SMART PCFD software includes AI-powered algorithms and is intended to be used to support orthopedic healthcare professionals in the diagnosis and surgical planning of Progressive Collapsing Foot Deformity (PCFD) in a hospital or clinic environment. The medical image modality intended to be used in the software is weight-bearing CT (WBCT).

SMART PCFD software provides for the user:

Visualization report of the three-dimensional (3D) mathematical models and measurements of the anatomical structures of foot and ankle and three-dimensional models of orthopedic fixation devices,
Measurement templates containing radiographic measures of foot and ankle, and
Surgical planning application for visualization of foot and ankle anatomical three-dimensional structures, radiographic measures, and surgical instrument parameters supporting the following common flatfoot procedures: Medial Displacement Calcaneal Osteotomy (MDCO), Lateral Column Lengthening (LCL), and Cotton Osteotomy (CO).

The visualization report containing the measurements is intended to be used to support orthopedic healthcare professionals in the diagnosis of PCFD. The surgical planning application contains the visualizations of the three-dimensional structural models, orthopedic fixation device models and surgical instrument parameters combined with the measurements is intended to be used to support orthopedic healthcare professionals in surgical planning of PCFD.

Device Description

The SMART PCFD software is intended to be used in reviewing and digitally processing computed tomography images for the purposes of interpretation by a specialized medical practitioner. The device segments the medical images and creates a 3D model of the bones of the foot and ankle. Measurements, including anatomical axes, are provided to the user and the device allows for presurgical planning.

The device includes the same machine learning derived outputs as the primary predicate SMART Bun-Yo-Matic CT (K240642) device and no new validations were conducted.

Details on the previously performed validation are summarized below. The testing for 82 CT image series presented 100% correctly identified bones of foot and ankle. The existence of metal was identified correctly for 98.8% of the images (specificity 98%, sensitivity 100%).

AI/ML Overview

Here's a breakdown of the acceptance criteria and study information for the SMART PCFD device, as extracted from the provided FDA 510(k) clearance letter:

1. Table of Acceptance Criteria and Reported Device Performance

The clearance letter does not explicitly state acceptance criteria in a formal table format with specific thresholds for each metric. Instead, it describes performance results. Based on the provided text, the acceptance criteria can be inferred from the reported performance, implying that these levels of performance were deemed acceptable.

Feature Assessed	Acceptance Criteria (Inferred from Performance)	Reported Device Performance
Bone Identification	100% correctly identified bones of foot and ankle	100% correctly identified bones of foot and ankle (for 82 CT image series)
Metal Identification	High specificity and sensitivity for metal identification	98.8% correctly identified metal (specificity 98%, sensitivity 100%) (for 82 CT image series)
Surgical Planning Component	Appropriate outputs for surgical planning (e.g., mathematical operations for estimated correction within certain tolerances)	Surgical planning executes mathematical operations for estimated correction ±1 degree for angular measurements and ±1.0 mm for distance measurements.

2. Sample Size Used for the Test Set and Data Provenance

Test Set Sample Size: 82 CT image studies.
Data Provenance:
- Country of Origin: Various sites across USA and Europe, with a minimum of 50% of the images originating from the USA.
- Retrospective/Prospective: Not explicitly stated, but the description of collected studies from "patients with different ages and racial groups" and "clinical subgroups ranging from control/normal feet to pre-/post-operative clinical conditions" suggests retrospective data collection.
- Patient Demographics: Different ages and racial groups, minimum of 35% male/female within each dataset, mean age approximately 47 years (SD 15 years), and representatives from White, (Non-)Hispanic, African American, and Native racial groups.
- Clinical Conditions: Balanced in terms of subjects with different foot alignment, and subjects from clinical subgroups ranging from control/normal feet (44% with test data) to pre-/post-operative clinical conditions such as Hallux Valgus, Progressive Collapsing Foot Deformity, fractures, or with metal implants (40% of the test data).

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

Number of Experts: Three (3).
Qualifications of Experts: U.S. Orthopedic surgeons. Specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

Adjudication Method: Majority vote. "Based on the majority vote of three, two same responses were required to establish a ground truth on each of the DICOM series." This indicates a "2-out-of-3" or "2+1" adjudication where two experts must agree to establish ground truth.

