iQ-solutions™ is a software medical device intended for automatic annotation, visualization, and quantification of segmentable brain structures from a set of brain MRI scans. It is intended to accelerate and improve the quantification of brain structures that would otherwise require a manual process of identifying, annotating, and measuring regions of interest in brain MRI scans.

iQ-solutions™ consists of both cross-sectional and longitudinal analysis pipelines.

. The cross-sectional pipeline is intended to conduct structure segmentation and volume analysis on brain MRI scans at a single time point.
. The longitudinal pipeline is intended to conduct volume change analysis on a single patient's MRI scans acquired on the same scanner, with consistent image acquisition protocol and with consistent contrast at two different time points.

The results of the cross-sectional pipeline cannot be compared with the results of the longitudinal pipeline.

Device Description

iQ-solutions™ is a standalone software device that processes brain MRI scans to outline and quantify the brain structures described in the intended use. The iQ-solutions™ software interacts with the user's picture archiving and communication system (PACS) to receive scans and returns the results to the same destination or other user-specified radiology software system or database.

iQ-solutions™ analysis module consists of pre-trained convolutional neural networks (CNN) that have been verified and validated to segment the specific brain structures and create binary masks accordingly using the incoming head MRI scans. Each convolutional neural network is coupled with a pre-processing component that transforms the MRI scans to the standard position and contrast; and a post-processing component that prepares for the output annotations, statistical calculation, and the input of the next analysis component in either analysis pipeline.

iQ-solutions™ operates together with a medical image routing software or an integration platform that can connect with iQ-solutions™ and a PACS system that can fulfill the requirements of iQsolutions™.

MRI scans are sent to iQ-solutions™ by means of transmission functions within the user's PACS system. Upon completion of processing, iQ-solutions™ returns results to the user's PACS or other userspecified radiology software system or database.

The results from iQ-solutions™ are not intended to be used as a diagnostic tool, and the interpretation of measurements contained in the iQ-solutions™ report remains entirely the responsibility of the qualified radiologists or physicians managing the individual patient's care.

AI/ML Overview

Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Device Performance Study for iQ-solutions™

1. Acceptance Criteria and Reported Device Performance

Analysis Module	Acceptance Metric & Criteria	Reported Performance	Pass/Fail
Sequence Classification	Accuracy > 0.9	Accuracy = 100%	Pass
Brain Extraction	DICE > 0.9	DICE = 0.982	Pass
Scaling Factor Estimation	Metrics better than previously accepted results	STD = 0.0096	Pass
White matter hyperintensity Segmentation	DICE > 0.6	DICE = 0.789	Pass
Contrast-Enhancing Lesion Segmentation	DICE > 0.6	DICE = 0.790	Pass
Lesion Inpainting	Metrics better than previously accepted results	PSNR = 30.79dB	Pass
Brain Tissue Segmentation	DICE > 0.9	DICE = 0.972	Pass
Brain Volume Change Estimation	R² > 0.7	R² = 0.869	Pass
WMH Lesion Activity	R² > 0.7	R² = 0.833	Pass
Cortical Lobar and Subcortical Structure Segmentation	R² > 0.7	R² = 0.833	Pass
Substructure Volume Change Estimation	Metrics better than previously accepted results	STD = 0.0102	Pass
Manual Acceptable Rate (for all models)	Higher than 80%	Ranges from 92.1% to 100%	Pass

2. Sample Size for Test Set and Data Provenance

The test set included various numbers of cases and subjects depending on the specific analysis module being evaluated. Here's a breakdown:

Sequence Classification: 1207 cases
Brain Extraction: 458 cases
Scaling Factor Estimation: 527 cases
White matter hyperintensity Segmentation: 464 cases
Contrast-Enhancing Lesion Segmentation: 737 cases
Lesion Inpainting: 80 cases
Brain Tissue Segmentation: 500 cases
Brain Volume Change Estimation: 166 cases
WMH Lesion Activity: 64 cases
Cortical Lobar and Subcortical Structure Segmentation: 1504 cases
Test-ReTest Dataset: 120 cases
Comprehensive Test Set (for all analysis components): 81 patients (81 cases)

Data Provenance:

The data used for both development and testing was a mix of:

Private Data (in-house datasets): Collected from Sydney Neuroimaging Analysis Centre Pty Ltd (SNAC) over ten years (commencing July 2012). This included over 1500 patients with Multiple Sclerosis, acquired from clinical scanners (1.5T and 3T) from Siemens, GE, and Philips.
Publicly Available MRI Datasets: From healthy individuals, including 2629 scans obtained from 2159 subjects.

