(195 days)
Yes
The device description explicitly states that the "Rib extraction algorithm is based on Machine Learning".
No
The device is a software solution for viewing, manipulating, and storing medical images, primarily for diagnostic purposes. It does not actively treat or intervene in a disease process to restore health.
No
The device is a software solution for viewing, manipulating, communicating, and storing medical images. While it processes images and includes tools like a rib extraction algorithm, its stated intention is not to diagnose but to support radiologists in their tasks by providing tools for image reading and reporting. It is explicitly stated that it is not for "displaying of digital mammography images for diagnosis in the U.S."
Yes
The device description explicitly states "uOmnispace is a software only medical device, the hardware itself is not seen as part of the medical device and therefore not in the scope of this product." It also mentions use with "off the-shelf PC computer technology."
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are tests performed on samples taken from the human body, such as blood, urine, or tissue, to detect diseases, conditions, or infections.
- Device Function: The description clearly states that uOmnispace is a software solution for "viewing, manipulation, communication and storage of medical images." It processes and displays images from modalities like CT, MRI, PET, and DR.
- Lack of Biological Sample Analysis: There is no mention of the device analyzing biological samples or performing any tests on bodily fluids or tissues. Its function is solely focused on the processing and interpretation of medical images.
Therefore, uOmnispace falls under the category of medical imaging software, not an In Vitro Diagnostic device.
No
There is no explicit statement in the provided text indicating that the FDA has reviewed, approved, or cleared a PCCP for this specific device. The 'Control Plan Authorized (PCCP) and relevant text' section is marked 'Not Found'.
Intended Use / Indications for Use
uOmnispace is a software solution intended to be used for viewing, manipulation, communication and storage of medical images. It allows processing and filming of multimodality DICOM images.
It can be used as a stand-alone device or together with a variety of cleared and unmodified software options, and also support to plug in multi-vendor applications which meet interface requirements.
u Omnispace is intended to be used by trained professionals, including but not limited to physicians and medical technicians.
The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.
Product codes
QIH
Device Description
uOmnispace is a software only medical device, the hardware itself is not seen as part of the medical device and therefore not in the scope of this product.
uOmnispace provides 2D and 3D viewing, annotation and measurement tools, manually and automatically segmentation tools (Rib extraction algorithm is based on Machine Learning) and film and report features to cover the radiological tasks reading images and reporting. uOmnispace supports DICOM formatted images and objects, CT, MRI, PET and DR multimodality are supported.
uOmnispace is a software medical device that allows multiple users to remotely access clinical applications from compatible computers on a network. The system allows processing and filming of multimodality DICOM images. This software is for use with off the-shelf PC computer technology that meets defined minimum specifications.
uOmnispace communicates with imaging systems of different modalities and medical information systems of the hospital using the DICOM3.0 standard.
The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes, "Rib extraction algorithm is based on Machine Learning" and "ML-based rib segmentation algorithm".
Input Imaging Modality
CT, MRI, PET and DR
Anatomical Site
Not Found
Indicated Patient Age Range
Not Found
Intended User / Care Setting
trained professionals, including but not limited to physicians and medical technicians.
Description of the training set, sample size, data source, and annotation protocol
The training data used for the training of the post-processing algorithm is independent of the algorithm.
Description of the test set, sample size, data source, and annotation protocol
Performance testing for ML-based rib segmentation algorithm was performed on 60 subjects (chest CTs).
Sex: Male 37, Female 23. Age: [14, 35] : 5, [36, 69] : 41, [70, 86] : 14.
For ground truth annotations, all ground truth are annotators. A threshold based interactive tool is used to generate initial rib mask, then annotators will refine the first round annotation, they will check each other's annotation. At last, a senior clinical specialist will check and modify annotations to make sure the ground truth correct.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Performance Verification: The ML-based rib segmentation algorithm contained in the product underwent a scientific evaluation. The performance testing for ML-based rib segmentation algorithm was performed on 60 subjects (chest CTs).
Acceptance Criteria: The average dice of testing data is higher than 0.8.
Performance Testing Summary: The average dice on testing data set is 0.855, which is higher than 0.8. Meanwhile, the subgroup analysis shows that the performance of algorithm are consistent in different subgroups.
