Who is the manufacturer of Pixyl.Neuro?

Pixyl SA filed the 510(k) submission for Pixyl.Neuro (K213253).

What is the FDA product code for Pixyl.Neuro?

LLZ. It is classified under 21 CFR 892.2050 as a Class 2 device in the Radiology panel.

What is the regulatory pathway for Pixyl.Neuro?

510(k) clearance (submission type: Traditional).

Does Pixyl.Neuro use AI or machine learning?

Yes. Pixyl.Neuro (K213253) is flagged as an AI/ML-enabled medical device in the FDA's AI/ML device list.

Who can help prepare an FDA 510(k) submission like Pixyl.Neuro?

Innolitics — a medical-device software consultancy — provides regulatory and engineering support for FDA 510(k) submissions. See https://innolitics.com/services/510ks/ or contact https://innolitics.com/contact.

Can an AI/ML device like Pixyl.Neuro get a guaranteed FDA 510(k) clearance?

Yes. Innolitics offers a guaranteed FDA 510(k) clearance engagement for AI/ML Software as a Medical Device — combining engineering and regulatory execution under one agreement with a guaranteed clearance outcome. Eligibility: the device must be an AI/ML Software as a Medical Device (SaMD), and its performance must meet the criteria Innolitics determines during an initial regulatory strategy engagement to be necessary for FDA clearance. See https://innolitics.com/services/end-to-end-samd/ or contact https://innolitics.com/contact.

Pixyl.Neuro

K213253 · Pixyl SA · LLZ · Jun 30, 2023 · Radiology

Device Facts

Record ID	K213253
Device Name	Pixyl.Neuro
Applicant	Pixyl SA
Product Code	LLZ · Radiology
Decision Date	Jun 30, 2023
Decision	SESE
Submission Type	Traditional
Regulation	21 CFR 892.2050
Device Class	Class 2
Attributes	AI/ML, Software as a Medical Device

Intended Use

Pixyl.Neuro is intended for automatic labeling, visualization and volumetric quantification of segmentable brain structures and lesions from a set of MRI images. Volumetric measurements may be compared to reference percentile data.

Device Story

Pixyl.Neuro is a cloud-based software application for automated analysis of brain MRI images (2D/3D T1 or FLAIR). It processes DICOM inputs through an internal pipeline performing artifact correction, segmentation, and volume calculation. The device outputs segmented color overlays and morphometric reports, which are displayed on standard DICOM workstations/PACS. Used by clinicians in routine settings or research to manage patients with neurological disorders; results must be reviewed by a trained physician. The device provides volumetric measurements and compares them to reference percentile data or prior scans, aiding clinical decision-making by quantifying brain structure and lesion volumes.

Clinical Evidence

Bench testing only. Evaluated on 238 subject datasets (healthy, MS, Alzheimer's, microangiopathy, white matter hyperintensities). Accuracy measured via Dice coefficient: 0.80 (+/- 0.06) and 0.730 (+/- 0.10) for MS/FL modules; 0.84 (+/- 0.02) and 0.83 (+/- 0.02) for BV module. Reproducibility (scan/re-scan) mean absolute volume difference: 0.199 ml (+/- 0.193) for MS/FL; 0.966 ml (+/- 1.098) for BV module. All experiments met acceptance criteria.

Technological Characteristics

Cloud-based software; Linux OS. Inputs: 2D/3D T1 or FLAIR MRI (DICOM). Automated pipeline: artifact correction, segmentation, volume calculation. Quality control: tissue contrast check, scan protocol verification. No atlas alignment check. Output: DICOM-compatible volumetric reports and overlays.

Indications for Use

Indicated for automatic labeling, visualization, and volumetric quantification of brain structures and lesions from MRI images in patients with neurological disorders, including multiple sclerosis, Alzheimer's, microangiopathy, and white matter hyperintensities.

Regulatory Classification

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.

Special Controls

*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).