The text does not explicitly state the specific countries of origin for the public datasets, but the in-house data is from SNAC in Australia. The data is retrospective as it was collected over a prior ten-year period.

3. Number of Experts used to Establish Ground Truth and Qualifications

The ground truth for the test set (and training set) was established through a combination of widely used software (FSL, FreeSurfer) and manual review:

Initial Generation: Annotations for skullstripping, brain tissues, cortical gray matter lobes, thalamus, hippocampus, and brain volume changes were initially generated using FSL and FreeSurfer.
Manual Review/Annotation:
- These initial annotations were manually reviewed and accepted by trained neuroimaging analysts.
- Annotations for white matter hyperintensities (pre-contrast, contrast-enhancing, and lesion changes) were manually annotated by trained neuroimaging analysts.
Further Review: All annotations were further reviewed by senior neuroimaging analysts according to SNAC SOP.
Expert Radiologists: The test dataset was "further verified by trained neuroimaging analysts and expert radiologists."

The specific number of neuroimaging analysts or expert radiologists is not explicitly stated, nor are their exact years of experience, beyond being "trained" and "senior" neuroimaging analysts and "expert" radiologists.

4. Adjudication Method for the Test Set

The adjudication method involved a multi-stage process:

Initial generation by FSL/FreeSurfer (for some structures).
Manual review and acceptance by trained neuroimaging analysts.
Manual annotation by trained neuroimaging analysts (for WMH).
Further review by senior neuroimaging analysts.
Verification by expert radiologists.

This implies a form of consensus-based adjudication, likely involving multiple individuals, but a specific "2+1" or "3+1" methodology is not detailed. The "manual acceptable rate" criterion suggests a qualitative evaluation by these human experts.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was done. The document states: "No clinical tests were conducted to test the performance and functionality of the subject device as verification and validation of the subject device have been performed through non-clinical bench testing." The acceptance criteria focus on the algorithm's performance against established ground truth, not on its assistance to human readers.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone (algorithm only) performance study was done. The entire "Performance Data" section (Section 5.8 to 5.14) details the results of "Software 'bench' testing" and the metrics presented in Table 5 ("Summary of Performances of all the Analysis Modules") are purely based on the algorithm's output compared to the ground truth.

7. Type of Ground Truth Used

The ground truth used was a combination of:

Expert Consensus / Expert-Reviewed Software Output: For many structures (skullstripping, brain tissues, cortical gray matter lobes, thalamus, hippocampus, brain volume changes), the ground truth was "originally generated using widely used software items such as FSL and FreeSurfer, and the annotations were manually reviewed and accepted by trained neuroimaging analysts."
Manual Annotation by Trained Experts: For white matter hyperintensities (including pre-contrast ones, contrast-enhancing ones, and lesion changes), the annotations were "manually annotated by trained neuroimaging analysts."
Senior Expert Review: All annotations (across both categories) underwent further review by senior neuroimaging analysts.

8. Sample Size for the Training Set

The sample sizes for the training set (including validation data which is part of the development phase before the final test set) varied by analysis module:

Sequence Classification: 4862 cases
Brain Extraction: 1843 cases
Scaling Factor Estimation: 2986 cases
White matter hyperintensity Segmentation: 1858 cases
Contrast-Enhancing Lesion Segmentation: 79 cases
Lesion Inpainting: 449 cases
Brain Tissue Segmentation: 4179 cases
Brain Volume Change Estimation: 1487 cases
WMH Lesion Activity: 116 cases
Cortical Lobar and Subcortical Structure Segmentation: Not applicable (likely handled by other modules or a different training approach).
Test-ReTest Dataset: Not applicable.
Comprehensive Test Set: Not applicable.