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

Was an MRMC study done? No. The document describes standalone algorithm performance, and comparison to human readers with or without AI assistance is not mentioned.

6. Standalone Performance Study

Was a standalone study done? Yes. The "Details on the previously performed validation are summarized below" section describes testing conducted on the algorithm itself, independently of human interaction. The reported device performance for bone and metal identification comes directly from this standalone evaluation.

7. Type of Ground Truth Used

Type of Ground Truth: Expert consensus. The ground truths for bone and metal identification were "independently established by three (3) U.S. Orthopedic surgeons" who "reviewed each of the DICOM series through axial/sagittal/coronal views and/or 3D reconstruction and marked on a spreadsheet the presence of a bone and metal."

8. Sample Size for the Training Set

AI algorithm for bone identification: 145 CT image studies.
Metal identification: 130 CT image studies.

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

The document states that the "AI algorithm for bone identification was developed using 145 CT image studies and metal identification was developed using 130 CT image studies." It then goes on to describe how ground truths for the test set were established by three U.S. Orthopedic surgeons. However, the document does not explicitly describe how the ground truth for the training set was established. It's common practice for training data to also be annotated by experts, but the details of that process are not provided in this specific excerpt.

Summary

FDA 510(k) Clearance Letter - SMART PCFD

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

Doc ID # 04017.08.00

September 29, 2025

Disior Ltd
℅ Kelsey Gibson
Regulatory Affairs Specialist
Paragon 28, Inc.
14445 Grasslands Dr.
Englewood, CO 80134

Re: K250023
Trade/Device Name: Smart PCFD
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical Image Management And Processing System
Regulatory Class: Class II
Product Code: QIH
Dated: August 29, 2025
Received: August 29, 2025

Dear Kelsey Gibson:

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 (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-reporting-combination-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.

All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.

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-devices/medical-device-safety/medical-device-reporting-mdr-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/medical-devices/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-devices/device-advice-comprehensive-regulatory-

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K250023 - Kelsey Gibson Page 3

assistance/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,

Jessica Lamb, Ph.D.
Assistant Director
Imaging Software Team
DHT8B: Division of Radiological Imaging Devices and Electronic Products
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: 07/31/2026
See PRA Statement below.

Submission Number (if known)
K250023

Device Name
SMART PCFD

Indications for Use (Describe)

SMART PCFD software provides for the user:

Visualization report of the three-dimensional (3D) mathematical models and measurements of the anatomical structures of foot and ankle and three-dimensional models of orthopedic fixation devices,
Measurement templates containing radiographic measures of foot and ankle, and
Surgical planning application for visualization of foot and ankle anatomical three-dimensional structures, radiographic measures, and surgical instrument parameters supporting the following common flatfoot procedures: Medial Displacement Calcaneal Osteotomy (MDCO), Lateral Column Lengthening (LCL), and Cotton Osteotomy (CO).

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
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Office of Chief Information Officer
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"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

K250023 Page 1 of 5

510(k) Number:	K250023
Manufacturer:	Disior LtdHTC Helsinki, Building Pinta, Tammasaarenkatu 3Helsinki Uusimaa, FL, 00180, Finland
Contact:	Markuu LaitinenDirector of Enabling TechnologyPhone: +358 405 430 673Email: mlaitinen@paragon28.com
Prepared By:	Kelsey R. GibsonRegulatory Affairs Specialist IIParagon 28, Inc.14445 Grasslands Dr.,Englewood, CO, 80134Phone: 720-994-5458
Date Prepared:	September 26, 2025
Device TradeName:	SMART PCFD
Device Class and Common Name:	Class II, Automated Radiological Image Processing Software
Classification:	21 CFR 892.2050: Medical image management and processing system
Product Codes:	QIH
Indications for Use:	SMART PCFD software includes AI-powered algorithms and is intended to be used to support orthopedic healthcare professionals in the diagnosis and surgical planning of Progressive Collapsing Foot Deformity (PCFD) in a hospital or clinic environment. The medical image modality intended to be used in the software is weight-bearing CT (WBCT).SMART PCFD software provides for the user:• Visualization report of the three-dimensional (3D) mathematical models and measurements of the anatomical structures of foot and ankle and three-dimensional models of orthopedic fixation devices,• Measurement templates containing radiographic measures of foot and ankle, and

