It is used by radiation oncology department to segment CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaption.

Device Description

The proposed device, AccuContour 4.0 Family, is a standalone software with the following variants: AccuContour and AccuContour-Lite. The functions of AccuContour-Lite is a subset of AccuContour.

AccuContour:
It is used by oncology department to register multi-modality images and segment (non-contrast) CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaptation.

The product has two image processing functions:

Deep learning contouring: it can automatically contour organs-at-risk, in head and neck, thorax, abdomen and pelvis (for both male and female) areas,
Automatic registration: rigid and deformable registration, and
Manual contouring.

It also has the following general functions:

Receive, add/edit/delete, transmit, input/export, medical images and DICOM data;
Patient management;
Review tool of processed images;
Extension tool;
Plan evaluation and plan comparison;
Dose analysis.

AccuContour-Lite:
It is used by oncology department to segment (non-contrast) CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaptation.

The product has one image processing function:
Deep learning contouring: it can automatically contour organs-at-risk, in head and neck, thorax, abdomen and pelvis (for both male and female) areas,

It also has the following general functions:

Receive, add/edit/delete, transmit, input/export, medical images and DICOM data;
Patient management;
Review tool of processed images.

AI/ML Overview

Here's an analysis of the acceptance criteria and study details for the AccuContour 4.0, extracted and organized from the provided FDA 510(k) clearance letter.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are derived from the "Pass Criteria" columns in Tables 1, 2, 3, and 4, which specify minimum DSC and maximum HD95 values. The reported device performance is represented by the "Lower Bound 95% CI" for both DSC and HD95, and the "Average Rating" for clinical applicability.

Table A: Performance for Synthetic CT (sCT) Contouring Function (Derived from MR Images)

Organ & Structure	Size	DSC Pass Criteria	HD95 Pass Criteria (mm)	Reported DSC (Lower Bound 95% CI)	Reported HD95 (Lower Bound 95% CI, mm)	Average Rating (1-5)	Meet Criteria? (DSC)	Meet Criteria? (HD95)
TemporalLobe_L	Medium	0.65	N/A	0.886	4.319 (N/A criteria)	4.5	Yes	N/A
TemporalLobe_R	Medium	0.65	N/A	0.878	4.382 (N/A criteria)	4.6	Yes	N/A
Brain	Large	0.8	N/A	0.986	1.877 (N/A criteria)	4.7	Yes	N/A
BrainStem	Medium	0.65	N/A	0.843	4.999 (N/A criteria)	4.5	Yes	N/A
SpinalCord	Medium	0.65	N/A	0.867	3.030 (N/A criteria)	4.8	Yes	N/A
OpticChiasm	Small	0.5	N/A	0.804	4.771 (N/A criteria)	4.1	Yes	N/A
OpticNerve_L	Small	0.5	N/A	0.822	2.235 (N/A criteria)	4.1	Yes	N/A
OpticNerve_R	Small	0.5	N/A	0.794	2.422 (N/A criteria)	4.2	Yes	N/A
InnerEar_L	Small	0.5	N/A	0.843	2.164 (N/A criteria)	4.2	Yes	N/A
InnerEar_R	Small	0.5	N/A	0.806	2.102 (N/A criteria)	4.4	Yes	N/A
MiddleEar_L	Small	0.5	N/A	0.824	3.580 (N/A criteria)	4.5	Yes	N/A
MiddleEar_R	Small	0.5	N/A	0.792	3.700 (N/A criteria)	4.4	Yes	N/A
Eye_L	Small	0.5	N/A	0.906	1.659 (N/A criteria)	4.8	Yes	N/A
Eye_R	Small	0.5	N/A	0.897	1.584 (N/A criteria)	4.9	Yes	N/A
Lens_L	Small	0.5	N/A	0.836	3.368 (N/A criteria)	4.5	Yes	N/A
Lens_R	Small	0.5	N/A	0.841	3.379 (N/A criteria)	4.2	Yes	N/A
Pituitary	Small	0.5	N/A	0.801	2.267 (N/A criteria)	4.4	Yes	N/A
Mandible	Small	0.5	N/A	0.913	1.844 (N/A criteria)	4.3	Yes	N/A
TMJ_L	Small	0.5	N/A	0.830	2.819 (N/A criteria)	4.4	Yes	N/A
TMJ_R	Small	0.5	N/A	0.817	2.722 (N/A criteria)	4.5	Yes	N/A
OralCavity	Medium	0.65	N/A	0.916	3.677 (N/A criteria)	4.7	Yes	N/A
Larynx	Medium	0.65	N/A	0.795	2.196 (N/A criteria)	4.4	Yes	N/A
Trachea	Medium	0.65	N/A	0.870	2.452 (N/A criteria)	4.5	Yes	N/A
Esophagus	Medium	0.65	N/A	0.800	2.680 (N/A criteria)	4.7	Yes	N/A
Parotid_L	Medium	0.65	N/A	0.851	2.386 (N/A criteria)	4.6	Yes	N/A
Parotid_R	Medium	0.65	N/A	0.868	2.328 (N/A criteria)	4.6	Yes	N/A
Submandibular_L	Medium	0.65	N/A	0.833	4.920 (N/A criteria)	4.5	Yes	N/A
Submandibular_R	Medium	0.65	N/A	0.783	2.348 (N/A criteria)	4.3	Yes	N/A
Thyroid	Medium	0.65	N/A	0.803	1.911 (N/A criteria)	4.8	Yes	N/A
BrachialPlexus_L	Medium	0.65	N/A	0.828	5.347 (N/A criteria)	4.4	Yes	N/A
BrachialPlexus_R	Medium	0.65	N/A	0.800	5.062 (N/A criteria)	4.3	Yes	N/A
Lung_L	Large	0.8	N/A	0.968	1.635 (N/A criteria)	4.5	Yes	N/A
Lung_R	Large	0.8	N/A	0.976	1.516 (N/A criteria)	4.7	Yes	N/A
Heart	Large	0.8	N/A	0.959	2.496 (N/A criteria)	4.5	Yes	N/A
Liver	Large	0.8	N/A	0.941	2.439 (N/A criteria)	4.0	Yes	N/A
Kidney_L	Large	0.8	N/A	0.892	2.748 (N/A criteria)	4.7	Yes	N/A
Kidney_R	Large	0.8	N/A	0.895	2.797 (N/A criteria)	4.5	Yes	N/A
Stomach	Large	0.8	N/A	0.782	4.754 (N/A criteria)	4.1	No*	N/A
Pancreas	Medium	0.65	N/A	0.827	6.271 (N/A criteria)	4.0	Yes	N/A
Duodenum	Medium	0.65	N/A	0.815	6.447 (N/A criteria)	4.1	Yes	N/A
Rectum	Medium	0.65	N/A	0.796	2.047 (N/A criteria)	3.9	Yes	N/A
BowelBag	Large	0.8	N/A	0.808	7.380 (N/A criteria)	4.0	Yes	N/A
Bladder	Large	0.8	N/A	0.943	2.082 (N/A criteria)	4.5	Yes	N/A
Marrow	Large	0.8	N/A	0.889	1.842 (N/A criteria)	4.6	Yes	N/A
FemurHead_L	Medium	0.65	N/A	0.950	2.261 (N/A criteria)	4.5	Yes	N/A
FemurHead_R	Medium	0.65	N/A	0.941	2.466 (N/A criteria)	4.6	Yes	N/A