The total number of patients/scans used in development (training and validation) drew from a pool of:

2159 subjects / 2629 scans (Public Data)
1570 subjects / 5664 scans (Private Data)
The total number of subjects for training and validation combined across all modules is not explicitly summed, but overall, it drew from "more than 1500 patients" of private data and 2159 subjects of public data.

9. How the Ground Truth for the Training Set was Established

The ground truth for the training set was established in the exact same manner as described for the test set (see point 7). It involved:

Initial generation by widely used software (FSL, FreeSurfer), followed by manual review and acceptance by trained neuroimaging analysts.
Direct manual annotation by trained neuroimaging analysts for certain structures like white matter hyperintensities.
Further review and acceptance by senior neuroimaging analysts according to SNAC SOP.

This robust process of combining automated tools with multiple levels of expert human review ensured the quality of the ground truth used for both training and evaluating the algorithms.

Summary

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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.

December 18, 2023

Sydney Neuroimaging Analysis Centre Pty Ltd % Belinda Dowsett Associate Director, Medical Devices / IVD PharmaLex Pty Ltd Suite 10.04. 1 Chandos Street St Leonards, NSW 2064 Australia

Re: K231929

Trade/Device Name: iQ-solutions™ Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH, LLZ Dated: September 19, 2023 Received: September 19, 2023

Dear Belinda Dowsett:

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 (the 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. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. 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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Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).

Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30. Design controls; 21 CFR 820.90. Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).

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 of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

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For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

Daniel M. Krainak, Ph.D. Assistant Director DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration

Indications for Use

Form Approved: OMB No. 0910-0120 Expiration Date: 06/30/2023 See PRA Statement below.

510(k) Number (if known) K231929

Device Name iO-solutionsTM

Indications for Use (Describe)

iQ-solutions™ is a software medical device intended for automatic annotation, visualization, and quantification of segmentable brain structures from a set of brain MRI scans. It is intended to accelerate and improve the quantification of brain structures that would otherwise require a manual process of identifying, and measuring regions of interest in brain MRI scans.

iQ-solutions TM consists of both cross-sectional and longitudinal analysis pipelines.

· The cross-sectional pipeline is intended to conduct structure segmentation and volume analysis on brain MRI scans at a single time point.

· The longitudinal pipeline is intended to conduct volume change analysis on a single patient's MRI scans acquired on the same scanner, with consistent image acquisition protocol and with contrast at two different time points. The results of the cross-sectional pipeline cannot be compared with the results of the longitudinal pipeline.

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)

CONTINUE ON A SEPARATE PAGE IF NEEDED.

This section applies only to requirements of the Paperwork Reduction Act of 1995.

DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.

The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:

Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov

"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."

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510(k) Summary – iQ-solutions™ 5

General Information 5.1

510(k) Sponsor:	Sydney Neuroimaging Analysis Centre Pty Ltd (SNAC)
Address:	Level 1, 94 Mallett StreetCamperdown NSW 2050Australia
Contact Person:	Dr Tim (Chenyu) WangDirector of Operations, Sydney Neuroimaging Analysis Centre
Contact Information:	Email: tim@snac.com.auPhone: + 61 2 9114 4187
Date Prepared:	16 Dec 2023

5.2 Device Name and Classification

Device Name:	iQ-solutions™
Trade Name:	iQ-solutions™
Common Name:	Medical Image Processing Software
Classification Name	System, Image processing, Radiological
Classification Panel:	Radiology
CFR Section:	21 CFR §892.2050
Device Class:	Class II
Product Code	QIH, LLZ

5.3 Predicate Device

Product Name:	icobrain
Device Trade Name:	Icobrain
510(k) Number	K192130
Clearance Date:	December 13, 2019
Manufacturer:	icometrix NV
Common Name	Medical Image Processing Software
Classification Name:	System, Image processing, Radiological
Classification Panel:	Radiology
CFR Section	21 CFR §892.2050

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Device Class	Class II
Product Code	LLZ

5.4 Standards Applied

iQ-solutions™ software has been designed, developed, and tested by the following product and process standards:

