This product is used in medical institutions, it can carry out 3D reconstruction, segmentation and semi-automatic identification of key points on CT images conforming to DICOM3.0 standard format, and assist physicians to overlay digital templates to assist surgeons with preoperative planning of adult hip and total knee replacement surgery. This product is intended for use by trained and qualified physicians and cannot be used as a basis for clinical diagnosis and treatment decisions alone.

Device Description

The proposed device, Orthopaedic Surgery Planning Software, is standalone software which is designed to help surgeons' specialists carry out the pre-operative planning for an adult hip and total knee replacement surgery for several surgical procedures, based on the patient's CT images. The Orthopaedic Surgery Planning Software can a carry out 3D reconstruction, segmentation and semi-automated identification of anatomical sites of CT images conforming to DICOM3.0 standard format, and assist physicians to simulate adult hip and total knee replacement surgery.

AI/ML Overview

The provided text describes the Orthopaedic Surgery Planning Software (AIJOINT) and its non-clinical test conclusions, which serve as proof that the device meets acceptance criteria. Here's a breakdown of the requested information:

1. Table of acceptance criteria and the reported device performance

Acceptance Criteria (Measurement)	Stated Acceptance Criteria	Reported Device Performance
Key Point Recognition Accuracy	Error distance below 1mm	All points within 95% CI on Bland-Altman plots, actual error distance below 1mm.
Image Segmentation Accuracy (Dice Coefficient)	Not explicitly stated but implied to be high for "mature" software comparison	Mean Dice coefficient of 0.9483
Image Segmentation Accuracy (Hausdorff Distance)	Not explicitly stated but implied to be low for "mature" software comparison	Mean Hausdorff Distance of 1.2917
Output Parameter (Length Measurement) Accuracy	Within 1mm	Within 1mm
Output Parameter (Angle Measurement) Accuracy	Within 1°	Within 1°
Prosthesis Model Data Consistency	Deviations below 0.5mm	Deviations all below 0.5mm
Acetabular Cup Coverage Accuracy	Within ±3%	Within ±3%

2. Sample size used for the test set and the data provenance

Sample Size: 200 patient cases (100 cases per region for image segmentation testing).
Data Provenance: Not explicitly stated from the provided text, but inferred to be retrospective as the testing involved existing patient cases. The country of origin of the data is also not explicitly stated; however, given the sponsor's address (Beijing, China), it is highly probable the data originated from China.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Number of Experts: Not explicitly stated how many professional physicians annotated the key points for ground truth.
Qualifications of Experts: Described as "professional physicians." No further details on their specific qualifications or years of experience are provided.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

The text states the accuracy testing of key point recognition involved "comparing with the key points identified annotated by professional physicians for precision." This implies a single expert or a consensus approach, but no specific adjudication method (e.g., 2+1, 3+1) is mentioned. It is possible a consensus was used, but it's not specified.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, if so, what was the effect size of how much human readers improve with AI vs. without AI assistance

No MRMC comparative effectiveness study was done. The document explicitly states: "No clinical study is included in this submission."

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

Yes, the described non-clinical tests are primarily standalone (algorithm only) performance evaluations. For example, key point recognition accuracy and image segmentation accuracy tests assess the algorithm's performance against established ground truth or mature software, without direct human interaction as part of the measured performance metric. The software is intended to "assist physicians," implying human-in-the-loop for clinical use, but the reported performance metrics are for the software's automated functions.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

Expert Consensus/Annotation: For key point recognition, the ground truth was established by "professional physicians" who identified/annotated key points.
Comparison with Established Software: For image segmentation accuracy, the device's performance was compared to "the segmentation results of the mature software available in the market," implying that the "mature software" results served as a form of ground truth or reference standard.
Reference Values/Measurements: For output parameter accuracy (length, angle, prosthesis model data, acetabular cup coverage), the ground truth was likely based on calculated reference values, measurements against known standards, or comparison with manufacturer-provided data.

8. The sample size for the training set

The document does not specify the sample size used for the training set. It only details the test set.

9. How the ground truth for the training set was established

The document does not provide information on how the ground truth for the training set was established. It focuses solely on the validation/test set.

Summary

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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 letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" and "ADMINISTRATION" in blue text.

Longwood Valley Medical Ltd Wei Yuanyuan RA Manager 2201 Floor 22, Tower 1, No.2 Ronghua South Rd., BDA 100176 Beijing, China

August 5, 2024

Re: K233761

Trade/Device Name: Orthopaedic Surgery Planning Software (AIJOINT) Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: LLZ Dated: July 1, 2024 Received: July 1, 2024

Dear Wei Yuanyuan :

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.

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

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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 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,

Jessica Lamb

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

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Indications for Use

Submission Number (if known)

K233761

Device Name

Orthopaedic Surgery Planning Software (AIJOINT)

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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K233761-510(k) Summary

Date of Preparation: 7/31/2024

1. Sponsor Identification

Longwood Valley Medical LTD.