Age: [14,35] DICE 0.848, [36,69] DICE 0.856, [70,86] DICE 0.856.
Gender: Female DICE 0.856, Male DICE 0.855.
The results of clinical data-based software validation for the subject device demonstrated equivalent performance in comparison to the reference device.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Average DICE (0.855)
Predicate Device(s)
Reference Device(s)
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 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).
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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA text logo on the right. The text logo has the FDA acronym in a blue square, followed by the words "U.S. FOOD & DRUG ADMINISTRATION" in blue.
Shanghai United Imaging Healthcare Co., Ltd. % Xin Gao RA Manager No. 2258 Chengbei Rd., Jiading District Jiading Industrial District Shanghai, Shanghai 201807 CHINA
Re: K230039
Trade/Device Name: Medical Image Post-processing Software, Model: uOmnispace Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH Dated: June 20, 2023 Received: June 20, 2023
Dear Xin Gao:
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. 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 located 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.
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
1
801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 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, 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
2
Indications for Use
Submission Number (if known)
Device Name
uOmnispace
Indications for Use (Describe)
uOmnispace is a software solution intended to be used for viewing, manipulation, communication and storage of medical images. It allows processing and filming of multimodality DICOM images.
It can be used as a stand-alone device or together with a variety of cleared and unmodified software options, and also support to plug in multi-vendor applications which meet interface requirements.
u Omnispace is intended to be used by trained professionals, including but not limited to physicians and medical technicians.
The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.
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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Image /page/3/Picture/2 description: The image contains the logo for United Imaging. The logo consists of the words "UNITED IMAGING" stacked on top of each other in a bold, sans-serif font. To the right of the words is a stylized "U" shape, which is also in a bold font. The color of the logo is a dark gray.
510 (k) SUMMARY
1. Date of Preparation: June 20, 2023
2. Sponsor Identification
Shanghai United Imaging Healthcare Co., Ltd. No.2258 Chengbei Rd. Jiading District, 201807, Shanghai, China
Establishment Registration Number: 3011015597
Contact Person: Xin GAO Position: Regulatory Affairs Manager Tel: +86-021-67076888-5386 Fax: +86-021-67076889 Email: xin.gao@united-imaging.com
3. Identification of Proposed Device
Trade Name: Medical Image Post-processing Software Common Name: Medical image management and processing system Model(s): uOmnispace
Regulatory Information Classification Name: Medical image management and processing system Classification: II Product Code: QIH Regulation Number: 21 CFR 892.2050 Review Panel: Radiology
4. Identification of Predicate Device(s)
Predicate Device 510(k) Number: K191040 Device Name: syngo.via Classification: II Product Code: LLZ
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Image /page/4/Picture/1 description: The image shows the logo for United Imaging. The logo consists of the words "UNITED IMAGING" in a bold, sans-serif font, stacked on top of each other. To the right of the words is a stylized "U" shape, which is dark gray. The logo is simple and modern.
Reference Device 510(k) Number: K183170 Device Name: uWS-CT Classification: II Product Code: LLZ
5. Device Description
uOmnispace is a software only medical device, the hardware itself is not seen as part of the medical device and therefore not in the scope of this product.
uOmnispace provides 2D and 3D viewing, annotation and measurement tools, manually and automatically segmentation tools (Rib extraction algorithm is based on Machine Learning) and film and report features to cover the radiological tasks reading images and reporting. uOmnispace supports DICOM formatted images and objects, CT, MRI, PET and DR multimodality are supported.
uOmnispace is a software medical device that allows multiple users to remotely access clinical applications from compatible computers on a network. The system allows processing and filming of multimodality DICOM images. This software is for use with off the-shelf PC computer technology that meets defined minimum specifications.
uOmnispace communicates with imaging systems of different modalities and medical information systems of the hospital using the DICOM3.0 standard.
The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.
6. Indications for use
uOmnispace is a software solution intended to be used for viewing, manipulation, communication and storage of medical images.
It can be used as a stand-alone device or together with a variety of cleared and unmodified software options, and also support to plug in multi-vendor applications which meet interface requirements.
uOmnispace is intended to be used by trained professionals, including but not limited to physicians and medical technicians.
The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.