. ISO 13485:2016 Medical devices — Quality management systems — Requirements for regulatory purposes
ISO 14971:2019 Medical devices – Application of risk management to medical devices
IEC 62304:2006 + A1:2015 Medical device software software life cycle processes ●
IEC 62366-1:2015 Medical devices – Part 1: Application of usability engineering to medical devices
ISO 12052:2006 Digital Imaging and communication in Medicine (DICOM)
CFR 21 Part 820 Quality System Regulation for Medical Devices

Device Description 5.5

The following flowchart describes the iQ-solutions™ process and analysis:

Image /page/5/Figure/13 description: The image is a flowchart that shows the steps involved in image processing. The first step is to input images in DICOM format. The next steps are pre-processing, image processing, and output generation. The final step is to generate a final report in PDF format, DICOM output images, and dynamic reports in a webpage format.

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iQ-solutions™ takes as input brain MRI scans. During image processing, cross-sectional and longitudinal segmentation is performed, and measurements of the segmented brain structures are provided. The resulting outputs are generated and provided in the form of quantitative reports and the annotation masks of specific segmentations in DICOM format. The reports are in PDF format which are returned to the PACS, together with DICOM images that display colored overlays of specific brain substructures and, where relevant, white matter hyperintensities superimposed on duplicates of the original DICOM images (with watermarks to inform users that these images are not to be used for diagnostic purposes). iQ-solutions™ also provide dynamic reports in a webpage format in which the scan overview panel becomes scrollable, allowing the user to browse through different slices of the scan in the sagittal, coronal, and axial planes.

In this release of iQ-solutions™, the two types of analysis pipelines (cross-sectional study and longitudinal study) are conducted, and different reports are generated together with the generated masks, including:

iQ-MS™ PDF report:

Normalized volume and volume change of the whole brain (sum of white matter and gray matter)
Normalized volume and volume change of gray matter
Normalized volume and volume change of the thalami
Unnormalized volume and volume changes of FLAIR white matter hyperintensities (if any)
Unnormalized volume of T1 post-contrast white matter hyperintensities
Brain and brain substructure volumes compared with a healthy cohort.

iQ-COG™ PDF report:

Normalized volume and volume change of the whole brain (sum of white matter and gray matter)
Normalized volume and volume change of cortical gray matter
Normalized volume of the cortex in brain lobes (frontal, parietal, temporal, occipital)
. Normalized volume and volume change of the hippocampi
Asymmetry index of left and right cortex in lobes and left and right hippocampi
Unnormalized volume and volume changes of FLAIR white matter hyperintensities (if any)
. Brain and brain substructure volumes compared with a healthy cohort.

5.6 Indications for Use

iQ-solutions™ consists of both cross-sectional and longitudinal analysis pipelines.

. The cross-sectional pipeline is intended to conduct structure segmentation and volume analysis on brain MRI scans at a single time point.
. The longitudinal pipeline is intended to conduct volume change analysis on a single patient's MRI scans acquired on the same scanner, with consistent image acquisition protocol and with consistent contrast at two different time points.

The results of the cross-sectional pipeline cannot be compared with the results of the longitudinal pipeline.

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5.7 Comparison with Predicate Device

iQ-solutions™ (subject device) has the same intended use as icobrain 5.0 (K192130) (predicate device) as both are intended for automatic labelling, visualization and volumetric quantification of segmentable brain structures based on three-dimensional medical images. The devices both take 3D images of the brain as input and generate an electronic report with similar quantitative information. The principal difference between the devices is that, in addition to MRI images, the predicate icobrain 5.0 (K192130) is able to process non-contrast CT (NCCT) images (for 'icobrain cross'). This difference does not result in a new intended use; and does not impact the safety or effectiveness of the subject device.

The subject device and the predicate device have different technological characteristics with respect to software features, functionalities and core algorithms. These different technological characteristics do not impact the safety or effectiveness of the subject device: specifically, performance data confirms that the subject device is as safe and effective as the predicate device.

Table 2 shows the comparison between the subject device and its predicate and no major technological differences were found between the two systems that raise new issues of safety and/or effectiveness. Thus, the iQ-solutions™ is substantially equivalent to the predicate device.

