(203 days)
DEN 200055
Not Found
Yes
The document explicitly states that the device uses "artificial intelligence algorithms" and a "customized deep learning model."
No
The device is described as a "computer-assisted detection device" that highlights regions of potential polyps and sounds alerts. It explicitly states it is "not intended to replace a full patient evaluation, nor is it intended to be relied upon to make or confirm a diagnosis," and physicians must confirm findings. This indicates it is a diagnostic aid, not a device that directly treats or provides therapy.
No
The device is explicitly stated as "not intended to be relied upon to make or confirm a diagnosis." Its purpose is to assist in real-time detection, but the final medical judgment and diagnosis remain the responsibility of the physician.
Yes
The device is described as "stand-alone software" and the performance studies mention evaluating the software device with "appropriate hardware components," implying the software is distinct from the hardware it runs on. The description focuses solely on the software's function of analyzing video streams and overlaying boxes.
Based on the provided information, the EndoScreener is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVD Definition: IVD devices are used to examine specimens (like blood, urine, tissue) taken from the human body to provide information about a person's health. This testing is performed in vitro (outside the body).
- EndoScreener's Function: The EndoScreener analyzes a live video stream from a colonoscopy procedure, which is performed in vivo (inside the body). It processes images of the colon directly, not specimens taken from the body.
- Intended Use: The intended use clearly states it's for "real-time automatic detection of polyps in colonoscopy video stream during the procedure." This is an in vivo application.
Therefore, the EndoScreener falls under the category of a medical device used during a procedure performed on a patient, rather than an IVD device used for testing specimens in a lab.
No
The input text does not contain any explicit statement that the FDA has reviewed, approved, or cleared a PCCP for this specific device.
Intended Use / Indications for Use
EndoScreener is intended as a stand-alone software for real-time automatic detection of polyps in colonoscopy video stream during the procedure.
Physicians are responsible for reviewing the identified areas of suspect polyps presented by EndoScreener and confirming the presence or absence of a polyp on the evaluation of the colonoscopy image on their own medical judgment. EndoScreener is not intended to replace a full patient evaluation, nor is it intended to be relied upon to make or confirm a diagnosis.
EndoScreener is indicated for use by licensed endoscopists who perform colonoscopy in adults. EndoScreener is indicated for use with white light colonoscopy.
Product codes
QNP
Device Description
The EndoScreener is a computer-assisted detection device for colorectal polyps. EndoScreener takes as input colonoscopy video stream from an endoscopy device, which is analyzed in real-time. The device output consists of blue boxes overlaid onto the colonoscopy images to highlight regions of potential polyp. EndoScreener also has the option to sound an alert to the physicians who perform the colonoscopy when a polyp has been detected. Following detection by EndoScreener, the physician must confirm the EndoScreener findings based on his/her own medical judgment.
Mentions image processing
EndoScreener takes as input colonoscopy video stream from an endoscopy device, which is analyzed in real-time. The device output consists of blue boxes overlaid onto the colonoscopy images to highlight regions of potential polyp. Endoscopic imaging degradation and latency due to the device were also evaluated, with appropriate hardware components, and the software device produced no imaging degradation and ignorable end-to-end latency.
Mentions AI, DNN, or ML
- Both the EndoScreener and the GI Genius use artificial intelligence algorithms to assist clinicians in detecting colon polyps colonoscopy examination.
- The subject device uses a customized deep learning model, which is likely to be slightly different from the deep learning model and customization used by GI Genius.
- In the nonclinical testing of the subject device included validation of the deep learning algorithm on multiple datasets to evaluate per-image sensitivity and specificity as well as per-polyp sensitivity and AUC.
Input Imaging Modality
colonoscopy video stream, white light colonoscopy
Anatomical Site
colorectal
Indicated Patient Age Range
adults
Intended User / Care Setting
licensed endoscopists who perform colonoscopy
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
In the nonclinical testing of the subject device included validation of the deep learning algorithm on multiple datasets to evaluate per-image sensitivity and specificity as well as per-polyp sensitivity and AUC. Specifically, performance was evaluated on a dataset of 1,138 consecutive polyp patients with histology confirmation and acceptable performance was obtained.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
- Nonclinical testing: validation of the deep learning algorithm on multiple datasets to evaluate per-image sensitivity and specificity as well as per-polyp sensitivity and AUC. Performance was evaluated on a dataset of 1,138 consecutive polyp patients with histology confirmation and acceptable performance was obtained. The EndoScreener functioned as intended and the polyp detection accuracy observed was as expected. Endoscopic imaging degradation and latency due to the device were also evaluated, with appropriate hardware components, and the software device produced no imaging degradation and ignorable end-to-end latency.