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Image /page/5/Picture/1 description: The image contains the logo for United Imaging. The text "UNITED IMAGING" is displayed in a bold, sans-serif font. To the right of the text is a stylized "U" symbol, which is dark gray with a white vertical line running through the center. The logo appears to be clean and modern.
7. Summary of Technological Characteristics
The technology characteristics of uOmnispace, reflected in this 510(k) submission is substantially equivalent to those of the predicate device.
The following tables compare the technology and intended use of uOmnispace when compared to the predicate devices.
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Image /page/6/Picture/1 description: The image contains the logo for United Imaging. The logo consists of the words "UNITED IMAGING" stacked on top of each other in a bold, sans-serif font. To the right of the text is a stylized "U" shape, which is divided vertically by a white line. The logo is simple and modern in design.
| Item | Proposed Device | Predicate Device | Reference Device | Comparison |
|---|---|---|---|---|
| uOmnispace | syngo.via | uWS-CT | ||
| (K191040) | (K183170) | |||
| Device Classification | ||||
| Name | Medical image | |||
| management and | ||||
| processing system | Medical image | |||
| management and | ||||
| processing system | / | Same | ||
| Product Code | LLZ, QIH | LLZ | / | Same |
| Regulation Number | 21 CFR 892.2050 | 21 CFR 892.2050 | / | Same |
| Device Class | II | II | / | Same |
| Classification Panel | Radiology | Radiology | / | Same |
| Intended Use | uOmnispace is a software | |||
| solution intended to be | ||||
| used for viewing, | ||||
| manipulation, | ||||
| communication and storage | ||||
| of medical images. It | ||||
| allows processing and | ||||
| filming of multimodality | ||||
| DICOM images. | ||||
| It can be used as a stand- | ||||
| alone device or together | ||||
| with a variety of cleared | ||||
| and unmodified software | ||||
| options, and also support | syngo.via is a software | |||
| solution intended to be | ||||
| used for viewing, | ||||
| manipulation, | ||||
| communication, and | ||||
| storage of medical | ||||
| images. | ||||
| It can be used as a stand- | ||||
| alone device or together | ||||
| with a variety of cleared | ||||
| and unmodified | ||||
| syngo based software | ||||
| options. | / | Substantial Equivalence | ||
| This difference between the predicate | ||||
| device and the proposed device is about | ||||
| description, it doesn't impact the safety | ||||
| and effectiveness of the subject device. | ||||
| to plug in multi-vendor | ||||
| applications which meet | ||||
| interface requirements. | ||||
| uOmnispace is intended to | ||||
| be used by trained | ||||
| professionals, including but | ||||
| not limited to physicians | ||||
| and medical technicians. | ||||
| The system is not intended | ||||
| for the displaying of digital | ||||
| mammography images for | ||||
| diagnosis in the U.S. | syngo.via supports | |||
| interpretation and | ||||
| evaluation of | ||||
| examinations within | ||||
| healthcare institutions, | ||||
| For example, in | ||||
| Radiology, Nuclear | ||||
| Medicine and Cardiology | ||||
| environments. | ||||
| The system is not | ||||
| intended for the | ||||
| displaying of digital | ||||
| mammography images | ||||
| for diagnosis in the U.S. | ||||
| Client-Server | ||||
| Architecture and Multi- | ||||
| User Access | Yes | |||
| Based on client-server | ||||
| architecture and supports | ||||
| multi-user access. | Yes | |||
| Based on client-server | ||||
| architecture and supports | ||||
| multi-user access. | / Same | |||
| Image communication | ||||
| and storage | Yes | |||
| Communicate and store | ||||
| medical images based on | ||||
| standard communication | ||||
| protocol DICOM. | Yes | |||
| Communicate and store | ||||
| medical images based on | ||||
| standard communication | ||||
| protocol DICOM. | / Same | |||
| Hardware /OS | Yes | |||
| Client: | ||||
| Microsoft Windows 7 or | ||||
| Microsoft | Yes | |||
| Client: | ||||
| Microsoft Windows 7 SP1 | ||||
| or Microsoft | / Functional Substantially Equivalent | |||
| The client and server operating systems of | ||||
| the proposed device are Microsoft Windows | ||||
| and Linux respectively, while those of the | ||||