*Note: For Stomach, the reported DSC (0.782) is below the pass criteria (0.8). However, the document states, "The results indicate that the auto-segmentation performance of the AccuContour system for sCT images derived from both CBCT and MR modalities meets the requirements for geometric accuracy." This suggests there might be an overall or combined assessment, or other factors led to acceptance despite this single instance. The average clinical rating is 4.1, which is above the threshold of 3.

Table B: Performance for Synthetic CT (sCT) Contouring Function (Derived from CBCT Images)

Organ & Structure	Size	DSC Pass Criteria	HD95 Pass Criteria (mm)	Reported DSC (Lower Bound 95% CI)	Reported HD95 (Lower Bound 95% CI, mm)	Average Rating (1-5)	Meet Criteria? (DSC)	Meet Criteria? (HD95)
TemporalLobe_L	Medium	0.65	N/A	0.854	3.451 (N/A criteria)	4.8	Yes	N/A
TemporalLobe_R	Medium	0.65	N/A	0.859	3.258 (N/A criteria)	4.6	Yes	N/A
Brain	Large	0.8	N/A	0.986	1.804 (N/A criteria)	4.7	Yes	N/A
BrainStem	Medium	0.65	N/A	0.903	4.678 (N/A criteria)	4.5	Yes	N/A
SpinalCord	Medium	0.65	N/A	0.869	2.088 (N/A criteria)	4.8	Yes	N/A
OpticChiasm	Small	0.5	N/A	0.795	5.252 (N/A criteria)	4.4	Yes	N/A
OpticNerve_L	Small	0.5	N/A	0.815	2.373 (N/A criteria)	4.2	Yes	N/A
OpticNerve_R	Small	0.5	N/A	0.816	2.210 (N/A criteria)	4.1	Yes	N/A
InnerEar_L	Small	0.5	N/A	0.800	2.144 (N/A criteria)	4.5	Yes	N/A
InnerEar_R	Small	0.5	N/A	0.794	2.171 (N/A criteria)	4.2	Yes	N/A
MiddleEar_L	Small	0.5	N/A	0.800	3.301 (N/A criteria)	4.5	Yes	N/A
MiddleEar_R	Small	0.5	N/A	0.797	3.888 (N/A criteria)	4.5	Yes	N/A
Eye_L	Small	0.5	N/A	0.944	1.553 (N/A criteria)	4.8	Yes	N/A
Eye_R	Small	0.5	N/A	0.941	1.678 (N/A criteria)	4.9	Yes	N/A
Lens_L	Small	0.5	N/A	0.820	3.532 (N/A criteria)	4.5	Yes	N/A
Lens_R	Small	0.5	N/A	0.821	3.370 (N/A criteria)	4.7	Yes	N/A
Pituitary	Small	0.5	N/A	0.802	2.496 (N/A criteria)	4.4	Yes	N/A
Mandible	Small	0.5	N/A	0.870	2.227 (N/A criteria)	4.3	Yes	N/A
TMJ_L	Small	0.5	N/A	0.774	2.775 (N/A criteria)	4.3	Yes	N/A
TMJ_R	Small	0.5	N/A	0.800	2.791 (N/A criteria)	4.5	Yes	N/A
OralCavity	Medium	0.65	N/A	0.885	3.794 (N/A criteria)	4.8	Yes	N/A
Larynx	Medium	0.65	N/A	0.793	2.827 (N/A criteria)	4.8	Yes	N/A
Trachea	Medium	0.65	N/A	0.873	2.545 (N/A criteria)	4.5	Yes	N/A
Esophagus	Medium	0.65	N/A	0.800	2.811 (N/A criteria)	4.5	Yes	N/A
Parotid_L	Medium	0.65	N/A	0.891	2.415 (N/A criteria)	4.6	Yes	N/A
Parotid_R	Medium	0.65	N/A	0.894	2.525 (N/A criteria)	4.6	Yes	N/A
Submandibular_L	Medium	0.65	N/A	0.745	5.026 (N/A criteria)	4.8	Yes	N/A
Submandibular_R	Medium	0.65	N/A	0.797	2.192 (N/A criteria)	4.7	Yes	N/A
Thyroid	Medium	0.65	N/A	0.823	2.182 (N/A criteria)	4.8	Yes	N/A
BrachialPlexus_L	Medium	0.65	N/A	0.805	3.922 (N/A criteria)	4.4	Yes	N/A
BrachialPlexus_R	Medium	0.65	N/A	0.823	3.529 (N/A criteria)	4.2	Yes	N/A
Lung_L	Large	0.8	N/A	0.947	1.587 (N/A criteria)	4.5	Yes	N/A
Lung_R	Large	0.8	N/A	0.971	1.635 (N/A criteria)	4.3	Yes	N/A
Heart	Large	0.8	N/A	0.896	1.823 (N/A criteria)	4.5	Yes	N/A
Liver	Large	0.8	N/A	0.914	2.595 (N/A criteria)	4.6	Yes	N/A
Kidney_L	Large	0.8	N/A	0.922	2.645 (N/A criteria)	4.7	Yes	N/A
Kidney_R	Large	0.8	N/A	0.906	2.611 (N/A criteria)	4.5	Yes	N/A
Stomach	Large	0.8	N/A	0.858	4.681 (N/A criteria)	4.2	Yes	N/A
Pancreas	Medium	0.65	N/A	0.822	5.548 (N/A criteria)	4.4	Yes	N/A
Duodenum	Medium	0.65	N/A	0.818	5.252 (N/A criteria)	4.1	Yes	N/A
Rectum	Medium	0.65	N/A	0.797	4.253 (N/A criteria)	4.3	Yes	N/A
BowelBag	Large	0.8	N/A	0.850	5.028 (N/A criteria)	4.0	Yes	N/A
Bladder	Large	0.8	N/A	0.926	3.322 (N/A criteria)	4.7	Yes	N/A
Marrow	Large	0.8	N/A	0.837	2.148 (N/A criteria)	4.7	Yes	N/A
FemurHead_L	Medium	0.65	N/A	0.893	1.639 (N/A criteria)	4.8	Yes	N/A
FemurHead_R	Medium	0.65	N/A	0.927	1.807 (N/A criteria)	4.9	Yes	N/A

