(144 days)
Smart Segmentation Knowledge Based Contouring provides a combined atlas and model based approach for automated and manual segmentation of structures including target volumes and organs at risk to support the radiation therapy treatment planning process.
Smart Segmentation - Knowledge Based Contouring is a software only product that provides a combined atlas and model based approach to automated segmentation of structures together with tools for manual contouring or editing of structures. A library of already contoured expert cases is provided which is searchable by anatomy, staging, or free text. Users also have the ability to add or modify expert cases to suit their clinical needs. Expert cases are registered to the target image and selected structures propagated. Smart Segmentation Knowledge Based Contouring supports inter and intra user consistency in contouring. This product also provides an anatomy atlas which gives examples of delineated organs for the whole upper body, as well as anatomy images and functional description for selectable structures.
The provided 510(k) summary for Varian's Smart Segmentation Knowledge Based Contouring (K133227) is primarily focused on demonstrating substantial equivalence to a predicate device (K112778 and K102011) due to changes in existing features and the addition of new ones (support for 4D-CT data and a new algorithm for mandible segmentation). The document does not contain a detailed study demonstrating specific acceptance criteria with reported performance metrics in the format requested.
The document states "Verification testing was performed to demonstrate that the performance and functionality of the new and existing features met the design input requirements" and "Validation testing was performed on a production equivalent device, under clinically representative conditions by qualified personnel." However, the specific acceptance criteria, performance results, and details of these tests (like sample sizes, ground truth establishment, expert qualifications, etc.) are not included in the provided text.
Therefore, for most of the requested information, a direct answer cannot be extracted from the given input.
Here's a breakdown of what can and cannot be answered based on the provided text:
1. Table of acceptance criteria and the reported device performance
- Cannot be provided. The document states that "performance and functionality of the new and existing features met the design input requirements" and "Results from Verification and Validation testing demonstrate that the product met defined user needs and defined design input requirements." However, specific numerical acceptance criteria (e.g., Dice similarity coefficient > 0.8) and the corresponding reported device performance values are not detailed.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Cannot be provided. The document mentions "Validation testing was performed... under clinically representative conditions," but it does not specify the sample size of the test set, the country of origin of the data, or whether it was retrospective or prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Cannot be provided. The document refers to "expert cases" in the context of the device's functionality (a library of already contoured expert cases), but it does not detail the number or qualifications of experts used to establish ground truth for validation testing of the device itself.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Cannot be provided. The document does not describe any adjudication methods used for establishing ground truth or evaluating the test set.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
- Cannot be provided. The document does not mention an MRMC comparative effectiveness study or the effect size of AI assistance on human readers. The device is described as "supporting inter and intra user consistency in contouring," but no study is detailed to quantify this improvement.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Implicitly yes, but no details are provided. The device is described as having "Automated Structure Delineation" and a "new algorithm for segmentation of the mandible." The "Verification testing" and "Validation testing" would logically evaluate the performance of these automated functions, implying a standalone evaluation. However, no specific performance metrics or study details for this standalone performance are given.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
- Implicitly expert contoured data, but no specific details for validation. The device itself uses a "library of already contoured expert cases." It is reasonable to infer that the ground truth for validation testing would also be based on expert contoured data, but the document does not explicitly state this for the validation set, nor does it specify if this was expert consensus, single expert, or another method.
8. The sample size for the training set
- Cannot be provided. The document mentions a "library of already contoured expert cases" which is central to a "knowledge based" system. This library would constitute the training data (or knowledge base). However, the sample size of this library or training set is not specified.
9. How the ground truth for the training set was established
- Implicitly by experts, but no specific details. The device uses a "library of already contoured expert cases." This implies the ground truth for these training cases was established by "experts." However, details on how these experts established this ground truth (e.g., number of experts, consensus process, qualifications) are not provided.
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K133227
Page 1 of 5
Varian
3100
Palo Alto, CA
USA
Tel +1
Varian Medical Systems, Inc.
3100 Hansen Way
Palo Alto, CA 94304-1038
USA
Tel +1 650 493 4000
www.varian.com
October 18, 2013
510(k) Summary
The information below is provided for the Smart Segmentation Knowledge Based Contouring, following the format of 21 CFR 807.92.
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- 510(k) Owner: Varian Medical Systems 3100 Hansen Way, M/S C 260 Palo Alto, CA 94304 Contact Name: Peter J. Coronado - Director, Regulatory Affairs Phone: 650/424.6320 Fax: 650/842.5040 E-mail: submissions.support@varian.com
| 2. Name of the Device: | Smart Segmentation Knowledge Based Contouring | |
|---|---|---|
| Trade/Proprietary Names: | Smart Segmentation - Knowledge Based Contouring |
| Common Name: | Smart Segmentation Knowledge Based Contouring |
|---|---|
| Classification Name: | Medical Charged Particle Radiation Therapy System21 CFR §892.5050Class IIProduct Code 90 IYE |
| 3. Predicate Devices: | Eclipse K102011 |
- Smart Segmentation Knowledge Based Contouring K112778
-
- Description of the Device:
The Smart Segmentation Knowledge Based Contouring was most recently cleared as the Varian Smart Segmentation Knowledge Based Contouring, K112778.