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Table 2: Comparison table for iQ-solutions™ as the subject device and icobrain 5.0 (K192130) as the Predicate Device.

Characteristic	Subject device:iQ-solutions™	Predicate Device:icobrain 5.0 (K192130)	Summary
Intended Use	iQ-solutions™ is a software medical deviceintended for automatic annotation,visualization, and quantification ofsegmentable brain structures from a set ofbrain MRI scans. It is intended to accelerateand improve the quantification of brainstructures that would otherwise require amanual process of identifying, annotating, andmeasuring regions of interest in brain MRIscans.iQ-solutions™ consists of both cross-sectionaland longitudinal analysis pipelines.The cross-sectional pipeline is intended toconduct structure segmentation andvolume analysis on brain MRI scans at asingle time point. The longitudinal pipeline is intended toconduct volume change analysis on a singlepatient's MRI scans acquired on the samescanner, with a consistent imageacquisition protocol and with consistentcontrast at two different time points. The results of the cross-sectional pipelinecannot be compared with the results of thelongitudinal pipeline.	icobrain 5.0 is intended for automatic labelling,visualization and volumetric quantification ofsegmentable brain structures from a set ofMRI or Non-Contrast CT (NCCT) images. Thissoftware is intended to automate the currentmanual process of identifying, labelling andquantifying the volume of segmentable brainstructures identified on MRI or NCCT images.icobrain 5.0 consists of two distinct imageprocessing pipelines: icobrain 5.0 cross andicobrain 5.0 long.icobrain 5.0 cross is intended to providevolumes from MRI or NCCT images acquiredat a single brain time point. icobrain 5.0 long is intended to providechanges in volumes between two MRIimages that were brain acquired on thesame scanner, with the same imageacquisition protocol and with the samecontrast at two different time points. The results of the icobrain 5.0 cross cannot becompared with the results of icobrain 5.0 long.	Intended use is the same.There is a difference in functionality that doesnot constitute a major difference.Both devices are intended for automaticlabelling, visualization and quantification ofsegmentable brain structures.Both devices have two pipelines that areintended for cross-sectional analysis andlongitudinal analysis, which are intended forimages from a single time point and differenttime points respectively. The results from thepipelines cannot be compared.iQ-solutions™ works with MRI images only,while icobrain 5.0 works with both MRIimages and NCCT images (only for icobrain 5.0cross). This difference does not result in a newintended use; rather, use with NCCT onlybroadens the application to scenarios in whichNCCT is the preferred input. This differencedoes not affect the safety or effectiveness ofthe subject device.
TechnologicalCharacteristics	Software package, with off-the-shelfsoftwareOperates on off-the-shelf hardware(multiple vendors)	Software package, with off-the-shelfsoftwareOperates on off-the-shelf hardware(multiple vendors)DICOM compatible	Same.
Characteristic	Subject device:iQ-solutions™	Predicate Device:icobrain 5.0 (K192130)	Summary
	DICOM compatible Segmentation by machine learning anddeep learning algorithms (supervisedsegmentation with Convolutional NeuralNetworks) Image pre-processing components Measurement calculation Report generation techniques	Segmentation by classical machine learningand deep learning (supervised voxelclassification with Convolutional NeuralNetworks) Image pre-processing components Measurement calculation Report generation techniques
Anatomical Regionof Interest	Head	Head	Same
Product Input(Data AcquisitionProtocol)	Pre-contrast T1-weighted MRI scans fromsingle or multiple time points, Fluid-attenuated inversion recovery (FLAIR)MRI scans from single or multiple timepoints, and Post-contrast T1-weighted MRI scans froma single time point.	T1-weighted and fluid-attenuated inversionrecovery (FLAIR) MRI images from a singleor multiple time points Non-contrast CT (NCCT) from a single timepoint.	Similar.Both the subject device and the predicatedevice process T1 and FLAIR MRI images fromsingle or multiple time points.NCCT may be used with icobrain 5.0 but not thesubject device; lack of this additional inputcompatibility does not impact the safety orclinical function of the subject device.