- Clinical study: multi-center, tandem colonoscopy, randomized controlled trial, performed at four United States academic medical centers. The study included 223 patients with screening and surveillance indications, whom were randomized to CADe-routine group and Routine-CADe group for back-to-back colonoscopy procedures. The primary endpoint adenoma miss rate (AMR) was significantly lower in CADe-first group and the 1st pass adenoma per colonoscopy (APC) was higher in the CADe-first group.
- Based on the clinical performance, the EndoScreener has a safety and effectiveness profile that is similar to the predicate device.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
- per-image sensitivity
- per-image specificity
- per-polyp sensitivity
- AUC
- adenoma miss rate (AMR)
- 1st pass adenoma per colonoscopy (APC)
Predicate Device(s)
GI Genius (DEN 200055)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 876.1520 Gastrointestinal lesion software detection system.
(a)
Identification. A gastrointestinal lesion software detection system is a computer-assisted detection device used in conjunction with endoscopy for the detection of abnormal lesions in the gastrointestinal tract. This device with advanced software algorithms brings attention to images to aid in the detection of lesions. The device may contain hardware to support interfacing with an endoscope.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Clinical performance testing must demonstrate that the device performs as intended under anticipated conditions of use, including detection of gastrointestinal lesions and evaluation of all adverse events.
(2) Non-clinical performance testing must demonstrate that the device performs as intended under anticipated conditions of use. Testing must include:
(i) Standalone algorithm performance testing;
(ii) Pixel-level comparison of degradation of image quality due to the device;
(iii) Assessment of video delay due to marker annotation; and
(iv) Assessment of real-time endoscopic video delay due to the device.
(3) Usability assessment must demonstrate that the intended user(s) can safely and correctly use the device.
(4) Performance data must demonstrate electromagnetic compatibility and electrical safety, mechanical safety, and thermal safety testing for any hardware components of the device.
(5) Software verification, validation, and hazard analysis must be provided. Software description must include a detailed, technical description including the impact of any software and hardware on the device's functions, the associated capabilities and limitations of each part, the associated inputs and outputs, mapping of the software architecture, and a description of the video signal pipeline.
(6) Labeling must include:
(i) Instructions for use, including a detailed description of the device and compatibility information;
(ii) Warnings to avoid overreliance on the device, that the device is not intended to be used for diagnosis or characterization of lesions, and that the device does not replace clinical decision making;
(iii) A summary of the clinical performance testing conducted with the device, including detailed definitions of the study endpoints and statistical confidence intervals; and
(iv) A summary of the standalone performance testing and associated statistical analysis.
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November 19, 2021
Chengdu Wision Medical Device Co., LTD. % John Smith Partner Hogan Lovells US LLP 555 Thirteenth St, NW Washington, DC 20004
Re: K211326
Trade/Device Name: EndoScreener Regulation Number: 21 CFR 876.1520 Regulation Name: Gastrointestinal lesion software detection system Regulatory Class: Class II Product Code: QNP Dated: November 18, 2021 Received: November 18, 2021
Dear John Smith:
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.
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You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatoryinformation/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 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,
Shanil P. Haugen, Ph.D. Assistant Director DHT3A: Division of Renal, Gastrointestinal, Obesity and Transplant Devices OHT3: Office of GastroRenal, ObGyn, General Hospital and Urology Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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510(k) Number (if known) K211326
Device Name
EndoScreener Indications for Use (Describe)
EndoScreener is intended as a stand-alone software for real-time automatic detection of polyps in colonoscopy video stream during the procedure.
Physicians are responsible for reviewing the identified areas of suspect polyps presented by EndoScreener and confirming the presence or absence of a polyp on the evaluation of the colonoscopy image on their own medical judgment. EndoScreener is not intended to replace a full patient evaluation, nor is it intended to be relied upon to make or confirm a diagnosis.
