(250 days)
Yes
The device description explicitly states that it "runs deep machine learning and additional supporting algorithms" and mentions "deep machine learning algorithms from the type of Deep Neural Networks (DNN) technology". The predicate device is also an AI-based system.
No.
The device functions as an adjunct to assist in identifying lesions, not to provide treatment or therapy.
No
The "Intended Use / Indications for Use" and "Device Description" both explicitly state that the device is "not intended to be used for diagnosis or characterization of lesions, and does not replace clinical decision making." It is intended as an "adjunct" to assist in identifying lesions.
No
The device description explicitly states that the system includes a separate touchscreen supplied as part of the ME-APDS and a 1x4 HDMI Splitter supplied with the system. These are hardware components, making it a system that includes both software and hardware, not a software-only medical device.
Based on the provided information, the ME-APDS is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVD Definition: In Vitro Diagnostics are devices intended for use in the collection, preparation, and examination of specimens taken from the human body (such as blood, urine, tissue) to provide information for diagnosis, monitoring, or screening.
- ME-APDS Function: The ME-APDS processes video images from a colonoscopy procedure in real-time. It does not analyze biological specimens taken from the patient. Its purpose is to assist the endoscopist in identifying potential lesions visually during the procedure.
- Intended Use: The intended use explicitly states it is an "adjunct to the common video colonoscopy procedure" and is "not intended to replace histopathological sampling as means of diagnosis." This reinforces that it's a tool for visual assistance during an in-vivo procedure, not for laboratory analysis of specimens.
- Device Description: The description details the processing of the "digital video output signal from the local endoscopy camera" and presenting the results on a screen. This is consistent with image processing during a live procedure, not with the analysis of biological samples.
Therefore, the ME-APDS falls under the category of a medical device used during an in-vivo procedure, specifically for image analysis and assistance, rather than an In Vitro Diagnostic device.
No
The letter does not state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The "Control Plan Authorized (PCCP)" section is explicitly marked as "Not Found."
Intended Use / Indications for Use
The ME-APDS (Magentig Eye's Automatic Polyp Detection System) is intended to be used by endoscopists as an adjunct to the common video colonoscopy procedure (screening and surveillance), aiming to assist in identifying lesions during colonoscopy procedure by highlighting regions with visual characteristics consistent with different types of mucosal abnormalities that appear in the colonoscopy video during the procedure. Highlighted regions can be independently assessed by the endoscopist and appropriate action taken according to standard clinical practice.
The ME-APDS is trained to process video images which may contain regions consistent with polyps.
The ME-APDS is limited for use with standard white-light endoscopy imaging only.
The ME-APDS is intended to be used as an adjunct to endoscopy procedures and is not intended to replace histopathological sampling as means of diagnosis.
Product codes
ONP
Device Description
The ME-APDS (Magentig Eve's Automatic Polvo Detection System) is intended to be used as an adjunct to the common video colonoscopy procedure. The system application aims to assist the endoscopist in identifying lesions, such as polyps, during the colonoscopy procedures in real time. The device is not intended to be used for diagnosis or characterization of lesions, and does not replace clinical decision making.
The system acquires the digital video output signal from the local endoscopy camera and processes the video frames. It runs deep machine learning and additional supporting algorithms in real time on the video frames in order to detect and identify regions having characteristics consistent with different tvpes of mucosal abnormalities such as polyps. The output video with the detected lesions is presented on a separate touchscreen, supplied as part of the ME-APDS, highlighting the suspicious areas on the original video. The output of the system can also be presented on additional monitors in the procedure room using the 1x4 HDMI Splitter supplied with the system. The user can also take snapshots of the videos, with and without the highlighting of the suspicious areas, record videos and view in full screen mode.
Mentions image processing
Yes
Mentions AI, DNN, or ML
The system acquires the digital video output signal from the local endoscopy camera and processes the video frames. It runs deep machine learning and additional supporting algorithms in real time on the video frames in order to detect and identify regions having characteristics consistent with different tvpes of mucosal abnormalities such as polyps.
Both systems' computing devices retrieve the video stream from the Endoscope and run a deep machine learning algorithms from the type of Deep Neural Networks (DNN) technology in real time.
