (95-99%) against expert manual segmentation implicitly indicate that these values met the internal performance requirements for substantial equivalence. The reliability criterion is directly stated as "equivalent."

Study Information

2. Sample Size and Data Provenance:
* Test Set Sample Size:
* Registration Accuracy: 100 randomly acquired CT head scans.
* Segmentation Accuracy/Reliability: 179 scans from 34 patients.
* Data Provenance: Retrospective (implied by "randomly acquired CT head scans" and "scans from 34 patients"). The country of origin is not specified. The scans included both normal patients and those with abnormal pathologies, and for segmentation, patients with ventriculostomy catheters.

3. Number of Experts and Qualifications:
* Number of Experts: The document refers to "medical expert manually segmented subjects" for establishing ground truth, implying multiple experts. The exact number is not stated.
* Qualifications of Experts: Not explicitly stated beyond "medical expert."

4. Adjudication Method:
* The document does not explicitly describe an adjudication method like 2+1 or 3+1. It states the correlation coefficients are "when compared against the same group of medical expert manually segmented subjects," suggesting a single set of expert segmentations used as ground truth for comparison.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
* No, an MRMC comparative effectiveness study that measures the effect size of how much human readers improve with AI vs. without AI assistance was not reported in this document. The study focused on the standalone performance of the device against expert manual segmentation and retest reliability.

6. Standalone Performance:
* Yes, a standalone performance study (algorithm only without human-in-the-loop performance) was conducted. The reported registration accuracy, segmentation accuracy (correlation coefficients), and segmentation reliability directly reflect the device's performance in isolation.

7. Type of Ground Truth Used:
* Expert Consensus/Manual Segmentation: For segmentation accuracy, the ground truth was established by "medical expert manually segmented subjects."
* For registration accuracy, the ground truth appears to be based on an internal reference (e.g., a "normalized anatomic index embedded in the program" or an "Atlas" as mentioned later in the document regarding alignment comparison).

8. Sample Size for the Training Set:
* The document does not specify the sample size used for the training set. It refers to a "reference neuroanatomic Atlas" but does not give details about its derivation or the number of cases used to build it.

9. How the Ground Truth for the Training Set Was Established:
* The document does not explicitly state how the ground truth for the training set was established. It mentions that the accuracy of CT CoPilot™ is affected by the subject's deviation from the "features embedded in the reference neuroanatomic Atlas." This implies the Atlas itself serves as a form of ground truth for some aspects of the algorithm's design, but the origin and ground truth establishment for this Atlas are not detailed. It also mentions "preexisting neuroanatomic Atlas," suggesting it might be an external resource.

Summary

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Food and Drug Administration 10903 New Hampshire Avenue Document Control Center - WO66-G609 Silver Spring, MD 20993-0002

December 7, 2016

ZepMed, LLC. % Mr. James Monroe CEO Monroe Medical Device Consulting, LLC 319 Shilling Drive SOMERSET NJ 08873

Re: K161322 Trade/Device Name: CT CoPilot™ Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: LLZ Dated: November 11, 2016 Received: November 14, 2016

Dear Mr. Monroe:

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.

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.

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If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Division of Industry and Consumer Education at its toll-free number (800) 638 2041 or (301) 796-7100 or at its Internet address

http://www.fda.gov/MedicalDevices/Resourcesfor You/Industry/default.htm. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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 Industry and Consumer Education 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.

Michael D'Hara

For

Robert Ochs, Ph.D. Director Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known)

K161322

Device Name CT CoPilot™

Indications for Use (Describe)

Type of Use (Select one or both, as applicable)
-------------------------------------------------

	Prescription Use (Part 21 CFR 801 Subpart D)	Over-The-Counter Use (21 CFR 801 Subpart C)
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05 - 510k Summary

CT Co-Pilot

Submitter's Name, Address, Telephone Number, Contact Person and Date Prepared:

Dr. Douglas J. Bates, MD ZepMed, LLC. 2465 Avenida de La Playa La Jolla, CA 92037

Phone: (858) 692-0795, Facsimile: (858) 412 - 3711

Contact Person: James W. Monroe; jwmonroe@monroemdc.com, (908) 809-0081

Date Prepared: November 11, 2016

Name of Device and Name/Address of Sponsor

CT CoPilot™

ZepMed, LLC. 2465 Avenida de La Playa La Jolla, CA 92037

Common or Usual Name

Picture Archiving and Communication System

Classification Name

System, Image Processing, Radiological (892.2050)

Classification Panel Radiology

Product Codes LLZ

Device Class II

Predicate Devices NeuroQuant (K061855)

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Intended Use / Indications for Use

Device Description

In laboratory testing, CT CoPilot™ demonstrates the following registration accuracy based on 100 randomly acquired CT head scans on both normal patients and those with abnormal

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pathologies: 1) The inter-subject variability of the angle formed by the inter-hemispheric plane and the vertical line, as measured on axial views (yaw), is less than 15 degrees. 2) The intersubject variability of the positioning of the inter-hemispheric plane and the vertical line, as measured on coronal views (roll), is less than 15 degrees. 3) The inter-subject variability of the positioning of the AC/PC plane and the horizontal line, as measured on sagittal views, is less than 15 degrees. Laboratory testing of CT CoPilot™ software on 179 scans from 34 patients with ventriculostomy catheters demonstrates the following correlation coefficients between the automatic software segmentation accuracy of relevant anatomical structures when compared against the same group of medical expert manually segmented subjects: (Lateral Ventricle Volume = 98%, Total CSF Volume = 98%, Intra-Cranial Volume = 99%, Midline Shift Index = 95%). Laboratory testing of CT CoPilot™ segmentation reliability demonstrates equivalent test-retest performance as expert manually segmented subjects. The accuracy testing of CT CoPilot™ registration and segmentation performance was similar to the predicate device (NeuroQuant) without additional safety risk.