Table C: Performance for 4DCT Registration Function (Rigid Registration)

Organ & Structure	Size	DSC Pass Criteria	Reported DSC (Lower Bound 95% CI)	Average Rating (1-5)	Meet Criteria?
Trachea	Medium	0.65	0.888	4.5	Yes
Esophagus	Medium	0.65	0.836	4.5	Yes
Lung_L	Large	0.8	0.932	4.7	Yes
Lung_R	Large	0.8	0.929	4.8	Yes
Lung_All	Large	0.8	0.930	4.8	Yes
Heart	Large	0.8	0.917	4.6	Yes
SpinalCord	Medium	0.65	0.943	4.6	Yes
Liver	Large	0.8	0.888	4.6	Yes
Stomach	Large	0.8	0.791	4.5	No*
A_Aorta	Large	0.8	0.917	4.4	Yes
Spleen	Large	0.8	0.786	4.5	No*
Body	Large	0.8	0.995	4.9	Yes

*Note: For Stomach (0.791) and Spleen (0.786), the reported DSC is below the pass criteria (0.8). However, the document states, "According to the results, the accuracy of 4DCT image registration images meets the requirements and all structure models demonstrating that only minor edits would be required in order to make the structure models acceptable for clinical use." The average clinical rating for both is 4.5, above the threshold of 3.

Table D: Performance for 4DCT Registration Function (Deformable Registration)

Organ & Structure	Size	DSC Pass Criteria	Reported DSC (Lower Bound 95% CI)	Average Rating (1-5)	Meet Criteria?
Trachea	Medium	0.65	0.940	4.7	Yes
Esophagus	Medium	0.65	0.866	4.6	Yes
Lung_L	Large	0.8	0.966	4.7	Yes
Lung_R	Large	0.8	0.949	4.5	Yes
Lung_All	Large	0.8	0.954	4.8	Yes
Heart	Large	0.8	0.931	4.6	Yes
SpinalCord	Medium	0.65	0.920	4.6	Yes
Liver	Large	0.8	0.936	4.5	Yes
Stomach	Large	0.8	0.889	4.5	Yes
A_Aorta	Large	0.8	0.947	4.6	Yes
Spleen	Large	0.8	0.913	4.8	Yes
Body	Large	0.8	0.997	4.9	Yes

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

Synthetic CT (sCT) Contouring Function:
- Sample Size: 247 synthetic CT images (116 generated from MR, 131 generated from CBCT).
- Data Provenance:
  - Demographic Distribution: 57% male, 43% female. Age distribution: 13% (21-40), 44.1% (41-60), 36.8% (61-80), 6.1% (81-100). Race: 78% White, 12% Black or African American, 10% Others.
  - Imaging Equipment: MR images from GE (21.6%), Philips (56.9%), Siemens (21.6%). CBCT images from Varian (58.8%), Elekta (41.2%).
  - Retrospective/Prospective: Not explicitly stated, but the description of demographic and equipment distribution from a "sample" indicates retrospective data collection from existing patient records.
  - Country of Origin: The racial distribution explicitly mentions "U.S. clinical radiotherapy practice," suggesting the data is primarily from the United States.
4DCT Registration Function:
- Sample Size: 30 4DCT image sets.
- Data Provenance:
  - Imaging Equipment: Siemens (90.0%), Philips (10.0%) scanners.
  - Demographic Distribution: 17 males (56.7%), 13 females (43.3%). Age: 33-82 years, with majority in 51-65 (40.0%) and 66-80 (43.3%) year brackets.
  - Image Characteristics: Uniform 3mm slice thickness (100%).
  - Sourcing Location: Most images (90.0%) from Drexel Town Square Health Center/Community Memorial Hospital, remainder from Froedtert Hospital.
  - Retrospective/Prospective: Not explicitly stated, but implies retrospective data from patient archives of the mentioned hospitals.
  - Country of Origin: Based on the hospital names (Drexel Town Square Health Center, Community Memorial Hospital, Froedtert Hospital), the data is from the United States.

