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The subject ALT-Y0003 is used to detect leaks from Olympus flexible endoscopes. It utilizes two testing modes; one is automated leak test mode (ALT mode) and the other is manual leak test mode (MLT mode). In ALT mode, it is not required to soak the tested endoscope in water. The ALT-Y0003 detects leak from the difference of air pressure. The ALT-Y0003 can also be used for conventional manual leak test by soaking an endoscope in water. The ALT-Y0003 has an RFID function to recognize endoscope and operator identification. It can store test results in its internal memory and this stored record can be printed out with the designated printer and/or transferred to deginated USB memory.

AI/ML Overview

1. Table of Acceptance Criteria and Reported Device Performance

Criterion	Acceptance Criteria	Reported Device Performance
Leak Detecting Rate (ALT vs. MLT)	The leak detecting rate of the Automated Leak Test (ALT) mode should be equivalent to that of the conventional Manual Leak Test (MLT) mode.	"It has been demonstrated that there is no significant difference in leak detection rates between ALT and conventional MLT." (The document states equivalency was confirmed in nonclinical testing).
Detection Threshold	The ALT-Y0003 should be able to detect a leak that actually causes a water leak.	"it has been confirmed that the detection threshold of the ALT-Y0003 can detect a leak which actually causes a water leak."
Software Validation	Compliance with FDA Guidance: "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." (Device software considered "Minor Level of Concern").	"The software validation activities were performed in accordance with the FDA Guidance, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.'"
Electrical Safety	Compliance with IEC 61010-1.	"Basic safety and performance testing was performed in accordance with IEC 61010-1..."
EMC Standard	Compliance with IEC 61326-1.	"...and IEC 61326-1."
FCC Part 15 Standard (Intentional Radiator)	Compliance with Federal Communications Commission (FCC) 47 CFR Part 15 - Radio Frequency Devices, Subject C - Intentional Radiators.	"As the ALT-Y0003 is considered to be an intentional radiator prescribed under Federal Communications Commission (FCC) 47 CFR Part 15 – Radio Frequency Devices, Subject C – Intentional Radiators, it has been evaluated to verify compliance with this regulation."
Mechanical and Functional Performance	Verification of mechanical and functional performance (specific criteria not detailed, but likely involve proper operation of all device features).	"In addition, verification was conducted to evaluate the mechanical and functional performance."
Risk Analysis	Risk analysis carried out in accordance with established in-house acceptance criteria based on ISO 14971:2007. Design verification tests and their acceptance criteria identified and performed as a result of this risk analysis assessment.	"Risk analysis was carried out in accordance with established in-house acceptance criteria based on ISO 14971:2007. The design verifications tests and their acceptance criteria were identified and performed as a result of this risk analysis assessment." (This implies the internal acceptance criteria were met, though specifics are not provided for each risk identified).

2. Sample Size Used for the Test Set and Data Provenance

The document does not explicitly state the specific sample size used for the test set of endoscopes in the performance testing. It refers to "nonclinical testing" without detailing the number of endoscopes or the specific characteristics of the leaks tested.

The data provenance is not explicitly stated in terms of country of origin, but the manufacturer is Japanese (Olympus Medical Systems Corp. and Shirakawa Olympus Co., Ltd.). The mention of "nonclinical testing" implies these were controlled laboratory tests rather than retrospective or prospective clinical data from patients.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided in the document. The study described is a performance validation of a leak detection device, not a diagnostic imaging device where expert interpretation of images would typically establish ground truth.

4. Adjudication Method for the Test Set

This information is not applicable and therefore not provided. The study compares the device's diagnostic capability (leak detection) to a conventional method, not to expert consensus on interpretation.

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. This device is an automated endoscope leak tester, not an AI-assisted diagnostic tool for human readers. The study compares the device's automated leak detection mode to a manual leak testing mode, not to human readers interpreting data.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, a standalone performance assessment of the automated leak test (ALT) mode was done. The study specifically compared the ALT mode (which operates without human intervention beyond setting up the test) to the conventional manual leak test (MLT) mode. The core of the performance testing revolved around demonstrating the standalone capability of the ALT mode to detect leaks effectively.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The ground truth for "leak detection" in this context would likely be the actual presence or absence of a leak in the tested endoscopes, confirmed by a reference method. The document mentions "it has been confirmed that the detection threshold of the ALT-Y0003 can detect a leak which actually causes a water leak," suggesting a direct physical assessment of leakage (e.g., observing water expulsion/bubbles when pressurized or actual damage causing water ingress) served as the ultimate ground truth for the detection threshold. For the comparison of detection rates, the "ground truth" would be which endoscopes actually had a leak, as determined by a highly sensitive method (possibly the conventional manual leak test itself, if it was deemed the gold standard, or a more rigorous laboratory-controlled method).

8. The Sample Size for the Training Set

This information is not provided. The document describes a performance validation study for a medical device that uses software, but it doesn't specify if the leak detection algorithm itself underwent a machine learning training phase. The context is more about validating a programmed automated test than a learned AI model.

9. How the Ground Truth for the Training Set Was Established

Since no training set is explicitly mentioned or defined in the context of machine learning, the question of how its ground truth was established is not applicable based on the provided document. If there was an internal development process involving data, that information is not detailed in this 510(k) summary.

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