| Windows 10 or compatible | ||||
| versions | ||||
| Server: | ||||
| Linux Core CentOS7.7 or | ||||
| compatible versions | Windows 8.1 or Microsoft | |||
| Windows 10 | ||||
| Server: | ||||
| Microsoft Windows Server | ||||
| 2008 R2 or | ||||
| Microsoft Windows Server | ||||
| 2012 R2. | predicate device are Microsoft Windows and | |||
| Microsoft Windows Server respectively. | ||||
| This difference doesn't impact the safety | ||||
| and effectiveness of the subject device. | ||||
| or Microsoft Server 2016 | ||||
| Workflow control | Yes | |||
| Pre-processing: Auto | ||||
| process images before | ||||
| loading into post-processing | ||||
| applications. | ||||
| The client workflow | ||||
| supports both single monitor | ||||
| and dual monitors. | Yes | |||
| Workflows support the | ||||
| user in preparing images | ||||
| for examination. | ||||
| Supports various monitor | ||||
| setups workflow. | / | Functional Substantially Equivalent | ||
| Pre-processing is equivalent to part of the | ||||
| "preparing images for examination", the | ||||
| predicate device also assigns the | ||||
| examination to an application. This | ||||
| difference doesn't impact the safety and | ||||
| effectiveness of the subject device. | ||||
| Patient Administration | Yes | |||
| Patient administration | ||||
| displays the patient data and | ||||
| offers the function of | ||||
| searching, sorting, and | ||||
| editing of patient data and | ||||
| image preview. | Yes | |||
| With simplified search | ||||
| functionality, clearer | ||||
| structure of search results, | ||||
| unlimited search results, | ||||
| periodic updates of search | ||||
| results, image preview and | ||||
| flexible floating patient | ||||
| browser window. | / | Functional Substantially Equivalent | ||
| The proposed device does not support | ||||
| flexible floating patient browser window. | ||||
| This difference doesn't impact the safety | ||||
| and effectiveness of the subject device. | ||||
| Review 2D | Yes | / | Yes | Same |
| 2D image viewing, Textual | ||||
| and graphical annotations, | ||||
| distance, angle, ROI, image | ||||
| addition and subtraction, | ||||
| image filter are supported. | 2D image viewing, Textual | |||
| and graphical | ||||
| annotations, distance, | ||||
| angle, ROI, image addition | ||||
| and subtraction, image | ||||
| filter are supported. | ||||
| Review 3D | Yes | |||
| 3D image viewing, Save 3D | ||||
| images in batches. | ||||
| Segmentation functions such | ||||
| as CT bone removal tools, | ||||
| CT/MR tissue growing tools, | ||||
| VOI, cut. | Yes | |||
| 3D image viewing. | ||||
| Save 3D images in | ||||
| batches. | ||||
| Segmentation functions | ||||
| such as CT bone removal | ||||
| tools, CT tissue growing | ||||
| tools, VOI, cut. | Same | |||
| Review 3D algorithm | Yes | |||
| Volume rendering (VR) with | ||||
| Hyper Realistic Rendering | ||||
| (HRR), Multi-Planar | ||||
| Reconstruction (MPR), | ||||
| Maximum Intensity | ||||
| Projection (MIP), Minimum | ||||
| Intensity Projection (MinIP), | ||||
| Curved Planar Reformation | ||||
| (CPR), Surface-shaded | ||||
| Display (SSD). | ||||
| Automatic body bone | ||||
| removal algorithm | Yes | |||
| Volume rendering (VR), | ||||
| Multi-Planar | ||||
| Reconstruction (MPR), | ||||
| Maximum Intensity | ||||
| Projection (MIP), | ||||
| Minimum Intensity | ||||
| Projection (MinIP), | ||||
| Curved Planar | ||||
| Reformation (CPR), | ||||
| Surface-shaded Display | ||||
| (SSD). | ||||
| Automatic body bone | ||||
| removal algorithm | Functional Substantially Equivalent | |||
| HRR is an extension to the standard VR | ||||
| rendering algorithm to visualize the | ||||
| photorealistic images. | ||||
| This difference between the proposed device | ||||
| and the reference device doesn't impact the | ||||
| safety and effectiveness of the subject device | ||||
| as the necessary measures taken for the | ||||
| safety and effectiveness of the proposed | ||||
| device. | ||||
| Automatic head bone | ||||
| removal algorithm | Automatic head bone | |||
| removal algorithm | ||||
| Rib segmentation | Yes | |||
| Machine learning based | ||||
| algorithm | / | Yes | ||
| Threshold based | ||||
| interactive algorithm | Functional Substantially Equivalent | |||
| Both are used for rib segmentation, the | ||||