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

Number of Experts: Not explicitly stated. The text mentions "clinical experts evaluate the clinical applicability" and "RTStruct contoured by the professional physician as the gold standard." This implies at least one, and likely multiple, qualified medical professionals.
Qualifications of Experts: The experts are described as "clinical experts" and "professional physician(s)." Their specific qualifications (e.g., "radiologist with 10 years of experience") are not provided. They are implied to be clinically qualified radiotherapy personnel.

4. Adjudication Method for the Test Set

Adjudication Method: Not explicitly stated. The ground truth for segmentation is stated to be "RTStruct contoured by the professional physician". For clinical applicability, "clinical experts evaluate the clinical applicability" and assign a 1-5 scale score. This suggests a single expert (or group consensus without specific adjudication rules like 2+1) established the ground truth segmentation, and separate clinical experts evaluated the results. There is no mention of a formal adjudication process for disagreements in ground truth labeling if multiple experts were involved in its creation.

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

Was an MRMC study done? No.
Effect Size of Human Improvement (if applicable): Not applicable, as no MRMC study comparing human readers with and without AI assistance was reported. The testing focused solely on the algorithm's performance against expert-generated ground truth and expert evaluation of the algorithm's output.

6. Standalone Performance

Was a standalone performance study done? Yes. The entire report details the "Performance Test Report on Synthetic CT (sCT) Contouring Function" and "Performance Test Report on 4DCT Registration Function," measuring the algorithm's performance (DSC, HD95) against gold standard contours and qualitative evaluation by clinical experts. This reflects the algorithm's performance independent of human interaction during the contouring process.

7. Type of Ground Truth Used

Ground Truth: For the synthetic CT contouring and 4DCT registration functions, the ground truth was "RTStruct contoured by the professional physician" (i.e., expert consensus or expert-generated contours).

8. Sample Size for the Training Set

Training Set Sample Size: Not provided in the document.

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

Training Set Ground Truth Establishment: Not provided in the document. The document only details the ground truth used for the validation/test set.

Summary

FDA 510(k) Clearance Letter - AccuContour 4.0

Page 1

January 23, 2026

Manteia Technologies Co., Ltd.
Chao Fang
Quality Manager
Unit 3001-3005
No.5 Huizhan North Road
Xiamen, Fujian 361008
China

Re: K251351
Trade/Device Name: AccuContour 4.0
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical Image Management And Processing System
Regulatory Class: Class II
Product Code: QKB
Dated: April 30, 2025
Received: April 30, 2025

Dear Chao Fang:

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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K251351 - Chao Fang Page 2

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-

Page 3

K251351 - Chao Fang 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,

Lora D. Weidner, Ph.D.
Assistant Director
Radiation Therapy 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

Page 4

DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration

Indications for Use

Form Approved: OMB No. 0910-0120
Expiration Date: 06/30/2023
See PRA Statement below.

510(k) Number (if known): K251351

Device Name: AccuContour 4.0

Indications for Use (Describe):
It is used by radiation oncology department to segment CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaption.

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.

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510(k) Summary

510(k) Number: K251351

The following information is provided as required by 21 CFR 807.92.

The assign 510(k) Number: K251351

I. SUBMITTER

Manteia Technologies Co., Ltd.
Unit 3001-3005, No.5 Huizhan North Road, Xiamen, Fujian, P.R. China
Establishment Registration Number: 3016686005
Contact Person: Chao Fang
Position: Quality Manager
Email: ra@manteiatech.com
Date of Prepared: 12/18/2025

II. DEVICE

Name of Device: AccuContour 4.0
Common or Usual Name: AI-assisted Auto-contouring Tool
Classification Name: Radiological Image Processing Software For Radiation Therapy
Regulatory Class: Class II
Product Code: QKB

III. PREDICATE DEVICE

Predicate Device: AccuContour, K221706

IV. DEVICE DESCRIPTION

The proposed device, AccuContour 4.0 Family, is a standalone software with the following variants: AccuContour and AccuContour-Lite. The functions of AccuContour-Lite is a subset of AccuContour.

The product has two image processing functions:

Deep learning contouring: it can automatically contour organs-at-risk, in head and neck, thorax, abdomen and pelvis (for both male and female) areas,
Automatic registration: rigid and deformable registration, and
Manual contouring.

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It also has the following general functions:

Receive, add/edit/delete, transmit, input/export, medical images and DICOM data;
Patient management;
Review tool of processed images;
Extension tool;
Plan evaluation and plan comparison;
Dose analysis.

AccuContour-Lite:
It is used by oncology department to segment (non-contrast) CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaptation.

The product has one image processing function:
Deep learning contouring: it can automatically contour organs-at-risk, in head and neck, thorax, abdomen and pelvis (for both male and female) areas,

It also has the following general functions:

Receive, add/edit/delete, transmit, input/export, medical images and DICOM data;
Patient management;
Review tool of processed images.

V. INDICATIONS FOR USE

It is used by radiation oncology department to segment CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaption.

VI. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE DEVICE

The major changes in the subject device compared with the predicate device are as follow:

Added the AccuContour-Lite variant as a lightweight version of AccuContour
Added AI-based Synthetic CT auto-contouring CT including 46 organs & structures
Added registration support for 4DCT

The detailed comparison of technical parameters is shown in the table below.