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• Surgical planning application for visualization of foot and ankle anatomical three-dimensional structures, radiographic measures, and surgical instrument parameters supporting the following common flatfoot procedures: Medial Displacement Calcaneal Osteotomy (MDCO), Lateral Column Lengthening (LCL), and Cotton Osteotomy (CO).

| Device Description: | The SMART PCFD software is intended to be used in reviewing and digitally processing computed tomography images for the purposes of interpretation by a specialized medical practitioner. The device segments the medical images and creates a 3D model of the bones of the foot and ankle. Measurements, including anatomical axes, are provided to the user and the device allows for presurgical planning.The device includes the same machine learning derived outputs as the primary predicate SMART Bun-Yo-Matic CT (K240642) device and no new validations were conducted.Details on the previously performed validation are summarized below. The testing for 82 CT image series presented 100% correctly identified bones of foot and ankle. The existence of metal was identified correctly for 98.8% of the images (specificity 98%, sensitivity 100%). |

Study Subjects

The AI algorithm for bone identification was developed using 145 CT image studies and metal identification was developed using 130 CT image studies. Testing was carried out using 82 CT image studies. Out of 357 CT image studies, 340 were from individual patients with few studies from same patient with different foot alignments. The CT image series' were collected from various sites across USA and Europe with a minimum of 50% of the images originating from the USA. The CT image studies were from patients with different ages and racial groups, with minimum of 35% male/female within each dataset, with mean age approximately 47 years (SD 15 years), and representatives from White, (Non-)Hispanic, African American, and Native racial groups. Each dataset was balanced in terms of subjects with different foot alignment, demographics, imaging devices and with subjects from clinical subgroups ranging from control/normal feet (44% with test data) to pre-/post-operative clinical conditions such as Hallux Valgus, Progressive Collapsing Foot Deformity, fractures, or with metal implants (40% of the test data).

Imaging Systems

The 357 image studies were collected using CT imaging system made by five (5) manufacturers (7 different models in total). From the test data of 82 images, 61% of the images were acquired using Curvebeam PedCAT, 11% with Planmed Verify, and 26% with Carestream OnSight 3D Extremity. In addition, system test data contains images acquired with Toshiba Somatom. Typical imaging protocol is disclosed within the IFU, however, the test data contains wider range of parameters for generalization (tube

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K250023 Page 3 of 5

voltages between 90-120 kV, tube currents 5-8 mA, and slice thickness/pixel spacing 0.37-1.5mm).

Ground Truth

The ground truths for bone and metal identification were independently established by three (3) U.S. Orthopedic surgeons with a 3rd party software. Each clinicians reviewed each of the DICOM series through axial/sagittal/coronal views and/or 3D reconstruction and marked on a spreadsheet the presence of a bone and metal in the image series. Based on the majority vote of three, two same responses were required to establish a ground truth on each of the DICOM series.

Training, Tuning, and Validation Data Independence

The SMART PCFD software machine learning algorithm training and tuning data used during the algorithm development, as well as test data used in the standalone software performance assessment study, were all independent data sets. Each CT image study was allowed to be allocated to only data set.

Predicate:	SMART Bun-Yo-Matic CT (K240642)
Substantial Equivalence:	The Indications for Use of the subject device and the predicate device are similar. Differences do not constitute a different intended use because both devices are intended to provide 3D models, measurements, and presurgical planning generated from CT input to orthopaedic healthcare professionals.The subject and predicate devices have similar technological characteristics. The main differences being in the surgical planning case report output for the device since the subject device is for Progressive Collapsing Foot Deformity (PCFD) while the predicate device is for Lapidus Arthrodesis. In support of the claim of substantial equivalence the comparison between the subject and predicate systems demonstrates a shared input, image processing, measuring and planning capabilities, and user interface.

