(263 days)
The SKOUT system is a software device designed to detect potential colorectal polyps in real time during colonoscopy examinations. It is indicated as a computer-aided detection tool providing colorectal polyps location information to assist qualified and trained gastroenterologists in identifying potential colorectal polyps during colonoscopy examinations in adult patients undergoing colorectal cancer screening or surveillance.
The SKOUT system is only intended to assist the gastroenterologist in identifying suspected colorectal polyps and the gastroenterologist is responsible for reviewing SKOUT suspected polyp areas and confirming the presence of a polyp based on their own medical judgment. SKOUT is not intended to replace a full patient evaluation, nor is it intended to be relied upon to make a primary interpretation of endoscopic procedures, medical diagnosis, or recommendations of treatment/course of action for patients. SKOUT is indicated for white light colonoscopy only.
The SKOUT™ system is a software-based computer aided detection (CADe) system for the analysis of high-definition endoscopic video during colonoscopy procedures. The SKOUT™ system is intended to aid gastroenterologists with the detection of potential colorectal polyps during colonoscopy by providing an informational visual aid on the endoscopic monitor using trained software that processes the endoscopic video in real time.
Users will primarily interact with the SKOUT™ system by observing the software display, including the polyp detection box and device status indicator signal.
Acceptance Criteria and Device Performance for SKOUT™ System
1. Table of Acceptance Criteria and Reported Device Performance
The provided document doesn't explicitly state "acceptance criteria" in a separate section. However, it presents the results of "Non-clinical performance testing" and "Clinical Testing" with specific metrics and confidence intervals, which serve as the performance benchmarks the device has met.
Based on the information provided, here's a table summarizing the implicit acceptance criteria (as demonstrated by the positive study outcomes) and the reported device performance:
| Acceptance Criterion (Implicit) | Reported Device Performance | Study Type |
|---|---|---|
| Non-Clinical Performance: | ||
| Object Level True Positive Rate (TPR): High proportion of actual polyps detected by the device. | 97.87% (95% CI: 94.96%, 100.0%) | Standalone Algorithm Performance Testing |
| Object Level False Positives (FP): Low number of non-polyps flagged as polyps per procedure. | 22.55 objects per 15-minute interval (95% CI: 18.954, 26.148) | Standalone Algorithm Performance Testing |
| Frame Level True Positive Rate (TPR): High proportion of frames with confirmed polyps where the device bounds the polyp. | Mean: 55.66% (95% CI: 55.50%, 55.83%) | Standalone Algorithm Performance Testing |
| Frame Level False Positive Rate (FPR): Low proportion of frames where the device bounds an object not detected by the gastroenterologist. | Mean: 2.31% (95% CI: 2.16%–2.44%) | Standalone Algorithm Performance Testing |
| Marker Overlap (IOGT): High proportion of ground truth polyp area engulfed by the SKOUT bounding box to ensure appropriate visibility for the physician. (Implied acceptance of IOGT = 1.0 as a positive indicator given the purpose of bounding box enlargement). | Median IOGT of signal: 1.0 (meaning on a median basis, all polyps were engulfed by a SKOUT bounding box). Mean IOU: 0.299 (95% CI: 0.289, 0.309) which is expected to be low due to artificial bounding box enlargement. | Standalone Algorithm Performance Testing |
| Image Quality Degradation: No visually detectable degradation due to the device. | No visually detectable differences between images found with the introduction of the SKOUT™ system. | Special Control Testing |
| Video Delay due to Marker Annotation: Minimal delay introduced by the device. | SDI: 56.00ms (95% CI: 50.54, 61.46) and 3.25 frame delay (95% CI: 2.93, 3.56). DVI: 62.33ms (95% CI: 60.76, 63.90) and 3.74 frame delay (95% CI: 3.65, 3.83). | Special Control Testing |
| Real-time Endoscopic Video Delay: Minimal delay in real-time video feed. | SDI: 56.67ms (95% CI: 51.01, 62.33) and 3.28 frame delay (95% CI: 2.96, 3.62). DVI: 60.67ms (95% CI: 57.72, 63.61) and 3.64 frame delay (95% CI: 3.46, 3.81). | Special Control Testing |
| Clinical Performance: | ||
| Adenomas Per Colonoscopy (APC): Significant improvement in the number of adenomas detected per colonoscopy with AI assistance. | Treatment (AI-aided arm): 1.054 Control (Standard colonoscopy): 0.830 Difference (Treatment - Control): 0.224 (95% CI: 0.060, 0.382), p-value: 0.002 (Statistically significant increase) | Multi-center, prospective, randomized controlled trial (Clinical Study) |
| Positive Percent Agreement (PPA) / Positive Predictive Value (PPV): Non-inferiority or comparable safety profile to standard colonoscopy. (PPA/PPV used as a safety endpoint representing the fraction of resected lesions that were indeed polyps). | PPA (mITT cohort): Control: 75.7% Treatment: 70.9% Difference: -4.8% (95% CI: -9.5% to 0.3%) and p-value: ** |
§ 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.