ITEM	Subject Device AccuContour 4.0		Predicate Device AccuContour (K221706)
Device Name	AccuContour	AccuContour-Lite	AccuContour
Regulatory Information
Regulation No.	21 CFR 892.2050	21 CFR 892.2050	21 CFR 892.2050
Product Code	QKB	QKB	QKB
Class	II	II	II
Intended Use	It is used by radiation oncology department to segment CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaptation.		It is used by radiation oncology department to register multi-modality

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			images and segment (non-contrast) CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaptation.
Intended User	Clinically qualified radiotherapy personnel with training.	Clinically qualified radiotherapy personnel with training.	Clinically qualified radiotherapy personnel with training.
Independent Software	Yes	Yes	Yes
Technological Characteristics
Operating System	Windows	Windows	Windows
Top Toolbar	Yes	Yes	Yes
Patient Management	Yes	Yes	Yes
Contour	Yes	Yes	Yes
Fusion Registration	Yes	No	Yes
Plan Comparison	Yes	No	Yes
Dose Display	Yes	No	Yes
Patient Management Features
Receive Files	Yes	Yes	Yes
Import/Export	Yes	Yes	Yes
Search	Yes	Yes	Yes
Advanced Search	Yes	Yes	Yes
Refresh	Yes	Yes	Yes
Auto-contouring	Yes	Yes	Yes
Generate Images	Yes	No	Yes
Generate Projections	Yes	Yes	Yes
Contouring Features
Algorithm	Deep learning with GPU/CPU support	Deep learning with GPU/CPU support	Deep learning with GPU support
Compatible Modality	Non-Contrast CT DICOM 3.0 compliance required.（Original CT and Synthetic CT）	Non-Contrast CT DICOM 3.0 compliance required.（Original CT and Synthetic CT）	Non-Contrast CT DICOM 3.0 compliance required. （Original CT）
Compatible Scanner Models	No limitation on scanner model, DICOM 3.0 compliance required.	No limitation on scanner model, DICOM 3.0 compliance required.	No limitation on scanner model, DICOM 3.0 compliance required.
Compatible Treatment Planning System	No limitation on scanner model, DICOM 3.0 compliance required.	No limitation on scanner model, DICOM 3.0 compliance required.	No limitation on scanner model, DICOM 3.0 compliance required.
Fusion Registration Features
Algorithm	Intensity Based with	No	Intensity Based with GPU

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	GPU/CPU support		support
Registration Type	Rigid Registration, Deformable Registration	No	Rigid Registration, Deformable Registration
Compatible Modality	Auto rigid registration: CT, MRI, PET, 4DCT Auto deformable registration: CT, MRI, CBCT, 4DCT	No	Auto rigid registration: CT, MRI, PET Auto deformable registration: CT, MRI, CBCT
Compatible Scanner Models	No limitation on scanner model, DICOM 3.0 compliance required.	No	No limitation on scanner model, DICOM 3.0 compliance required.
Compatible Treatment Planning System	No limitation on scanner model, DICOM 3.0 compliance required.	No	No limitation on scanner model, DICOM 3.0 compliance required.
Registration Export	Yes	No	Yes
Fusion Contouring	Yes	No	Yes
Synchronized Contouring	Yes	No	Yes
Plan Comparison Feature
Plan Evaluation	Yes	No	Yes
Plan Comparison	Yes	No	Yes
Export Report	Yes	No	Yes
Isodose Line Display	Yes	No	Yes
Dose Display Feature
Dose Analysis	Yes	No	Yes
Dose to Contour	Yes	No	Yes
Dose Accumulation	Yes	No	Yes
ART Dose Accumulation	Yes	No	Yes

VII. PERFORMANCE DATA

The following performance data were provided in support of the substantial equivalence determination.

Biocompatibility Testing

Not Applicable (Standalone Software).

Electrical Safety and Electromagnetic Compatibility (EMC)

Not Applicable (Standalone Software).

Software Verification and Validation Testing

Software verification and validation testings were conducted, and documentation was

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provided as recommended by FDA's Guideline for Industry and FDA Staff - Content of Premarket Submission for Device Software Functions. Verification and validation of the software was conducted to ensure that the product meet users needs and intended use. AccuContour passed all software verification and validation tests.

Performance Test Report on Synthetic CT (sCT) Contouring Function

The performance test was performed to evaluate the synthetic CT(sCT) auto-contouring function of the test article(AccuContour) by DICE and HD95 Assessment Method.Verify whether all ROI indicators meet the criteria by calculating the Dice Similarity Coefficient (DSC) and 95% Hausdorff Distance (HD95) between the automatically delineated contours and the gold-standard contours.Meanwhile, clinical experts evaluate the clinical applicability of the automatically delineated contours using a 1-5 scale scoring system.The results indicate that the auto-segmentation performance of the AccuContour system for sCT images derived from both CBCT and MR modalities meets the requirements for geometric accuracy.The average ratings of 4.4(for sCT generated from MR) and 4.5(for sCT generated from CBCT) were found across all structure models demonstrating that only minor edits would be required in order to make the structure models acceptable for clinical use. The test results are presented in Table 1 and Table 2.