Predicate:

SMART Bun-Yo-Matic CT (K240642)

Substantial Equivalence:

The Indications for Use of the subject device and the predicate device are similar. Differences do not constitute a different intended use because both devices are intended to provide 3D models, measurements, and presurgical planning generated from CT input to orthopaedic healthcare professionals.The subject and predicate devices have similar technological characteristics. The main differences being in the surgical planning case report output for the device since the subject device is for Progressive Collapsing Foot Deformity (PCFD) while the predicate device is for Lapidus Arthrodesis. In support of the claim of substantial equivalence the comparison between the subject and predicate systems demonstrates a shared input, image processing, measuring and planning capabilities, and user interface.

	Subject Device	Primary Predicate Device	Additional Predicate Device
Manufacturer	Disior Ltd	Disior Ltd	Disior Ltd
Trade Name	SMART PCFD	SMART Bun-Yo-Matic CT	Bonelogic
510(k)	Subject Device	K240642	K223757
Indications for Use	SMART PCFD software includes AI-powered algorithms and is intended to be used to support orthopedic healthcare professionals in the diagnosis and surgical planning of Progressive Collapsing Foot Deformity (PCFD) in a hospital or clinic environment. The medical image modality intended to be used in the software is weight-bearing CT (WBCT).	SMART Bun-Yo-Matic CT software is to be used by orthopaedic healthcare professionals for diagnosis and surgical planning in a hospital or clinic environment. The medical imaging type intended to be used as the input of the software is Computed Tomography (CT).SMART Bun-Yo-Matic CT software provides:• Visualization report of the three-dimensional	Bonelogic software is to be used by orthopaedic healthcare professionals for diagnosis and surgical planning in a hospital or clinic environment.Bonelogic software provides:• Semi-automatic segmentation with manual or assisted input of bony structure identification from CT imaging input,

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SMART PCFD software provides for the user:	mathematical models of the anatomical structures of foot and ankle and three-dimensional models of orthopaedic fixation devices,	• Three-dimensional mathematical models of the anatomical structures of foot and ankle,
• Visualization report of the three-dimensional (3D) mathematical models and measurements of the anatomical structures of foot and ankle and three-dimensional models of orthopedic fixation devices,	• Measurement templates containing radiographic measures of foot and ankle,	• Measurement templates containing radiographic measures of foot and ankle, and tools for manually obtaining lines and angular measurements,
• Measurement templates containing radiographic measures of foot and ankle, and	• Surgical planning application for visualization of foot and ankle anatomical three-dimensional structures, radiographic measures, and surgical instrument parameters.	• Surgical planning application for foot and ankle using three-dimensional models of the anatomical structures and radiographic measures.
• Surgical planning application for visualization of foot and ankle anatomical three-dimensional structures, radiographic measures, and surgical instrument parameters supporting the following common flatfoot procedures: Medial Displacement Calcaneal Osteotomy (MDCO), Lateral Column Lengthening (LCL), and Cotton Osteotomy (CO).	The visualization report containing the measurements can be used for the diagnosis of orthopaedic healthcare conditions. The surgical planning application containing the visualizations of the three-dimensional structural models, orthopaedic fixation device models and surgical instrument parameters combined with the measurements can be used for the planning of treatments and operations to correct orthopaedic healthcare conditions of foot and ankle.	The three-dimensional models of the anatomical structures combined with the measurements can be used for the diagnosis of orthopaedic healthcare conditions. The surgical planning application containing the three-dimensional structural models combined with the measurements can be used for the planning of treatments and operations to correct orthopaedic healthcare conditions of foot and ankle.
The visualization report containing the measurements is intended to be used to support orthopedic healthcare professionals in the diagnosis of PCFD. The surgical planning application contains the visualizations of the three-dimensional structural models, orthopedic fixation device models and

