target3D Fusion is a software application intended to be used by physicians in a clinic or hospital for visualization in 2D and 3D, registration, and fusion of Ultrasound (US), Magnetic Resonance (MR) and Computed Tomography (CT) images of the prostate. The software features also include multi-modality data communication, surface and volume rendering, segmentation, multi-planar reconstruction, organ and regions of interest delineation, landmark selection, measurements, patient database management, and data reporting.

Device Description

target3D Fusion is a software application, which allows a physician to segment the prostate gland, and identify and label various structures including regions of interest (ROIs) on a pre-procedural DICOM image. The software further allows a physician to fuse the prepared pre-procedural DICOM image files with one or more intra-procedure live DICOM image files to guide the procedure.

The software can delineate the gland boundary as well the boundaries of any other anatomical landmarks on a pre-procedure DICOM image. The structures including regions of interest are identified using visualization, and stored as standard surface format meshes. Each such structure is labeled uniquely.

target3D Fusion provides a physician with image fusion such that the information from a pre-procedure or planning imaging modality such as MR or CT is mapped to the frame of reference of the intra-procedure or live imaging modality such as ultrasound for real-time guidance while taking advantage of diagnostic capabilities of the pre-procedural planning image. The mapped information contains at least one structural image, and the target area to be treated. The pre-procedure image is registered with the intra-procedure image using a combination of rigid, affine and non-rigid elastic registration provides a correspondence or a deformation map, which is used to map planning information from the frame of reference of the planning image to an intra-procedure image.

AI/ML Overview

The target3D Fusion device has acceptance criteria related to its segmentation accuracy, affine registration accuracy, and overall registration accuracy.

Here's a breakdown of the information requested:

Table of acceptance criteria and the reported device performance:

Acceptance Criteria Category	Specific Criterion	Reported Device Performance
Segmentation Accuracy	Not explicitly stated as a numerical criterion, but aims for accurate segmentation compared to ground truth.	Average absolute volume difference errors: 2.8525%
Affine Registration Accuracy	Errors measured as overlap between objects being registered.	Overlap errors: under 0.0001 mm
Overall Registration Accuracy	Target registration error measured as average distance between landmarks (beads) across datasets.	Average distance (TRE): 1.7093 mm Standard deviation: 0.4008 mm

Sample size used for the test set and the data provenance:
- Sample Size: Not explicitly stated as a number of cases or images. The document mentions "datasets" for overall registration accuracy and "surfaces" for affine registration.
- Data Provenance: Not specified. It's unclear if the data was retrospective or prospective, or its country of origin. The test for overall registration accuracy mentions "phantoms containing beads," indicating some artificial data was used alongside potentially real clinical data for other tests.
Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This information is not provided in the given text.
Adjudication method for the test set:
- This information is not provided in the given text.
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:
- A MRMC comparative effectiveness study was not described for target3D Fusion. The studies focused on the performance of the software itself rather than its impact on human reader performance.
If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Yes, the described tests ("Segmentation Accuracy," "Affine Registration Accuracy," "Overall Registration Accuracy") appear to be standalone performance evaluations of the algorithm's capabilities against ground truth or synthetic deformations. The phrasing "compared segmentation algorithms in target3D Fusion with ground truth data" and "errors measured as the overlap between objects being registered" indicates algorithmic performance.
The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- For Segmentation Accuracy, it mentions "ground truth data" generally.
- For Affine Registration Accuracy, "synthetic deformations between surfaces" were used, meaning the ground truth for deformation was known.
- For Overall Registration Accuracy, "phantoms containing beads used as landmarks" were used, where the positions of these beads likely served as the ground truth for registration accuracy.
The sample size for the training set:
- This information is not provided in the given text.
How the ground truth for the training set was established:
- This information is not provided in the given text.

Summary

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Submitter's Name:	Convergent Life Sciences, Inc.
Submitter's Address:	2377 Gold Meadow Way, Suite 160, Gold River, CA 95670
Submitter's Telephone:	916-526-2775
Contact Name:	Dinesh Kumar
Date Summary was Prepared:	11/18/2013
Trade or Proprietary Name:	target3D Fusion
Common or Usual Name:	target3D Fusion
Classification Name:	System, Image Processing, Radiological Picture Archiving andCommunications, 21CFR 892.2050
Device Class:	II
Product Code:	LLZ
Predicate Devices:	Device Name 510(k) Number Multi-Modality Image Fusion K120187

UROSTATION-3D Prostate Suite

K131448

K041182

Intended Use

software features also include multi-modality data communication, surface and volume .

a rendering, segmentation, multi-planar reconstruction, organ and regions of interest delineation, landmark selection, measurements, patient database management, and data reporting.