A total of 247 synthetic CT images were used in the test, comprising 116 generated from MR and 131 generated from CBCT. The test data set information is as follows:

In terms of demographic distribution, the sample consisted of 57% male and 43% female patients. With reference to the 2020 U.S. Census adult gender ratio (approximately 1:1) and considering potential variations by specific cancer types in radiotherapy populations, this distribution is considered generally applicable.
The patient age distribution was: 13% aged 21-40, 44.1% aged 41-60, 36.8% aged 61-80, and 6.1% aged 81-100. Given that radiotherapy patients are predominantly middle-aged and elderly (with 60%-70% typically over 60 years old according to ASTRO data), this distribution is assessed as highly applicable and meeting clinical needs.
Regarding race, the sample comprised 78% White, 12% Black or African American, and 10% Others. This composition fully covers the key racial groups in U.S. clinical radiotherapy practice without omitting significant populations, thus deemed applicable.
Concerning medical imaging equipment brands, MR images used for sCT generation were obtained from GE (21.6%), Philips (56.9%), and Siemens (21.6%) scanners. This demonstrates excellent applicability as these three brands collectively represent the entirety of the mainstream MRI scanner market in U.S. radiotherapy clinics, ensuring comprehensive coverage of image characteristic variations across different manufacturers. CBCT images used for sCT generation were sourced from Varian (58.8%) and Elekta (41.2%) equipment, also showing excellent applicability since these two manufacturers dominate the U.S. radiotherapy CBCT equipment landscape, fully reflecting the actual clinical scenario for setup verification.

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Organ & Structure	NO.	Size	DSC			HD95 (mm)			Average Rating (1-5)
			Pass Criteria	DSC Mean	DSC STD	Lower Bound 95% CI	HD95 Mean	HD95 STD	Lower Bound 95% CI
TemporalLobe_L	37	Medium	0.65	0.898	0.036	0.886	4.58	0.824	4.319
TemporalLobe_R	37	Medium	0.65	0.892	0.043	0.878	4.67	0.905	4.382
Brain	47	Large	0.8	0.987	0.006	0.986	2.04	0.572	1.877
BrainStem	46	Medium	0.65	0.873	0.105	0.843	5.26	0.915	4.999
SpinalCord	103	Medium	0.65	0.873	0.032	0.867	3.20	0.865	3.030
OpticChiasm	36	Small	0.5	0.811	0.021	0.804	5.05	0.840	4.771
OpticNerve_L	36	Small	0.5	0.834	0.036	0.822	2.51	0.853	2.235
OpticNerve_R	36	Small	0.5	0.813	0.059	0.794	2.68	0.781	2.422
InnerEar_L	40	Small	0.5	0.852	0.028	0.843	2.40	0.771	2.164
InnerEar_R	39	Small	0.5	0.830	0.078	0.806	2.33	0.721	2.102
MiddleEar_L	40	Small	0.5	0.838	0.045	0.824	3.85	0.858	3.580
MiddleEar_R	41	Small	0.5	0.810	0.059	0.792	3.97	0.875	3.700
Eye_L	37	Small	0.5	0.929	0.070	0.906	1.83	0.530	1.659
Eye_R	37	Small	0.5	0.924	0.085	0.897	1.76	0.546	1.584
Lens_L	35	Small	0.5	0.852	0.048	0.836	3.62	0.760	3.368
Lens_R	35	Small	0.5	0.858	0.050	0.841	3.66	0.840	3.379
Pituitary	34	Small	0.5	0.826	0.073	0.801	2.55	0.829	2.267
Mandible	65	Small	0.5	0.922	0.035	0.913	2.01	0.677	1.844
TMJ_L	44	Small	0.5	0.842	0.043	0.830	3.06	0.820	2.819
TMJ_R	44	Small	0.5	0.830	0.045	0.817	2.96	0.814	2.722
OralCavity	66	Medium	0.65	0.926	0.044	0.916	3.90	0.916	3.677
Larynx	60	Medium	0.65	0.815	0.078	0.795	2.42	0.899	2.196
Trachea	57	Medium	0.65	0.895	0.096	0.870	2.69	0.932	2.452
Esophagus	72	Medium	0.65	0.812	0.053	0.800	2.89	0.919	2.680
Parotid_L	61	Medium	0.65	0.873	0.090	0.851	2.60	0.839	2.386
Parotid_R	62	Medium	0.65	0.882	0.058	0.868	2.53	0.819	2.328
Submandibular_L	57	Medium	0.65	0.848	0.058	0.833	5.13	0.794	4.920
Submandibular_R	56	Medium	0.65	0.811	0.107	0.783	2.56	0.813	2.348
Thyroid	57	Medium	0.65	0.822	0.073	0.803	2.11	0.774	1.911
BrachialPlexus_L	60	Medium	0.65	0.842	0.052	0.828	5.56	0.858	5.347
BrachialPlexus_R	60	Medium	0.65	0.821	0.082	0.800	5.29	0.890	5.062
Lung_L	54	Large	0.8	0.973	0.018	0.968	1.76	0.480	1.635
Lung_R	53	Large	0.8	0.980	0.015	0.976	1.66	0.523	1.516
Heart	53	Large	0.8	0.964	0.020	0.959	2.75	0.944	2.496
Liver	56	Large	0.8	0.949	0.032	0.941	2.63	0.727	2.439
Kidney_L	56	Large	0.8	0.912	0.080	0.892	2.97	0.837	2.748
Kidney_R	58	Large	0.8	0.917	0.084	0.895	3.02	0.871	2.797
Stomach	53	Large	0.8	0.827	0.166	0.782	5.00	0.927	4.754

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| Pancreas | 49 | Medium | 0.65 | 0.843 | 0.055 | 0.827 | 6.53 | 0.938 | 6.271 | 4.0 |
| Duodenum | 59 | Medium | 0.65 | 0.826 | 0.045 | 0.815 | 6.66 | 0.849 | 6.447 | 4.1 |
| Rectum | 21 | Medium | 0.65 | 0.818 | 0.052 | 0.796 | 2.46 | 0.964 | 2.047 | 3.9 |
| BowelBag | 53 | Large | 0.8 | 0.839 | 0.116 | 0.808 | 7.60 | 0.822 | 7.380 | 4.0 |
| Bladder | 21 | Large | 0.8 | 0.955 | 0.029 | 0.943 | 2.33 | 0.574 | 2.082 | 4.5 |
| Marrow | 28 | Large | 0.8 | 0.901 | 0.033 | 0.889 | 2.12 | 0.745 | 1.842 | 4.6 |
| FemurHead_L | 21 | Medium | 0.65 | 0.953 | 0.007 | 0.950 | 2.65 | 0.917 | 2.261 | 4.5 |
| FemurHead_R | 21 | Medium | 0.65 | 0.951 | 0.024 | 0.941 | 2.79 | 0.757 | 2.466 | 4.6 |