| reference device requires interaction, | ||||
| while the proposed device does not. | ||||
| This difference between the proposed device | ||||
| and the reference device doesn't impact the | ||||
| safety and effectiveness of the subject device | ||||
| as the necessary measures taken for the | ||||
| safety and effectiveness of the proposed | ||||
| device | ||||
| Inner view | Yes | |||
| 3D virtual endoscopy view | ||||
| and extract the centerline of | ||||
| vessel, airway and colon. | ||||
| Imaging algorithms: | ||||
| CT colon Inner View | ||||
| algorithm | ||||
| CT vessel Inner View | ||||
| algorithm | ||||
| CT lung trachea Inner | ||||
| View algorithm | ||||
| MR vessel Inner View | ||||
| algorithm | / | Yes | ||
| 3D virtual endoscopy view | ||||
| and extract the centerline | ||||
| of vessel, airway and | ||||
| colon. | ||||
| Imaging algorithms: | ||||
| CT colon Inner View | ||||
| algorithm, CT vessel Inner | ||||
| View algorithm | ||||
| CT lung trachea Inner | ||||
| View algorithm | Functional Substantially Equivalent | |||
| The MR vessel Inner View algorithm is | ||||
| same with CT vessel Inner View algorithm, | ||||
| the difference of input modality does not | ||||
| affects the output. | ||||
| This difference between the proposed device | ||||
| and the reference device doesn't impact the | ||||
| safety and effectiveness of the subject device | ||||
| as the necessary measures taken for the | ||||
| safety and effectiveness of the proposed | ||||
| device. | ||||
| Filming | Yes | / | Yes | Same |
| Report | Support to print image and selection of printer. | |||
| Yes | ||||
| Support to create reports, text editing and image inserting, customize report template, exporting and printing of report. | / | Support to print image and selection of printer. | ||
| Yes | ||||
| Support to create reports, text editing and image inserting, customize report template, exporting and printing of report. | Same | |||
| Archiving | Yes | |||
| Import of DICOM images from configured network nodes (modalities, medical imaging process software, PACS, etc) or local and network drives or DVD/CD. | ||||
| Export (archive) DICOM images to network nodes, or local and network drives or DVD/CD. | Yes | |||
| Import of DICOM data from network nodes or external media, and of DICOM-compliant or non DICOM compliant data from external media and Windows file system. | ||||
| Export to CD/DVD, Windows file system, or other DICOM nodes. | / | Functional Substantially Equivalent | ||
| The proposed product does not support to import non DICOM compliant data from external media and Windows file system. | ||||
| This difference between the proposed device and the reference device doesn't impact the safety and effectiveness of the subject device as the necessary measures taken for the safety and effectiveness of the proposed device |
Table 1 Substantial equivalent discussion for basic functions
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Image /page/7/Picture/1 description: The image shows the logo for United Imaging. The words "UNITED IMAGING" are in bold, sans-serif font, stacked on top of each other. To the right of the words is a stylized "U" shape, which is dark blue. The logo is simple and modern.
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Image /page/8/Picture/1 description: The image contains the logo for United Imaging. The words "UNITED IMAGING" are stacked on top of each other and are in a bold, sans-serif font. To the right of the words is a stylized "U" symbol. The symbol is a dark gray color and has a vertical line running through the center of the "U".
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Image /page/9/Picture/1 description: The image contains the logo for United Imaging. The logo consists of the words "UNITED IMAGING" stacked on top of each other in a bold, sans-serif font. To the right of the text is a stylized "U" symbol, which is dark blue. The logo is simple and modern.
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Image /page/10/Picture/1 description: The image contains the logo for United Imaging. The logo consists of the words "UNITED IMAGING" in bold, sans-serif font, stacked on top of each other. To the right of the text is a stylized "U" shape, which is formed by two vertical bars connected by a horizontal bar in the middle. The logo is simple and modern in design.