Smart Segmentation - Knowledge Based Contouring is a software only product that provides a combined atlas and model based approach to automated segmentation of structures together with tools for manual contouring or editing of structures. A library of already contoured expert cases is provided which is searchable by anatomy, staging, or free text. Users also have the ability to add or modify expert cases to suit their clinical needs. Expert cases are registered to the target image and selected
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structures propagated. Smart Segmentation Knowledge Based Contouring supports inter and intra user consistency in contouring. This product also provides an anatomy atlas which gives examples of delineated organs for the whole upper body, as well as anatomy images and functional description for selectable structures.
-
- Reason for submission:
Changes in SS-KBC have prompted a new submission. Support of 4D-CT data sets and a new algorithm for segmentation of the mandible are changes new to Smart Segmentation Knowledge Based Contouring.
- Reason for submission:
-
- Intended Use Statement
Smart Segmentation - Knowledge Based Contouring provides a combined atlas and model based approach for automated and manual segmentation of structures including target volumes and organs at risk to support the radiation therapy treatment planning process.
- Intended Use Statement
-
- Indications for Use Statement
Smart Segmentation Knowledge Based Contouring provides a combined atlas and model based approach for automated and manual segmentation of structures including target volumes and organs at risk to support the radiation therapy treatment planning process.
- Indications for Use Statement
8. Substantial Equivalence
The modified device, the Smart Segmentation Knowledge Based Contouring, is substantially equivalent to the predicate devices, the Smart Segmentation Knowledge Based Contouring (K112778) and Eclipse (K102011). The Intended Use and Indications for Use are unchanged.
Compared with the predicate devices, the Smart Segmentation Knowledge Based Contouring (K112778) and Eclipse with Smart Segmentation (K102011), the basic operation and technological characteristics are the same. Operational differences are described in the Instructions for Use for the SS-KBC 2.1. A comparison table illustrating the substantial equivalence of the modified device to the predicate devices appears below.
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| Changes in Technological characteristics: | |||
|---|---|---|---|
| Feature List | Eclipse(K102011) | SmartSegmentation -KBC 2.0(K112778) | SmartSegmentation -KBC 2.1 |
| General Usage | |||
| Support for External beam PHOTONplanning | yes | yes | yes |
| Support for External beam PHOTONinverse planning | yes | yes | yes |
| Support for External beam ELECTRONplanning | yes | yes | yes |
| Support for External beam PROTONplanning | yes | yes | yes |
| Automated Structure Delineation | yes | yes | yes |
| Graphical User Interface | |||
| Three View Layout | yes | yes | yes |
| Four View Layout (ortho & 3d) | yes | yes | yes |
| 3d volume rendering | yes | yes | yes |
| 3d volume MIP rendering | yes | yes | yes |
| 3d volume MIP (rotating) rendering | yes | yes | yes |
| 3d mesh rendering | yes | yes | yes |
| 3d multiplane rendering single image | yes | yes | yes |
| 3d multiplane rendering blended image | yes | yes | yes |
| 3d segments rendering | yes | yes | yes |
| Pixel Info Tool | yes | yes | yes |
| Distance Tool | yes | yes | yes |
| Pan Image | yes | yes | yes |
| Adjust window / level | yes | yes | yes |
| Angle Tool | yes | yes | yes |
| Area Profile Tool | yes | yes | yes |
| Histogram Tool | yes | yes | yes |
| Select Structure Tool | yes | yes | yes |
| Planar Contour Drawing Tool | yes | yes | yes |
| Brush Tool | yes | yes | yes |
| Diffusion Brush Tool | yes | yes | yes |
| Volumetric Contour Drawing Tool | yes | yes | yes |
| Deform Structure Tool | no | yes | yes |
| Image Threshold Tool | yes | yes | yes |
| PET Subvolume Threshold Tool | yes | yes | yes |
| Boolean Structure Operations | yes | yes | yes |
| Feature List | Eclipse(K102011) | SmartSegmentation -KBC 2.0(K112778) | SmartSegmentation -KBC 2.1 |
| Auto Match 3d (rigid) | yes | yes | yes |
| Manual Match (rigid) | yes | yes | yes |
| Automatic Deformable Registration | no | yes | yes |
| Region of interest selection | yes | yes | yes |
| Body Search Tool | yes | no | yes |
| Post-processing Tool (smoothing) | yes | no | yes |
| Add Margins Tool | yes | no | yes |
| High Density Tool | yes | no | yes |
| Flood Fill Tool | yes | no | yes |
| Extract Wall Tool | yes | no | yes |
| Structure templates | yes | no | yes |
| 4D-CT: player | yes | no | yes |
| 4D-CT: merge structures | yes | no | yes |
| 4D-CT: paste structures to all phases | yes | no | yes |
| 4D-CT: automatic segmentation | yes | no | yes |
| 4D-CT: RPM respiration trace viewer | no | no | yes |
| Structure Editing | |||
| Clear Structure | yes | yes | yes |
| Delete Structure | yes | yes | yes |
| Delete Structure Set | yes | yes | yes |
| Copy Structure to registered image | yes | yes | yes |