Address: 2201 Floor 22, Tower 1, No.2 Ronghua South Rd., BDA 100176 Beijing, China Contact Person: Peng Chen Position: RA manager Tel: +86 13511033835 Email: pchen@changmugu.com

1. Designated Submission Correspondent
  Mr. Peng Chen (Primary Contact Person) Ms. Yuanyuan Wei (Alternative Contact Person)

Longwood Valley Medical LTD.

2201 Floor 22, Tower 1, No.2 Ronghua South Rd., BDA 100176 Beijing, China

Tel: +86 4001004670 Fax: +86 (010)62692997 Email: pchen@changmugu.com

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Identification of Proposed Device 3.

Trade Name: Orthopaedic Surgery Planning Software (AIJOINT) Common Name: Pre-operative planning software

Regulatory Information

Regulation Name: Medical image management and processing system Classification: Class II Product Code: LLZ Regulation Number: 21 CFR 892.2050 Review Panel: Radiology

Indication for Use:

Identification of Predicate Devices 4.
510(k) Number: K182464 Product Name: PeekMed

Indications for Use:

PeekMed is a software system designed to help surgeons' specialists carry out the pre-operative planning in a prompt and efficient manner for several surgical procedures, based on their patients' imaging studies.

The software imports diagnostics imaging studies such as x-rays, CT or magnetic resonance image (MRI). The import process can retrieve files from a CD ROM, a local folder or the PACS. In parallel, there is a database of digital representations related to prosthetic materials supplied by their producing companies.

PeekMed allows health professional to digitally perform the surgical planning without adding any additional steps to that process. This software system requires no imaging study acquisition specification (no protocol). Experience in usage and a clinical assessment are necessary for a proper use of the software.

Device Description న్.

The proposed device, Orthopaedic Surgery Planning Software, is standalone software which is designed to help surgeons' specialists carry out the pre-operative planning for an adult hip and total

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knee replacement surgery for several surgical procedures, based on the patient's CT images.

The Orthopaedic Surgery Planning Software can a carry out 3D reconstruction, segmentation and semi-automated identification of anatomical sites of CT images conforming to DICOM3.0 standard format, and assist physicians to simulate adult hip and total knee replacement surgery.

Substantially Equivalent (SE) Comparison 6.

ITEM	Proposed Device	Predicate Device K182464	Remark
Product name	OrthopaedicSurgeryPlanning Software	PeekMed	/
Regulation No.	21 CFR 892.2050	21 CFR 892.2050	Same
Product Code	LLZ	LLZ	Same
Class	II	II	Same
Intended for Use	A pre-operative planningsoftware for surgery	A pre-operative planningsoftware for surgery	Same
Indication for Use	This product is used inmedical institutions, it cancarry out 3Dreconstruction,segmentation andsemi-automaticidentification of key pointson CT images conformingto DICOM3.0 standardformat, and assistphysicians to overlaydigital templates to assistsurgeons with preoperativeplanning of adult hip andtotal knee replacementsurgery. This product isintended for use by trainedand qualified physiciansand cannot be used as abasis for clinical diagnosisand treatment decisions	PeekMed is a software systemdesigned to help surgeons'specialists carry out thepre-operative planning in aprompt and efficient manner forseveral surgical procedures, basedon their patients' imaging studies.The software imports diagnosticsimaging studies such as x-rays,CT or magnetic resonance image(MRI). The import process canretrieve files from a CD ROM, alocal folder or the PACS. Inparallel, there is a database ofdigital representations related toprosthetic materials supplied bytheir producing companies.PeekMed allows healthprofessional to digitally performthe surgical planning withoutadding any additional steps to	SimilarAnalysis1

	alone.	that process. This software
		system requires no imaging study
		acquisition specification (no
		protocol). Experience in usage
		and a clinical assessment are
		necessary for a proper use of the
		software.
		PeekMed allows the surgeon to
		perform the pre-surgical planning
	AIJOINT allows the	efficiently in the following
	surgeon to perform the	subspecialties:
	pre-surgical planning
	efficiently in the following	- Hip
	subspecialties:	- Knee
	- Hip	- Spine
		- Upper Limb
	- Knee	- Foot and Ankle
		- Trauma
		For each subspecialty, there are
	For each subspecialty, there	several procedures:

	are several procedures:
		-Hip:
	-Hip:	Hip Dysplasia Correction,
	Hip Dysplasia Correction,	Limb Length Discrepancy,
	Limb Length Discrepancy,	Center of Rotation - Ranawat	Different
Subspecialties	Acetabular Angle,	method,	Analysis
	Hip Arthroplasty	Acetabular Angle,	2

		Total Hip Arthroplasty
		-Knee: Leg Deformity
	-Knee: Knee Arthroplasty	Correction, AP Knee Resection,
		AP Full Leg
		resection, High Tibial Osteotomy,
		ACL Tunnel Reconstruction,
		Medial Patellofemoral Ligament