Input Imaging Modality
standard white-light endoscopy imaging
Anatomical Site
Colon
Indicated Patient Age Range
Not Found
Intended User / Care Setting
endoscopists
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
The algorithm was tested offline on 172 unique full colonoscopy videos, containing 449 polyps, 16 videos contained no polyps. Of the 449 polyps, 330 were small (s≤5mm), 76 have medium size (5mm6-9 mm polyps, sessile and flat polyps and adenomas in the proximal colon. In addition, more sessile serrated adenomas (SSAs) were identified in MEACs as compared to CCs, which resulted in also a higher sessile serrated detection rate (SDR). Despite the increased detection rate, the MEAC adenomas per extraction (APE) proved non-inferior to that of CC, and did not involve clinically relevant longer withdrawal times or delayed bleeding. In line with these findings, AMR was significantly lower and ADR was significantly higher in the MEAC vs. CC arm. As expected, given the above findings, time to next scheduled colonoscopy was 4 months earlier in the MEAC as compared to the CC cohort.
No intervention-related adverse events were reported during this study in either arm.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Standalone Performance Testing:
- Polyp-wise Recall (with Histology): 100.0% (PRecall1), 99.6% (PRecall3), 99.6% (PRecall5), 99.6% (PRecall7)
- Polyp-wise Recall (without Histology): 100.0% (PRecall1), 100.0% (PRecall3), 100.0% (PRecall5), 100.0% (PRecall7)
- Polyp-wise Recall (Entire Testing Dataset): 98.2% (PRecall1), 94.2% (PRecall3), 91.5% (PRecall5), 90.0% (PRecall7)
- False Positives Per Full Video (procedure) rate: 0.0328 (when all the videos are normalized to a time length of 15 minutes)
Predicate Device(s)
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.
0
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July 25, 2023
Magentiq Eye LTD % John Smith Partner Hogan Lovells US LLP Columbia Square, 555 Thirteenth Street, NW Washington, District of Columbia 20004
Re: K223473
Trade/Device Name: ME-APDS™; MAGENTIQ-COLO™ Regulation Number: 21 CFR 876.1520 Regulation Name: Gastrointestinal Lesion Software Detection System Regulatory Class: Class II Product Code: ONP Dated: June 22, 2023 Received: June 22, 2023
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
1
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 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 medical devices and radiation-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 -S
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
2
510(k) Number (if known) K223473
Device Name
ME-APDS™: MAGENTIQ-COLOTM
Indications for Use (Describe)
The ME-APDS (Magentig Eye's Automatic Polyp Detection System) is intended to be used by endoscopists as an adjunct to the common video colonoscopy procedure (screening and surveillance), aiming to assist in identifying lesions during colonoscopy procedure by highlighting regions with visual characteristics consistent with different types of mucosal abnormalities that appear in the colonoscopy video during the procedure. Highlighted regions can be independently assessed by the endoscopist and appropriate action taken according to standard clinical practice.
The ME-APDS is trained to process video images which may contain regions consistent with polyps.
The ME-APDS is limited for use with standard white-light endoscopy imaging only.
The ME-APDS is intended to be used as an adjunct to endoscopy procedures and is not intended to replace histopathological sampling as means of diagnosis.
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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3
510(k) SUMMARY Magentig Eye's ME-APDS
Submitter:
Magentiq Eye Ltd. 6 Ben-Gurion Blvd., Haifa. 3541416. lsrael
Phone: +972 (77) 2018838
Contact Person: Dr. Dror Zur
Date Prepared: July 23, 2023
Name of Device: Magentiq Eye's Automatic Polyp Detection System (ME-APDS™)
Common or Usual Name: Computer aided detection software for colorectal polyps
Classification Name: Gastrointestinal Lesion Software Detection System
Regulatory Class: II
Product Code: QNP
Predicate Device: Cosmo Artificial Intelligence - AI, LTD's GI Genius (K211951)
Device Description:
The ME-APDS (Magentig Eve's Automatic Polvo Detection System) is intended to be used as an adjunct to the common video colonoscopy procedure. The system application aims to assist the endoscopist in identifying lesions, such as polyps, during the colonoscopy procedures in real time. The device is not intended to be used for diagnosis or characterization of lesions, and does not replace clinical decision making.
The system acquires the digital video output signal from the local endoscopy camera and processes the video frames. It runs deep machine learning and additional supporting algorithms in real time on the video frames in order to detect and identify regions having characteristics consistent with different tvpes of mucosal abnormalities such as polyps. The output video with the detected lesions is presented on a separate touchscreen, supplied as part of the ME-APDS, highlighting the suspicious areas on the original video. The output of the system can also be presented on additional monitors in the procedure room using the 1x4 HDMI Splitter supplied with the system. The user can also take snapshots of the videos, with and without the highlighting of the suspicious areas, record videos and view in full screen mode.