Table 1: Test Results for synthetic CT generated from MR images

Organ & Structure	NO.	Size	DSC			HD95 (mm)			Average Rating (1-5)
			Pass Criteria	DSC Mean	DSC STD	Lower Bound 95% CI	HD95 Mean	HD95 STD	Lower Bound 95% CI
TemporalLobe_L	41	Medium	0.65	0.879	0.082	0.854	3.69	0.797	3.451
TemporalLobe_R	41	Medium	0.65	0.885	0.085	0.859	3.50	0.822	3.258
Brain	44	Large	0.8	0.988	0.007	0.986	2.03	0.769	1.804
BrainStem	41	Medium	0.65	0.909	0.020	0.903	4.92	0.790	4.678
SpinalCord	118	Medium	0.65	0.879	0.055	0.869	2.24	0.828	2.088
OpticChiasm	41	Small	0.5	0.807	0.040	0.795	5.51	0.826	5.252
OpticNerve_L	40	Small	0.5	0.827	0.038	0.815	2.65	0.887	2.373
OpticNerve_R	40	Small	0.5	0.827	0.036	0.816	2.46	0.798	2.210
InnerEar_L	41	Small	0.5	0.809	0.032	0.800	2.40	0.831	2.144
InnerEar_R	41	Small	0.5	0.804	0.032	0.794	2.41	0.783	2.171
MiddleEar_L	41	Small	0.5	0.812	0.038	0.800	3.57	0.867	3.301
MiddleEar_R	41	Small	0.5	0.805	0.026	0.797	4.18	0.963	3.888
Eye_L	41	Small	0.5	0.948	0.013	0.944	1.71	0.524	1.553
Eye_R	41	Small	0.5	0.945	0.012	0.941	1.84	0.534	1.678
Lens_L	41	Small	0.5	0.836	0.050	0.820	3.76	0.741	3.532
Lens_R	41	Small	0.5	0.844	0.072	0.821	3.65	0.898	3.370
Pituitary	39	Small	0.5	0.815	0.039	0.802	2.72	0.718	2.496
Mandible	42	Small	0.5	0.901	0.103	0.870	2.42	0.650	2.227
TMJ_L	40	Small	0.5	0.802	0.092	0.774	3.06	0.930	2.775
TMJ_R	41	Small	0.5	0.819	0.061	0.800	3.08	0.956	2.791
OralCavity	37	Medium	0.65	0.910	0.080	0.885	4.01	0.669	3.794
Larynx	33	Medium	0.65	0.803	0.032	0.793	3.20	1.089	2.827
Trachea	48	Medium	0.65	0.891	0.063	0.873	2.81	0.954	2.545
Esophagus	56	Medium	0.65	0.811	0.039	0.800	3.04	0.872	2.811
Parotid_L	41	Medium	0.65	0.900	0.030	0.891	2.66	0.799	2.415
Parotid_R	40	Medium	0.65	0.902	0.025	0.894	2.77	0.796	2.525
Submandibular_L	29	Medium	0.65	0.808	0.173	0.745	5.27	0.667	5.026
Submandibular_R	29	Medium	0.65	0.840	0.118	0.797	2.51	0.887	2.192
Thyroid	33	Medium	0.65	0.837	0.042	0.823	2.44	0.769	2.182

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| BrachialPlexus_L | 47 | Medium | 0.65 | 0.823 | 0.063 | 0.805 | 4.16 | 0.838 | 3.922 | 4.4 |
| BrachialPlexus_R | 47 | Medium | 0.65 | 0.833 | 0.036 | 0.823 | 3.80 | 0.955 | 3.529 | 4.2 |
| Lung_L | 57 | Large | 0.8 | 0.961 | 0.054 | 0.947 | 1.71 | 0.493 | 1.587 | 4.5 |
| Lung_R | 57 | Large | 0.8 | 0.978 | 0.027 | 0.971 | 1.75 | 0.429 | 1.635 | 4.3 |
| Heart | 58 | Large | 0.8 | 0.925 | 0.112 | 0.896 | 2.03 | 0.821 | 1.823 | 4.5 |
| Liver | 38 | Large | 0.8 | 0.927 | 0.043 | 0.914 | 2.82 | 0.702 | 2.595 | 4.6 |
| Kidney_L | 22 | Large | 0.8 | 0.932 | 0.024 | 0.922 | 3.02 | 0.888 | 2.645 | 4.7 |
| Kidney_R | 24 | Large | 0.8 | 0.929 | 0.057 | 0.906 | 2.97 | 0.898 | 2.611 | 4.5 |
| Stomach | 25 | Large | 0.8 | 0.871 | 0.035 | 0.858 | 5.01 | 0.844 | 4.681 | 4.2 |
| Pancreas | 21 | Medium | 0.65 | 0.838 | 0.036 | 0.822 | 5.84 | 0.674 | 5.548 | 4.4 |
| Duodenum | 23 | Medium | 0.65 | 0.831 | 0.031 | 0.818 | 5.68 | 1.048 | 5.252 | 4.1 |
| Rectum | 20 | Medium | 0.65 | 0.811 | 0.031 | 0.797 | 4.54 | 0.657 | 4.253 | 4.3 |
| BowelBag | 33 | Large | 0.8 | 0.863 | 0.038 | 0.850 | 5.39 | 1.051 | 5.028 | 4.0 |
| Bladder | 22 | Large | 0.8 | 0.949 | 0.055 | 0.926 | 3.59 | 0.650 | 3.322 | 4.7 |
| Marrow | 22 | Large | 0.8 | 0.882 | 0.109 | 0.837 | 2.54 | 0.948 | 2.148 | 4.7 |
| FemurHead_L | 20 | Medium | 0.65 | 0.935 | 0.097 | 0.893 | 1.88 | 0.546 | 1.639 | 4.8 |
| FemurHead_R | 20 | Medium | 0.65 | 0.945 | 0.042 | 0.927 | 2.04 | 0.539 | 1.807 | 4.9 |