| Duplicate structure | yes | yes | yes |
| Set Structure Status | yes | yes | yes |
| Change Structure ID | yes | yes | yes |
| Change Structure color & Style | yes | yes | yes |
| Show PET Patient Data | yes | yes | yes |
| Crop structure | yes | no | yes |
| Extend Segmentation | yes | no | yes |
| Interpolate Segmentation | yes | no | yes |
| Structure Segmentation and Expert Case Selection | |||
| Default to algorithm basedsegmentation for certain structures | yes (algorithmbased is onlyoption) | yes | yes |
| Expert Case browser | no | yes | yes |
| Expert case search - filters | no | yes | yes |
| Expert case search - free text search | no | yes | yes |
Changes in Technological characteristics:
510(k) Summary – SS-KBC 2.1
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510(k) Summary – SS-KBC 2.1
·
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| ッフ12 | r |
|---|---|
| and | ﺴﺘﻤ |
| 0 | // |
| 1 | 20 |
| Feature List | Eclipse(K102011) | SmartSegmentation -KBC 2.0(K112778) | SmartSegmentation -KBC 2.1 |
|---|---|---|---|
| Expert case search - add / removebookmarks | no | yes | yes |
| Expert opinion text display | no | yes | yes |
| Add new customer case to database | no | yes | yes |
| Modify existing expert case ondatabase | no | yes | yes |
| Generate thumbnail preview for expertcase | no | yes | yes |
| Anatomy text book display | no | yes | yes |
| Expert Case Library content and supported structures | |||
| Segmentation of mandible | no | no | yes |
| Connectivity | |||
| DICOM compatibility | yes | yes | yes |
-
- Summary of Non-Clinical Testing
Verification testing was performed to demonstrate that the performance and functionality of the new and existing features met the design input requirements.
- Summary of Non-Clinical Testing
Regression testing was performed to verify the integrity of any changes. Validation testing was performed on a production equivalent device, under clinically representative conditions by qualified personnel,
-
- Conclusions from Non-Clinical testing
Results from Verification and Validation testing demonstrate that the product met defined user needs and defined design input requirements. Varian therefore considers Smart Segmentation Knowledge Based Contouring to be safe and effective and to perform at least as well as the predicate device.
- Conclusions from Non-Clinical testing
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DEPARTMENT OF HEALTH & HUMAN SERVICES
Public Health Service
Food and Drug Administration 10903 New Hampshire Avenue Document Control Center - WO66-G609 Silver Spring, MD 20993-0002
March 14, 2014
Varian Medical Systems, Inc. % Mr. Peter J. Coronado Director, Global Regulatory Affairs 3100 Hansen Way PALO ALTO CA 94304
Re: K133227
Trade/Device Name: Smart Segmentation - Knowledge Based Contouring Regulation Number: 21 CFR 892.5050 Regulation Name: Medical charged-particle radiation therapy system Regulatory Class: II Product Code: IYE Dated: January 31, 2014 Received: February 3, 2014
Dear Mr. Coronado:
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, 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 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. Peter J. Coronado
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" (21 CFR 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/ReportalProblem/default.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,
Andrew D. O'Hara
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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Indications for Use
510(k) Number (if known): K133227
Device Name: Smart Segmentation Knowledge Based Contouring
Indications for Use:
Smart Segmentation Knowledge Based Contouring provides a combined atlas and model based approach for automated and manual segmentation of structures including target volumes and organs at risk to support the radiation therapy treatment planning process.
Prescription Use × (Part 21 CFR 801 Subpart D)
AND/OR
Over-The-Counter Use (21 CFR 807 Subpart C)
(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)
Concurrence of CDRH, Office of In Vitro Diagnostics and Radiological Health (OIR)
Michael D. O'Hara
(Division Sign-Off) Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health 510(k) _______________________________________________________________________________________________________________________________________________________________________ K133227
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§ 892.5050 Medical charged-particle radiation therapy system.
(a)
Identification. A medical charged-particle radiation therapy system is a device that produces by acceleration high energy charged particles (e.g., electrons and protons) intended for use in radiation therapy. This generic type of device may include signal analysis and display equipment, patient and equipment supports, treatment planning computer programs, component parts, and accessories.(b)
Classification. Class II. When intended for use as a quality control system, the film dosimetry system (film scanning system) included as an accessory to the device described in paragraph (a) of this section, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.