Intended Use / Indications for Use:
The ME-APDS (Magentiq Eye's Automatic Polyp Detection System) is intended to be used by endoscopists as an adjunct to the common video colonoscopy procedure (screening and surveillance). aiming to assist the endoscopist in identifying lesions during colonoscopy procedure by highlighting regions with visual characteristics consistent with different types of mucosal abnormalities that appear
4
in the colonoscopy video during the procedure. Highlighted regions can be independently assessed by the endoscopist and appropriate action taken according to standard clinical practice.
The ME-APDS is trained to process video images which may contain regions consistent with polyps.
The ME-APDS is limited for use with standard white-light endoscopy imaging only.
The ME-APDS is intended to be used as an adjunct to endoscopy procedures and is not intended to replace histopathological sampling as means of diagnosis.
Summary of Technological Characteristics:
Computer-Aided Polyp Detection (CADe) engine is the technological principle for both the subject and predicate devices. The maior roles of CADe engine during colonoscopy is to process a video frame and to indicate the presence and location of detected lesions (such as polyps) in real time during colonoscopy procedure in order to improve mucosal lesion rates, thus improving the performance of the endoscopist.
At a high level, the subject and predicate devices are based on the following same technological elements:
- Both systems have similar intended use, intended user and patient population. ●
- Both systems' computing devices retrieve the video stream from the Endoscope and ● run a deep machine learning algorithms from the type of Deep Neural Networks (DNN) technology in real time. It then feeds a video output with the detected lesions (such as polyps) in an overlay highlighting the suspicious areas on the original video.
- Both systems do not make any elaboration or alteration of the colonoscopy video ● streaming.
- o Both systems are suitable for use in white-light endoscopic mode of operations.
The following technological differences exist between the subject and predicate device:
- o The ME-APDS is comprises a cart, monitor, a computing device, transformer and 1x4 HDMI Splitter. The ME-APDS shall be positioned adjacent to the colonoscopy cart, connected to the electricity and to the video output of coloscopy device. The GI Genius is comprised from a computing module only that is positioned on the coloscopy cart and connected to the video output of coloscopy device and to the coloscopy device display monitor.
- The ME-APDS uses dual monitor display setup and is supplied together with a 1x4 HDMI Splitter to allow connecting the system's output to additional monitors in the procedure room. The predicate device uses a single monitor display setup and is connected directly to the coloscopy device display monitor.
- The ME-APDS user interface is a touchscreen monitor allowing touch control of the ● system. The GI Genius uses the existing colonoscopy system display monitor and control.
As validated in the clinical study, none of the identified technological differences introduce new aspects of safety or effectiveness. Both systems clinical efficacy and safety performances are very similar.
5
Performance Data:
Non-Clinical Testing:
The non-clinical performance studies of the subject device included:
- o Pixel-level comparison of degradation of image quality
- o Software validation
- . EMC testing in accordance with the requirements of IEC 60601-1-2:2014
- o Electrical safety testing in accordance with IEC 60601-1:2005.
In all instances, the ME-APDS functioned as intended and all tests' results observed were as expected.
Assessment of marker annotation delay
Marker annotation delay was assessed for all polyps all in the standalone performance testing. The marker annotation latency's median, calculated over all the polyps, is 0.166 sec (5 frames) and its average is 0.85 sec.
Standalone Performance Testing:
The algorithm was tested offline on 172 unique full colonoscopy videos, containing 449 polyps, 16 videos contained no polyps. Of the 449 polyps, 330 were small (s≤5mm), 76 have medium size (5mm 60 | 205 (51.5) | 38 (55.1) | 203 (52.7) | 32 (50.0) | 478 |
| Sex, n (%) | | | | | |
| Male | 219 (55.0) | 38 (55.1) | 202 (52.5) | 34 (53.1) | 493(53.8) |
| Female | 179 (45.0) | 31 (44.9) | 183 (47.5) | 30 (46.9) | 423 |
| BMI (kg/m²) | | | | | |
| Mean (SD) | 27.5 (5.1) | 25.9 (4.8) | 27.0 (4.8) | 27.2 (4.8) | 27.2 (4.9) |
| Median | 26.7 | 26.1 | 26.2 | 25.8 | 26.2 |
12
| Minimum, Maximum | 15.8, 57.4 | 15.5, 39.3 | 17.1, 52.6 | 19.4, 39.0 | 15.5, |
|---|---|---|---|---|---|
| Race, n (%)* | |||||
| Caucasian | 374 (94.2) | 67 (97.1) | 370 (96.1) | 63 (98.4) | 874 |
| African-American | 18 (4.5) | 2 (2.9) | 12 (3.1) | 1 (1.6) | 33 (3.6) |
| Asian | 1 (0.3) | - | 1 (0.3) | - | 2 (0.2) |
| Other | 4 (1.0) | - | 2 (0.5) | - | 6 (0.7) |
| Reason for Colonoscopy, n | |||||
| Screening | 222 (55.8) | 37 (53.6) | 219 (56.9) | 36 (56.3) | 514 |
| Surveillance | 176 (44.2) | 32 (46.4) | 166 (43.1) | 28 (43.8) | 402 |
*For one patient in the CC treatment group the race information was not reported
Primary endpoints:
- APC: total number of adenomas detected and removed per examination
- APE: the percentage of adenomas detected and removed divided by the total number of ● extractions (polypectomies or biopsies) during index colonoscopies
Success criteria:
More adenomas will be detected with MEAC compared to CC. This will result in higher APC with MEAC compared to CC. APE of MEAC is expected to be non-inferior to APE of CC.