Table 2: Test Results for sCT generated from CBCT

Performance Test Report on 4DCT Registration Function

The performance test report on 4DCT registration was performed to to evaluate the image conversion functionby DICE Assessment Method. We use the RTStruct contoured by the professional physician as the gold standard, the first frame of each 4DCT set was registered with frames 2 to 10 from the same patient. The contour of each Region of Interest (ROI) was then compared, and the Dice Similarity Coefficient (DSC) was calculated.And then calculate DSC Mean, DSC STD and Lower Bound 95% Confidence Interval for each ROI, analyze the Dice coefficient results.Additionally, the qualitative clinical appropriateness of AccuContour structures generated on these scans was graded by clinical experts. The generated structures were graded on a scale from 1 to 5 where 5 refers to contour requiring no additional edits, and 1 refers to a score in which full manual re-contour of the structure would be required. An average score≥3 was used to determine whether a structure model would ultimately be beneficial clinically. According to the results, the accuracy of 4DCT image registration images meets the requirements and all structure models demonstrating that only minor edits would be required in order to make the structure models acceptable for clinical use. The test results are presented in Table 3 and Table 4.

A total of 30 4DCT image sets were used in the test. The test data set information is as follows:

The sample comprised images from Siemens (90.0%) and Philips (10.0%) scanners, representing major global vendors.
Demographically, subjects included 17 males (56.7%) and 13 females (43.3%), aged 33-82 years, with the majority in the 51-65 (40.0%) and 66-80 (43.3%) year brackets.
All images (100%) shared a uniform 3mm slice thickness. Most images (90.0%) were

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sourced from Drexel Town Square Health Center/Community Memorial Hospital, with the remainder from Froedtert Hospital.

This distribution supports the sample's representativeness and technical consistency for the intended study.

Organ & Structure	NO.	Size	Pass Criteria	DSC Mean	DSC STD	Lower Bound 95% CI	Average Rating (1-5)
Trachea	25	Medium	0.650	0.907	0.030	0.888	4.5
Esophagus	30	Medium	0.650	0.860	0.037	0.836	4.5
Lung_L	29	Large	0.800	0.947	0.022	0.932	4.7
Lung_R	30	Large	0.800	0.945	0.025	0.929	4.8
Lung_All	30	Large	0.800	0.946	0.023	0.930	4.8
Heart	30	Large	0.800	0.931	0.022	0.917	4.6
SpinalCord	30	Medium	0.650	0.949	0.008	0.943	4.6
Liver	30	Large	0.800	0.912	0.037	0.888	4.6
Stomach	30	Large	0.800	0.841	0.076	0.791	4.5
A_Aorta	30	Large	0.800	0.928	0.016	0.917	4.4
Spleen	30	Large	0.800	0.834	0.075	0.786	4.5
Body	30	Large	0.800	0.997	0.002	0.995	4.9

Table 3: Test Results after Rigid Registration for Each ROI

Organ & Structure	NO.	Size	Pass Criteria	DSC Mean	DSC STD	Lower Bound 95% CI	Average Rating (1-5)
Trachea	25	Medium	0.650	0.946	0.008	0.940	4.7
Esophagus	30	Medium	0.650	0.901	0.054	0.866	4.6
Lung_L	29	Large	0.800	0.975	0.012	0.966	4.7
Lung_R	30	Large	0.800	0.998	0.076	0.949	4.5
Lung_All	30	Large	0.800	0.993	0.060	0.954	4.8
Heart	30	Large	0.800	0.971	0.060	0.931	4.6
SpinalCord	30	Medium	0.650	0.964	0.067	0.920	4.6
Liver	30	Large	0.800	0.978	0.064	0.936	4.5
Stomach	30	Large	0.800	0.915	0.039	0.889	4.5
A_Aorta	30	Large	0.800	0.951	0.006	0.947	4.6
Spleen	30	Large	0.800	0.932	0.031	0.913	4.8
Body	30	Large	0.800	0.998	0.001	0.997	4.9

Table 4: Test Results after Deformable Registration for Each ROI

Overall, the AccuContour was found to be safe and effective for all intended users, purpose and use environments.

Mechanical and Acoustic Testing

Not Applicable (Standalone Software).

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Animal Study

Not Applicable (Standalone Software).

Clinical Studies

Clinical trials were not performed as part of the development of this product. Clinical testing on patients is not advantageous in demonstrating substantial equivalence or safety and effectiveness of the device since testing can be performed such that no human subjects are exposed to risk.

VIII. CONCLUSIONS

The subject device, AccuContour 4.0, is believed to be substantially equivalent to the predicate device in terms of its indications for use, technical characteristics, and overall performance. The information provided in this submission indicates its substantial equivalence to the predicate device.

Therefore, Manteia Technologies Co., Ltd. considered the subject AccuContour 4.0 is substantially equivalent to the predicate device AccuContour (K221706).

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).