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LTF-Y0009 (3D Laparo-Thoraco Videoscope): This instrument has been designed for use in conjunction with light source, video system centers, 3D Video Mixer, 3D monitor, documentation equipment, hand instruments, and other ancillary equipment for endoscopy and endoscopic surgery within the peritoneal and thoracic cavity.

MAJ-Y0041 (3D Video Mixer): This instrument has been designed to be used with Olympus 3D Laparo-Thoraco videoscope and Video System Center for 3D video observation.

XOEV-3D1(Polarized 3D Monitor): This instrument has been designed to be used with Olympus 3D Laparo-Thoraco videoscope, light source, video system center and 3D Video Mixer for endoscopic diagnosis and video observation.

MAJ-Y0108 (3D glasses): This instrument has been designed to be used with Olympus 3D Laparo-Thoraco videoscope, light source, video system center, 3D Video Mixer and 3D monitor for 3D video observation.

3D Laparo-Thoraco Videoscope (LTF-Y0009) is a video endoscope used for endoscopy and endoscopic surgery within the peritoneal and thoracic cavity. LTF-Y0009 is basically identical to predicate device 3D Laparoscope, for the same application areas. The 3D video observation of this system is implemented with following process. The captured signals from two CCDs which correspond to left and right eye incorporated in distal end of the subject LTF-Y0009 are transferred to the MAJ-Y0041 via CV-Y0001. CV-Y0001 converts the captured signals into video image signals, and transmits them to the MAJ-Y0041. The MAJ-Y0041 converts the image signals into 3D video signal and transfers it to the XOEV-3D1. On the XOEV-3D1, 3D video image is displayed as passive stereo type which has different polarizing angle in the left and right; therefore, the MAJ-Y0108 is required to obtain 3D video image. The MAJ-Y0108's glasses have polarizing films on them which correspond to their each polarizing angle and it enables 3D observation to the users.

The provided 510(k) summary for the Olympus 3D Laparo-Thoraco Videoscope, Polarized 3D Monitor, and 3D Video Mixer focuses on demonstrating substantial equivalence to a predicate device. This type of submission generally does not include detailed performance studies with acceptance criteria, sample sizes, and ground truth establishment in the way that, for example, a new diagnostic AI device would.

The summary states:
"The LTF-Y0009, XOEV-3D1. MAJ-Y0041 is basically identical to the predicate device in intended use, and similar in specifications except for the optical system of the subject LTF-Y0009." (Section 6)
And in the conclusion:
"When compared to the predicate device, the LTF-Y0009, XQEV-3D1, MAJ-Y0041 do not incorporate any significant changes in intended use, method of operation, material, or design that could affect the safety or effectiveness of the device." (Section 7)

Because the device is considered "substantially equivalent" to a legally marketed predicate device, the regulatory pathway relies on demonstrating that the new device does not raise new questions of safety or effectiveness. This is different from proving that a device meets specific performance metrics against a defined acceptance criterion through a dedicated study. Therefore, the information requested in your prompt (acceptance criteria, specific study details like sample sizes, ground truth, expert qualifications, adjudication methods, MRMC studies, and standalone performance) is not typically part of a 510(k) summary for a device like this.

The key 'proof' that the device meets "acceptance criteria" (in the context of a 510(k)) is the demonstration of substantial equivalence to the predicate device. This is typically achieved through comparisons of technological characteristics, intended use, and safety profiles.

Therefore, many of the specific details you requested are not present in this 510(k) summary. I can, however, extract the information that is available:

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

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

This information is not provided in the 510(k) summary. For a 510(k) based on substantial equivalence, specific clinical performance testing with a "test set" in the context of an AI/diagnostic device is not usually required or described in this format. The comparison is primarily against the specifications and performance of the predicate device.

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)

This information is not provided in the 510(k) summary. This type of detail would be relevant for a device making a new diagnostic claim or employing a novel algorithm requiring clinical validation against a ground truth. This is not such a device.

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

This information is not provided in the 510(k) summary.

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

This information is not provided in the 510(k) summary. This is not an AI-assisted diagnostic device, but rather an imaging system.

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

This information is not applicable/provided in the 510(k) summary. This device is a video endoscope system, not an algorithm.

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

This information is not provided in the 510(k) summary.

8. The sample size for the training set

This information is not provided in the 510(k) summary. The device is not an AI/machine learning model that undergoes a training process in the conventional sense.

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

This information is not applicable/provided in the 510(k) summary, as it does not relate to an AI/machine learning model.

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