Predicate Devices

NeuroQuant (K170981)

Related Devices

K193287 — CorInsights MRI · Adm Diagnostics, Inc. · Nov 20, 2020
K170981 — NeuroQuant · Cortechs Labs, Inc. · Sep 7, 2017
K231398 — VUNO Med-DeepBrain · Vuno, Inc. · Oct 4, 2023
K242215 — Neurophet AQUA (V3.1) · Neurophet., Inc. · Oct 25, 2024
K251483 — SwiftSight-Brain · Airs Medical, Inc. · Sep 23, 2025

Submission Summary (Full Text)

{0}------------------------------------------------ Image /page/0/Picture/0 description: The image contains the logos of the Department of Health & Human Services and the Food and Drug Administration (FDA). The Department of Health & Human Services logo is on the left, and the FDA logo is on the right. The FDA logo includes the agency's name, "U.S. Food & Drug Administration," in blue text. June 30, 2023 Pixyl SA % Robert Packard President Medical Device Academy Inc. 345 Lincoln Hill Road SHREWSBURY VT 05738 Re: K213253 Trade/Device Name: Pixyl.Neuro Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: May 26, 2023 Received: May 26, 2023 Dear Robert Packard: 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. 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 located 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. 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 {1}------------------------------------------------ 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 803) for devices or postmarketing safety reporting (21 CFR 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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050. 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 https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems. For comprehensive regulatory information about medical devices and radiation-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 Magnetic Resonance and Nuclear Medicine Team 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 {2}------------------------------------------------ ## Indications for Use 510(k) Number (if known) K213253 Device Name Pixyl.Neuro Indications for Use (Describe) Pixyl.Neuro is intended for automatic labeling, visualization of segmentable brain structures and lesions from a set of MRI images. Volumetric measurements may be compared to reference percentile data. 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." {3}------------------------------------------------ system # 510(k) SUMMARY This summary of 510(k) safety and effectiveness information is submitted in accordance with the requirements of 21 CFR §807.92: | SUBMITTER | | |--------------------------|--| | Pixyl SAS | | | 5 Avenue du Grand Sablon | | | La Tronche, 38700 France | | | +33 6 19 53 14 48 | | | Contact Person: | Senan Doyle | |-----------------|----------------------| | Date Prepared: | September 29th, 2021 | | II. DEVICE | | |------------------------------|-----------------------------------------| | Name of Device: | Pixyl.Neuro | | Classification Name: | Medical image management and processing | | Regulation: | 21 CFR §892.2050 | | Regulatory Class: | Class II | | Product Classification Code: | LLZ | | III. PREDICATE DEVICE | | | Predicate Manufacturer: | CorTechs Labs, Inc | |-------------------------|--------------------| | Predicate Trade Name: | NeuroQuant | | Predicate 510(k): | K170981 | No reference devices were used in this submission. #### IV. DEVICE DESCRIPTION Pixyl.Neuro is a software application for the analysis of medical images of the brain. Specifically, the application takes as input MRI images and outputs brain region volumes and lesion volumes in a report format. The application is designed to be used by clinicians treating patients with a range of neurological disorders. The application can be used in the management of patients in a routine setting and in clinical research. #### V. INDICATIONS FOR USE Pixyl.Neuro is intended for automatic labeling, visualization and volumetric quantification of segmentable brain structures and lesions from a set of MRI images. Volumetric measurements may be compared to reference percentile data. {4}------------------------------------------------ ### COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE VI. PREDICATE DEVICE The following characteristics were compared between the subject device and the predicate device in order to demonstrate substantial equivalence: | Device | Pixyl.Neuro | NeuroQuant® (K170981) | Comments | |------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Indications for Use | Pixyl.Neuro is intended for automatic labeling, visualization and volumetric quantification of segmentable brain structures and lesions from a set of MRI images. Volumetric measurements may be compared to reference percentile data. | NeuroQuant® is intended for automatic labeling, Visualization and volumetric quantification of segmentable brain structures and lesions from a set of MR images. Volumetric measurements may be compared to reference percentile data. | Substantially equivalent. | | Design and Incorporated Technology | • Automated measurement and segmentation of brain tissue volumes and structures | • Automated measurement of brain tissue volumes and structures • Automatic segmentation and quantification of brain structures using a probabilistic neuroanatomical atlas based on the MR image intensity | Input and output data and validation methods are similar, although incorporated technology applied to the segmentation techniques may differ. This does not introduce any additional risk since results are comparable. | | Physical characteristics | • Cloud-based software launchable through Picture Archive and Communications Systems (multiple vendors) • Operates on off-the-shelf hardware/platform (multiple vendors) | • Software package • Operates on off-the-shelf hardware (multiple vendors) | Pixyl.Neuro is accessible through users' preferred platforms, directly from their work stations. This does not introduce any additional risk since the use of Pixyl.Neuro is seamlessly integrated into their routine work practice, and does not require any installation or tuning from the end users. | | Operating System | Linux | Supports Linux and Mac OS X | Substantially equivalent. | | Processing Architecture | Automated internal pipeline that performs: - artifact correction - segmentation - volume calculation | Automated internal pipeline that performs: - artifact correction - segmentation - volume calculation | Substantially equivalent. | | Data Source | MRI scanner: 2D or 3D FLAIR or T1 MRI scans acquired with specified protocols. Pixyl.Neuro supports DICOM format as input. | MRI scanner: 3D T1 MRI scans acquired with specified protocols • NeuroQuant® Supports DICOM format as input | Pixyl.Neuro supports more options for input MRI sequences. This does not introduce any new risks. Clinical performance evaluation is also performed on these additional inputs. | | Output | • Provides volumetric measurements of brain structures. • Includes segmented color overlays and morphometric reports | • Provides volumetric measurements of brain structures • Includes segmented color overlays and morphometric reports | Substantially equivalent. | | | • Automatically compares results to reference percentile data and to prior scans when available | • Automatically compares results to reference percentile data and to prior scans when available | | | | • Supports DICOM format as output of results that can be displayed on DICOM workstations and Picture Archive and Communications Systems | • Supports DICOM format as output of results that can be displayed on DICOM workstations and Picture Archive and Communications Systems | | | Safety | • Automated quality control functions: - Tissue contrast check - Scan protocol verification • Results must be reviewed by a trained physician | • Automated quality control functions - Tissue contrast check - Scan protocol verification - Atlas alignment check • Results must be reviewed by a trained physician | Pixyl.Neuro does not perform atlas alignment checks as part of its automated quality control functions. However, the transform used in Pixyl.Neuro's registration step is widely used in neuroimaging as the base step of further image processing. In addition, misalignments are generated on the training dataset for the algorithms to learn the variability of the alignment on the atlases. It has been estimated that this does not introduce any additional risk. | {5}------------------------------------------------ {6}------------------------------------------------ #### VII. PERFORMANCE DATA To demonstrate the performance of Pixyl.Neuro, the measured volumes and volume changes of the segmented brain structures are validated for accuracy and reproducibility. The device was tested upon subjects from the following groups: healthy subjects, multiple sclerosis patients, Alzheimer's patients, microangiopathy patients and white matter hyperintensities (of presumed vascular origin) patients. In the accuracy experiments, the volumes or volume changes are compared to ground truth volumes or volume changes. In the reproducibility experiments, scan / re-scan sessions of the same patients are processed by Pixyl.Neuro and the calculated volumes compared between the two scans. Relevant acceptance criteria have been set based on the results of a literature review for each type of experiment. All experiments passed the acceptance criteria. The experiments included a total of 238 subject datasets. The segmentation accuracy of Pixyl.Neuro compared to the reference was evaluated using the Dice coefficient metric. The Dice coefficient between the compared measurements is as follows for the different analysis pipelines of Pixyl.Neuro: 0.80 (+/- 0.06) and 0.730 (+/- 0.10) (calculated at the subject level) for MS and FL according to the used testing dataset; 0.84 (+/- 0.02) and 0.83 (+/- 0.02) (averaged Dice scores across the labeled brain structures) for BV according to the used testing dataset. For reproducibility analyses, the mean absolute volume difference between the calculated total lesion volumes from the two scans is: 0.199 ml (+/- 0.193) for the MS and FL modules (total lesion load) and 0.966 ml (+/- 1.098) (mean across de 20 brain structures) for the BV module. #### VIII. CONCLUSIONS The performance testing presented above shows that the device is as safe, as effective and performs as well as the predicate device. By virtue of the physical characteristics and intended use, Pixyl Neuro is substantially equivalent to its predicate device and its technological improvements do not raise new questions of safety and effectiveness.