Product Output	Multiple electronic reports with volumetricinformation on brain structures and whitematter hyperintensities (if any) Automatically compares results toreference percentile data and to prior scanswhen available Annotated DICOM images that can bedisplayed on DICOM workstations andPicture Archive and CommunicationsSystems (PACS)	Multiple electronic reports with volumetricinformation on brain structures andhyperintensities and midline shift (for NCCTonly) Automatically compares results to areference healthy population data and toprior scans when available Annotated DICOM images that can bedisplayed on DICOM workstations andPicture Archive and CommunicationsSystems (PACS)	Similar.icobrain 5.0 additionally outputs the degree of'midline shift' but this is calculated on NCCT(relevant to specific clinical scenarios only). AsiQ-solutions™ does not analyze NCCT, thisdifference does not impact the safety of thesubject device and is not clinically significant
Characteristic	Subject device:iQ-solutions™	Predicate Device:icobrain 5.0 (K192130)	Summary
Findings Covered	MR:Normalized volume and volume changes of the whole brain Normalized volume and volume changes of gray matter Normalized volume and volume changes of cortical gray matter Normalized cortical volumes of cortex in brain lobes (frontal, temporal, parietal and occipital) Normalized volume and volume changes in the hippocampi Normalized volume and volume changes of the thalamus Asymmetry index of structures, including cortex in lobes and hippocampus Unnormalized volume and volume changes of FLAIR white matter hyperintensities Unnormalized volume and volume changes of T1-w white matter hyperintensities (in post-contrast T1-w only)	MR:Normalized volume and volume changes of the whole brain Normalized volume and volume changes of gray matter Normalized volume and volume changes of cortical gray matter Normalized volume and volume changes of cortex in frontal, temporal, parietal and occipital lobes Normalized volume and volume changes in the hippocampi Normalized volume and volume change of left and right hippocampus Asymmetry index of structures, including cortex in lobes and hippocampus Unnormalized volume and volume changes of FLAIR white matter hyperintensities FLAIR white matter hyperintensities in different regions (juxtacortical, periventricular, deep white matter and infratentorial). Unnormalized volume and volume changes of T1-w white matter hyperintensities and hypointensities CT: Normalized volumes of the whole brain Normalized volumes of the lateral ventricles Normalized volumes of basal cisterns	Similar.iQ-solutions™ does not process NCCT images and therefore does not report findings for CT images.For head MRI analysis, iQ-solutions™ is similar to icobrain 5.0, except that the subject device iQ-solutions™ does not report statistics related to regional (lobar) cortical volume change or T1-w image-derived hypo-intensities. iQ-solutions™ additionally reports volume analysis of the thalamus.These differences are not expected to affect the safety or effectiveness of the subject device or to be clinically significant in the proposed intended use.
Characteristic	Subject device:iQ-solutions™	Predicate Device:icobrain 5.0 (K192130)	Summary
		Measurement of midline shiftVolume of hyperintensities
Removal of Casesfrom the WorklistQueue	No	No	Same
Performancemeasurementtesting	Accuracy (for MRI only)Brain segmentable structurevolumes/volume changes compared to FSLgenerated and manually verified groundtruth. Reproducibility (for MRI only) Brain segmentable structurevolumes/volume changes compared to test-retest images	Accuracy for MRI measurement Brain segmentable structure volumes/volume changes compared to simulated and/or manually labelled ground truth. Accuracy for CT measurement lesions and midline shift compared to manually labelled ground truth lateral ventricles and the whole brain: MRI images segmented by cleared icobrain 3.0 software taken as ground truth Reproducibility for MRI measurement Brain segmentable structure volumes/volume changes compared to test- retest images. Reproducibility for CT measurements Simulation study	Same for MRI measurements.As iQ-solutions™ is not designed to analyze CTimages, the measurements for CT input are notapplicable in the subject device.
Environment ofUse	iQ-solutions™ is used by trained professionalsin hospitals, imaging centers or in image-processing labs	icobrain 5.0 is used by trained professionals inhospitals, imaging centers or image-processinglabs	Same
Tested Items	Product Risk AssessmentSoftware verification testsSoftware validation tests	Product Risk AssessmentSoftware verification testsSoftware validation tests	Same

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SNAC has determined that the predicate icobrain 5.0 (K192130) has similar technological and performance characteristics with respect to the segmentation and quantification of normalized volume and volume changes of different brain structures, including the whole brain, the gray matter, the cortical gray matter and the cortex in the brain lobes; the unnormalized volume and volume changes of FLAIR white matter hyperintensities; and the volume of contrast-enhancing T1 white matter hyperintensities. The differences between the subject device and the predicate device are not considered to be substantial or significant in the proposed intended use.

