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The invendo C25 Colonoscopy System is intended to provide visualization and diagnostic / therapeutic access to the adult lower gastrointestinal tract (including but not limited to, the anus, rectum, sigmoid colon, colon, cecum and ileocecal valve) for endoscopy and endoscopic surgery.

The colonoscope component of the invendo C25 Colonoscopy System, the SC20 colonoscope, is a single-use disposable device. The SC20 colonoscope cannot be reprocessed.

The invendo C25 Colonoscopy System is a modified version of the invendo C20 Colonoscopy System.

Like the predicate device, the invendo C25 Colonoscopy System is steered and controlled by the operator. The distal tip of the colonoscope is deflectable and includes a CMOS camera and LEDs for illumination. A working channel is incorporated to enable biopsies and polypectomies. The invendo C25 Colonoscopy System includes insufflation, irrigation and suction functions.

The invendo C25 Colonoscopy System consists of two components: (1) the invendo C25 base system; and (2) a single-use, disposable colonoscope, the SC20 colonoscope.

The invendo C25 base system provides the SC20 colonoscope with the above mentioned functions and transfers user commands to the colonoscope. To control the colonoscope, the operator uses a handheld control unit. All colonoscope functions are solely activated by the user. The invendo C25 base system consists of the Supply and Processing Unit (SPU or base unit), the handheld control and the drive unit.

The provided document is a 510(k) premarket notification for the invendo C25 Colonoscopy System. This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving a device meets specific acceptance criteria through a clinical study for novel performance claims.

Therefore, many of the requested details about acceptance criteria, clinical study methodology, and training/test set specifics are not applicable or available within this document, as it describes a technical modification and equivalence demonstration, not a de novo clinical performance study against pre-defined metrics.

However, I can extract the information that is present:

1. A table of acceptance criteria and the reported device performance

Since this filing is for substantial equivalence to a predicate device (invendo C20 Colonoscopy System), the "acceptance criteria" are primarily related to meeting established safety standards and demonstrating that the new device performs at least as well as the predicate with its modifications.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: This document does not specify sample sizes for any human clinical test sets, as the testing described is primarily non-clinical (engineering and biocompatibility). The "Evaluation of the performance compared to the predicate device" would have been a non-clinical, comparative engineering/functional test, not a clinical trial.
• Data Provenance: Not applicable, as the document details non-clinical laboratory testing.

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)

• Not applicable. This document describes non-clinical testing against engineering standards and a predicate device, not a study requiring expert-established ground truth on medical data.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not applicable for the type of testing described in this 510(k).

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

• No, an MRMC comparative effectiveness study was not done as this is a device modification submission, not an AI-enabled diagnostic device.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done

• Not applicable, as this is a medical device (colonoscope system), not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• The "ground truth" for the non-clinical tests were the specified engineering standards (e.g., IEC, ISO) and the functional and safety performance of the predicate device.

8. The sample size for the training set

• Not applicable, as this is not an AI/algorithm device that requires a training set. The "design validation" mentioned refers to engineering design and testing, not machine learning model training.

9. How the ground truth for the training set was established

• Not applicable, as there is no training set for an AI/algorithm.

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