- APC: Difference between the event rates of MEAC vs. CC were compared using a t test, with a . two-sided alpha of 5%. The two-sided lower limit of a 95% confidence interval (CI) of the MEAC/CC ratio of events was expected to be >1.05.
- APE: A two-sided Wilcoxon test with a non-inferiority margin of 20% was performed with a two-. sided alpha of 5%. The two-sided lower limit of the 95% Cl of the difference between the APE of each colonoscopy technique was expected be above -0.20. In addition, 95% Cls of the APE proportions of MEAC and CC were calculated using normal approximation.
APC & APE Results
The primary analysis assessed APC and APE: the percentage of adenomas detected and removed divided by the total number of extractions (polypectomies or biopsies) during index colonoscopies
| Treatment | ||
|---|---|---|
| CC | ||
| (N=467) | MEAC | |
| (N=449) | ||
| Total Adenomas | 238 | 314 |
| Total Colonoscopies | 467 | 449 |
| Adenomas Per Colonoscopy | ||
| (APC) | 0.51 (1.03) | 0.70 (1.30) |
| SE | 0.05 | 0.06 |
Adenoma per Colonoscopy (APC) and Adenoma per Extraction (APE) (ITT Population)
13
| 95% Cl | 0.42, 0.60 | 0.58, 0.82 |
|---|---|---|
| Total Adenomas | 238 | 314 |
| Total Extractions | 360 | 536 |
| Adenomas Per Extraction (APE) | ||
| Mean (SD) | 0.27 (0.43) | 0.31 (0.43) |
| SE | 0.02 | 0.20 |
| 95% Cl | 0.23, 0.31 | 0.27, 0.35 |
Subgroup Performance
Adenoma per Colonoscopy (APC) and Adenoma per Extraction (APE) by Study Region (ITT Population)
| Treatment | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| CC | ||||||||||
| (N=467) | MEAC | |||||||||
| (N=449) | ||||||||||
| Total | ||||||||||
| Adenomas | Total | |||||||||
| Colonoscopies | APC | Total | ||||||||
| Extractions | APE | Total | ||||||||
| Adenomas | Total | |||||||||
| Colonoscopies | APC | Total | ||||||||
| Extractions | APE | |||||||||
| USA | 102 | 84 | 1.21 | 142 | 0.72 | 105 | 77 | 1.36 | 171 | 0.61 |
| OUS | 136 | 383 | 0.36 | 218 | 0.62 | 209 | 372 | 0.56 | 365 | 0.57 |
Adenoma per Colonoscopy (APC) and Adenoma per Extraction (APE) by Subgroup (ITT Population)
| Treatment | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| CC | ||||||||||
| (N=467) | MEAC | |||||||||
| (N=449) | ||||||||||
| Subgroup | Total | |||||||||
| Adenomas | Total | |||||||||
| Colonoscopies | APC | Total | ||||||||
| Extractions | APE | Total | ||||||||
| Adenomas | Total | |||||||||
| Colonoscopies | APC | Total | ||||||||
| Extractions | APE | |||||||||
| Reason for colonoscopy | ||||||||||
| Screening | 106 | 259 | 0.41 | 171 | 0.62 | 149 | 255 | 0.58 | 239 | 0.62 |
| Surveillance | 132 | 208 | 0.63 | 189 | 0.70 | 165 | 194 | 0.85 | 297 | 0.56 |
| Sex | ||||||||||
| Female | 91 | 210 | 0.43 | 138 | 0.66 | 136 | 213 | 0.64 | 246 | 0.55 |
| Male | 147 | 257 | 0.57 | 222 | 0.66 | 178 | 236 | 0.75 | 290 | 0.61 |
| Age Group | ||||||||||
| 60 yrs | 158 | 243 | 0.65 | 223 | 0.71 | 186 | 235 | 0.79 | 327 | 0.57 |
The table below provides the two sided 95% Cl's for APC and APE by subgroup. Calculations were made on patient level results assuming normal distribution.