EndoScreener is indicated for use by licensed endoscopists who perform colonoscopy in adults. EndoScreener is indicated for use with white light colonoscopy.
Type of Use (Select one or both, as applicable)
区 Prescription Use (Part 21 CFR 801 Subpart D)
□ Over-The-Counter Use (21 CFR 801 Subpart C)
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510(k) SUMMARY
Changdu Wision's EndoScreener
Submitter
Chengdu Wision Medical Device Co., Ltd. Unit 802, Floor 8, Building 17, Yintaicheng No.1999 Yizhou Road, Wuhou District
Chengdu, Sichuan, China, 610041
Phone: +86 139-1030-8383
Contact Person: JingJia Liu
Date Prepared: November 16, 2021
Name of Device: EndoScreener
Common or Usual Name: Computer aided detection software for colorectal polyps
Classification Name: Gastrointestinal lesion software detection system
Requlatory Class: Class II (21 CFR 876.1520)
Product Code: QNP
Predicate Device: GI Genius (DEN 200055)
Device Description
The EndoScreener is a computer-assisted detection device for colorectal polyps. EndoScreener takes as input colonoscopy video stream from an endoscopy device, which is analyzed in real-time. The device output consists of blue boxes overlaid onto the colonoscopy images to highlight regions of potential polyp. EndoScreener also has the option to sound an alert to the physicians who perform the colonoscopy when a polyp has been detected. Following detection by EndoScreener, the physician must confirm the EndoScreener findings based on his/her own medical judgment.
Intended Use / Indications for Use
EndoScreener is intended as a stand-alone software for real-time automatic detection of polyps in colonoscopy video stream during the procedure.
Physicians are responsible for reviewing the identified areas of suspect polyps presented by EndoScreener and confirming the presence or absence of a polyp on the evaluation of the
4
colonoscopy image on the monitor and their own medical judgment. EndoScreener is not intended to replace a full patient evaluation, nor is it intended to be relied upon to make or confirm a diagnosis.
EndoScreener is indicated for use by licensed endoscopists who perform colonoscopy in adults. EndoScreener is indicated for use with white light colonoscopy.
Summary of Technological Characteristics
At a high level, the subject and predicate devices are based on the following same technological elements:
- . Both the EndoScreener and the GI Genius use artificial intelligence algorithms to assist clinicians in detecting colon polyps colonoscopy examination.
- Both devices take as input a colonoscopy video stream from an endoscopy device and provide as an output a bounding box that highlights the detected polyps.
- Both devices are used in real-time to aid the clinicians in identifying abnormal lesions. .
The following technological differences exist between the subject and predicate devices:
- . The subject device uses a customized deep learning model, which is likely to be slightly different from the deep learning model and customization used by GI Genius.
Performance Data
In the nonclinical testing of the subject device included validation of the deep learning algorithm on multiple datasets to evaluate per-image sensitivity and specificity as well as per-polyp sensitivity and AUC. Specifically, performance was evaluated on a dataset of 1,138 consecutive polyp patients with histology confirmation and acceptable performance was obtained. For all assessments performed, the EndoScreener functioned as intended and the polyp detection accuracy observed was as expected. Endoscopic imaging degradation and latency due to the device were also evaluated, with appropriate hardware components, and the software device produced no imaging degradation and ignorable end-to-end latency.
EndoScreener performance was also evaluated in a multi-center, tandem colonoscopy, randomized controlled trial, performed at four United States academic medical centers. The study included 223 patients with screening and surveillance indications, whom were randomized to CADe-routine group and Routine-CADe group for back-to-back colonoscopy procedures. The primary endpoint adenoma miss rate (AMR) was significantly lower in CADefirst group and the 1st pass adenoma per colonoscopy (APC) was higher in the CADe-first group.
Based on the clinical performance as documented in the pivotal clinical study, the EndoScreener has a safety and effectiveness profile that is similar to the predicate device.
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Conclusions
The EndoScreener is as safe and effective as the GI Genius. The EndoScreener has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences in indications do not alter the intended use of the device and do not affect its safety and effectiveness when used as labeled. In addition, the minor technological differences between the EndoScreener and its predicate device raise no new issues of safety or effectiveness. Performance data demonstrate that the EndoScreener is as safe and effective as GI Genius. Thus, the EndoScreener is substantially equivalent.