The conclusions from the verification and validation data support the assertion that the safety and effectiveness of the subject and predicate devices are equivalent; and that any differences in the technological characteristics and functionalities of the subject device do not alter/impact its intended use relative to the predicate product or have any additional implications with respect to safety or efficacy. We (SNAC) conclude that iQ-solutions™ is substantially equivalent to icobrain 5.0.

5.8 Performance Data

Each algorithm was tested using the test dataset, which was further verified by trained neuroimaging analysts and expert radiologists. All algorithms within iQ-solutions™ were verified to have generated results/metrics for compatible scans that met the pre-determined acceptance level(s).

5.9 Data Preparation and Demographics Info

The algorithms were developed based on SNAC in-house datasets collected from more than 1500 patients over a period of ten years, commencing July 2012, acquired from a wide range of clinical scanners, including 1.5T and 3T scanners from Siemens (1750 scans in total), GE (2214 scans in total) and Philips (1593 scans in total). Additionally, publicly available MRI datasets from healthy people were included for both training and testing, including 2629 scans obtained from 2159 subjects. The demographic information is included in Table 3.

Datasets	Diagnosis(subject/scans)	Number ofSubjects (F/M)	Age (mean ± std)	Number of Scans(Vendor:1.5T/3T)
PublicData	Healthy (1823/2225),Dementia (336/404)	2159 (1146/1013)	18y to 95y(44.84±20.63)	2629, including SIEMENS(347/1449), Philips(307/208), GE (79/221)and others.
PrivateData	Multiple sclerosis(1570/5664)	1570 (1069/501)	18y to 93y(44.02±13.49)	5664, including SIEMENS(698/1052), Philips(243/1350), GE(1008/1206) and others.

Table 3. Demographic Summary for Used Data

The in-house dataset contains patients diagnosed with multiple sclerosis, and the patients are also with brain atrophy and related cognitive dysfunctions. The scans of healthy people were also included in the training process to avoid bias. Table 4 summarizes the number of cases and involved subjects used in training and testing all the algorithms.

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Analysis Modules/Datasets	Number of Cases(Train/Validation)	Number ofCases (Test)	Number ofSubjects (All)
Sequence Classification	4862	1207	2784
Brain Extraction	1843	458	1454
Scaling Factor Estimation	2986	527	3513
White matter hyperintensity Segmentation	1858	464	1026
Contrast-Enhancing Lesion Segmentation	79	737	310
Lesion Inpainting	449	80	529
Brain Tissue Segmentation	4179	500	3313
Brain Volume Change Estimation	1487	166	1648
WMH Lesion Activity	116	64	180
Cortical Lobar and Subcortical StructureSegmentation	Not applicable **	1504	1436
Test-ReTest Dataset	Not applicable **	120	3
Comprehensive Test Set	Not applicable **	81	81

Table 4. Summary of Number of Cases used in Developing/Evaluating Analysis Modules

5.10 Data Annotation and Acceptance Criteria

All data used for development were manually labelled to form the ground truth. The labelled items included sequence types (pre-contrast or post-contrast, T1-weighted or FLAR, brainbased or spine-based), skull and scaling factor based on skulls, skull stripped head, brain tissues (white matter, gray matter and CSF), white matter hyperintensities in patients, contrast-enhancing lesions, white matter hyperintensity lesion changes (new lesions or enlarged lesions), cortical gray matter lobes, thalamus, hippocampus, brain volume change. Specifically, the annotations for skullstripping, brain tissues, cortical gray matter lobes, thalamus, hippocampus, and brain volume changes were originally generated using widely used software items such as FSL and FreeSurfer, and the annotations were manually reviewed and accepted by trained neuroimaging analysts. The annotations for white matter hyperintensities (including pre-contrast ones, contrast-enhancing ones, and lesion changes) were manually annotated by trained neuroimaging analysts. All the annotations are further reviewed by senior neuroimaging analysts according to SNAC SOP.