Confidence Intervals for APC and APE by Subgroup
14
| K223473 | |||||
|---|---|---|---|---|---|
| Page 12 of 13 |
| Endpoint | Subgroup | Treatment | Mean | Lower
95% | Upper
95% |
|----------|--------------|-----------|-------|--------------|--------------|
| APC | US | CC | 1.214 | 0.872 | 1.556 |
| | | MEAC | 1.364 | 0.976 | 1.751 |
| | OUS | CC | 0.355 | 0.277 | 0.434 |
| | | MEAC | 0.562 | 0.444 | 0.679 |
| | Screening | CC | 0.409 | 0.305 | 0.514 |
| | | MEAC | 0.584 | 0.455 | 0.714 |
| | Surveillance | CC | 0.635 | 0.471 | 0.798 |
| | | MEAC | 0.851 | 0.630 | 1.071 |
| | Female | CC | 0.433 | 0.304 | 0.563 |
| | | MEAC | 0.638 | 0.453 | 0.824 |
| | Male | CC | 0.572 | 0.439 | 0.705 |
| | | MEAC | 0.754 | 0.596 | 0.912 |
| | 60 | CC | 0.650 | 0.501 | 0.799 |
| | | MEAC | 0.791 | 0.608 | 0.975 |
| APE | US | CC | 0.484 | 0.384 | 0.584 |
| | | MEAC | 0.443 | 0.351 | 0.536 |
| | OUS | CC | 0.222 | 0.181 | 0.262 |
| | | MEAC | 0.278 | 0.234 | 0.321 |
| | Screening | CC | 0.247 | 0.196 | 0.299 |
| | | MEAC | 0.300 | 0.247 | 0.354 |
| | Surveillance | CC | 0.295 | 0.236 | 0.355 |
| | | MEAC | 0.314 | 0.255 | 0.373 |
| | Female | CC | 0.240 | 0.183 | 0.297 |
| | | MEAC | 0.269 | 0.214 | 0.325 |
| | Male | CC | 0.292 | 0.239 | 0.346 |
| | | MEAC | 0.340 | 0.283 | 0.396 |
| | 60 | CC | 0.337 | 0.279 | 0.395 |
| | | MEAC | 0.324 | 0.269 | 0.379 |
The study results showed that the MEAC adenoma per colonoscopy (APC) was 37% higher (relative increase) than CC APC and was consistently higher across all patient subgroups. Inter-arm comparisons found consistently higher APC rates for MEAC as compared to CC procedures, regardless of colonoscopy indication, patient sex, or patient age, with a mean 0.20 increment between arms for each analyzed subgroup. In particular. MEAC proved more effective than CC in detecting ≤5mm polyps and in detecting >6-9 mm polyps, sessile and flat polyps and adenomas in the proximal colon. In addition, more sessile serrated adenomas (SSAs) were identified in MEACs as compared to CCs, which resulted in also a higher sessile serrated detection rate (SDR). Despite the increased detection rate, the MEAC adenomas per extraction (APE) proved non-inferior to that of CC, and did not involve clinically relevant longer withdrawal times or delayed bleeding. In line with these findings, AMR was significantly lower and ADR was significantly higher in the MEAC vs. CC arm. As expected, given the above findings, time to next scheduled colonoscopy was 4 months earlier in the MEAC as compared to the CC cohort.
15
These observations suggest a critical contribution of MEAC in minimizing the effects of confounding clinical and operator-related factors on colonoscopy outcomes. No intervention-related adverse events were reported during this study in either arm.
Based on the clinical performance as documented in the pivotal clinical study, the ME-APDS performs as intended under anticipated conditions of use and has a safety and effectiveness profile that is similar to the predicate device.
Conclusions:
The ME-APDS is as safe and effective as Cosmo Artificial Intelligence - Al. LTD's GI Genius. The ME-APDS 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. In addition, the minor technological differences between the ME-APDS and its predicate devices raise no new issues of safety or effectiveness. Performance data demonstrate that the ME-APDS is as safe and effective as the GI Genius. Thus, the ME-APDS is substantially equivalent.