ClearPoint Maestro Brain Model

{0}------------------------------------------------ Image /page/0/Picture/0 description: The image shows 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. August 8, 2022 ClearPoint Neuro, Inc. % John J. Smith Partner Hogan Lovells US LPP 555 Thirteenth St., NW WASHINGTON DC 20004 Re: K213645 Trade/Device Name: ClearPoint Maestro™ Brain Model Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: OIH Dated: June 16, 2022 Received: June 16, 2022 Dear John Smith: 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). 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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, for Michael D. O'Hara, Ph.D. Deputy 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 {2}------------------------------------------------ 510(k) Number (if known) K213645 #### Device Name #### ClearPoint Maestro™ Brain Model #### Indications for Use (Describe) ClearPoint Maestro™ Brain Model is intended for automatic labeling, visualization, volumetric and shape quantification of segmentable brain structures from a set of MR images. This software is intended to automate the process of identifying, labelling, and quantifying the volume and shape of brain structures visible in MRI images. Type of Use (Select one or both, as applicable) | X 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}------------------------------------------------ K213645 # 510(k) Summary ## ClearPoint Neuro's ClearPoint Maestro™ Brain Model ### Submitter ClearPoint Neuro. Inc. 5 Musick Irvine, CA 92618 Phone: (888) 287-9109 Contact Person: Megan Faulkenberry, VP, Quality and Regulatory Date Prepared: August 5, 2022 Name of Device: ClearPoint Maestro™ Brain Model Common or Usual Name: System, Image Processing, Radiological Classification Name: Medical Image Management and Processing System (892.2050) Regulatory Class: Class II Product Code: QIH ### Predicate Devices CorTech Labs, Inc. - NeuroQuant (K061855) #### Device Description The ClearPoint Maestro™ Brain Model provides automated image processing of brain structures from T1-weighted MR images. Specifically, the device automates the manual process of identifying, labeling, and quantifying the volume and shape of subcortical structures to simplify the workflow for MRI segmentation. The ClearPoint Maestro™ Brain Model consists of the following key functional modules. - DICOM Read Module . - Segmentation Module ● - Visualization Module ● - . Exporting Module The segmented brain structures are color coded and overlayed onto the MR images or be displayed as 3-D triangular mesh representation. The viewing capabilities of the device also provides anatomic orientation labels (left, right, inferior, superior, anterior, posterior), image slice selection, standard image manipulation such as contrast adjustment, rotation, zoom, and the ability to adjust the transparency of the image overlay. {4}------------------------------------------------ The output from ClearPoint Maestro™ Brain Model can also exported as a report in PDF format. The report also provides a comparison of segmented volume to normative values of brain structures based on reference data. # Intended Use / Indications for Use ClearPoint Maestro™ Brain Model is intended for automatic labeling, visualization, volumetric and shape quantification of segmentable brain structures from a set of MR images. This software is intended to automate the process of identifying, labelling, and quantifying the volume and shape of brain structures visible in MRI images. ## Comparison of Technological Characteristics with Predicate Device Both ClearPoint Maestro™ Brain Model and NeuroQuant automate MR image post-processing to provide labeling, visualization, and volumetric quantification of brain structures. Both systems use as input clinical T1-weighted brain MR scans and automatically provide quantification of brain structures. The output results are provided in DICOM format and provide the segmented structures as a color-coded overlay onto the image series. The results can also be exported within a report as a PDF. There are minor technological differences between the ClearPoint Maestro™ Brain Model and NeuroQuant. Notably, NeuroQuant performs automatic segmentation and quantification of brain structures using a probabilistic neuroanatomical atlas based on MR image intensity, while ClearPoint Maestro™ Brain Model uses shape-constrained segmentation of sub-cortical brain regions, the hemispheres, and the cerebellum, followed by voxel-wise tissue parcellation of the hemispheres and the cerebellum into tissue types. However, based on the assessment of device performance, these minor differences do not affect safety and effectiveness. Both ClearPoint Maestro™ Brain Model and NeuroQuant are intended to be used by medical professionals such as radiologists, neurologists, and neuroradiologists as a tool to aid in the assessment and the simplification of the workflow for MR image segmentation. ### Performance Data The segmentation accuracy and reproducibility of ClearPoint Maestro™ Brain Model was assessed by comparing the device output to manually labeled data T1-weighted MRI data. The segmentation accuracy success was defined as Dice coefficient >0.7 and relative volume difference <0.3 between the device output and manually labeled data for the validation of the validation data. The reproducibility success criteria were defined as absolute volume differences <15% between segmentation performed on two repeated scans. The means of computed Dice coefficients for 21 segmented brain structures in 101 subjects from the validation dataset were significantly greater than 70%, meeting the acceptance criteria. This result was observed in both the full population and in all subgroups. The only region with a mean Dice coefficient less than 70% was the third ventricle, which was attributed to variability in the manual labeling rather than device performance. This was further supported by the ClearPoint Maestro™ Brain Model reproducibility results, which showed that the device provided results while the manual labeling showed large variability. {5}------------------------------------------------ The means of computed relative volume differences for 21 segmented brain structures in 101 subjects from the validation dataset were significantly less than 0.3, meeting the acceptance criteria. This result was observed in the full population and in all subgroups except one (18-25yo) where the left and right lateral ventricles were with higher means. That was again attributed to variability in the manual labeling rather than device performance. In the reproducibility analysis, absolute volume differences using ClearPoint Maestro Brain Model 1.0 to segment the repeated scans in the 20Repeat data set were less than 10% for all segmented brain regions, including the third ventricle. Machine learning derived outputs are the volumes of the gray and white matter in the cerebellum and the left and right cerebral hemispheres: Cerebellum GM, Cerebellum WM, L Cortical GM, and R Cortical GM, L Cortical WM, R Cortical WM. The training data was created by the three technical experts at Philips Research Hamburg. Validation was performed in 101 subjects from the validation dataset, which was completely independent from the training data created by Philips. All machine learning derived outputs met the acceptance criteria. Their Dice coefficient was greater than 70% and their mean relative volume difference was less than 0.3 in both the full population and in all subgroups. Based on the bench testing performance, the ClearPoint Maestro™ Brain Model has a safety and effectiveness profile that is similar to the predicate device. # Conclusion The ClearPoint Maestro™Brain Model has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences in indications do not alter the intended use of the device and do not affect its safety and effectiveness when used as labeled. In addition, the minor technological differences between the ClearPoint Maestro™ Brain Model and its predicate devices raise no new issues of safety or effectiveness. Performance data demonstrate that the ClearPoint Maestro™ Brain Model is as safe and effective as NeuroQuant. Thus, the ClearPoint Maestro™ Brain Model is substantially equivalent.