The Pass/Fail criteria are based on both the metrics and acceptable rate of the manual review. For classification modules, accuracy is higher than 0.9 to be accepted; for segmentation modules, DICE score is higher than 0.6 (for brains the DICE should be higher than 0.9) or R² is higher than 0.7 to be accepted. For modules that are lack of ground truths (scaling factor estimation, lesion inpainting, and substructure volume change estimation), the metrics are better than previously accepted results to be accepted. For all models, the manual acceptable rate should be higher than 80% to call it acceptable.

5.11 Data Split

When used for development, the data were split into training, validation, and test splits. For the training/validation/test splits of each task, the same subject was ensured to be included in only one of the three splits, therefore it is ensured the same subject was not used for training and evaluation. The splits of each analysis component have been reviewed before the development process.

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Besides the data used for development, 81 extra patients were reserved as the Comprehensive Test Set, which is used to evaluate the performance of all the analysis components.

5.12 Verification and Validation Result

The performance data demonstrates continued conformance with special controls for medical devices containing software. Non-clinical tests were conducted on the subject device during product development.

Software "bench" testing was performed to evaluate the performance and functionality of the technical characteristics of iQ-solutions™. All testable requirement Specifications and the Risk Analysis have been successfully verified and traced.

Analysis Modules	Metric Result	Acceptable Rate	Pass/Fail
Sequence Classification	Accuracy = 100%	100%	Pass
Brain Extraction	DICE = 0.982	99.3%	Pass
Scaling Factor Estimation	STD = 0.0096	100%	Pass
White matter hyperintensity Segmentation	DICE = 0.789	98.8%	Pass
Contrast-Enhancing Lesion Segmentation	DICE = 0.790	92.1%	Pass
Lesion Inpainting	PSNR = 30.79dB	97.5%	Pass
Brain Tissue Segmentation	DICE = 0.972	100%	Pass
Brain Volume Change Estimation	$R^2 = 0.869$	96.3%	Pass
WMH Lesion Activity	$R^2 = 0.833$	97.5%	Pass
Cortical Lobar and Subcortical StructureSegmentation	$R^2 = 0.833$	96.0%	Pass
Substructure Volume Change Estimation	STD = 0.0102	98.8%	Pass

Table 5: Summary of Performances of all the Analysis Modules

The conclusions from the verification and validation data support the assertion that the safety and effectiveness of the subject and predicate devices are equivalent; and that any differences in the technological characteristics and functionalities of the subject device do not alter/impact its intended use relative to the predicate product or have any additional implications with respect to safety or efficacy. SNAC concludes that iQ-solutions™ is substantially equivalent to icobrain 5.0 (K192130).

5.13 Non-Clinical Tests

Non-clinical tests were conducted to test the functionality of iQ-solutions™. Software validation and bench testing have been conducted to assess the performance claims as well as the claim of substantial equivalence to the predicate device. A summary of tests is provided in Table 5 above.

iQ-solutions™ has been tested to meet the requirements of conformity to multiple industry standards. Non-clinical performance testing demonstrates that iQ-solutions™ complies with the FDA guidance document, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" (May 11, 2005).

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5.14 Clinical Tests

No clinical tests were conducted to test the performance and functionality of the subject device as verification and validation of the subject device have been performed through non-clinical bench testing. The data from non-clinical bench testing activities were used to support the subject device and the substantial equivalence argument. No animal testing has been performed on the subject device.

5.15 Conclusion

The performance testing presented above establishes that iQ-solutions™ is equivalent concerning safety and effectiveness of the predicate device. The differences in the iQ-solutions™ technological characteristics do not affect the intended use of the iQ-solutions™ device is substantially equivalent to the currently marketed device icobrain 5.0 (K192130).

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).