	/	-Spine: Single Cobb Angle,Thoracic Kyphosis Angle,Lumbar Lordosis Angle, SagittalVertical Axis, Pelvic Angles,Coronal Balance, Sacro- femoralAngle, Sagittal Balance,
		Smith-Petersen
	Osteotomy, Pedicle Subtraction Osteotomy
	-Upper Limb: Total Shoulder Replacement, Clavicular Angle, Shoulder Resurfacing
	-Foot and Ankle: Talar Tilt, Hallux Valgus, Moreau-Costa-Bertani Internal Angle, Moreau- Costa-Bertani External Angle, Maestro Formula
	-Trauma: Diaphyseal Shaft Fracture Angle, Metaphyseal Shaft Fracture Angle, Roof Arc
Patient Population	Adults	Adults and pediatrics	Different Analysis 3
End Users	Surgeons	Surgeons	Same
Computer	Personal Computer	Personal Computer or Workstation	Same
Operating System	Windows	Windows or OS X	Different Analysis 4
Device Availability	It can be set to start from a computer standalone for planning procedures	It can be set to start from a workstation or standalone for planning procedures	Same
Images Source	Receives medical images from computer local client end.	Receives medical images from various sources (including PACS)	Same
Data Processing	The software processes data in order to provide an overlap and dimensioning of digital representations of the prosthetic material	The software processes data in order to provide an overlap and dimensioning of digital representations of the prosthetic material	Same

Table 1 Technical Characteristics Comparison

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Digital Overlap ofProsthetic Material	Allows the overlap ofmodels and the intersectionof the models	Allows the overlap of models andthe intersection of the models	Same
Interactive ModelPositioning	Yes	Yes	Same
Interactive ModelDimensioning	Yes	Yes	Same
Model Rotation	Yes	Yes	Same
Support for DigitalProsthetic MaterialsProvided by theManufacturers	Yes	Yes	Same
Automatic Calibration	Yes	Yes	Same
Pre-surgical Planning	Yes	Yes	Same
Contact with thePatient	No	No	Same
Control of lifeSupporting Devices	No	No	Same
Human Intervention forImage Interpretation	Yes	Yes	Same

Similar Analysis 1- Indication for Use

Both the proposed device and predicate device are the pre-operative planning software for surgery. Both the proposed device and predicate device have a database of digital representations related to prosthetic materials supplied by their producing companies.

The image source for the proposed device is CT, the image source for the predicate device is CT, x-rays and MRI. The image source for the proposed device is within the scope of the image sources for the predicate device.

The import process for the proposed device can retrieve files from a local folder; The import process for the predicate device can retrieve files from a CD ROM, a local folder or the PACS. The import process for the proposed device is within the scope of the import process for the predicate device.

Based on above analysis, the indication for use of the proposed device is within the scope of the indication for use of the predicate device.

Different Analysis 2- Subspecialties

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The Subspecialties of the proposed device and the predicate device is different. The proposed device and predicate device are all applicable to the Hip and Knee procedures, although they are applicable to different detail hip/knee procedure, the software verification and validation testing and performance testing demonstrate that the proposed device's safety and effectiveness.

Different Analysis 3- Patient Population

The patient population of the proposed device and the predicate device is different. The users use the proposed device for adult patients according to the indications for use that the difference will not affect the safety and effectiveness of the proposed device.

Different Analysis 4- Operating System

The type of operating system of proposed device is within the types of the predicate device. The difference will not affect the safety and effectiveness of the proposed device.

Non-Clinical Test Conclusion 7.
Internal verification and validation testing were conducted to verify that the proposed device met all design requirements and was Substantially Equivalent (SE) to the predicate devices.

Validation activities for the proposed device consisted of:

The accuracy testing of key point recognition, comparing with the key points identified . annotated by professional physicians for precision. Testing shows that key point coordinates have actual error distance is below 1mm. Bland-Altman plots show that all points are within the 95% CI.
The accuracy testing of image segmentation, comparing with the segmentation results of the . mature software available in the market. Testing shows that the mean Dice coefficient and the mean Hausdorff Distance of 200 patient cases (100 cases per region) were 0.9483 and 1.2917.
. The accuracy verification of the output parameters from the proposed device. Testing shows that the accuracy of the output parameters of the orthopedic surgery planning software is within the length measurement accuracy of 1mm and the Angle measurement accuracy of 1°.
The verification on the consistency of prosthesis model data. Comparing the self-drawn ● prosthesis model data and the real prosthesis model data provided by the manufacturer, the deviations are all below 0.5mm.
The accuracy verification of the output acetabular cup coverage. Testing shows that the accuracy . of the output acetabular cup coverage of the orthopedic surgery planning software is within ±3%.

Software verification and validation were performed, and documentation was provided following the FDA guidance "Content of Premarket Submissions for Device Software Functions." This includes verification against defined requirements, and validation against user needs.

The conclusions drawn from the nonclinical tests demonstrate that the proposed device is as safe, as

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effective, and performs as well as the legally marketed predicate devices.

1. Clinical Test Conclusion
  No clinical study is included in this submission.
1. Substantially Equivalent (SE) Conclusion
  Based on the comparison and analysis above, the subject device is substantially equivalent to the legally marketed predicate device, K182464.

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).