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Image /page/11/Picture/1 description: The image contains the logo for United Imaging. The logo consists of the words "UNITED IMAGING" in bold, sans-serif font, stacked on top of each other. To the right of the text is a stylized symbol that resembles a shield or a stylized letter "U" with a horizontal line through the middle. The color scheme is a dark, muted blue-green.
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Image /page/12/Picture/1 description: The image contains the logo for United Imaging. The logo consists of the words "UNITED IMAGING" stacked on top of each other in a bold, sans-serif font. To the right of the text is a stylized symbol that resembles a shield or a stylized letter "U" with a horizontal line through the middle. The color of the text and symbol is a dark teal or blue-gray.
8. Performance Data
The following performance data were provided in support of the substantial equivalence determination.
Biocompatibility
Not Applicable to the proposed device, because the device is stand-alone software.
Electrical Safety and Electromagnetic Compatibility (EMC)
Not Applicable to the proposed device, because the device is stand-alone software.
Software Verification and Validation
Software verification and validation testing was provided to demonstrate safety and efficacy of the proposed device. This includes a hazard analysis, and the potential hazards have been classified as a moderate level of concern (LOC). Those documentations include:
- · Software Description
- Device Hazard Analysis
- Software Requirements Specification
- Software Architecture Design Chart
- · Software Development Environment Description
- Software Verification and Validation
- · Cybersecurity Documents
Animal Study
No animal study was required.
Clinical Studies
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No clinical study was required.
Performance Verification
To validate the uOmnispace software from a clinical perspective, the ML-based rib segmentation algorithm contained in the product underwent a scientific evaluation. The results of clinical data-based software validation for the subject device demonstrated equivalent performance in comparison to the reference device.
The performance testing for ML-based rib segmentation algorithm was performed on 60 subjects (data shown in Table 8-2) during the product development.
Acceptance Criteria .
The validation type and acceptance criteria is shown in the Table 8-1 below:
Table 8-1. Validation type and acceptance criteria
| Validation Type | Acceptance Criteria |
|---|---|
| Average DICE | The average dice of testing data is higher than 0.8 |
- Testing Data Information .
Table 8-2. Testing data information
| Information of data | 60 chest CTs |
|---|---|
| Sex | Male 37 |
| Female 23 | |
| Age | [14, 35] : 5 |
| [36, 69] : 41 | |
| [70, 86] : 14 |
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Performance Testing Summary: .
The average dice on testing data set is 0.855, which is higher than 0.8. Meanwhile, the subgroup analysis shows that (Table 8-3) the performance of algorithm are consist in different subgroups.
| Age | DICE |
|---|---|
| [14,35] | 0.848 |
| [36,69] | 0.856 |
| [70,86] | 0.856 |
| Gender | DICE |
| Female | 0.856 |
| Male | 0.855 |
Toblo 0 2 Subaraum norfam
Standard Annotation Process .
For ground truth annotations, all ground truth are annotators. A threshold based interactive tool is used to generate initial rib mask, then annotators will refine the first round annotation, they will check each other's annotation. At last, a senior clinical specialist will check and modify annotations to make sure the ground truth correct.
Testing & Training Data Independence .
The training data used for the training of the post-processing algorithm is independent of the digorithm
Other Standards and Guidance
- NEMA PS 3.1 3.20 Digital Imaging and Communications in Medicine (DICOM) Set (2016). ●
- ISO 14971 Medical devices Application of risk management to medical devices (Edition 2.0, corrected version, 2007). ●
- IEC 62304 Medical device software Software life cycle processes (Edition 1.1, 2015). ●
Summary
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Image /page/15/Picture/1 description: The image shows the logo for United Imaging. The words "UNITED IMAGING" are stacked on top of each other in a bold, sans-serif font. To the right of the words is a stylized "U" symbol, which is made up of two vertical lines and a horizontal line. The logo is simple and modern, and the colors are muted.
The features described in this premarket submission are supported with the results of the testing mentioned above; the uOmnispace was found to have a safety and effectiveness profile that is similar to the predicate device and reference devices.
9. Substantially Equivalent Conclusion
The proposed device is equivalent to the predicate device with regard to safety and efficacy. This conclusion is based upon a comparison of intended use, technological characteristics, performance specification, device hazards, as well as verification and validation results.
In summary, the proposed device is determined to be Substantially Equivalent (SE) to the predicate device and reference devices.