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Fuse Colonoscopy System: The Fuse Colonoscope with FuseBox Processor is intended for diagnostic visualization of the digestive tract. The system also provides access for therapeutic interventions using standard endoscopy tools. The system consists of EndoChoice camera heads, endoscopes, video system, light source and other ancillary equipment. Fuse Colonoscopes, in conjunction with the FuseBox® processor, are indicated for use within the lower digestive tract (including the anus, rectum, sigmoid colon, colon and ileocecal valve) for adult patients. The system includes Lumos, a digital post processing inage enhancement technology. Lumos is intended to be used as an optional adjunct following white light endoscopy and is not intended to replace histopathological sampling as a means of diagnosis.

Fuse 1G Gastroscopy System: The Fuse 1G Gastroscope with FuseBox Processor is intended for diagnostic visualization of the digestive tract. The system also provides access for therventions using standard endoscopy tools. The system consists of EndoChoice camera heads, endoscopes, video system, light source and other ancillary equipment. The Fuse 1G Gastroscope, in conjunction with the FuseBox processor, is indicated for use within the upper digestive tract (including the esophagus, stomach and duodenum). The system includes Lumos, a digital post processing image enhancement technology. Lumos is intended to be used as an optional adjunct following white light endoscopy and is not intended to replace histopathological sampling as a means of diagnosis.

The Fuse Endoscopy System is a GI platform indicated for diagnostic visualization and therapeutic intervention of the digestive tract. The system labeled for healthcare facilities/hospitals enables physicians to view a high-resolution wide field of view. The FuseBox is responsible for image processing, transferring video signals from the endoscope, pneumatic control, and outputting high definition (HD 1080p) video signal. The current FuseBox version, unlike the version used with the two predicate devices, includes image post processing algorithm as an adjunct tool to white light visualization.

The feature provides real-time enhancement and will be used as an adjunctive tool. to supplement the white light endoscopic examination. The new feature may enhance appearance of surface vessels, visualization of the mucosal surface texture and visibility of borders of areas of interest when present.

The provided text describes the Fuse® Endoscopy System with FuseBox® Processor, which includes a digital post-processing image enhancement technology called Lumos. The information primarily focuses on establishing substantial equivalence to predicate devices for regulatory approval, rather than detailed acceptance criteria and a specific study proving it meets those criteria.

However, I can extract the available information and structure it as requested, making note of where specific details are not provided in the document.

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

The document does not explicitly state numerical acceptance criteria for the Lumos feature. Instead, it refers to overall device safety and effectiveness. The performance characteristics mentioned are comparisons to predicate devices for the white light aspects of the system. For Lumos, it states its function as an "enhancement feature."

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

The document mentions "Clinical Survey on videos with the Lumos compared to white light" was performed. However, it does not provide any details regarding:

• The sample size of videos or cases used in this clinical survey.
• The provenance of the data (e.g., country of origin).
• Whether the data 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)

The document does not specify the number of experts or their qualifications used to establish ground truth for the "Clinical Survey on videos." It only states that a clinical survey was conducted.

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

The document does not provide any information about the adjudication method used for the "Clinical Survey on videos."

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

The document mentions a "Clinical Survey on videos with the Lumos compared to white light." While this implies a comparison, it does not explicitly state that it was a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. Furthermore, it does not provide any effect size or quantitative measure of how much human readers improve with AI (Lumos) vs. without AI assistance. It only broadly states that the feature "may enhance appearance of surface vessels, visualization of the mucosal surface texture and visibility of borders of areas of interest."

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

The document describes Lumos as an "optional adjunct" and an "adjunctive tool to supplement the white light endoscopic examination." This strongly suggests that it is not intended for standalone performance but rather for human-in-the-loop use. No standalone algorithm performance study is described.

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

The document does not explicitly state the type of ground truth used for the "Clinical Survey on videos." Given the context of "diagnostic visualization" and "adjunct following white light endoscopy," it's plausible that expert interpretation/consensus of standard white light imagery or potentially pathological findings serve as an implicit ground truth, but this is not mentioned. It specifically states that Lumos "is not intended to replace histopathological sampling as a means of diagnosis."

8. The sample size for the training set

The document does not provide any information regarding the sample size for a training set. The descriptions focus on the device's function and comparison to predicate devices, not on the development or training of the Lumos algorithm.

