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The Expect™ Pulmonary Endobronchial Ultrasound Transbronchial Aspiration Needle is designed to be used with endobronchial ultrasound endoscopes for ultrasound guided fine needle aspiration (FNA) of the submucosal and extramural lesions of the gastrointestinal tract. Do not use this instrument for any purpose other than its intended use.

The Expect™ Pulmonary device is comprised of the following: Expect™ Pulmonary needle, Expect™ Pulmonary adaptor, Syringe, Stopcock. The Expect™ Pulmonary needle is an Endobronchial Ultrasound guided Transbronchial Aspiration Needle used for fine needle aspiration (FNA) of submucosal and extramural lesions of the gastrointestinal tract. The device consists of a sheath covered needle which extends into the accessory channel of an endobronchial ultrasound (EBUS) endoscope and is locked into place. A handle on the proximal end of the device is used to actuate the needle in order gather samples. Both the sheath and needle length are adjustable while in the scope. A stylet is in place in order to provide protection to the inside of the sheath during device passage through the scope. The stylet may also be used to expel the sample after the procedure. Expect™ Pulmonary adaptor is an accessory to be attached and locked onto the biopsy port of the bronchoscope. It allows Expect™ Pulmonary needle to pass through it and to be secured in place with a luer connection. Syringe and stopcock are accessories to provide and control the vacuum suction to aspirate the sample. They also can be used to expel the samples after the procedure.

The provided text is a 510(k) summary for the Boston Scientific Expect™ Pulmonary Endobronchial Ultrasound Transbronchial Aspiration Needle. It focuses on demonstrating substantial equivalence to predicate devices rather than proving a device meets specific acceptance criteria based on clinical outcomes or a standalone algorithm performance.

Therefore, many of the requested categories for describing acceptance criteria and a study to prove device performance (e.g., sample size for test set, number of experts, adjudication method, MRMC study, standalone performance, ground truth types for test and training sets) are not applicable or not present in this type of submission.

This document describes a pre-market notification for a medical device that functions as a tool for obtaining tissue samples. The "acceptance criteria" here are related to the device's physical and functional properties, primarily demonstrating that it performs as intended and is as safe and effective as a legally marketed predicate device.

Here's the information extracted and formatted, with "N/A" for criteria not applicable or not found in the text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implied by the successful completion of the performance tests, demonstrating that the device functions as intended and is comparable to predicate devices. The reported device performance is that all tests were successfully completed. No specific numerical performance metrics (e.g., "flexibility must be < X N") are provided, only that the tests were completed with acceptable results.

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

This document describes non-clinical comparative performance bench testing. It does not involve a "test set" in the context of patient data or algorithm evaluation. The testing was conducted on manufactured devices.

• Sample Size: Not specified. Standard practice for bench testing would involve a statistically relevant number of devices, but the exact number is not provided in this summary.
• Data Provenance: N/A (bench testing, not patient data).
• Retrospective or Prospective: N/A (bench testing).

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

N/A. This is a medical device's physical and functional performance test, not a diagnostic algorithm. Ground truth, in this context, refers to engineering specifications and performance standards met by the device itself, not interpretation by experts.

4. Adjudication Method for the Test Set

N/A. Adjudication methods are typically used in clinical studies or expert reviews of data, not for bench testing of device mechanics.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

N/A. This is a physical medical device (needle), not an AI algorithm. Therefore, no MRMC study comparing human readers with or without AI assistance was performed.

6. Standalone Performance (Algorithm Only without Human-in-the-Loop Performance)

N/A. This is a physical medical device (needle), not an AI algorithm.

7. Type of Ground Truth Used

The "ground truth" for the performance testing is based on engineering specifications and established performance standards for medical devices of this type, as demonstrated by the predicate devices. For biocompatibility, it's based on ISO 10993-1:2009.

8. Sample Size for the Training Set

N/A. This is a physical medical device. There is no "training set" in the context of machine learning. The device design and manufacturing processes are developed based on engineering principles and previous device designs.

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

N/A. No training set as per machine learning definition. Design ground truth is established through engineering design principles, material science, and regulatory requirements, often benchmarked against existing devices (predicates).

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