Description of the Device and Summary of the Technological Characteristics

Syntegra

target3D Fusion provides a physician with image fusion such that the information from a pre-procedure or planning imaging modality such as MR or CT is mapped to the frame of

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reference of the intra-procedure or live imaging modality such as ultrasound for real-time guidance while taking advantage of diagnostic capabilities of the pre-procedural planning image. The mapped information contains at least one structural image, and the target area to be treated. The pre-procedure image is registered with the intra-procedure image using a combination of rigid, affine and non-rigid elastic registration provides a correspondence or a deformation map, which is used to map planning information from the frame of reference of the planning image to an intra-procedure image.

Substantial Equivalence

target3D Fusion product's technological features are substantially equivalent to its predicate devices. Table 5.1 shows the comprehensive comparison of the features and technological characteristics of target3D Fusion with the predicates. The table shows that all of them:

are PC based software applications, ●
run on Windows operating system, .
. provide 2D and 3D medical image acquisition and visualization,
. fuse (co-register) pre-procedure medical images in DICOM formats with intra-procedure medical images,
. provide data communication between imaging modalities,
. provide surface and volume rendering,
. provide multi-planar reformatting,
. allow for organ and regions of interest delineation/segmentation,
. include image enhancements such as zoom controls, and
. incorporate patient database management.

target3D Fusion differs in the following feature from its predicate devices. However, this does not cause any safety or effectiveness concerns:

. target3D Fusion uses a patented co-registration/fusion algorithm, which uses a combination of rigid, affine and non-rigid (elastic) registration.

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Product	target3D Fusion	Multi-ModalityImage Fusion	UROSTATION-3DProstate Suite	Syntegra
Manufacturer	Convergent LifeSciences	Eigen	Koelis	ADAC Laboratories
510(k) Number	pending	K120187	K131448	K041182
Intended Use	target3D Fusion is asoftware applicationintended to be usedby physicians in aclinic or hospital forvisualization in 2D and3D, registration, andfusion of Ultrasound(US), MagneticResonance (MR) andComputedTomography (CT)images of theprostate. The softwarefeatures also includemulti-modality datacommunication,surface and volumerendering,segmentation, multi-planar reconstruction,organ and regions ofinterest delineation,landmark selection,measurements,patient databasemanagement, anddata reporting.	Multi-ModalityImageFusion is a softwareapplication used byphysicians in theclinic or hospital for2-D and3-D visualization,multi-modalityimage registration,and fusion ofmedical images.Additional softwarefeatures includedatabasemanagement,communication,surface rendering,segmentation, ROIdelineation,measurements, andreporting.	UROSTATION - 3DPROSTATE SUITEWith MRI/3DTRUSfusion option andwith Second Look3D)TRUS fusionoption is intendedto be used byphysicians in theclinic or hospital for2D and3D) visualization ofthe prostate glandand for the 3D)transrectalultrasound basedfusion of multipleimaging modalities(ultrasound, MRZI)in order to mapsuch prostategland. Additionalsoftware featuresinclude patient datamanagement,multimodal datacommunication,multiplanarreconstruction,surface and volumerendering, organdelineation, regionof interestdelineation, 3D3image registrationand data reporting.	Syntegra is asoftwareapplication formulti- modalityimage registrationand diagnosticfusion. Images areregistered anddisplayed in a"fused" (overlaid inthe same spatialorientation) formatto providecombinedfunctional andanatomical dataproviding differentangularperspectives forinterpretation bytrainedprofessionals.
Product Type	Software	Software	Software	Software
SoftwarePlatform	PC running WindowsOS	PC runningWindows OS	PC runningWindows OS	PC runningWindows OS
Product Usage	Clinic or hospital	Clinic or hospital	Clinic or hospital	Clinic or hospital