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	surgical instrument parameters combined with the measurements is intended to be used to support orthopedic healthcare professionals in surgical planning of PCFD.	mathematical models of the anatomical structures of foot and ankle and three-dimensional models of orthopaedic fixation devices,• Measurement templates containing radiographic measures of foot and ankle,• Surgical planning application for visualization of foot and ankle anatomical three-dimensional structures, radiographic measures, and surgical instrument parameters.The visualization report containing the measurements can be used for the diagnosis of orthopaedic healthcare conditions. The surgical planning application containing the visualizations of the three-dimensional structural models, orthopaedic fixation device models and surgical instrument parameters combined with the measurements can be used for the planning of treatments and operations to correct orthopaedic healthcare conditions of foot and ankle.	• Three-dimensional mathematical models of the anatomical structures of foot and ankle,• Measurement templates containing radiographic measures of foot and ankle, and tools for manually obtaining lines and angular measurements,• Surgical planning application for foot and ankle using three-dimensional models of the anatomical structures and radiographic measures.The three-dimensional models of the anatomical structures combined with the measurements can be used for the diagnosis of orthopaedic healthcare conditions. The surgical planning application containing the three-dimensional structural models combined with the measurements can be used for the planning of treatments and operations to correct orthopaedic healthcare conditions of foot and ankle.
Input	Weight Bearing CT DICOM Computed tomography	Computed tomography DICOM Computed tomography	Computed tomography DICOM Computed tomography
Image Processing	Segmentation of bone structures	Segmentation of bone structures	Segmentation of bone structures
Output	Automated case report of the 3D model of patient anatomy, surgical instrument parameters, and visualization of implant	Automated case report of the 3D model of patient anatomy, surgical instrument parameters, and visualization of implant	3D model of patient anatomy and case report of the 3D model patient anatomy
Measuring and Planning	Perform measurements for presurgical planning	Perform measurements for presurgical planning	Perform measurements for presurgical planning
User Interface	Graphical user interface (GUI) to a web application used with a standard web browser.	Graphical user interface (GUI) to a web application used with a standard web browser.	Graphical user interface (GUI) built on the Unity development engine.

Differences do not introduce new questions of safety and effectiveness.

Performance Testing:	All necessary testing has been performed on the SMART PCFD device to assure substantial equivalence to its predicate and demonstrate the subject device performs as intended.Software Verification and ValidationSoftware verification and validation were carried out based on the "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices", at the unit, integration, and system levels to determine substantial equivalence to the predicate device.Non-Clinical Bench TestingPerformance testing was conducted to evaluate the Surgical Planning Component of the device. The Surgical Planning Component was tested with multiple images and appropriate outputs for the subject device were evaluated by qualified truthers. Results showed the subject device performed as intended. Surgery planning executes mathematical operations for estimated correction ±1 degree for angular measurements and ±1.0 mm for distance measurements.Clinical data are not needed to support the safety and effectiveness of the subject device.
Conclusions:	The SMART PCFD device subject to this submission possesses the same intended use and has similar technological characteristics as the predicate device. All performance testing conducted for the SMART PCFD device met the predetermined acceptance criteria or were otherwise considered acceptable. As such, the SMART PCFD device is substantially equivalent to the predicate device for the intended use.

Performance Testing:

All necessary testing has been performed on the SMART PCFD device to assure substantial equivalence to its predicate and demonstrate the subject device performs as intended.Software Verification and ValidationSoftware verification and validation were carried out based on the "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices", at the unit, integration, and system levels to determine substantial equivalence to the predicate device.Non-Clinical Bench TestingPerformance testing was conducted to evaluate the Surgical Planning Component of the device. The Surgical Planning Component was tested with multiple images and appropriate outputs for the subject device were evaluated by qualified truthers. Results showed the subject device performed as intended. Surgery planning executes mathematical operations for estimated correction ±1 degree for angular measurements and ±1.0 mm for distance measurements.Clinical data are not needed to support the safety and effectiveness of the subject device.

Conclusions:

The SMART PCFD device subject to this submission possesses the same intended use and has similar technological characteristics as the predicate device. All performance testing conducted for the SMART PCFD device met the predetermined acceptance criteria or were otherwise considered acceptable. As such, the SMART PCFD device is substantially equivalent to the predicate device for the intended use.

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).