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determination of alignment accuracy instantiated in the predicate device (NeuroQuant) for establishing the relationship between image quality and overall alignment accuracy. Specifically, a "measurement index" is determined for each study based on the deviation of each image from the normalized anatomic index embedded in the program. The measurement index is determined by the deviation of the image volumes from normal atlas space. The automatically determined "measurement index" is used to define the limit of anatomic alignment variance which has been determined through laboratory testing of CT CoPilot™ to be accepted by the program. As a safety feature, the CT CoPilot™ software calculates and reports a measurement index number which reflects the adequacy of overall single image and serial image alignment. If the measurement index exceeds specified limits, an error report is generated to inform the user and further processing is terminated.

Factors that may degrade the technical quality and accuracy of CT CoPilot™ registration and segmentation results include:

a) Patient's motion during scan.
b) Artifacts affecting overall image quality.
c) Reconstruction artifacts.
d) Pathological and or anatomical deviations from the Atlas.
e) Large initial alignment deviations between the patient and the Atlas.

Non-Clinical Testing

ISO 14971 Second Edition 2007, Medical Devices Application Of Risk Management o To Medical Devices.
ISO 62304: The Harmonized Standard for Medical Device Software Development .
. NEMA PS 3.1 - 3.20 (2011), Digital Imaging And Communications In Medicine (Dicom) Set.

Comparison to Predicate Device

ZepMed's CT CoPilot™ , is substantially equivalent to the predicate devices listed below with respect to intended use/indications for use, principles of operation and technological characteristics.

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Substantial Equivalence Table

Attribute	CT CoPilot™	NeuroQuant	Equivalence

510(k)	(Subject Device)	K061855
Product Code	LLZ	LLZ	Yes
Intended Use	CT CoPilot™ isintended for automaticlabeling, visualizationand volumetricquantification ofsegmentable structuresfrom sets of CT imagesof the brain. Thissoftware is intended toautomate the currentmanual process ofidentifying, labelingand quantifyingstructures identified onCT images of the brainand to provideautomated registrationand reformatting ofdata.	NeuroQuant™ is intendedfor automatic labeling,visualization andvolumetric quantificationof segmentable brainstructures from sets of MRimages. This software isintended to automate thecurrent manual process ofidentifying, labeling andquantifying the volume ofsegmental brain structuresidentified on MR images.	Yes
Data Source	CT Scanner	MRI Scanner	Different
Display images	Reformatted, realignedaxial, coronal, and sagittalimages.	Reformatted, realignedaxial, coronal and sagittalimages.	Yes
QuantitativeMetrics	CSF volumes, Intracranialvolume, Midline shift.	CSF volumes, Intracranialvolume, Brain structurevolumes.	Similar
PhysicalCharacteristics	Software package• Operates off-the-shelfsoftware (multiplevendors)	Software package• Operates off-the-shelfsoftware (multiplevendors)	Yes
OperatingSystem	OS:Linux	OS: Linux,Mac,Windows	Yes
DICOMcompatible	Yes	Yes	Yes
PerformancemeasurementTesting	Reproducibility andAccuracy testing	Reproducibility andAccuracy testing	Yes
Safety	Measurement data can beviewed, accepted orrejected by a physician	Measurement data can beviewed, accepted orrejected by a physician	Yes
In plane voxelResolution(Input Data)	0.1-1mm	1mm	Similar
SliceThickness(Input Data)	0.2-1mm	1.2mm	Similar
AutomaticAlignment	Yes	Yes	Yes
RegistrationTarget Data	Atlas, Prior	Atlas	Similar
SkullStripping	Yes	Yes	Yes
AutomaticSegmentation	Yes	Yes	Yes
ErrorDetection	Yes	Yes	Yes
Output ImageData Format	3D Volumetric, 2D MPR-1mm isotropic volume-1-5mm thick MPR	3D Volumetric-1mm isotropic volume	Similar
Color-codedSegmentationSeries(Output Data)	Yes	Yes	Yes

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Substantial Equivalence Discussion:

Both CT CoPilot™ and NeuroQuant (K061855) allow for the visualization and volumetric quantification of brain images. Similarly, both systems incorporate post-acquisition quantitative analysis of acquired images and transform and display the results in DICOM standard formatted images and reports. Both systems perform reproducibility and accuracy testing. The difference between the post processing systems is that CT CoPilot™ is analyzing CT images of the brain

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whereas NeuroQuant analyzes MRI images of the brain. Although CT CoPilot™ utilizes CT scans and NeuroQuant utilizes MRI scans, they both perform automated segmentation and quantification of segmental structures within the brain. Post-processing of the images with the Subject device (CT CoPilot™) and predicate device (NeuroQuant) use similar algorithms for segmentation and registration of scans to an Atlas as well as similar safety procedures to assess the quality of segmentation and registration accuracy.

CT CoPilot™ is substantially equivalent in performance, technology, and characteristics. The differences between the two devices do not raise any new questions of safety and effectiveness.

Regulation Number and Section

§ 892.2050 Medical image management and processing system.

(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).