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	setting	setting	setting	setting
Product	target3D Fusion	Multi-ModalityImage Fusion	UROSTATION-3DProstate Suite	Syntegra
Manufacturer	Convergent LifeSciences	Eigen	Koelis	ADAC Laboratories
510(k) Number	pending	K120187	K131448	K041182
Visualization ofImages	2D and 3D	2D and 3D	2D and 3D	2D and 3D
ImageFusion/Registration	Multiple modalityimage fusion	Multiple modalityimage fusion	Multiple modalityimage fusion	Multiple modalityimage fusion
Display of ImageFusion	Fused overlay ofimages from differentmodalities	Fused overlay ofimages fromdifferent modalities	Fused overlay ofimages fromdifferent modalities	Fused overlay ofimages fromdifferent modalities
DataCommunicationbetweenImagingModalities	Yes	Yes	Yes	Yes
SurfaceRendering	Yes	Yes	Yes	Yes
VolumeRendering	Yes	Yes	Yes	Yes
Multi-planarreformatting	Yes	Yes	Yes	Yes
GlandSegmentation	Yes	Yes	Yes	Yes
Regions ofInterestSegmentation(Delineation)	Yes	Yes	Yes	Yes
ConfigurableImage Layouts	Yes	Yes	Yes	Yes
ImageEnhancements	Yes	Yes	Yes	Yes

Summary of Testing and Performance Data

The software was tested against the engineering specifications and additional requirements arising from risk management activities. In addition, the software was rigorously tested and debugged as part of product development lifecycle.

The following bench tests were conducted to meet the product requirements and customer expectations:

Segmentation Accuracy: Performance tests for segmentation compared segmentation algorithms in target3D Fusion with ground truth data. Average absolute volume difference errors were found to be 2.8525%.

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· · Affine Registration Accuracy: Affine registration tests were performed to recover synthetic deformations between surfaces. The errors measured as the overlap between objects being registered were found to be under 0.0001 mm.
Overall Registration Accuracy: Registration errors for the entire system that included . manual, affine and non-rigid registration were measured by registering multimodality images of phantoms containing beads used as landmarks for computing target registration error. Target registration error measured as the average distance between beads across datasets was found to be 1.7093 mm with a standard deviation of 0.4008 mm.

Conclusion

Substantial equivalence comparison including intended use, function, specifications and technological characteristics of target3D Fusion with the predicate devices demonstrates that target3D Fusion is substantially equivalent to the listed predicates.

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DEPARTMENT OF HEALTH & HUMAN SERVICES

Public Heatth Service

Food and Drug Administration 10903 New Hampshire Avenue Document Control Center - WO66-G609 Silver Spring, MD 20993-0002

February 27, 2014

Convergent Life Sciences, Inc. % Mr. Mark Job Responsible Third Party Official Regulatory Technology Services, LLC 1934 25th Street NW BUFFALO MN 55313

Re: K140033

Trade/Device Name: target3D Fusion Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: 11 Product Code: LLZ. Dated: February 11, 2014 Received: February 12, 2014

Dear Mr. Job:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments. or to devices that have been reclassified in accordance with the provisions of the Federal Food. Drug. and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration. Iisting of devices, good manufacturing practice. labeling, and prohibitions against misbranding and adulteration. Please note: CDRH docs 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. FIDA may publish further announcements concerning your device in the Federal Register.

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 803); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

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Page 2-Mr. Job

If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Division of Small Manufacturers, International and Consumer Assistance at its tollfree number (800) 638 2041 or (301) 796-7100 or at its Internet address

http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to

http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/dcfault.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.

You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.

Sincerely yours,

for

Janine M. Morris Director, Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health 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: January 31, 2017 See PRA Statement on last page.

510(k) Number (if known)

K140033 Pending

Device Name

イ

target3D Fusion

Indications for Use (Describe)

target >> Fusion is a software application intended to be used by physicians in a clinic or hospital for visualization in 2D and 3D, registration. and fusion of Ultrasound (US). Magnetic Resonance (MR) and Computed Tomography (CT) inages of the prossate. The software features also include multi-modality data communication, surface and volume rendering, segmentation, multi-planar reconstruction, organ and regions of interest delinent selection, measurements, patient database management, and data reporting.

Type of Use (Select one or both, as applicable)

[8] Prescription Use (Part 21 CFR 801 Subpart D)

Over-The-Counter Use (21 CFR 801 Subpart C)

PLEASE DO NOT WRITE BELOW THIS LINE - CONTINUE ON A SEPARATE PAGE IF NEEDED.

FOR FDA USE ONLY

Concurrence of Center for Devices and Radiological Health (CDRH) (Signature)

FORM FDA 3881 (1/14)

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).