aprevo® Digital Segmentation software is intended to be used by trained, medically knowledgeable design personnel to perform digital image segmentation of the spine, primarily lumbar anatomy. The device inputs DICOM images and outputs a 3-D model of the spine.

Device Description

The device is a software medical device that will use DICOM images as input and provide 3D model of the spine structure. Pre-processing will be performed on the uploaded DICOM files to filter soft tissue and identifying spine. Upon removal of soft tissue and identification of spine structure, the software will utilize an AI-based algorithm to segment the structure and render a 3D model as an output.

AI/ML Overview

The provided text describes the acceptance criteria and the study that proves the device meets those criteria for the "aprevo® Digital Segmentation" software.

Here's a breakdown of the requested information:

Acceptance Criteria and Device Performance

Acceptance Criteria	Reported Device Performance
IOU (Intersection Over Union) score > 80%	Exceeded 80%
Vertebral body labeling accuracy > 90%	Exceeded 90% overall
Vertebral body labeling sensitivity > 80%	Exceeded 80%
Vertebral body labeling specificity > 80%	Exceeded 80%

Study Details:

Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: Not explicitly stated in the provided text, but it mentions that "Independent training and validation datasets were selected to ensure model performance would reflect real clinical performance" and "Validation datasets represented diversity in populations and equipment."
- Data Provenance: Not explicitly stated, however, the phrase "diversity in populations and equipment" suggests data from various sources but does not specify countries of origin. The study was a "Non-Clinical Testing" which implies retrospective data.
Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
- Not specified. The document states that the ground truth for the algorithm was used for model performance evaluation, but does not detail how this ground truth was established, or the number/qualifications of experts involved.
Adjudication Method for the Test Set:
- Not specified.
Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- If done: No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned or indicated. The document states "CLINICAL TESTING: Not applicable." The study solely focuses on the standalone performance of the software.
- Effect size of human readers improvement: Not applicable, as no MRMC study was conducted.
Standalone Performance (Algorithm only without human-in-the-loop):
- If done: Yes, a standalone performance evaluation was done. The "NON-CLINICAL TESTING" section describes the evaluation of the "software performance" using IOU and accuracy metrics for segmentation and labeling, without human intervention in the reported performance metrics.
Type of Ground Truth Used:
- The type of ground truth used is not explicitly stated as expert consensus, pathology, or outcomes data. However, for "segmentation" and "vertebral body labeling," the ground truth would typically be established by expert annotation or a similar gold standard, refined through a consensus process, but this is not detailed.
Sample Size for the Training Set:
- Not explicitly stated. It only mentions that "Independent training and validation datasets were selected to ensure model performance would reflect real clinical performance."
How the Ground Truth for the Training Set Was Established:
- Not explicitly stated. The document mentions that "Independent training and validation datasets were selected," but does not elaborate on the method used to establish the ground truth for the training data (e.g., expert annotations, manual segmentation).

Summary

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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food & 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.

Carlsmed, Inc. Karen Liu VP Quality and Regulatory 1800 Aston Ave. Suite 100 SAN DIEGO, CALIFORNIA 92008

Re: K231955

November 3, 2023

Trade/Device Name: aprevo® Digital Segmentation Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH Dated: September 28, 2023 Received: October 5, 2023

Dear Karen Liu:

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/cdrb/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.

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).

U.S. Food & Drug Administration 10903 New Hampshire Avenue Silver Spring, MD 20993 www.fda.gov

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ements, the Quality System (QS) regulation (21 CFR Part

Page 2

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.

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).

Sincerelv.

Jessica Lamb

Jessica Lamb Assistant Director DHT8B: Division of Radiologic Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

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DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration

Indications for Use

Submission Number (if known)

K231955

Device Name

aprevo® Digital Segmentation

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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K231955 510(K) SUMMARY

Submitter's Name:	Carlsmed, Inc.
Submitter's Address:	1800 Aston Ave, Ste 100Carlsbad, CA 92008
Submitter's Telephone:	760-766-1926
Contact Person:	Karen Liu, VP Quality and RegulatoryCarlsmed, Inc.1800 Aston Avenue Suite 100Carlsbad, CA 92008760-766-1926regulatory@carlsmed.com
Date Summary was Prepared:	October 31, 2023
Trade or Proprietary Name:	aprevo® Digital Segmentation
Predicate Clearance Numbersand Name	K183105, Mimics Medical
Reference Device Numberand Name	K202034 aprevo™ Intervertebral Body Fusion DeviceK201232 Limbus Contour
Common or Usual Name:	Medical Image Management and Processing System
Classification:	Class II per 21 CFR §892.2050
Product Code:	QIH
Classification Panel:	Radiology