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

Since no training set details (including sample size) are provided, the document does not describe how ground truth for a training set was established.

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The Fuse Gastroscopy System is intended for diagnostic visualization of the digestive tract. The system also provides access for therapeutic interventions using standard endoscopy tools. The Fuse Gastroscopy System is indicated for use within the upper digestive tract (including the esophagus, stomach, and duodenum). The Fuse Gastroscopy System consists of camera heads, endoscopes, video system, light source and other ancillary equipment.

The Fuse Gastroscopy System is a GI platform indicated for diagnostic visualization and therapeutic intervention of the upper digestive tract. The purpose of this submission is to propose new biopsy channel supplier and also to present several design changes that enhance device usability and robustness. The indications for use, fundamental technology and operation principals of the legally marketed device were not changed. The system labeled for healthcare facilities/hospitals enables physicians to view a high-resolution wide field of view of up to 245° (measured diagonally), or 210° (measured horizontally)

The provided text describes a 510(k) premarket notification for the "Fuse® Gastroscopy System" by EndoChoice Inc. This document focuses on demonstrating substantial equivalence to a predicate device (Fuse PeerScope HG, K131422) after making modifications to the existing device. It does not contain information about a study proving the device meets specific acceptance criteria in the context of diagnostic performance or a comparative effectiveness study with human readers.

The performance testing described here is focused on engineering verification and validation of design changes, ensuring safety and effectiveness after modifications, rather than establishing diagnostic performance acceptance criteria for a new AI or image analysis algorithm.

Therefore, many of the requested sections about acceptance criteria, diagnostic performance, sample sizes for test/training sets, expert ground truth establishment, MRMC studies, and standalone algorithm performance cannot be extracted from this document.

Here's a breakdown of what can be extracted or inferred based on the provided text, and what cannot:

1. Table of acceptance criteria and the reported device performance:
This information is not explicitly provided in terms of diagnostic performance metrics like sensitivity, specificity, or AUC against specific acceptance criteria. The performance testing section states: "All test results passed, demonstrating that the device is safe and effective in comparison with the predicate device." This refers to internal engineering/safety testing, not diagnostic accuracy.

2. Sample sized used for the test set and the data provenance:
Not applicable. The document discusses performance testing for mechanical, electrical, and reprocessing aspects, not a clinical diagnostic test set.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable. Ground truth for diagnostic performance is not mentioned as this is not a diagnostic performance study.

4. Adjudication method for the test set:
Not applicable.

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. The device is a gastroscopy system (an endoscope), not an AI or image analysis system intended to assist human readers in diagnosis.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Not applicable. This is not an AI or algorithm-based device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
Not applicable, as it's not a diagnostic performance study.

8. The sample size for the training set:
Not applicable, as it's not an AI or algorithm-based device requiring training data.

9. How the ground truth for the training set was established:
Not applicable.

Summary of available information:

The document describes the modifications made to an existing medical device (Fuse® Gastroscopy System) and the engineering-focused performance testing conducted to ensure these modifications did not negatively impact the device's safety and effectiveness.

• Acceptance Criteria & Performance (General): The general acceptance criterion was that "All test results passed," demonstrating the device is "safe and effective in comparison with the predicate device." This relates to bench tests (functional, performance, software), laboratory safety/EMC compatibility, biocompatibility, and reprocessing testing. Specific numerical acceptance criteria for these tests are not provided in this summary.
• Study Type: This was a series of engineering verification and validation tests rather than a clinical diagnostic study. It aimed to demonstrate that design modifications (e.g., new biopsy channel supplier, angulation knob brake, umbilical cord plug, locking lever, 90-degree umbilical cord orientation, updated reprocessing methods) maintained the device's safety and effectiveness compared to the predicate.
• Sample Size/Data Provenance for these engineering tests: Not explicitly stated, though implicitly the tests would have involved a number of manufactured devices or components. Data provenance is "within EndoChoice's laboratory or by accredited third parties."
• Ground Truth for these engineering tests: Established by predefined engineering specifications, regulatory standards (listed in the document), and comparison to the performance of the predicate device. For example, reprocessing testing would have had objective criteria for efficacy.

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