DESCRIPTION OF THE DEVICE SUBJECT TO PREMARKET NOTIFICATION:

INDICATIONS FOR USE

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TECHNOLOGICAL CHARACTERISTICS

The aprevo® Digital Segmentation will allow the user to import, visualize and segment medical images, check and correct the segmentations, and create digital 3D models. The software functionality is equivalent to the predicate device (Mimics Medical, K183105) from intended use and technological characteristics, and does not raise any new question of safety and effectiveness.

SUBSTANTIAL EQUIVALENCE

The subject device, aprevo® Digital Segmentation is software intended to segment spine bony structure in an automated manner. The device has similar intended use and technological characteristics to its predicate device Mimics Medical. The table below includes detail on comparison between the subject device to its predicate device, Mimics Medical (K183105)

Characteristic	Subject Device	Predicate Device	Differences
Name	aprevo® DigitalSegmentation	Mimics Medical
ClearanceNumber	K231955	K183105
RegulationNumber	892.2050	892.2050	Identical
Product Code	QIH	LLZ	Similar: both are ImageProcessing Systems
Indications ForUse	aprevo® DigitalSegmentation softwareis intended to be usedby trained, medicallyknowledgeable designpersonnel to performdigital imagesegmentation of thespine, primarilylumbar anatomy. Thedevice inputs DICOMimages and outputs a3-D model of thespine.	Mimics Medical isintended for use as asoftware interface andimage segmentation systemfor the transfer of medicalimaging information to anoutput file. MimicsMedical is also intended formeasuring and treatmentplanning.The Mimics Medicaloutput can be used for thefabrication of physicalreplicas of the output fileusing traditional or additivemanufacturing methods.The physical replica can beused for diagnosticpurposes in the field oforthopaedic, maxillofacialand cardiovascularapplications.Mimics Medical should beused in conjunction withexpert clinical judgment.	Similar. The subject devicehas a narrower indication foruse compared to thepredicate device.

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Characteristic	Subject Device	Predicate Device	Differences
Technical Characteristics
CompatibleInput FileTypes	DICOM	DICOM and standardimaging formats (such asRAW, TIFF, BMP andjpeg format)	Similar. The subject devicehas narrower input file types.
SegmentationFunctionality	Automatic SpinalAlgorithm	Manual tools, Semi-automatic tools, andautomatic algorithms	Similar. Both devicesinclude automated spinesegmentation tool.
UserInteraction	User cannot reviewand edit segmentationand 3D models	Contains tools to reviewand edit segmentation and3D models	Similar: The output of bothdevices can be reviewed bythe user. While the predicatedevice has a viewer toreview and editsegmentation outputs thesubject device output doesnot include any viewer butits outputs can be reviewedas part of the entireworkflow utilizing 3rd partysoftware.
3D ModelGeneration	The subject devicegenerates a 3D model	The predicate devicegenerates a 3D model	Identical
Export Outputs	The subject devicegenerates an outputfile.	The predicate devicegenerates an output file.	Identical
Intended UserPopulation	Trained Personnel,Knowledgeable inMedicine	Trained personnel,knowledgeable in medicine	Identical

NON-CLINICAL TESTING

The aprevo® Digital Segmentation has been evaluated in accordance with internal software specifications and applicable performance standards through the software development and verification and validation procedures to ensure performance according to specifications, user requirements, and the FDA guidance document Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.

Independent training and validation datasets were selected to ensure model performance would reflect real clinical performance. Validation datasets represented diversity in populations and equipment.

The software performance was evaluated using an IOU (intersection over union) score for segmentation which exceeded the acceptance criteria of 80%. It was also evaluated for accuracy of vertebral body labeling which exceeded the acceptance criteria of 90% overall, with sensitivity and specificity exceeding 80% each. Additionally, the performance was evaluated across key cohorts.

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CLINICAL TESTING

Not applicable.

CONCLUSION

The overall indications for use and technology characteristics of the aprevo® Digital Segmentation are similar to the primary predicate device. This leads to the conclusion that the proposed aprevo® Digital Segmentation is substantially equivalent to its primary predicate from the safety and effectiveness perspective.

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).